references.bib

@book{abelson1995,
  title = {Statistics as Principled Argument.},
  author = {Abelson, Robert P},
  year = {1995},
  series = {Statistics as Principled Argument.},
  publisher = {{Lawrence Erlbaum Associates, Inc}},
  address = {{Hillsdale, NJ, US}},
  abstract = {Abelson delves into the . . . problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. [This book is] filled with . . . real-life (and real-research) examples rather than . . . recipes for analysis. [It is intended for] beginning graduate students and researchers alike. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
  rating = {0},
  uri = {papers3://publication/uuid/3744008D-0698-4668-BEC3-5281D85126D5}
}

@article{abraham2014,
  title = {Machine {{Learning}} for {{Neuroimaging}} with {{Scikit-Learn}}},
  author = {Abraham, Alexandre and Pedregosa, Fabian and Eickenberg, Michael and Gervais, Philippe and Muller, Andreas and Kossaifi, Jean and Gramfort, Alexandre and Thirion, Bertrand and Varoquaux, G{\"a}el},
  year = {2014},
  journal = {arXiv},
  abstract = {Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g. resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.},
  keywords = {fMRI,Machine Learning,Methods},
  annotation = {\_eprint: 1412.3919},
  file = {/Users/morteza/Documents/Zotero/storage/MCFMR4UK/Abraham et al. - 2014 - Machine learning for neuroimaging with scikit-lear.pdf}
}

@article{adachi2013,
  title = {More {{Than Just Fun}} and {{Games}}: {{The Longitudinal Relationships Between Strategic Video Games}}, {{Self-Reported Problem Solving Skills}}, and {{Academic Grades}}},
  shorttitle = {More {{Than Just Fun}} and {{Games}}},
  author = {Adachi, Paul J. C. and Willoughby, Teena},
  year = {2013},
  month = jul,
  journal = {Journal of Youth and Adolescence},
  volume = {42},
  number = {7},
  pages = {1041--1052},
  issn = {0047-2891, 1573-6601},
  doi = {10.1007/s10964-013-9913-9},
  langid = {english},
  annotation = {200 citations (Semantic Scholar/DOI) [2022-12-11] 00171}
}

@article{adams2016,
  title = {Evaluating the {{Cognitive Consequences}} of {{Playing}} {{{\emph{Portal}}}} for a {{Short Duration}}},
  author = {Adams, Deanne M. and Pilegard, Celeste and Mayer, Richard E.},
  year = {2016},
  month = apr,
  journal = {Journal of Educational Computing Research},
  volume = {54},
  number = {2},
  pages = {173--195},
  issn = {0735-6331, 1541-4140},
  doi = {10.1177/0735633115620431},
  langid = {english},
  annotation = {17 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{ahissar1993,
  title = {Attentional Control of Early Perceptual Learning},
  author = {Ahissar, M and Hochstein, S},
  year = {1993},
  journal = {Proceedings of the National Academy of Sciences},
  volume = {90},
  number = {12},
  issn = {0027-8424},
  abstract = {The performance of adult humans in simple visual tasks improves dramatically with practice. This improvement is highly specific to basic attributes of the trained stimulus, suggesting that the underlying changes occur at low-level processing stages in the brain, where different orientations and spatial frequencies are handled by separate channels. We asked whether these practice effects are determined solely by activity in stimulus-driven mechanisms or whether high-level attentional mechanisms, which are linked to the perceptual task, might control the learning process. We found that practicing one task did not improve performance in an alternative task, even though both tasks used exactly the same visual stimuli but depended on different stimulus attributes (either orientation of local elements or global shape). Moreover, even when the experiment was designed so that the same responses were associated with the same stimuli (although subjects were instructed to attend to the attribute underlying one task), learning did not transfer from one task to the other. These results suggest that specific high-level attentional mechanisms, controlling changes at early visual processing levels, are essential in perceptual learning.},
  pmcid = {PMC46793},
  pmid = {8516322}
}

@article{al-hashimi2015,
  title = {Neural Sources of Performance Decline during Continuous Multitasking},
  author = {{Al-Hashimi}, Omar and Zanto, Theodore P. and Gazzaley, Adam},
  year = {2015},
  month = oct,
  journal = {Cortex},
  volume = {71},
  pages = {49--57},
  issn = {00109452},
  doi = {10.1016/j.cortex.2015.06.001},
  langid = {english},
  annotation = {15 citations (Semantic Scholar/DOI) [2022-12-11] 00018}
}

@article{anderson2004,
  title = {An {{Integrated Theory}} of the {{Mind}}.},
  author = {Anderson, John R. and Bothell, Daniel and Byrne, Michael D. and Douglass, Scott and Lebiere, Christian and Qin, Yulin},
  year = {2004},
  journal = {Psychological Review},
  volume = {111},
  number = {4},
  pages = {1036--1060},
  issn = {1939-1471, 0033-295X},
  doi = {10.1037/0033-295X.111.4.1036},
  langid = {english},
  annotation = {2871 citations (Semantic Scholar/DOI) [2022-12-14]}
}

@article{angelov2020,
  title = {{{Top2Vec}}: {{Distributed Representations}} of {{Topics}}},
  shorttitle = {{{Top2Vec}}},
  author = {Angelov, Dimo},
  year = {2020},
  publisher = {{arXiv}},
  doi = {10.48550/ARXIV.2008.09470},
  abstract = {Topic modeling is used for discovering latent semantic structure, usually referred to as topics, in a large collection of documents. The most widely used methods are Latent Dirichlet Allocation and Probabilistic Latent Semantic Analysis. Despite their popularity they have several weaknesses. In order to achieve optimal results they often require the number of topics to be known, custom stop-word lists, stemming, and lemmatization. Additionally these methods rely on bag-of-words representation of documents which ignore the ordering and semantics of words. Distributed representations of documents and words have gained popularity due to their ability to capture semantics of words and documents. We present \$\textbackslash texttt\{top2vec\}\$, which leverages joint document and word semantic embedding to find \$\textbackslash textit\{topic vectors\}\$. This model does not require stop-word lists, stemming or lemmatization, and it automatically finds the number of topics. The resulting topic vectors are jointly embedded with the document and word vectors with distance between them representing semantic similarity. Our experiments demonstrate that \$\textbackslash texttt\{top2vec\}\$ finds topics which are significantly more informative and representative of the corpus trained on than probabilistic generative models.},
  copyright = {arXiv.org perpetual, non-exclusive license},
  keywords = {Computation and Language (cs.CL),FOS: Computer and information sciences,Machine Learning (cs.LG),Machine Learning (stat.ML)},
  annotation = {82 citations (Semantic Scholar/arXiv) [2022-12-09]}
}

@article{anguera2013,
  title = {Video Game Training Enhances Cognitive Control in Older Adults},
  author = {Anguera, J. A. and Boccanfuso, J. and Rintoul, J. L. and {Al-Hashimi}, O. and Faraji, F. and Janowich, J. and Kong, E. and Larraburo, Y. and Rolle, C. and Johnston, E. and Gazzaley, A.},
  year = {2013},
  month = sep,
  journal = {Nature},
  volume = {501},
  number = {7465},
  pages = {97--101},
  issn = {0028-0836, 1476-4687},
  doi = {10.1038/nature12486},
  langid = {english},
  annotation = {1244 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/9M5YE4RX/Anguera et al. - 2013 - Video game training enhances cognitive control in .pdf}
}

@article{ansarinia2022,
  title = {Linking Theories and Methods in Cognitive Sciences via Joint Embedding of the Scientific Literature: {{The}} Example of Cognitive Control},
  author = {Ansarinia, Morteza and Schrater, Paul and {Cardoso-Leite}, Pedro},
  year = {2022},
  journal = {arXiv preprint arXiv:2203.11016},
  eprint = {2203.11016},
  eprinttype = {arxiv},
  archiveprefix = {arXiv}
}

@misc{ansarinia2022a,
  title = {Weighted {{Metapath2Vec Graph Embedding}} ({{Version}} v0.1.4)},
  shorttitle = {Morteza/Weighted-Metapath2vec},
  author = {Ansarinia, Morteza},
  year = {2022},
  month = jun,
  doi = {10.5281/ZENODO.7096229},
  abstract = {Initial release.},
  copyright = {Open Access},
  howpublished = {Zenodo}
}

@misc{ansarinia2022b,
  title = {Nilearn {{Extra}}: {{Drop-in}} Extra Features for {{Nilearn}} ({{Version}} v0.1.1)},
  shorttitle = {Morteza/Nilearn-Extra},
  author = {Ansarinia, Morteza},
  year = {2022},
  month = sep,
  doi = {10.5281/ZENODO.7096267},
  abstract = {Initial Zenedo release},
  copyright = {Open Access},
  howpublished = {Zenodo}
}

@misc{ansarinia2022c,
  title = {{{UpSet2D}}: {{Hypergraphs Visualization Package}} ({{Version}} v0.1.4)},
  shorttitle = {Morteza/{{UpSet2D}}},
  author = {Ansarinia, Morteza},
  year = {2022},
  month = sep,
  doi = {10.5281/ZENODO.7096256},
  abstract = {Initial release for Zenedo DOI},
  copyright = {MIT License, Open Access},
  howpublished = {Zenodo},
  langid = {english}
}

@inproceedings{ansarinia2022d,
  title = {{{CogEnv}}: {{A Reinforcement Learning Environment}} for {{Cognitive Tests}}},
  shorttitle = {{{CogEnv}}},
  booktitle = {2022 {{Conference}} on {{Cognitive Computational Neuroscience}}},
  author = {Ansarinia, Morteza and Clocher, Brice and Defossez, Aur{\'e}lien and Schm{\"u}ck, Emmanuel and {Cardoso-Leite}, Pedro},
  year = {2022},
  publisher = {{Cognitive Computational Neuroscience}},
  address = {{San Francisco}},
  doi = {10.32470/CCN.2022.1198-0},
  annotation = {0 citations (Semantic Scholar/DOI) [2023-01-02]}
}

@article{anticevic2012,
  title = {The Role of Default Network Deactivation in Cognition and Disease},
  author = {Anticevic, Alan and Cole, Michael W. and Murray, John D. and Corlett, Philip R. and Wang, Xiao-Jing and Krystal, John H.},
  year = {2012},
  month = dec,
  journal = {Trends in Cognitive Sciences},
  volume = {16},
  number = {12},
  pages = {584--592},
  issn = {13646613},
  doi = {10.1016/j.tics.2012.10.008},
  langid = {english},
  annotation = {734 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/9G8WGCRU/Anticevic et al. - 2012 - The role of default network deactivation in cognit.pdf}
}

@article{antzaka2017,
  title = {Enhancing Reading Performance through Action Video Games: The Role of Visual Attention Span},
  shorttitle = {Enhancing Reading Performance through Action Video Games},
  author = {Antzaka, A. and Lallier, M. and Meyer, S. and Diard, J. and Carreiras, M. and Valdois, S.},
  year = {2017},
  month = nov,
  journal = {Scientific Reports},
  volume = {7},
  number = {1},
  pages = {14563},
  issn = {2045-2322},
  doi = {10.1038/s41598-017-15119-9},
  abstract = {Recent studies reported that Action Video Game-AVG training improves not only certain attentional components, but also reading fluency in children with dyslexia. We aimed to investigate the shared attentional components of AVG playing and reading, by studying whether the Visual Attention (VA) span, a component of visual attention that has previously been linked to both reading development and dyslexia, is improved in frequent players of AVGs. Thirty-six French fluent adult readers, matched on chronological age and text reading proficiency, composed two groups: frequent AVG players and non-players. Participants performed behavioural tasks measuring the VA span, and a challenging reading task (reading of briefly presented pseudo-words). AVG players performed better on both tasks and performance on these tasks was correlated. These results further support the transfer of the attentional benefits of playing AVGs to reading, and indicate that the VA span could be a core component mediating this transfer. The correlation between VA span and pseudo-word reading also supports the involvement of VA span even in adult reading. Future studies could combine VA span training with defining features of AVGs, in order to build a new generation of remediation software.},
  copyright = {2017 The Author(s)},
  langid = {english},
  annotation = {32 citations (Semantic Scholar/DOI) [2022-12-11] 00010},
  file = {/Users/morteza/Documents/Zotero/storage/VVACV4AB/Antzaka et al. - 2017 - Enhancing reading performance through action video.pdf;/Users/morteza/Documents/Zotero/storage/CEDJD4LM/s41598-017-15119-9.html}
}

@article{astle2015,
  title = {Cognitive {{Training Enhances Intrinsic Brain Connectivity}} in {{Childhood}}},
  author = {Astle, D E and Barnes, J J and Baker, K and Colclough, G L and Woolrich, M W},
  year = {2015},
  month = apr,
  journal = {Journal of Neuroscience},
  volume = {35},
  number = {16},
  pages = {6277--6283},
  annotation = {00000}
}

@article{au2015,
  title = {Improving Fluid Intelligence with Training on Working Memory: {{A}} Meta-Analysis},
  shorttitle = {Improving Fluid Intelligence with Training on Working Memory},
  author = {Au, Jacky and Sheehan, Ellen and Tsai, Nancy and Duncan, Greg J. and Buschkuehl, Martin and Jaeggi, Susanne M.},
  year = {2015},
  journal = {Psychonomic Bulletin \& Review},
  volume = {22},
  number = {2},
  pages = {366--377},
  issn = {1069-9384, 1531-5320},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/4U3VG3Q9/au2015.pdf;/Users/morteza/Documents/Zotero/storage/FZ8AUWP5/au2015.pdf}
}

@article{badre2008,
  title = {Cognitive Control, Hierarchy, and the Rostro\textendash Caudal Organization of the Frontal Lobes},
  author = {Badre, David},
  year = {2008},
  journal = {Trends in Cognitive Sciences},
  volume = {12},
  number = {5},
  pages = {193--200},
  issn = {1364-6613},
  doi = {10.1016/j.tics.2008.02.004},
  abstract = {Cognitive control supports flexible behavior by selecting actions that are consistent with our goals and appropriate for our environment. The prefrontal cortex (PFC) has an established role in cognitive control, and research on the functional organization of PFC promises to contribute to our understanding of the architecture of control. A recently popular hypothesis is that the rostro\textendash caudal axis of PFC supports a control hierarchy whereby posterior-to-anterior PFC mediates progressively abstract, higher-order control. This review discusses evidence for a rostro\textendash caudal gradient of function in PFC and the theories proposed to account for these results, including domain generality in working memory, relational complexity, the temporal organization of behavior and abstract representational hierarchy. Distinctions among these frameworks are considered as a basis for future research.},
  pmid = {18403252},
  annotation = {00953}
}

@article{badre2011,
  title = {Defining an Ontology of Cognitive Control Requires Attention to Component Interactions},
  author = {Badre, David},
  year = {2011},
  journal = {Topics in Cognitive Science},
  volume = {3},
  number = {2},
  issn = {1756-8765},
  abstract = {Cognitive control is not only componential, but those components may interact in complicated ways in the service of cognitive control tasks. This complexity poses a challenge for developing an ontological description, because the mapping may not be direct between our task descriptions and true component differences reflected in indicators. To illustrate this point, I discuss two examples: (a) the relationship between adaptive gating and working memory and (b) the recent evidence for a control hierarchy. From these examples, I argue that an ontological program must simultaneously seek to identify component processes and their interactions within a broader processing architecture.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/Badre{$_2$}011.pdf},
  pmid = {21666845}
}

@book{badre2020,
  title = {On {{Task}}: {{How Our Brain Gets Things Done}}},
  author = {Badre, David},
  year = {2020},
  isbn = {978-0-691-21234-0}
}

@article{baggetta2016,
  title = {Conceptualization and {{Operationalization}} of {{Executive Function}}: {{Executive Function}}},
  shorttitle = {Conceptualization and {{Operationalization}} of {{Executive Function}}},
  author = {Baggetta, Peter and Alexander, Patricia A.},
  year = {2016},
  month = mar,
  journal = {Mind, Brain, and Education},
  volume = {10},
  number = {1},
  pages = {10--33},
  issn = {17512271},
  doi = {10.1111/mbe.12100},
  langid = {english},
  keywords = {Executive Functions},
  annotation = {156 citations (Semantic Scholar/DOI) [2022-12-11]}
}

@article{baker2022,
  title = {Degenerate Boundaries for Multiple-Alternative Decisions},
  author = {Baker, Sophie-Anne and Griffith, Thom and Lepora, Nathan F.},
  year = {2022},
  month = aug,
  journal = {Nature Communications},
  volume = {13},
  number = {1},
  pages = {5066},
  publisher = {{Nature Publishing Group}},
  issn = {2041-1723},
  doi = {10.1038/s41467-022-32741-y},
  abstract = {Integration-to-threshold models of two-choice perceptual decision making have guided our understanding of human and animal behavior and neural processing. Although such models seem to extend naturally to multiple-choice decision making, consensus on a normative framework has yet to emerge, and hence the implications of threshold characteristics for multiple choices have only been partially explored. Here we consider sequential Bayesian inference and a conceptualisation of decision making as a particle diffusing in n-dimensions. We show by simulation that, within a parameterised subset of time-independent boundaries, the optimal decision boundaries comprise a degenerate family of nonlinear structures that jointly depend on the state of multiple accumulators and speed-accuracy trade-offs. This degeneracy is contrary to current 2-choice results where there is a single optimal threshold. Such boundaries support both stationary and collapsing thresholds as optimal strategies for decision-making, both of which result from stationary representations of nonlinear boundaries. Our findings point towards a normative theory of multiple-choice decision making, provide a characterisation of optimal decision thresholds under this framework, and inform the debate between stationary and dynamic decision boundaries for optimal decision making.},
  copyright = {2022 The Author(s)},
  langid = {english},
  keywords = {Computational neuroscience,Decision},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/YAKZ6Z3F/Baker et al_2022_Degenerate boundaries for multiple-alternative decisions.pdf}
}

@article{ball1993,
  title = {Visual Attention Problems as a Predictor of Vehicle Crashes in Older Drivers},
  author = {Ball, K. and Owsley, C. and Sloane, M. E. and Roenker, D. L. and Bruni, J. R.},
  year = {1993},
  month = oct,
  journal = {Investigative Ophthalmology \& Visual Science},
  volume = {34},
  number = {11},
  pages = {3110--3123},
  issn = {0146-0404},
  abstract = {PURPOSE: To identify visual factors that are significantly associated with increased vehicle crashes in older drivers. METHODS: Several aspects of vision and visual information processing were assessed in 294 drivers aged 55 to 90 years. The sample was stratified with respect to age and crash frequency during the 5-year period before the test date. Variables assessed included eye health status, visual sensory function, the size of the useful field of view, and cognitive status. Crash data were obtained from state records. RESULTS: The size of the useful field of view, a test of visual attention, had high sensitivity (89\%) and specificity (81\%) in predicting which older drivers had a history of crash problems. This level of predictability is unprecedented in research on crash risk in older drivers. Older adults with substantial shrinkage in the useful field of view were six times more likely to have incurred one or more crashes in the previous 5-year period. Eye health status, visual sensory function, cognitive status, and chronological age were significantly correlated with crashes, but were relatively poor at discriminating between crash-involved versus crash-free drivers. CONCLUSIONS: This study suggests that policies that restrict driving privileges based solely on age or on common stereotypes of age-related declines in vision and cognition are scientifically unfounded. With the identification of a visual attention measure highly predictive of crash problems in the elderly, this study points to a way in which the suitability of licensure in the older adult population could be based on objective, performance-based criteria.},
  langid = {english},
  pmid = {8407219},
  keywords = {Accidents; Traffic,Aged,Aged; 80 and over,Aging,Attention,Automobile Driving,Cognition Disorders,Contrast Sensitivity,Health Status,Humans,Middle Aged,Models; Statistical,Predictive Value of Tests,Vision Disorders,Visual Acuity,Visual Fields,Visual Perception}
}

@article{banino2021,
  title = {{{PonderNet}}: {{Learning}} to {{Ponder}}},
  shorttitle = {{{PonderNet}}},
  author = {Banino, Andrea and Balaguer, Jan and Blundell, Charles},
  year = {2021},
  publisher = {{arXiv}},
  doi = {10.48550/ARXIV.2107.05407},
  abstract = {In standard neural networks the amount of computation used grows with the size of the inputs, but not with the complexity of the problem being learnt. To overcome this limitation we introduce PonderNet, a new algorithm that learns to adapt the amount of computation based on the complexity of the problem at hand. PonderNet learns end-to-end the number of computational steps to achieve an effective compromise between training prediction accuracy, computational cost and generalization. On a complex synthetic problem, PonderNet dramatically improves performance over previous adaptive computation methods and additionally succeeds at extrapolation tests where traditional neural networks fail. Also, our method matched the current state of the art results on a real world question and answering dataset, but using less compute. Finally, PonderNet reached state of the art results on a complex task designed to test the reasoning capabilities of neural networks.1},
  copyright = {arXiv.org perpetual, non-exclusive license},
  keywords = {Artificial Intelligence (cs.AI),Computational Complexity (cs.CC),FOS: Computer and information sciences,Machine Learning (cs.LG)},
  annotation = {30 citations (Semantic Scholar/arXiv) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/L32ZT6AI/Banino et al. - 2021 - PonderNet Learning to Ponder.pdf}
}

@article{baniqued2013,
  title = {Selling Points: {{What}} Cognitive Abilities Are Tapped by Casual Video Games?},
  shorttitle = {Selling Points},
  author = {Baniqued, Pauline L. and Lee, Hyunkyu and Voss, Michelle W. and Basak, Chandramallika and Cosman, Joshua D. and DeSouza, Shanna and Severson, Joan and Salthouse, Timothy A. and Kramer, Arthur F.},
  year = {2013},
  month = jan,
  journal = {Acta Psychologica},
  volume = {142},
  number = {1},
  pages = {74--86},
  issn = {00016918},
  doi = {10.1016/j.actpsy.2012.11.009},
  langid = {english},
  annotation = {126 citations (Semantic Scholar/DOI) [2022-12-11] 00092},
  file = {/Users/morteza/Documents/Zotero/storage/2UDW22NT/Selling points- What cognitive abilities are tapped by casual video games (Baniqued, Voss, Krammer et al 2013).pdf}
}

@article{baniqued2014,
  title = {Cognitive Training with Casual Video Games: Points to Consider},
  shorttitle = {Cognitive Training with Casual Video Games},
  author = {Baniqued, Pauline L. and Kranz, Michael B. and Voss, Michelle W. and Lee, Hyunkyu and Cosman, Joshua D. and Severson, Joan and Kramer, Arthur F.},
  year = {2014},
  journal = {Frontiers in Psychology},
  volume = {4},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2013.01010},
  annotation = {38 citations (Semantic Scholar/DOI) [2022-12-11] 00075},
  file = {/Users/morteza/Documents/Zotero/storage/3XS23EHD/fpsyg-04-01010.pdf}
}

@article{barch2009,
  title = {{{CNTRICS}} Final Task Selection: {{Working}} Memory},
  author = {Barch, D M and Berman, M G and Engle, R and Jones, J H and Jonides, J and MacDonald, A and Nee, D E and Redick, T S and Sponheim, S R},
  year = {2009},
  journal = {Schizophrenia Bulletin},
  volume = {35},
  number = {1},
  pages = {136--152},
  issn = {0586-7614},
  doi = {10.1093/schbul/sbn153},
  abstract = {The third meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) was focused on selecting promising measures for each of the cognitive constructs selected in the first CNTRICS meeting. In the domain of working memory, the 2 constructs of interest were goal maintenance and interference control. CNTRICS received 3 task nominations for each of these constructs, and the breakout group for working memory evaluated the degree to which each of these tasks met prespecified criteria. For goal maintenance, the breakout group for working memory recommended the AX-Continuous Performance Task/Dot Pattern Expectancy task for translation for use in clinical trial contexts in schizophrenia research. For interference control, the breakout group recommended the recent probes and operation/symmetry span tasks for translation for use in clinical trials. This article describes the ways in which each of these tasks met the criteria used by the breakout group to recommend tasks for further development.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2009/Barch\%202009.pdf},
  pmcid = {PMC2643954},
  pmid = {18990711},
  keywords = {Task Selection,Working Memory},
  annotation = {00108}
}

@article{barch2009a,
  title = {{{CNTRICS}} Final Task Selection: {{Executive}} Control},
  author = {Barch, Deanna M. and Braver, Todd S. and Carter, Cameron S. and Poldrack, Russell A. and Robbins, Trevor W.},
  year = {2009},
  journal = {Schizophrenia Bulletin},
  volume = {35},
  number = {1},
  issn = {0586-7614},
  abstract = {The third meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) was focused on selecting promising measures for each of the cognitive constructs selected in the first CNTRICS meeting. In the domain of executive control, the 2 constructs of interest were ``rule generation and selection'' and ``dynamic adjustments in control.'' CNTRICS received 4 task nominations for each of these constructs, and the breakout group for executive control evaluated the degree to which each of these tasks met prespecified criteria. For rule generation and selection, the breakout group for executive control recommended the intradimensional/extradimensional shift task and the switching Stroop for translation for use in clinical trial contexts in schizophrenia research. For dynamic adjustments in control, the breakout group recommended conflict and error adaptation in the Stroop and the stop signal task for translation for use in clinical trials. This article describes the ways in which each of these tasks met the criteria used by the breakout group to recommend tasks for further development.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/Barch{$_2$}009.pdf},
  pmid = {19011235}
}

@article{basak2008,
  title = {Can Training in a Real-Time Strategy Video Game Attenuate Cognitive Decline in Older Adults?},
  author = {Basak, Chandramallika and Boot, Walter R. and Voss, Michelle W. and Kramer, Arthur F.},
  year = {2008},
  month = dec,
  journal = {Psychology and Aging},
  volume = {23},
  number = {4},
  pages = {765--777},
  issn = {0882-7974},
  doi = {10.1037/a0013494},
  abstract = {Declines in various cognitive abilities, particularly executive control functions, are observed in older adults. An important goal of cognitive training is to slow or reverse these age-related declines. However, opinion is divided in the literature regarding whether cognitive training can engender transfer to a variety of cognitive skills in older adults. In the current study, the authors trained older adults in a real-time strategy video game for 23.5 hr in an effort to improve their executive functions. A battery of cognitive tasks, including tasks of executive control and visuospatial skills, were assessed before, during, and after video-game training. The trainees improved significantly in the measures of game performance. They also improved significantly more than the control participants in executive control functions, such as task switching, working memory, visual short-term memory, and reasoning. Individual differences in changes in game performance were correlated with improvements in task switching. The study has implications for the enhancement of executive control processes of older adults.},
  langid = {english},
  pmcid = {PMC4041116},
  pmid = {19140648},
  keywords = {Aged,Aged; 80 and over,Cognition Disorders,Computer Systems,Female,Humans,Male,Memory; Short-Term,Mental Recall,Neuropsychological Tests,Orientation,Practice (Psychology),Problem Solving,Psychomotor Performance,Transfer (Psychology),Video Games},
  annotation = {770 citations (Semantic Scholar/DOI) [2022-12-11] 00793},
  file = {/Users/morteza/Documents/Zotero/storage/26A3GEKQ/Basak et al. - 2008 - Can training in a real-time strategy video game at.pdf}
}

@article{basak2011,
  title = {Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame},
  author = {Basak, Chandramallika and Voss, Michelle W. and Erickson, Kirk I. and Boot, Walter R. and Kramer, Arthur F.},
  year = {2011},
  month = aug,
  journal = {Brain and Cognition},
  volume = {76},
  number = {3},
  pages = {407--414},
  issn = {02782626},
  doi = {10.1016/j.bandc.2011.03.017},
  langid = {english},
  annotation = {78 citations (Semantic Scholar/DOI) [2022-12-11] 00071},
  file = {/Users/morteza/Documents/Zotero/storage/2K4N8WUF/Basak et al. - 2011 - Regional differences in brain volume predict the a.pdf}
}

@misc{bastian2020,
  title = {Advancing the Understanding of Individual Differences in Attentional Control: {{Theoretical}}, Methodological, and Analytical Considerations},
  author = {von Bastian, Claudia Christina and Blais, Chris and Brewer, Gene Arnold and Gyurkovics, Mate and Hedge, Craig and Ka{\l}ama{\l}a, Patrycja and Meier, Matt Ethan and Oberauer, Klaus and {Rey-Mermet}, Alodie and Rouder, Jeffrey N and Souza, Alessandra S and Bartsch, Lea Maria and Conway, Andrew R A and Draheim, Chris and Engle, Randall W and Friedman, Naomi P and Frischkorn, Gidon T and Gustavson, Daniel E and Koch, Iring and Redick, Thomas and Smeekens, Bridget Anne and Whitehead, Peter S and Wiemers, Elizabeth A},
  year = {2020},
  number = {10.31234/osf.io/x3b9k},
  publisher = {{PsyArXiv}},
  doi = {10.31234/osf.io/x3b9k},
  annotation = {20 citations (Semantic Scholar/DOI) [2022-12-09]}
}

@article{batou2013,
  title = {Calculation of {{Lagrange Multipliers}} in the {{Construction}} of {{Maximum Entropy Distributions}} in {{High Stochastic Dimension}}},
  author = {Batou, A. and Soize, C.},
  year = {2013},
  month = jan,
  journal = {SIAM/ASA Journal on Uncertainty Quantification},
  volume = {1},
  number = {1},
  pages = {431--451},
  issn = {2166-2525},
  doi = {10.1137/120901386},
  langid = {english},
  annotation = {22 citations (Semantic Scholar/DOI) [2022-12-11] 00014},
  file = {/Users/morteza/Documents/Zotero/storage/7KKIUTQ9/batou2013.pdf}
}

@article{battiston2021,
  title = {The Physics of Higher-Order Interactions in Complex Systems},
  author = {Battiston, Federico and Amico, Enrico and Barrat, Alain and Bianconi, Ginestra and {Ferraz de Arruda}, Guilherme and Franceschiello, Benedetta and Iacopini, Iacopo and K{\'e}fi, Sonia and Latora, Vito and Moreno, Yamir and Murray, Micah M. and Peixoto, Tiago P. and Vaccarino, Francesco and Petri, Giovanni},
  year = {2021},
  month = oct,
  journal = {Nature Physics},
  volume = {17},
  number = {10},
  pages = {1093--1098},
  issn = {1745-2473, 1745-2481},
  doi = {10.1038/s41567-021-01371-4},
  langid = {english},
  keywords = {Chapter 5 (fMRI),Graph Theory}
}

@article{bavelier2010,
  title = {Children, {{Wired}}: {{For Better}} and for {{Worse}}},
  shorttitle = {Children, {{Wired}}},
  author = {Bavelier, Daphne and Green, C. Shawn and Dye, Matthew W.G.},
  year = {2010},
  month = sep,
  journal = {Neuron},
  volume = {67},
  number = {5},
  pages = {692--701},
  issn = {08966273},
  doi = {10.1016/j.neuron.2010.08.035},
  langid = {english},
  annotation = {162 citations (Semantic Scholar/DOI) [2022-12-11] 00182},
  file = {/Users/morteza/Documents/Zotero/storage/RYRHW9TV/BavelierGreenDye_Neuron_10.pdf}
}

@article{bavelier2012,
  title = {Neural Bases of Selective Attention in Action Video Game Players},
  author = {Bavelier, D and Achtman, R L and Mani, M and F{\"o}cker, J},
  year = {2012},
  month = may,
  journal = {Vision Research},
  volume = {61},
  number = {C},
  pages = {132--143},
  doi = {10.1016/j.visres.2011.08.007},
  abstract = {Vision Research, 61 (2012) 132-143. doi:10.1016/j.visres.2011.08.007},
  keywords = {Action video games,Brain plasticity,fMRI,Fronto-parietal network,Perceptual load,Visual attention},
  annotation = {231 citations (Semantic Scholar/DOI) [2022-12-11]},
  file = {/Users/morteza/Documents/Zotero/storage/D8SMY773/Bavelier et al. - 2012 - Neural bases of selective attention in action vide.pdf;/Users/morteza/Documents/Zotero/storage/D9FJK63F/bavelier2012.pdf;/Users/morteza/Documents/Zotero/storage/EKL7PU23/Bavelier et al. - 2012 - Neural bases of selective attention in action vide.pdf;/Users/morteza/Documents/Zotero/storage/LV7QRGHN/Bavelier et al_2012_Neural bases of selective attention in action video game players.pdf;/Users/morteza/Documents/Zotero/storage/XWGIZBUX/S0042698911002872.html}
}

@misc{bavelier2016,
  title = {Brain {{Tune-Up}} from {{Action Video Game Play}}},
  author = {Bavelier, Daphne and Green, Shawn},
  year = {2016},
  month = jul,
  journal = {Scientific American},
  doi = {10.1038/scientificamerican0716-26},
  abstract = {Shooting zombies and repelling aliens can lead to lasting improvement in mental skills},
  howpublished = {https://www.scientificamerican.com/article/brain-tune-up-from-action-video-game-play/},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/TS5LQZV6/brain-tune-up-from-action-video-game-play.html}
}

@article{bavelier2019a,
  title = {Rethinking Human Enhancement as Collective Welfarism},
  author = {Bavelier, Daphne and Savulescu, Julian and Fried, Linda P. and Friedmann, Theodore and Lathan, Corinna E. and Sch{\"u}rle, Simone and Beard, John R.},
  year = {2019},
  month = mar,
  journal = {Nature Human Behaviour},
  volume = {3},
  number = {3},
  pages = {204},
  issn = {2397-3374},
  doi = {10.1038/s41562-019-0545-2},
  abstract = {Human enhancement technologies are opening tremendous opportunities but also challenges to the core of what it means to be human. We argue that the goal of human enhancement should be to enhance quality of life and well-being not only of individuals but also of the communities they inhabit.},
  copyright = {2019 Springer Nature Limited},
  langid = {english},
  annotation = {6 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/QS6NSAZK/s41562-019-0545-2.html}
}

@article{bavelier2019,
  title = {Enhancing {{Attentional Control}}: {{Lessons}} from {{Action Video Games}}},
  shorttitle = {Enhancing {{Attentional Control}}},
  author = {Bavelier, Daphne and Green, C. Shawn},
  year = {2019},
  month = oct,
  journal = {Neuron},
  volume = {104},
  number = {1},
  pages = {147--163},
  issn = {08966273},
  doi = {10.1016/j.neuron.2019.09.031},
  langid = {english},
  annotation = {77 citations (Semantic Scholar/DOI) [2023-01-23]},
  file = {/Users/morteza/Documents/Zotero/storage/DJR6V8SI/Bavelier and Green - 2019 - Enhancing Attentional Control Lessons from Action.pdf}
}

@article{beam2021,
  title = {A Data-Driven Framework for Mapping Domains of Human Neurobiology},
  author = {Beam, Elizabeth and Potts, Christopher and Poldrack, Russell A. and Etkin, Amit},
  year = {2021},
  month = dec,
  journal = {Nature Neuroscience},
  volume = {24},
  number = {12},
  pages = {1733--1744},
  issn = {1097-6256, 1546-1726},
  doi = {10.1038/s41593-021-00948-9},
  langid = {english},
  annotation = {8 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/FQUBHB85/Beam et al. - 2021 - A data-driven framework for mapping domains of hum.pdf}
}

@article{bediou2018,
  title = {Meta-Analysis of Action Video Game Impact on Perceptual, Attentional, and Cognitive Skills.},
  author = {Bediou, Benoit and Adams, Deanne M. and Mayer, Richard E. and Tipton, Elizabeth and Green, C. Shawn and Bavelier, Daphne},
  year = {2018},
  month = jan,
  journal = {Psychological Bulletin},
  volume = {144},
  number = {1},
  pages = {77--110},
  issn = {1939-1455, 0033-2909},
  doi = {10.1037/bul0000130},
  langid = {english},
  keywords = {Attention,Cognition,Computer Games,Perception},
  file = {/Users/morteza/Documents/Zotero/storage/KWMZYJ7A/Bediou et al. - 2018 - Meta-analysis of action video game impact on perce.pdf}
}

@article{bediou2018correction,
  title = {"{{Meta-analysis}} of Action Video Game Impact on Perceptual, Attentional, and Cognitive Skills": {{Correction}} to {{Bediou}} et al. (2018)},
  shorttitle = {"{{Meta-analysis}} of Action Video Game Impact on Perceptual, Attentional, and Cognitive Skills"},
  year = {2018},
  month = sep,
  journal = {Psychological Bulletin},
  volume = {144},
  number = {9},
  pages = {978--979},
  issn = {1939-1455},
  doi = {10.1037/bul0000168},
  abstract = {Reports an error in "Meta-analysis of action video game impact on perceptual, attentional, and cognitive skills" by Benoit Bediou, Deanne M. Adams, Richard E. Mayer, Elizabeth Tipton, C. Shawn Green and Daphne Bavelier (Psychological Bulletin, 2018[Jan], Vol 144[1], 77-110). In the article, a number of issues related to clustering in cases of partial overlap between participants were identified following publication. This document clarifies these issues and extends the original results by adding additional sensitivity analyses. Please see the erratum for the full correction. (The following abstract of the original article appeared in record 2017-52625-001.) The ubiquity of video games in today's society has led to significant interest in their impact on the brain and behavior and in the possibility of harnessing games for good. The present meta-analyses focus on one specific game genre that has been of particular interest to the scientific community-action video games, and cover the period 2000-2015. To assess the long-lasting impact of action video game play on various domains of cognition, we first consider cross-sectional studies that inform us about the cognitive profile of habitual action video game players, and document a positive average effect of about half a standard deviation (g = 0.55). We then turn to long-term intervention studies that inform us about the possibility of causally inducing changes in cognition via playing action video games, and show a smaller average effect of a third of a standard deviation (g = 0.34). Because only intervention studies using other commercially available video game genres as controls were included, this latter result highlights the fact that not all games equally impact cognition. Moderator analyses indicated that action video game play robustly enhances the domains of top-down attention and spatial cognition, with encouraging signs for perception. Publication bias remains, however, a threat with average effects in the published literature estimated to be 30\% larger than in the full literature. As a result, we encourage the field to conduct larger cohort studies and more intervention studies, especially those with more than 30 hours of training. (PsycINFO Database Record},
  langid = {english},
  pmid = {30148383},
  annotation = {1 citations (Semantic Scholar/DOI) [2022-12-15]}
}

@article{bejjanki2014,
  title = {Action Video Game Play Facilitates the Development of Better Perceptual Templates},
  author = {Bejjanki, Vikranth R. and Zhang, Ruyuan and Li, Renjie and Pouget, Alexandre and Green, C. Shawn and Lu, Zhong-Lin and Bavelier, Daphne},
  year = {2014},
  month = nov,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {111},
  number = {47},
  pages = {16961--16966},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1417056111},
  langid = {english},
  annotation = {138 citations (Semantic Scholar/DOI) [2022-12-11] 00108},
  file = {/Users/morteza/Documents/Zotero/storage/F9PCP39J/Bejjanki et al. - 2014 - Action video game play facilitates the development.pdf}
}

@article{belchior2012,
  ids = {belchior2012a},
  title = {Older Adults' Engagement with a Video Game Training Program},
  author = {Belchior, Patr{\'i}cia and Marsiske, Michael and Sisco, Shannon and Yam, Anna and Mann, William},
  year = {2012},
  month = dec,
  journal = {Activities, adaptation \& aging},
  volume = {36},
  number = {4},
  pages = {269--279},
  issn = {0192-4788},
  doi = {10.1080/01924788.2012.702307},
  abstract = {Objectives The current study investigated older adults' level of engagement with a video game training program. Engagement was measured using the concept of Flow (). Methods Forty-five older adults were randomized to receive practice with an action game (Medal of Honor), a puzzle-like game (Tetris), or a gold-standard Useful Field of View (UFOV) training program. Results Both Medal of Honor and Tetris participants reported significantly higher Flow ratings at the conclusion, relative to the onset of training. Discussion Participants are more engaged in games that can be adjusted to their skill levels and that provide incremental levels of difficulty. This finding was consistent with the Flow theory ()},
  pmcid = {PMC3596832},
  pmid = {23504652},
  annotation = {42 citations (Semantic Scholar/DOI) [2022-12-11] 00026},
  file = {/Users/morteza/Documents/Zotero/storage/UWMC9D3P/belchior2012.pdf}
}

@article{belchior2013,
  title = {Video Game Training to Improve Selective Visual Attention in Older Adults},
  author = {Belchior, Patr{\'i}cia and Marsiske, Michael and Sisco, Shannon M. and Yam, Anna and Bavelier, Daphne and Ball, Karlene and Mann, William C.},
  year = {2013},
  month = jul,
  journal = {Computers in Human Behavior},
  volume = {29},
  number = {4},
  pages = {1318--1324},
  issn = {0747-5632},
  abstract = {The current study investigated the effect of video game training on older adult's useful field of view performance (the UFOV\textregistered{} test). Fifty-eight older adult participants were randomized to receive practice with the target action game (Medal of Honor), a placebo control arcade game (Tetris), a clinically validated UFOV training program, or into a no contact control group. Examining pretest-posttest change in selective visual attention, the UFOV improved significantly more than the game groups; all three intervention groups improved significantly more than no-contact controls. There was a lack of difference between the two game conditions, differing from findings with younger adults. Discussion considers whether games posing less challenge might still be effective interventions for elders, and whether optimal training dosages should be higher.},
  langid = {english},
  pmcid = {PMC3758751},
  pmid = {24003265},
  keywords = {Aging,Older adults,Training,Videogames,Visual attention},
  annotation = {00000}
}

@article{belchior2019,
  ids = {belchior2018},
  title = {Computer and {{Videogame Interventions}} for {{Older Adults}}' {{Cognitive}} and {{Everyday Functioning}}},
  author = {Belchior, Patr{\'i}cia and Yam, Anna and Thomas, Kelsey R. and Bavelier, Daphne and Ball, Karlene K. and Mann, William C. and Marsiske, Michael},
  year = {2019},
  month = apr,
  journal = {Games for Health Journal},
  volume = {8},
  number = {2},
  pages = {129--143},
  issn = {2161-783X, 2161-7856},
  doi = {10.1089/g4h.2017.0092},
  langid = {english},
  annotation = {24 citations (Semantic Scholar/DOI) [2022-12-11] 00001},
  file = {/Users/morteza/Documents/Zotero/storage/J9B2UEZD/g4h.2017.html}
}

@article{benady-chorney2020,
  ids = {benady-chorney2020a,benady-chorney2020b},
  title = {Action Video Game Experience Is Associated with Increased Resting State Functional Connectivity in the Caudate Nucleus and Decreased Functional Connectivity in the Hippocampus},
  author = {{Benady-Chorney}, Jessica and Aumont, {\'E}tienne and Yau, Yvonne and Zeighami, Yashar and Bohbot, Veronique D. and West, Greg L.},
  year = {2020},
  month = may,
  journal = {Computers in Human Behavior},
  volume = {106},
  pages = {106200},
  issn = {0747-5632},
  doi = {10.1016/j.chb.2019.106200},
  abstract = {Habitual action video game experience is associated with both increased grey matter and activity in the striatum and decreased grey matter in the hippocampus. To further investigate this relationship, we tested differences in resting state functional connectivity (rsFC) between action video games players (actionVGPs) compared to non-video game players (NVGPs) using the hippocampus, the caudate nucleus and the nucleus accumbens as regions of interest. Seventeen actionVGPs and 16 NVGPs were scanned using fMRI to measure rsFC. Results show that when compared to NVGPs, actionVGPs have increased rsFC between the nucleus accumbens and the subgenual anterior cingulate cortex and between the caudate nucleus and the precentral gyrus. ActionVGPs also displayed decreased rsFC between the hippocampus and the superior temporal gyrus and between the nucleus accumbens and the ventral tegmental area. Together, these results follow previous research examining changes in grey matter and suggest that frequent action video game playing is associated with higher functional activity in the reward circuit and lower functional activity within the hippocampus.},
  langid = {english},
  keywords = {Action video games,Caudate nucleus,Hippocampus,Resting state functional connectivity},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-12-06]},
  file = {/Users/morteza/Documents/Zotero/storage/R42PNTRY/Benady-Chorney et al. - 2020 - Action video game experience is associated with in.pdf;/Users/morteza/Documents/Zotero/storage/ZN4L39WY/Benady-Chorney et al_2020_Action video game experience is associated with increased resting state.pdf;/Users/morteza/Documents/Zotero/storage/RGMZYFER/S0747563219304200.html}
}

@misc{benning2019,
  title = {Deep Learning as Optimal Control Problems: Models and Numerical Methods},
  shorttitle = {Deep Learning as Optimal Control Problems},
  author = {Benning, Martin and Celledoni, Elena and Ehrhardt, Matthias J. and Owren, Brynjulf and Sch{\"o}nlieb, Carola-Bibiane},
  year = {2019},
  month = sep,
  number = {arXiv:1904.05657},
  eprint = {1904.05657},
  eprinttype = {arxiv},
  primaryclass = {cs, math},
  publisher = {{arXiv}},
  doi = {10.48550/arXiv.1904.05657},
  abstract = {We consider recent work of Haber and Ruthotto 2017 and Chang et al. 2018, where deep learning neural networks have been interpreted as discretisations of an optimal control problem subject to an ordinary differential equation constraint. We review the first order conditions for optimality, and the conditions ensuring optimality after discretisation. This leads to a class of algorithms for solving the discrete optimal control problem which guarantee that the corresponding discrete necessary conditions for optimality are fulfilled. The differential equation setting lends itself to learning additional parameters such as the time discretisation. We explore this extension alongside natural constraints (e.g. time steps lie in a simplex). We compare these deep learning algorithms numerically in terms of induced flow and generalisation ability.},
  archiveprefix = {arXiv},
  keywords = {Computer Science - Machine Learning,Mathematics - Numerical Analysis,Mathematics - Optimization and Control},
  annotation = {56 citations (Semantic Scholar/arXiv) [2022-12-03]}
}

@article{bensoussan2020,
  title = {Machine {{Learning}} and {{Control Theory}}},
  author = {Bensoussan, Alain and Li, Yiqun and Nguyen, Dinh Phan Cao and Tran, Minh-Binh and Yam, Sheung Chi Phillip and Zhou, Xiang},
  year = {2020},
  publisher = {{arXiv}},
  doi = {10.48550/ARXIV.2006.05604},
  abstract = {We survey in this article the connections between Machine Learning and Control Theory. Control Theory provide useful concepts and tools for Machine Learning. Conversely Machine Learning can be used to solve large control problems. In the first part of the paper, we develop the connections between reinforcement learning and Markov Decision Processes, which are discrete time control problems. In the second part, we review the concept of supervised learning and the relation with static optimization. Deep learning which extends supervised learning, can be viewed as a control problem. In the third part, we present the links between stochastic gradient descent and mean-field theory. Conversely, in the fourth and fifth parts, we review machine learning approaches to stochastic control problems, and focus on the deterministic case, to explain, more easily, the numerical algorithms.},
  copyright = {arXiv.org perpetual, non-exclusive license},
  keywords = {FOS: Computer and information sciences,FOS: Mathematics,Machine Learning (cs.LG),Machine Learning (stat.ML),Optimization and Control (math.OC)},
  annotation = {2 citations (Semantic Scholar/arXiv) [2022-12-09]}
}

@article{bird2008,
  title = {The Hippocampus and Memory: Insights from Spatial Processing},
  shorttitle = {The Hippocampus and Memory},
  author = {Bird, Chris M. and Burgess, Neil},
  year = {2008},
  month = mar,
  journal = {Nature Reviews Neuroscience},
  volume = {9},
  number = {3},
  pages = {182--194},
  issn = {1471-003X, 1471-0048},
  doi = {10.1038/nrn2335},
  langid = {english},
  annotation = {933 citations (Semantic Scholar/DOI) [2022-12-11] 00746}
}

@article{birn2013,
  title = {The Effect of Scan Length on the Reliability of Resting-State {{fMRI}} Connectivity Estimates},
  author = {Birn, Rasmus M. and Molloy, Erin K. and Patriat, R{\'e}mi and Parker, Taurean and Meier, Timothy B. and Kirk, Gregory R. and Nair, Veena A. and Meyerand, M. Elizabeth and Prabhakaran, Vivek},
  year = {2013},
  month = dec,
  journal = {NeuroImage},
  volume = {83},
  pages = {550--558},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2013.05.099},
  langid = {english},
  annotation = {558 citations (Semantic Scholar/DOI) [2022-11-29]}
}

@article{bitzer2014,
  title = {Perceptual Decision Making: Drift-Diffusion Model Is Equivalent to a {{Bayesian}} Model},
  shorttitle = {Perceptual Decision Making},
  author = {Bitzer, Sebastian and Park, Hame and Blankenburg, Felix and Kiebel, Stefan},
  year = {2014},
  journal = {Frontiers in Human Neuroscience},
  volume = {8},
  issn = {1662-5161},
  abstract = {Behavioral data obtained with perceptual decision making experiments are typically analyzed with the drift-diffusion model. This parsimonious model accumulates noisy pieces of evidence toward a decision bound to explain the accuracy and reaction times of subjects. Recently, Bayesian models have been proposed to explain how the brain extracts information from noisy input as typically presented in perceptual decision making tasks. It has long been known that the drift-diffusion model is tightly linked with such functional Bayesian models but the precise relationship of the two mechanisms was never made explicit. Using a Bayesian model, we derived the equations which relate parameter values between these models. In practice we show that this equivalence is useful when fitting multi-subject data. We further show that the Bayesian model suggests different decision variables which all predict equal responses and discuss how these may be discriminated based on neural correlates of accumulated evidence. In addition, we discuss extensions to the Bayesian model which would be difficult to derive for the drift-diffusion model. We suggest that these and other extensions may be highly useful for deriving new experiments which test novel hypotheses.},
  file = {/Users/morteza/Documents/Zotero/storage/C7N4Q44A/Bitzer et al_2014_Perceptual decision making.pdf}
}

@article{blair2017,
  title = {Educating Executive Function},
  author = {Blair, Clancy},
  year = {2017},
  journal = {WIREs Cognitive Science},
  volume = {8},
  number = {1-2},
  pages = {e1403},
  issn = {1939-5086},
  doi = {10.1002/wcs.1403},
  abstract = {Executive functions are thinking skills that assist with reasoning, planning, problem solving, and managing one's life. The brain areas that underlie these skills are interconnected with and influenced by activity in many different brain areas, some of which are associated with emotion and stress. One consequence of the stress-specific connections is that executive functions, which help us to organize our thinking, tend to be disrupted when stimulation is too high and we are stressed out, or too low when we are bored and lethargic. Given their central role in reasoning and also in managing stress and emotion, scientists have conducted studies, primarily with adults, to determine whether executive functions can be improved by training. By and large, results have shown that they can be, in part through computer-based videogame-like activities. Evidence of wider, more general benefits from such computer-based training, however, is mixed. Accordingly, scientists have reasoned that training will have wider benefits if it is implemented early, with very young children as the neural circuitry of executive functions is developing, and that it will be most effective if embedded in children's everyday activities. Evidence produced by this research, however, is also mixed. In sum, much remains to be learned about executive function training. Without question, however, continued research on this important topic will yield valuable information about cognitive development. WIREs Cogn Sci 2017, 8:e1403. doi: 10.1002/wcs.1403 This article is categorized under: Psychology {$>$} Attention Psychology {$>$} Learning},
  copyright = {\textcopyright{} 2016 Wiley Periodicals, Inc.},
  langid = {english},
  annotation = {00040  \_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcs.1403},
  file = {/Users/morteza/Documents/Zotero/storage/WSJN4KUG/Blair_2017_Educating executive function.pdf;/Users/morteza/Documents/Zotero/storage/MMGTBS7M/wcs.html}
}

@techreport{bodson2017,
  title = {Regards Sur Les Activit\'es Quotidiennes Des Jeunes R\'esidents ({{Regards}} Du {{STATEC Nr}}. 15).},
  author = {Bodson, L.},
  year = {2017},
  address = {{Luxembourg}},
  institution = {{Institut national de la statistique et des \'etudes \'economiques (statec)}}
}

@article{boot2008,
  title = {The Effects of Video Game Playing on Attention, Memory, and Executive Control},
  author = {Boot, Walter R. and Kramer, Arthur F. and Simons, Daniel J. and Fabiani, Monica and Gratton, Gabriele},
  year = {2008},
  month = nov,
  journal = {Acta Psychologica},
  volume = {129},
  number = {3},
  pages = {387--398},
  issn = {00016918},
  doi = {10.1016/j.actpsy.2008.09.005},
  langid = {english},
  annotation = {913 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{boot2011,
  title = {Do {{Action Video Games Improve Perception}} and {{Cognition}}?},
  author = {Boot, Walter R. and Blakely, Daniel P. and Simons, Daniel J.},
  year = {2011},
  journal = {Frontiers in Psychology},
  volume = {2},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2011.00226},
  annotation = {403 citations (Semantic Scholar/DOI) [2022-12-10]},
  file = {/Users/morteza/Documents/Zotero/storage/N22GHB5M/Boot et al. - 2011 - Do Action Video Games Improve Perception and Cogni.pdf}
}

@article{boot2013,
  title = {Video {{Games}} as a {{Means}} to {{Reduce Age-Related Cognitive Decline}}: {{Attitudes}}, {{Compliance}}, and {{Effectiveness}}},
  shorttitle = {Video {{Games}} as a {{Means}} to {{Reduce Age-Related Cognitive Decline}}},
  author = {Boot, Walter R. and Champion, Michael and Blakely, Daniel P. and Wright, Timothy and Souders, Dustin J. and Charness, Neil},
  year = {2013},
  month = feb,
  journal = {Frontiers in Psychology},
  volume = {4},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2013.00031},
  abstract = {Recent research has demonstrated broad benefits of video game play to perceptual and cognitive abilities. These broad improvements suggest that video game-based cognitive interventions may be ideal to combat the many perceptual and cognitive declines associated with advancing age. Furthermore, game interventions have the potential to induce higher rates of intervention compliance compared to other cognitive interventions as they are assumed to be inherently enjoyable and motivating. We explored these issues in an intervention that tested the ability of an action game and a ``brain fitness'' game to improve a variety of abilities. Cognitive abilities did not significantly improve, suggesting caution when recommending video game interventions as a means to reduce the effects of cognitive aging. However, the game expected to produce the largest benefit based on previous literature (an action game) induced the lowest intervention compliance. We explain this low compliance by participants' ratings of the action game as less enjoyable and by their prediction that training would have few meaningful benefits. Despite null cognitive results, data provide valuable insights into the types of video games older adults are willing to play and why.},
  pmcid = {PMC3561600},
  pmid = {23378841},
  annotation = {142 citations (Semantic Scholar/DOI) [2022-12-11] 00102}
}

@article{botvinick2002,
  title = {Representing Task Context: Proposals Based on a Connectionist Model of Action},
  shorttitle = {Representing Task Context},
  author = {Botvinick, Matthew and Plaut, David C.},
  year = {2002},
  month = nov,
  journal = {Psychological Research},
  volume = {66},
  number = {4},
  pages = {298--311},
  issn = {0340-0727},
  doi = {10.1007/s00426-002-0103-8},
  abstract = {Representations of task context play a crucial role in shaping human behavior. While the nature of these representations remains poorly understood, existing theories share a number of basic assumptions. One of these is that task representations are discrete, independent, and non-overlapping. We present here an alternative view, according to which task representations are instead viewed as graded, distributed patterns occupying a shared, continuous representational space. In recent work, we have implemented this view in a computational model of routine sequential action. In the present article, we focus specifically on this model's implications for understanding task representation, considering the implications of the account for two influential concepts: (1) cognitive underspecification, the idea that task representations may be imprecise or vague, especially in contexts where errors occur, and (2) information-sharing, the idea that closely related operations rely on common sets of internal representations.},
  langid = {english},
  pmid = {12466927},
  keywords = {Behavior,Cognition,Cognitive Science,Humans,Learning,Models; Psychological},
  annotation = {28 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/PKYMJT3E/Botvinick_Plaut_2002_Representing task context.pdf}
}

@article{botvinick2008,
  title = {Hierarchical Models of Behavior and Prefrontal Function},
  author = {Botvinick, Matthew M.},
  year = {2008},
  month = may,
  journal = {Trends in Cognitive Sciences},
  volume = {12},
  number = {5},
  pages = {201--208},
  issn = {1364-6613},
  doi = {10.1016/j.tics.2008.02.009},
  abstract = {The recognition of hierarchical structure in human behavior was one of the founding insights of the cognitive revolution. Despite decades of research, however, the computational mechanisms underlying hierarchically organized behavior are still not fully understood. Recent findings from behavioral and neuroscientific research have fueled a resurgence of interest in the problem, inspiring a new generation of computational models. In addition to developing some classic proposals, these models also break fresh ground, teasing apart different forms of hierarchical structure, placing a new focus on the issue of learning and addressing recent findings concerning the representation of behavioral hierarchies within the prefrontal cortex. In addition to offering explanations for some key aspects of behavior and functional neuroanatomy, the latest models also pose new questions for empirical research.},
  langid = {english},
  pmcid = {PMC2957875},
  pmid = {18420448},
  keywords = {Behavior,Cognition,Computer Simulation,Humans,Learning,Models; Psychological,Neuroanatomy,Prefrontal Cortex,Reaction Time,Task Performance and Analysis},
  file = {/Users/morteza/Documents/Zotero/storage/U6PNDSLZ/Botvinick_2008_Hierarchical models of behavior and prefrontal function.pdf}
}

@article{botvinick2014,
  ids = {botvinick2014a},
  title = {The {{Computational}} and {{Neural Basis}} of {{Cognitive Control}}: {{Charted Territory}} and {{New Frontiers}}},
  shorttitle = {The {{Computational}} and {{Neural Basis}} of {{Cognitive Control}}},
  author = {Botvinick, Matthew M. and Cohen, Jonathan D.},
  year = {2014},
  month = aug,
  journal = {Cognitive Science},
  volume = {38},
  number = {6},
  pages = {1249--1285},
  issn = {03640213},
  doi = {10.1111/cogs.12126},
  langid = {english},
  keywords = {Cognitive control,Cognitive Control,Computational modeling},
  annotation = {00258},
  file = {/Users/morteza/Documents/Zotero/storage/RZUU856N/Botvinick_Cohen_2014_The Computational and Neural Basis of Cognitive Control.pdf;/Users/morteza/Documents/Zotero/storage/PYKHKA8G/cogs.html}
}

@article{botvinick2015,
  title = {Motivation and Cognitive Control: From Behavior to Neural Mechanism},
  shorttitle = {Motivation and Cognitive Control},
  author = {Botvinick, Matthew and Braver, Todd},
  year = {2015},
  month = jan,
  journal = {Annual Review of Psychology},
  volume = {66},
  pages = {83--113},
  issn = {1545-2085},
  doi = {10.1146/annurev-psych-010814-015044},
  abstract = {Research on cognitive control and executive function has long recognized the relevance of motivational factors. Recently, however, the topic has come increasingly to center stage, with a surge of new studies examining the interface of motivation and cognitive control. In the present article we survey research situated at this interface, considering work from cognitive and social psychology and behavioral economics, but with a particular focus on neuroscience research. We organize existing findings into three core areas, considering them in the light of currently vying theoretical perspectives. Based on the accumulated evidence, we advocate for a view of control function that treats it as a domain of reward-based decision making. More broadly, we argue that neuroscientific evidence plays a critical role in understanding the mechanisms by which motivation and cognitive control interact. Opportunities for further cross-fertilization between behavioral and neuroscientific research are highlighted.},
  langid = {english},
  pmid = {25251491},
  keywords = {Cerebrum,cognitive control,Decision Making,effort,Executive Function,Humans,motivation,Motivation,prefrontal cortex,reward,Reward},
  annotation = {578 citations (Semantic Scholar/DOI) [2022-10-27]}
}

@article{botvinick2022,
  title = {Realizing the Promise of {{AI}}: A New Calling for Cognitive Science},
  shorttitle = {Realizing the Promise of {{AI}}},
  author = {Botvinick, Matthew M.},
  year = {2022},
  month = sep,
  journal = {Trends in Cognitive Sciences},
  issn = {1364-6613},
  doi = {10.1016/j.tics.2022.08.004},
  abstract = {Rapid progress in artificial intelligence (AI) places a new spotlight on a long-standing question: how can we best develop AI to maximize its benefits to humanity? Answering this question in a satisfying and timely way represents an exciting challenge not only for AI research but also for all member disciplines of cognitive science.},
  langid = {english},
  keywords = {AI ethics,alignment problem,human–AI interaction},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-10-27]}
}

@article{botvinik-nezer2020,
  title = {Variability in the Analysis of a Single Neuroimaging Dataset by Many Teams},
  author = {{Botvinik-Nezer}, Rotem and Holzmeister, Felix and Camerer, Colin F. and Dreber, Anna and Huber, Juergen and Johannesson, Magnus and Kirchler, Michael and Iwanir, Roni and Mumford, Jeanette A. and Adcock, R. Alison and Avesani, Paolo and Baczkowski, Blazej M. and Bajracharya, Aahana and Bakst, Leah and Ball, Sheryl and Barilari, Marco and Bault, Nad{\`e}ge and Beaton, Derek and Beitner, Julia and Benoit, Roland G. and Berkers, Ruud M. W. J. and Bhanji, Jamil P. and Biswal, Bharat B. and {Bobadilla-Suarez}, Sebastian and Bortolini, Tiago and Bottenhorn, Katherine L. and Bowring, Alexander and Braem, Senne and Brooks, Hayley R. and Brudner, Emily G. and Calderon, Cristian B. and Camilleri, Julia A. and Castrellon, Jaime J. and Cecchetti, Luca and Cieslik, Edna C. and Cole, Zachary J. and Collignon, Olivier and Cox, Robert W. and Cunningham, William A. and Czoschke, Stefan and Dadi, Kamalaker and Davis, Charles P. and Luca, Alberto De and Delgado, Mauricio R. and Demetriou, Lysia and Dennison, Jeffrey B. and Di, Xin and Dickie, Erin W. and Dobryakova, Ekaterina and Donnat, Claire L. and Dukart, Juergen and Duncan, Niall W. and Durnez, Joke and Eed, Amr and Eickhoff, Simon B. and Erhart, Andrew and Fontanesi, Laura and Fricke, G. Matthew and Fu, Shiguang and Galv{\'a}n, Adriana and Gau, Remi and Genon, Sarah and Glatard, Tristan and Glerean, Enrico and Goeman, Jelle J. and Golowin, Sergej A. E. and {Gonz{\'a}lez-Garc{\'i}a}, Carlos and Gorgolewski, Krzysztof J. and Grady, Cheryl L. and Green, Mikella A. and Guassi Moreira, Jo{\~a}o F. and Guest, Olivia and Hakimi, Shabnam and Hamilton, J. Paul and Hancock, Roeland and Handjaras, Giacomo and Harry, Bronson B. and Hawco, Colin and Herholz, Peer and Herman, Gabrielle and Heunis, Stephan and Hoffstaedter, Felix and Hogeveen, Jeremy and Holmes, Susan and Hu, Chuan-Peng and Huettel, Scott A. and Hughes, Matthew E. and Iacovella, Vittorio and Iordan, Alexandru D. and Isager, Peder M. and Isik, Ayse I. and Jahn, Andrew and Johnson, Matthew R. and Johnstone, Tom and Joseph, Michael J. E. and Juliano, Anthony C. and Kable, Joseph W. and Kassinopoulos, Michalis and Koba, Cemal and Kong, Xiang-Zhen and Koscik, Timothy R. and Kucukboyaci, Nuri Erkut and Kuhl, Brice A. and Kupek, Sebastian and Laird, Angela R. and Lamm, Claus and Langner, Robert and Lauharatanahirun, Nina and Lee, Hongmi and Lee, Sangil and Leemans, Alexander and Leo, Andrea and Lesage, Elise and Li, Flora and Li, Monica Y. C. and Lim, Phui Cheng and Lintz, Evan N. and Liphardt, Schuyler W. and Losecaat Vermeer, Annabel B. and Love, Bradley C. and Mack, Michael L. and Malpica, Norberto and Marins, Theo and Maumet, Camille and McDonald, Kelsey and McGuire, Joseph T. and Melero, Helena and M{\'e}ndez Leal, Adriana S. and Meyer, Benjamin and Meyer, Kristin N. and Mihai, Glad and Mitsis, Georgios D. and Moll, Jorge and Nielson, Dylan M. and Nilsonne, Gustav and Notter, Michael P. and Olivetti, Emanuele and Onicas, Adrian I. and Papale, Paolo and Patil, Kaustubh R. and Peelle, Jonathan E. and P{\'e}rez, Alexandre and Pischedda, Doris and Poline, Jean-Baptiste and Prystauka, Yanina and Ray, Shruti and {Reuter-Lorenz}, Patricia A. and Reynolds, Richard C. and Ricciardi, Emiliano and Rieck, Jenny R. and {Rodriguez-Thompson}, Anais M. and Romyn, Anthony and Salo, Taylor and {Samanez-Larkin}, Gregory R. and {Sanz-Morales}, Emilio and Schlichting, Margaret L. and Schultz, Douglas H. and Shen, Qiang and Sheridan, Margaret A. and Silvers, Jennifer A. and Skagerlund, Kenny and Smith, Alec and Smith, David V. and {Sokol-Hessner}, Peter and Steinkamp, Simon R. and Tashjian, Sarah M. and Thirion, Bertrand and Thorp, John N. and Tingh{\"o}g, Gustav and Tisdall, Loreen and Tompson, Steven H. and {Toro-Serey}, Claudio and Torre Tresols, Juan Jesus and Tozzi, Leonardo and Truong, Vuong and Turella, Luca and {van `t Veer}, Anna E. and Verguts, Tom and Vettel, Jean M. and Vijayarajah, Sagana and Vo, Khoi and Wall, Matthew B. and Weeda, Wouter D. and Weis, Susanne and White, David J. and Wisniewski, David and {Xifra-Porxas}, Alba and Yearling, Emily A. and Yoon, Sangsuk and Yuan, Rui and Yuen, Kenneth S. L. and Zhang, Lei and Zhang, Xu and Zosky, Joshua E. and Nichols, Thomas E. and Poldrack, Russell A. and Schonberg, Tom},
  year = {2020},
  month = jun,
  journal = {Nature},
  volume = {582},
  number = {7810},
  pages = {84--88},
  publisher = {{Nature Publishing Group}},
  issn = {1476-4687},
  doi = {10.1038/s41586-020-2314-9},
  abstract = {Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging~by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2\textendash 5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.},
  copyright = {2020 The Author(s), under exclusive licence to Springer Nature Limited},
  langid = {english},
  keywords = {Decision,Decision making,Human behaviour,Scientific community},
  annotation = {420 citations (Semantic Scholar/DOI) [2022-12-10]},
  file = {/Users/morteza/Documents/Zotero/storage/W93SHTKY/Botvinik-Nezer et al. - 2020 - Variability in the analysis of a single neuroimagi.pdf}
}

@misc{brandman2020,
  type = {Preprint},
  title = {The {{Surprising Role}} of the {{Default Mode Network}}},
  author = {Brandman, T. and Malach, R. and Simony., E.},
  year = {2020},
  month = may,
  publisher = {{Neuroscience}},
  doi = {10.1101/2020.05.18.101758},
  abstract = {Abstract                          The default mode network (DMN) is a group of high-order brain regions recently implicated in processing external naturalistic events, yet it remains unclear what cognitive function it serves. Here we identified the cognitive states predictive of DMN fMRI coactivation. Particularly, we developed a              state-fluctuation pattern analysis              , matching network coactivations across a short movie with retrospective behavioral sampling of movie events. Network coactivation was selectively correlated with the state of              surprise              across movie events, compared to all other cognitive states (e.g. emotion, vividness). The effect was exhibited in the DMN, but not dorsal attention or visual networks. Furthermore, surprise was found to mediate DMN coactivations with hippocampus and nucleus accumbens. These unexpected findings point to the DMN as a major hub in high-level prediction-error representations.},
  langid = {english}
}

@article{braver2001,
  title = {Context Processing in Older Adults: {{Evidence}} for a Theory Relating Cognitive Control to Neurobiology in Healthy Aging.},
  shorttitle = {Context Processing in Older Adults},
  author = {Braver, Todd S. and Barch, Deanna M. and Keys, Beth A. and Carter, Cameron S. and Cohen, Jonathan D. and Kaye, Jeffrey A. and Janowsky, Jeri S. and Taylor, Stephan F. and Yesavage, Jerome A. and Mumenthaler, Martin S. and Jagust, William J. and Reed, Bruce R.},
  year = {2001},
  month = dec,
  journal = {Journal of Experimental Psychology: General},
  volume = {130},
  number = {4},
  pages = {746--763},
  issn = {1939-2222, 0096-3445},
  doi = {10.1037/0096-3445.130.4.746},
  langid = {english},
  annotation = {494 citations (Semantic Scholar/DOI) [2022-12-14]}
}

@article{braver2007,
  title = {Explaining the Many Varieties of Working Memory Variation: {{Dual}} Mechanisms of Cognitive Control.},
  author = {Braver, Todd S. and Gray, Jeremy R. and Burgess, Gregory C.},
  year = {2007},
  journal = {Variation in working memory.},
  pages = {76--106},
  publisher = {{Oxford University Press}},
  address = {{New York,  NY,  US}},
  issn = {0-19-516863-1 (Hardcover); 978-0-19-516863-1 (Hardcover)},
  abstract = {In this chapter, we put forth a theory of cognitive control in working memory (WM) that attempts to explain this variability. Our central hypothesis is that cognitive control operates via two distinct operating modes: proactive control and reactive control. We will present arguments suggesting that these two modes are dissociable on a number of dimensions, such as computational properties, neural substrates, temporal dynamics, and consequences for information processing. We will suggest that although most formulations of cognitive control in WM only consider proactive control, reactive control mechanisms may be more dominant. We will further suggest that by distinguishing between these two modes we will be able to (1) resolve some of the apparent inconsistencies in the existing WM literature; (2) understand how and why the impact of cognitive control processes in WM can vary so strongly within individuals across time and task situations; (3) gain insight into the nature of cognitive control impairments found in healthy aging (and possibly in other populations suffering from neuropsychiatric disorders); (4) understand some of the critical underlying mechanisms related to individual differences in WM function; and (5) account for potentially surprising data indicating that putatively "noncognitive" variables such as mood states and personality traits (e.g., extraversion, neuroticism) may also influence WM function. The general theoretical framework that we advance here for understanding the sources of variation that affect WM and cognitive control is termed the dual mechanisms of control, or DMC account. It is worth noting that, although we have been developing this framework for several years now, this chapter marks the first comprehensive treatment of the theory and its empirical support. As such, we combine discussion of both published and not-yet-published experimental data in the sections below, to better make the case for how the DMC theory provides a fully integrated account of a variety of cognitive-control phenomena. Moreover, before turning to experimental findings, we first provide important theoretical background that motivated the development of this new theory. (PsycINFO Database Record (c) 2019 APA, all rights reserved)},
  keywords = {*Cognitive Ability,*Individual Differences,*Psychological Theories,*Short Term Memory,Cognitive Control},
  annotation = {00959}
}

@article{braver2012,
  title = {The Variable Nature of Cognitive Control: A Dual Mechanisms Framework},
  shorttitle = {The Variable Nature of Cognitive Control},
  author = {Braver, Todd S.},
  year = {2012},
  month = feb,
  journal = {Trends in Cognitive Sciences},
  volume = {16},
  number = {2},
  pages = {106--113},
  issn = {13646613},
  doi = {10.1016/j.tics.2011.12.010},
  langid = {english},
  annotation = {1617 citations (Semantic Scholar/DOI) [2022-12-11] 01090},
  file = {/Users/morteza/Documents/Zotero/storage/VE2VZGDA/false}
}

@article{braver2021,
  title = {The {{Dual Mechanisms}} of {{Cognitive Control Project}}},
  author = {Braver, Todd S. and Kizhner, Alexander and Tang, Rongxiang and Freund, Michael C. and Etzel, Joset A.},
  year = {2021},
  month = aug,
  journal = {Journal of Cognitive Neuroscience},
  pages = {1--26},
  issn = {1530-8898},
  doi = {10.1162/jocn_a_01768},
  abstract = {We describe an ambitious ongoing study that has been strongly influenced and inspired by Don Stuss's career-long efforts to identify key cognitive processes that characterize executive control, investigate potential unifying dimensions that define prefrontal function, and carefully attend to individual differences. The Dual Mechanisms of Cognitive Control project tests a theoretical framework positing two key control dimensions: proactive and reactive. The framework's central tenets are that proactive and reactive control modes reflect domain-general dimensions of individual variation, with distinctive neural signatures, involving the lateral pFC as a central node within associated brain networks (e.g., fronto-parietal, cingulo-opercular). In the Dual Mechanisms of Cognitive Control project, each participant is scanned while performing theoretically targeted variants of multiple well-established cognitive control tasks (Stroop, cued task-switching, AX-CPT, Sternberg working memory) in three separate imaging sessions, that each encourages utilization of different control modes plus also completes an extensive out-of-scanner individual differences battery. Additional key features of the project include a high spatio-temporal resolution (multiband) acquisition protocol and a sample that includes a substantial subset of monozygotic twin pairs and participants recruited from the Human Connectome Project. Although data collection is still continuing (target n = 200), we provide an overview of the study design and protocol, along with initial results (n = 80) revealing evidence of a domain-general neural signature of cognitive control and its modulation under reactive conditions. Aligned with Don Stuss's legacy of scientific community building, a partial data set has been publicly released, with the full data set released at project completion, so it can serve as a valuable resource.},
  langid = {english},
  pmid = {34407191},
  file = {/Users/morteza/Documents/Zotero/storage/FZFPMUGH/Braver et al_2021_The Dual Mechanisms of Cognitive Control Project.pdf}
}

@article{bressler2010,
  title = {Large-Scale Brain Networks in Cognition: Emerging Methods and Principles},
  shorttitle = {Large-Scale Brain Networks in Cognition},
  author = {Bressler, Steven L. and Menon, Vinod},
  year = {2010},
  month = jun,
  journal = {Trends in Cognitive Sciences},
  volume = {14},
  number = {6},
  pages = {277--290},
  issn = {13646613},
  doi = {10.1016/j.tics.2010.04.004},
  langid = {english},
  annotation = {1791 citations (Semantic Scholar/DOI) [2022-12-11] 01342}
}

@article{brick2021,
  title = {Illusory Essences: {{A}} Bias Holding Back Theorizing in Psychological Science},
  author = {Brick, C and Hood, B and Ekroll, V and {de-Wit}, L},
  year = {2021},
  journal = {Perspectives on Psychological Science},
  issn = {1745-6916},
  abstract = {The reliance in psychology on verbal definitions means that psychological research is unusually moored to how humans think and communicate about categories. Psychological concepts (e.g., intelligence, attention) are easily assumed to represent objective, definable categories with an underlying essence. Like the ``vital forces'' previously thought to animate life, these assumed essences can create an illusion of understanding. By synthesizing a wide range of research lines from cognitive, clinical, and biological psychology and neuroscience, we describe a pervasive tendency across psychological science to assume that essences explain phenomena. Labeling a complex phenomenon can appear as theoretical progress before there is sufficient evidence that the described category has a definable essence or known boundary conditions. Category labels can further undermine progress by masking contingent and contextual relationships and obscuring the need to specify mechanisms. Finally, we highlight examples of promising methods that circumvent the lure of essences and suggest four concrete strategies for identifying and avoiding essentialist intuitions in theory development.},
  pmid = {34283676}
}

@article{brown2020,
  title = {Language Models Are Few-Shot Learners},
  author = {Brown, Tom B and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and {Herbert-Voss}, Ariel and Krueger, Gretchen and Henighan, Tom and Child, Rewon and Ramesh, Aditya and Ziegler, Daniel M and Wu, Jeffrey and Winter, Clemens and Hesse, Christopher and Chen, Mark and Sigler, Eric and Litwin, Mateusz and Gray, Scott and Chess, Benjamin and Clark, Jack and Berner, Christopher and McCandlish, Sam and Radford, Alec and Sutskever, Ilya and Amodei, Dario},
  year = {2020},
  journal = {arXiv},
  eprint = {2005.14165},
  abstract = {Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-training on a large corpus of text followed by fine-tuning on a specific task. While typically task-agnostic in architecture, this method still requires task-specific fine-tuning datasets of thousands or tens of thousands of examples. By contrast, humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do. Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with prior state-of-the-art fine-tuning approaches. Specifically, we train GPT-3, an autoregressive language model with 175 billion parameters, 10x more than any previous non-sparse language model, and test its performance in the few-shot setting. For all tasks, GPT-3 is applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model. GPT-3 achieves strong performance on many NLP datasets, including translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a sentence, or performing 3-digit arithmetic. At the same time, we also identify some datasets where GPT-3's few-shot learning still struggles, as well as some datasets where GPT-3 faces methodological issues related to training on large web corpora. Finally, we find that GPT-3 can generate samples of news articles which human evaluators have difficulty distinguishing from articles written by humans. We discuss broader societal impacts of this finding and of GPT-3 in general.}
}

@misc{brunton2017,
  title = {Control Bootcamp},
  author = {Brunton, Steve},
  year = {2017},
  annotation = {00000}
}

@article{bull2008,
  title = {Short-Term Memory, Working Memory, and Executive Functioning in Preschoolers: Longitudinal Predictors of Mathematical Achievement at Age 7 Years},
  shorttitle = {Short-Term Memory, Working Memory, and Executive Functioning in Preschoolers},
  author = {Bull, Rebecca and Espy, Kimberly Andrews and Wiebe, Sandra A.},
  year = {2008},
  journal = {Developmental Neuropsychology},
  volume = {33},
  number = {3},
  pages = {205--228},
  issn = {1532-6942},
  doi = {10.1080/87565640801982312},
  abstract = {This study examined whether measures of short-term memory, working memory, and executive functioning in preschool children predict later proficiency in academic achievement at 7 years of age (third year of primary school). Children were tested in preschool (M age = 4 years, 6 months) on a battery of cognitive measures, and mathematics and reading outcomes (from standardized, norm-referenced school-based assessments) were taken on entry to primary school, and at the end of the first and third year of primary school. Growth curve analyses examined predictors of math and reading achievement across the duration of the study and revealed that better digit span and executive function skills provided children with an immediate head start in math and reading that they maintained throughout the first three years of primary school. Visual-spatial short-term memory span was found to be a predictor specifically of math ability. Correlational and regression analyses revealed that visual short-term and working memory were found to specifically predict math achievement at each time point, while executive function skills predicted learning in general rather than learning in one specific domain. The implications of the findings are discussed in relation to further understanding the role of cognitive skills in different mathematical tasks, and in relation to the impact of limited cognitive skills in the classroom environment.},
  langid = {english},
  pmcid = {PMC2729141},
  pmid = {18473197},
  keywords = {Achievement,Age Factors,Aptitude,Attention,Child,Child; Preschool,Color Perception,Concept Formation,Discrimination Learning,Female,Games; Experimental,Humans,Longitudinal Studies,Male,Mathematics,Memory; Short-Term,Neuropsychological Tests,Orientation,Pattern Recognition; Visual,Problem Solving,Psychometrics,Psychomotor Performance,Reaction Time,Reading,Sex Factors},
  annotation = {1377 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/GZMIIRKM/Bull et al. - 2008 - Short-term memory, working memory, and executive f.pdf}
}

@article{burgoyne2020,
  title = {Attention Control: {{A}} Cornerstone of Higher-Order Cognition},
  author = {Burgoyne, Alexander P. and Engle, Randall W.},
  year = {2020},
  journal = {Current Directions in Psychological Science},
  volume = {29},
  number = {6},
  issn = {0963-7214},
  abstract = {For years, psychologists have wondered why people who are highly skilled in one cognitive domain tend to be skilled in other cognitive domains, too. In this article, we explain how attention control provides a common thread among broad cognitive abilities, including fluid intelligence, working memory capacity, and sensory discrimination. Attention control allows us to pursue our goals despite distractions and temptations, to deviate from the habitual, and to keep information in mind amid a maelstrom of divergent thought. Highlighting results from our lab, we describe the role of attention control in information maintenance and disengagement and how these functions contribute to performance in a variety of complex cognitive tasks. We also describe a recent undertaking in which we developed new and improved attention-control tasks, which had higher reliabilities, stronger intercorrelations, and higher loadings on a common factor than traditional measures. From an applied perspective, these new attention-control tasks show great promise for use in personnel selection assessments. We close by outlining exciting avenues for future research.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/Burgoyne{$_2$}020{$_1$}.pdf},
  keywords = {Executive Functions}
}

@article{buschkuehl2012,
  title = {Neuronal Effects Following Working Memory Training.},
  author = {Buschkuehl, Martin and Jaeggi, Susanne M and Jonides, John},
  year = {2012},
  month = feb,
  journal = {Developmental cognitive neuroscience},
  volume = {2 Suppl 1},
  pages = {S167--79},
  doi = {10.1016/j.dcn.2011.10.001},
  abstract = {There is accumulating evidence that training working memory (WM) leads to beneficial effects in tasks that were not trained, but the mechanisms underlying this transfer remain elusive. Brain imaging can be a valuable method to gain insights into such mechanisms. Here, we discuss the impact of cognitive training on neural correlates with an emphasis on studies that implemented a WM intervention. We focus on changes in activation patterns, changes in resting state connectivity, changes in brain structure, and changes in the dopaminergic system. Our analysis of the existing literature reveals that there is currently no clear pattern of results that would single out a specific neural mechanism underlying training and transfer. We conclude that although brain imaging has provided us with information about the mechanisms of WM training, more research is needed to understand its neural impact.},
  langid = {english},
  pmid = {22682905},
  annotation = {196 citations (Semantic Scholar/DOI) [2022-12-11] 00168}
}

@article{capretto2022,
  title = {Bambi: {{A}} Simple Interface for Fitting Bayesian Linear Models in Python},
  author = {Capretto, Tom{\'a}s and Piho, Camen and Kumar, Ravin and Westfall, Jacob and Yarkoni, Tal and Martin, Osvaldo A},
  year = {2022},
  journal = {Journal of Statistical Software},
  volume = {103},
  number = {15},
  pages = {1--29},
  doi = {10.18637/jss.v103.i15},
  annotation = {13 citations (Semantic Scholar/DOI) [2022-12-14]}
}

@article{cardoso-leite2015,
  title = {On the Impact of New Technologies on Multitasking},
  author = {{Cardoso-Leite}, Pedro and Green, C. Shawn and Bavelier, Daphne},
  year = {2015},
  month = mar,
  journal = {Developmental Review},
  volume = {35},
  pages = {98--112},
  issn = {02732297},
  doi = {10.1016/j.dr.2014.12.001},
  langid = {english},
  annotation = {36 citations (Semantic Scholar/DOI) [2022-12-11] 00025},
  file = {/Users/morteza/Documents/Zotero/storage/DWJTP8PW/CardosoG&B_DevReview 0214.pdf}
}

@article{cardoso-leite2016,
  ids = {cardoso-leite2016a},
  title = {Technology Consumption and Cognitive Control: {{Contrasting}} Action Video Game Experience with Media Multitasking},
  shorttitle = {Technology Consumption and Cognitive Control},
  author = {{Cardoso-Leite}, Pedro and Kludt, Rachel and Vignola, Gianluca and Ma, Wei Ji and Green, C. Shawn and Bavelier, Daphne},
  year = {2016},
  journal = {Attention, Perception, \& Psychophysics},
  volume = {78},
  number = {1},
  pages = {218--241},
  annotation = {00029},
  file = {/Users/morteza/Documents/Zotero/storage/LIVPGLZ7/s1-ln2011024395844769-1939656818Hwf-1530618246IdV191325474220110243PDF_HI0001.pdf;/Users/morteza/Documents/Zotero/storage/M3TWC685/Cardoso-Leite et al. - 2016 - Technology consumption and cognitive control Cont.pdf;/Users/morteza/Documents/Zotero/storage/RDJ7RSGB/cardoso-leite2016.pdf}
}

@incollection{cardoso-leite2020,
  title = {Games for Enhancing Cognitive Abili\-ties},
  booktitle = {Handbook of Game-Based Learning},
  author = {{Pedro Cardoso-Leite} and {Augustin Joessel} and {Daphne Bavelier}},
  editor = {{Jan L. Plass} and {Richard E. Mayer} and {Bruce D. Homer}},
  year = {2020},
  publisher = {{The MIT Press}},
  address = {{Cambridge, MA}},
  isbn = {978-0-262-04338-0},
  lccn = {LB1029.G3 H34 2020},
  keywords = {Educational games,Educational technology,Handbooks; manuals; etc}
}

@inbook{cardoso-leite2021,
  title = {Training Cognition with Video Games},
  booktitle = {The {{Oxford Handbook}} of {{Developmental Cognitive Neuroscience}}},
  author = {{Cardoso-Leite}, Pedro and Ansarinia, Morteza and Schm{\"u}ck, Emmanuel and Bavelier, Daphne},
  year = {2021},
  month = jan,
  publisher = {{Oxford University Press}},
  doi = {10.1093/oxfordhb/9780198827474.013.38},
  abstract = {This chapter reviews the behavioral and neuroimaging scientific literature on the cognitive consequences of playing various genres of video games. The available research highlights that not all video games have similar cognitive impact; action video games as defined by first- and third-person shooter games have been associated with greater cognitive enhancement, especially when it comes to top-down attention, than puzzle or life-simulation games. This state of affairs suggests specific game mechanics need to be embodied in a video game for it to enhance cognition. These hypothesized game mechanics are reviewed; yet, the authors note that the advent of more complex, hybrid, video games poses new research challenges and call for a more systematic assessment of how specific video game mechanics relate to cognitive enhancement.},
  collaborator = {{Cardoso-Leite}, Pedro and Ansarinia, Morteza and Schm{\"u}ck, Emmanuel and Bavelier, Daphne},
  isbn = {978-0-19-882747-4},
  langid = {english}
}

@incollection{cardoso-leiteinpress,
  title = {Games for Enhancing Cognitive Abilities},
  booktitle = {Handbook of {{Game-based Learning}}},
  author = {{Cardoso-Leite}, P and Joessel, A and Bavelier, D},
  editor = {Plass, Jan and Mayer, Richard E. and Homer, Bruce D},
  year = {in press},
  publisher = {{MIT Press}},
  address = {{Boston}},
  keywords = {\#nosource},
  annotation = {00000}
}

@article{cellier2022,
  title = {Dynamics of {{Hierarchical Task Representations}}},
  author = {Cellier, Dillan and Petersen, Isaac T. and Hwang, Kai},
  year = {2022},
  month = aug,
  journal = {The Journal of Neuroscience: The Official Journal of the Society for Neuroscience},
  pages = {JN-RM-0233-22},
  issn = {1529-2401},
  doi = {10.1523/JNEUROSCI.0233-22.2022},
  abstract = {Task representations are critical for cognitive control and adaptive behavior. The hierarchical organization of task representations allows humans to maintain goals, integrate information across varying contexts, and select potential responses. In this study we characterized the structure and interactive dynamics of task representations that facilitate cognitive control. Human participants (both males and females) performed a hierarchical task that required them to select a response rule while considering the contingencies from different contextual inputs. By applying time- and frequency-resolved representational similarity analysis to human electroencephalography data, we characterized properties of task representations that are otherwise difficult to observe. We found that participants formed multiple representations of task-relevant contexts and features from the presented stimuli, beyond simple stimulus-response mappings. These disparate representations were hierarchically structured, with higher-order contextual representations dominantly influencing subordinate representations of task features and response rules. Furthermore, this cascade of top-down interactions facilitated faster responses. Our results describe key properties of task representations that support hierarchical cognitive control.SIGNIFICANCE STATEMENTHumans can adjust their actions in response to contingencies imposed from the environment. Though it has long been hypothesized that this ability depends on mental representations of tasks, the neural dynamics of task representations have been difficult to characterize. Our study utilized electroencephalography data from human participants to demonstrate the neural organization and interactive dynamics of task representations. Our results revealed a top-down, hierarchically organized representational structure that encoded multiple contexts and features from the environment. To support cognitive control, higher-level contextual representations influenced subordinate representations of task-relevant features and potential responses, facilitating response selection in a context-dependent manner. Our results provide direct evidence on organizational properties of task representations, which are cornerstones of cognitive control theories.},
  langid = {english},
  pmcid = {PMC9512570},
  pmid = {35985836},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/MVH3CLMQ/Cellier et al_2022_Dynamics of Hierarchical Task Representations.pdf}
}

@inproceedings{ChalnickBillman1988a,
  title = {Unsupervised Learning of Correlational Structure},
  booktitle = {Proceedings of the Tenth Annual Conference of the Cognitive Science Society},
  author = {Chalnick, A. and Billman, D.},
  year = {1988},
  pages = {510--516},
  publisher = {{Lawrence Erlbaum Associates}},
  address = {{Hillsdale, NJ}}
}

@article{chan2008,
  title = {Assessment of Executive Functions: {{Review}} of Instruments and Identification of Critical Issues},
  shorttitle = {Assessment of Executive Functions},
  author = {Chan, Raymond C. K. and Shum, David and Toulopoulou, Timothea and Chen, Eric Y. H.},
  year = {2008},
  month = mar,
  journal = {Archives of Clinical Neuropsychology},
  volume = {23},
  number = {2},
  pages = {201--216},
  issn = {0887-6177},
  doi = {10.1016/j.acn.2007.08.010},
  abstract = {``Executive functions'' is an umbrella term for functions such as planning, working memory, inhibition, mental flexibility, as well as the initiation and monitoring of action. The impairment of executive functions in various clinical groups is a topic of much debate, as are recent attempts to formulate the corresponding intervention and rehabilitation regimes of these dysfunctions. This article reviewed current theories of executive functions and their associated assessment instruments. In addition, it identified issues that are imperative for more accurate, sensitive, and specific assessment of various components of this construct. It is concluded that more research is needed to fractionate the executive system by assessing a wide range of functions and to verify their neuroanatomical correlates. Recently developed measurement models and technology may also facilitate a more ecologically and ethologically valid assessment for the specific needs of different individuals.},
  langid = {english},
  keywords = {Assessment,Executive function,Rehabilitation},
  annotation = {1190 citations (Semantic Scholar/DOI) [2022-12-11] 01620},
  file = {/Users/morteza/Documents/Zotero/storage/MNZ3YY8Q/Chan et al_2008_Assessment of executive functions.pdf;/Users/morteza/Documents/Zotero/storage/FM6EGVMU/S0887617707001928.html}
}

@article{chen2019,
  title = {Testing a Cognitive Control Model of Human Intelligence},
  author = {Chen, Yu and Spagna, Alfredo and Wu, Tingting and Kim, Tae Hyeong and Wu, Qiong and Chen, Caiqi and Wu, Yanhong and Fan, Jin},
  year = {2019},
  journal = {Scientific Reports},
  volume = {9},
  number = {1},
  pages = {2898},
  doi = {10.1038/s41598-019-39685-2},
  abstract = {The definition of human intelligence and its underlying psychological constructs have long been debated. Although previous studies have investigated the fundamental cognitive functions determining intellectual abilities, such as the broadly defined executive functions including working memory, the core process has yet to be identified. A potential candidate for such a role might be cognitive control, a psychological construct for the coordination of thoughts and actions under conditions of uncertainty. In this study, we tested a cognitive control model of intellectual ability by examining the association between cognitive control, measured by a perceptual decision-making task and by the attention network test, and general intelligence including components of fluid intelligence (Gf, concerning the ability to solve problems by abstraction) and crystalized intelligence (Gc, related to learning from prior knowledge and experience) measured by the Wechsler Adult Intelligence Scale. We also examined the potential role of cognitive control as a core process involved in another determinant of intellectual abilities, the working memory, measured by the N-back tasks and the working memory complex span tasks. The relationship among intelligence, cognitive control, and working memory was examined using structural equation modeling. Results showed that cognitive control shared a large amount of variance with working memory and both measures were strongly associated with Gf and Gc, with a stronger association with Gf than Gc. These findings suggest that cognitive control, serving as a core construct of executive functions, contributes substantially to general intellectual ability, especially fluid intelligence.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2019/Chen\%202019.pdf},
  pmid = {30814663},
  keywords = {Cognitive Control},
  annotation = {00019}
}

@article{cherney2008,
  title = {Mom, {{Let Me Play More Computer Games}}: {{They Improve My Mental Rotation Skills}}},
  shorttitle = {Mom, {{Let Me Play More Computer Games}}},
  author = {Cherney, Isabelle D.},
  year = {2008},
  month = dec,
  journal = {Sex Roles},
  volume = {59},
  number = {11-12},
  pages = {776--786},
  issn = {0360-0025, 1573-2762},
  doi = {10.1007/s11199-008-9498-z},
  langid = {english},
  annotation = {189 citations (Semantic Scholar/DOI) [2022-12-11] 00187}
}

@article{cherney2014,
  title = {Training {{Spatial Skills}} in {{Men}} and {{Women}}},
  author = {Cherney, Isabelle D. and Bersted, Kyle and Smetter, Joseph},
  year = {2014},
  month = aug,
  journal = {Perceptual and Motor Skills},
  volume = {119},
  number = {1},
  pages = {82--99},
  issn = {0031-5125, 1558-688X},
  doi = {10.2466/23.25.PMS.119c12z0},
  langid = {english},
  annotation = {32 citations (Semantic Scholar/DOI) [2022-12-11] 00020}
}

@article{chesham2017,
  title = {What {{Older People Like}} to {{Play}}: {{Genre Preferences}} and {{Acceptance}} of {{Casual Games}}},
  shorttitle = {What {{Older People Like}} to {{Play}}},
  author = {Chesham, Alvin and Wyss, Patric and M{\"u}ri, Ren{\'e} Martin and Mosimann, Urs Peter and Nef, Tobias},
  year = {2017},
  month = apr,
  journal = {JMIR Serious Games},
  volume = {5},
  number = {2},
  pages = {e8},
  issn = {2291-9279},
  doi = {10.2196/games.7025},
  langid = {english},
  annotation = {50 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/ZA3JDJIY/chesham2017.pdf}
}

@misc{chollet2019,
  title = {On the {{Measure}} of {{Intelligence}}},
  author = {Chollet, Fran{\c c}ois},
  year = {2019},
  month = nov,
  number = {arXiv:1911.01547},
  eprint = {1911.01547},
  eprinttype = {arxiv},
  primaryclass = {cs},
  publisher = {{arXiv}},
  abstract = {To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans. Over the past hundred years, there has been an abundance of attempts to define and measure intelligence, across both the fields of psychology and AI. We summarize and critically assess these definitions and evaluation approaches, while making apparent the two historical conceptions of intelligence that have implicitly guided them. We note that in practice, the contemporary AI community still gravitates towards benchmarking intelligence by comparing the skill exhibited by AIs and humans at specific tasks such as board games and video games. We argue that solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience: unlimited priors or unlimited training data allow experimenters to "buy" arbitrary levels of skills for a system, in a way that masks the system's own generalization power. We then articulate a new formal definition of intelligence based on Algorithmic Information Theory, describing intelligence as skill-acquisition efficiency and highlighting the concepts of scope, generalization difficulty, priors, and experience. Using this definition, we propose a set of guidelines for what a general AI benchmark should look like. Finally, we present a benchmark closely following these guidelines, the Abstraction and Reasoning Corpus (ARC), built upon an explicit set of priors designed to be as close as possible to innate human priors. We argue that ARC can be used to measure a human-like form of general fluid intelligence and that it enables fair general intelligence comparisons between AI systems and humans.},
  archiveprefix = {arXiv},
  keywords = {Artificial Intelligence (cs.AI),Computer Science - Artificial Intelligence,FOS: Computer and information sciences},
  annotation = {17 citations (Semantic Scholar/arXiv) [2022-12-01]},
  file = {/Users/morteza/Documents/Zotero/storage/3LFUILLN/Chollet_2019_On the Measure of Intelligence.pdf;/Users/morteza/Documents/Zotero/storage/CMSZS74U/1911.html}
}

@article{chopin2019,
  title = {Altering Perception: The Case of Action Video Gaming},
  shorttitle = {Altering Perception},
  author = {Chopin, Adrien and Bediou, Benoit and Bavelier, Daphne},
  year = {2019},
  month = oct,
  journal = {Current Opinion in Psychology},
  volume = {29},
  pages = {168--173},
  issn = {2352250X},
  doi = {10.1016/j.copsyc.2019.03.004},
  langid = {english},
  annotation = {26 citations (Semantic Scholar/DOI) [2022-12-09]}
}

@book{christian2016,
  title = {Algorithms to Live by: The Computer Science of Human Decisions},
  shorttitle = {Algorithms to Live By},
  author = {Christian, Brian and Griffiths, Tom},
  year = {2016},
  edition = {First international edition},
  publisher = {{Henry Holt and Company}},
  address = {{New York}},
  isbn = {978-1-62779-036-9},
  langid = {english}
}

@inproceedings{christie2019,
  title = {Understanding the Timing of Cognitive Processes with a Variable Rate Neural Code},
  booktitle = {2019 {{Conference}} on {{Cognitive Computational Neuroscience}}},
  author = {Christie, S. Thomas and Schrater, Paul},
  year = {2019},
  publisher = {{Cognitive Computational Neuroscience}},
  address = {{Berlin, Germany}},
  doi = {10.32470/CCN.2019.1397-0},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-12-06]}
}

@article{chu2021,
  title = {Slowed Canonical Progress in Large Fields of Science},
  author = {Chu, Johan S. G. and Evans, James A.},
  year = {2021},
  month = oct,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {118},
  number = {41},
  pages = {e2021636118},
  publisher = {{Proceedings of the National Academy of Sciences}},
  doi = {10.1073/pnas.2021636118},
  abstract = {In many academic fields, the number of papers published each year has increased significantly over time. Policy measures aim to increase the quantity of scientists, research funding, and scientific output, which is measured by the number of papers produced. These quantitative metrics determine the career trajectories of scholars and evaluations of academic departments, institutions, and nations. Whether and how these increases in the numbers of scientists and papers translate into advances in knowledge is unclear, however. Here, we first lay out a theoretical argument for why too many papers published each year in a field can lead to stagnation rather than advance. The deluge of new papers may deprive reviewers and readers the cognitive slack required to fully recognize and understand novel ideas. Competition among many new ideas may prevent the gradual accumulation of focused attention on a promising new idea. Then, we show data supporting the predictions of this theory. When the number of papers published per year in a scientific field grows large, citations flow disproportionately to already well-cited papers; the list of most-cited papers ossifies; new papers are unlikely to ever become highly cited, and when they do, it is not through a gradual, cumulative process of attention gathering; and newly published papers become unlikely to disrupt existing work. These findings suggest that the progress of large scientific fields may be slowed, trapped in existing canon. Policy measures shifting how scientific work is produced, disseminated, consumed, and rewarded may be called for to push fields into new, more fertile areas of study.},
  file = {/Users/morteza/Documents/Zotero/storage/Q45TNQ3E/Chu_Evans_2021_Slowed canonical progress in large fields of science.pdf}
}

@inproceedings{chuang2007a,
  title = {Effect of {{Computer-Based Video Games}} on {{Children}}: {{An Experimental Study}}},
  shorttitle = {Effect of {{Computer-Based Video Games}} on {{Children}}},
  booktitle = {2007 {{First IEEE International Workshop}} on {{Digital Game}} and {{Intelligent Toy Enhanced Learning}} ({{DIGITEL}}'07)},
  author = {Chuang, Tsung-Yen and Chen, Wei-Fan},
  year = {2007},
  month = mar,
  pages = {114--118},
  publisher = {{IEEE}},
  address = {{Jhongli City}},
  doi = {10.1109/DIGITEL.2007.24},
  isbn = {978-0-7695-2801-4},
  annotation = {168 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{chuang2007b,
  title = {Effect of {{Digital Games}} on {{Children}}'s {{Cognitive Achievement}}.},
  author = {Chuang, Tsung-Yen and Chen, Wei-Fan},
  year = {2007},
  journal = {Journal of Multimedia},
  volume = {2},
  number = {5},
  annotation = {00034},
  file = {/Users/morteza/Documents/Zotero/storage/EDZH9QQB/Chuang and Chen - 2007 - Effect of Digital Games on Children's Cognitive Ac.pdf}
}

@article{chun2011,
  title = {A Taxonomy of External and Internal Attention},
  author = {Chun, Marvin M and Golomb, Julie D and {Turk-Browne}, Nicholas B},
  year = {2011},
  journal = {Annual Review of Psychology},
  volume = {62},
  number = {1},
  pages = {73--101},
  issn = {0066-4308},
  doi = {10.1146/annurev.psych.093008.100427},
  abstract = {Attention is a core property of all perceptual and cognitive operations. Given limited capacity to process competing options, attentional mechanisms select, modulate, and sustain focus on information most relevant for behavior. A significant problem, however, is that attention is so ubiquitous that it is unwieldy to study. We propose a taxonomy based on the types of information that attention operates over\textemdash the targets of attention. At the broadest level, the taxonomy distinguishes between external attention and internal attention. External attention refers to the selection and modulation of sensory information. External attention selects locations in space, points in time, or modality-specific input. Such perceptual attention can also select features defined across any of these dimensions, or object representations that integrate over space, time, and modality. Internal attention refers to the selection, modulation, and maintenance of internally generated information, such as task rules, responses, long-term memory, or working memory. Working memory, in particular, lies closest to the intersection between external and internal attention. The taxonomy provides an organizing framework that recasts classic debates, raises new issues, and frames understanding of neural mechanisms.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2011/Chun\%202011.pdf},
  pmid = {19575619},
  annotation = {01011}
}

@article{churchland2008,
  title = {Decision-Making with Multiple Alternatives},
  author = {Churchland, Anne K. and Kiani, Roozbeh and Shadlen, Michael N.},
  year = {2008},
  month = jun,
  journal = {Nature Neuroscience},
  volume = {11},
  number = {6},
  pages = {693--702},
  publisher = {{Nature Publishing Group}},
  issn = {1546-1726},
  doi = {10.1038/nn.2123},
  abstract = {Simple perceptual tasks have laid the groundwork for understanding the neurobiology of decision-making. Here, we examined this foundation to explain how decision-making circuitry adjusts in the face of a more difficult task. We measured behavioral and physiological responses of monkeys on a two- and four-choice direction-discrimination decision task. For both tasks, firing rates in the lateral intraparietal area appeared to reflect the accumulation of evidence for or against each choice. Evidence accumulation began at a lower firing rate for the four-choice task, but reached a common level by the end of the decision process. The larger excursion suggests that the subjects required more evidence before making a choice. Furthermore, on both tasks, we observed a time-dependent rise in firing rates that may impose a deadline for deciding. These physiological observations constitute an effective strategy for handling increased task difficulty. The differences appear to explain subjects' accuracy and reaction times.},
  copyright = {2008 Nature Publishing Group},
  langid = {english},
  keywords = {Animal Genetics and Genomics,Behavioral Sciences,Biological Techniques,Biomedicine,general,Neurobiology,Neurosciences},
  annotation = {599 citations (Semantic Scholar/DOI) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/DPVCSUDX/Churchland et al_2008_Decision-making with multiple alternatives.pdf}
}

@techreport{ciric2021,
  type = {Preprint},
  title = {{{TemplateFlow}}: {{FAIR-sharing}} of Multi-Scale, Multi-Species Brain Models},
  shorttitle = {{{TemplateFlow}}},
  author = {Ciric, Rastko and Thompson, William H. and Lorenz, Romy and Goncalves, Mathias and MacNicol, Eilidh and Markiewicz, Christopher J. and Halchenko, Yaroslav O. and Ghosh, Satrajit S. and Gorgolewski, Krzysztof J. and Poldrack, Russell A. and Esteban, Oscar},
  year = {2021},
  month = feb,
  institution = {{Neuroscience}},
  doi = {10.1101/2021.02.10.430678},
  abstract = {Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references \textemdash i.e., templates\textemdash{} and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR \textemdash findable, accessible, interoperable, reusable\textemdash{} principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/NHWXGLWB/Ciric et al. - 2021 - TemplateFlow FAIR-sharing of multi-scale, multi-s.pdf}
}

@article{cohen2008,
  title = {Defining Functional Areas in Individual Human Brains Using Resting Functional Connectivity {{MRI}}},
  author = {Cohen, Alexander L. and Fair, Damien A. and Dosenbach, Nico U.F. and Miezin, Francis M. and Dierker, Donna and Van Essen, David C. and Schlaggar, Bradley L. and Petersen, Steven E.},
  year = {2008},
  month = may,
  journal = {NeuroImage},
  volume = {41},
  number = {1},
  pages = {45--57},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2008.01.066},
  langid = {english},
  annotation = {541 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/YZ3WNJIC/Cohen et al. - 2008 - Defining functional areas in individual human brai.pdf}
}

@article{cohen2014,
  title = {Quantifying the {{Reconfiguration}} of {{Intrinsic Networks}} during {{Working Memory}}},
  author = {Cohen, Jessica R. and Gallen, Courtney L. and Jacobs, Emily G. and Lee, Taraz G. and D'Esposito, Mark},
  year = {2014},
  month = sep,
  journal = {PLOS ONE},
  volume = {9},
  number = {9},
  pages = {e106636},
  publisher = {{Public Library of Science}},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0106636},
  abstract = {Rapid, flexible reconfiguration of connections across brain regions is thought to underlie successful cognitive control. Two intrinsic networks in particular, the cingulo-opercular (CO) and fronto-parietal (FP), are thought to underlie two operations critical for cognitive control: task-set maintenance/tonic alertness and adaptive, trial-by-trial updating. Using functional magnetic resonance imaging, we directly tested whether the functional connectivity of the CO and FP networks was related to cognitive demands and behavior. We focused on working memory because of evidence that during working memory tasks the entire brain becomes more integrated. When specifically probing the CO and FP cognitive control networks, we found that individual regions of both intrinsic networks were active during working memory and, as expected, integration across the two networks increased during task blocks that required cognitive control. Crucially, increased integration between each of the cognitive control networks and a task-related, non-cognitive control network (the hand somatosensory-motor network; SM) was related to increased accuracy. This implies that dynamic reconfiguration of the CO and FP networks so as to increase their inter-network communication underlies successful working memory.},
  langid = {english},
  keywords = {Behavior,Cingulate cortex,Functional magnetic resonance imaging,Neural networks,Neuroimaging,Prefrontal cortex,Thalamus,Working memory},
  annotation = {49 citations (Semantic Scholar/DOI) [2022-12-06]},
  file = {/Users/morteza/Documents/Zotero/storage/NLTZCYI8/Cohen et al_2014_Quantifying the Reconfiguration of Intrinsic Networks during Working Memory.pdf;/Users/morteza/Documents/Zotero/storage/KLN4UBPZ/article.html}
}

@incollection{cohen2017,
  title = {Cognitive {{Control}}},
  booktitle = {The {{Wiley Handbook}} of {{Cognitive Control}}},
  author = {Cohen, Jonathan D.},
  year = {2017},
  pages = {1--28},
  publisher = {{John Wiley \& Sons, Ltd}},
  doi = {10.1002/9781118920497.ch1},
  abstract = {This chapter reviews the original formulations of the distinction between controlled and automatic processing. This review is intended to be useful in at least two ways: as a guide to the central constructs and most pressing issues concerning cognitive control for those who are new to this area of research; and as an inventory of challenges that a satisfying account of cognitive control must address for those who are familiar with the area. The chapter discusses the issues into three broad categories: core, defining features of cognitive control; the relationship of cognitive control to other closely related constructs in psychology; and ways in which the understanding of cognitive control may be informed by theoretical approaches that have proved valuable in other areas such as computer science. The construct of cognitive control has been inextricably intertwined with several others in the psychological literature. Several of these stand out: executive function, intelligence, volition, attention, working memory, and inhibition.},
  chapter = {1},
  isbn = {978-1-118-92049-7},
  langid = {english},
  keywords = {automatic processing,cognitive control,competitive inhibition,executive function,long-term memory,motivational factors,prospective memory,psychological constructs,working memory},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781118920497.ch1},
  file = {/Users/morteza/Documents/Zotero/storage/H93V83YG/9781118920497.html}
}

@article{cohen2022,
  title = {Recent {{Advances}} at the {{Interface}} of {{Neuroscience}} and {{Artificial Neural Networks}}},
  author = {Cohen, Yarden and Engel, Tatiana A. and Langdon, Christopher and Lindsay, Grace W. and Ott, Torben and Peters, Megan A. K. and Shine, James M. and {Breton-Provencher}, Vincent and Ramaswamy, Srikanth},
  year = {2022},
  month = nov,
  journal = {Journal of Neuroscience},
  volume = {42},
  number = {45},
  pages = {8514--8523},
  issn = {0270-6474, 1529-2401},
  doi = {10.1523/JNEUROSCI.1503-22.2022},
  abstract = {Biological neural networks adapt and learn in diverse behavioral contexts. Artificial neural networks (ANNs) have exploited biological properties to solve complex problems. However, despite their effectiveness for specific tasks, ANNs are yet to realize the flexibility and adaptability of biological cognition. This review highlights recent advances in computational and experimental research to advance our understanding of biological and artificial intelligence. In particular, we discuss critical mechanisms from the cellular, systems, and cognitive neuroscience fields that have contributed to refining the architecture and training algorithms of ANNs. Additionally, we discuss how recent work used ANNs to understand complex neuronal correlates of cognition and to process high throughput behavioral data.},
  copyright = {Copyright \textcopyright{} 2022 the authors. SfN exclusive license.},
  langid = {english},
  pmid = {36351830},
  keywords = {artificial neural networks,behavior,cognition,neuromodulators,plasticity,vision},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-12-08]}
}

@article{cole2013,
  title = {Multi-Task Connectivity Reveals Flexible Hubs for Adaptive Task Control},
  author = {Cole, Michael W and Reynolds, Jeremy R and Power, Jonathan D and Repovs, Grega and Anticevic, Alan and Braver, Todd S},
  year = {2013},
  month = sep,
  journal = {Nature Neuroscience},
  volume = {16},
  number = {9},
  pages = {1348--1355},
  issn = {1097-6256, 1546-1726},
  doi = {10.1038/nn.3470},
  langid = {english},
  annotation = {1205 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/7XU36SM6/Cole et al. - 2013 - Multi-task connectivity reveals flexible hubs for .pdf}
}

@incollection{colzato2021,
  title = {The {{Future}} of {{Cognitive Training}}},
  booktitle = {Cognitive {{Training}}},
  author = {Colzato, Lorenza S. and Hommel, Bernhard},
  editor = {Strobach, Tilo and Karbach, Julia},
  year = {2021},
  pages = {397--410},
  publisher = {{Springer International Publishing}},
  address = {{Cham}},
  doi = {10.1007/978-3-030-39292-5_27},
  isbn = {978-3-030-39291-8 978-3-030-39292-5},
  langid = {english},
  annotation = {00000}
}

@article{comstockjr1992,
  title = {The Multi-Attribute Task Battery for Human Operator Workload and Strategic Behavior Research},
  author = {Comstock Jr, J. Raymond and Arnegard, Ruth J.},
  year = {1992},
  annotation = {00350},
  file = {/Users/morteza/Documents/Zotero/storage/2W4SRYBJ/Comstock Jr and Arnegard - 1992 - The multi-attribute task battery for human operato.pdf;/Users/morteza/Documents/Zotero/storage/J3EH7CRJ/search.html}
}

@article{cools2016,
  title = {The Costs and Benefits of Brain Dopamine for Cognitive Control},
  author = {Cools, Roshan},
  year = {2016},
  month = sep,
  journal = {Wiley Interdisciplinary Reviews. Cognitive Science},
  volume = {7},
  number = {5},
  pages = {317--329},
  issn = {1939-5086},
  doi = {10.1002/wcs.1401},
  abstract = {Cognitive control helps us attain our goals by resisting distraction and temptations. Dopaminergic drugs are well known to enhance cognitive control. However, there is great variability in the effects of dopaminergic drugs across different contexts, with beneficial effects on some tasks but detrimental effects on other tasks. The mechanisms underlying this variability across cognitive task demands remain unclear. I aim to elucidate this across-task variability in dopaminergic drug efficacy by going beyond classic models that emphasize the importance of dopamine in the prefrontal cortex for cognitive control and working memory. To this end, I build on recent advances in cognitive neuroscience that highlight a role for dopamine in cost-benefit decision making. Specifically, I reconceptualize cognitive control as involving not just prefrontal dopamine but also modulation of cost-benefit decision making by striatal dopamine. This approach will help us understand why we sometimes fail to (choose to) exert cognitive control while also identifying mechanistic factors that predict dopaminergic drug effects on cognitive control. WIREs Cogn Sci 2016, 7:317-329. doi: 10.1002/wcs.1401 For further resources related to this article, please visit the WIREs website.},
  langid = {english},
  pmid = {27507774},
  keywords = {Animals,Corpus Striatum,Decision Making,Dopamine,Dopamine Agents,Executive Function,Humans,Motivation,Prefrontal Cortex},
  annotation = {70 citations (Semantic Scholar/DOI) [2022-10-27]}
}

@article{corbetta2002,
  ids = {corbetta2002a,corbetta2002b},
  title = {Control of Goal-Directed and Stimulus-Driven Attention in the Brain},
  author = {Corbetta, Maurizio and Shulman, Gordon L.},
  year = {2002},
  month = mar,
  journal = {Nature Reviews Neuroscience},
  volume = {3},
  number = {3},
  pages = {201--215},
  issn = {1471-003X, 1471-0048},
  doi = {10.1038/nrn755},
  langid = {english},
  annotation = {9985 citations (Semantic Scholar/DOI) [2022-12-06] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/87I86RF7/Corbetta_Shulman_2002_Control of goal-directed and stimulus-driven attention in the brain.pdf}
}

@article{corbetta2008,
  title = {The {{Reorienting System}} of the {{Human Brain}}: {{From Environment}} to {{Theory}} of {{Mind}}},
  shorttitle = {The {{Reorienting System}} of the {{Human Brain}}},
  author = {Corbetta, Maurizio and Patel, Gaurav and Shulman, Gordon L.},
  year = {2008},
  month = may,
  journal = {Neuron},
  volume = {58},
  number = {3},
  pages = {306--324},
  issn = {08966273},
  doi = {10.1016/j.neuron.2008.04.017},
  langid = {english},
  annotation = {3173 citations (Semantic Scholar/DOI) [2022-12-11] 02962}
}

@book{cormen2022,
  title = {Introduction to Algorithms},
  author = {Cormen, Thomas H. and Leiserson, Charles Eric and Rivest, Ronald Linn and Stein, Clifford},
  year = {2022},
  edition = {Fourth edition},
  publisher = {{The MIT Press}},
  address = {{Cambridge, Massachusetts London, England}},
  abstract = {"The leading introductory textbook and reference on algorithms"--},
  isbn = {978-0-262-04630-5},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/3G592MBJ/Cormen et al. - 2022 - Introduction to algorithms.pdf;/Users/morteza/Documents/Zotero/storage/HN2WHDM6/Cormen et al. - 2022 - Introduction to algorithms.pdf;/Users/morteza/Documents/Zotero/storage/QPD94MDK/Cormen et al. - 2022 - Introduction to algorithms.pdf;/Users/morteza/Documents/Zotero/storage/S8UFTB6W/Cormen et al. - 2022 - Introduction to algorithms.pdf}
}

@article{costa2019,
  title = {Virtual {{Reality-Based Exercise}} with {{Exergames}} as {{Medicine}} in {{Different Contexts}}: {{A Short Review}}},
  shorttitle = {Virtual {{Reality-Based Exercise}} with {{Exergames}} as {{Medicine}} in {{Different Contexts}}},
  author = {Costa, Marcos T{\'u}lio Silva and Vieira, Lanna Pinheiro and Barbosa, Elizabete de Oliveira and Mendes Oliveira, Luciana and Maillot, Pauline and Ottero Vaghetti, C{\'e}sar Augusto and Giovani Carta, Mauro and Machado, S{\'e}rgio and {Gatica-Rojas}, Valeska and {Monteiro-Junior}, Renato Sobral},
  year = {2019},
  month = jan,
  journal = {Clinical Practice \& Epidemiology in Mental Health},
  volume = {15},
  number = {1},
  pages = {15--20},
  issn = {1745-0179},
  doi = {10.2174/1745017901915010015},
  langid = {english},
  annotation = {40 citations (Semantic Scholar/DOI) [2022-12-11]},
  file = {/Users/morteza/Documents/Zotero/storage/TFV24YEZ/Costa et al. - 2019 - Virtual Reality-Based Exercise with Exergames as M.pdf}
}

@inproceedings{crosby2020,
  title = {The Animal-{{AI}} Testbed and Competition},
  booktitle = {Proceedings of the {{NeurIPS}} 2019 Competition and Demonstration Track},
  author = {Crosby, Matthew and Beyret, Benjamin and Shanahan, Murray and {Hern{\'a}ndez-Orallo}, Jos{\'e} and Cheke, Lucy and Halina, Marta},
  editor = {Escalante, Hugo Jair and Hadsell, Raia},
  year = {2020},
  month = dec,
  series = {Proceedings of Machine Learning Research},
  volume = {123},
  pages = {164--176},
  publisher = {{PMLR}}
}

@article{dadi2019,
  title = {Benchmarking Functional Connectome-Based Predictive Models for Resting-State {{fMRI}}},
  author = {Dadi, Kamalaker and Rahim, Mehdi and Abraham, Alexandre and Chyzhyk, Darya and Milham, Michael and Thirion, Bertrand and Varoquaux, Ga{\"e}l},
  year = {2019},
  month = may,
  journal = {NeuroImage},
  volume = {192},
  pages = {115--134},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2019.02.062},
  langid = {english},
  annotation = {174 citations (Semantic Scholar/DOI) [2022-12-10]},
  file = {/Users/morteza/Documents/Zotero/storage/ED2QG4CI/Dadi et al. - 2019 - Benchmarking functional connectome-based predictiv.pdf}
}

@article{dadi2020,
  title = {Fine-Grain Atlases of Functional Modes for {{fMRI}} Analysis},
  author = {Dadi, Kamalaker and Varoquaux, Ga{\"e}l and {Machlouzarides-Shalit}, Antonia and Gorgolewski, Krzysztof J. and Wassermann, Demian and Thirion, Bertrand and Mensch, Arthur},
  year = {2020},
  month = nov,
  journal = {NeuroImage},
  volume = {221},
  pages = {117126},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2020.117126},
  langid = {english},
  annotation = {31 citations (Semantic Scholar/DOI) [2022-12-06]},
  file = {/Users/morteza/Documents/Zotero/storage/IPW7VVSZ/Dadi et al. - 2020 - Fine-grain atlases of functional modes for fMRI an.pdf}
}

@article{dale2017,
  title = {The {{Changing Face}} of {{Video Games}} and {{Video Gamers}}: {{Future Directions}} in the {{Scientific Study}} of {{Video Game Play}} and {{Cognitive Performance}}},
  shorttitle = {The {{Changing Face}} of {{Video Games}} and {{Video Gamers}}},
  author = {Dale, Gillian and Shawn Green, C.},
  year = {2017},
  month = sep,
  journal = {Journal of Cognitive Enhancement},
  volume = {1},
  number = {3},
  pages = {280--294},
  issn = {2509-3290, 2509-3304},
  doi = {10.1007/s41465-017-0015-6},
  langid = {english},
  annotation = {60 citations (Semantic Scholar/DOI) [2022-12-11] 00061}
}

@article{dale2017a,
  title = {Associations {{Between Avid Action}} and {{Real-Time Strategy Game Play}} and {{Cognitive Performance}}: A {{Pilot Study}}},
  shorttitle = {Associations {{Between Avid Action}} and {{Real-Time Strategy Game Play}} and {{Cognitive Performance}}},
  author = {Dale, Gillian and Green, C. Shawn},
  year = {2017},
  month = sep,
  journal = {Journal of Cognitive Enhancement},
  volume = {1},
  number = {3},
  pages = {295--317},
  issn = {2509-3290, 2509-3304},
  doi = {10.1007/s41465-017-0021-8},
  langid = {english},
  annotation = {22 citations (Semantic Scholar/DOI) [2022-12-11] 00005}
}

@article{dale2020,
  title = {A New Look at the Cognitive Neuroscience of Video Game Play},
  author = {Dale, Gillian and Joessel, Augustin and Bavelier, Daphne and Green, C. Shawn},
  year = {2020},
  journal = {Annals of the New York Academy of Sciences},
  volume = {1464},
  number = {1},
  pages = {192--203},
  issn = {1749-6632},
  doi = {10.1111/nyas.14295},
  abstract = {A growing body of literature has investigated the effects of playing video games on brain function and behavior. One key takeaway from this literature has been that not all entertainment video games are created equal with respect to their effects on cognitive functioning. The majority of the research to date has contrasted the cognitive impact of playing first- or third-person shooter games (together dubbed ``action video games'') against the effects of playing other game types. Indeed, when the research began in the late 1990s, action video games placed a load upon the perceptual, attentional, and cognitive systems in a manner not seen in other video games. However, the video game industry has shifted dramatically over the intervening years. In particular, first- and third-person shooter games are no longer unique in the extent to which they load upon cognitive abilities. Instead, a host of other game genres appear to place similar degrees of load upon these systems. This state of affairs calls for a paradigm shift in the way that the cognitive neuroscience field examines the impact of video game play on cognitive skills and their neural mediators\textemdash a shift that is only just now slowly occurring.},
  langid = {english},
  keywords = {action video games,behavioral intervention studies,cognitive enhancement,video games},
  annotation = {34 citations (Semantic Scholar/DOI) [2022-12-06] \_eprint: https://nyaspubs.onlinelibrary.wiley.com/doi/pdf/10.1111/nyas.14295},
  file = {/Users/morteza/Documents/Zotero/storage/EBHIDGYY/Dale et al_2020_A new look at the cognitive neuroscience of video game play.pdf;/Users/morteza/Documents/Zotero/storage/3JYRSWSX/nyas.html}
}

@article{davelaar2011,
  title = {Processes {{Versus Representations}}: {{Cognitive Control}} as {{Emergent}}, {{Yet Componential}}},
  shorttitle = {Processes {{Versus Representations}}},
  author = {Davelaar, Eddy J.},
  year = {2011},
  journal = {Topics in Cognitive Science},
  volume = {3},
  number = {2},
  pages = {247--252},
  issn = {1756-8765},
  doi = {10.1111/j.1756-8765.2011.01138.x},
  abstract = {In this commentary, I focus on the difference between processes and representations and how this distinction relates to the question of what is controlled. Despite some views that task switching is a prototypical control process, the analysis concludes that task switching depends on the task goal representation and that control processes are there to prevent goal representations from disintegrating. Over time, these processes become obsolete, leaving behind a representation that automatically controls task performance. The distinction between processes and representations relates to practice effects and automaticity and sheds light on what is meant by the phrase ``automatic control.''},
  langid = {english},
  keywords = {Automaticity,Cognitive control,Goal neglect,Representation,Representational acuity,Task difficulty},
  annotation = {10 citations (Semantic Scholar/DOI) [2022-10-27] \_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1756-8765.2011.01138.x},
  file = {/Users/morteza/Documents/Zotero/storage/RYH96LV3/Davelaar_2011_Processes Versus Representations.pdf;/Users/morteza/Documents/Zotero/storage/3H9FCQ9G/j.1756-8765.2011.01138.html}
}

@article{daw2011,
  title = {Model-{{Based Influences}} on {{Humans}}' {{Choices}} and {{Striatal Prediction Errors}}},
  author = {Daw, Nathaniel~D. and Gershman, Samuel~J. and Seymour, Ben and Dayan, Peter and Dolan, Raymond~J.},
  year = {2011},
  month = mar,
  journal = {Neuron},
  volume = {69},
  number = {6},
  pages = {1204--1215},
  issn = {08966273},
  doi = {10.1016/j.neuron.2011.02.027},
  abstract = {The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which modelbased and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and modelbased predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decisionmaking.},
  langid = {english},
  annotation = {1291 citations (Semantic Scholar/DOI) [2022-12-01]},
  file = {/Users/morteza/Documents/Zotero/storage/HF9CLGUS/Daw et al_2011_Model-Based Influences on Humans' Choices and Striatal Prediction Errors.pdf}
}

@article{deboeck2019,
  title = {An {{Overview}} of {{Models}} for {{Response Times}} and {{Processes}} in {{Cognitive Tests}}},
  author = {De Boeck, Paul and Jeon, Minjeong},
  year = {2019},
  journal = {Frontiers in Psychology},
  volume = {10},
  issn = {1664-1078},
  abstract = {Response times (RTs) are a natural kind of data to investigate cognitive processes underlying cognitive test performance. We give an overview of modeling approaches and of findings obtained with these approaches. Four types of models are discussed: response time models (RT as the sole dependent variable), joint models (RT together with other variables as dependent variable), local dependency models (with remaining dependencies between RT and accuracy), and response time as covariate models (RT as independent variable). The evidence from these approaches is often not very informative about the specific kind of processes (other than problem solving, information accumulation, and rapid guessing), but the findings do suggest dual processing: automated processing (e.g., knowledge retrieval) vs. controlled processing (e.g., sequential reasoning steps), and alternative explanations for the same results exist. While it seems well-possible to differentiate rapid guessing from normal problem solving (which can be based on automated or controlled processing), further decompositions of response times are rarely made, although possible based on some of model approaches.},
  file = {/Users/morteza/Documents/Zotero/storage/3QUWA9Z7/De Boeck_Jeon_2019_An Overview of Models for Response Times and Processes in Cognitive Tests.pdf}
}

@article{delisi2002,
  title = {Improving Children's Mental Rotation Accuracy with Computer Game Playing},
  author = {De Lisi, Richard and Wolford, Jennifer L.},
  year = {2002},
  month = sep,
  journal = {The Journal of Genetic Psychology},
  volume = {163},
  number = {3},
  pages = {272--282},
  issn = {0022-1325},
  doi = {10.1080/00221320209598683},
  abstract = {The authors investigated the relation between mental rotation (MR) and computer game-playing experience. Third grade boys (n = 24) and girls (n = 23) completed a 2-dimensional MR test before and after playing computer games (during 11 separate 30-min sessions), which either involved the use of MR skills (the experimental group) or did not involve the use of MR skills (the control group). The experimental group outperformed the control group on the MR posttest but not on the pretest. Boys outperformed girls on the pretest but not on the posttest. Children whose initial MR performance was low improved after playing computer games that entailed MR skills. The findings imply that computer-based instructional activities can be used in schools to enhance children's spatial abilities.},
  langid = {english},
  pmid = {12230149},
  keywords = {Analysis of Variance,Child,Cognition,Female,Humans,Male,New Jersey,Practice (Psychology),Rotation,Sex Factors,Space Perception,Video Games},
  annotation = {326 citations (Semantic Scholar/DOI) [2022-12-11] 00386}
}

@article{diamond2007,
  title = {{{THE EARLY YEARS}}: {{Preschool Program Improves Cognitive Control}}},
  shorttitle = {{{THE EARLY YEARS}}},
  author = {Diamond, A. and Barnett, W. S. and Thomas, J. and Munro, S.},
  year = {2007},
  month = nov,
  journal = {Science},
  volume = {318},
  number = {5855},
  pages = {1387--1388},
  issn = {0036-8075, 1095-9203},
  doi = {10.1126/science.1151148},
  langid = {english},
  annotation = {1812 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/KVSWDS7G/diamond2007.pdf}
}

@article{diamond2013,
  ids = {diamond2012},
  title = {Executive {{Functions}}},
  author = {Diamond, Adele},
  year = {2013},
  month = jan,
  journal = {Annual Review of Psychology},
  volume = {64},
  number = {1},
  pages = {135--168},
  issn = {0066-4308, 1545-2085},
  doi = {10.1146/annurev-psych-113011-143750},
  abstract = {Executive functions (EFs) make possible mentally playing with ideas; taking the time to think before acting; meeting novel, unanticipated challenges; resisting temptations; and staying focused. Core EFs are inhibition [response inhibition (self-control\textemdash resisting temptations and resisting acting impulsively) and interference control (selective attention and cognitive inhibition)], working memory, and cognitive flexibility (including creatively thinking ``outside the box,'' seeing anything from different perspectives, and quickly and flexibly adapting to changed circumstances). The developmental progression and representative measures of each are discussed. Controversies are addressed (e.g., the relation between EFs and fluid intelligence, self-regulation, executive attention, and effortful control, and the relation between working memory and inhibition and attention). The importance of social, emotional, and physical health for cognitive health is discussed because stress, lack of sleep, loneliness, or lack of exercise each impair EFs. That EFs are trainable and can be improved with practice is addressed, including diverse methods tried thus far.},
  langid = {english},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2012/Diamond\%202012.pdf},
  pmcid = {PMC4084861},
  pmid = {23020641},
  keywords = {Executive Functions},
  file = {/Users/morteza/Documents/Zotero/storage/BSQ6UQUE/false}
}

@inbook{diamond2019,
  title = {Review of the {{Evidence}} on, and {{Fundamental Questions About}}, {{Efforts}} to {{Improve Executive Functions}}, {{Including Working Memory}}},
  booktitle = {Cognitive and {{Working Memory Training}}},
  author = {Diamond, Adele and Ling, Daphne S.},
  year = {2019},
  month = dec,
  pages = {143--431},
  publisher = {{Oxford University Press}},
  doi = {10.1093/oso/9780199974467.003.0008},
  abstract = {This systematic review of executive function (EF) interventions is the largest such review thus far, including 179 studies from all over the world, reported in 193 papers. It covers all the ways that have been tried to improve EFs, including computerized and noncomputerized cognitive training, neurofeedback, school programs, physical activities, mindfulness practices, and miscellaneous approaches (e.g., drama and Experience Corps), at all ages. A little studied approach\textemdash mindfulness practices involving movement (such as taekwondo and t'ai chi)\textemdash shows the best results for improving EFs. Promising school programs are second. Both approaches show better results than any cognitive training. Third best at improving EFs is noncomputerized cognitive training. Perhaps these three approaches show better results than computerized training because they involve more in-person trainer-trainee interaction. The best-performing computerized cognitive-training method for improving EFs is Cogmed\textregistered. Support was lacking for claims that N-back training improves fluid intelligence. Resistance training and ``plain'' aerobic-exercise interventions (e.g., running or walking) show the least evidence of benefit to EFs of all methods. Results for aerobic exercise with more cognitive or motor-skill challenges are only slightly better. This probably reflects how physical-activity interventions have been structured, rather than that physical activity does not benefit EFs. For any intervention, trainers' ability to make the training activity enjoyable and to communicate their unwavering faith in participants and the program plus the activity being personally meaningful and relevant, inspiring commitment and emotional investment in participants to the activity and to one another is probably what is most important.},
  collaborator = {Diamond, Adele and Ling, Daphne S.},
  isbn = {978-0-19-997446-7 978-0-19-007617-7},
  langid = {english}
}

@article{diamond2019a,
  title = {Cognitive and Working Memory Training},
  author = {Diamond, Adele and Ling, Daphne S},
  year = {2019},
  pages = {143--431},
  doi = {10.1093/oso/9780199974467.003.0008},
  abstract = {This systematic review of executive function (EF) interventions is the largest such review thus far, including 179 studies from all over the world, reported in 193 papers. It covers all the ways that have been tried to improve EFs, including computerized and noncomputerized cognitive training, neurofeedback, school programs, physical activities, mindfulness practices, and miscellaneous approaches (e.g., drama and Experience Corps), at all ages. A little studied approach\textemdash mindfulness practices involving movement (such as taekwondo and t'ai chi)\textemdash shows the best results for improving EFs. Promising school programs are second. Both approaches show better results than any cognitive training. Third best at improving EFs is noncomputerized cognitive training. Perhaps these three approaches show better results than computerized training because they involve more in-person trainer-trainee interaction. The best-performing computerized cognitive-training method for improving EFs is Cogmed\textregistered. Support was lacking for claims that N-back training improves fluid intelligence. Resistance training and ``plain'' aerobic-exercise interventions (e.g., running or walking) show the least evidence of benefit to EFs of all methods. Results for aerobic exercise with more cognitive or motor-skill challenges are only slightly better. This probably reflects how physical-activity interventions have been structured, rather than that physical activity does not benefit EFs. For any intervention, trainers' ability to make the training activity enjoyable and to communicate their unwavering faith in participants and the program plus the activity being personally meaningful and relevant, inspiring commitment and emotional investment in participants to the activity and to one another is probably what is most important.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2019/Diamond\%202019.pdf},
  annotation = {00004}
}

@article{dieng2020,
  title = {Topic {{Modeling}} in {{Embedding Spaces}}},
  author = {Dieng, Adji B. and Ruiz, Francisco J. R. and Blei, David M.},
  year = {2020},
  month = dec,
  journal = {Transactions of the Association for Computational Linguistics},
  volume = {8},
  pages = {439--453},
  issn = {2307-387X},
  doi = {10.1162/tacl_a_00325},
  abstract = {Topic modeling analyzes documents to learn meaningful patterns of words. However, existing topic models fail to learn interpretable topics when working with large and heavy-tailed vocabularies. To this end, we develop the embedded topic model (etm), a generative model of documents that marries traditional topic models with word embeddings. More specifically, the etm models each word with a categorical distribution whose natural parameter is the inner product between the word's embedding and an embedding of its assigned topic. To fit the etm, we develop an efficient amortized variational inference algorithm. The etm discovers interpretable topics even with large vocabularies that include rare words and stop words. It outperforms existing document models, such as latent Dirichlet allocation, in terms of both topic quality and predictive performance.},
  langid = {english},
  annotation = {208 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/XFWWF36K/Dieng et al. - 2020 - Topic Modeling in Embedding Spaces.pdf}
}

@article{doebel2020,
  title = {Rethinking {{Executive Function}} and {{Its Development}}},
  author = {Doebel, Sabine},
  year = {2020},
  month = jul,
  journal = {Perspectives on Psychological Science},
  volume = {15},
  number = {4},
  pages = {942--956},
  issn = {1745-6916, 1745-6924},
  doi = {10.1177/1745691620904771},
  abstract = {Research on executive function in early childhood has flourished in recent years. Much of this work is premised on a view of development of executive function as the emergence of a set of domain-general component processes (e.g., working memory updating, inhibitory control, shifting). This view has shaped how we think about relations between executive function and other aspects of development, the role of the environment in executive-function development, and how best to improve executive function in children who struggle with it. However, there are conceptual and empirical reasons to doubt that executive function should be defined in this way. I argue that the development of executive function is better understood as the emergence of skills in using control in the service of specific goals. Such goals activate and are influenced by mental content such as knowledge, beliefs, norms, values, and preferences that are acquired with development and are important to consider in understanding children's performance on measures of executive function. This account better explains empirical findings than the component-process view; leads to specific, testable hypotheses; and has implications for theory, measurement, and interventions.},
  langid = {english},
  keywords = {Executive Functions},
  annotation = {78 citations (Semantic Scholar/DOI) [2022-12-09]}
}

@article{dolan2013,
  title = {Goals and {{Habits}} in the {{Brain}}},
  author = {Dolan, Ray~J. and Dayan, Peter},
  year = {2013},
  month = oct,
  journal = {Neuron},
  volume = {80},
  number = {2},
  pages = {312--325},
  issn = {08966273},
  doi = {10.1016/j.neuron.2013.09.007},
  langid = {english},
  annotation = {724 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/JFDXINKJ/Dolan and Dayan - 2013 - Goals and Habits in the Brain.pdf}
}

@article{dong2017,
  title = {Metapath2vec: {{Scalable}} Representation Learning for Heterogeneous Networks},
  author = {Dong, Yuxiao and Chawla, Nitesh V and Swami, Ananthram},
  year = {2017},
  journal = {Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  doi = {10.1145/3097983.3098036},
  abstract = {We study the problem of representation learning in heterogeneous networks. Its unique challenges come from the existence of multiple types of nodes and links, which limit the feasibility of the conventional network embedding techniques. We develop two scalable representation learning models, namely metapath2vec and metapath2vec++. The metapath2vec model formalizes meta-path-based random walks to construct the heterogeneous neighborhood of a node and then leverages a heterogeneous skip-gram model to perform node embeddings. The metapath2vec++ model further enables the simultaneous modeling of structural and semantic correlations in heterogeneous networks. Extensive experiments show that metapath2vec and metapath2vec++ are able to not only outperform state-of-the-art embedding models in various heterogeneous network mining tasks, such as node classification, clustering, and similarity search, but also discern the structural and semantic correlations between diverse network objects.},
  annotation = {1396 citations (Semantic Scholar/DOI) [2022-12-09]}
}

@article{dosenbach2007,
  title = {Distinct Brain Networks for Adaptive and Stable Task Control in Humans},
  author = {Dosenbach, Nico U. F. and Fair, Damien A. and Miezin, Francis M. and Cohen, Alexander L. and Wenger, Kristin K. and Dosenbach, Ronny A. T. and Fox, Michael D. and Snyder, Abraham Z. and Vincent, Justin L. and Raichle, Marcus E. and Schlaggar, Bradley L. and Petersen, Steven E.},
  year = {2007},
  month = jun,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {104},
  number = {26},
  pages = {11073--11078},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.0704320104},
  abstract = {Control regions in the brain are thought to provide signals that configure the brain's moment-to-moment information processing. Previously, we identified regions that carried signals related to task-control initiation, maintenance, and adjustment. Here we characterize the interactions of these regions by applying graph theory to resting state functional connectivity MRI data. In contrast to previous, more unitary models of control, this approach suggests the presence of two distinct task-control networks. A frontoparietal network included the dorsolateral prefrontal cortex and intraparietal sulcus. This network emphasized start-cue and error-related activity and may initiate and adapt control on a trial-by-trial basis. The second network included dorsal anterior cingulate/medial superior frontal cortex, anterior insula/frontal operculum, and anterior prefrontal cortex. Among other signals, these regions showed activity sustained across the entire task epoch, suggesting that this network may control goal-directed behavior through the stable maintenance of task sets. These two independent networks appear to operate on different time scales and affect downstream processing via dissociable mechanisms.},
  langid = {english},
  annotation = {2250 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/96UHCDEX/Dosenbach et al. - 2007 - Distinct brain networks for adaptive and stable ta.pdf}
}

@article{dosenbach2008,
  title = {A Dual-Networks Architecture of Top-down Control},
  author = {Dosenbach, Nico U.F. and Fair, Damien A. and Cohen, Alexander L. and Schlaggar, Bradley L. and Petersen, Steven E.},
  year = {2008},
  month = mar,
  journal = {Trends in Cognitive Sciences},
  volume = {12},
  number = {3},
  pages = {99--105},
  issn = {13646613},
  doi = {10.1016/j.tics.2008.01.001},
  langid = {english},
  annotation = {1508 citations (Semantic Scholar/DOI) [2022-12-11] 01341},
  file = {/Users/morteza/Documents/Zotero/storage/ATLFRC6U/Dosenbach et al. - 2008 - A dual-networks architecture of top-down control.pdf}
}

@article{dosenbach2010,
  title = {Prediction of {{Individual Brain Maturity Using fMRI}}},
  author = {Dosenbach, Nico U. F. and Nardos, Binyam and Cohen, Alexander L. and Fair, Damien A. and Power, Jonathan D. and Church, Jessica A. and Nelson, Steven M. and Wig, Gagan S. and Vogel, Alecia C. and {Lessov-Schlaggar}, Christina N. and Barnes, Kelly Anne and Dubis, Joseph W. and Feczko, Eric and Coalson, Rebecca S. and Pruett, John R. and Barch, Deanna M. and Petersen, Steven E. and Schlaggar, Bradley L.},
  year = {2010},
  month = sep,
  journal = {Science},
  volume = {329},
  number = {5997},
  pages = {1358--1361},
  issn = {0036-8075, 1095-9203},
  doi = {10.1126/science.1194144},
  abstract = {Connectivity Map of the Brain                            The growing appreciation that clinically abnormal behaviors in children and adolescents may be influenced or perhaps even initiated by developmental miscues has stoked an interest in mapping normal human brain maturation. Several groups have documented changes in gray and white matter using structural and functional magnetic resonance imaging (fMRI) in cross-sectional and longitudinal studies.                                Dosenbach                 et al.                              (p.               1358               ) developed an index of resting-state functional connectivity (that is, how tightly neuronal activities in distinct brain regions are correlated while the subject is at rest or even asleep) from analyses of three independent data sets (each based on fMRI scans of 150 to 200 individuals from ages 6 to 35 years old). Long-range connections increased with age and short-range connections decreased, indicating that networks become sparser and sharper with brain maturation.                        ,              Multivariate pattern analysis of 5-minute brain scans provides a measure of brain maturity.           ,              Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55\% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.},
  langid = {english},
  annotation = {1726 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/PTYI5IIJ/Dosenbach et al. - 2010 - Prediction of Individual Brain Maturity Using fMRI.pdf}
}

@article{draganski2008,
  title = {Training-Induced Structural Changes in the Adult Human Brain},
  author = {Draganski, B and May, A},
  year = {2008},
  month = sep,
  journal = {Behavioural brain research},
  volume = {192},
  number = {1},
  pages = {137--142},
  annotation = {00000}
}

@article{dye2009,
  title = {Increasing {{Speed}} of {{Processing With Action Video Games}}},
  author = {Dye, Matthew W.G. and Green, C. Shawn and Bavelier, Daphne},
  year = {2009},
  month = dec,
  journal = {Current Directions in Psychological Science},
  volume = {18},
  number = {6},
  pages = {321--326},
  issn = {0963-7214, 1467-8721},
  doi = {10.1111/j.1467-8721.2009.01660.x},
  langid = {english},
  annotation = {439 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/P95THFXM/dye2009.pdf}
}

@article{eich2020,
  title = {Towards an Ontology of Cognitive Processes and Their Neural Substrates: {{A}} Structural Equation Modeling Approach},
  author = {Eich, Teal and Parker, David and Gazes, Yunglin and Razlighi, Qolamreza and Habeck, Christian and Stern, Yaakov},
  year = {2020},
  journal = {PLOS ONE},
  volume = {15},
  number = {2},
  pages = {e0228167},
  doi = {10.1371/journal.pone.0228167},
  abstract = {A key challenge in the field of cognitive neuroscience is to identify discriminable cognitive functions, and then map these functions to brain activity. In the current study, we set out to explore the relationships between performance arising from different cognitive tasks thought to tap different domains of cognition, and then to test whether these distinct latent cognitive abilities also are subserved by corresponding ``latent'' brain substrates. To this end, we tested a large sample of adults under the age of 40 on twelve cognitive tasks as they underwent fMRI scanning. Exploratory factor analysis revealed 4-factor model, dissociating tasks into processes corresponding to episodic memory retrieval, reasoning, speed of processing and vocabulary. An analysis of the topographic covariance patterns of the BOLD-response acquired during each task similarity also converged on four neural networks that corresponded to the 4 latent factors. These results suggest that distinct ontologies of cognition are subserved by corresponding distinct neural networks.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2020/Eich\%202020.pdf},
  pmid = {32040518},
  keywords = {EFO},
  annotation = {00005}
}

@article{eichenbaum2017,
  title = {The Role of the Hippocampus in Navigation Is Memory},
  author = {Eichenbaum, Howard},
  year = {2017},
  month = apr,
  journal = {Journal of Neurophysiology},
  volume = {117},
  number = {4},
  pages = {1785--1796},
  issn = {0022-3077, 1522-1598},
  doi = {10.1152/jn.00005.2017},
  langid = {english},
  annotation = {178 citations (Semantic Scholar/DOI) [2022-12-11] 00038}
}

@article{eisenberg2019,
  ids = {eisenberg2019a},
  title = {Uncovering the Structure of Self-Regulation through Data-Driven Ontology Discovery},
  author = {Eisenberg, Ian W. and Bissett, Patrick G. and Zeynep Enkavi, A. and Li, Jamie and MacKinnon, David P. and Marsch, Lisa A. and Poldrack, Russell A.},
  year = {2019},
  month = dec,
  journal = {Nature Communications},
  volume = {10},
  number = {1},
  pages = {2319},
  issn = {2041-1723},
  doi = {10.1038/s41467-019-10301-1},
  langid = {english},
  annotation = {155 citations (Semantic Scholar/DOI) [2022-11-29]},
  file = {/Users/morteza/Documents/Zotero/storage/86WFCBNI/Eisenberg et al_2019_Uncovering the structure of self-regulation through data-driven ontology.pdf}
}

@article{engelhard2010,
  title = {The Impact of Taxing Working Memory on Negative and Positive Memories},
  author = {Engelhard, Iris M. and {van Uijen}, Sophie L. and {van den Hout}, Marcel A.},
  year = {2010},
  journal = {European Journal of Psychotraumatology},
  volume = {1},
  issn = {2000-8066},
  doi = {10.3402/ejpt.v1i0.5623},
  abstract = {BACKGROUND: Earlier studies have shown that horizontal eye movement (EM) during retrieval of a negative memory reduces its vividness and emotionality. This may be due to both tasks competing for working memory (WM) resources. This study examined whether playing the computer game "Tetris" also blurs memory. METHOD: PARTICIPANTS RECALLED NEGATIVE AND POSITIVE MEMORIES IN THREE CONDITIONS: recall only, recall with concurrent EM, and recall with playing Tetris. Before and after these conditions, vividness, emotionality, and physiological startle responses during recall were measured. RESULTS: A reaction time task showed that EM and Tetris draw on WM, compared to no dual-task. Compared to recall only, EM and Tetris both decreased reported emotionality and startle responses. CONCLUSIONS: The effects of EM and Tetris did not differ, even though the tasks differed in the degree of taxing WM. This suggests that taxing WM and its effects on emotional memories may not be linearly related. Potential clinical implications are discussed.},
  langid = {english},
  pmcid = {PMC3402003},
  pmid = {22893797},
  keywords = {EMDR,Intrusive memory,PTSD,working memory},
  annotation = {126 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/FQVU7VFY/Engelhard et al. - 2010 - The impact of taxing working memory on negative an.pdf}
}

@article{enkavi2019,
  title = {Large-Scale Analysis of Test\textendash Retest Reliabilities of Self-Regulation Measures},
  author = {Enkavi, A. Zeynep and Eisenberg, Ian W. and Bissett, Patrick G. and Mazza, Gina L. and MacKinnon, David P. and Marsch, Lisa A. and Poldrack, Russell A.},
  year = {2019},
  journal = {Proceedings of the National Academy of Sciences},
  volume = {116},
  number = {12},
  issn = {0027-8424},
  abstract = {The ability to regulate behavior in service of long-term goals is a widely studied psychological construct known as self-regulation. This wide interest is in part due to the putative relations between self-regulation and a range of real-world behaviors. Self-regulation is generally viewed as a trait, and individual differences are quantified using a diverse set of measures, including self-report surveys and behavioral tasks. Accurate characterization of individual differences requires measurement reliability, a property frequently characterized in self-report surveys, but rarely assessed in behavioral tasks. We remedy this gap by (i) providing a comprehensive literature review on an extensive set of self-regulation measures and (ii) empirically evaluating test\textendash retest reliability of this battery in a new sample. We find that dependent variables (DVs) from self-report surveys of self-regulation have high test\textendash retest reliability, while DVs derived from behavioral tasks do not. This holds both in the literature and in our sample, although the test\textendash retest reliability estimates in the literature are highly variable. We confirm that this is due to differences in between-subject variability. We also compare different types of task DVs (e.g., model parameters vs. raw response times) in their suitability as individual difference DVs, finding that certain model parameters are as stable as raw DVs. Our results provide greater psychometric footing for the study of self-regulation and provide guidance for future studies of individual differences in this domain.},
  pmid = {30842284},
  keywords = {Task Selection}
}

@article{erickson2010,
  title = {Striatal {{Volume Predicts Level}} of {{Video Game Skill Acquisition}}},
  author = {Erickson, K. I. and Boot, W. R. and Basak, C. and Neider, M. B. and Prakash, R. S. and Voss, M. W. and Graybiel, A. M. and Simons, D. J. and Fabiani, M. and Gratton, G. and Kramer, A. F.},
  year = {2010},
  month = nov,
  journal = {Cerebral Cortex},
  volume = {20},
  number = {11},
  pages = {2522--2530},
  issn = {1047-3211, 1460-2199},
  doi = {10.1093/cercor/bhp293},
  langid = {english},
  annotation = {138 citations (Semantic Scholar/DOI) [2022-12-11] 00127}
}

@article{eronen2021,
  ids = {eronen2021a},
  title = {The {{Theory Crisis}} in {{Psychology}}: {{How}} to {{Move Forward}}},
  shorttitle = {The {{Theory Crisis}} in {{Psychology}}},
  author = {Eronen, Markus I. and Bringmann, Laura F.},
  year = {2021},
  month = jul,
  journal = {Perspectives on Psychological Science},
  volume = {16},
  number = {4},
  pages = {779--788},
  issn = {1745-6916, 1745-6924},
  doi = {10.1177/1745691620970586},
  abstract = {Meehl argued in 1978 that theories in psychology come and go, with little cumulative progress. We believe that this assessment still holds, as also evidenced by increasingly common claims that psychology is facing a ``theory crisis'' and that psychologists should invest more in theory building. In this article, we argue that the root cause of the theory crisis is that developing good psychological theories is extremely difficult and that understanding the reasons why it is so difficult is crucial for moving forward in the theory crisis. We discuss three key reasons based on philosophy of science for why developing good psychological theories is so hard: the relative lack of robust phenomena that impose constraints on possible theories, problems of validity of psychological constructs, and obstacles to discovering causal relationships between psychological variables. We conclude with recommendations on how to move past the theory crisis.},
  langid = {english},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2021/Eronen\%202021.pdf},
  pmid = {33513314}
}

@article{esteban2017,
  title = {{{MRIQC}}: {{Advancing}} the Automatic Prediction of Image Quality in {{MRI}} from Unseen Sites},
  shorttitle = {{{MRIQC}}},
  author = {Esteban, Oscar and Birman, Daniel and Schaer, Marie and Koyejo, Oluwasanmi O. and Poldrack, Russell A. and Gorgolewski, Krzysztof J.},
  editor = {Bernhardt, Boris C},
  year = {2017},
  month = sep,
  journal = {PLOS ONE},
  volume = {12},
  number = {9},
  pages = {e0184661},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0184661},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/BCKDDYNS/Esteban et al. - 2017 - MRIQC Advancing the automatic prediction of image.pdf}
}

@article{esteban2019,
  title = {{{fMRIPrep}}: A Robust Preprocessing Pipeline for Functional {{MRI}}},
  shorttitle = {{{fMRIPrep}}},
  author = {Esteban, Oscar and Markiewicz, Christopher J. and Blair, Ross W. and Moodie, Craig A. and Isik, A. Ilkay and Erramuzpe, Asier and Kent, James D. and Goncalves, Mathias and DuPre, Elizabeth and Snyder, Madeleine and Oya, Hiroyuki and Ghosh, Satrajit S. and Wright, Jessey and Durnez, Joke and Poldrack, Russell A. and Gorgolewski, Krzysztof J.},
  year = {2019},
  month = jan,
  journal = {Nature Methods},
  volume = {16},
  number = {1},
  pages = {111--116},
  issn = {1548-7091, 1548-7105},
  doi = {10.1038/s41592-018-0235-4},
  langid = {english},
  annotation = {1092 citations (Semantic Scholar/DOI) [2022-12-07]},
  file = {/Users/morteza/Documents/Zotero/storage/AKPQAVZK/Esteban et al. - 2019 - fMRIPrep a robust preprocessing pipeline for func.pdf}
}

@article{etzel2022,
  title = {The {{Dual Mechanisms}} of {{Cognitive Control}} Dataset, a Theoretically-Guided within-Subject Task {{fMRI}} Battery},
  author = {Etzel, Joset A. and Brough, Rachel E. and Freund, Michael C. and Kizhner, Alexander and Lin, Yanli and Singh, Matthew F. and Tang, Rongxiang and Tay, Allison and Wang, Anxu and Braver, Todd S.},
  year = {2022},
  month = mar,
  journal = {Scientific Data},
  volume = {9},
  number = {1},
  pages = {114},
  issn = {2052-4463},
  doi = {10.1038/s41597-022-01226-4},
  abstract = {Cognitive control is a critical higher mental function, which is subject to considerable individual variation, and is impaired in a range of mental health disorders. We describe here the initial release of Dual Mechanisms of Cognitive Control (DMCC) project data, the DMCC55B dataset, with 55 healthy unrelated young adult participants. Each participant performed four well-established cognitive control tasks (AX-CPT, Cued Task-Switching, Sternberg Working Memory, and Stroop) while undergoing functional MRI scanning. The dataset includes a range of state and trait self-report questionnaires, as well as behavioural tasks assessing individual differences in cognitive ability. The DMCC project is on-going and features additional components (e.g., related participants, manipulations of cognitive control mode, resting state fMRI, longitudinal testing) that will be publicly released following study completion. This DMCC55B subset is released early with the aim of encouraging wider use and greater benefit to the scientific community. The DMCC55B dataset is suitable for benchmarking and methods exploration, as well as analyses of task performance and individual differences.},
  langid = {english},
  pmcid = {PMC8964804},
  pmid = {35351911},
  keywords = {Brain,Cognition,Humans,Magnetic Resonance Imaging,Memory; Short-Term,Neuropsychological Tests,Young Adult},
  file = {/Users/morteza/Documents/Zotero/storage/D2D34MD2/Etzel et al_2022_The Dual Mechanisms of Cognitive Control dataset, a theoretically-guided.pdf}
}

@article{farah1991,
  title = {A Computational Model of Semantic Memory Impairment: Modality Specificity and Emergent Category Specificity},
  shorttitle = {A Computational Model of Semantic Memory Impairment},
  author = {Farah, M. J. and McClelland, J. L.},
  year = {1991},
  month = dec,
  journal = {Journal of Experimental Psychology. General},
  volume = {120},
  number = {4},
  pages = {339--357},
  issn = {0096-3445},
  abstract = {It is demonstrated how a modality-specific semantic memory system can account for category-specific impairments after brain damage. In Experiment 1, the hypothesis that visual and functional knowledge play different roles in the representation of living things and nonliving things is tested and confirmed. A parallel distributed processing model of semantic memory in which knowledge is subdivided by modality into visual and functional components is described. In Experiment 2, the model is lesioned, and it is confirmed that damage to visual semantics primarily impairs knowledge of living things, and damage to functional semantics primarily impairs knowledge of nonliving things. In Experiment 3, it is demonstrated that the model accounts naturally for a finding that had appeared problematic for a modality-specific architecture, namely, impaired retrieval of functional knowledge about living things. Finally, in Experiment 4, it is shown how the model can account for a recent observation of impaired knowledge of living things only when knowledge is probed verbally.},
  langid = {english},
  pmid = {1837294},
  keywords = {Amnesia,Brain Damage; Chronic,Computer Simulation,Humans,Mental Recall,Models; Neurological,Neuropsychological Tests,Retention; Psychology,Semantics}
}

@article{fatemi2014,
  title = {Cognitive Control: {{Theory}} and Application},
  author = {Fatemi, Mehdi and Haykin, Simon},
  year = {2014},
  journal = {IEEE Access},
  volume = {2},
  pages = {698--710},
  issn = {2169-3536},
  doi = {10.1109/access.2014.2332333},
  abstract = {From an engineering point-of-view, cognitive control is inspired by the prefrontal cortex of the human brain; cognitive control may therefore be viewed as the overarching function of a cognitive dynamic system. In this paper, we describe a new way of thinking about cognitive control that embodies two basic components: learning and planning, both of which are based on two notions: 1) two-state model of the environment and the perceptor and 2) perception-action cycle, which is a distinctive characteristic of the cognitive dynamic system. Most importantly, it is shown that the cognitive control learning algorithm is a special form of Bellman's dynamic programming. Distinctive properties of the new algorithm include the following: 1) optimality of performance; 2) algorithmic convergence to optimal policy; and 3) linear law of complexity measured in terms of the number of actions taken by the cognitive controller on the environment. To validate these intrinsic properties of the algorithm, a computational experiment is presented, which involves a cognitive tracking radar that is known to closely mimic the visual brain. The experiment illustrates two different scenarios: 1) the impact of planning on learning curves of the new cognitive controller and 2) comparison of the learning curves of three different controllers, based on dynamic optimization, traditional \textbackslash (Q\textbackslash ) -learning, and the new algorithm. The latter two algorithms are based on the two-state model, and they both involve the use of planning.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2014/Fatemi\%202014.pdf},
  annotation = {00053}
}

@incollection{Feigenbaum1963a,
  title = {The Simulation of Verbal Learning Behavior},
  booktitle = {Computers and Thought},
  author = {Feigenbaum, E. A.},
  editor = {Feigenbaum, E. A. and Feldman, J.},
  year = {1963},
  publisher = {{McGraw-Hill}},
  address = {{New York}}
}

@incollection{fellows2017,
  title = {Cognitive {{Control}} in the {{Injured Brain}}},
  booktitle = {The {{Wiley Handbook}} of {{Cognitive Control}}},
  author = {Fellows, Lesley K.},
  year = {2017},
  pages = {513--538},
  publisher = {{John Wiley \& Sons, Ltd}},
  doi = {10.1002/9781118920497.ch29},
  abstract = {This chapter considers cognitive control in the injured brain from both fundamental and translational-applied perspectives. It reviews major cognitive neuroscience models of cognitive control, asking to what extent these models can be related to the clinical phenomena conceptually, and whether they have empirical support from studies of the effects of focal brain injury. The chapter discusses how current ideas about cognitive control are being applied in diagnosis and treatment of brain disorders. Clinicians have long recognised a constellation of symptoms and signs that tend to occur together in disorders affecting either the frontal lobes themselves, or subcortical regions connected to the frontal lobes, such as the mediodorsal thalamus and the basal ganglia. Alien limb is another striking symptom, traditionally associated with damage to the dorsome-dial frontal lobe, perhaps due to associated anterior corpus callosum disruption, but also a feature of parietal injury.},
  chapter = {29},
  isbn = {978-1-118-92049-7},
  langid = {english},
  keywords = {basal ganglia,brain disorders,clinical symptoms,cognitive control,dorsomedial frontal lobe,focal brain injury,subcortical regions},
  annotation = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781118920497.ch29},
  file = {/Users/morteza/Documents/Zotero/storage/G7XUTPMW/9781118920497.html}
}

@article{feltgen2021,
  title = {An {{Overcomplete Approach}} to {{Fitting Drift-Diffusion Decision Models}} to {{Trial-By-Trial Data}}},
  author = {Feltgen, Q. and Daunizeau, J.},
  year = {2021},
  month = apr,
  journal = {Frontiers in Artificial Intelligence},
  volume = {4},
  pages = {531316},
  issn = {2624-8212},
  doi = {10.3389/frai.2021.531316},
  abstract = {Drift-diffusion models or DDMs are becoming a standard in the field of computational neuroscience. They extend models from signal detection theory by proposing a simple mechanistic explanation for the observed relationship between decision outcomes and reaction times (RT). In brief, they assume that decisions are triggered once the accumulated evidence in favor of a particular alternative option has reached a predefined threshold. Fitting a DDM to empirical data then allows one to interpret observed group or condition differences in terms of a change in the underlying model parameters. However, current approaches only yield reliable parameter estimates in specific situations (c.f. fixed drift rates vs drift rates varying over trials). In addition, they become computationally unfeasible when more general DDM variants are considered (e.g., with collapsing bounds). In this note, we propose a fast and efficient approach to parameter estimation that relies on fitting a ``self-consistency'' equation that RT fulfill under the DDM. This effectively bypasses the computational bottleneck of standard DDM parameter estimation approaches, at the cost of estimating the trial-specific neural noise variables that perturb the underlying evidence accumulation process. For the purpose of behavioral data analysis, these act as nuisance variables and render the model ``overcomplete,'' which is finessed using a variational Bayesian system identification scheme. However, for the purpose of neural data analysis, estimates of neural noise perturbation terms are a desirable (and unique) feature of the approach. Using numerical simulations, we show that this ``overcomplete'' approach matches the performance of current parameter estimation approaches for simple DDM variants, and outperforms them for more complex DDM variants. Finally, we demonstrate the added-value of the approach, when applied to a recent value-based decision making experiment.},
  annotation = {5 citations (Semantic Scholar/DOI) [2022-09-26]},
  file = {/Users/morteza/Documents/Zotero/storage/3TYXB7RU/Feltgen and Daunizeau - 2021 - An Overcomplete Approach to Fitting Drift-Diffusio.pdf}
}

@article{feng2007,
  title = {Playing an {{Action Video Game Reduces Gender Differences}} in {{Spatial Cognition}}},
  author = {Feng, Jing and Spence, Ian and Pratt, Jay},
  year = {2007},
  month = oct,
  journal = {Psychological Science},
  volume = {18},
  number = {10},
  pages = {850--855},
  issn = {0956-7976, 1467-9280},
  doi = {10.1111/j.1467-9280.2007.01990.x},
  langid = {english},
  annotation = {1044 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/3E2PFQ62/Feng et al. - 2007 - Playing an Action Video Game Reduces Gender Differ.pdf}
}

@article{fiez1996,
  title = {Cerebellar {{Contributions}} to {{Cognition}}},
  author = {Fiez, Julie A},
  year = {1996},
  month = jan,
  journal = {Neuron},
  volume = {16},
  number = {1},
  pages = {13--15},
  issn = {08966273},
  doi = {10.1016/S0896-6273(00)80018-5},
  langid = {english},
  annotation = {166 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/43F7CX97/Fiez - 1996 - Cerebellar Contributions to Cognition.pdf}
}

@article{fikkers2019,
  title = {Child's {{Play}}? {{Assessing}} the {{Bidirectional Longitudinal Relationship}} between {{Gaming}} and {{Intelligence}} in {{Early Childhood}}},
  shorttitle = {Child's {{Play}}?},
  author = {Fikkers, Karin M and Piotrowski, Jessica Taylor and Valkenburg, Patti M},
  year = {2019},
  month = apr,
  journal = {Journal of Communication},
  volume = {69},
  number = {2},
  pages = {124--143},
  issn = {0021-9916, 1460-2466},
  doi = {10.1093/joc/jqz003},
  langid = {english},
  annotation = {19 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{finnigan2011,
  title = {{{ERP}} Measures Indicate Both Attention and Working Memory Encoding Decrements in Aging: {{Age}} Effects on Attention and Memory Encoding {{ERPs}}},
  shorttitle = {{{ERP}} Measures Indicate Both Attention and Working Memory Encoding Decrements in Aging},
  author = {Finnigan, Simon and O'Connell, Redmond G. and Cummins, Tarrant D. R. and Broughton, Megan and Robertson, Ian H.},
  year = {2011},
  month = may,
  journal = {Psychophysiology},
  volume = {48},
  number = {5},
  pages = {601--611},
  issn = {00485772},
  doi = {10.1111/j.1469-8986.2010.01128.x},
  langid = {english},
  annotation = {94 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{fitch2014,
  title = {Toward a Computational Framework for Cognitive Biology: {{Unifying}} Approaches from Cognitive Neuroscience and Comparative Cognition},
  shorttitle = {Toward a Computational Framework for Cognitive Biology},
  author = {Fitch, W. Tecumseh},
  year = {2014},
  month = sep,
  journal = {Physics of Life Reviews},
  volume = {11},
  number = {3},
  pages = {329--364},
  issn = {1571-0645},
  doi = {10.1016/j.plrev.2014.04.005},
  abstract = {Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity ``dendrophilia'', and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology.},
  langid = {english},
  keywords = {Cognitive science,Comparative cognition,Computational neuroscience,Formal language theory,Mathematical psychology,Neurolinguistics},
  annotation = {138 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/MWWG7PL3/Fitch_2014_Toward a computational framework for cognitive biology.pdf}
}

@article{föcker2018,
  title = {Neural Bases of Enhanced Attentional Control: {{Lessons}} from Action Video Game Players},
  shorttitle = {Neural Bases of Enhanced Attentional Control},
  author = {F{\"o}cker, Julia and Cole, Daniel and Beer, Anton L. and Bavelier, Daphne},
  year = {2018},
  month = jul,
  journal = {Brain and Behavior},
  volume = {8},
  number = {7},
  pages = {e01019},
  issn = {21623279},
  doi = {10.1002/brb3.1019},
  langid = {english},
  annotation = {29 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{föcker2019,
  title = {Neural {{Correlates}} of {{Enhanced Visual Attentional Control}} in {{Action Video Game Players}}: {{An Event-Related Potential Study}}},
  shorttitle = {Neural {{Correlates}} of {{Enhanced Visual Attentional Control}} in {{Action Video Game Players}}},
  author = {F{\"o}cker, Julia and Mortazavi, Matin and Khoe, Wayne and Hillyard, Steven A. and Bavelier, Daphne},
  year = {2019},
  month = mar,
  journal = {Journal of Cognitive Neuroscience},
  volume = {31},
  number = {3},
  pages = {377--389},
  issn = {0898-929X, 1530-8898},
  doi = {10.1162/jocn_a_01230},
  langid = {english},
  annotation = {23 citations (Semantic Scholar/DOI) [2022-12-11] 00005}
}

@article{forbus2017,
  title = {Representation and {{Computation}} in {{Cognitive Models}}},
  author = {Forbus, Kenneth D. and Liang, Chen and Rabkina, Irina},
  year = {2017},
  month = jul,
  journal = {Topics in Cognitive Science},
  volume = {9},
  number = {3},
  pages = {694--718},
  issn = {1756-8765},
  doi = {10.1111/tops.12277},
  abstract = {One of the central issues in cognitive science is the nature of human representations. We argue that symbolic representations are essential for capturing human cognitive capabilities. We start by examining some common misconceptions found in discussions of representations and models. Next we examine evidence that symbolic representations are essential for capturing human cognitive capabilities, drawing on the analogy literature. Then we examine fundamental limitations of feature vectors and other distributed representations that, despite their recent successes on various practical problems, suggest that they are insufficient to capture many aspects of human cognition. After that, we describe the implications for cognitive architecture of our view that analogy is central, and we speculate on roles for hybrid approaches. We close with an analogy that might help bridge the gap.},
  langid = {english},
  pmid = {28635155},
  keywords = {Analogy,Cognition,Cognitive Science,Computational modeling,Humans,Learning,Machine learning,Models; Theoretical,Relational representations,Representation,Symbolic modeling},
  annotation = {13 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/6B6EFBAS/Forbus et al_2017_Representation and Computation in Cognitive Models.pdf}
}

@article{forstmann2016,
  title = {Sequential {{Sampling Models}} in {{Cognitive Neuroscience}}: {{Advantages}}, {{Applications}}, and {{Extensions}}},
  shorttitle = {Sequential {{Sampling Models}} in {{Cognitive Neuroscience}}},
  author = {Forstmann, B.U. and Ratcliff, R. and Wagenmakers, E.-J.},
  year = {2016},
  month = jan,
  journal = {Annual Review of Psychology},
  volume = {67},
  number = {1},
  pages = {641--666},
  issn = {0066-4308, 1545-2085},
  doi = {10.1146/annurev-psych-122414-033645},
  abstract = {Sequential sampling models assume that people make speeded decisions by gradually accumulating noisy information until a threshold of evidence is reached. In cognitive science, one such model\textemdash the diffusion decision model\textemdash is now regularly used to decompose task performance into underlying processes such as the quality of information processing, response caution, and a priori bias. In the cognitive neurosciences, the diffusion decision model has recently been adopted as a quantitative tool to study the neural basis of decision making under time pressure. We present a selective overview of several recent applications and extensions of the diffusion decision model in the cognitive neurosciences.},
  langid = {english},
  keywords = {Cognitive Neuroscience,decision making,Decision Making,diffusion decision model,drift rate,Humans,information accumulation,Models; Psychological,Reaction Time,response time,speed-accuracy trade-off,Task Performance and Analysis},
  annotation = {311 citations (Semantic Scholar/DOI) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/64WERGKB/Forstmann et al_2016_Sequential Sampling Models in Cognitive Neuroscience.pdf;/Users/morteza/Documents/Zotero/storage/ZZHEB44D/Forstmann et al. - 2016 - Sequential Sampling Models in Cognitive Neuroscien.pdf}
}

@article{fox2005,
  title = {The Human Brain Is Intrinsically Organized into Dynamic, Anticorrelated Functional Networks},
  author = {Fox, Michael D. and Snyder, Abraham Z. and Vincent, Justin L. and Corbetta, Maurizio and Van Essen, David C. and Raichle, Marcus E.},
  year = {2005},
  month = jul,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {102},
  number = {27},
  pages = {9673--9678},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.0504136102},
  abstract = {During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.},
  langid = {english},
  annotation = {7340 citations (Semantic Scholar/DOI) [2022-12-07]},
  file = {/Users/morteza/Documents/Zotero/storage/XTP975JG/Fox et al. - 2005 - The human brain is intrinsically organized into dy.pdf}
}

@article{fox2006,
  title = {Spontaneous Neuronal Activity Distinguishes Human Dorsal and Ventral Attention Systems},
  author = {Fox, M. D. and Corbetta, M. and Snyder, A. Z. and Vincent, J. L. and Raichle, M. E.},
  year = {2006},
  month = jun,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {103},
  number = {26},
  pages = {10046--10051},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.0604187103},
  langid = {english},
  annotation = {1846 citations (Semantic Scholar/DOI) [2022-12-11] 01468},
  file = {/Users/morteza/Documents/Zotero/storage/F5SHN7B8/fox2006.pdf}
}

@article{franceschini2012,
  title = {A {{Causal Link}} between {{Visual Spatial Attention}} and {{Reading Acquisition}}},
  author = {Franceschini, Sandro and Gori, Simone and Ruffino, Milena and Pedrolli, Katia and Facoetti, Andrea},
  year = {2012},
  month = may,
  journal = {Current Biology},
  volume = {22},
  number = {9},
  pages = {814--819},
  issn = {09609822},
  doi = {10.1016/j.cub.2012.03.013},
  abstract = {Reading is a unique, cognitive human skill crucial to life in modern societies, but, for about 10\% of the children, learning to read is extremely difficult. They are affected by a neurodevelopmental disorder called dyslexia [1, 2]. Although impaired auditory and speech sound processing is widely assumed to characterize dyslexic individuals [1\textendash 5], emerging evidence suggests that dyslexia could arise from a more basic cross-modal letter-to-speech sound integration deficit [6\textendash 9]. Letters have to be precisely selected from irrelevant and cluttering letters [10, 11] by rapid orienting of visual attention before the correct letter-to-speech sound integration applies [12\textendash 17]. Here we ask whether prereading visual parietal-attention functioning may explain future reading emergence and development. The present 3 year longitudinal study shows that prereading attentional orienting\textemdash assessed by serial search performance and spatial cueing facilitation\textemdash captures future reading acquisition skills in grades 1 and 2 after controlling for age, nonverbal IQ, speech-sound processing, and nonalphabetic crossmodal mapping. Our findings provide the first evidence that visual spatial attention in preschoolers specifically predicts future reading acquisition, suggesting new approaches for early identification and efficient prevention of dyslexia.},
  langid = {english},
  annotation = {418 citations (Semantic Scholar/DOI) [2022-11-30]},
  file = {/Users/morteza/Documents/Zotero/storage/9XLKTP39/Franceschini et al_2012_A Causal Link between Visual Spatial Attention and Reading Acquisition.pdf}
}

@article{franceschini2013,
  title = {Action {{Video Games Make Dyslexic Children Read Better}}},
  author = {Franceschini, Sandro and Gori, Simone and Ruffino, Milena and Viola, Simona and Molteni, Massimo and Facoetti, Andrea},
  year = {2013},
  month = mar,
  journal = {Current Biology},
  volume = {23},
  number = {6},
  pages = {462--466},
  issn = {09609822},
  doi = {10.1016/j.cub.2013.01.044},
  langid = {english},
  annotation = {388 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{franceschini2015,
  title = {``{{Shall We Play}} a {{Game}}?'': {{Improving Reading Through Action Video Games}} in {{Developmental Dyslexia}}},
  shorttitle = {``{{Shall We Play}} a {{Game}}?},
  author = {Franceschini, Sandro and Bertoni, Sara and Ronconi, Luca and Molteni, Massimo and Gori, Simone and Facoetti, Andrea},
  year = {2015},
  month = dec,
  journal = {Current Developmental Disorders Reports},
  volume = {2},
  number = {4},
  pages = {318--329},
  issn = {2196-2987},
  doi = {10.1007/s40474-015-0064-4},
  langid = {english},
  annotation = {35 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/R44AN8EB/Franceschini et al. - 2015 - “Shall We Play a Game” Improving Reading Through.pdf}
}

@article{franceschini2017,
  title = {Action Video Games Improve Reading Abilities and Visual-to-Auditory Attentional Shifting in {{English-speaking}} Children with Dyslexia},
  author = {Franceschini, Sandro and Trevisan, Piergiorgio and Ronconi, Luca and Bertoni, Sara and Colmar, Susan and Double, Kit and Facoetti, Andrea and Gori, Simone},
  year = {2017},
  month = dec,
  journal = {Scientific Reports},
  volume = {7},
  number = {1},
  pages = {5863},
  issn = {2045-2322},
  doi = {10.1038/s41598-017-05826-8},
  langid = {english},
  annotation = {100 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/2HSGQNTN/franceschini2017.pdf;/Users/morteza/Documents/Zotero/storage/IWBQZP7R/Franceschini et al. - 2017 - Action video games improve reading abilities and v.pdf}
}

@article{freund2021,
  title = {A {{Representational Similarity Analysis}} of {{Cognitive Control}} during {{Color-Word Stroop}}},
  author = {Freund, Michael C. and Bugg, Julie M. and Braver, Todd S.},
  year = {2021},
  month = sep,
  journal = {The Journal of Neuroscience: The Official Journal of the Society for Neuroscience},
  volume = {41},
  number = {35},
  pages = {7388--7402},
  issn = {1529-2401},
  doi = {10.1523/JNEUROSCI.2956-20.2021},
  abstract = {Progress in understanding the neural bases of cognitive control has been supported by the paradigmatic color-word Stroop task, in which a target response (color name) must be selected over a more automatic, yet potentially incongruent, distractor response (word). For this paradigm, models have postulated complementary coding schemes: dorsomedial frontal cortex (DMFC) is proposed to evaluate the demand for control via incongruency-related coding, whereas dorsolateral PFC (DLPFC) is proposed to implement control via goal and target-related coding. Yet, mapping these theorized schemes to measured neural activity within this task has been challenging. Here, we tested for these coding schemes relatively directly, by decomposing an event-related color-word Stroop task via representational similarity analysis. Three neural coding models were fit to the similarity structure of multivoxel patterns of human fMRI activity, acquired from 65 healthy, young-adult males and females. Incongruency coding was predominant in DMFC, whereas both target and incongruency coding were present with indistinguishable strength in DLPFC. In contrast, distractor information was strongly encoded within early visual cortex. Further, these coding schemes were differentially related to behavior: individuals with stronger DLPFC (and lateral posterior parietal cortex) target coding, but weaker DMFC incongruency coding, exhibited less behavioral Stroop interference. These results highlight the utility of the representational similarity analysis framework for investigating neural mechanisms of cognitive control and point to several promising directions to extend the Stroop paradigm.SIGNIFICANCE STATEMENT How the human brain enables cognitive control - the ability to override behavioral habits to pursue internal goals - has been a major focus of neuroscience research. This ability has been frequently investigated by using the Stroop color-word naming task. With the Stroop as a test-bed, many theories have proposed specific neuroanatomical dissociations, in which medial and lateral frontal brain regions underlie cognitive control by encoding distinct types of information. Yet providing a direct confirmation of these claims has been challenging. Here, we demonstrate that representational similarity analysis, which estimates and models the similarity structure of brain activity patterns, can successfully establish the hypothesized functional dissociations within the Stroop task. Representational similarity analysis may provide a useful approach for investigating cognitive control mechanisms.},
  langid = {english},
  pmcid = {PMC8412987},
  pmid = {34162756},
  keywords = {Adult,Brain Mapping,Cognition,Color,dorsal ACC,dorsolateral PFC,Dorsolateral Prefrontal Cortex,executive function,Female,fMRI,Frontal Lobe,Goals,Habits,Humans,Imagination,Intention,Magnetic Resonance Imaging,Male,Models; Neurological,Models; Psychological,multivariate pattern analysis,Psychomotor Performance,response conflict,Signal-To-Noise Ratio,Stroop Test,Twins,Young Adult},
  file = {/Users/morteza/Documents/Zotero/storage/3UH9Y3T2/Freund et al_2021_A Representational Similarity Analysis of Cognitive Control during Color-Word.pdf}
}

@article{freund2021a,
  title = {Neural {{Coding}} of {{Cognitive Control}}: {{The Representational Similarity Analysis Approach}}},
  shorttitle = {Neural {{Coding}} of {{Cognitive Control}}},
  author = {Freund, Michael C. and Etzel, Joset A. and Braver, Todd S.},
  year = {2021},
  month = jul,
  journal = {Trends in Cognitive Sciences},
  volume = {25},
  number = {7},
  pages = {622--638},
  issn = {1879-307X},
  doi = {10.1016/j.tics.2021.03.011},
  abstract = {Cognitive control relies on distributed and potentially high-dimensional frontoparietal task representations. Yet, the classical cognitive neuroscience approach in this domain has focused on aggregating and contrasting neural measures - either via univariate or multivariate methods - along highly abstracted, 1D factors (e.g., Stroop congruency). Here, we present representational similarity analysis (RSA) as a complementary approach that can powerfully inform representational components of cognitive control theories. We review several exemplary uses of RSA in this regard. We further show that most classical paradigms, given their factorial structure, can be optimized for RSA with minimal modification. Our aim is to illustrate how RSA can be incorporated into cognitive control investigations to shed new light on old questions.},
  langid = {english},
  pmcid = {PMC8279005},
  pmid = {33895065},
  keywords = {anterior cingulate cortex (ACC),Brain Mapping,Cognition,executive function,Humans,Magnetic Resonance Imaging,multivariate pattern analysis (MVPA),Neurosciences,prefrontal cortex (PFC),representational similarity analysis (RSA)},
  file = {/Users/morteza/Documents/Zotero/storage/JYTTWYJ5/Freund et al_2021_Neural Coding of Cognitive Control.pdf}
}

@article{friedman2022,
  title = {The Role of Prefrontal Cortex in Cognitive Control and Executive Function},
  author = {Friedman, Naomi P. and Robbins, Trevor W.},
  year = {2022},
  month = jan,
  journal = {Neuropsychopharmacology},
  volume = {47},
  number = {1},
  pages = {72--89},
  issn = {1740-634X},
  doi = {10.1038/s41386-021-01132-0},
  abstract = {Concepts of cognitive control (CC) and executive function (EF) are defined in terms of their relationships with goal-directed behavior versus habits and controlled versus automatic processing, and related to the functions of the prefrontal cortex (PFC) and related regions and networks. A psychometric approach shows unity and diversity in CC constructs, with 3 components in the most commonly studied constructs: general or common CC and components specific to mental set shifting and working memory updating. These constructs are considered against the cellular and systems neurobiology of PFC and what is known of its functional neuroanatomical or network organization based on lesioning, neurochemical, and neuroimaging approaches across species. CC is also considered in the context of motivation, as ``cool'' and ``hot'' forms. Its Common CC component is shown to be distinct from general intelligence (g) and closely related to response inhibition. Impairments in CC are considered as possible causes of psychiatric symptoms and consequences of disorders. The relationships of CC with the general factor of psychopathology (p) and dimensional constructs such as impulsivity in large scale developmental and adult populations are considered, as well~as implications for genetic studies and RDoC approaches to psychiatric classification.},
  copyright = {2021 The Author(s)},
  langid = {english},
  keywords = {Cognitive control,Human behaviour,Psychiatric disorders}
}

@article{fromer2022,
  title = {Filling the Gaps: {{Cognitive}} Control as a Critical Lens for Understanding Mechanisms of Value-Based Decision-Making},
  shorttitle = {Filling the Gaps},
  author = {Fr{\"o}mer, R. and Shenhav, A.},
  year = {2022},
  month = mar,
  journal = {Neuroscience and Biobehavioral Reviews},
  volume = {134},
  pages = {104483},
  issn = {1873-7528},
  doi = {10.1016/j.neubiorev.2021.12.006},
  abstract = {While often seeming to investigate rather different problems, research into value-based decision making and cognitive control have historically offered parallel insights into how people select thoughts and actions. While the former studies how people weigh costs and benefits to make a decision, the latter studies how they adjust information processing to achieve their goals. Recent work has highlighted ways in which decision-making research can inform our understanding of cognitive control. Here, we provide the complementary perspective: how cognitive control research has informed understanding of decision-making. We highlight three particular areas of research where this critical interchange has occurred: (1) how different types of goals shape the evaluation of choice options, (2) how people use control to adjust the ways they make their decisions, and (3) how people monitor decisions to inform adjustments to control at multiple levels and timescales. We show how adopting this alternate viewpoint offers new insight into the determinants of both decisions and control; provides alternative interpretations for common neuroeconomic findings; and generates fruitful directions for future research.},
  langid = {english},
  pmcid = {PMC8844247},
  pmid = {34902441},
  keywords = {Attention,Choice conflict,Cognition,Humans,Metacognition,Performance monitoring,Reward},
  file = {/Users/morteza/Documents/Zotero/storage/2VSPU9GP/Frömer_Shenhav_2022_Filling the gaps.pdf}
}

@article{fudenberg2020,
  title = {Testing the Drift-Diffusion Model},
  author = {Fudenberg, Drew and Newey, Whitney and Strack, Philipp and Strzalecki, Tomasz},
  year = {2020},
  month = dec,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {117},
  number = {52},
  pages = {33141--33148},
  publisher = {{Proceedings of the National Academy of Sciences}},
  doi = {10.1073/pnas.2011446117},
  annotation = {11 citations (Semantic Scholar/DOI) [2022-09-26]},
  file = {/Users/morteza/Documents/Zotero/storage/B96782RT/Fudenberg et al_2020_Testing the drift-diffusion model.pdf}
}

@article{gathercole2003,
  title = {Working Memory Assessments at School Entry as Longitudinal Predictors of {{National Curriculum}} Attainment Levels},
  author = {Gathercole, Susan E. and Brown, Leanne and Pickering, Susan J.},
  year = {2003},
  journal = {Educational and Child Psychology},
  volume = {20},
  number = {3},
  pages = {109--122},
  issn = {2396-8702(Electronic),0267-1611(Print)},
  abstract = {A longitudinal study of 54 children aged between 4 and 7 years of age investigated whether measures of working memory skills taken shortly after school entry served as useful predictors of children's attainment levels in National Curriculum assessments at Key Stage 1. Early working memory scores were found to be highly significant predictors of children's subsequent levels of attainment in literacy, but not in mathematics. Compared with the local education authority baseline assessments also administered at 4 years of age that are designed in large part to predict later attainments, working memory scores accounted for unique variance in children's spelling and writing scores at 7 years. These findings point to the utility of combining knowledge-based assessments with measures of fluid cognitive ability in order to obtain the best estimates of a child's chances of future academic success. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
  keywords = {Academic Achievement,Literacy,Mathematics Achievement,Preschool Students,Short Term Memory,Standardized Tests},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/AUUFIWNP/2004-11157-009.html}
}

@article{gathercole2004,
  title = {Working Memory Skills and Educational Attainment: Evidence from National Curriculum Assessments at 7 and 14 Years of Age},
  shorttitle = {Working Memory Skills and Educational Attainment},
  author = {Gathercole, Susan E. and Pickering, Susan J. and Knight, Camilla and Stegmann, Zoe},
  year = {2004},
  month = jan,
  journal = {Applied Cognitive Psychology},
  volume = {18},
  number = {1},
  pages = {1--16},
  issn = {0888-4080, 1099-0720},
  doi = {10.1002/acp.934},
  langid = {english},
  annotation = {898 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{gathercole2005,
  title = {Developmental Consequences of Poor Phonological Short-Term Memory Function in Childhood: A Longitudinal Study},
  shorttitle = {Developmental Consequences of Poor Phonological Short-Term Memory Function in Childhood},
  author = {Gathercole, Susan E. and Tiffany, Claire and Briscoe, Josie and Thorn, Annabel and {ALSPAC team}},
  year = {2005},
  month = jun,
  journal = {Journal of Child Psychology and Psychiatry, and Allied Disciplines},
  volume = {46},
  number = {6},
  pages = {598--611},
  issn = {0021-9630},
  doi = {10.1111/j.1469-7610.2004.00379.x},
  abstract = {BACKGROUND: A longitudinal study investigated the cognitive skills and scholastic attainments at 8 years of age of children selected on the basis of poor phonological loop skills at 5 years. METHODS: Children with low and average performance at 5 years were tested three years later on measures of working memory, phonological awareness, vocabulary, language, reading, and number skill. RESULTS: Two subgroups of children with poor early performance on phonological memory tests were identified. In one subgroup, the poor phonological memory skills persisted at 8 years. These children performed at comparable levels to the control group on measures of vocabulary, language and mathematics. They scored more poorly on literacy assessments, but this deficit was associated with group differences in complex memory span and phonological awareness performance. The second subgroup of children performed more highly on phonological memory tests at 8 years, but had enduring deficits in language assessments from 4 to 8 years. CONCLUSIONS: Persistently poor phonological memory skills do not appear to significantly constrain the acquisition of language, mathematics or number skills over the early school years. More general working memory skills do, however, appear to be crucial.},
  langid = {english},
  pmid = {15877766},
  keywords = {Articulation Disorders,Child,Child; Preschool,Epidemiologic Methods,Female,Humans,Language Development Disorders,Language Tests,Male,Memory; Short-Term},
  annotation = {221 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{gathercole2016,
  title = {How {{Common}} Are {{WM Deficits}} in {{Children}} with {{Difficulties}} in {{Reading}} and {{Mathematics}}?},
  author = {Gathercole, Susan E. and Woolgar, Francesca and Kievit, Rogier A. and Astle, Duncan and Manly, Tom and Holmes, Joni},
  year = {2016},
  month = dec,
  journal = {Journal of Applied Research in Memory and Cognition},
  volume = {5},
  number = {4},
  pages = {384--394},
  issn = {22113681},
  doi = {10.1016/j.jarmac.2016.07.013},
  langid = {english},
  annotation = {55 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@incollection{geary2019,
  title = {Introduction: {{Cognitive Foundations}} for {{Improving Mathematical Learning}}},
  shorttitle = {Introduction},
  booktitle = {Cognitive {{Foundations}} for {{Improving Mathematical Learning}}},
  author = {Geary, David C. and Berch, Daniel B. and Mann Koepke, Kathleen},
  year = {2019},
  pages = {1--36},
  publisher = {{Elsevier}},
  doi = {10.1016/B978-0-12-815952-1.00001-3},
  isbn = {978-0-12-815952-1},
  langid = {english},
  annotation = {00000}
}

@article{gentile2017,
  title = {Internet {{Gaming Disorder}} in {{Children}} and {{Adolescents}}},
  author = {Gentile, Douglas A. and Bailey, Kira and Bavelier, Daphne and Brockmyer, Jeanne Funk and Cash, Hilarie and Coyne, Sarah M. and Doan, Andrew and Grant, Donald S. and Green, C. Shawn and Griffiths, Mark and Markle, Tracy and Petry, Nancy M. and Prot, Sara and Rae, Cosette D. and Rehbein, Florian and Rich, Michael and Sullivan, Dave and Woolley, Elizabeth and Young, Kimberly},
  year = {2017},
  month = nov,
  journal = {Pediatrics},
  volume = {140},
  number = {Supplement 2},
  pages = {S81-S85},
  issn = {0031-4005, 1098-4275},
  doi = {10.1542/peds.2016-1758H},
  langid = {english},
  annotation = {118 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/4XDYITE8/Gentile et al. - 2017 - Internet Gaming Disorder in Children and Adolescen.pdf;/Users/morteza/Documents/Zotero/storage/9QUMXDLU/Gentile et al. - 2017 - Internet Gaming Disorder in Children and Adolescen.pdf;/Users/morteza/Documents/Zotero/storage/QEWUZZHX/S81+.html}
}

@article{gentile2017a,
  title = {Violent Video Game Effects on Salivary Cortisol, Arousal, and Aggressive Thoughts in Children},
  author = {Gentile, Douglas A. and Bender, Patrick K. and Anderson, Craig A.},
  year = {2017},
  month = may,
  journal = {Computers in Human Behavior},
  volume = {70},
  pages = {39--43},
  issn = {07475632},
  doi = {10.1016/j.chb.2016.12.045},
  langid = {english},
  annotation = {44 citations (Semantic Scholar/DOI) [2022-12-11] 00000}
}

@article{gershman2022,
  title = {Mental Control of Uncertainty},
  author = {Gershman, Samuel J. and Burke, Taylor},
  year = {2022},
  month = sep,
  journal = {Cognitive, Affective \& Behavioral Neuroscience},
  issn = {1531-135X},
  doi = {10.3758/s13415-022-01034-8},
  abstract = {Can you reduce uncertainty by thinking? Intuition suggests that this happens through the elusive process of attention: if we expend mental effort, we can increase the reliability of our sensory data. Models based on "rational inattention" formalize this idea in terms of a trade-off between the costs and benefits of attention. This paper surveys the origin of these models in economics, their connection to rate-distortion theory, and some of their recent applications to psychology and neuroscience. We also report new data from a numerosity judgment task in which we manipulate performance incentives. Consistent with rational inattention, people are able to improve performance on this task when incentivized, in part by increasing the reliability of their sensory data.},
  langid = {english},
  pmid = {36168079},
  keywords = {Bayesian inference,Information theory,Numerosity,Perception,Rational inattention},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-10-27]}
}

@article{glass2013,
  title = {Real-{{Time Strategy Game Training}}: {{Emergence}} of a {{Cognitive Flexibility Trait}}},
  shorttitle = {Real-{{Time Strategy Game Training}}},
  author = {Glass, Brian D. and Maddox, W. Todd and Love, Bradley C.},
  editor = {Wenderoth, Nicole},
  year = {2013},
  month = aug,
  journal = {PLoS ONE},
  volume = {8},
  number = {8},
  pages = {e70350},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0070350},
  langid = {english},
  annotation = {156 citations (Semantic Scholar/DOI) [2022-12-11] 00124},
  file = {/Users/morteza/Documents/Zotero/storage/MBIT3VI6/Glass et al. - 2013 - Real-Time Strategy Game Training Emergence of a C.pdf}
}

@article{gold2007,
  title = {The {{Neural Basis}} of {{Decision Making}}},
  author = {Gold, Joshua I. and Shadlen, Michael N.},
  year = {2007},
  month = jul,
  journal = {Annual Review of Neuroscience},
  volume = {30},
  number = {1},
  pages = {535--574},
  issn = {0147-006X, 1545-4126},
  doi = {10.1146/annurev.neuro.29.051605.113038},
  abstract = {The study of decision making spans such varied fields as neuroscience, psychology, economics, statistics, political science, and computer science. Despite this diversity of applications, most decisions share common elements including deliberation and commitment. Here we evaluate recent progress in understanding how these basic elements of decision formation are implemented in the brain. We focus on simple decisions that can be studied in the laboratory but emphasize general principles likely to extend to other settings.},
  langid = {english},
  annotation = {3042 citations (Semantic Scholar/DOI) [2022-11-29]},
  file = {/Users/morteza/Documents/Zotero/storage/F23ZSHPA/Gold_Shadlen_2007_The Neural Basis of Decision Making.pdf}
}

@article{goldin2014,
  title = {Far Transfer to Language and Math of a Short Software-Based Gaming Intervention},
  author = {Goldin, A. P. and Hermida, M. J. and Shalom, D. E. and Elias Costa, M. and {Lopez-Rosenfeld}, M. and Segretin, M. S. and {Fernandez-Slezak}, D. and Lipina, S. J. and Sigman, M.},
  year = {2014},
  month = apr,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {111},
  number = {17},
  pages = {6443--6448},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1320217111},
  langid = {english},
  annotation = {99 citations (Semantic Scholar/DOI) [2022-12-11] 00086},
  file = {/Users/morteza/Documents/Zotero/storage/EXAK24LL/goldin2014.pdf}
}

@article{goldstein2013,
  title = {Handbook of Executive Functioning},
  author = {Goldstein, Sam and Naglieri, Jack A. and Princiotta, Dana and Otero, Tulio M.},
  year = {2013},
  pages = {3--12},
  doi = {10.1007/978-1-4614-8106-5\_1},
  abstract = {Executive function (EF) has come to be an umbrella term used for a diversity of hypothesized cognitive processes, including planning, working memory, attention, inhibition, self-monitoring, self-regulation, and initiation carried out by prefrontal areas of the frontal lobes.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2013/Goldstein\%202013.pdf},
  keywords = {Cognitive Control,Executive Functions},
  annotation = {00232}
}

@incollection{goldstein2014,
  title = {Introduction: {{A History}} of {{Executive Functioning}} as a {{Theoretical}} and {{Clinical Construct}}},
  shorttitle = {Introduction},
  booktitle = {Handbook of {{Executive Functioning}}},
  author = {Goldstein, Sam and Naglieri, Jack A. and Princiotta, Dana and Otero, Tulio M.},
  editor = {Goldstein, Sam and Naglieri, Jack A.},
  year = {2014},
  pages = {3--12},
  publisher = {{Springer New York}},
  address = {{New York, NY}},
  doi = {10.1007/978-1-4614-8106-5_1},
  isbn = {978-1-4614-8105-8 978-1-4614-8106-5},
  langid = {english},
  annotation = {00002}
}

@article{gong2015,
  title = {Enhanced Functional Connectivity and Increased Gray Matter Volume of Insula Related to Action Video Game Playing},
  author = {Gong, Diankun and He, Hui and Liu, Dongbo and Ma, Weiyi and Dong, Li and Luo, Cheng and Yao, Dezhong},
  year = {2015},
  month = sep,
  journal = {Scientific Reports},
  volume = {5},
  number = {1},
  pages = {9763},
  issn = {2045-2322},
  doi = {10.1038/srep09763},
  langid = {english},
  annotation = {75 citations (Semantic Scholar/DOI) [2022-12-11]},
  file = {/Users/morteza/Documents/Zotero/storage/ZMKL8RG5/gong2015.pdf}
}

@article{gong2016,
  title = {Functional {{Integration}} between {{Salience}} and {{Central Executive Networks}}: {{A Role}} for {{Action Video Game Experience}}},
  author = {Gong, Diankun and He, Hui and Ma, Weiyi and Liu, Dongbo and Huang, Mengting and Dong, Li and Gong, Jinnan and Li, Jianfu and Luo, Cheng and Yao, Dezhong},
  year = {2016},
  journal = {Neural Plasticity},
  volume = {2016},
  number = {4},
  pages = {1--9},
  doi = {10.1155/2016/9803165},
  langid = {english},
  annotation = {49 citations (Semantic Scholar/DOI) [2022-12-11] 00026}
}

@article{gong2017,
  title = {Action {{Video Game Experience Related}} to {{Altered Large-Scale White Matter Networks}}},
  author = {Gong, Diankun and Ma, Weiyi and Gong, Jinnan and He, Hui and Dong, Li and Zhang, Dan and Li, Jianfu and Luo, Cheng and Yao, Dezhong},
  year = {2017},
  journal = {Neural Plasticity},
  volume = {2017},
  pages = {1--7},
  doi = {10.1155/2017/7543686},
  langid = {english},
  keywords = {AVGP,WM},
  annotation = {14 citations (Semantic Scholar/DOI) [2022-12-11] 00002}
}

@article{gong2019,
  title = {A {{Reduction}} in {{Video Gaming Time Produced}} a {{Decrease}} in {{Brain Activity}}},
  author = {Gong, Diankun and Yao, Yutong and Gan, Xianyang and Peng, Yurui and Ma, Weiyi and Yao, Dezhong},
  year = {2019},
  month = apr,
  journal = {Frontiers in Human Neuroscience},
  volume = {13},
  pages = {134},
  issn = {1662-5161},
  doi = {10.3389/fnhum.2019.00134},
  annotation = {13 citations (Semantic Scholar/DOI) [2022-12-11] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/MEWC9Q8L/gong2019.pdf}
}

@article{gorbet2018,
  title = {Move Faster, Think Later: {{Women}} Who Play Action Video Games Have Quicker Visually- Guided Responses with Later Onset Visuomotor-Related Brain Activity},
  author = {Gorbet, Diana J and Sergio, Lauren E},
  year = {2018},
  month = jan,
  journal = {PLoS ONE},
  volume = {13},
  number = {1},
  pages = {e0189110},
  doi = {10.1371/journal.pone.0189110},
  abstract = {A history of action video game (AVG) playing is associated with improvements in several visuospatial and attention-related skills and these improvements may be transferable to unrelated tasks. These facts make video games a potential medium for skill-training and rehabilitation. However, examinations of the neural correlates underlying these observations are almost non-existent in the visuomotor system. Further, the vast majority of studies on the effects of a history of AVG play have been done using almost exclusively male participants. Therefore, to begin to fill these gaps in the literature, we present findings from two experiments. In the first, we use functional MRI to examine brain activity in experienced, female AVG players during visually-guided reaching. In the second, we examine the kinematics of visually-guided reaching in this population. Imaging data demonstrate that relative to women who do not play, AVG players have less motor-related preparatory activity in the cuneus, middle occipital gyrus, and cerebellum. This decrease is correlated with estimates of time spent playing. Further, these correlations are strongest during the performance of a visuomotor mapping that spatially dissociates eye and arm movements. However, further examinations of the full time-course of visuomotor-related activity in the AVG players revealed that the decreased activity during motor preparation likely results from a later onset of activity in AVG players, which occurs closer to beginning motor execution relative to the non-playing group. Further, the data presented here suggest that this later onset of preparatory activity represents greater neural efficiency that is associated with faster visually-guided responses.},
  langid = {english},
  pmcid = {PMC5783344},
  pmid = {29364891},
  annotation = {19 citations (Semantic Scholar/DOI) [2022-12-11] 00005}
}

@article{gordon2016,
  title = {Generation and {{Evaluation}} of a {{Cortical Area Parcellation}} from {{Resting-State Correlations}}},
  author = {Gordon, Evan M. and Laumann, Timothy O. and Adeyemo, Babatunde and Huckins, Jeremy F. and Kelley, William M. and Petersen, Steven E.},
  year = {2016},
  month = jan,
  journal = {Cerebral Cortex},
  volume = {26},
  number = {1},
  pages = {288--303},
  issn = {1047-3211, 1460-2199},
  doi = {10.1093/cercor/bhu239},
  langid = {english},
  annotation = {902 citations (Semantic Scholar/DOI) [2022-12-06]},
  file = {/Users/morteza/Documents/Zotero/storage/IEBX7XU9/Gordon et al. - 2016 - Generation and Evaluation of a Cortical Area Parce.pdf}
}

@article{gorgolewski2016,
  title = {The Brain Imaging Data Structure, a Format for Organizing and Describing Outputs of Neuroimaging Experiments},
  author = {Gorgolewski, Krzysztof J. and Auer, Tibor and Calhoun, Vince D. and Craddock, R. Cameron and Das, Samir and Duff, Eugene P. and Flandin, Guillaume and Ghosh, Satrajit S. and Glatard, Tristan and Halchenko, Yaroslav O. and Handwerker, Daniel A. and Hanke, Michael and Keator, David and Li, Xiangrui and Michael, Zachary and Maumet, Camille and Nichols, B. Nolan and Nichols, Thomas E. and Pellman, John and Poline, Jean-Baptiste and Rokem, Ariel and Schaefer, Gunnar and Sochat, Vanessa and Triplett, William and Turner, Jessica A. and Varoquaux, Ga{\"e}l and Poldrack, Russell A.},
  year = {2016},
  month = dec,
  journal = {Scientific Data},
  volume = {3},
  number = {1},
  pages = {160044},
  issn = {2052-4463},
  doi = {10.1038/sdata.2016.44},
  langid = {english},
  annotation = {759 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/LYWIDC9H/Gorgolewski et al. - 2016 - The brain imaging data structure, a format for org.pdf}
}

@incollection{gorman2017,
  title = {Young {{Minds}} on {{Video Games}}},
  booktitle = {Cognitive {{Development}} in {{Digital Contexts}}},
  author = {Gorman, Thomas E. and Green, C. Shawn},
  year = {2017},
  pages = {121--143},
  publisher = {{Elsevier}},
  doi = {10.1016/B978-0-12-809481-5.00006-7},
  isbn = {978-0-12-809481-5},
  langid = {english},
  annotation = {00000}
}

@article{gozli2014,
  title = {The Effect of Action Video Game Playing on Sensorimotor Learning: {{Evidence}} from a Movement Tracking Task},
  shorttitle = {The Effect of Action Video Game Playing on Sensorimotor Learning},
  author = {Gozli, Davood G. and Bavelier, Daphne and Pratt, Jay},
  year = {2014},
  month = dec,
  journal = {Human Movement Science},
  volume = {38},
  pages = {152--162},
  issn = {01679457},
  doi = {10.1016/j.humov.2014.09.004},
  langid = {english},
  annotation = {53 citations (Semantic Scholar/DOI) [2022-12-01]}
}

@article{gratton2018,
  title = {Control Networks and Hubs},
  author = {Gratton, Caterina and Sun, Haoxin and Petersen, Steven E.},
  year = {2018},
  journal = {Psychophysiology},
  volume = {55},
  number = {3},
  pages = {e13032},
  issn = {1469-8986},
  doi = {10.1111/psyp.13032},
  abstract = {Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease.},
  langid = {english},
  keywords = {cognitive control,executive control,fMRI,functional connectivity,networks},
  annotation = {90 citations (Semantic Scholar/DOI) [2022-10-27] \_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/psyp.13032},
  file = {/Users/morteza/Documents/Zotero/storage/TTD8V2C6/Gratton et al_2018_Control networks and hubs.pdf}
}

@article{gratton2018a,
  title = {Dynamics of Cognitive Control: {{Theoretical}} Bases, Paradigms, and a View for the Future},
  shorttitle = {Dynamics of Cognitive Control},
  author = {Gratton, Gabriele and Cooper, Patrick and Fabiani, Monica and Carter, Cameron S. and Karayanidis, Frini},
  year = {2018},
  journal = {Psychophysiology},
  volume = {55},
  number = {3},
  pages = {e13016},
  issn = {1469-8986},
  doi = {10.1111/psyp.13016},
  abstract = {Cognitive control (with the closely related concepts of attention control and executive function) encompasses the collection of processes that are involved in generating and maintaining appropriate task goals and suppressing task goals that are no longer relevant, as well as the way in which current goal representations are used to modify attentional biases to improve task performance. Here, we provide a comprehensive but nonexhaustive review of this complex literature, with an emphasis on the contributions made by techniques for studying human brain function. The review is divided into five sections: (a) overview and historical perspective of cognitive control, its subcomponent processes, and its neural substrate; (b) most common types of tasks used to assess and/or manipulate the level of control; (c) main research findings obtained with various imaging methodologies, with a focus on ERP data, and briefer overviews of oscillatory (event-related spectral perturbations) and fMRI data; (d) major theories of cognitive control; and (e) discussion of open questions regarding how to integrate the various dimensions of control, as well as the faster versus slower temporal dynamics informing this complex and multifaceted concept.},
  langid = {english},
  keywords = {cognitive control,control dynamics,EEG,ERPs,executive function,fMRI,neuroimaging},
  annotation = {112 citations (Semantic Scholar/DOI) [2022-10-27] \_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/psyp.13016},
  file = {/Users/morteza/Documents/Zotero/storage/BIP3QLJB/Gratton et al_2018_Dynamics of cognitive control.pdf;/Users/morteza/Documents/Zotero/storage/9CHWKWMT/psyp.html}
}

@article{green2003,
  title = {Action Video Game Modifies Visual Selective Attention},
  author = {Green, C. Shawn and Bavelier, Daphne},
  year = {2003},
  month = may,
  journal = {Nature},
  volume = {423},
  number = {6939},
  pages = {534--537},
  issn = {0028-0836},
  doi = {10.1038/nature01647},
  abstract = {As video-game playing has become a ubiquitous activity in today's society, it is worth considering its potential consequences on perceptual and motor skills. It is well known that exposing an organism to an altered visual environment often results in modification of the visual system of the organism. The field of perceptual learning provides many examples of training-induced increases in performance. But perceptual learning, when it occurs, tends to be specific to the trained task; that is, generalization to new tasks is rarely found. Here we show, by contrast, that action-video-game playing is capable of altering a range of visual skills. Four experiments establish changes in different aspects of visual attention in habitual video-game players as compared with non-video-game players. In a fifth experiment, non-players trained on an action video game show marked improvement from their pre-training abilities, thereby establishing the role of playing in this effect.},
  langid = {english},
  pmid = {12774121},
  keywords = {Adolescent,Adult,Attention,Female,Humans,Learning,Male,Photic Stimulation,Psychomotor Performance,Space Perception,Video Games},
  annotation = {2291 citations (Semantic Scholar/DOI) [2022-12-11]}
}

@article{green2008,
  title = {Exercising Your Brain: {{A}} Review of Human Brain Plasticity and Training-Induced Learning.},
  shorttitle = {Exercising Your Brain},
  author = {Green, C. S. and Bavelier, D.},
  year = {2008},
  journal = {Psychology and Aging},
  volume = {23},
  number = {4},
  pages = {692--701},
  issn = {1939-1498, 0882-7974},
  doi = {10.1037/a0014345},
  langid = {english},
  keywords = {Aged,Aging,Arousal,Attention,Brain,Feedback; Psychological,Humans,Intelligence,Motivation,Music,Neuronal Plasticity,Practice (Psychology),Sports,Transfer (Psychology),Video Games},
  annotation = {599 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/25ZPKXXW/Green and Bavelier - 2008 - Exercising your brain A review of human brain pla.pdf}
}

@article{green2010,
  title = {Perceptual {{Learning During Action Video Game Playing}}},
  author = {Green, C. Shawn and Li, Renjie and Bavelier, Daphne},
  year = {2010},
  month = apr,
  journal = {Topics in Cognitive Science},
  volume = {2},
  number = {2},
  pages = {202--216},
  issn = {17568757, 17568765},
  doi = {10.1111/j.1756-8765.2009.01054.x},
  langid = {english},
  annotation = {166 citations (Semantic Scholar/DOI) [2022-12-11] 00147},
  file = {/Users/morteza/Documents/Zotero/storage/L8P9XSQW/Green et al. - 2010 - Perceptual Learning During Action Video Game Playi.pdf}
}

@article{green2010a,
  title = {Improved Probabilistic Inference as a General Learning Mechanism with Action Video Games},
  author = {Green, C. Shawn and Pouget, Alexandre and Bavelier, Daphne},
  year = {2010},
  month = sep,
  journal = {Current biology: CB},
  volume = {20},
  number = {17},
  pages = {1573--1579},
  issn = {1879-0445},
  doi = {10.1016/j.cub.2010.07.040},
  abstract = {Action video game play benefits performance in an array of sensory, perceptual, and attentional tasks that go well beyond the specifics of game play [1-9]. That a training regimen may induce improvements in so many different skills is notable because the majority of studies on training-induced learning report improvements on the trained task but limited transfer to other, even closely related, tasks ([10], but see also [11-13]). Here we ask whether improved probabilistic inference may explain such broad transfer. By using a visual perceptual decision making task [14, 15], the present study shows for the first time that action video game experience does indeed improve probabilistic inference. A neural model of this task [16] establishes how changing a single parameter, namely the strength of the connections between the neural layer providing the momentary evidence and the layer integrating the evidence over time, captures improvements in action-gamers behavior. These results were established in a visual, but also in a novel auditory, task, indicating generalization across modalities. Thus, improved probabilistic inference provides a general mechanism for why action video game playing enhances performance in a wide variety of tasks. In addition, this mechanism may serve as a signature of training regimens that are likely to produce transfer of learning.},
  langid = {english},
  pmcid = {PMC2956114},
  pmid = {20833324},
  keywords = {Decision Making,Humans,Learning,Probability,Visual Perception},
  annotation = {00275},
  file = {/Users/morteza/Documents/Zotero/storage/SAK3MYDP/Green et al. - 2010 - Improved probabilistic inference as a general lear.pdf}
}

@article{green2012,
  ids = {green2012b},
  title = {Learning, {{Attentional Control}}, and {{Action Video Games}}},
  author = {Green, C.S. and Bavelier, D.},
  year = {2012},
  month = mar,
  journal = {Current Biology},
  shortjournal = {Current Biology},
  volume = {22},
  number = {6},
  pages = {R197-R206},
  issn = {09609822},
  doi = {10.1016/j.cub.2012.02.012},
  langid = {english},
  annotation = {478 citations (Semantic Scholar/DOI) [2022-11-19] 00000},
  file = {/Users/morteza/Documents/Zotero/storage/DRCMHG5A/Green_Bavelier_2012_Learning, Attentional Control, and Action Video Games.pdf}
}

@article{green2012a,
  title = {The Effect of Action Video Game Experience on Task-Switching},
  author = {Green, C. Shawn and Sugarman, Michael A. and Medford, Katherine and Klobusicky, Elizabeth and Daphne Bavelier, null},
  year = {2012},
  month = may,
  journal = {Computers in Human Behavior},
  volume = {28},
  number = {3},
  pages = {984--994},
  issn = {0747-5632},
  doi = {10.1016/j.chb.2011.12.020},
  abstract = {There is now a substantial body of work demonstrating that action video game experience results in enhancements in a wide variety of perceptual skills. More recently, several groups have also demonstrated improvements in abilities that are more cognitive in nature, in particular, the ability to efficiently switch between tasks. In a series of four experiments, we add to this body of work, demonstrating that the action video game player advantage is not exclusively due to an ability to map manual responses onto arbitrary buttons, but rather generalizes to vocal responses, is not restricted to tasks that are perceptual in nature (e.g. respond to a physical dimension of the stimulus such as its color), but generalizes to more cognitive tasks (e.g. is a number odd or even), and is present whether the switch requires a goal-switch or only a motor switch. Finally, a training study establishes that the relationship between the reduction in switch cost and action game playing is causal.},
  langid = {english},
  pmcid = {PMC3292256},
  pmid = {22393270},
  annotation = {00159},
  file = {/Users/morteza/Documents/Zotero/storage/HX925A5A/Green et al. - 2012 - The effect of action video game experience on task.pdf}
}

@article{green2014,
  ids = {green2014a},
  title = {On Methodological Standards in Training and Transfer Experiments},
  author = {Green, C. Shawn and Strobach, Tilo and Schubert, Torsten},
  year = {2014},
  month = nov,
  journal = {Psychological Research},
  volume = {78},
  number = {6},
  pages = {756--772},
  issn = {0340-0727, 1430-2772},
  doi = {10.1007/s00426-013-0535-3},
  langid = {english},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-12-08]},
  file = {/Users/morteza/Documents/Zotero/storage/8ARJZ6TQ/Green et al InPress - Psych Research.pdf;/Users/morteza/Documents/Zotero/storage/8S3HLF6Z/Green et al. - 2014 - On methodological standards in training and transf.pdf}
}

@article{green2017,
  title = {Playing {{Some Video Games}} but {{Not Others Is Related}} to {{Cognitive Abilities}}: {{A Critique}} of {{Unsworth}} et al. (2015)},
  shorttitle = {Playing {{Some Video Games}} but {{Not Others Is Related}} to {{Cognitive Abilities}}},
  author = {Green, C. Shawn and Kattner, Florian and Eichenbaum, Adam and Bediou, Benoit and Adams, Deanne M. and Mayer, Richard E. and Bavelier, Daphne},
  year = {2017},
  month = may,
  journal = {Psychological Science},
  volume = {28},
  number = {5},
  pages = {679--682},
  issn = {0956-7976},
  doi = {10.1177/0956797616644837},
  langid = {english},
  keywords = {Video Recording},
  annotation = {45 citations (Semantic Scholar/DOI) [2022-12-11] 00020}
}

@article{green2019,
  title = {Improving {{Methodological Standards}} in {{Behavioral Interventions}} for {{Cognitive Enhancement}}},
  author = {Green, C. Shawn and Bavelier, Daphne and Kramer, Arthur F. and Vinogradov, Sophia and Ansorge, Ulrich and Ball, Karlene K. and Bingel, Ulrike and Chein, Jason M. and Colzato, Lorenza S. and Edwards, Jerri D. and Facoetti, Andrea and Gazzaley, Adam and Gathercole, Susan E. and Ghisletta, Paolo and Gori, Simone and Granic, Isabela and Hillman, Charles H. and Hommel, Bernhard and Jaeggi, Susanne M. and Kanske, Philipp and Karbach, Julia and Kingstone, Alan and Kliegel, Matthias and Klingberg, Torkel and K{\"u}hn, Simone and Levi, Dennis M. and Mayer, Richard E. and McLaughlin, Anne Collins and McNamara, Danielle S. and Morris, Martha Clare and Nahum, Mor and Newcombe, Nora S. and Panizzutti, Rogerio and Prakash, Ruchika Shaurya and Rizzo, Albert and Schubert, Torsten and Seitz, Aaron R. and Short, Sarah J. and Singh, Ilina and Slotta, James D. and Strobach, Tilo and Thomas, Michael S. C. and Tipton, Elizabeth and Tong, Xin and Vlach, Haley A. and Wetherell, Julie Loebach and Wexler, Anna and Witt, Claudia M.},
  year = {2019},
  month = mar,
  journal = {Journal of Cognitive Enhancement},
  volume = {3},
  number = {1},
  pages = {2--29},
  issn = {2509-3290, 2509-3304},
  doi = {10.1007/s41465-018-0115-y},
  langid = {english},
  annotation = {109 citations (Semantic Scholar/DOI) [2022-12-10]},
  file = {/Users/morteza/Documents/Zotero/storage/7JVI48HI/Shawn Green et al. - 2019 - Improving Methodological Standards in Behavioral I.pdf;/Users/morteza/Documents/Zotero/storage/IQET5CQV/Shawn Green et al_2019_Improving Methodological Standards in Behavioral Interventions for Cognitive.pdf}
}

@article{greicius2004,
  title = {Default-{{Mode Activity}} during a {{Passive Sensory Task}}: {{Uncoupled}} from {{Deactivation}} but {{Impacting Activation}}},
  shorttitle = {Default-{{Mode Activity}} during a {{Passive Sensory Task}}},
  author = {Greicius, Michael D. and Menon, Vinod},
  year = {2004},
  journal = {Journal of Cognitive Neuroscience},
  volume = {16},
  pages = {1484--1492},
  issn = {1530-8898},
  doi = {10.1162/0898929042568532},
  abstract = {Deactivation refers to increased neural activity during low demand tasks or rest compared with high-demand tasks. Several groups have reported that a particular set of brain regions, including the posterior cingulate cortex and the medial prefrontal cortex, among others, is consistently deactivated. Taken together, these typically deactivated brain regions appear to constitute a default-mode network of brain activity that predominates in the absence of a demanding external task. Examining a passive, block-design sensory task with a standard deactivation analysis (rest epochs vs. stimulus epochs), we demonstrate that the default-mode network is undetectable in one run and only partially detectable in a second run. Using independent component analysis, however, we were able to detect the full default-mode network in both runs and to demonstrate that, in the majority of subjects, it persisted across both rest and stimulus epochs, uncoupled from the task waveform, and so mostly undetectable as deactivation. We also replicate an earlier finding that the default-mode network includes the hippocampus suggesting that episodic memory is incorporated in default-mode cognitive processing. Furthermore, we show that the more a subject's default-mode activity was correlated with the rest epochs (and "deactivated" during stimulus epochs), the greater that subject's activation to the visual and auditory stimuli. We conclude that activity in the default-mode network may persist through both experimental and rest epochs if the experiment is not sufficiently challenging. Time-series analysis of default-mode activity provides a measure of the degree to which a task engages a subject and whether it is sufficient to interrupt the processes-presumably cognitive, internally generated, and involving episodic memory-mediated by the default-mode network. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
  keywords = {Cingulate Cortex,Cognitive Processes,Electrical Activity,Neural Pathways,Prefrontal Cortex},
  annotation = {701 citations (Semantic Scholar/DOI) [2022-11-29]}
}

@article{gu2015,
  title = {Controllability of Structural Brain Networks},
  author = {Gu, Shi and Pasqualetti, Fabio and Cieslak, Matthew and Telesford, Qawi K. and Yu, Alfred B. and Kahn, Ari E. and Medaglia, John D. and Vettel, Jean M. and Miller, Michael B. and Grafton, Scott T. and Bassett, Danielle S.},
  year = {2015},
  month = oct,
  journal = {Nature Communications},
  volume = {6},
  pages = {8414},
  issn = {2041-1723},
  doi = {10.1038/ncomms9414},
  abstract = {Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.},
  langid = {english},
  pmcid = {PMC4600713},
  pmid = {26423222},
  keywords = {Adult,Brain,Cognition,Female,Humans,Male,Nerve Net,Young Adult},
  annotation = {514 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/MUXWXPFJ/Gu et al_2015_Controllability of structural brain networks.pdf}
}

@misc{guest2021,
  title = {On Logical Inference over Brains, Behaviour, and Artificial Neural Networks},
  author = {Guest, Olivia and Martin, Andrea E.},
  year = {2021},
  month = oct,
  publisher = {{PsyArXiv}},
  doi = {10.31234/osf.io/tbmcg},
  abstract = {In the cognitive, computational, and neuro- sciences, practitioners often reason about what computational models represent or learn, as well as what algorithm is instantiated. The putative goal of such reasoning is to generalize claims about the model in question, to claims about the mind and brain, and the neurocognitive capacities of those systems. Such inference is often based on a model's performance on a task, and whether that performance approximates human behavior or brain activity. Here we demonstrate how such argumentation problematizes the relationship between models and their targets; we place emphasis on artificial neural networks (ANNs), though any theory-brain relationship that falls into the same schema of reasoning is at risk. In this paper, we model inferences from ANNs to brains and back within a formal framework \textemdash{} metatheoretical calculus \textemdash{} in order to initiate a dialogue on both how models are broadly understood and used, and on how to best formally characterise them and their functions. To these ends, we express claims from the published record about models' successes and failures in first-order logic. Our proposed formalisation describes the decision-making processes enacted by scientists to adjudicate over theories. We demonstrate that formalising the argumentation in the literature can uncover potential deep issues about how theory is related to phenomena. We discuss what this means broadly for research in cognitive science, neuroscience, and psychology; what it means for models when they lose the ability to mediate between theory and data in a meaningful way; and what this means for the metatheoretical calculus our fields deploy when performing high-level scientific inference.},
  langid = {american},
  keywords = {Cognitive Neuroscience,Cognitive Psychology,Computational Neuroscience,Meta-science,Neuroscience,Social and Behavioral Sciences,Theory and Philosophy of Science},
  annotation = {9 citations (Semantic Scholar/DOI) [2023-02-15]},
  file = {/Users/morteza/Documents/Zotero/storage/QIVAAV75/Guest_Martin_2021_On logical inference over brains, behaviour, and artificial neural networks.pdf}
}

@article{gullich2018,
  title = {Sport-Specific and Non-Specific Practice of Strong and Weak Responders in Junior and Senior Elite Athletics \textendash{} {{A}} Matched-Pairs Analysis},
  author = {G{\"u}llich, Arne},
  year = {2018},
  month = oct,
  journal = {Journal of Sports Sciences},
  volume = {36},
  number = {19},
  pages = {2256--2264},
  issn = {0264-0414, 1466-447X},
  doi = {10.1080/02640414.2018.1449089},
  langid = {english},
  annotation = {35 citations (Semantic Scholar/DOI) [2022-12-14]}
}

@article{habibi2017,
  title = {Deep Learning with Word Embeddings Improves Biomedical Named Entity Recognition},
  author = {Habibi, Maryam and Weber, Leon and Neves, Mariana and Wiegandt, David Luis and Leser, Ulf},
  year = {2017},
  month = jul,
  journal = {Bioinformatics},
  volume = {33},
  number = {14},
  pages = {i37-i48},
  issn = {1367-4803},
  doi = {10.1093/bioinformatics/btx228},
  abstract = {Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult.We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5\% above that of the baselines, mostly due to a sharp increase in recall.The source code for LSTM-CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github.io/corpora/.},
  annotation = {409 citations (Semantic Scholar/DOI) [2022-11-06]},
  file = {/Users/morteza/Documents/Zotero/storage/V3J8AYYJ/Habibi et al_2017_Deep learning with word embeddings improves biomedical named entity recognition.pdf}
}

@article{hampshire2012,
  title = {Fractionating {{Human Intelligence}}},
  author = {Hampshire, Adam and Highfield, Roger~R. and Parkin, Beth~L. and Owen, Adrian~M.},
  year = {2012},
  month = dec,
  journal = {Neuron},
  volume = {76},
  number = {6},
  pages = {1225--1237},
  issn = {08966273},
  doi = {10.1016/j.neuron.2012.06.022},
  langid = {english},
  annotation = {00240}
}

@article{hasson2009,
  title = {Task-Dependent Organization of Brain Regions Active during Rest},
  author = {Hasson, Uri and Nusbaum, Howard C. and Small, Steven L.},
  year = {2009},
  month = jun,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {106},
  number = {26},
  pages = {10841--10846},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.0903253106},
  abstract = {The human brain demonstrates complex yet systematic patterns of neural activity at rest. We examined whether functional connectivity among those brain regions typically active during rest depends on ongoing and recent task demands and individual differences. We probed the temporal coordination among these regions during periods of language comprehension and during the rest periods that followed comprehension. Our findings show that the topography of this ``rest network'' varies with exogenous processing demands. The network encompassed more highly interconnected regions during rest than during listening, but also when listening to unsurprising vs. surprising information. Furthermore, connectivity patterns during rest varied as a function of recent listening experience. Individual variability in connectivity strength was associated with cognitive function: more attentive comprehenders demonstrated weaker connectivity during language comprehension, and a greater differentiation between connectivity during comprehension and rest. The regions we examined have generally been thought to form an invariant physiological and functional network whose activity reflects spontaneous cognitive processes. Our findings suggest that their function extends beyond the mediation of unconstrained thought, and that they play an important role in higher-level cognitive function.},
  langid = {english},
  annotation = {180 citations (Semantic Scholar/DOI) [2022-12-07]},
  file = {/Users/morteza/Documents/Zotero/storage/GB2ZG34B/Hasson et al. - 2009 - Task-dependent organization of brain regions activ.pdf}
}

@article{haykin2012,
  title = {Cognitive Control},
  author = {Haykin, Simon and Fatemi, Mehdi and Setoodeh, Peyman and Xue, Yanbo},
  year = {2012},
  journal = {Proceedings of the IEEE},
  volume = {100},
  number = {12},
  pages = {3156--3169},
  issn = {0018-9219},
  doi = {10.1109/jproc.2012.2215773},
  abstract = {This paper is inspired by how cognitive control manifests itself in the human brain and does so in a remarkable way. It addresses the many facets involved in the control of directed information flow in a dynamic system, culminating in the notion of information gap, defined as the difference between relevant information (useful part of what is extracted from the incoming measurements) and sufficient information representing the information needed for achieving minimal risk. The notion of information gap leads naturally to how cognitive control can itself be defined. Then, another important idea is described, namely the two-state model, in which one is the system's state and the other is the entropic state that provides an essential metric for quantifying the information gap. The entropic state is computed in the perceptual part (i.e., perceptor) of the dynamic system and sent to the controller directly as feedback information. This feedback information provides the cognitive controller the information needed about the environment and the system to bring reinforcement leaning into play; reinforcement learning (RL), incorporating planning as an integral part, is at the very heart of cognitive control. The stage is now set for a computational experiment, involving cognitive radar wherein the cognitive controller is enabled to control the receiver via the environment. The experiment demonstrates how RL provides the mechanism for improved utilization of computational resources, and yet is able to deliver good performance through the use of planning. The paper finishes with concluding remarks.},
  annotation = {00087}
}

@article{hebart2018,
  title = {The Representational Dynamics of Task and Object Processing in Humans},
  author = {Hebart, Martin N and Bankson, Brett B and Harel, Assaf and Baker, Chris I and Cichy, Radoslaw M},
  editor = {Culham, Jody C},
  year = {2018},
  month = jan,
  journal = {eLife},
  volume = {7},
  pages = {e32816},
  publisher = {{eLife Sciences Publications, Ltd}},
  issn = {2050-084X},
  doi = {10.7554/eLife.32816},
  abstract = {Despite the importance of an observer's goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and multivariate techniques, we studied the spatial and temporal dynamics of task and object processing. Our results reveal a sequence of separate but overlapping task-related processes spread across frontoparietal and occipitotemporal cortex. Task exhibited late effects on object processing by selectively enhancing task-relevant object features, with limited impact on the overall pattern of object representations. Combining MEG and fMRI data, we reveal a parallel rise in task-related signals throughout the cerebral cortex, with an increasing dominance of task over object representations from early to higher visual areas. Collectively, our results reveal the complex dynamics underlying task and object representations throughout human cortex.},
  keywords = {fMRI,MEG,MEG-fMRI fusion,multivariate analysis,object processing,task context},
  annotation = {101 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/A7ER8R58/Hebart et al_2018_The representational dynamics of task and object processing in humans.pdf}
}

@article{herd2013,
  title = {Strategic Cognitive Sequencing: A Computational Cognitive Neuroscience Approach},
  shorttitle = {Strategic Cognitive Sequencing},
  author = {Herd, Seth A. and Krueger, Kai A. and Kriete, Trenton E. and Huang, Tsung-Ren and Hazy, Thomas E. and O'Reilly, Randall C.},
  year = {2013},
  journal = {Computational Intelligence and Neuroscience},
  volume = {2013},
  pages = {149329},
  issn = {1687-5273},
  doi = {10.1155/2013/149329},
  abstract = {We address strategic cognitive sequencing, the "outer loop" of human cognition: how the brain decides what cognitive process to apply at a given moment to solve complex, multistep cognitive tasks. We argue that this topic has been neglected relative to its importance for systematic reasons but that recent work on how individual brain systems accomplish their computations has set the stage for productively addressing how brain regions coordinate over time to accomplish our most impressive thinking. We present four preliminary neural network models. The first addresses how the prefrontal cortex (PFC) and basal ganglia (BG) cooperate to perform trial-and-error learning of short sequences; the next, how several areas of PFC learn to make predictions of likely reward, and how this contributes to the BG making decisions at the level of strategies. The third models address how PFC, BG, parietal cortex, and hippocampus can work together to memorize sequences of cognitive actions from instruction (or "self-instruction"). The last shows how a constraint satisfaction process can find useful plans. The PFC maintains current and goal states and associates from both of these to find a "bridging" state, an abstract plan. We discuss how these processes could work together to produce strategic cognitive sequencing and discuss future directions in this area.},
  langid = {english},
  pmcid = {PMC3722785},
  pmid = {23935605},
  keywords = {Brain,Cognition,Humans,Models; Neurological,Neural Networks; Computer,Neurosciences},
  file = {/Users/morteza/Documents/Zotero/storage/6EANA6EV/Herd et al_2013_Strategic cognitive sequencing.pdf}
}

@article{Hill1983a,
  title = {A Computational Model of Language Acquisition in the Two-Year Old},
  author = {Hill, J. A. C.},
  year = {1983},
  journal = {Cognition and Brain Theory},
  volume = {6},
  pages = {287--317}
}

@article{ho2022,
  title = {Cognitive {{Science}} as a {{Source}} of {{Forward}} and {{Inverse Models}} of {{Human Decisions}} for {{Robotics}} and {{Control}}},
  author = {Ho, Mark K. and Griffiths, Thomas L.},
  year = {2022},
  month = may,
  journal = {Annual Review of Control, Robotics, and Autonomous Systems},
  volume = {5},
  number = {1},
  pages = {33--53},
  issn = {2573-5144, 2573-5144},
  doi = {10.1146/annurev-control-042920-015547},
  abstract = {Those designing autonomous systems that interact with humans will invariably face questions about how humans think and make decisions. Fortunately, computational cognitive science offers insight into human decision-making using tools that will be familiar to those with backgrounds in optimization and control (e.g., probability theory, statistical machine learning, and reinforcement learning). Here, we review some of this work, focusing on how cognitive science can provide forward models of human decision-making and inverse models of how humans think about others' decision-making. We highlight relevant recent developments, including approaches that synthesize black box and theory-driven modeling, accounts that recast heuristics and biases as forms of bounded optimality, and models that characterize human theory of mind and communication in decision-theoretic terms. In doing so, we aim to provide readers with a glimpse of the range of frameworks, methodologies, and actionable insights that lie at the intersection of cognitive science and control research.},
  langid = {english},
  annotation = {7 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/5ZRJSU8W/Ho and Griffiths - 2022 - Cognitive Science as a Source of Forward and Inver.pdf}
}

@article{hoffman2020,
  title = {Acme: {{A}} Research Framework for Distributed Reinforcement Learning},
  author = {Hoffman, Matt and Shahriari, Bobak and Aslanides, John and {Barth-Maron}, Gabriel and Behbahani, Feryal and Norman, Tamara and Abdolmaleki, Abbas and Cassirer, Albin and Yang, Fan and Baumli, Kate and others},
  year = {2020},
  journal = {arXiv preprint arXiv:2006.00979},
  eprint = {2006.00979},
  eprinttype = {arxiv},
  archiveprefix = {arXiv}
}

@article{holmes2009,
  ids = {holmes2009a},
  title = {Can {{Playing}} the {{Computer Game}} ``{{Tetris}}'' {{Reduce}} the {{Build-Up}} of {{Flashbacks}} for {{Trauma}}? {{A Proposal}} from {{Cognitive Science}}},
  shorttitle = {Can {{Playing}} the {{Computer Game}} ``{{Tetris}}'' {{Reduce}} the {{Build-Up}} of {{Flashbacks}} for {{Trauma}}?},
  author = {Holmes, Emily A. and James, Ella L. and {Coode-Bate}, Thomas and Deeprose, Catherine},
  year = {2009},
  month = jan,
  journal = {PLOS ONE},
  volume = {4},
  number = {1},
  pages = {e4153},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0004153},
  abstract = {Background Flashbacks are the hallmark symptom of Posttraumatic Stress Disorder (PTSD). Although we have successful treatments for full-blown PTSD, early interventions are lacking. We propose the utility of developing a `cognitive vaccine' to prevent PTSD flashback development following exposure to trauma. Our theory is based on two key findings: 1) Cognitive science suggests that the brain has selective resources with limited capacity; 2) The neurobiology of memory suggests a 6-hr window to disrupt memory consolidation. The rationale for a `cognitive vaccine' approach is as follows: Trauma flashbacks are sensory-perceptual, visuospatial mental images. Visuospatial cognitive tasks selectively compete for resources required to generate mental images. Thus, a visuospatial computer game (e.g. ``Tetris'') will interfere with flashbacks. Visuospatial tasks post-trauma, performed within the time window for memory consolidation, will reduce subsequent flashbacks. We predicted that playing ``Tetris'' half an hour after viewing trauma would reduce flashback frequency over 1-week. Methodology/Principal Findings The Trauma Film paradigm was used as a well-established experimental analog for Post-traumatic Stress. All participants viewed a traumatic film consisting of scenes of real injury and death followed by a 30-min structured break. Participants were then randomly allocated to either a no-task or visuospatial (``Tetris'') condition which they undertook for 10-min. Flashbacks were monitored for 1-week. Results indicated that compared to the no-task condition, the ``Tetris'' condition produced a significant reduction in flashback frequency over 1-week. Convergent results were found on a clinical measure of PTSD symptomatology at 1-week. Recognition memory between groups did not differ significantly. Conclusions/Significance Playing ``Tetris'' after viewing traumatic material reduces unwanted, involuntary memory flashbacks to that traumatic film, leaving deliberate memory recall of the event intact. Pathological aspects of human memory in the aftermath of trauma may be malleable using non-invasive, cognitive interventions. This has implications for a novel avenue of preventative treatment development, much-needed as a crisis intervention for the aftermath of traumatic events.},
  langid = {english},
  keywords = {Cognition,Computer games,Memory,Memory consolidation,Post-traumatic stress disorder,Recall (memory),Vision,Working memory},
  annotation = {00293}
}

@article{hopf2000,
  title = {Neural Sources of Focused Attention in Visual Search},
  author = {Hopf, J. M. and Luck, S. J. and Girelli, M. and Hagner, T. and Mangun, G. R. and Scheich, H. and Heinze, H. J.},
  year = {2000},
  month = dec,
  journal = {Cerebral Cortex (New York, N.Y.: 1991)},
  volume = {10},
  number = {12},
  pages = {1233--1241},
  issn = {1047-3211},
  abstract = {Previous studies of visual search in humans using event-related potentials (ERPs) have revealed an ERP component called 'N2pc' (180-280 ms) that reflects the focusing of attention onto potential target items in the search array. The present study was designed to localize the neuroanatomical sources of this component by means of magnetoencephalographic (MEG) recordings, which provide greater spatial precision than ERP recordings. MEG recordings were obtained with an array of 148 magnetometers from six normal adult subjects, one of whom was tested in multiple sessions so that both single-subject and group analyses could be performed. Source localization procedures revealed that the N2pc is composed of two distinct neural responses, an early parietal source (180-200 ms) and a later occipito-temporal source (220-240 ms). These findings are consistent with the proposal that parietal areas are used to initiate a shift of attention within a visual search array and that the focusing of attention is implemented by extrastriate areas of the occipital and inferior temporal cortex.},
  langid = {english},
  pmid = {11073872},
  keywords = {Adult,Attention,Brain,Evoked Potentials,Female,Humans,Magnetoencephalography,Male,Occipital Lobe,Parietal Lobe,Reaction Time,Space Perception,Temporal Lobe},
  annotation = {00392}
}

@article{howard-jones2016,
  title = {Reward, Learning and Games},
  author = {{Howard-Jones}, Paul A. and Jay, Tim},
  year = {2016},
  month = aug,
  journal = {Current Opinion in Behavioral Sciences},
  volume = {10},
  pages = {65--72},
  issn = {23521546},
  doi = {10.1016/j.cobeha.2016.04.015},
  langid = {english},
  annotation = {00012},
  file = {/Users/morteza/Documents/Zotero/storage/E6W9B6Q7/howard-jones2016.pdf}
}

@article{hsu2015,
  title = {Delayed Enhancement of Multitasking Performance: {{Effects}} of Anodal Transcranial Direct Current Stimulation on the Prefrontal Cortex},
  shorttitle = {Delayed Enhancement of Multitasking Performance},
  author = {Hsu, Wan-Yu and Zanto, Theodore P. and Anguera, Joaquin A. and Lin, Yung-Yang and Gazzaley, Adam},
  year = {2015},
  month = aug,
  journal = {Cortex},
  volume = {69},
  pages = {175--185},
  issn = {00109452},
  doi = {10.1016/j.cortex.2015.05.014},
  langid = {english},
  annotation = {00053}
}

@article{hutzler2014,
  title = {Reverse Inference Is Not a Fallacy per Se: {{Cognitive}} Processes Can Be Inferred from Functional Imaging Data},
  shorttitle = {Reverse Inference Is Not a Fallacy per Se},
  author = {Hutzler, Florian},
  year = {2014},
  month = jan,
  journal = {NeuroImage},
  volume = {84},
  pages = {1061--1069},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2012.12.075},
  langid = {english},
  annotation = {153 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/ARL6RRN4/Hutzler - 2014 - Reverse inference is not a fallacy per se Cogniti.pdf}
}

@article{ie2019,
  title = {Recsim: {{A}} Configurable Simulation Platform for Recommender Systems},
  author = {Ie, Eugene and Hsu, Chih-wei and Mladenov, Martin and Jain, Vihan and Narvekar, Sanmit and Wang, Jing and Wu, Rui and Boutilier, Craig},
  year = {2019},
  journal = {arXiv preprint arXiv:1909.04847},
  eprint = {1909.04847},
  eprinttype = {arxiv},
  archiveprefix = {arXiv}
}

@article{iyadurai2018,
  title = {Preventing Intrusive Memories after Trauma via a Brief Intervention Involving {{Tetris}} Computer Game Play in the Emergency Department: A Proof-of-Concept Randomized Controlled Trial},
  shorttitle = {Preventing Intrusive Memories after Trauma via a Brief Intervention Involving {{Tetris}} Computer Game Play in the Emergency Department},
  author = {Iyadurai, L. and Blackwell, S. E. and {Meiser-Stedman}, R. and Watson, P. C. and Bonsall, M. B. and Geddes, J. R. and Nobre, A. C. and Holmes, E. A.},
  year = {2018},
  month = mar,
  journal = {Molecular Psychiatry},
  volume = {23},
  number = {3},
  pages = {674--682},
  issn = {1476-5578},
  doi = {10.1038/mp.2017.23},
  abstract = {After psychological trauma, recurrent intrusive visual memories may be distressing and disruptive. Preventive interventions post trauma are lacking. Here we test a behavioural intervention after real-life trauma derived from cognitive neuroscience. We hypothesized that intrusive memories would be significantly reduced in number by an intervention involving a computer game with high visuospatial demands (Tetris), via disrupting consolidation of sensory elements of trauma memory. The Tetris-based intervention (trauma memory reminder cue plus c. 20 min game play) vs attention-placebo control (written activity log for same duration) were both delivered in an emergency department within 6 h of a motor vehicle accident. The randomized controlled trial compared the impact on the number of intrusive trauma memories in the subsequent week (primary outcome). Results vindicated the efficacy of the Tetris-based intervention compared with the control condition: there were fewer intrusive memories overall, and time-series analyses showed that intrusion incidence declined more quickly. There were convergent findings on a measure of clinical post-trauma intrusion symptoms at 1 week, but not on other symptom clusters or at 1 month. Results of this proof-of-concept study suggest that a larger trial, powered to detect differences at 1 month, is warranted. Participants found the intervention easy, helpful and minimally distressing. By translating emerging neuroscientific insights and experimental research into the real world, we offer a promising new low-intensity psychiatric intervention that could prevent debilitating intrusive memories following trauma.},
  copyright = {2017 Nature Publishing Group},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/ZXTV8XNZ/Iyadurai et al. - 2018 - Preventing intrusive memories after trauma via a b.pdf;/Users/morteza/Documents/Zotero/storage/5IRHAT7A/mp201723.html}
}

@article{jaeggi2008,
  ids = {jaeggi2008a},
  title = {Improving Fluid Intelligence with Training on Working Memory},
  author = {Jaeggi, Susanne M. and Buschkuehl, Martin and Jonides, John and Perrig, Walter J.},
  year = {2008},
  journal = {Proceedings of the National Academy of Sciences},
  volume = {105},
  number = {19},
  pages = {6829--6833},
  annotation = {01918},
  file = {/Users/morteza/Documents/Zotero/storage/RJ27DYGT/jaeggi2008.pdf;/Users/morteza/Documents/Zotero/storage/WQUAXBRE/Jaeggi et al. - 2008 - Improving fluid intelligence with training on work.pdf;/Users/morteza/Documents/Zotero/storage/YCP6D7KC/PNAS-2008-Jaeggi-6829-33.pdf}
}

@article{jaeggi2010,
  title = {The Concurrent Validity of the {{N-back}} Task as a Working Memory Measure},
  author = {Jaeggi, Susanne M. and Buschkuehl, Martin and Perrig, Walter J. and Meier, Beat},
  year = {2010},
  month = may,
  journal = {Memory},
  volume = {18},
  number = {4},
  pages = {394--412},
  issn = {0965-8211, 1464-0686},
  doi = {10.1080/09658211003702171},
  langid = {english},
  annotation = {00483}
}

@book{jensen2006,
  title = {Clocking the Mind: Mental Chronometry and Individual Differences},
  shorttitle = {Clocking the Mind},
  author = {Jensen, Arthur Robert},
  year = {2006},
  edition = {1st ed},
  publisher = {{Elsevier}},
  address = {{Amsterdam ; Boston ; London}},
  isbn = {978-0-08-044939-5},
  lccn = {QP445 .J46 2006},
  keywords = {Cognition,methods,Neuropsychology,physiology,Reaction Time,Time perception,Time Perception},
  annotation = {OCLC: ocm67393035}
}

@article{jiang2018,
  title = {Integrated Externally and Internally Generated Task Predictions Jointly Guide Cognitive Control in Prefrontal Cortex},
  author = {Jiang, Jiefeng and Wagner, Anthony D and Egner, Tobias},
  year = {2018},
  month = aug,
  journal = {eLife},
  volume = {7},
  pages = {e39497},
  issn = {2050-084X},
  doi = {10.7554/eLife.39497},
  abstract = {Cognitive control proactively configures information processing to suit expected task demands. Predictions of forthcoming demand can be driven by explicit external cues or be generated internally, based on past experience (cognitive history). However, it is not known whether and how the brain reconciles these two sources of information to guide control. Pairing a probabilistic task-switching paradigm with computational modeling, we found that external and internally generated predictions jointly guide task preparation, with a bias for internal predictions. Using model-based neuroimaging, we then show that the two sources of task prediction are integrated in dorsolateral prefrontal cortex, and jointly inform a representation of the likelihood of a change in task demand, encoded in frontoparietal cortex. Upon task-stimulus onset, dorsomedial prefrontal cortex encoded the need for reactive task-set adjustment. These data reveal how the human brain integrates external cues and cognitive history to prepare for an upcoming task.},
  langid = {english},
  annotation = {21 citations (Semantic Scholar/DOI) [2022-12-12]},
  file = {/Users/morteza/Documents/Zotero/storage/TJ8559GX/Jiang et al. - 2018 - Integrated externally and internally generated tas.pdf}
}

@article{jolly2019,
  title = {The Flatland Fallacy: {{Moving}} beyond {{Low}}\textendash{{Dimensional}} Thinking},
  author = {Jolly, Eshin and Chang, Luke J},
  year = {2019},
  journal = {Topics in Cognitive Science},
  volume = {11},
  number = {2},
  pages = {433--454},
  issn = {1756-8757},
  doi = {10.1111/tops.12404},
  abstract = {Psychology is a complicated science. It has no general axioms or mathematical proofs, is rarely directly observable, and is the only discipline in which the subject matter (i.e., human psychological phenomena) is also the tool of investigation. Like the Flatlanders in Edwin Abbot's famous short story (1884), we may be led to believe that the parsimony offered by our low-dimensional theories reflects the reality of a much higher-dimensional problem. Here we contend that this ``Flatland fallacy'' leads us to seek out simplified explanations of complex phenomena, limiting our capacity as scientists to build and communicate useful models of human psychology. We suggest that this fallacy can be overcome through (a) the use of quantitative models, which force researchers to formalize their theories to overcome this fallacy, and (b) improved quantitative training, which can build new norms for conducting psychological research. In rebellion against low-dimensional (e.g., two-factor) theories in psychology, the authors make the case for high-dimensional theories. This change in perspective requires a shift towards a focus on computation and quantitative reasoning.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2019/Jolly\%202019.pdf},
  pmid = {30576066},
  keywords = {Methods},
  annotation = {00034}
}

@inproceedings{juvina2007,
  title = {Modeling Control Strategies in the {{N-Back}} Task},
  booktitle = {Proceedings of the Eight {{International Conference}} on {{Cognitive Modeling}}},
  author = {Juvina, I and Taatgen, N.A.},
  year = {2007},
  pages = {73--78},
  publisher = {{Psychology Press}},
  langid = {english}
}

@article{karimpur2015,
  title = {The {{Future}} of {{Action Video Games}} in {{Psychological Research}} and {{Application}}},
  author = {Karimpur, Harun and Hamburger, Kai},
  year = {2015},
  month = nov,
  journal = {Frontiers in Psychology},
  volume = {6},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2015.01747},
  annotation = {00006},
  file = {/Users/morteza/Documents/Zotero/storage/2E9QWU32/Karimpur and Hamburger - 2015 - The Future of Action Video Games in Psychological .pdf}
}

@article{katsyri2013,
  title = {Just Watching the Game Ain't Enough: Striatal {{fMRI}} Reward Responses to Successes and Failures in a Video Game during Active and Vicarious Playing},
  shorttitle = {Just Watching the Game Ain't Enough},
  author = {K{\"a}tsyri, Jari and Hari, Riitta and Ravaja, Niklas and Nummenmaa, Lauri},
  year = {2013},
  journal = {Frontiers in Human Neuroscience},
  volume = {7},
  issn = {1662-5161},
  doi = {10.3389/fnhum.2013.00278},
  annotation = {00046},
  file = {/Users/morteza/Documents/Zotero/storage/DQBZ6K5L/kätsyri2013.pdf}
}

@article{katz2014,
  title = {Differential Effect of Motivational Features on Training Improvements in School-Based Cognitive Training},
  author = {Katz, Benjamin and Jaeggi, Susanne and Buschkuehl, Martin and Stegman, Alyse and Shah, Priti},
  year = {2014},
  month = apr,
  journal = {Frontiers in Human Neuroscience},
  volume = {8},
  issn = {1662-5161},
  doi = {10.3389/fnhum.2014.00242},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/RAABZL3E/fnhum-08-00242.pdf}
}

@article{katz2018,
  title = {How to Play 20 Questions with Nature and Lose: {{Reflections}} on 100 Years of Brain-Training Research},
  shorttitle = {How to Play 20 Questions with Nature and Lose},
  author = {Katz, Benjamin and Shah, Priti and Meyer, David E.},
  year = {2018},
  month = oct,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {115},
  number = {40},
  pages = {9897--9904},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1617102114},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/XLT66UJD/Katz et al. - 2018 - How to play 20 questions with nature and lose Ref.pdf}
}

@incollection{kawamura2015,
  title = {Implementation of {{Cognitive Controls}} for {{Robots}}},
  booktitle = {Household {{Service Robotics}}},
  author = {Kawamura, Kazuhiko and Gordon, Stephen M. and Ratanaswasd, Palis and Garber, Christopher~S. and Erdemir, Erdem},
  year = {2015},
  pages = {429--454},
  publisher = {{Elsevier}},
  doi = {10.1016/B978-0-12-800881-2.00019-0},
  isbn = {978-0-12-800881-2},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/7ET79HN8/Kawamura et al. - 2015 - Implementation of Cognitive Controls for Robots.pdf}
}

@article{kennedy2021,
  title = {Text Analysis for Psychology: {{Methods}}, Principles, and Practices},
  author = {Kennedy, Brendan and Ashokkumar, Ashwini and Boyd, Ryan L and Dehghani, Morteza},
  year = {2021},
  doi = {10.31234/osf.io/h2b8t},
  abstract = {Due to the explosion of new sources of human language data and the rapid progression of computational methods for extracting meaning from natural language, language analysis is a promising, though complicated, category of psychological research. In this chapter, we give a modern perspective on language analysis as it applies to psychology, uniting historical context, the diverse range of domains studied in psychology via language, and the methodological rigor of natural language processing (NLP) and machine learning. Top\textendash down methods (e.g., dictionary approaches, text annotation) are presented alongside bottom\textendash up methods (e.g., topic modeling, word embedding, language modeling) in order to give the reader a comprehensive grounding in the tools available and the recommended practices involved in applying them. We conclude with a view of the future of language analysis, specifically the ways in which psychology and NLP will continue to co-develop.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/Text\%20Analysis\%20for\%20Psychology\textsubscript{\%}20Methods,\%20Principles,\%20and\%20Practices.pdf},
  annotation = {00000}
}

@article{kim2015,
  title = {Real-{{Time Strategy Video Game Experience}} and {{Visual Perceptual Learning}}},
  author = {Kim, Y.-H. and Kang, D.-W. and Kim, D. and Kim, H.-J. and Sasaki, Y. and Watanabe, T.},
  year = {2015},
  month = jul,
  journal = {Journal of Neuroscience},
  volume = {35},
  number = {29},
  pages = {10485--10492},
  issn = {0270-6474, 1529-2401},
  doi = {10.1523/JNEUROSCI.3340-14.2015},
  langid = {english},
  annotation = {00027}
}

@article{kim2017,
  title = {Bridging the Gap: {{Incorporating}} a Semantic Similarity Measure for Effectively Mapping {{PubMed}} Queries to Documents},
  shorttitle = {Bridging the Gap},
  author = {Kim, Sun and Fiorini, Nicolas and Wilbur, W. John and Lu, Zhiyong},
  year = {2017},
  month = nov,
  journal = {Journal of Biomedical Informatics},
  volume = {75},
  pages = {122--127},
  issn = {1532-0464},
  doi = {10.1016/j.jbi.2017.09.014},
  abstract = {The main approach of traditional information retrieval (IR) is to examine how many words from a query appear in a document. A drawback of this approach, however, is that it may fail to detect relevant documents where no or only few words from a query are found. The semantic analysis methods such as LSA (latent semantic analysis) and LDA (latent Dirichlet allocation) have been proposed to address the issue, but their performance is not superior compared to common IR approaches. Here we present a query-document similarity measure motivated by the Word Mover's Distance. Unlike other similarity measures, the proposed method relies on neural word embeddings to compute the distance between words. This process helps identify related words when no direct matches are found between a query and a document. Our method is efficient and straightforward to implement. The experimental results on TREC Genomics data show that our approach outperforms the BM25 ranking function by an average of 12\% in mean average precision. Furthermore, for a real-world dataset collected from the PubMed\textregistered{} search logs, we combine the semantic measure with BM25 using a learning to rank method, which leads to improved ranking scores by up to 25\%. This experiment demonstrates that the proposed approach and BM25 nicely complement each other and together produce superior performance.},
  langid = {english},
  keywords = {Learning to rank,PubMed literature search,Semantic similarity,Word embeddings,Word Mover’s Distance},
  annotation = {35 citations (Semantic Scholar/DOI) [2022-11-06]},
  file = {/Users/morteza/Documents/Zotero/storage/M93MDV9V/Kim et al_2017_Bridging the gap.pdf}
}

@article{kiraly2017,
  title = {Intense Video Gaming Is Not Essentially Problematic.},
  author = {Kir{\'a}ly, Orsolya and T{\'o}th, D{\'e}nes and Urb{\'a}n, R{\'o}bert and Demetrovics, Zsolt and Maraz, Aniko},
  year = {2017},
  month = nov,
  journal = {Psychology of Addictive Behaviors},
  volume = {31},
  number = {7},
  pages = {807--817},
  issn = {1939-1501, 0893-164X},
  doi = {10.1037/adb0000316},
  langid = {english},
  keywords = {\#nosource},
  annotation = {00000}
}

@article{koepp1998,
  title = {Evidence for Striatal Dopamine Release during a Video Game},
  author = {Koepp, M. J. and Gunn, R. N. and Lawrence, A. D. and Cunningham, V. J. and Dagher, A. and Jones, T. and Brooks, D. J. and Bench, C. J. and Grasby, P. M.},
  year = {1998},
  month = may,
  journal = {Nature},
  volume = {393},
  number = {6682},
  pages = {266--268},
  issn = {0028-0836, 1476-4687},
  doi = {10.1038/30498},
  langid = {english},
  annotation = {01314}
}

@article{kok2001,
  title = {On the Utility of {{P3}} Amplitude as a Measure of Processing Capacity},
  author = {Kok, A.},
  year = {2001},
  month = may,
  journal = {Psychophysiology},
  volume = {38},
  number = {3},
  pages = {557--577},
  issn = {0048-5772},
  abstract = {The present review focuses on the utility of the amplitude of P3 of as a measure of processing capacity and mental workload. The paper starts with a brief outline of the conceptual framework underlying the relationship between P3 amplitude and task demands, and the cognitive task manipulations that determine demands on capacity. P3 amplitude results are then discussed on the basis of an extensive review of the relevant literature. It is concluded that although it has often been assumed that P3 amplitude depends on the capacity for processing task relevant stimuli, the utility of P3 amplitude as a sensitive and diagnostic measure of processing capacity remains limited. The major factor that prompts this conclusion is that the two principal task variables that have been used to manipulate capacity allocation, namely task difficulty and task emphasis, have opposite effects on the amplitude of P3. I suggest that this is because, in many tasks, an increase in difficulty transforms the structure or actual content of the flow of information in the processing systems, thereby interfering with the very processes that underlie P3 generation. Finally, in an attempt to theoretically integrate the results of the reviewed studies, it is proposed that P3 amplitude reflects activation of elements in a event-categorization network that is controlled by the joint operation of attention and working memory.},
  langid = {english},
  pmid = {11352145},
  keywords = {Electroencephalography,Evoked Potentials,Humans,Mental Processes,Psychomotor Performance},
  annotation = {00000}
}

@article{kononova2015,
  title = {Why Do We Multitask with Media? {{Predictors}} of Media Multitasking among {{Internet}} Users in the {{United States}} and {{Taiwan}}},
  shorttitle = {Why Do We Multitask with Media?},
  author = {Kononova, Anastasia and Chiang, Yi-Hsuan},
  year = {2015},
  month = sep,
  journal = {Computers in Human Behavior},
  volume = {50},
  pages = {31--41},
  issn = {07475632},
  doi = {10.1016/j.chb.2015.03.052},
  langid = {english}
}

@article{kotseruba2018,
  ids = {kotseruba2020},
  title = {40 Years of Cognitive Architectures: Core Cognitive Abilities and Practical Applications},
  author = {Kotseruba, Iuliia and Tsotsos, John K},
  year = {2018},
  journal = {Artificial Intelligence Review},
  volume = {53},
  number = {1},
  pages = {17--94},
  issn = {0269-2821},
  doi = {10.1007/s10462-018-9646-y},
  abstract = {In this paper we present a broad overview of the last 40 years of research on cognitive architectures. To date, the number of existing architectures has reached several hundred, but most of the existing surveys do not reflect this growth and instead focus on a handful of well-established architectures. In this survey we aim to provide a more inclusive and high-level overview of the research on cognitive architectures. Our final set of 84 architectures includes 49 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, action selection, memory, learning, reasoning and metareasoning. In order to assess the breadth of practical applications of cognitive architectures we present information on over 900 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight the overall trends in the development of the field. In addition to summarizing the current state-of-the-art in the cognitive architecture research, this survey describes a variety of methods and ideas that have been tried and their relative success in modeling human cognitive abilities, as well as which aspects of cognitive behavior need more research with respect to their mechanistic counterparts and thus can further inform how cognitive science might progress.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2018/Kotseruba\%202018.pdf},
  annotation = {00096}
}

@article{kovess-masfety2016,
  title = {Is Time Spent Playing Video Games Associated with Mental Health, Cognitive and Social Skills in Young Children?},
  author = {{Kovess-Masfety}, Viviane and Keyes, Katherine and Hamilton, Ava and Hanson, Gregory and Bitfoi, Adina and Golitz, Dietmar and Ko{\c c}, Ceren and Kuijpers, Rowella and Lesinskiene, Sigita and Mihova, Zlatka and Otten, Roy and Fermanian, Christophe and Pez, Ondine},
  year = {2016},
  month = mar,
  journal = {Social Psychiatry and Psychiatric Epidemiology},
  volume = {51},
  number = {3},
  pages = {349--357},
  issn = {0933-7954, 1433-9285},
  doi = {10.1007/s00127-016-1179-6},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/4PZW94VN/kovess-masfety2016.pdf}
}

@article{kowalczyk2018,
  title = {Real-Time Strategy Video Game Experience and Structural Connectivity - {{A}} Diffusion Tensor Imaging Study},
  author = {Kowalczyk, Natalia and Shi, Feng and Magnuski, Mikolaj and Skorko, Maciek and Dobrowolski, Pawel and Kossowski, Bartosz and Marchewka, Artur and Bielecki, Maksymilian and Kossut, Malgorzata and Brzezicka, Aneta},
  year = {2018},
  month = sep,
  journal = {Human Brain Mapping},
  volume = {39},
  number = {9},
  pages = {3742--3758},
  issn = {10659471},
  doi = {10.1002/hbm.24208},
  langid = {english},
  annotation = {00000}
}

@book{koziol2014,
  title = {The Myth of Executive Functioning: {{Missing}} Elements in Conceptualization, Evaluation, and Assessment},
  shorttitle = {The Myth of Executive Functioning},
  author = {Koziol, Leonard F.},
  editor = {Deborah Ely Budding, Dana Chidekel},
  year = {2014},
  series = {{{SpringerBriefs}} in Neuroscience: {{The}} Vertically Organized Brain in Theory and Practice},
  doi = {10.1007/978-3-319-04477-4},
  isbn = {978-3-319-04477-4},
  langid = {english},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/9/Koziol\%209.pdf},
  keywords = {Book},
  annotation = {00000}
}

@article{kraus2021,
  title = {Network Variants Are Similar between Task and Rest States},
  author = {Kraus, Brian T. and Perez, Diana and Ladwig, Zach and Seitzman, Benjamin A. and Dworetsky, Ally and Petersen, Steven E. and Gratton, Caterina},
  year = {2021},
  month = apr,
  journal = {NeuroImage},
  volume = {229},
  pages = {117743},
  issn = {1053-8119},
  doi = {10.1016/j.neuroimage.2021.117743},
  abstract = {Recent work has demonstrated that individual-specific variations in functional networks (termed ``network variants'') can be identified in individuals using resting state functional magnetic resonance imaging (fMRI). These network variants exhibit reliability over time, suggesting that they may be trait-like markers of individual differences in brain organization. However, while networks variants are reliable at rest, is is still untested whether they are stable between task and rest states. Here, we use precision data from the Midnight Scan Club (MSC) to demonstrate that (1) task data can be used to identify network variants reliably, (2) these network variants show substantial spatial overlap with those observed in rest, although state-specific effects are present, (3) network variants assign to similar canonical functional networks in task and rest states, and (4) single tasks or a combination of multiple tasks produce similar network variants to rest. Together, these findings further reinforce the trait-like nature of network variants and demonstrate the utility of using task data to define network variants.},
  langid = {english}
}

@article{krishnan2013,
  title = {Neural {{Strategies}} for {{Selective Attention Distinguish Fast-Action Video Game Players}}},
  author = {Krishnan, Lavanya and Kang, Albert and Sperling, George and Srinivasan, Ramesh},
  year = {2013},
  month = jan,
  journal = {Brain Topography},
  volume = {26},
  number = {1},
  pages = {83--97},
  issn = {0896-0267, 1573-6792},
  doi = {10.1007/s10548-012-0232-3},
  langid = {english},
  annotation = {00049},
  file = {/Users/morteza/Documents/Zotero/storage/5XVX5326/krishnan2013.pdf}
}

@article{kuhn2011,
  title = {The Neural Basis of Video Gaming},
  author = {K{\"u}hn, Simone and Romanowski, A and Schilling, C and Lorenz, R and M{\"o}rsen, C and Seiferth, N and Banaschewski, T and Barbot, A and Barker, G J and B{\"u}chel, C and Conrod, P J and Dalley, J W and Flor, H and Garavan, H and Ittermann, B and Mann, K and Martinot, J-L and Paus, T and Rietschel, M and Smolka, M N and Str{\"o}hle, A and Walaszek, B and Schumann, G and Heinz, A and Gallinat, J},
  year = {2011},
  month = nov,
  journal = {Translational Psychiatry},
  volume = {1},
  number = {11},
  pages = {e53-e53},
  issn = {2158-3188},
  doi = {10.1038/tp.2011.53},
  langid = {english},
  annotation = {00163}
}

@article{kuhn2014,
  title = {Playing {{Super Mario}} Induces Structural Brain Plasticity: Gray Matter Changes Resulting from Training with a Commercial Video Game},
  shorttitle = {Playing {{Super Mario}} Induces Structural Brain Plasticity},
  author = {K{\"u}hn, Simone and Gleich, T and Lorenz, R C and Lindenberger, U and Gallinat, J},
  year = {2014},
  month = feb,
  journal = {Molecular Psychiatry},
  volume = {19},
  number = {2},
  pages = {265--271},
  issn = {1359-4184, 1476-5578},
  doi = {10.1038/mp.2013.120},
  langid = {english}
}

@article{kuhn2014a,
  title = {Positive {{Association}} of {{Video Game Playing}} with {{Left Frontal Cortical Thickness}} in {{Adolescents}}},
  author = {K{\"u}hn, Simone and Lorenz, Robert and Banaschewski, Tobias and Barker, Gareth J. and B{\"u}chel, Christian and Conrod, Patricia J. and Flor, Herta and Garavan, Hugh and Ittermann, Bernd and Loth, Eva and Mann, Karl and Nees, Frauke and Artiges, Eric and Paus, Tomas and Rietschel, Marcella and Smolka, Michael N. and Str{\"o}hle, Andreas and Walaszek, Bernadetta and Schumann, Gunter and Heinz, Andreas and Gallinat, J{\"u}rgen and {The IMAGEN Consortium}},
  editor = {Krueger, Frank},
  year = {2014},
  month = mar,
  journal = {PLoS ONE},
  volume = {9},
  number = {3},
  pages = {e91506},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0091506},
  langid = {english},
  annotation = {00069}
}

@article{kuhn2014b,
  title = {Amount of Lifetime Video Gaming Is Positively Associated with Entorhinal, Hippocampal and Occipital Volume},
  author = {K{\"u}hn, Simone and Gallinat, J},
  year = {2014},
  month = jul,
  journal = {Molecular Psychiatry},
  volume = {19},
  number = {7},
  pages = {842--847},
  issn = {1359-4184, 1476-5578},
  doi = {10.1038/mp.2013.100},
  langid = {english},
  annotation = {00083}
}

@article{kursa2010,
  title = {Feature {{Selection}} with the {{Boruta Package}}},
  author = {Kursa, Miron B. and Rudnicki, Witold R.},
  year = {2010},
  journal = {Journal of Statistical Software},
  volume = {36},
  number = {11},
  issn = {1548-7660},
  doi = {10.18637/jss.v036.i11},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/4M65A5XW/kursa2010.pdf}
}

@article{lachman2022,
  title = {Cost-Benefit Considerations Have Limited Effect on the Decision to Exert Cognitive Effort in Real-World Computer-Programming Tasks},
  author = {Lachman, Itamar and Hadar, Irit and Hertz, Uri},
  year = {2022},
  month = jun,
  journal = {Royal Society Open Science},
  volume = {9},
  number = {6},
  pages = {211885},
  issn = {2054-5703},
  doi = {10.1098/rsos.211885},
  abstract = {Recent research shows that people usually try to avoid exerting cognitive effort yet they are willing to exert effort to gain rewards. This cost-benefit framework provides predictions for behaviour outside the laboratory. Nevertheless, the extent to which such considerations affect real-life decisions is not clear. Here we experimentally examined computer-programmers' decisions to write code in a reusable manner, using functions, which demands an initial investment of cognitive effort or to clone and tweak code, a strategy whose cost increases with repetitions. Only a small portion of our participants demonstrated sensitivity to the benefits and costs of programming strategies. When asked to solve the tasks, participants tended to avoid using functions, demonstrating biased effort estimation. By contrast, when asked how they planned to solve the tasks, participants tended to demonstrate an opposite trend, overestimating effort, in line with an injunctive norm involving the overuse of functions. In the context of real-world problems, the effect of cost-benefit considerations may therefore be limited by task-irrelevant factors. Our interdisciplinary approach may be useful in providing novel theoretical insights and in promoting cognitive-effort investments outside the laboratory.},
  langid = {english},
  pmcid = {PMC9214280},
  pmid = {35754993},
  keywords = {code reuse,cognitive effort,decision-making,programming,subjective value},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-10-27]}
}

@article{laird2017,
  title = {A {{Standard Model}} of the {{Mind}}: {{Toward}} a {{Common Computational Framework}} across {{Artificial Intelligence}}, {{Cognitive Science}}, {{Neuroscience}}, and {{Robotics}}},
  shorttitle = {A {{Standard Model}} of the {{Mind}}},
  author = {Laird, John E. and Lebiere, Christian and Rosenbloom, Paul S.},
  year = {2017},
  month = dec,
  journal = {AI Magazine},
  volume = {38},
  number = {4},
  pages = {13--26},
  issn = {2371-9621, 0738-4602},
  doi = {10.1609/aimag.v38i4.2744},
  abstract = {The purpose of this article is to begin the process of engaging the international research community in developing what can be called a standard model of the mind, where the mind we have in mind here is human-like. The notion of a standard model has its roots in physics, where over more than a half-century the international community has developed and tested a standard model that combines much of what is known about particles. This model is assumed to be internally consistent, yet still have major gaps. Its function is to serve as a cumulative reference point for the field while also driving efforts to both extend and break it.},
  file = {/Users/morteza/Documents/Zotero/storage/HF4BMH67/Laird et al. - 2017 - A Standard Model of the Mind Toward a Common Comp.pdf}
}

@article{lecun2015,
  title = {Deep Learning},
  author = {LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  year = {2015},
  month = may,
  journal = {Nature},
  volume = {521},
  number = {7553},
  pages = {436--444},
  issn = {0028-0836, 1476-4687},
  doi = {10.1038/nature14539},
  langid = {english},
  annotation = {36526 citations (Crossref) [2022-10-17]}
}

@misc{lecun2022,
  title = {A {{Path Towards Autonomous Machine Intelligence}}},
  author = {LeCun, Yann},
  year = {2022},
  month = jun,
  abstract = {How could machines learn as efficiently as humans and animals?  How could machines learn to reason and plan?  How could machines learn representations of percepts and action plans at multiple...},
  annotation = {Version 0.9.2, 2022-06-27},
  file = {/Users/morteza/Documents/Zotero/storage/4ZBA9D4D/LeCun - 2022 - A Path Towards Autonomous Machine Intelligence.pdf}
}

@article{lefebvre2005,
  title = {Assessment of Working Memory Abilities Using an Event-Related Brain Potential ({{ERP}})-Compatible Digit Span Backward Task},
  author = {Lefebvre, Celeste D. and Marchand, Yannick and Eskes, Gail A. and Connolly, John F.},
  year = {2005},
  month = jul,
  journal = {Clinical Neurophysiology},
  volume = {116},
  number = {7},
  pages = {1665--1680},
  issn = {13882457},
  doi = {10.1016/j.clinph.2005.03.015},
  langid = {english},
  annotation = {00087}
}

@misc{leibo2018,
  title = {Psychlab: {{A Psychology Laboratory}} for {{Deep Reinforcement Learning Agents}}},
  shorttitle = {Psychlab},
  author = {Leibo, Joel Z. and {d'Autume}, Cyprien de Masson and Zoran, Daniel and Amos, David and Beattie, Charles and Anderson, Keith and Casta{\~n}eda, Antonio Garc{\'i}a and Sanchez, Manuel and Green, Simon and Gruslys, Audrunas and Legg, Shane and Hassabis, Demis and Botvinick, Matthew M.},
  year = {2018},
  month = feb,
  number = {arXiv:1801.08116},
  eprint = {1801.08116},
  eprinttype = {arxiv},
  primaryclass = {cs, q-bio},
  publisher = {{arXiv}},
  abstract = {Psychlab is a simulated psychology laboratory inside the first-person 3D game world of DeepMind Lab (Beattie et al., 2016). Psychlab enables implementations of classical laboratory psychological experiments so that they work with both human and artificial agents. Psychlab has a simple and flexible API that enables users to easily create their own tasks. As examples, we are releasing Psychlab implementations of several classical experimental paradigms including visual search, change detection, random dot motion discrimination, and multiple object tracking. We also contribute a study of the visual psychophysics of a specific state-of-the-art deep reinforcement learning agent: UNREAL (Jaderberg et al., 2016). This study leads to the surprising conclusion that UNREAL learns more quickly about larger target stimuli than it does about smaller stimuli. In turn, this insight motivates a specific improvement in the form of a simple model of foveal vision that turns out to significantly boost UNREAL's performance, both on Psychlab tasks, and on standard DeepMind Lab tasks. By open-sourcing Psychlab we hope to facilitate a range of future such studies that simultaneously advance deep reinforcement learning and improve its links with cognitive science.},
  archiveprefix = {arXiv},
  langid = {english},
  keywords = {Computer Science - Artificial Intelligence,Computer Science - Neural and Evolutionary Computing,Quantitative Biology - Neurons and Cognition},
  annotation = {60 citations (Semantic Scholar/arXiv) [2022-12-27]},
  file = {/Users/morteza/Documents/Zotero/storage/S42JRN9H/Leibo et al_2018_Psychlab.pdf}
}

@phdthesis{Lewis1978a,
  title = {Production System Models of Practice Effects},
  author = {Lewis, C.},
  year = {1978},
  school = {Department of Psychology, University of Michigan, Ann Arbor}
}

@article{lewis2011,
  title = {A Corpus Analysis of Strategy Video Game Play in Starcraft: {{Brood}} War},
  author = {Lewis, Joshua M. and Trinh, Patrick and Kirsh, David},
  year = {2011},
  journal = {Cognitive Science},
  volume = {33}
}

@article{li2016,
  title = {Playing {{Action Video Games Improves Visuomotor Control}}},
  author = {Li, Li and Chen, Rongrong and Chen, Jing},
  year = {2016},
  month = aug,
  journal = {Psychological Science},
  volume = {27},
  number = {8},
  pages = {1092--1108},
  issn = {0956-7976, 1467-9280},
  doi = {10.1177/0956797616650300},
  langid = {english},
  annotation = {00013}
}

@misc{li2022,
  title = {Scikit-{{Learn-Extra Documentation}}\textemdash{{Comparison}} of {{EigenPro}} and {{SVC}} on {{Digit Classification}}},
  author = {Li, Alex},
  year = {2022},
  journal = {Comparison of EigenPro and SVC on Digit Classification},
  howpublished = {https://scikit-learn-extra.readthedocs.io/en/stable/auto\_examples/eigenpro/plot\_eigenpro\_synthetic.html},
  langid = {english}
}

@article{libertus2017,
  title = {The {{Impact}} of {{Action Video Game Training}} on {{Mathematical Abilities}} in {{Adults}}},
  author = {Libertus, Melissa E. and Liu, Allison and Pikul, Olga and Jacques, Theodore and {Cardoso-Leite}, Pedro and Halberda, Justin and Bavelier, Daphne},
  year = {2017},
  month = oct,
  journal = {AERA Open},
  volume = {3},
  number = {4},
  pages = {233285841774085},
  issn = {2332-8584, 2332-8584},
  doi = {10.1177/2332858417740857},
  langid = {english},
  annotation = {00002},
  file = {/Users/morteza/Documents/Zotero/storage/6NYEA8WF/Libertus et al. - 2017 - The Impact of Action Video Game Training on Mathem.pdf;/Users/morteza/Documents/Zotero/storage/RY26QCNW/Libertus et al. - 2017 - The Impact of Action Video Game Training on Mathem.pdf}
}

@article{lindquist2019,
  title = {Modular Preprocessing Pipelines Can Reintroduce Artifacts into {{fMRI}} Data},
  author = {Lindquist, Martin A. and Geuter, Stephan and Wager, Tor D. and Caffo, Brian S.},
  year = {2019},
  month = jun,
  journal = {Human Brain Mapping},
  volume = {40},
  number = {8},
  pages = {2358--2376},
  issn = {1065-9471, 1097-0193},
  doi = {10.1002/hbm.24528},
  langid = {english},
  annotation = {112 citations (Semantic Scholar/DOI) [2022-12-07]},
  file = {/Users/morteza/Documents/Zotero/storage/7FW3HM4P/Lindquist et al. - 2019 - Modular preprocessing pipelines can reintroduce ar.pdf}
}

@article{lindsay2020,
  title = {Attention in {{Psychology}}, {{Neuroscience}}, and {{Machine Learning}}},
  author = {Lindsay, Grace W.},
  year = {2020},
  month = apr,
  journal = {Frontiers in Computational Neuroscience},
  volume = {14},
  pages = {29},
  issn = {1662-5188},
  doi = {10.3389/fncom.2020.00029},
  abstract = {Attention is the important ability to flexibly control limited computational resources. It has been studied in conjunction with many other topics in neuroscience and psychology including awareness, vigilance, saliency, executive control, and learning. It has also recently been applied in several domains in machine learning. The relationship between the study of biological attention and its use as a tool to enhance artificial neural networks is not always clear. This review starts by providing an overview of how attention is conceptualized in the neuroscience and psychology literature. It then covers several use cases of attention in machine learning, indicating their biological counterparts where they exist. Finally, the ways in which artificial attention can be further inspired by biology for the production of complex and integrative systems is explored.},
  annotation = {70 citations (Semantic Scholar/DOI) [2022-12-03]},
  file = {/Users/morteza/Documents/Zotero/storage/WYLNN9FC/Lindsay - 2020 - Attention in Psychology, Neuroscience, and Machine.pdf}
}

@article{lisman2017,
  title = {Viewpoints: How the Hippocampus Contributes to Memory, Navigation and Cognition},
  shorttitle = {Viewpoints},
  author = {Lisman, John and Buzs{\'a}ki, Gy{\"o}rgy and Eichenbaum, Howard and Nadel, Lynn and Ranganath, Charan and Redish, A David},
  year = {2017},
  month = nov,
  journal = {Nature Neuroscience},
  volume = {20},
  number = {11},
  pages = {1434--1447},
  issn = {1097-6256, 1546-1726},
  doi = {10.1038/nn.4661},
  langid = {english},
  annotation = {00028}
}

@article{logan1988,
  title = {Toward an Instance Theory of Automatization},
  author = {Logan, Gordon D.},
  year = {1988},
  journal = {Psychological Review},
  volume = {95},
  number = {4},
  pages = {492--527},
  issn = {0033-295X},
  doi = {10.1037/0033-295x.95.4.492},
  abstract = {This article presents a theory in which automatization is construed as the acquisition of a domain-specific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur only after practice in a consistent environment. Practice is important because it increases the amount retrieved and the speed of retrieval; consistency is important because it ensures that the retrieved instances will be useful. The theory accounts quantitatively for the power-function speed-up and predicts a power-function reduction in the standard deviation that is constrained to have the same exponent as the power function for the speed-up. The theory accounts for qualitative properties as well, explaining how some may disappear and others appear with practice. More generally, it provides an alternative to the modal view of automaticity, arguing that novice performance is limited by a lack of knowledge rather than a scarcity of resources. The focus on learning avoids many problems with the modal view that stem from its focus on resource limitations.},
  annotation = {04354}
}

@article{logan2017,
  title = {Taking Control of Cognition: {{An}} Instance Perspective on Acts of Control},
  author = {Logan, Gordon D.},
  year = {2017},
  journal = {American Psychologist},
  volume = {72},
  number = {9},
  pages = {875--884},
  issn = {0003-066X},
  doi = {10.1037/amp0000226},
  abstract = {Cognitive control is often viewed as an ability or as an interaction between higher and lower level systems. This article takes an instance perspective, articulating the view that cognitive control is accomplished by a multiplicity of specific acts of control tailored to accomplish specific adjustments to the cognitive system in specific circumstances. Acts of control take states of the cognitive system and states of the world as inputs, perform computations, and produce changes in the state of the cognitive system as output. Acts of control take measurable time. They are voluntary and specific, and they can be learned. The article addresses acts of control for inhibiting responses, shifting attention, and switching tasks, describing how to measure their durations and assess whether they are voluntary and specific. It concludes by reconciling ability, interactive systems, and instance perspectives and considering implications for research and practice.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2017/Logan\%202017.pdf},
  pmid = {29283627},
  rating = {5},
  annotation = {00013}
}

@article{looi2016,
  title = {Combining Brain Stimulation and Video Game to Promote Long-Term Transfer of Learning and Cognitive Enhancement},
  author = {Looi, Chung Yen and Duta, Mihaela and Brem, Anna-Katharine and Huber, Stefan and Nuerk, Hans-Christoph and Cohen Kadosh, Roi},
  year = {2016},
  month = apr,
  journal = {Scientific Reports},
  volume = {6},
  number = {1},
  pages = {22003},
  issn = {2045-2322},
  doi = {10.1038/srep22003},
  langid = {english},
  annotation = {00041},
  file = {/Users/morteza/Documents/Zotero/storage/A239ESNP/looi2016.pdf}
}

@techreport{lor2022,
  type = {Preprint},
  title = {Pre- and Post-Task Resting-State Differs in Clinical Populations},
  author = {Lor, Cindy Sumaly and Zhang, Mengfan and Karner, Alexander and Steyrl, David and Sladky, Ronald and Scharnowski, Frank and Haugg, Amelie},
  year = {2022},
  month = sep,
  institution = {{Neuroscience}},
  doi = {10.1101/2022.09.20.508750},
  abstract = {Abstract           Resting-state functional connectivity has generated great hopes as a potential brain biomarker for improving prevention, diagnosis, and treatment in psychiatry. This neuroimaging protocol can routinely be performed by patients and does not depend on the specificities of a task. Thus, it seems ideal for big data approaches that require aggregating data across multiple studies and sites. However, technical variability, diverging data analysis approaches, and differences in data acquisition protocols might introduce heterogeneity to the aggregated data. Besides these technical aspects, the psychological state of participants might also contribute to heterogeneity. In healthy participants, studies have shown that behavioral tasks can influence resting-state measures, but such effects have not yet been reported in clinical populations. Here, we fill this knowledge gap by comparing resting-state functional connectivity before and after clinically relevant tasks in two clinical conditions, namely substance use disorders and phobias. The tasks consisted of viewing craving-inducing and spider anxiety provoking pictures that are frequently used in cue-reactivity studies and exposure therapy. We found distinct pre- vs. post-task resting-state connectivity differences in each group, as well as decreased thalamo-cortical and increased intra-thalamic connectivity which might be associated with decreased vigilance in both groups. Notably, the pre- vs. post-task thalamus-amygdala connectivity change within a patient cohort seems more pronounced than the difference of that connection between the smoker vs. phobia clinical trait. Our results confirm that resting-state measures can be strongly influenced by changes in psychological states that need to be taken into account when pooling resting-state scans for clinical biomarker detection. This demands that resting-state datasets should include a complete description of the experimental design, especially when a task preceded data collection.},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/65J2LCN9/Lor et al. - 2022 - Pre- and post-task resting-state differs in clinic.pdf}
}

@article{lorenz2015,
  title = {Video Game Training and the Reward System},
  author = {Lorenz, Robert C. and Gleich, Tobias and Gallinat, J{\"u}rgen and K{\"u}hn, Simone},
  year = {2015},
  journal = {Frontiers in Human Neuroscience},
  volume = {9},
  pages = {40},
  issn = {1662-5161},
  doi = {10.3389/fnhum.2015.00040},
  abstract = {Video games contain elaborate reinforcement and reward schedules that have the potential to maximize motivation. Neuroimaging studies suggest that video games might have an influence on the reward system. However, it is not clear whether reward-related properties represent a precondition, which biases an individual toward playing video games, or if these changes are the result of playing video games. Therefore, we conducted a longitudinal study to explore reward-related functional predictors in relation to video gaming experience as well as functional changes in the brain in response to video game training. Fifty healthy participants were randomly assigned to a video game training (TG) or control group (CG). Before and after training/control period, functional magnetic resonance imaging (fMRI) was conducted using a non-video game related reward task. At pretest, both groups showed strongest activation in ventral striatum (VS) during reward anticipation. At posttest, the TG showed very similar VS activity compared to pretest. In the CG, the VS activity was significantly attenuated. This longitudinal study revealed that video game training may preserve reward responsiveness in the VS in a retest situation over time. We suggest that video games are able to keep striatal responses to reward flexible, a mechanism which might be of critical value for applications such as therapeutic cognitive training.},
  langid = {english},
  pmcid = {PMC4318496},
  pmid = {25698962},
  keywords = {fMRI,longitudinal,reward anticipation,training,video gaming},
  annotation = {00028},
  file = {/Users/morteza/Documents/Zotero/storage/XYUYD4KR/lorenz2015.pdf}
}

@incollection{lundberg2017,
  title = {A Unified Approach to Interpreting Model Predictions},
  booktitle = {Advances in Neural Information Processing Systems 30},
  author = {Lundberg, Scott M and Lee, Su-In},
  editor = {Guyon, I. and Luxburg, U. V. and Bengio, S. and Wallach, H. and Fergus, R. and Vishwanathan, S. and Garnett, R.},
  year = {2017},
  pages = {4765--4774},
  publisher = {{Curran Associates, Inc.}}
}

@article{luniewska2018,
  title = {Neither Action nor Phonological Video Games Make Dyslexic Children Read Better},
  author = {{\L}uniewska, Magdalena and Chyl, Katarzyna and D{\k{e}}bska, Agnieszka and Kacprzak, Agnieszka and Plewko, Joanna and Szczerbi{\'n}ski, Marcin and Szewczyk, Jakub and Grabowska, Anna and Jednor{\'o}g, Katarzyna},
  year = {2018},
  month = dec,
  journal = {Scientific Reports},
  volume = {8},
  number = {1},
  pages = {549},
  issn = {2045-2322},
  doi = {10.1038/s41598-017-18878-7},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/6FIL7MK6/Łuniewska et al. - 2018 - Neither action nor phonological video games make d.pdf;/Users/morteza/Documents/Zotero/storage/SJFZT6JH/Łuniewska et al. - 2018 - Neither action nor phonological video games make d.pdf}
}

@article{mackie2013,
  title = {Cognitive Control and Attentional Functions.},
  author = {Mackie, Melissa-Ann and Dam, Nicholas T Van and Fan, Jin},
  year = {2013},
  journal = {Brain and cognition},
  volume = {82},
  number = {3},
  pages = {301--12},
  issn = {0278-2626},
  doi = {10.1016/j.bandc.2013.05.004},
  abstract = {Cognitive control is essential to flexible, goal-directed behavior under uncertainty, yet its underlying mechanisms are not clearly understood. Because attentional functions are known to allocate mental resources and prioritize the information to be processed, we propose that the attentional functions of alerting, orienting, and executive control and the interactions among them contribute to cognitive control in the service of uncertainty reduction. To test this hypothesis, we examined the relationship between cognitive control and attentional functions. We used the Majority Function Task (MFT) to manipulate uncertainty in order to evoke cognitive control along with the Revised Attention Network Test (ANT-R) to measure the efficiency and the interactions of attentional functions. A backwards, stepwise regression model revealed that performance on the MFT could be significantly predicted by attentional functions and their interactions as measured by the ANT-R. These results provide preliminary support for our theory that the attentional functions are involved in the implementation of cognitive control as required to reduce uncertainty, though further investigation is needed.},
  pmcid = {PMC3722267},
  pmid = {23792472},
  keywords = {Attention,Cognitive Control},
  annotation = {00137}
}

@book{martin2009,
  title = {Clean Code: A Handbook of Agile Software Craftsmanship},
  shorttitle = {Clean Code},
  editor = {Martin, Robert C.},
  year = {2009},
  publisher = {{Prentice Hall}},
  address = {{Upper Saddle River, NJ}},
  isbn = {978-0-13-235088-4},
  lccn = {QA76.76.D47 C583 2009},
  keywords = {Agile software development,Computer software,Reliability}
}

@phdthesis{Matlock2001,
  title = {How Real Is Fictive Motion?},
  author = {Matlock, Teenie},
  year = {2001},
  school = {Psychology Department, University of California, Santa Cruz}
}

@article{mcclelland2009,
  title = {The Place of Modeling in Cognitive Science},
  author = {McClelland, James L.},
  year = {2009},
  month = jan,
  journal = {Topics in Cognitive Science},
  volume = {1},
  number = {1},
  pages = {11--38},
  issn = {1756-8765},
  doi = {10.1111/j.1756-8765.2008.01003.x},
  abstract = {I consider the role of cognitive modeling in cognitive science. Modeling, and the computers that enable it, are central to the field, but the role of modeling is often misunderstood. Models are not intended to capture fully the processes they attempt to elucidate. Rather, they are explorations of ideas about the nature of cognitive processes. In these explorations, simplification is essential-through simplification, the implications of the central ideas become more transparent. This is not to say that simplification has no downsides; it does, and these are discussed. I then consider several contemporary frameworks for cognitive modeling, stressing the idea that each framework is useful in its own particular ways. Increases in computer power (by a factor of about 4 million) since 1958 have enabled new modeling paradigms to emerge, but these also depend on new ways of thinking. Will new paradigms emerge again with the next 1,000-fold increase?},
  langid = {english},
  pmid = {25164798},
  keywords = {Bayesian approaches,Cognitive architectures,Cognitive Science,Computer simulation,Connectionist models,Dynamical systems,Humans,Hybrid models,Modeling frameworks,Models; Theoretical,Neural Networks; Computer,Symbolic models of cognition},
  annotation = {195 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/UD848QUZ/McClelland_2009_The place of modeling in cognitive science.pdf}
}

@article{mcgovern2019,
  title = {Making the {{Black Box More Transparent}}: {{Understanding}} the {{Physical Implications}} of {{Machine Learning}}},
  shorttitle = {Making the {{Black Box More Transparent}}},
  author = {McGovern, Amy and Lagerquist, Ryan and John Gagne, David and Jergensen, G. Eli and Elmore, Kimberly L. and Homeyer, Cameron R. and Smith, Travis},
  year = {2019},
  month = nov,
  journal = {Bulletin of the American Meteorological Society},
  volume = {100},
  number = {11},
  pages = {2175--2199},
  issn = {0003-0007, 1520-0477},
  doi = {10.1175/BAMS-D-18-0195.1},
  abstract = {Abstract             This paper synthesizes multiple methods for machine learning (ML) model interpretation and visualization (MIV) focusing on meteorological applications. ML has recently exploded in popularity in many fields, including meteorology. Although ML has been successful in meteorology, it has not been as widely accepted, primarily due to the perception that ML models are ``black boxes,'' meaning the ML methods are thought to take inputs and provide outputs but not to yield physically interpretable information to the user. This paper introduces and demonstrates multiple MIV techniques for both traditional ML and deep learning, to enable meteorologists to understand what ML models have learned. We discuss permutation-based predictor importance, forward and backward selection, saliency maps, class-activation maps, backward optimization, and novelty detection. We apply these methods at multiple spatiotemporal scales to tornado, hail, winter precipitation type, and convective-storm mode. By analyzing such a wide variety of applications, we intend for this work to demystify the black box of ML, offer insight in applying MIV techniques, and serve as a MIV toolbox for meteorologists and other physical scientists.},
  annotation = {179 citations (Semantic Scholar/DOI) [2022-12-10]},
  file = {/Users/morteza/Documents/Zotero/storage/EXF2AUR3/McGovern et al. - 2019 - Making the Black Box More Transparent Understandi.pdf}
}

@article{mcmillan2007,
  title = {Self-Paced Working Memory: {{Validation}} of Verbal Variations of the n-Back Paradigm},
  shorttitle = {Self-Paced Working Memory},
  author = {McMillan, Kathryn M. and Laird, Angela R. and Witt, Suzanne T. and Meyerand, M. Elizabeth},
  year = {2007},
  month = mar,
  journal = {Brain Research},
  volume = {1139},
  pages = {133--142},
  issn = {00068993},
  doi = {10.1016/j.brainres.2006.12.058},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/8S4CT43P/mcmillan2007.pdf}
}

@article{mcphetres2021,
  title = {A Decade of Theory as Reflected in {{Psychological Science}} (2009\textendash 2019)},
  author = {McPhetres, Jonathon and {Albayrak-Aydemir}, Nihan and Mendes, Ana Barbosa and Chow, Elvina C. and {Gonzalez-Marquez}, Patricio and Loukras, Erin and Maus, Annika and O'Mahony, Aoife and Pomareda, Christina and Primbs, Maximilian A. and Sackman, Shalaine L. and Smithson, Conor J. R. and Volodko, Kirill},
  year = {2021},
  journal = {PLOS ONE},
  volume = {16},
  number = {3},
  pages = {e0247986},
  doi = {10.1371/journal.pone.0247986},
  abstract = {The dominant belief is that science progresses by testing theories and moving towards theoretical consensus. While it's implicitly assumed that psychology operates in this manner, critical discussions claim that the field suffers from a lack of cumulative theory. To examine this paradox, we analysed research published in Psychological Science from 2009\textendash 2019 (N = 2,225). We found mention of 359 theories in-text, most were referred to only once. Only 53.66\% of all manuscripts included the word theory, and only 15.33\% explicitly claimed to test predictions derived from theories. We interpret this to suggest that the majority of research published in this flagship journal is not driven by theory, nor can it be contributing to cumulative theory building. These data provide insight into the kinds of research psychologists are conducting and raises questions about the role of theory in the psychological sciences.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2021/McPhetres\%202021.pdf},
  pmid = {33667242},
  annotation = {00004}
}

@article{medaglia2019,
  title = {Clarifying Cognitive Control and the Controllable Connectome},
  author = {Medaglia, John D.},
  year = {2019},
  month = jan,
  journal = {Wiley Interdisciplinary Reviews. Cognitive Science},
  volume = {10},
  number = {1},
  pages = {e1471},
  issn = {1939-5086},
  doi = {10.1002/wcs.1471},
  abstract = {Cognitive control researchers aim to describe the processes that support adaptive cognition to achieve specific goals. Control theorists consider how to influence the state of systems to reach certain user-defined goals. In brain networks, some conceptual and lexical similarities between cognitive control and control theory offer appealing avenues for scientific discovery. However, these opportunities also come with the risk of conceptual confusion. Here, I suggest that each field of inquiry continues to produce novel and distinct insights. Then, I describe opportunities for synergistic research at the intersection of these subdisciplines with a critical stance that reduces the risk of conceptual confusion. Through this exercise, we can observe that both cognitive neuroscience and systems engineering have much to contribute to cognitive control research in human brain networks. This article is categorized under: Neuroscience {$>$} Cognition Computer Science {$>$} Neural Networks Neuroscience {$>$} Clinical Neuroscience.},
  langid = {english},
  pmcid = {PMC6642819},
  pmid = {29971940},
  keywords = {Brain,cognitive control,Connectome,control theory,diffusion imaging,Executive Function,fMRI,Humans,Nerve Net,neural networks,Neurosciences},
  annotation = {13 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/M3TUBUZA/medaglia2018.pdf}
}

@article{meier2020,
  title = {Verbal {{Instructions}} and {{Motor Learning}}: {{How Analogy}} and {{Explicit Instructions Influence}} the {{Development}} of {{Mental Representations}} and {{Tennis Serve Performance}}},
  shorttitle = {Verbal {{Instructions}} and {{Motor Learning}}},
  author = {Meier, Christopher and Frank, Cornelia and Gr{\"o}ben, Bernd and Schack, Thomas},
  year = {2020},
  month = feb,
  journal = {Frontiers in Psychology},
  volume = {11},
  pages = {2},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2020.00002},
  file = {/Users/morteza/Documents/Zotero/storage/MRDCQCRX/Meier et al. - 2020 - Verbal Instructions and Motor Learning How Analog.pdf}
}

@article{melby-lervag2013,
  title = {Is Working Memory Training Effective? {{A}} Meta-Analytic Review.},
  shorttitle = {Is Working Memory Training Effective?},
  author = {{Melby-Lerv{\aa}g}, Monica and Hulme, Charles},
  year = {2013},
  journal = {Developmental Psychology},
  volume = {49},
  number = {2},
  pages = {270--291},
  issn = {1939-0599, 0012-1649},
  doi = {10.1037/a0028228},
  langid = {english},
  annotation = {01334},
  file = {/Users/morteza/Documents/Zotero/storage/Q3FBVB5C/melby-lervåg2013.pdf}
}

@incollection{menon2015,
  title = {Salience {{Network}}},
  booktitle = {Brain {{Mapping}}},
  author = {Menon, V.},
  year = {2015},
  pages = {597--611},
  publisher = {{Elsevier}},
  doi = {10.1016/B978-0-12-397025-1.00052-X},
  isbn = {978-0-12-397316-0},
  langid = {english},
  annotation = {00308}
}

@article{menon2022,
  title = {The Role of {{PFC}} Networks in Cognitive Control and Executive Function},
  author = {Menon, Vinod and D'Esposito, Mark},
  year = {2022},
  month = jan,
  journal = {Neuropsychopharmacology},
  volume = {47},
  number = {1},
  pages = {90--103},
  issn = {0893-133X, 1740-634X},
  doi = {10.1038/s41386-021-01152-w},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/RCK3SFW2/Nature---Menon---Role-of-PFC.pdf}
}

@article{menu2022,
  title = {A Network Analysis of Executive Functions before and after Computerized Cognitive Training in Children and Adolescents},
  author = {Menu, Iris and Rezende and Le Stanc and Borst and Cachia},
  year = {2022},
  month = aug,
  journal = {Scientific reports},
  volume = {12},
  number = {1},
  publisher = {{Sci Rep}},
  issn = {2045-2322},
  doi = {10.1038/s41598-022-17695-x},
  abstract = {Executive functions (EFs) play a key role in cognitive and socioemotional development. Factor analyses have revealed an age dependent structure of EFs spanning from a single common factor in early childhood to three factors in adults corresponding to inhibitory control (IC), switching and updating. \ldots},
  langid = {english},
  pmid = {36038599},
  file = {/Users/morteza/Documents/Zotero/storage/Q2FE6NQU/I et al_2022_A network analysis of executive functions before and after computerized.pdf;/Users/morteza/Documents/Zotero/storage/YSYRGPXE/36038599.html}
}

@article{miendlarzewska2016,
  title = {Influence of Reward Motivation on Human Declarative Memory},
  author = {Miendlarzewska, Ewa A. and Bavelier, Daphne and Schwartz, Sophie},
  year = {2016},
  month = feb,
  journal = {Neuroscience \& Biobehavioral Reviews},
  volume = {61},
  pages = {156--176},
  issn = {01497634},
  doi = {10.1016/j.neubiorev.2015.11.015},
  langid = {english},
  annotation = {00052},
  file = {/Users/morteza/Documents/Zotero/storage/HXMPPPB4/miendlarzewska2016.pdf}
}

@misc{miller1960,
  title = {Plans and the Structure of Behavior.},
  author = {Miller, GA and Galanter, E and Pribram, KH},
  year = {1960}
}

@article{miller2009,
  title = {Is the {{N-Back Task}} a {{Valid Neuropsychological Measure}} for {{Assessing Working Memory}}?},
  author = {Miller, K.M. and Price, C.C. and Okun, M.S. and Montijo, H. and Bowers, D.},
  year = {2009},
  month = nov,
  journal = {Archives of Clinical Neuropsychology},
  volume = {24},
  number = {7},
  pages = {711--717},
  issn = {0887-6177, 1873-5843},
  doi = {10.1093/arclin/acp063},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/UCIRXPDX/miller2009.pdf}
}

@incollection{miller2012,
  title = {The Prefrontal Cortex and Executive Brain Functions},
  author = {Miller and Wallis},
  year = {2012},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/pdf.sciencedirectassets.com\%202172021,\%2090048\%20PM.pdf},
  keywords = {Executive Functions,PFC}
}

@article{mirelman2012,
  title = {Executive {{Function}} and {{Falls}} in {{Older Adults}}: {{New Findings}} from a {{Five-Year Prospective Study Link Fall Risk}} to {{Cognition}}},
  shorttitle = {Executive {{Function}} and {{Falls}} in {{Older Adults}}},
  author = {Mirelman, Anat and Herman, Talia and Brozgol, Marina and Dorfman, Moran and Sprecher, Elliot and Schweiger, Avraham and Giladi, Nir and Hausdorff, Jeffrey M.},
  year = {2012},
  month = jun,
  journal = {PLoS ONE},
  volume = {7},
  number = {6},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0040297},
  abstract = {Background Recent findings suggest that executive function (EF) plays a critical role in the regulation of gait in older adults, especially under complex and challenging conditions, and that EF deficits may, therefore, contribute to fall risk. The objective of this study was to evaluate if reduced EF is a risk factor for future falls over the course of 5 years of follow-up. Secondary objectives were to assess whether single and dual task walking abilities, an alternative window into EF, were associated with fall risk. Methodology/Main Results We longitudinally followed 256 community-living older adults (age: 76.4{$\pm$}4.5 yrs; 61\% women) who were dementia free and had good mobility upon entrance into the study. At baseline, a computerized cognitive battery generated an index of EF, attention, a closely related construct, and other cognitive domains. Gait was assessed during single and dual task conditions. Falls data were collected prospectively using monthly calendars. Negative binomial regression quantified risk ratios (RR). After adjusting for age, gender and the number of falls in the year prior to the study, only the EF index (RR: .85; CI: .74\textendash.98, p{$\mkern1mu$}={$\mkern1mu$}.021), the attention index (RR: .84; CI: .75\textendash.94, p{$\mkern1mu$}={$\mkern1mu$}.002) and dual tasking gait variability (RR: 1.11; CI: 1.01\textendash 1.23; p{$\mkern1mu$}={$\mkern1mu$}.027) were associated with future fall risk. Other cognitive function measures were not related to falls. Survival analyses indicated that subjects with the lowest EF scores were more likely to fall sooner and more likely to experience multiple falls during the 66 months of follow-up (p{$<$}0.02). Conclusions/Significance These findings demonstrate that among community-living older adults, the risk of future falls was predicted by performance on EF and attention tests conducted 5 years earlier. The present results link falls among older adults to cognition, indicating that screening EF will likely enhance fall risk assessment, and that treatment of EF may reduce fall risk.},
  pmcid = {PMC3386974},
  pmid = {22768271},
  file = {/Users/morteza/Documents/Zotero/storage/YW5YCVID/Mirelman et al. - 2012 - Executive Function and Falls in Older Adults New .pdf}
}

@article{mishra2011,
  title = {Neural {{Basis}} of {{Superior Performance}} of {{Action Videogame Players}} in an {{Attention-Demanding Task}}},
  author = {Mishra, J. and Zinni, M. and Bavelier, D. and Hillyard, S. A.},
  year = {2011},
  month = jan,
  journal = {Journal of Neuroscience},
  volume = {31},
  number = {3},
  pages = {992--998},
  issn = {0270-6474, 1529-2401},
  doi = {10.1523/JNEUROSCI.4834-10.2011},
  langid = {english},
  annotation = {00177},
  file = {/Users/morteza/Documents/Zotero/storage/T2C3HASB/mishra2011.pdf}
}

@article{miyake2000,
  title = {The {{Unity}} and {{Diversity}} of {{Executive Functions}} and {{Their Contributions}} to {{Complex}} ``{{Frontal Lobe}}'' {{Tasks}}: {{A Latent Variable Analysis}}},
  shorttitle = {The {{Unity}} and {{Diversity}} of {{Executive Functions}} and {{Their Contributions}} to {{Complex}} ``{{Frontal Lobe}}'' {{Tasks}}},
  author = {Miyake, Akira and Friedman, Naomi P. and Emerson, Michael J. and Witzki, Alexander H. and Howerter, Amy and Wager, Tor D.},
  year = {2000},
  month = aug,
  journal = {Cognitive Psychology},
  volume = {41},
  number = {1},
  pages = {49--100},
  issn = {00100285},
  doi = {10.1006/cogp.1999.0734},
  langid = {english}
}

@article{miyake2012,
  title = {The {{Nature}} and {{Organization}} of {{Individual Differences}} in {{Executive Functions}}: {{Four General Conclusions}}},
  shorttitle = {The {{Nature}} and {{Organization}} of {{Individual Differences}} in {{Executive Functions}}},
  author = {Miyake, Akira and Friedman, Naomi P.},
  year = {2012},
  month = feb,
  journal = {Current Directions in Psychological Science},
  volume = {21},
  number = {1},
  pages = {8--14},
  issn = {0963-7214, 1467-8721},
  doi = {10.1177/0963721411429458},
  abstract = {Executive functions (EFs)\textemdash a set of general-purpose control processes that regulate one's thoughts and behaviors\textemdash have become a popular research topic lately and have been studied in many subdisciplines of psychological science. This article summarizes the EF research that our group has conducted to understand the nature of individual differences in EFs and their cognitive and biological underpinnings. In the context of a new theoretical framework that we have been developing (the unity/diversity framework), we describe four general conclusions that have emerged. Specifically, we argue that individual differences in EFs, as measured with simple laboratory tasks, (a) show both unity and diversity (different EFs are correlated yet separable), (b) reflect substantial genetic contributions, (c) are related to various clinically and societally important phenomena, and (d) show some developmental stability.},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/GTW69X8K/Miyake and Friedman - 2012 - The Nature and Organization of Individual Differen.pdf}
}

@article{mnih2015,
  title = {Human-Level Control through Deep Reinforcement Learning},
  author = {Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A. and Veness, Joel and Bellemare, Marc G. and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K. and Ostrovski, Georg and Petersen, Stig and Beattie, Charles and Sadik, Amir and Antonoglou, Ioannis and King, Helen and Kumaran, Dharshan and Wierstra, Daan and Legg, Shane and Hassabis, Demis},
  year = {2015},
  month = feb,
  journal = {Nature},
  volume = {518},
  number = {7540},
  pages = {529--533},
  publisher = {{Nature Publishing Group}},
  issn = {1476-4687},
  doi = {10.1038/nature14236},
  abstract = {An artificial agent is developed that learns to play~a diverse range of classic Atari 2600 computer games directly from sensory experience, achieving a~performance comparable to that of an expert human player; this work paves the way to building general-purpose learning algorithms that bridge the divide between perception and action.},
  langid = {english},
  keywords = {Computer science},
  annotation = {9996 citations (Semantic Scholar/DOI) [2022-11-15]},
  file = {/Users/morteza/Documents/Zotero/storage/FN43JKGK/Mnih et al_2015_Human-level control through deep reinforcement learning.pdf;/Users/morteza/Documents/Zotero/storage/CJ2BZC4P/nature14236.html}
}

@article{moffitt2011,
  title = {A Gradient of Childhood Self-Control Predicts Health, Wealth, and Public Safety},
  author = {Moffitt, Terrie E. and Arseneault, Louise and Belsky, Daniel and Dickson, Nigel and Hancox, Robert J. and Harrington, HonaLee and Houts, Renate and Poulton, Richie and Roberts, Brent W. and Ross, Stephen and Sears, Malcolm R. and Thomson, W. Murray and Caspi, Avshalom},
  year = {2011},
  month = feb,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {108},
  number = {7},
  pages = {2693--2698},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1010076108},
  abstract = {Policy-makers are considering large-scale programs aimed at self-control to improve citizens' health and wealth and reduce crime. Experimental and economic studies suggest such programs could reap benefits. Yet, is self-control important for the health, wealth, and public safety of the population? Following a cohort of 1,000 children from birth to the age of 32 y, we show that childhood self-control predicts physical health, substance dependence, personal finances, and criminal offending outcomes, following a gradient of self-control. Effects of children's self-control could be disentangled from their intelligence and social class as well as from mistakes they made as adolescents. In another cohort of 500 sibling-pairs, the sibling with lower self-control had poorer outcomes, despite shared family background. Interventions addressing self-control might reduce a panoply of societal costs, save taxpayers money, and promote prosperity.},
  langid = {english},
  annotation = {3522 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/PIR4D8GN/Moffitt et al. - 2011 - A gradient of childhood self-control predicts heal.pdf}
}

@book{molnar2022,
  title = {Interpretable Machine Learning: A Guide for Making Black Box Models Explainable},
  shorttitle = {Interpretable Machine Learning},
  author = {Molnar, Christoph},
  year = {2022},
  edition = {Second edition},
  publisher = {{Christoph Molnar}},
  address = {{Munich, Germany}},
  isbn = {9798411463330},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/KKWEDHH5/Molnar - 2022 - Interpretable machine learning a guide for making.pdf}
}

@article{monsell2003,
  title = {Task Switching},
  author = {Monsell, Stephen},
  year = {2003},
  month = mar,
  journal = {Trends in Cognitive Sciences},
  volume = {7},
  number = {3},
  pages = {134--140},
  issn = {13646613},
  doi = {10.1016/S1364-6613(03)00028-7},
  langid = {english},
  annotation = {845 citations (Semantic Scholar/DOI) [2022-12-14]}
}

@article{moreau2013,
  title = {Differentiating Two- from Three-Dimensional Mental Rotation Training Effects},
  author = {Moreau, David},
  year = {2013},
  journal = {Quarterly Journal of Experimental Psychology (2006)},
  volume = {66},
  number = {7},
  pages = {1399--1413},
  issn = {1747-0226},
  doi = {10.1080/17470218.2012.744761},
  abstract = {Block videogame training has consistently demonstrated transfer effects to mental rotation tasks, yet how variations in training influence performance with different stimuli remains unclear. In this study, participants took mental rotation assessments before and after a 3-week training programme based on 2D or 3D block videogames. Assessments varied in terms of dimensionality (2D or 3D) and stimulus type (polygon or body). Increases in videogame scores throughout training were correlated with mental rotation improvements. In particular, 2D training led to improvements in 2D tasks, whereas 3D training led to improvements in both 2D and 3D tasks. This effect did not depend on stimulus type, demonstrating that training can transfer to different stimuli of identical dimensionality. Interestingly, traditional gender differences in 3D mental rotation tasks vanished after 3D videogame training, highlighting the malleability of mental rotation ability given adequate training. These findings emphasize the influence of dimensionality in transfer effects and offer promising perspectives to reduce differences in mental rotation via designed training programmes.},
  langid = {english},
  pmid = {23163833},
  keywords = {Adolescent,Analysis of Variance,Female,Humans,Male,Mental Processes,Neuropsychological Tests,Reaction Time,Rotation,Space Perception,Statistics as Topic,Teaching,Transfer (Psychology),Video Recording,Young Adult},
  annotation = {00000}
}

@article{moreau2014,
  title = {The Case for an Ecological Approach to Cognitive Training},
  author = {Moreau, David and Conway, Andrew R.A.},
  year = {2014},
  month = jul,
  journal = {Trends in Cognitive Sciences},
  volume = {18},
  number = {7},
  pages = {334--336},
  issn = {13646613},
  doi = {10.1016/j.tics.2014.03.009},
  langid = {english}
}

@article{morton2011,
  title = {Cognitive {{Control}}: {{Easy}} to {{Identify But Hard}} to {{Define}}},
  shorttitle = {Cognitive {{Control}}},
  author = {Morton, J. Bruce and Ezekiel, Fredrick and Wilk, Heather A.},
  year = {2011},
  month = apr,
  journal = {Topics in Cognitive Science},
  volume = {3},
  number = {2},
  pages = {212--216},
  issn = {17568757},
  doi = {10.1111/j.1756-8765.2011.01139.x},
  langid = {english}
}

@article{moskovitz2022,
  title = {A {{Unified Theory}} of {{Dual-Process Control}}},
  author = {Moskovitz, Ted and Miller, Kevin and Sahani, Maneesh and Botvinick, Matthew M.},
  year = {2022},
  publisher = {{arXiv}},
  doi = {10.48550/ARXIV.2211.07036},
  abstract = {Dual-process theories play a central role in both psychology and neuroscience, figuring prominently in fields ranging from executive control to reward-based learning to judgment and decision making. In each of these domains, two mechanisms appear to operate concurrently, one relatively high in computational complexity, the other relatively simple. Why is neural information processing organized in this way? We propose an answer to this question based on the notion of compression. The key insight is that dual-process structure can enhance adaptive behavior by allowing an agent to minimize the description length of its own behavior. We apply a single model based on this observation to findings from research on executive control, reward-based learning, and judgment and decision making, showing that seemingly diverse dual-process phenomena can be understood as domain-specific consequences of a single underlying set of computational principles.},
  copyright = {Creative Commons Attribution 4.0 International},
  keywords = {FOS: Biological sciences,Generalization,Neurons and Cognition (q-bio.NC)},
  annotation = {0 citations (Semantic Scholar/arXiv) [2022-11-19]},
  file = {/Users/morteza/Documents/Zotero/storage/ANV7PXKV/Moskovitz et al_2022_A Unified Theory of Dual-Process Control.pdf}
}

@book{musslick2016,
  title = {Controlled vs. {{Automatic Processing}}: {{A Graph-Theoretic Approach}} to the {{Analysis}} of {{Serial}} vs. {{Parallel Processing}} in {{Neural Network Architectures}}},
  shorttitle = {Controlled vs. {{Automatic Processing}}},
  author = {Musslick, Sebastian and Dey, Biswadip and Ozcimder, Kayhan and Mostofa, Md and Patwary, Ali and Willke, Theodore and Cohen, Jonathan},
  year = {2016},
  month = aug,
  abstract = {The limited ability to simultaneously perform multiple tasks is one of the most salient features of human performance and a defining characteristic of controlled processing. We propose that this reflects the degree to which individual tasks rely on shared representations, and the constraints this places on parallel processing in neural network architectures. We describe a graph-theoretic approach to analyzing these constraints. Our results are consistent with previous numerical work (Feng, Schwemmer, Gershman, \& Cohen, 2014), showing that even modest amounts of shared representation induce dramatic constraints on the parallel processing capability of a network. We further illustrate how this analysis method can be applied to specific networks to efficiently characterize the full profile of their parallel processing capabilities. We present simulation results that validate theoretical predictions, and discuss how these methods can be applied to empirical studies of controlled vs. and automatic processing and multitasking performance in humans.},
  keywords = {Cognitive Control},
  file = {/Users/morteza/Documents/Zotero/storage/BV443YKE/Musslick et al. - 2016 - Controlled vs. Automatic Processing A Graph-Theor.pdf}
}

@incollection{nahum2020,
  title = {Video Games as Rich Environments to Foster Brain Plasticity},
  booktitle = {Handbook of {{Clinical Neurology}}},
  author = {Nahum, Mor and Bavelier, Daphne},
  year = {2020},
  volume = {168},
  pages = {117--136},
  publisher = {{Elsevier}},
  doi = {10.1016/B978-0-444-63934-9.00010-X},
  isbn = {978-0-444-63934-9},
  langid = {english}
}

@article{nau2018,
  title = {How the {{Brain}}'s {{Navigation System Shapes Our Visual Experience}}},
  author = {Nau, Matthias and Julian, Joshua B. and Doeller, Christian F.},
  year = {2018},
  month = sep,
  journal = {Trends in Cognitive Sciences},
  volume = {22},
  number = {9},
  pages = {810--825},
  issn = {13646613},
  doi = {10.1016/j.tics.2018.06.008},
  langid = {english}
}

@article{nava2019,
  title = {Children Can Optimally Integrate Multisensory Information after a Short Action-like Mini Game Training},
  author = {Nava, Elena and F{\"o}cker, Julia and Gori, Monica},
  year = {2019},
  month = apr,
  journal = {Developmental Science},
  pages = {e12840},
  issn = {1363-755X, 1467-7687},
  doi = {10.1111/desc.12840},
  langid = {english},
  annotation = {00000}
}

@article{newell1973,
  title = {You Can't Play 20 Questions with Nature and Win: {{Projective}} Comments on the Papers of This Symposium},
  shorttitle = {You Can't Play 20 Questions with Nature and Win},
  author = {Newell, Allen},
  year = {1973},
  file = {/Users/morteza/Documents/Zotero/storage/T39786DN/Newell_1973_You can't play 20 questions with nature and win.pdf}
}

@book{NewellSimon1972a,
  title = {Human Problem Solving},
  author = {Newell, A. and Simon, H. A.},
  year = {1972},
  publisher = {{Prentice-Hall}},
  address = {{Englewood Cliffs, NJ}}
}

@article{nigg2016,
  ids = {nigg2017,nigg2017a},
  title = {Annual {{Research Review}}: {{On}} the Relations among Self-Regulation, Self-Control, Executive Functioning, Effortful Control, Cognitive Control, Impulsivity, Risk-Taking, and Inhibition for Developmental Psychopathology},
  author = {Nigg, Joel T},
  year = {2016},
  journal = {Journal of Child Psychology and Psychiatry},
  volume = {58},
  number = {4},
  pages = {361--383},
  issn = {0021-9630},
  doi = {10.1111/jcpp.12675},
  abstract = {Self-regulation (SR) is central to developmental psychopathology, but progress has been impeded by varying terminology and meanings across fields and literatures. The present review attempts to move that discussion forward by noting key sources of prior confusion such as measurement-concept confounding, and then arguing the following major points. First, the field needs a domain-general construct of SR that encompasses SR of action, emotion, and cognition and involves both top-down and bottom-up regulatory processes. This does not assume a shared core process across emotion, action, and cognition, but is intended to provide clarity on the extent of various claims about kinds of SR. Second, top-down aspects of SR need to be integrated. These include (a) basic processes that develop early and address immediate conflict signals, such as cognitive control and effortful control (EC), and (b) complex cognition and strategies for addressing future conflict, represented by the regulatory application of complex aspects of executive functioning. Executive function (EF) and cognitive control are not identical to SR because they can be used for other activities, but account for top-down aspects of SR at the cognitive level. Third, impulsivity, risk-taking, and disinhibition are distinct although overlapping; a taxonomy of the kinds of breakdowns of SR associated with psychopathology requires their differentiation. Fourth, different aspects of the SR universe can be organized hierarchically in relation to granularity, development, and time. Low-level components assemble into high-level components. This hierarchical perspective is consistent across literatures. It is hoped that the framework outlined here will facilitate integration and cross-talk among investigators working from different perspectives, and facilitate individual differences research on how SR relates to developmental psychopathology.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2016/Nigg\%202016.pdf},
  pmcid = {PMC5367959},
  pmid = {28035675},
  keywords = {Attention,Cognitive Control,executive function,Executive Function,Executive Functions,Human Development,Humans,Impulsive Behavior,impulsivity,Inhibition; Psychological,Mental Disorders,Risk-Taking,self-control,Self-Control},
  annotation = {00607},
  file = {/Users/morteza/Documents/Zotero/storage/MDLYR5SZ/Nigg_2017_Annual Research Review.pdf;/Users/morteza/Documents/Zotero/storage/U4R7AZUU/Nigg_2017_Annual Research Review.pdf}
}

@misc{NilearnConfounds,
  title = {Confound {{Strategies}} ({{Nilearn}} v9.2)},
  shorttitle = {Nilearn {{fMRIPrep Confounds Strategies}}},
  author = {Nilearn Team},
  year = {2022},
  howpublished = {https://nilearn.github.io/stable/modules/generated/nilearn.interfaces.fmriprep.load\_confounds\_strategy.html}
}

@misc{NilearnDiFuMo,
  title = {Nilearn Documentation (v0.9) - Fetch {{DiFuMo}} Brain Atlas},
  author = {{Nilearn Team}},
  year = {2022},
  journal = {nilearn.datasets.fetch\_atlas\_difumo},
  howpublished = {https://nilearn.github.io/stable/modules/generated/nilearn.datasets.fetch\_atlas\_difumo.html}
}

@misc{NilearnDosenbach2010,
  title = {Nilearn Documentation (v0.9) - {{Load}} the {{Dosenbach}} et al. {{ROIs}}},
  author = {{Nilearn Team}},
  year = {2022},
  journal = {nilearn.datasets.fetch\_coords\_dosenbach\_2010},
  howpublished = {https://nilearn.github.io/stable/modules/generated/nilearn.datasets.fetch\_coords\_dosenbach\_2010.html}
}

@article{odgers2018,
  title = {Smartphones Are Bad for Some Teens, Not All},
  author = {Odgers, Candice},
  year = {2018},
  month = feb,
  journal = {Nature},
  volume = {554},
  number = {7693},
  pages = {432--434},
  publisher = {{Nature Publishing Group}},
  doi = {10.1038/d41586-018-02109-8},
  abstract = {Young people who are already struggling offline might experience greater negative effects of life online, writes Candice Odgers.},
  copyright = {2021 Nature},
  langid = {english},
  annotation = {00093},
  file = {/Users/morteza/Documents/Zotero/storage/P8UIGS5L/Odgers_2018_Smartphones are bad for some teens, not all.pdf;/Users/morteza/Documents/Zotero/storage/U8AGCU39/d41586-018-02109-8.html}
}

@article{oei2013,
  title = {Enhancing {{Cognition}} with {{Video Games}}: {{A Multiple Game Training Study}}},
  shorttitle = {Enhancing {{Cognition}} with {{Video Games}}},
  author = {Oei, Adam C. and Patterson, Michael D.},
  editor = {Geng, Joy J.},
  year = {2013},
  month = mar,
  journal = {PLoS ONE},
  volume = {8},
  number = {3},
  pages = {e58546},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0058546},
  langid = {english},
  annotation = {00200},
  file = {/Users/morteza/Documents/Zotero/storage/HNWAXZUT/Oei and Patterson - 2013 - Enhancing Cognition with Video Games A Multiple G.pdf}
}

@article{oei2014,
  title = {Playing a Puzzle Video Game with Changing Requirements Improves Executive Functions},
  author = {Oei, Adam C. and Patterson, Michael D.},
  year = {2014},
  month = aug,
  journal = {Computers in Human Behavior},
  volume = {37},
  pages = {216--228},
  issn = {07475632},
  doi = {10.1016/j.chb.2014.04.046},
  langid = {english},
  annotation = {00042}
}

@article{oei2014a,
  title = {Are Videogame Training Gains Specific or General?},
  author = {Oei, Adam C. and Patterson, Michael D.},
  year = {2014},
  journal = {Frontiers in Systems Neuroscience},
  volume = {8},
  issn = {1662-5137},
  doi = {10.3389/fnsys.2014.00054},
  annotation = {00069}
}

@techreport{OhlssonLangley1985a,
  title = {Identifying Solution Paths in Cognitive Diagnosis},
  author = {Ohlsson, S. and Langley, P.},
  year = {1985},
  number = {CMU-RI-TR-85-2},
  address = {{Pittsburgh, PA}},
  institution = {{Carnegie Mellon University, The Robotics Institute}}
}

@article{okagaki1994,
  title = {Effects of Video Game Playing on Measures of Spatial Performance: {{Gender}} Effects in Late Adolescence},
  shorttitle = {Effects of Video Game Playing on Measures of Spatial Performance},
  author = {Okagaki, Lynn and Frensch, Peter A.},
  year = {1994},
  month = jan,
  journal = {Journal of Applied Developmental Psychology},
  volume = {15},
  number = {1},
  pages = {33--58},
  issn = {01933973},
  doi = {10.1016/0193-3973(94)90005-1},
  langid = {english},
  annotation = {00451}
}

@article{ophir2009,
  title = {Cognitive Control in Media Multitaskers},
  author = {Ophir, Eyal and Nass, Clifford and Wagner, Anthony D.},
  year = {2009},
  month = sep,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {106},
  number = {37},
  pages = {15583--15587},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.0903620106},
  abstract = {Chronic media multitasking is quickly becoming ubiquitous, although processing multiple incoming streams of information is considered a challenge for human cognition. A series of experiments addressed whether there are systematic differences in information processing styles between chronically heavy and light media multitaskers. A trait media multitasking index was developed to identify groups of heavy and light media multitaskers. These two groups were then compared along established cognitive control dimensions. Results showed that heavy media multitaskers are more susceptible to interference from irrelevant environmental stimuli and from irrelevant representations in memory. This led to the surprising result that heavy media multitaskers performed worse on a test of task-switching ability, likely due to reduced ability to filter out interference from the irrelevant task set. These results demonstrate that media multitasking, a rapidly growing societal trend, is associated with a distinct approach to fundamental information processing.},
  langid = {english},
  annotation = {01405}
}

@article{oreilly2010,
  title = {Computational Models of Cognitive Control},
  author = {O'Reilly, Randall C and Herd, Seth A and Pauli, Wolfgang M},
  year = {2010},
  month = apr,
  journal = {Current Opinion in Neurobiology},
  volume = {20},
  number = {2},
  pages = {257--261},
  issn = {09594388},
  doi = {10.1016/j.conb.2010.01.008},
  langid = {english}
}

@article{otto2013,
  title = {Working-Memory Capacity Protects Model-Based Learning from Stress},
  author = {Otto, A. Ross and Raio, Candace M. and Chiang, Alice and Phelps, Elizabeth A. and Daw, Nathaniel D.},
  year = {2013},
  month = dec,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {110},
  number = {52},
  pages = {20941--20946},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1312011110},
  abstract = {Significance             The physiological response evoked by short-lived stressful events, referred to as acute stress, impacts human decision-making. Past studies assume that stress causes people to fall back, from more cognitive or deliberative modes of choice, to more primitive or automatic modes of choice because stress impairs peoples' capacity to process information (working memory). We directly examined how acute stress affects choice in a laboratory decision-making task for which the working memory demands of the two forms of decision-making are well understood, finding that stress impaired use of sophisticated choice strategies that require working memory but did not affect use of simpler, more primitive strategies. Further, this impairment was exacerbated in individuals with smaller working memory capacity, which is related to general intelligence.           ,              Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the involvement of the dopaminergic system in model-free learning and prefrontal, central executive\textendash dependent control systems in model-based choice. Here we hypothesized that the hypothalamic-pituitary-adrenal (HPA) axis stress response\textemdash believed to have detrimental effects on prefrontal cortex function\textemdash should selectively attenuate model-based contributions to behavior. To test this, we paired an acute stressor with a sequential decision-making task that affords distinguishing the relative contributions of the two learning strategies. We assessed baseline working-memory (WM) capacity and used salivary cortisol levels to measure HPA axis stress response. We found that stress response attenuates the contribution of model-based, but not model-free, contributions to behavior. Moreover, stress-induced behavioral changes were modulated by individual WM capacity, such that low-WM-capacity individuals were more susceptible to detrimental stress effects than high-WM-capacity individuals. These results enrich existing accounts of the interplay between acute stress, working memory, and prefrontal function and suggest that executive function may be protective against the deleterious effects of acute stress.},
  langid = {english},
  annotation = {354 citations (Semantic Scholar/DOI) [2022-12-01]},
  file = {/Users/morteza/Documents/Zotero/storage/QTVKB8QL/Otto et al_2013_Working-memory capacity protects model-based learning from stress.pdf}
}

@article{otto2015,
  ids = {otto2015b},
  title = {Cognitive {{Control Predicts Use}} of {{Model-based Reinforcement Learning}}},
  author = {Otto, A. Ross and Skatova, Anya and {Madlon-Kay}, Seth and Daw, Nathaniel D.},
  year = {2015},
  month = feb,
  journal = {Journal of Cognitive Neuroscience},
  volume = {27},
  number = {2},
  pages = {319--333},
  issn = {0898-929X, 1530-8898},
  doi = {10.1162/jocn_a_00709},
  langid = {english},
  annotation = {152 citations (Semantic Scholar/DOI) [2022-12-01]},
  file = {/Users/morteza/Documents/Zotero/storage/99UK2SA7/jocn_a_00709.pdf;/Users/morteza/Documents/Zotero/storage/RA87RI6B/Otto et al. - 2015 - Cognitive Control Predicts Use of Model-based Rein.pdf}
}

@article{owen2010,
  ids = {owen2010a},
  title = {Putting Brain Training to the Test},
  author = {Owen, Adrian M. and Hampshire, Adam and Grahn, Jessica A. and Stenton, Robert and Dajani, Said and Burns, Alistair S. and Howard, Robert J. and Ballard, Clive G.},
  year = {2010},
  month = jun,
  journal = {Nature},
  volume = {465},
  number = {7299},
  pages = {775--778},
  issn = {0028-0836, 1476-4687},
  doi = {10.1038/nature09042},
  keywords = {Attention,Brain,Cognition,Computers,Exercise,Humans,Memory,Task Performance and Analysis,Thinking,Time Factors},
  annotation = {1013 citations (Semantic Scholar/DOI) [2022-11-30]},
  file = {/Users/morteza/Documents/Zotero/storage/AFS5KFNV/Owen et al. - 2010 - Putting brain training to the test.pdf;/Users/morteza/Documents/Zotero/storage/S6G5KDV3/Owen et al. - 2010 - Putting brain training to the test.pdf;/Users/morteza/Documents/Zotero/storage/VRTK6IXB/nature09042-s1.pdf;/Users/morteza/Documents/Zotero/storage/WME7KI8R/nature09042-s1.pdf;/Users/morteza/Documents/Zotero/storage/WRWHS957/Owen et al_2010_Putting brain training to the test.pdf;/Users/morteza/Documents/Zotero/storage/WYFVDGX6/Owen et al. - 2010 - Putting brain training to the test.pdf}
}

@article{palaus2017,
  title = {Neural {{Basis}} of {{Video Gaming}}: {{A Systematic Review}}},
  shorttitle = {Neural {{Basis}} of {{Video Gaming}}},
  author = {Palaus, Marc and Marron, Elena M. and {Viejo-Sobera}, Raquel and {Redolar-Ripoll}, Diego},
  year = {2017},
  journal = {Frontiers in Human Neuroscience},
  volume = {11},
  pages = {248},
  issn = {1662-5161},
  doi = {10.3389/fnhum.2017.00248},
  abstract = {Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games. Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass. Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games. Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14\% focused on video game related violence. Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies.},
  langid = {english},
  pmcid = {PMC5438999},
  pmid = {28588464},
  keywords = {addiction,cognitive improvement,functional changes,internet gaming disorder,neural correlates,neuroimaging,structural changes,video games},
  annotation = {00025},
  file = {/Users/morteza/Documents/Zotero/storage/RF6YFDYW/palaus2017.pdf;/Users/morteza/Documents/Zotero/storage/ZEAWCJZR/Palaus et al. - 2017 - Neural Basis of Video Gaming A Systematic Review.pdf}
}

@article{palaus2017a,
  title = {Cognitive Enhancement by Means of {{TMS}} and Video Game Training: Preliminary Analysis},
  author = {Palaus, Marc and {Redolar-Ripoll}, Diego and {Viejo-Sobera}, Raquel and {Mu{\~n}oz-Marr{\'o}n}, Elena},
  year = {2017},
  month = jun,
  annotation = {00000  cites: unknown}
}

@article{parong2022,
  title = {Expectation Effects in Working Memory Training},
  author = {Parong, Jocelyn and Seitz, Aaron R. and Jaeggi, Susanne M. and Green, C. Shawn},
  year = {2022},
  month = sep,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {119},
  number = {37},
  pages = {e2209308119},
  publisher = {{Proceedings of the National Academy of Sciences}},
  doi = {10.1073/pnas.2209308119},
  abstract = {There is a growing body of research focused on developing and evaluating behavioral training paradigms meant to induce enhancements in cognitive function. It has recently been proposed that one mechanism through which such performance gains could be induced involves participants' expectations of improvement. However, no work to date has evaluated whether it is possible to cause changes in cognitive function in a long-term behavioral training study by manipulating expectations. In this study, positive or negative expectations about cognitive training were both explicitly and associatively induced before either a working memory training intervention or a control intervention. Consistent with previous work, a main effect of the training condition was found, with individuals trained on the working memory task showing larger gains in cognitive function than those trained on the control task. Interestingly, a main effect of expectation was also found, with individuals given positive expectations showing larger cognitive gains than those who were given negative expectations (regardless of training condition). No interaction effect between training and expectations was found. Exploratory analyses suggest that certain individual characteristics (e.g., personality, motivation) moderate the size of the expectation effect. These results highlight aspects of methodology that can inform future behavioral interventions and suggest that participant expectations could be capitalized on to maximize training outcomes.},
  file = {/Users/morteza/Documents/Zotero/storage/6DBS6NY9/Parong et al_2022_Expectation effects in working memory training.pdf}
}

@article{pavan2019,
  title = {Visual Short-Term Memory for Coherent Motion in Video Game Players: Evidence from a Memory-Masking Paradigm},
  shorttitle = {Visual Short-Term Memory for Coherent Motion in Video Game Players},
  author = {Pavan, Andrea and Hobaek, Martine and Blurton, Steven P. and Contillo, Adriano and Ghin, Filippo and Greenlee, Mark W.},
  year = {2019},
  month = apr,
  journal = {Scientific Reports},
  volume = {9},
  number = {1},
  pages = {6027},
  issn = {2045-2322},
  doi = {10.1038/s41598-019-42593-0},
  abstract = {In this study, we investigated visual short-term memory for coherent motion in action video game players (AVGPs), non-action video game players (NAVGPs), and non-gamers (control group: CONs). Participants performed a visual memory-masking paradigm previously used with macaque monkeys and humans. In particular, we tested whether video game players form a more robust visual short-term memory trace for coherent moving stimuli during the encoding phase, and whether such memory traces are less affected by an intervening masking stimulus presented 0.2\,s after the offset of the to-be-remembered sample. The results showed that task performance of all groups was affected by the masking stimulus, but video game players were affected to a lesser extent than controls. Modelling of performance values and reaction times revealed that video game players have a lower guessing rate than CONs, and higher drift rates than CONs, indicative of more efficient perceptual decisions. These results suggest that video game players exhibit a more robust VSTM trace for moving objects and this trace is less prone to external interference.},
  copyright = {2019 The Author(s)},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/42PM9SR4/Pavan et al. - 2019 - Visual short-term memory for coherent motion in vi.pdf;/Users/morteza/Documents/Zotero/storage/2DIKNGFS/s41598-019-42593-0.html}
}

@article{pedersen2017,
  title = {The Drift Diffusion Model as the Choice Rule in Reinforcement Learning},
  author = {Pedersen, Mads Lund and Frank, Michael J. and Biele, Guido},
  year = {2017},
  month = aug,
  journal = {Psychonomic Bulletin \& Review},
  volume = {24},
  number = {4},
  pages = {1234--1251},
  issn = {1531-5320},
  doi = {10.3758/s13423-016-1199-y},
  abstract = {Current reinforcement-learning models often assume simplified decision processes that do not fully reflect the dynamic complexities of choice processes. Conversely, sequential-sampling models of decision making account for both choice accuracy and response time, but assume that decisions are based on static decision values. To combine these two computational models of decision making and learning, we implemented reinforcement-learning models in which the drift diffusion model describes the choice process, thereby capturing both within- and across-trial dynamics. To exemplify the utility of this approach, we quantitatively fit data from a common reinforcement-learning paradigm using hierarchical Bayesian parameter estimation, and compared model variants to determine whether they could capture the effects of stimulant medication in adult patients with attention-deficit hyperactivity disorder (ADHD). The model with the best relative fit provided a good description of the learning process, choices, and response times. A parameter recovery experiment showed that the hierarchical Bayesian modeling approach enabled accurate estimation of the model parameters. The model approach described here, using simultaneous estimation of reinforcement-learning and drift diffusion model parameters, shows promise for revealing new insights into the cognitive and neural mechanisms of learning and decision making, as well as the alteration of such processes in clinical groups.},
  langid = {english},
  keywords = {Bayesian modeling,Decision making,Mathematical models,Reinforcement learning},
  annotation = {133 citations (Semantic Scholar/DOI) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/IBRM9RPT/Pedersen et al_2017_The drift diffusion model as the choice rule in reinforcement learning.pdf}
}

@article{pedersen2022,
  title = {Computational {{Modeling}} of the N-{{Back Task}} in the {{ABCD Study}}: {{Associations}} of {{Drift Diffusion Model Parameters}} to {{Polygenic Scores}} of {{Mental Disorders}} and {{Cardiometabolic Diseases}}},
  shorttitle = {Computational {{Modeling}} of the N-{{Back Task}} in the {{ABCD Study}}},
  author = {Pedersen, Mads L. and Aln{\ae}s, Dag and {van der Meer}, Dennis and {Fernandez-Cabello}, Sara and Berthet, Pierre and Dahl, Andreas and Kjelkenes, Rikka and Schwarz, Emanuel and Thompson, Wesley K. and Barch, Deanna M. and Andreassen, Ole A. and Westlye, Lars T.},
  year = {2022},
  month = apr,
  journal = {Biological Psychiatry: Cognitive Neuroscience and Neuroimaging},
  issn = {2451-9022},
  doi = {10.1016/j.bpsc.2022.03.012},
  abstract = {Background Cognitive dysfunction is common in mental disorders and represents a potential risk factor in childhood. The nature and extent of associations between childhood cognitive function and polygenic risk for mental disorders is unclear. We applied computational modeling to gain insight into mechanistic processes underlying decision making and working memory in childhood and their associations with polygenic risk scores (PRSs) for mental disorders and comorbid cardiometabolic diseases. Methods We used the drift diffusion model to infer latent computational processes underlying decision making and working memory during the n-back task in 3707 children ages 9 to 10 years from the Adolescent Brain Cognitive Development (ABCD) Study. Single nucleotide polymorphism\textendash based heritability was estimated for cognitive phenotypes, including computational parameters, aggregated n-back task performance, and neurocognitive assessments. PRSs were calculated for Alzheimer's disease, bipolar disorder, coronary artery disease (CAD), major depressive disorder, obsessive-compulsive disorder, schizophrenia, and type 2 diabetes. Results Heritability estimates of cognitive phenotypes ranged from 12\% to 38\%. Bayesian mixed models revealed that slower accumulation of evidence was associated with higher PRSs for CAD and schizophrenia. Longer nondecision time was associated with higher PRSs for Alzheimer's disease and lower PRSs for CAD. Narrower decision threshold was associated with higher PRSs for CAD. Load-dependent effects on nondecision time and decision threshold were associated with PRSs for Alzheimer's disease and CAD, respectively. Aggregated neurocognitive test scores were not associated with PRSs for any of the mental or cardiometabolic phenotypes. Conclusions We identified distinct associations between computational cognitive processes and genetic risk for mental illness and cardiometabolic disease, which could represent childhood cognitive risk factors.},
  langid = {english},
  keywords = {Cardiometabolic disease,Childhood,Cognitive computational modeling,Decision making,Mental disorder,Polygenic risk scores},
  file = {/Users/morteza/Documents/Zotero/storage/X7NFMEU4/Pedersen et al_2022_Computational Modeling of the n-Back Task in the ABCD Study.pdf;/Users/morteza/Documents/Zotero/storage/NLHGM6N7/S2451902222000787.html}
}

@article{pereira2018,
  title = {How Executive Functions Are Evaluated in Children and Adolescents with Cerebral Palsy? {{A}} Systematic Review},
  author = {Pereira, Armanda and Lopes, S{\'i}lvia and Magalh{\~a}es, Paula and Sampaio, Adriana and Chaleta, Elisa and Ros{\'a}rio, Pedro},
  year = {2018},
  journal = {Frontiers in Psychology},
  volume = {9},
  pages = {21},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2018.00021},
  abstract = {Aims: The aim of the present study was to examine how executive functions are assessed in children and adolescents with Cerebral Palsy. Method: A systematic literature review was conducted using four bibliographic databases (WebScience, Scopus, PubMed, and Psycinfo), and only studies that evaluated at least one executive function were selected. Both the research and reporting of results were based on Cochrane's recommendations and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. Results: The instrument most frequently used was the D-KEFS. All studies point to the existence of impairments in the executive functions among children and adolescents with Cerebral Palsy with an impact on several cognitive and life domains. Interpretation: There is a need to further systematize the research protocols to study the executive functions and their assessment in the intervention context. Findings of this review presented a diversity of tests (e.g., D-KEFS) or tasks (e.g., The inhibitory ability task) used with children with Cerebral Palsy. However, no information was given about adaptations performed to the test/task to meet Cerebral Palsy's specificities. Future research could consider including this information, which is key both to researchers and practitioners. The results of this study have important implications and suggestions for future avenues and guidelines for research and practice.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2018/Pereira\%202018.pdf},
  pmid = {29467685},
  annotation = {00005}
}

@article{perone2021,
  title = {A {{Dynamical Reconceptualization}} of {{Executive-Function Development}}},
  author = {Perone, Sammy and Simmering, Vanessa R. and Buss, Aaron T.},
  year = {2021},
  month = nov,
  journal = {Perspectives on Psychological Science},
  volume = {16},
  number = {6},
  pages = {1198--1208},
  issn = {1745-6916, 1745-6924},
  doi = {10.1177/1745691620966792},
  abstract = {Executive function plays a foundational role in everyday behaviors across the life span. The theoretical understanding of executive-function development, however, is still a work in progress. Doebel proposed that executive-function development reflects skills using control in the service of behavior\textemdash using mental content such as knowledge and beliefs to guide behavior in a context-specific fashion. This liberating view contrasts with modular views of executive function. This new view resembles some older dynamic-systems concepts that long ago proposed that behavior reflects the assembly of multiple pieces in context. We dig into this resemblance and evaluate what else dynamic-systems theory adds to the understanding of executive-function development. We describe core dynamic-systems concepts and apply them to executive function\textemdash as conceptualized by Doebel\textemdash and through this lens explain the multilevel nature of goal-directed behavior and how a capacity to behave in a goal-directed fashion across contexts emerges over development. We then describe a dynamic systems model of goal-directed behavior during childhood and, finally, address broader theoretical implications of dynamic-systems theory and propose new translational implications for fostering children's capacity to behave in a goal-directed fashion across everyday contexts.},
  langid = {english},
  annotation = {13 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/2I5VJ843/Perone et al. - 2021 - A Dynamical Reconceptualization of Executive-Funct.pdf}
}

@article{petersen2012,
  title = {The {{Attention System}} of the {{Human Brain}}: 20 {{Years After}}},
  shorttitle = {The {{Attention System}} of the {{Human Brain}}},
  author = {Petersen, Steven E. and Posner, Michael I.},
  year = {2012},
  month = jul,
  journal = {Annual Review of Neuroscience},
  volume = {35},
  number = {1},
  pages = {73--89},
  issn = {0147-006X, 1545-4126},
  doi = {10.1146/annurev-neuro-062111-150525},
  langid = {english},
  annotation = {00000}
}

@article{pilegard2018,
  title = {Game over for {{Tetris}} as a Platform for Cognitive Skill Training},
  author = {Pilegard, Celeste and Mayer, Richard E.},
  year = {2018},
  month = jul,
  journal = {Contemporary Educational Psychology},
  volume = {54},
  pages = {29--41},
  issn = {0361476X},
  doi = {10.1016/j.cedpsych.2018.04.003},
  langid = {english},
  annotation = {00001}
}

@article{piray2021,
  title = {Linear Reinforcement Learning in Planning, Grid Fields, and Cognitive Control},
  author = {Piray, Payam and Daw, Nathaniel D.},
  year = {2021},
  month = aug,
  journal = {Nature Communications},
  volume = {12},
  number = {1},
  pages = {4942},
  issn = {2041-1723},
  doi = {10.1038/s41467-021-25123-3},
  abstract = {It is thought that the brain's judicious reuse of previous computation underlies our ability to plan flexibly, but also that inappropriate reuse gives rise to inflexibilities like habits and compulsion. Yet we lack a complete, realistic account of either. Building on control engineering, here we introduce a model for decision making in the brain that reuses a temporally abstracted map of future events to enable biologically-realistic, flexible choice at the expense of specific, quantifiable biases. It replaces the classic nonlinear, model-based optimization with a linear approximation that softly maximizes around (and is weakly biased toward) a default policy. This solution demonstrates connections between seemingly disparate phenomena across behavioral neuroscience, notably flexible replanning with biases and cognitive control. It also provides insight into how the brain can represent maps of long-distance contingencies stably and componentially, as in entorhinal response fields, and exploit them to guide choice even under changing goals.},
  langid = {english},
  pmcid = {PMC8368103},
  pmid = {34400622},
  keywords = {Brain,Cognition,Decision Making,Humans,Learning,Models; Neurological,Reinforcement; Psychology},
  file = {/Users/morteza/Documents/Zotero/storage/AVEG7R6C/Piray_Daw_2021_Linear reinforcement learning in planning, grid fields, and cognitive control.pdf}
}

@article{poldrack2006,
  title = {Can Cognitive Processes Be Inferred from Neuroimaging Data?},
  author = {Poldrack, R},
  year = {2006},
  month = feb,
  journal = {Trends in Cognitive Sciences},
  volume = {10},
  number = {2},
  pages = {59--63},
  issn = {13646613},
  doi = {10.1016/j.tics.2005.12.004},
  langid = {english},
  annotation = {1791 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/BVRGVQYA/Poldrack - 2006 - Can cognitive processes be inferred from neuroimag.pdf}
}

@article{poldrack2011,
  title = {The {{Cognitive Atlas}}: {{Toward}} a {{Knowledge Foundation}} for {{Cognitive Neuroscience}}},
  shorttitle = {The {{Cognitive Atlas}}},
  author = {Poldrack, Russell A. and Kittur, Aniket and Kalar, Donald and Miller, Eric and Seppa, Christian and Gil, Yolanda and Parker, D. Stott and Sabb, Fred W. and Bilder, Robert M.},
  year = {2011},
  journal = {Frontiers in Neuroinformatics},
  volume = {5},
  issn = {1662-5196},
  doi = {10.3389/fninf.2011.00017},
  annotation = {276 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/BN7GNJS6/Poldrack et al. - 2011 - The Cognitive Atlas Toward a Knowledge Foundation.pdf}
}

@article{poldrack2015,
  title = {Long-Term Neural and Physiological Phenotyping of a Single Human},
  author = {Poldrack, Russell A. and Laumann, Timothy O. and Koyejo, Oluwasanmi and Gregory, Brenda and Hover, Ashleigh and Chen, Mei-Yen and Gorgolewski, Krzysztof J. and Luci, Jeffrey and Joo, Sung Jun and Boyd, Ryan L. and {Hunicke-Smith}, Scott and Simpson, Zack Booth and Caven, Thomas and Sochat, Vanessa and Shine, James M. and Gordon, Evan and Snyder, Abraham Z. and Adeyemo, Babatunde and Petersen, Steven E. and Glahn, David C. and Reese Mckay, D. and Curran, Joanne E. and G{\"o}ring, Harald H. H. and Carless, Melanie A. and Blangero, John and Dougherty, Robert and Leemans, Alexander and Handwerker, Daniel A. and Frick, Laurie and Marcotte, Edward M. and Mumford, Jeanette A.},
  year = {2015},
  month = dec,
  journal = {Nature Communications},
  volume = {6},
  number = {1},
  pages = {8885},
  issn = {2041-1723},
  doi = {10.1038/ncomms9885},
  langid = {english},
  annotation = {312 citations (Semantic Scholar/DOI) [2022-11-29]}
}

@article{poldrack2020,
  title = {Establishment of {{Best Practices}} for {{Evidence}} for {{Prediction}}: {{A Review}}},
  shorttitle = {Establishment of {{Best Practices}} for {{Evidence}} for {{Prediction}}},
  author = {Poldrack, Russell A. and Huckins, Grace and Varoquaux, Gael},
  year = {2020},
  month = may,
  journal = {JAMA Psychiatry},
  volume = {77},
  number = {5},
  pages = {534},
  issn = {2168-622X},
  doi = {10.1001/jamapsychiatry.2019.3671},
  langid = {english},
  annotation = {252 citations (Semantic Scholar/DOI) [2022-12-12]}
}

@article{powers2013,
  title = {Effects of Video-Game Play on Information Processing: {{A}} Meta-Analytic Investigation},
  shorttitle = {Effects of Video-Game Play on Information Processing},
  author = {Powers, Kasey L. and Brooks, Patricia J. and Aldrich, Naomi J. and Palladino, Melissa A. and Alfieri, Louis},
  year = {2013},
  month = dec,
  journal = {Psychonomic Bulletin \& Review},
  volume = {20},
  number = {6},
  pages = {1055--1079},
  issn = {1069-9384, 1531-5320},
  doi = {10.3758/s13423-013-0418-z},
  langid = {english},
  annotation = {00000}
}

@incollection{powers2014,
  title = {Evaluating the {{Specificity}} of {{Effects}} of {{Video Game Training}}},
  booktitle = {Learning by {{Playing}}},
  author = {Powers, Kasey L. and Brooks, Patricia J.},
  editor = {Blumberg, Fran C.},
  year = {2014},
  month = may,
  pages = {302--330},
  publisher = {{Oxford University Press}},
  doi = {10.1093/acprof:osobl/9780199896646.003.0021},
  isbn = {978-0-19-989664-6},
  annotation = {00000}
}

@article{prena2018,
  title = {Game {{Mechanics Matter}}: {{Differences}} in {{Video Game Conditions Influence Memory Performance}}},
  shorttitle = {Game {{Mechanics Matter}}},
  author = {Prena, Kelsey and Reed, Amanda and Weaver, Andrew J. and Newman, Sharlene D.},
  year = {2018},
  month = may,
  journal = {Communication Research Reports},
  volume = {35},
  number = {3},
  pages = {222--231},
  issn = {0882-4096, 1746-4099},
  doi = {10.1080/08824096.2018.1428545},
  langid = {english},
  annotation = {00002}
}

@article{pujol2016,
  title = {Video Gaming in School Children: {{How}} Much Is Enough?: {{Video Gaming}}},
  shorttitle = {Video Gaming in School Children},
  author = {Pujol, Jesus and Fenoll, Raquel and Forns, Joan and Harrison, Ben J. and {Mart{\'i}nez-Vilavella}, Gerard and Maci{\`a}, D{\'i}dac and {Alvarez-Pedrerol}, Mar and {Blanco-Hinojo}, Laura and {Gonz{\'a}lez-Ortiz}, Sof{\'i}a and Deus, Joan and Sunyer, Jordi},
  year = {2016},
  month = sep,
  journal = {Annals of Neurology},
  volume = {80},
  number = {3},
  pages = {424--433},
  issn = {03645134},
  doi = {10.1002/ana.24745},
  langid = {english},
  annotation = {00000}
}

@misc{rafiei2022,
  title = {{{RTNet}}: {{A}} Neural Network That Exhibits the Signatures of Human Perceptual Decision Making},
  shorttitle = {{{RTNet}}},
  author = {Rafiei, Farshad and Rahnev, Dobromir},
  year = {2022},
  month = aug,
  pages = {2022.08.23.505015},
  publisher = {{bioRxiv}},
  doi = {10.1101/2022.08.23.505015},
  abstract = {Convolutional neural networks currently provide the best models of biological vision. However, their decision behavior, including the facts that they are deterministic and use equal number of computations for easy and difficult stimuli, differs markedly from human decision-making, thus limiting their applicability as models of human perceptual behavior. Here we develop a new neural network, RTNet, that generates stochastic decisions and human-like response time (RT) distributions, and also reproduces all foundational features of human accuracy, RT, and confidence. To test RTNet's ability to predict human behavior on novel images, we collected accuracy, RT, and confidence data from 60 human subjects performing a digit discrimination task. We found that the accuracy, RT, and confidence produced by RTNet for individual novel images correlated with the same quantities produced by human subjects. Critically, human subjects who were more similar to the average human performance were also found to be closer to RTNet's predictions. Overall, RTNet is the first neural network that exhibits all basic signatures of perceptual decision making, and therefore provides the most detailed model of all critical features of human behavior for novel images.},
  chapter = {New Results},
  copyright = {\textcopyright{} 2022, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution-NonCommercial-NoDerivs 4.0 International), CC BY-NC-ND 4.0, as described at http://creativecommons.org/licenses/by-nc-nd/4.0/},
  langid = {english},
  annotation = {0 citations (Semantic Scholar/DOI) [2022-11-29]},
  file = {/Users/morteza/Documents/Zotero/storage/W8AZYMY6/Rafiei_Rahnev_2022_RTNet.pdf;/Users/morteza/Documents/Zotero/storage/YFJJHW9I/Rafiei and Rahnev - 2022 - RTNet A neural network that exhibits the signatur.pdf;/Users/morteza/Documents/Zotero/storage/RM7J8WI7/2022.08.23.html}
}

@phdthesis{ralph2014,
  type = {Thesis},
  title = {Statistical Manipulation and Control Strategies of the N-Back Task},
  author = {Ralph, Jason},
  year = {2014},
  address = {{Troy, NY}},
  abstract = {The impact of task environments on cognitive strategies are well known and have formed the basis of many important findings in cognitive science. However, these effects are often overlooked in research design. The n-back, thought to measure working memory and executive control capacity, is especially prone to misinterpretation because of a lack of standardization in how researchers administer the task. This dissertation chronicles a set of experiments investigating experimental design variation along several dimensions. The results showed that differences in stimulus frequency distributions and the ratio of targets to lures cause variation in performance by stimulating strategic differences. Variations in n-back performance across different populations or different n-back paradigms are often interpreted in terms of resource capacity or strategic views of memory, attention, and cognitive control. Hence, the results of this work highlight the importance of understanding the connection between strategy and the environment when applying cognitive theory to tasks like the n-back.; The impact of task environments on cognitive strategies are well known and have formed the basis of many important findings in cognitive science. However, these effects are often overlooked in research design. The n-back, thought to measure working memory and executive control capacity, is especially prone to misinterpretation because of a lack of standardization in how researchers administer the task. This dissertation chronicles a set of experiments investigating experimental design variation along several dimensions. The results showed that differences in stimulus frequency distributions and the ratio of targets to lures cause variation in performance by stimulating strategic differences. Variations in n-back performance across different populations or different n-back paradigms are often interpreted in terms of resource capacity or strategic views of memory, attention, and cognitive control. Hence, the results of this work highlight the importance of understanding the connection between strategy and the environment when applying cognitive theory to tasks like the n-back.},
  langid = {english},
  school = {Rensselaer Polytechnic Institute}
}

@misc{ramstedt2019,
  title = {Real-{{Time Reinforcement Learning}}},
  author = {Ramstedt, Simon and Pal, Christopher},
  year = {2019},
  month = dec,
  number = {arXiv:1911.04448},
  eprint = {1911.04448},
  eprinttype = {arxiv},
  primaryclass = {cs, stat},
  publisher = {{arXiv}},
  abstract = {Markov Decision Processes (MDPs), the mathematical framework underlying most algorithms in Reinforcement Learning (RL), are often used in a way that wrongfully assumes that the state of an agent's environment does not change during action selection. As RL systems based on MDPs begin to find application in realworld, safety-critical situations, this mismatch between the assumptions underlying classical MDPs and the reality of real-time computation may lead to undesirable outcomes. In this paper, we introduce a new framework, in which states and actions evolve simultaneously and show how it is related to the classical MDP formulation. We analyze existing algorithms under the new real-time formulation and show why they are suboptimal when used in real time. We then use those insights to create a new algorithm Real-Time Actor-Critic (RTAC) that outperforms the existing stateof-the-art continuous control algorithm Soft Actor-Critic both in real-time and nonreal-time settings. Code and videos can be found at github.com/rmst/rtrl.},
  archiveprefix = {arXiv},
  langid = {english},
  keywords = {Computer Science - Machine Learning,FOS: Computer and information sciences,Machine Learning (cs.LG),Machine Learning (stat.ML),Statistics - Machine Learning},
  annotation = {27 citations (Semantic Scholar/arXiv) [2022-10-18]},
  file = {/Users/morteza/Documents/Zotero/storage/X6IUHZL2/Ramstedt and Pal - 2019 - Real-Time Reinforcement Learning.pdf}
}

@article{ratcliff1978,
  ids = {ratcliff},
  title = {A Theory of Memory Retrieval.},
  author = {Ratcliff, Roger},
  year = {1978},
  journal = {Psychological review},
  volume = {85},
  number = {2},
  pages = {59},
  file = {/Users/morteza/Documents/Zotero/storage/GA4Q2XYK/Ratcliff_1978.pdf;/Users/morteza/Documents/Zotero/storage/PHTB8NAB/Ratcliff_1978_A theory of memory retrieval.pdf}
}

@article{ratcliff2008,
  title = {The {{Diffusion Decision Model}}: {{Theory}} and {{Data}} for {{Two-Choice Decision Tasks}}},
  shorttitle = {The {{Diffusion Decision Model}}},
  author = {Ratcliff, Roger and McKoon, Gail},
  year = {2008},
  month = apr,
  journal = {Neural computation},
  volume = {20},
  number = {4},
  pages = {873--922},
  issn = {0899-7667},
  doi = {10.1162/neco.2008.12-06-420},
  abstract = {The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data\textemdash accuracy, mean response times, and response time distributions\textemdash into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either speed or accuracy affect the criterial amounts of information that a subject requires before initiating a response; and the relative proportions of the two stimuli affect biases in drift rate and starting point. The experiments also illustrate the strong constraints that ensure the model is empirically testable and potentially falsifiable. The broad range of applications of the model is also reviewed, including research in the domains of aging and neurophysiology.},
  pmcid = {PMC2474742},
  pmid = {18085991},
  file = {/Users/morteza/Documents/Zotero/storage/SLGQ469Y/Ratcliff_McKoon_2008_The Diffusion Decision Model.pdf}
}

@article{ratcliff2013,
  title = {Modeling {{Confidence Judgments}}, {{Response Times}}, and {{Multiple Choices}} in {{Decision Making}}: {{Recognition Memory}} and {{Motion Discrimination}}},
  shorttitle = {Modeling {{Confidence Judgments}}, {{Response Times}}, and {{Multiple Choices}} in {{Decision Making}}},
  author = {Ratcliff, Roger and Starns, Jeffrey J.},
  year = {2013},
  month = jul,
  journal = {Psychological review},
  volume = {120},
  number = {3},
  pages = {697},
  publisher = {{NIH Public Access}},
  doi = {10.1037/a0033152},
  abstract = {Confidence in judgments is a fundamental aspect of decision making, and tasks that collect confidence judgments are an instantiation of multiple-choice decision making. We present a model for confidence judgments in recognition memory tasks that uses ...},
  langid = {english},
  pmid = {23915088},
  annotation = {123 citations (Semantic Scholar/DOI) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/QG5XVFMH/Ratcliff_Starns_2013_Modeling Confidence Judgments, Response Times, and Multiple Choices in Decision.pdf;/Users/morteza/Documents/Zotero/storage/6NTCX8QB/PMC4106127.html}
}

@article{ratcliff2016,
  title = {Diffusion {{Decision Model}}: {{Current Issues}} and {{History}}},
  shorttitle = {Diffusion {{Decision Model}}},
  author = {Ratcliff, Roger and Smith, Philip L. and Brown, Scott D. and McKoon, Gail},
  year = {2016},
  month = apr,
  journal = {Trends in Cognitive Sciences},
  volume = {20},
  number = {4},
  pages = {260--281},
  issn = {13646613},
  doi = {10.1016/j.tics.2016.01.007},
  langid = {english},
  annotation = {758 citations (Semantic Scholar/DOI) [2022-11-29]},
  file = {/Users/morteza/Documents/Zotero/storage/2JCHUEWL/Ratcliff_TiCS_2016.pdf;/Users/morteza/Documents/Zotero/storage/RDFGDRT7/Ratcliff et al_2016_Diffusion Decision Model.pdf}
}

@article{ratcliff2018,
  title = {Modeling {{Individual Differences}} in the {{Go}}/{{No-go Task}} with a {{Diffusion Model}}},
  author = {Ratcliff, Roger and {Huang-Pollock}, Cynthia and McKoon, Gail},
  year = {2018},
  month = jan,
  journal = {Decision (Washington, D.C.)},
  volume = {5},
  number = {1},
  pages = {42--62},
  issn = {2325-9965},
  doi = {10.1037/dec0000065},
  abstract = {The go/no-go task is one in which there are two choices, but the subject responds only to one of them, waiting out a time-out for the other choice. The task has a long history in psychology and modern applications in the clinical/neuropsychological domain. In this article we fit a diffusion model to both experimental and simulated data. The model is the same as the two-choice model and assumes that there are two decision boundaries and termination at one of them produces a response and at the other, the subject waits out the trial. In prior modeling, both two-choice and go/no-go data were fit simultaneously and only group data were fit. Here the model is fit to just go/no-go data for individual subjects. This allows analyses of individual differences which is important for clinical applications. First, we fit the standard two-choice model to two-choice data and fit the go/no-go model to RTs from one of the choices and accuracy from the two-choice data. Parameter values were similar between the models and had high correlations. The go/no-go model was also fit to data from a go/no-go version of the task with the same subjects as the two-choice task. A simulation study with ranges of parameter values that are obtained in practice showed similar parameter recovery between the two-choice and go/no-go models. Results show that a diffusion model with an implicit (no response) boundary can be fit to data with almost the same accuracy as fitting the two-choice model to two-choice data.},
  langid = {english},
  pmcid = {PMC5796558},
  pmid = {29404378},
  keywords = {CPT task,Diffusion model,go/no-go task,reaction time,response accuracy},
  annotation = {38 citations (Semantic Scholar/DOI) [2022-11-29]},
  file = {/Users/morteza/Documents/Zotero/storage/6HKKV6BG/Ratcliff et al_2018_Modeling Individual Differences in the Go-No-go Task with a Diffusion Model.pdf}
}

@misc{reed2022,
  title = {A {{Generalist Agent}}},
  author = {Reed, Scott and Zolna, Konrad and Parisotto, Emilio and Colmenarejo, Sergio Gomez and Novikov, Alexander and {Barth-Maron}, Gabriel and Gimenez, Mai and Sulsky, Yury and Kay, Jackie and Springenberg, Jost Tobias and Eccles, Tom and Bruce, Jake and Razavi, Ali and Edwards, Ashley and Heess, Nicolas and Chen, Yutian and Hadsell, Raia and Vinyals, Oriol and Bordbar, Mahyar and {de Freitas}, Nando},
  year = {2022},
  month = nov,
  number = {arXiv:2205.06175},
  eprint = {2205.06175},
  eprinttype = {arxiv},
  primaryclass = {cs},
  publisher = {{arXiv}},
  abstract = {Inspired by progress in large-scale language modeling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we refer to as Gato, works as a multi-modal, multi-task, multi-embodiment generalist policy. The same network with the same weights can play Atari, caption images, chat, stack blocks with a real robot arm and much more, deciding based on its context whether to output text, joint torques, button presses, or other tokens. In this report we describe the model and the data, and document the current capabilities of Gato.},
  archiveprefix = {arXiv},
  keywords = {Computer Science - Artificial Intelligence,Computer Science - Computation and Language,Computer Science - Machine Learning,Computer Science - Robotics},
  annotation = {19 citations (Semantic Scholar/arXiv) [2022-12-03]},
  file = {/Users/morteza/Documents/Zotero/storage/TPFWIIQA/Reed et al. - 2022 - A Generalist Agent.pdf;/Users/morteza/Documents/Zotero/storage/RYB3BFYN/2205.html}
}

@article{reineberg2015,
  title = {Resting-State Networks Predict Individual Differences in Common and Specific Aspects of Executive Function},
  author = {Reineberg, Andrew E. and {Andrews-Hanna}, Jessica R. and Depue, Brendan E. and Friedman, Naomi P. and Banich, Marie T.},
  year = {2015},
  month = jan,
  journal = {NeuroImage},
  volume = {104},
  pages = {69--78},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2014.09.045},
  langid = {english}
}

@article{rey-mermet2021,
  title = {Neither Measurement Error nor Speed-Accuracy Trade-Offs Explain the Difficulty of Establishing Attentional Control as a Psychometric Construct: {{Evidence}} from a Latent-Variable Analysis Using Diffusion Modeling},
  author = {{Rey-Mermet}, Alodie and Singmann, Henrik and Oberauer, Klaus},
  year = {2021},
  month = mar,
  journal = {PsyArXiv},
  abstract = {Attentional control refers to the ability to maintain and implement a goal and goal-relevant information when facing distraction. So far, previous research has failed to substantiate strong evidence for a psychometric construct of attentional control. This has been argued to result from two methodological shortcomings: (a) the neglect of individual differences in speed-accuracy trade-offs when only speed or accuracy is used as dependent variable, and (b) the difficulty of isolating attentional control from measurement error. To overcome both issues, we combined hierarchical-Bayesian Wiener diffusion modeling with structural equation modeling. We re-analyzed the dataset from Rey-Mermet, Gade, and Oberauer (2018), which includes data from a large set of attentional-control tasks from young and older adults. Even when accounting for speed-accuracy trade-offs and removing measurement error, measures of attentional control failed to correlate with each other and to load on a latent variable. These results emphasize the necessity of rethinking attentional control.}
}

@article{richards2019,
  title = {A Deep Learning Framework for Neuroscience},
  author = {Richards, Blake A. and Lillicrap, Timothy P. and Beaudoin, Philippe and Bengio, Yoshua and Bogacz, Rafal and Christensen, Amelia and Clopath, Claudia and Costa, Rui Ponte and {de Berker}, Archy and Ganguli, Surya and Gillon, Colleen J. and Hafner, Danijar and Kepecs, Adam and Kriegeskorte, Nikolaus and Latham, Peter and Lindsay, Grace W. and Miller, Kenneth D. and Naud, Richard and Pack, Christopher C. and Poirazi, Panayiota and Roelfsema, Pieter and Sacramento, Jo{\~a}o and Saxe, Andrew and Scellier, Benjamin and Schapiro, Anna C. and Senn, Walter and Wayne, Greg and Yamins, Daniel and Zenke, Friedemann and Zylberberg, Joel and Therien, Denis and Kording, Konrad P.},
  year = {2019},
  month = nov,
  journal = {Nature Neuroscience},
  volume = {22},
  number = {11},
  pages = {1761--1770},
  issn = {1097-6256, 1546-1726},
  doi = {10.1038/s41593-019-0520-2},
  langid = {english}
}

@article{rideout2003,
  title = {Zero to Six: {{Electronic}} Media in the Lives of Infants, Toddlers and Preschoolers.},
  author = {Rideout, Victoria J and Vandewater, Elizabeth A and Wartella, Ellen A},
  year = {2003},
  publisher = {ERIC},
  annotation = {00815}
}

@article{rideout2010,
  title = {Generation {{M}} 2: {{Media}} in the {{Lives}} of 8-to 18-{{Year-Olds}}.},
  author = {Rideout, Victoria J and Foehr, Ulla G and Roberts, Donald F},
  year = {2010},
  journal = {Henry J. Kaiser Family Foundation},
  publisher = {ERIC},
  annotation = {03292}
}

@article{rideout2010a,
  title = {Generation {{M}} [Superscript 2]: {{Media}} in the {{Lives}} of 8-to 18-{{Year-Olds}}.},
  shorttitle = {Generation {{M}} [Superscript 2]},
  author = {Rideout, Victoria J. and Foehr, Ulla G. and Roberts, Donald F.},
  year = {2010},
  journal = {Henry J. Kaiser Family Foundation},
  annotation = {01099},
  file = {/Users/morteza/Documents/Zotero/storage/AU2RTSUG/kff2010.pdf}
}

@techreport{rideout2015,
  title = {The {{Common Sense Census}}: {{Media Use}} by {{Tweens}} and {{Teens}}},
  author = {Rideout, Victoria},
  year = {2015},
  pages = {104},
  address = {{San Francisco}},
  institution = {{Common Sense Media}},
  langid = {english},
  annotation = {00111},
  file = {/Users/morteza/Documents/Zotero/storage/VWYFY27K/Rideout_2015_The Common Sense Census.pdf}
}

@article{rideout2016,
  title = {Measuring Time Spent with Media: The {{Common Sense}} Census of Media Use by {{US}} 8- to 18-Year-Olds},
  shorttitle = {Measuring Time Spent with Media},
  author = {Rideout, Vicky},
  year = {2016},
  month = jan,
  journal = {Journal of Children and Media},
  volume = {10},
  number = {1},
  pages = {138--144},
  issn = {1748-2798, 1748-2801},
  doi = {10.1080/17482798.2016.1129808},
  langid = {english},
  annotation = {00038}
}

@article{ritz2022,
  title = {Cognitive {{Control}} as a {{Multivariate Optimization Problem}}},
  author = {Ritz, Harrison and Leng, Xiamin and Shenhav, Amitai},
  year = {2022},
  month = mar,
  journal = {Journal of Cognitive Neuroscience},
  volume = {34},
  number = {4},
  pages = {569--591},
  issn = {1530-8898},
  doi = {10.1162/jocn_a_01822},
  abstract = {A hallmark of adaptation in humans and other animals is our ability to control how we think and behave across different settings. Research has characterized the various forms cognitive control can take-including enhancement of goal-relevant information, suppression of goal-irrelevant information, and overall inhibition of potential responses-and has identified computations and neural circuits that underpin this multitude of control types. Studies have also identified a wide range of situations that elicit adjustments in control allocation (e.g., those eliciting signals indicating an error or increased processing conflict), but the rules governing when a given situation will give rise to a given control adjustment remain poorly understood. Significant progress has recently been made on this front by casting the allocation of control as a decision-making problem. This approach has developed unifying and normative models that prescribe when and how a change in incentives and task demands will result in changes in a given form of control. Despite their successes, these models, and the experiments that have been developed to test them, have yet to face their greatest challenge: deciding how to select among the multiplicity of configurations that control can take at any given time. Here, we will lay out the complexities of the inverse problem inherent to cognitive control allocation, and their close parallels to inverse problems within motor control (e.g., choosing between redundant limb movements). We discuss existing solutions to motor control's inverse problems drawn from optimal control theory, which have proposed that effort costs act to regularize actions and transform motor planning into a well-posed problem. These same principles may help shed light on how our brains optimize over complex control configuration, while providing a new normative perspective on the origins of mental effort.},
  langid = {english},
  pmcid = {PMC8939373},
  pmid = {35061027},
  keywords = {Animals,Brain,Cognition,Humans,Inhibition; Psychological,Movement},
  file = {/Users/morteza/Documents/Zotero/storage/P5GWH347/Ritz et al_2022_Cognitive Control as a Multivariate Optimization Problem.pdf}
}

@misc{ritz2022a,
  title = {Cognitive Control as a Multivariate Optimization Problem},
  author = {Ritz, Harrison and Leng, Xiamin and Shenhav, Amitai},
  year = {2022},
  month = jan,
  number = {arXiv:2110.00668},
  eprint = {2110.00668},
  eprinttype = {arxiv},
  primaryclass = {q-bio},
  publisher = {{arXiv}},
  doi = {10.48550/arXiv.2110.00668},
  abstract = {Research has characterized the various forms cognitive control can take, including enhancement of goal-relevant information, suppression of goal-irrelevant information, and overall inhibition of potential responses, and has identified computations and neural circuits that underpin this multitude of control types. Studies have also identified a wide range of situations that elicit adjustments in control allocation (e.g., those eliciting signals indicating an error or increased processing conflict), but the rules governing when a given situation will give rise to a given control adjustment remain poorly understood. Significant progress has recently been made on this front by casting the allocation of control as a decision-making problem, and developing unifying and normative models that prescribe when and how a change in incentives and task demands will result in changes in a given form of control. Despite their successes, these models, and the experiments that have been developed to test them, have yet to face their greatest challenge: deciding how to allocate control across the multiplicity of control signals that one could engage at any given time. Here, we will lay out the complexities of the inverse problem inherent to cognitive control allocation, and their close parallels to inverse problems within motor control (e.g., choosing between redundant limb movements). We discuss existing solutions to motor control`s inverse problems drawn from optimal control theory, which have proposed that effort costs act to regularize actions and transform motor planning into a well-posed problem. These same principles may help shed light on how our brains optimize over complex control configuration, while providing a new normative perspective on the origins of mental effort.},
  archiveprefix = {arXiv},
  keywords = {Quantitative Biology - Neurons and Cognition},
  annotation = {14 citations (Semantic Scholar/arXiv) [2023-02-15]},
  file = {/Users/morteza/Documents/Zotero/storage/9EBDEZPE/Ritz et al_2022_Cognitive control as a multivariate optimization problem.pdf;/Users/morteza/Documents/Zotero/storage/9UWQWM2Q/2110.html}
}

@article{roberts2005,
  title = {Generation {{M}}: {{Media}} in the {{Lives}} of 8-18 {{Year-Olds}}, {{Kaiser Family Foundation}}},
  author = {Roberts, DF and Foehr, UG and Rideout, Victoria},
  year = {2005},
  journal = {March. http://www. kff. org/entmedia/entmedia030905nr. cfm},
  annotation = {00004}
}

@article{robertson1997,
  title = {`{{Oops}}!': {{Performance}} Correlates of Everyday Attentional Failures in Traumatic Brain Injured and Normal Subjects},
  shorttitle = {`{{Oops}}!'},
  author = {Robertson, Ian H and Manly, Tom and Andrade, Jackie and Baddeley, Bart T and Yiend, Jenny},
  year = {1997},
  month = may,
  journal = {Neuropsychologia},
  volume = {35},
  number = {6},
  pages = {747--758},
  issn = {00283932},
  doi = {10.1016/S0028-3932(97)00015-8},
  langid = {english},
  annotation = {1658 citations (Semantic Scholar/DOI) [2022-12-14]}
}

@article{rogers2014,
  title = {Parallel {{Distributed Processing}} at 25: Further Explorations in the Microstructure of Cognition},
  shorttitle = {Parallel {{Distributed Processing}} at 25},
  author = {Rogers, Timothy T. and McClelland, James L.},
  year = {2014},
  month = aug,
  journal = {Cognitive Science},
  volume = {38},
  number = {6},
  pages = {1024--1077},
  issn = {1551-6709},
  doi = {10.1111/cogs.12148},
  abstract = {This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called "deep networks"-systems that build on key ideas presented in the PDP volumes.},
  langid = {english},
  pmid = {25087578},
  keywords = {Cognition,Cognitive control,Cognitive Science,Connectionist models,Consciousness,Humans,Language,Learning,Memory,Models; Neurological,Neural networks,Neural Networks; Computer,Perception},
  annotation = {125 citations (Semantic Scholar/DOI) [2022-10-27]}
}

@article{roxin2019,
  title = {Drift\textendash Diffusion Models for Multiple-Alternative Forced-Choice Decision Making},
  author = {Roxin, Alex},
  year = {2019},
  month = jul,
  journal = {The Journal of Mathematical Neuroscience},
  volume = {9},
  number = {1},
  pages = {5},
  issn = {2190-8567},
  doi = {10.1186/s13408-019-0073-4},
  abstract = {The canonical computational model for the cognitive process underlying two-alternative forced-choice decision making is the so-called drift\textendash diffusion model (DDM). In this model, a decision variable keeps track of the integrated difference in sensory evidence for two competing alternatives. Here I extend the notion of a drift\textendash diffusion process to multiple alternatives. The competition between n alternatives takes place in a linear subspace of \$n-1\$dimensions; that is, there are \$n-1\$decision variables, which are coupled through correlated noise sources. I derive the multiple-alternative DDM starting from a system of coupled, linear firing rate equations. I also show that a Bayesian sequential probability ratio test for multiple alternatives is, in fact, equivalent to these same linear DDMs, but with time-varying thresholds. If the original neuronal system is nonlinear, one can once again derive a model describing a lower-dimensional diffusion process. The dynamics of the nonlinear DDM can be recast as the motion of a particle on a potential, the general form of which is given analytically for an arbitrary number of alternatives.},
  langid = {english},
  keywords = {Decision making,Networks,Winner-take-all},
  annotation = {7 citations (Semantic Scholar/DOI) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/FF3K46XR/Roxin_2019_Drift–diffusion models for multiple-alternative forced-choice decision making.pdf}
}

@article{ruch2020,
  title = {Can X2vec Save Lives? {{Integrating}} Graph and Language Embeddings for Automatic Mental Health Classification},
  author = {Ruch, Alexander},
  year = {2020},
  journal = {Journal of Physics: Complexity},
  volume = {1},
  number = {3},
  abstract = {Graph and language embedding models are becoming commonplace in large scale analyses given their ability to represent complex sparse data densely in low-dimensional space. Integrating these models' complementary relational and communicative data may be especially helpful if predicting rare events or classifying members of hidden populations\textemdash tasks requiring huge and sparse datasets for generalizable analyses. For example, due to social stigma and comorbidities, mental health support groups often form in amorphous online groups. Predicting suicidality among individuals in these settings using standard network analyses is prohibitive due to resource limits (e.g., memory), and adding auxiliary data like text to such models exacerbates complexity- and sparsity-related issues. Here, I show how merging graph and language embedding models (metapath2vec and doc2vec) avoids these limits and extracts unsupervised clustering data without domain expertise or feature engineering. Graph and language distances to a suicide support group have little correlation ({$\rho$} \textexclamdown{} 0.23), implying the two models are not embedding redundant information. When used separately to predict suicidality among individuals, graph and language data generate relatively accurate results (69\% and 76\%, respectively) but have moderately large false-positive (25\% and 21\%, respectively) and false-negative (38\% and 27\%, respectively) rates; however, when integrated, both data produce highly accurate predictions (90\%, with 10\% false-positives and 12\% false-negatives). Visualizing graph embeddings annotated with predictions of potentially suicidal individuals shows the integrated model could classify such individuals even if they are positioned far from the support group. These results extend research on the importance of simultaneously analyzing behavior and language in massive networks and efforts to integrate embedding models for different kinds of data when predicting and classifying, particularly when they involve rare events.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/Ruch{$_2$}020{$_1$}.pdf}
}

@book{russell2020,
  title = {Human Compatible: Artificial Intelligence and the Problem of Control},
  shorttitle = {Human Compatible},
  author = {Russell, Stuart J.},
  year = {2020},
  publisher = {{Penguin Books}},
  address = {{[London] New York NY}},
  isbn = {978-0-14-198750-7 978-0-525-50776-5},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/MUGQUZG2/Russell - 2020 - Human compatible artificial intelligence and the .pdf}
}

@article{sabb2008,
  title = {A Collaborative Knowledge Base for Cognitive Phenomics},
  author = {Sabb, F W and Bearden, C E and Glahn, D C and Parker, D S and Freimer, N and Bilder, R M},
  year = {2008},
  month = apr,
  journal = {Molecular Psychiatry},
  volume = {13},
  number = {4},
  pages = {350--360},
  issn = {1359-4184, 1476-5578},
  doi = {10.1038/sj.mp.4002124},
  langid = {english},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2008/Sabb\%202008.pdf},
  pmcid = {PMC3952067},
  pmid = {18180765},
  annotation = {00086}
}

@article{sala2018,
  title = {Video Game Training Does Not Enhance Cognitive Ability: {{A}} Comprehensive Meta-Analytic Investigation},
  shorttitle = {Video Game Training Does Not Enhance Cognitive Ability},
  author = {Sala, Giovanni and Tatlidil, K. Semir and Gobet, Fernand},
  year = {2018},
  month = feb,
  journal = {Psychological Bulletin},
  volume = {144},
  number = {2},
  pages = {111--139},
  issn = {1939-1455},
  doi = {10.1037/bul0000139},
  abstract = {As a result of considerable potential scientific and societal implications, the possibility of enhancing cognitive ability by training has been one of the most influential topics of cognitive psychology in the last two decades. However, substantial research into the psychology of expertise and a recent series of meta-analytic reviews have suggested that various types of cognitive training (e.g., working memory training) benefit performance only in the trained tasks. The lack of skill generalization from one domain to different ones-that is, far transfer-has been documented in various fields of research such as working memory training, music, brain training, and chess. Video game training is another activity that has been claimed by many researchers to foster a broad range of cognitive abilities such as visual processing, attention, spatial ability, and cognitive control. We tested these claims with three random-effects meta-analytic models. The first meta-analysis (k = 310) examined the correlation between video game skill and cognitive ability. The second meta-analysis (k = 315) dealt with the differences between video game players and nonplayers in cognitive ability. The third meta-analysis (k = 359) investigated the effects of video game training on participants' cognitive ability. Small or null overall effect sizes were found in all three models. These outcomes show that overall cognitive ability and video game skill are only weakly related. Importantly, we found no evidence of a causal relationship between playing video games and enhanced cognitive ability. Video game training thus represents no exception to the general difficulty of obtaining far transfer. (PsycINFO Database Record},
  langid = {english},
  pmid = {29239631},
  keywords = {Aptitude,Cognition,Humans,Practice (Psychology),Transfer (Psychology),Video Games}
}

@article{salehi2019,
  title = {There Is No Single Functional Atlas Even for a Single Individual: {{Functional}} Parcel Definitions Change with Task},
  author = {Salehi, Mehraveh and Greene, Abigail S and Karbasi, Amin and Shen, Xilin and Scheinost, Dustin and Constable, R Todd},
  year = {2019},
  journal = {NeuroImage},
  pages = {116366},
  issn = {1053-8119},
  doi = {10.1016/j.neuroimage.2019.116366},
  abstract = {The goal of human brain mapping has long been to delineate the functional subunits in the brain and elucidate the functional role of each of these brain regions. Recent work has focused on whole-brain parcellation of functional Magnetic Resonance Imaging (fMRI) data to identify these subunits and create a functional atlas. Functional connectivity approaches to understand the brain at the network level require such an atlas to assess connections between parcels and extract network properties. While no single functional atlas has emerged as the dominant atlas to date, there remains an underlying assumption that such an atlas exists. Using fMRI data from a highly sampled subject as well as two independent replication data sets, we demonstrate that functional parcellations based on fMRI connectivity data reconfigure substantially and in a meaningful manner, according to brain state.},
  pmid = {31740342},
  keywords = {fMRI}
}

@article{seguin2020,
  title = {Network Communication Models Improve the Behavioral and Functional Predictive Utility of the Human Structural Connectome},
  author = {Seguin, Caio and Tian, Ye and Zalesky, Andrew},
  year = {2020},
  journal = {Network Neuroscience},
  volume = {4},
  number = {4},
  pages = {980--1006},
  doi = {10.1162/netn_a_00161},
  abstract = {The connectome provides the structural substrate facilitating communication between brain regions. We aimed to establish whether accounting for polysynaptic communication in structural connectomes would improve prediction of interindividual variation in behavior as well as increase structure-function coupling strength. Connectomes were mapped for 889 healthy adults participating in the Human Connectome Project. To account for polysynaptic signaling, connectomes were transformed into communication matrices for each of 15 different network communication models. Communication matrices were (a) used to perform predictions of five data-driven behavioral dimensions and (b) correlated to resting-state functional connectivity (FC). While FC was the most accurate predictor of behavior, communication models, in particular communicability and navigation, improved the performance of structural connectomes. Communication also strengthened structure-function coupling, with the navigation and shortest paths models leading to 35\textendash 65\% increases in association strength with FC. We combined behavioral and functional results into a single ranking that provides insight into which communication models may more faithfully recapitulate underlying neural signaling patterns. Comparing results across multiple connectome mapping pipelines suggested that modeling polysynaptic communication is particularly beneficial in sparse high-resolution connectomes. We conclude that network communication models can augment the functional and behavioral predictive utility of the human structural connectome.}
}

@inproceedings{seok2019,
  ids = {SeokDaCos2019ab,seok2019a},
  title = {Video {{Games}} as a {{Literacy Tool}}: {{A Comparison}} of {{Players}}' and {{Nonplayers}}' {{Grades}}, {{Reading Test Scores}}, and {{Self-Perceived Digital Reading Ability}}},
  shorttitle = {Video {{Games}} as a {{Literacy Tool}}},
  booktitle = {Society for {{Information Technology}} \& {{Teacher Education International Conference}}},
  author = {Seok, Soonhwa and DaCosta, Boaventura},
  year = {2019},
  pages = {777--781},
  publisher = {{Association for the Advancement of Computing in Education (AACE)}},
  abstract = {Given the growing importance of digital literacy, and the continued deliberation about the academic potential of video games, this study explored if and how video game play contributes to reading performance. Specifically, the grade point level, silent contextual reading fluency, and perceived digital reading ability of South Korean video game players (N = 589) and nonplayers (N = 617) were examined. The findings revealed that nonplayers had better grades and were better readers, while players held stronger positive perceptions about their reading ability not aligned with their grade point ...},
  isbn = {978-1-939797-37-7},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/493IB9WA/207731.html;/Users/morteza/Documents/Zotero/storage/XX2NS27P/207731.html}
}

@article{shenhav2017,
  title = {Toward a {{Rational}} and {{Mechanistic Account}} of {{Mental Effort}}},
  author = {Shenhav, Amitai and Musslick, Sebastian and Lieder, Falk and Kool, Wouter and Griffiths, Thomas L. and Cohen, Jonathan D. and Botvinick, Matthew M.},
  year = {2017},
  month = jul,
  journal = {Annual Review of Neuroscience},
  volume = {40},
  pages = {99--124},
  issn = {1545-4126},
  doi = {10.1146/annurev-neuro-072116-031526},
  abstract = {In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly understood. Although most researchers agree that mental effort is aversive and stems from limitations in our capacity to exercise cognitive control, it is unclear what gives rise to those limitations and why they result in an experience of control as costly. The presence of these control costs also raises further questions regarding how best to allocate mental effort to minimize those costs and maximize the attendant benefits. This review explores recent advances in computational modeling and empirical research aimed at addressing these questions at the level of psychological process and neural mechanism, examining both the limitations to mental effort exertion and how we manage those limited cognitive resources. We conclude by identifying remaining challenges for theoretical accounts of mental effort as well as possible applications of the available findings to understanding the causes of and potential solutions for apparent failures to exert the mental effort required of us.},
  langid = {english},
  pmid = {28375769},
  keywords = {cognitive control,Decision Making,Executive Function,Humans,Motivation,Prefrontal Cortex,Reward}
}

@article{shenhav2021,
  title = {Decomposing the Motivation to Exert Mental Effort},
  author = {Shenhav, Amitai and Fahey, Mahalia Prater and Grahek, Ivan},
  year = {2021},
  month = aug,
  journal = {Current Directions in Psychological Science},
  volume = {30},
  number = {4},
  pages = {307--314},
  issn = {0963-7214},
  doi = {10.1177/09637214211009510},
  abstract = {Achieving most goals demands cognitive control, yet people vary widely in their success at meeting these demands. While motivation is known to be fundamental to determining these successes, what determines one's motivation to perform a given task remains poorly understood. Here, we describe recent efforts towards addressing this question using the Expected Value of Control model, which simulates the process by which people weigh the costs and benefits of exerting mental effort. By functionally decomposing this cost-benefit analysis, this model has been used to fill gaps in our understanding of the mechanisms of mental effort and to generate novel predictions about the sources of variability in real-world performance. We discuss the opportunities the model provides for formalizing hypotheses about why people vary in their motivation to perform tasks, as well as for understanding limitations in our ability to test these hypotheses based on a given measure of performance.},
  langid = {english},
  pmcid = {PMC8528169},
  pmid = {34675454},
  keywords = {achievement,cognitive control,decision-making,motivation,punishment,reward,self-efficacy},
  file = {/Users/morteza/Documents/Zotero/storage/DHXGD4RB/Shenhav et al_2021_Decomposing the motivation to exert mental effort.pdf}
}

@article{shine2016,
  title = {The {{Dynamics}} of {{Functional Brain Networks}}: {{Integrated Network States}} during {{Cognitive Task Performance}}},
  shorttitle = {The {{Dynamics}} of {{Functional Brain Networks}}},
  author = {Shine, James M. and Bissett, Patrick G. and Bell, Peter T. and Koyejo, Oluwasanmi and Balsters, Joshua H. and Gorgolewski, Krzysztof J. and Moodie, Craig A. and Poldrack, Russell A.},
  year = {2016},
  month = oct,
  journal = {Neuron},
  volume = {92},
  number = {2},
  pages = {544--554},
  issn = {0896-6273},
  doi = {10.1016/j.neuron.2016.09.018},
  abstract = {Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses~between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative~modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.},
  langid = {english},
  annotation = {125 citations (Semantic Scholar/DOI) [2022-12-06]},
  file = {/Users/morteza/Documents/Zotero/storage/QTEYAHJW/Shine et al_2016_The Dynamics of Functional Brain Networks.pdf;/Users/morteza/Documents/Zotero/storage/RTIE2L74/S0896627316305773.html}
}

@article{shine2018,
  title = {Principles of Dynamic Network Reconfiguration across Diverse Brain States},
  author = {Shine, James M. and Poldrack, Russell A.},
  year = {2018},
  month = oct,
  journal = {NeuroImage},
  series = {Brain {{Connectivity Dynamics}}},
  volume = {180},
  pages = {396--405},
  issn = {1053-8119},
  doi = {10.1016/j.neuroimage.2017.08.010},
  abstract = {Recent methodological advances have enabled researchers to track the network structure of the human brain over time. Together, these studies provide novel insights into effective brain function, highlighting the importance of the systems-level perspective in understanding the manner in which the human brain organizes its activity to facilitate behavior. Here, we review a range of recent fMRI and electrophysiological studies that have mapped the relationship between inter-regional communication and network structure across a diverse range of brain states. In doing so, we identify both behavioral and biological axes that may underlie the tendency for network reconfiguration. We conclude our review by providing suggestions for future research endeavors that may help to refine our understanding of the functioning of the human brain.},
  langid = {english},
  keywords = {fMRI,Integration,Network,Segregation,Topology},
  annotation = {143 citations (Semantic Scholar/DOI) [2022-12-06]},
  file = {/Users/morteza/Documents/Zotero/storage/UF7NQ3K4/Shine_Poldrack_2018_Principles of dynamic network reconfiguration across diverse brain states.pdf;/Users/morteza/Documents/Zotero/storage/TX96QY8Y/S1053811917306572.html}
}

@article{shinn2020,
  title = {A Flexible Framework for Simulating and Fitting Generalized Drift-Diffusion Models},
  author = {Shinn, Maxwell and Lam, Norman H and Murray, John D},
  year = {2020},
  month = aug,
  journal = {eLife},
  volume = {9},
  pages = {e56938},
  issn = {2050-084X},
  doi = {10.7554/eLife.56938},
  abstract = {The drift-diffusion model (DDM) is an important decision-making model in cognitive neuroscience. However, innovations in model form have been limited by methodological challenges. Here, we introduce the generalized drift-diffusion model (GDDM) framework for building and fitting DDM extensions, and provide a software package which implements the framework. The GDDM framework augments traditional DDM parameters through arbitrary userdefined functions. Models are solved numerically by directly solving the Fokker-Planck equation using efficient numerical methods, yielding a 100-fold or greater speedup over standard methodology. This speed allows GDDMs to be fit to data using maximum likelihood on the full response time (RT) distribution. We demonstrate fitting of GDDMs within our framework to both animal and human datasets from perceptual decision-making tasks, with better accuracy and fewer parameters than several DDMs implemented using the latest methodology, to test hypothesized decision-making mechanisms. Overall, our framework will allow for decision-making model innovation and novel experimental designs.},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/LSY28TIY/Shinn et al. - 2020 - A flexible framework for simulating and fitting ge.pdf}
}

@book{ShragerLangley1990a,
  title = {Computational Models of Scientific Discovery and Theory Formation},
  editor = {Shrager, J. and Langley, P.},
  year = {1990},
  publisher = {{Morgan Kaufmann}},
  address = {{San Mateo, CA}}
}

@article{simons2016,
  title = {Do "{{Brain-Training}}" {{Programs Work}}?},
  author = {Simons, Daniel J. and Boot, Walter R. and Charness, Neil and Gathercole, Susan E. and Chabris, Christopher F. and Hambrick, David Z. and {Stine-Morrow}, Elizabeth A. L.},
  year = {2016},
  month = oct,
  journal = {Psychological Science in the Public Interest: A Journal of the American Psychological Society},
  volume = {17},
  number = {3},
  pages = {103--186},
  issn = {2160-0031},
  doi = {10.1177/1529100616661983},
  abstract = {In 2014, two groups of scientists published open letters on the efficacy of brain-training interventions, or "brain games," for improving cognition. The first letter, a consensus statement from an international group of more than 70 scientists, claimed that brain games do not provide a scientifically grounded way to improve cognitive functioning or to stave off cognitive decline. Several months later, an international group of 133 scientists and practitioners countered that the literature is replete with demonstrations of the benefits of brain training for a wide variety of cognitive and everyday activities. How could two teams of scientists examine the same literature and come to conflicting "consensus" views about the effectiveness of brain training?In part, the disagreement might result from different standards used when evaluating the evidence. To date, the field has lacked a comprehensive review of the brain-training literature, one that examines both the quantity and the quality of the evidence according to a well-defined set of best practices. This article provides such a review, focusing exclusively on the use of cognitive tasks or games as a means to enhance performance on other tasks. We specify and justify a set of best practices for such brain-training interventions and then use those standards to evaluate all of the published peer-reviewed intervention studies cited on the websites of leading brain-training companies listed on Cognitive Training Data (www.cognitivetrainingdata.org), the site hosting the open letter from brain-training proponents. These citations presumably represent the evidence that best supports the claims of effectiveness.Based on this examination, we find extensive evidence that brain-training interventions improve performance on the trained tasks, less evidence that such interventions improve performance on closely related tasks, and little evidence that training enhances performance on distantly related tasks or that training improves everyday cognitive performance. We also find that many of the published intervention studies had major shortcomings in design or analysis that preclude definitive conclusions about the efficacy of training, and that none of the cited studies conformed to all of the best practices we identify as essential to drawing clear conclusions about the benefits of brain training for everyday activities. We conclude with detailed recommendations for scientists, funding agencies, and policymakers that, if adopted, would lead to better evidence regarding the efficacy of brain-training interventions.},
  langid = {english},
  pmid = {27697851},
  keywords = {brain training,Cognition,cognitive,cognitive training,Humans,learning,Learning,skill,transfer},
  annotation = {00340}
}

@article{sims2002,
  title = {Domain Specificity of Spatial Expertise: The Case of Video Game Players},
  shorttitle = {Domain Specificity of Spatial Expertise},
  author = {Sims, Valerie K. and Mayer, Richard E.},
  year = {2002},
  month = jan,
  journal = {Applied Cognitive Psychology},
  volume = {16},
  number = {1},
  pages = {97--115},
  issn = {08884080, 10990720},
  doi = {10.1002/acp.759},
  langid = {english},
  annotation = {00000}
}

@article{siniatchkin2017,
  title = {Anodal {{tDCS}} over the Left {{DLPFC}} Improved Working Memory and Reduces Symptoms in Children with {{ADHD}}},
  author = {Siniatchkin, M.},
  year = {2017},
  month = mar,
  journal = {Brain Stimulation},
  volume = {10},
  number = {2},
  pages = {517},
  issn = {1935861X},
  doi = {10.1016/j.brs.2017.01.509},
  langid = {english},
  annotation = {00000}
}

@article{skorka-brown2015,
  title = {Playing {{Tetris}} Decreases Drug and Other Cravings in Real World Settings},
  author = {{Skorka-Brown}, Jessica and Andrade, Jackie and Whalley, Ben and May, Jon},
  year = {2015},
  month = dec,
  journal = {Addictive Behaviors},
  volume = {51},
  pages = {165--170},
  issn = {1873-6327},
  doi = {10.1016/j.addbeh.2015.07.020},
  abstract = {Most research on cognitive processes in craving has been carried out in the laboratory and focuses on food craving. This study extends laboratory findings to real world settings and cravings for drugs or activities as well as food. Previous laboratory research has found that playing Tetris reduces craving strength. The present study used an ecological momentary assessment protocol in which 31 undergraduate participants carried iPods for a week and were prompted 7 times each day, by SMS message, to use their iPod to report craving. Participants reported craving target and strength (0-100), whether they indulged their previous craving (yes/no), and whether they were under the influence of alcohol (yes/no). Those randomly assigned to the intervention condition (n=15) then played Tetris for 3min and reported their craving again. Those in the monitoring-only control condition (n=16) provided baseline craving data to test if Tetris reduced the incidence and strength of spontaneous cravings across the week. Playing Tetris decreased craving strength for drugs (alcohol, nicotine, caffeine), food and drink, and activities (sex, exercise, gaming), with a mean reduction of 13.9 percentage points, effect size f(2)=0.11. This effect was consistent across the week. This is the first demonstration that visual cognitive interference can be used in the field to reduce cravings for substances and activities other than eating.},
  langid = {english},
  pmid = {26275843},
  keywords = {Addiction,Adolescent,Adult,Behavior; Addictive,Behavioural research,Cognitive theory,Craving,Desire,Elaborated Intrusion theory,Female,Humans,Male,Multilevel models,Students,Substance-Related Disorders,Technology,Video Games,Young Adult},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/UB4LARYZ/Skorka-Brown et al. - 2015 - Playing Tetris decreases drug and other cravings i.pdf}
}

@article{solway2014,
  ids = {solway2014a},
  title = {Optimal {{Behavioral Hierarchy}}},
  author = {Solway, Alec and Diuk, Carlos and C{\'o}rdova, Natalia and Yee, Debbie and Barto, Andrew G. and Niv, Yael and Botvinick, Matthew M.},
  year = {2014},
  month = aug,
  journal = {PLOS Computational Biology},
  volume = {10},
  number = {8},
  pages = {e1003779},
  publisher = {{Public Library of Science}},
  issn = {1553-7358},
  doi = {10.1371/journal.pcbi.1003779},
  abstract = {Human behavior has long been recognized to display hierarchical structure: actions fit together into subtasks, which cohere into extended goal-directed activities. Arranging actions hierarchically has well established benefits, allowing behaviors to be represented efficiently by the brain, and allowing solutions to new tasks to be discovered easily. However, these payoffs depend on the particular way in which actions are organized into a hierarchy, the specific way in which tasks are carved up into subtasks. We provide a mathematical account for what makes some hierarchies better than others, an account that allows an optimal hierarchy to be identified for any set of tasks. We then present results from four behavioral experiments, suggesting that human learners spontaneously discover optimal action hierarchies.},
  langid = {english},
  pmcid = {PMC4133163},
  pmid = {25122479},
  keywords = {Adolescent,Adult,Behavior,Community structure,Computational Biology,Female,Goals,Human learning,Humans,Information theory,Learning,Machine learning,Male,Middle Aged,Models; Neurological,Subroutines,Towns,Young Adult},
  annotation = {113 citations (Semantic Scholar/DOI) [2022-10-27]},
  file = {/Users/morteza/Documents/Zotero/storage/2GWIL3YE/Solway et al_2014_Optimal Behavioral Hierarchy.pdf}
}

@article{sparrow2011,
  title = {Google Effects on Memory: Cognitive Consequences of Having Information at Our Fingertips},
  shorttitle = {Google Effects on Memory},
  author = {Sparrow, Betsy and Liu, Jenny and Wegner, Daniel M.},
  year = {2011},
  month = aug,
  journal = {Science (New York, N.Y.)},
  volume = {333},
  number = {6043},
  pages = {776--778},
  issn = {1095-9203},
  doi = {10.1126/science.1207745},
  abstract = {The advent of the Internet, with sophisticated algorithmic search engines, has made accessing information as easy as lifting a finger. No longer do we have to make costly efforts to find the things we want. We can "Google" the old classmate, find articles online, or look up the actor who was on the tip of our tongue. The results of four studies suggest that when faced with difficult questions, people are primed to think about computers and that when people expect to have future access to information, they have lower rates of recall of the information itself and enhanced recall instead for where to access it. The Internet has become a primary form of external or transactive memory, where information is stored collectively outside ourselves.},
  langid = {english},
  pmid = {21764755},
  keywords = {Cognition,Computers,Cues,Female,Humans,Information Storage and Retrieval,Internet,Male,Memory,Mental Recall,Reaction Time,Search Engine,Stroop Test},
  annotation = {00952}
}

@article{spence2010,
  title = {Video {{Games}} and {{Spatial Cognition}}},
  author = {Spence, Ian and Feng, Jing},
  year = {2010},
  month = jun,
  journal = {Review of General Psychology},
  volume = {14},
  number = {2},
  pages = {92--104},
  issn = {1089-2680, 1939-1552},
  doi = {10.1037/a0019491},
  langid = {english},
  annotation = {00000}
}

@article{stafford2014,
  title = {Tracing the {{Trajectory}} of {{Skill Learning With}} a {{Very Large Sample}} of {{Online Game Players}}},
  author = {Stafford, T. and Dewar, M.},
  year = {2014},
  month = feb,
  journal = {Psychological Science},
  volume = {25},
  number = {2},
  pages = {511--518},
  issn = {0956-7976, 1467-9280},
  doi = {10.1177/0956797613511466},
  langid = {english},
  annotation = {00071},
  file = {/Users/morteza/Documents/Zotero/storage/UQS8VK2E/Stafford and Dewar - 2014 - Tracing the Trajectory of Skill Learning With a Ve.pdf;/Users/morteza/Documents/Zotero/storage/V9U5SAFQ/Psychological Science-2013-Stafford-0956797613511466.pdf}
}

@article{stanhope2015,
  title = {Stress {{Reduction}}: {{Casual Gaming}} versus {{Guided Relaxation}}},
  author = {Stanhope, Jenny L and Owens, Caresse and Elliott, L Jo},
  year = {2015},
  journal = {Human Factors and Applied Psychology Student Conference HFAP Conference},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/5BYRQA7I/Stanhope, Owens, Elliott - 2015 - Stress Reduction Casual Gaming versus Guided Relaxation.pdf}
}

@article{steinke2020,
  title = {Toward a {{Computational Neuropsychology}} of {{Cognitive Flexibility}}},
  author = {Steinke, Alexander and Kopp, Bruno},
  year = {2020},
  month = dec,
  journal = {Brain Sciences},
  volume = {10},
  number = {12},
  pages = {E1000},
  issn = {2076-3425},
  doi = {10.3390/brainsci10121000},
  abstract = {Cognitive inflexibility is a well-documented, yet non-specific corollary of many neurological diseases. Computational modeling of covert cognitive processes supporting cognitive flexibility may provide progress toward nosologically specific aspects of cognitive inflexibility. We review computational models of the Wisconsin Card Sorting Test (WCST), which represents a gold standard for the clinical assessment of cognitive flexibility. A parallel reinforcement-learning (RL) model provides the best conceptualization of individual trial-by-trial WCST responses among all models considered. Clinical applications of the parallel RL model suggest that patients with Parkinson's disease (PD) and patients with amyotrophic lateral sclerosis (ALS) share a non-specific covert cognitive symptom: bradyphrenia. Impaired stimulus-response learning appears to occur specifically in patients with PD, whereas haphazard responding seems to occur specifically in patients with ALS. Computational modeling hence possesses the potential to reveal nosologically specific profiles of covert cognitive symptoms, which remain undetectable by traditionally applied behavioral methods. The present review exemplifies how computational neuropsychology may advance the assessment of cognitive flexibility. We discuss implications for neuropsychological assessment and directions for future research.},
  langid = {english},
  pmcid = {PMC7766646},
  pmid = {33348638},
  keywords = {amyotrophic lateral sclerosis,cognitive flexibility,computational modeling,Parkinson’s disease,Wisconsin Card Sorting Test},
  file = {/Users/morteza/Documents/Zotero/storage/6ZFJL86F/Steinke_Kopp_2020_Toward a Computational Neuropsychology of Cognitive Flexibility.pdf}
}

@article{steinke2020a,
  title = {Parallel Model-Based and Model-Free Reinforcement Learning for Card Sorting Performance},
  author = {Steinke, Alexander and Lange, Florian and Kopp, Bruno},
  year = {2020},
  month = sep,
  journal = {Scientific Reports},
  volume = {10},
  number = {1},
  pages = {15464},
  issn = {2045-2322},
  doi = {10.1038/s41598-020-72407-7},
  abstract = {The Wisconsin Card Sorting Test (WCST) is considered a gold standard for the assessment of cognitive flexibility. On the WCST, repeating a sorting category following negative feedback is typically treated as indicating reduced cognitive flexibility. Therefore such responses are referred to as 'perseveration' errors. Recent research suggests that the propensity for perseveration errors is modulated by response demands: They occur less frequently when their commitment repeats the previously executed response. Here, we propose parallel reinforcement-learning models of card sorting performance, which assume that card sorting performance can be conceptualized as resulting from model-free reinforcement learning at the level of responses that occurs in parallel with model-based reinforcement learning at the categorical level. We compared parallel reinforcement-learning models with purely model-based reinforcement learning, and with the state-of-the-art attentional-updating model. We analyzed data from 375 participants who completed a computerized WCST. Parallel reinforcement-learning models showed best predictive accuracies for the majority of participants. Only parallel reinforcement-learning models accounted for the modulation of perseveration propensity by response demands. In conclusion, parallel reinforcement-learning models provide a new theoretical perspective on card sorting and it offers a suitable framework for discerning individual differences in latent processes that subserve behavioral flexibility.},
  langid = {english},
  pmcid = {PMC7508815},
  pmid = {32963297},
  keywords = {Adult,Attention,Female,Humans,Learning,Male,Models; Statistical,Neuropsychological Tests,Psychomotor Performance,Reinforcement; Psychology,Wisconsin Card Sorting Test,Young Adult},
  file = {/Users/morteza/Documents/Zotero/storage/8ZS8RC8K/Steinke et al_2020_Parallel model-based and model-free reinforcement learning for card sorting.pdf}
}

@article{stocco2021,
  title = {Analysis of the Human Connectome Data Supports the Notion of a ``{{Common Model}} of {{Cognition}}'' for Human and Human-like Intelligence across Domains},
  author = {Stocco, Andrea and Sibert, Catherine and {Steine-Hanson}, Zoe and Koh, Natalie and Laird, John E. and Lebiere, Christian J. and Rosenbloom, Paul},
  year = {2021},
  month = jul,
  journal = {NeuroImage},
  volume = {235},
  pages = {118035},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2021.118035},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/GJIT59FM/Stocco et al. - 2021 - Analysis of the human connectome data supports the.pdf}
}

@article{strenziok2014,
  title = {Neurocognitive Enhancement in Older Adults: Comparison of Three Cognitive Training Tasks to Test a Hypothesis of Training Transfer in Brain Connectivity},
  shorttitle = {Neurocognitive Enhancement in Older Adults},
  author = {Strenziok, Maren and Parasuraman, Raja and Clarke, Ellen and Cisler, Dean S. and Thompson, James C. and Greenwood, Pamela M.},
  year = {2014},
  month = jan,
  journal = {NeuroImage},
  volume = {85 Pt 3},
  pages = {1027--1039},
  issn = {1095-9572},
  doi = {10.1016/j.neuroimage.2013.07.069},
  abstract = {The ultimate goal of cognitive enhancement as an intervention for age-related cognitive decline is transfer to everyday cognitive functioning. Development of training methods that transfer broadly to untrained cognitive tasks (far transfer) requires understanding of the neural bases of training and far transfer effects. We used cognitive training to test the hypothesis that far transfer is associated with altered attentional control demands mediated by the dorsal attention network and trained sensory cortex. In an exploratory study, we randomly assigned 42 healthy older adults to six weeks of training on Brain Fitness (BF-auditory perception), Space Fortress (SF-visuomotor/working memory), or Rise of Nations (RON-strategic reasoning). Before and after training, cognitive performance, diffusion-derived white matter integrity, and functional connectivity of the superior parietal cortex (SPC) were assessed. We found the strongest effects from BF training, which transferred to everyday problem solving and reasoning and selectively changed integrity of occipito-temporal white matter associated with improvement on untrained everyday problem solving. These results show that cognitive gain from auditory perception training depends on heightened white matter integrity in the ventral attention network. In BF and SF (which also transferred positively), a decrease in functional connectivity between SPC and inferior temporal lobe (ITL) was observed compared to RON-which did not transfer to untrained cognitive function. These findings highlight the importance for cognitive training of top-down control of sensory processing by the dorsal attention network. Altered brain connectivity - observed in the two training tasks that showed far transfer effects - may be a marker for training success.},
  langid = {english},
  pmid = {23933474},
  keywords = {Aged,Aging,Attention,Biomedical Enhancement,Brain,Brain Mapping,Cognition,Cognitive training,Diffusion Tensor Imaging,Far transfer,Female,Functional connectivity,Humans,Image Processing; Computer-Assisted,Male,Neural Pathways,Superior parietal cortex,Transfer (Psychology),White matter integrity},
  annotation = {00082}
}

@article{strobach2012,
  title = {Video Game Practice Optimizes Executive Control Skills in Dual-Task and Task Switching Situations},
  author = {Strobach, Tilo and Frensch, Peter A. and Schubert, Torsten},
  year = {2012},
  month = may,
  journal = {Acta Psychologica},
  volume = {140},
  number = {1},
  pages = {13--24},
  issn = {1873-6297},
  doi = {10.1016/j.actpsy.2012.02.001},
  abstract = {We examined the relation of action video game practice and the optimization of executive control skills that are needed to coordinate two different tasks. As action video games are similar to real life situations and complex in nature, and include numerous concurrent actions, they may generate an ideal environment for practicing these skills (Green \& Bavelier, 2008). For two types of experimental paradigms, dual-task and task switching respectively; we obtained performance advantages for experienced video gamers compared to non-gamers in situations in which two different tasks were processed simultaneously or sequentially. This advantage was absent in single-task situations. These findings indicate optimized executive control skills in video gamers. Similar findings in non-gamers after 15 h of action video game practice when compared to non-gamers with practice on a puzzle game clarified the causal relation between video game practice and the optimization of executive control skills.},
  langid = {english},
  pmid = {22426427},
  keywords = {Adolescent,Adult,Attention,Executive Function,Humans,Male,Neuropsychological Tests,Practice (Psychology),Psychomotor Performance,Reaction Time,Video Games,Visual Perception},
  annotation = {00206}
}

@article{sungur2012,
  title = {Action Video Game Players Form More Detailed Representation of Objects},
  author = {Sungur, Hande and Boduroglu, Aysecan},
  year = {2012},
  month = feb,
  journal = {Acta Psychologica},
  volume = {139},
  number = {2},
  pages = {327--334},
  issn = {00016918},
  doi = {10.1016/j.actpsy.2011.12.002},
  langid = {english},
  annotation = {00000}
}

@article{tailby2015,
  title = {Resting State Functional Connectivity Changes Induced by Prior Brain State Are Not Network Specific},
  author = {Tailby, Chris and Masterton, Richard A.J. and Huang, Jenny Y. and Jackson, Graeme D. and Abbott, David F.},
  year = {2015},
  month = feb,
  journal = {NeuroImage},
  volume = {106},
  pages = {428--440},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2014.11.037},
  langid = {english},
  annotation = {24 citations (Semantic Scholar/DOI) [2022-12-07]}
}

@article{takeuchi2011,
  title = {Working {{Memory Training Using Mental Calculation Impacts Regional Gray Matter}} of the {{Frontal}} and {{Parietal Regions}}},
  author = {Takeuchi, Hikaru and Taki, Yasuyuki and Sassa, Yuko and Hashizume, Hiroshi and Sekiguchi, Atsushi and Fukushima, Ai and Kawashima, Ryuta},
  editor = {Chapouthier, Georges},
  year = {2011},
  month = aug,
  journal = {PLoS ONE},
  volume = {6},
  number = {8},
  pages = {e23175},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0023175},
  langid = {english},
  annotation = {00127},
  file = {/Users/morteza/Documents/Zotero/storage/QEAIVPI9/takeuchi2011.pdf}
}

@article{tang2022,
  title = {The {{Dual Mechanisms}} of {{Cognitive Control}} ({{DMCC}}) Project: {{Validation}} of an Online Behavioural Task Battery},
  shorttitle = {The {{Dual Mechanisms}} of {{Cognitive Control}} ({{DMCC}}) Project},
  author = {Tang, Rongxiang and Bugg, Julie M. and Snijder, Jean-Paul and Conway, Andrew Ra and Braver, Todd S.},
  year = {2022},
  month = aug,
  journal = {Quarterly Journal of Experimental Psychology (2006)},
  pages = {17470218221114769},
  issn = {1747-0226},
  doi = {10.1177/17470218221114769},
  abstract = {Cognitive control serves a crucial role in human higher mental functions. The Dual Mechanisms of Control theoretical framework provides a unifying account that decomposes cognitive control into two qualitatively distinct mechanisms-proactive control and reactive control. Here, we describe the Dual Mechanisms of Cognitive Control (DMCC) task battery, which was developed to probe cognitive control modes in a theoretically targeted manner, along with detailed descriptions of the experimental manipulations used to encourage shifts to proactive or reactive mode in each of four prototypical domains of cognition: selective attention, context processing, multitasking, and working memory. We present results from this task battery, conducted from a large (N\,{$>$}\,100), online sample that rigorously evaluates the group effects of these manipulations in primary indices of proactive and reactive control, establishing the validity of the battery in providing dissociable yet convergent measures of the two cognitive control modes. The DMCC battery may be a useful tool for the research community to examine cognitive control in a theoretically targeted manner across different individuals and groups.},
  langid = {english},
  pmid = {35815536},
  keywords = {Cognitive control,context processing,Stroop,task-switching,working memory}
}

@article{teeters2015,
  title = {Neurodata {{Without Borders}}: {{Creating}} a {{Common Data Format}} for {{Neurophysiology}}},
  shorttitle = {Neurodata {{Without Borders}}},
  author = {Teeters, Jeffery~L. and Godfrey, Keith and Young, Rob and Dang, Chinh and Friedsam, Claudia and Wark, Barry and Asari, Hiroki and Peron, Simon and Li, Nuo and Peyrache, Adrien and Denisov, Gennady and Siegle, Joshua~H. and Olsen, Shawn~R. and Martin, Christopher and Chun, Miyoung and Tripathy, Shreejoy and Blanche, Timothy~J. and Harris, Kenneth and Buzs{\'a}ki, Gy{\"o}rgy and Koch, Christof and Meister, Markus and Svoboda, Karel and Sommer, Friedrich~T.},
  year = {2015},
  month = nov,
  journal = {Neuron},
  volume = {88},
  number = {4},
  pages = {629--634},
  issn = {08966273},
  doi = {10.1016/j.neuron.2015.10.025},
  langid = {english},
  annotation = {126 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/SRAME8SD/Teeters et al. - 2015 - Neurodata Without Borders Creating a Common Data .pdf}
}

@article{tenenbaum2011,
  title = {How to {{Grow}} a {{Mind}}: {{Statistics}}, {{Structure}}, and {{Abstraction}}},
  shorttitle = {How to {{Grow}} a {{Mind}}},
  author = {Tenenbaum, Joshua B. and Kemp, Charles and Griffiths, Thomas L. and Goodman, Noah D.},
  year = {2011},
  month = mar,
  journal = {Science},
  volume = {331},
  number = {6022},
  pages = {1279--1285},
  issn = {0036-8075, 1095-9203},
  doi = {10.1126/science.1192788},
  abstract = {In coming to understand the world\textemdash in learning concepts, acquiring language, and grasping causal relations\textemdash our minds make inferences that appear to go far beyond the data available. How do we do it? This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference over hierarchies of flexibly structured representations can address some of the deepest questions about the nature and origins of human thought: How does abstract knowledge guide learning and reasoning from sparse data? What forms does our knowledge take, across different domains and tasks? And how is that abstract knowledge itself acquired?},
  langid = {english},
  keywords = {Artificial Intelligence,Bayes Theorem,Cognition,Concept Formation,Humans,Knowledge,Learning,Models,Models; Statistical,Statistical,Theory of Mind,Thinking},
  annotation = {1373 citations (Semantic Scholar/DOI) [2022-12-03]},
  file = {/Users/morteza/Documents/Zotero/storage/6UMKCAN5/Tenenbaum et al. - 2011 - How to Grow a Mind Statistics, Structure, and Abs.pdf;/Users/morteza/Documents/Zotero/storage/QUZAXLYL/Tenenbaum et al. - 2011 - How to Grow a Mind Statistics, Structure, and Abs.pdf;/Users/morteza/Documents/Zotero/storage/S622E68N/Tenenbaum et al. - 2011 - How to Grow a Mind Statistics, Structure, and Abs.pdf}
}

@article{terlecki2008,
  title = {Durable and Generalized Effects of Spatial Experience on Mental Rotation: Gender Differences in Growth Patterns},
  shorttitle = {Durable and Generalized Effects of Spatial Experience on Mental Rotation},
  author = {Terlecki, Melissa S. and Newcombe, Nora S. and Little, Michelle},
  year = {2008},
  journal = {Applied Cognitive Psychology},
  volume = {22},
  number = {7},
  pages = {996--1013},
  issn = {1099-0720},
  doi = {10.1002/acp.1420},
  abstract = {This study addressed questions about improvement in mental rotation skills: (1) whether growth trajectories differ for men and women with higher or lower spatial experience, (2) whether videogame training has effects on performance and leads to transfer, (3) whether effects of repeated testing or training effects are durable and (4) whether transfer is durable. Undergraduates participated in repeated testing on the MRT or played the videogame Tetris. Analyses showed large improvements in mental rotation with both repeated testing and training; these gains were maintained several months later. MRT scores of men and women did not converge, but men showed faster initial growth and women showed more improvement later. Videogame training showed greater initial growth than repeated testing alone, but final performance did not differ. Effects of videogame training transferred to other spatial tasks exceeding the effects of repeated testing, and this transfer advantage was still evident after several months. Copyright \textcopyright{} 2007 John Wiley \& Sons, Ltd.},
  copyright = {Copyright \textcopyright{} 2007 John Wiley \& Sons, Ltd.},
  langid = {english},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/3NKGVCZD/acp.html}
}

@article{thorndike1901,
  title = {The Influence of Improvement in One Mental Function upon the Efficiency of Other Functions. {{II}}. {{The}} Estimation of Magnitudes.},
  author = {Thorndike, Edward L. and Woodworth, R. S.},
  year = {1901},
  journal = {Psychological Review},
  volume = {8},
  number = {4},
  pages = {384--395},
  issn = {0033-295X},
  doi = {10.1037/h0071280},
  langid = {english},
  annotation = {00162}
}

@article{tidwell2014,
  title = {What Counts as Evidence for Working Memory Training? {{Problems}} with Correlated Gains and Dichotomization},
  shorttitle = {What Counts as Evidence for Working Memory Training?},
  author = {Tidwell, Joe W. and Dougherty, Michael R. and Chrabaszcz, Jeffrey R. and Thomas, Rick P. and Mendoza, Jorge L.},
  year = {2014},
  month = jun,
  journal = {Psychonomic Bulletin \& Review},
  volume = {21},
  number = {3},
  pages = {620--628},
  issn = {1531-5320},
  doi = {10.3758/s13423-013-0560-7},
  abstract = {The question of whether computerized cognitive training leads to generalized improvements of intellectual abilities has been a popular, yet contentious, topic within both the psychological and neurocognitive literatures. Evidence for the effective transfer of cognitive training to nontrained measures of cognitive abilities is mixed, with some studies showing apparent successful transfer, while others have failed to obtain this effect. At the same time, several authors have made claims about both successful and unsuccessful transfer effects on the basis of a form of responder analysis, an analysis technique that shows that those who gain the most on training show the greatest gains on transfer tasks. Through a series of Monte Carlo experiments and mathematical analyses, we demonstrate that the apparent transfer effects observed through responder analysis are illusory and are independent of the effectiveness of cognitive training. We argue that responder analysis can be used neither to support nor to refute hypotheses related to whether cognitive training is a useful intervention to obtain generalized cognitive benefits. We end by discussing several proposed alternative analysis techniques that incorporate training gain scores and argue that none of these methods are appropriate for testing hypotheses regarding the effectiveness of cognitive training.},
  langid = {english},
  pmid = {24307249},
  keywords = {Data Interpretation; Statistical,Humans,Intelligence,Memory; Short-Term,Transfer (Psychology)},
  annotation = {00029}
}

@article{tiraboschi2019,
  title = {An {{Expectancy Effect Causes Improved Visual Attention Performance After Video Game Playing}}},
  author = {Tiraboschi, Gabriel Arantes and Fukusima, S{\'e}rgio S. and West, Greg L.},
  year = {2019},
  month = dec,
  journal = {Journal of Cognitive Enhancement},
  volume = {3},
  number = {4},
  pages = {436--444},
  issn = {2509-3304},
  doi = {10.1007/s41465-019-00130-x},
  abstract = {Numerous studies in the last decade have shown the potential for video games to enhance several cognitive processes, with most evidence targeting visual attention. However, a debate has emerged in the literature pointing to flawed experimental design being responsible for such findings. For example, participants' expectancy effects (i.e., a placebo) have been proposed as an alternate explanation for observed cognitive enhancement resulting from video game training. Nevertheless, to this day, there is no empirical evidence suggesting that video game studies are susceptible to expectancy effects. Here, we investigate whether we could induce an expectancy effect in visual attentional performance with a brief single placebo video game training session. We recruited naive participants and randomly assigned them into two groups that went through the same experimental procedure, except for the experimental instructions. The experimental procedure included a pre-test with an Attentional Blink task and a Useful field of view task, then a single 15-min video game training session, and finally a post-test with the same tasks as the pre-test. The placebo group received instructions implying that the video game would make them perform better, while the control group was told that they would play a video game to give them a break from the experiment. Our results show an overall significant increase in the Useful field of view performance uniquely for the placebo group. Together, these results confirm the hypothesis that video game training experiments are susceptible to expectancy effects.},
  langid = {english},
  keywords = {Attention,Attentional blink,Expectancy effects,Useful field of view,Video games},
  annotation = {5 citations (Semantic Scholar/DOI) [2022-12-06]}
}

@article{tomov2021,
  title = {Multi-Task Reinforcement Learning in Humans},
  author = {Tomov, Momchil S. and Schulz, Eric and Gershman, Samuel J.},
  year = {2021},
  month = jun,
  journal = {Nature Human Behaviour},
  volume = {5},
  number = {6},
  pages = {764--773},
  issn = {2397-3374},
  doi = {10.1038/s41562-020-01035-y},
  langid = {english},
  file = {/Users/morteza/Documents/Zotero/storage/25NXC4RB/Tomov et al_2021_Multi-task reinforcement learning in humans.pdf}
}

@article{toril2014,
  title = {Video Game Training Enhances Cognition of Older Adults: {{A}} Meta-Analytic Study.},
  shorttitle = {Video Game Training Enhances Cognition of Older Adults},
  author = {Toril, Pilar and Reales, Jos{\'e} M. and Ballesteros, Soledad},
  year = {2014},
  journal = {Psychology and Aging},
  volume = {29},
  number = {3},
  pages = {706--716},
  issn = {1939-1498, 0882-7974},
  doi = {10.1037/a0037507},
  langid = {english},
  keywords = {\#nosource},
  annotation = {00139}
}

@article{toro2008,
  title = {Functional {{Coactivation Map}} of the {{Human Brain}}},
  author = {Toro, R. and Fox, P. T. and Paus, T.},
  year = {2008},
  month = nov,
  journal = {Cerebral Cortex},
  volume = {18},
  number = {11},
  pages = {2553--2559},
  issn = {1047-3211, 1460-2199},
  doi = {10.1093/cercor/bhn014},
  langid = {english},
  annotation = {376 citations (Semantic Scholar/DOI) [2023-01-12]},
  file = {/Users/morteza/Documents/Zotero/storage/8XMZTB54/Toro et al. - 2008 - Functional Coactivation Map of the Human Brain.pdf}
}

@article{touzel2022,
  title = {Performance-Gated Deliberation: {{A}} Context-Adapted Strategy in Which Urgency Is Opportunity Cost},
  shorttitle = {Performance-Gated Deliberation},
  author = {Touzel, Maximilian Puelma and Cisek, Paul and Lajoie, Guillaume},
  year = {2022},
  month = may,
  journal = {PLOS Computational Biology},
  volume = {18},
  number = {5},
  pages = {e1010080},
  publisher = {{Public Library of Science}},
  issn = {1553-7358},
  doi = {10.1371/journal.pcbi.1010080},
  abstract = {Finding the right amount of deliberation, between insufficient and excessive, is a hard decision making problem that depends on the value we place on our time. Average-reward, putatively encoded by tonic dopamine, serves in existing reinforcement learning theory as the opportunity cost of time, including deliberation time. Importantly, this cost can itself vary with the environmental context and is not trivial to estimate. Here, we propose how the opportunity cost of deliberation can be estimated adaptively on multiple timescales to account for non-stationary contextual factors. We use it in a simple decision-making heuristic based on average-reward reinforcement learning (AR-RL) that we call Performance-Gated Deliberation (PGD). We propose PGD as a strategy used by animals wherein deliberation cost is implemented directly as urgency, a previously characterized neural signal effectively controlling the speed of the decision-making process. We show PGD outperforms AR-RL solutions in explaining behaviour and urgency of non-human primates in a context-varying random walk prediction task and is consistent with relative performance and urgency in a context-varying random dot motion task. We make readily testable predictions for both neural activity and behaviour.},
  langid = {english},
  keywords = {Algorithms,Animal behavior,Behavior,Decision making,Dopamine,Learning,Primates,Random walk},
  file = {/Users/morteza/Documents/Zotero/storage/2CHQEDX7/Touzel et al_2022_Performance-gated deliberation.pdf}
}

@article{toyama2021,
  title = {{{AndroidEnv}}: {{A}} Reinforcement Learning Platform for Android},
  author = {Toyama, Daniel and Hamel, Philippe and Gergely, Anita and Comanici, Gheorghe and Glaese, Amelia and Ahmed, Zafarali and Jackson, Tyler and Mourad, Shibl and Precup, Doina},
  year = {2021},
  journal = {arXiv preprint arXiv:2105.13231},
  eprint = {2105.13231},
  eprinttype = {arxiv},
  archiveprefix = {arXiv}
}

@article{uncapher2018,
  title = {Minds and Brains of Media Multitaskers: {{Current}} Findings and Future Directions},
  shorttitle = {Minds and Brains of Media Multitaskers},
  author = {Uncapher, Melina R. and Wagner, Anthony D.},
  year = {2018},
  month = oct,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {115},
  number = {40},
  pages = {9889--9896},
  issn = {0027-8424, 1091-6490},
  doi = {10.1073/pnas.1611612115},
  abstract = {Media and technology are ubiquitous elements of our daily lives, and their use can offer many benefits and rewards. At the same time, decisions about how individuals structure their use of media can be informed by consideration of whether, and if so how, the mind and brain are shaped by different use patterns. Here we review the growing body of research that investigates the cognitive and neural profiles of individuals who differ in the extent to which they simultaneously engage with multiple media streams, or \quotedblbase media multitasking.'' While the literature is still sparse, and is marked by both convergent and divergent findings, the balance of evidence suggests that heavier media multitaskers exhibit poorer performance in a number of cognitive domains, relative to lighter media multitaskers (although many studies find no performance differences between groups). When evidence points to a relationship between media multitasking level and cognition, it is often on tasks that require or are influenced by fluctuations in sustained goal-directed attention. Given the real-world significance of such findings, further research is needed to uncover the mechanistic underpinnings of observed differences, to determine the direction of causality, to understand whether remediation efforts are needed and effective, and to determine how measurement heterogeneity relates to variable outcomes. Such efforts will ultimately inform decisions about how to minimize the potential costs and maximize the many benefits of our ever-evolving media landscape.},
  langid = {english},
  annotation = {72 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/TIKFJYTT/Uncapher and Wagner - 2018 - Minds and brains of media multitaskers Current fi.pdf}
}

@article{vanzandt2000,
  title = {How to Fit a Response Time Distribution},
  author = {Van Zandt, Trisha},
  year = {2000},
  month = sep,
  journal = {Psychonomic Bulletin \& Review},
  volume = {7},
  number = {3},
  pages = {424--465},
  issn = {1069-9384, 1531-5320},
  doi = {10.3758/BF03214357},
  langid = {english},
  keywords = {response time},
  file = {/Users/morteza/Documents/Zotero/storage/U8Z27WC8/Van Zandt - 2000 - How to fit a response time distribution.pdf}
}

@article{varma2011,
  title = {Criteria for the Design and Evaluation of Cognitive Architectures},
  author = {Varma, Sashank},
  year = {2011 Sep-Oct},
  journal = {Cognitive science},
  volume = {35},
  number = {7},
  publisher = {{Cogn Sci}},
  issn = {1551-6709},
  doi = {10.1111/j.1551-6709.2011.01190.x},
  abstract = {Cognitive architectures are unified theories of cognition that take the form of computational formalisms. They support computational models that collectively account for large numbers of empirical regularities using small numbers of computational mechanisms. Empirical coverage and parsimony are the \ldots},
  langid = {english},
  pmid = {21824179},
  file = {/Users/morteza/Documents/Zotero/storage/8PTEZ8D5/S_2011_Criteria for the design and evaluation of cognitive architectures.pdf;/Users/morteza/Documents/Zotero/storage/MYLKMRKL/21824179.html}
}

@article{varoquaux2013,
  title = {Learning and Comparing Functional Connectomes across Subjects},
  author = {Varoquaux, Ga{\"e}l and Craddock, R. Cameron},
  year = {2013},
  month = oct,
  journal = {NeuroImage},
  volume = {80},
  pages = {405--415},
  issn = {10538119},
  doi = {10.1016/j.neuroimage.2013.04.007},
  langid = {english},
  annotation = {202 citations (Semantic Scholar/DOI) [2022-12-10]},
  file = {/Users/morteza/Documents/Zotero/storage/IFBIFK2M/Varoquaux and Craddock - 2013 - Learning and comparing functional connectomes acro.pdf}
}

@misc{varoquaux2020,
  type = {Pdf},
  title = {Estimating Brain Functional Connectivity and Its Variations from {{fMRI}}},
  author = {Varoquaux, Ga{\"e}l},
  year = {2020},
  journal = {Estimating brain functional connectivity and its variations from fMRI},
  howpublished = {https://www.normalesup.org/\textasciitilde varoquau/HDR\_Gael\_Varoquaux.pdf},
  langid = {english}
}

@article{verbruggen2014,
  title = {Banishing the Control Homunculi in Studies of Action Control and Behavior Change},
  author = {Verbruggen, Frederick and McLaren, Ian P. L. and Chambers, Christopher D.},
  year = {2014},
  journal = {Perspectives on Psychological Science},
  volume = {9},
  number = {5},
  pages = {497--524},
  issn = {1745-6916},
  doi = {10.1177/1745691614526414},
  abstract = {For centuries, human self-control has fascinated scientists and nonscientists alike. Current theories often attribute it to an executive control system. But even though executive control receives a great deal of attention across disciplines, most aspects of it are still poorly understood. Many theories rely on an ill-defined set of ``homunculi'' doing jobs like ``response inhibition'' or ``updating'' without explaining how they do so. Furthermore, it is not always appreciated that control takes place across different timescales. These two issues hamper major advances. Here we focus on the mechanistic basis for the executive control of actions. We propose that at the most basic level, action control depends on three cognitive processes: signal detection, action selection, and action execution. These processes are modulated via error-correction or outcome-evaluation mechanisms, preparation, and task rules maintained in working and long-term memory. We also consider how executive control of actions becomes automatized with practice and how people develop a control network. Finally, we discuss how the application of this unified framework in clinical domains can increase our understanding of control deficits and provide a theoretical basis for the development of novel behavioral change interventions.},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2014/Verbruggen\%202014.pdf},
  pmid = {25419227},
  annotation = {00185}
}

@article{viola2017,
  title = {The Standard Ontological Framework of Cognitive Neuroscience: {{Some}} Lessons from {{Broca}}'s Area},
  author = {Viola, Marco and Zanin, Elia},
  year = {2017},
  journal = {Philosophical Psychology},
  volume = {30},
  number = {7},
  pages = {1--25},
  issn = {0951-5089},
  doi = {10.1080/09515089.2017.1322193},
  abstract = {Since cognitive neuroscience aims at giving an integrated account of mind and brain, its ontology should include both neural and cognitive entities and specify their relations. According to what we call the standard ontological framework of cognitive neuroscience (SOFCN), the aim of cognitive neuroscience should be to establish one-to-one mappings between neural and cognitive entities. Where such entities do not yet closely align, this can be achieved by reforming the cognitive ontology, the neural ontology, or both. In order to assess the limits and the possibilities of the SOFCN, we will examine a paradigmatic case study: the concept of Broca's area, which indicates an alleged mapping between the left inferofrontal gyrus and the production of language. We review evidence showing that such a mapping does not hold, thus calling into question either the status of Broca's area or the validity of the SOFCN. We then propose some strategies for addressing the issue and suggest that it may be solved within the SOFCN by adopting both of the following strategies: first, more accurately defining the relevant neural structures and second, switching the focus of neural ontology from structures to events, individuated by a where (neural structures) conjoint with a how (oscillatiory frequency).},
  local-url = {file://localhost/Users/morteza/Documents/Papers\%20Library/2017/Viola\%202017.pdf},
  keywords = {EFO},
  annotation = {00000}
}

@techreport{waller2016,
  title = {{{JAMES}} - {{Jeunes}}, Activit\'es, M\'edias \textendash{} Enqu\^ete {{Suisse}}},
  author = {Waller, Gregor and Willemse, Isabel and Genner, Sarah and Suter, Lilian and S{\"u}ss, Daniel},
  year = {2016},
  address = {{Zurich}},
  institution = {{Haute \'ecole des sciences appliqu\'ees de Zurich}},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/T2A3D3NQ/Waller et al. - 2016 - JAMES - Jeunes, activités, médias – enquête Suisse.pdf}
}

@article{wang2016,
  title = {Action {{Video Game Training}} for {{Healthy Adults}}: {{A Meta-Analytic Study}}},
  shorttitle = {Action {{Video Game Training}} for {{Healthy Adults}}},
  author = {Wang, Ping and Liu, Han-Hui and Zhu, Xing-Ting and Meng, Tian and Li, Hui-Jie and Zuo, Xi-Nian},
  year = {2016},
  month = jun,
  journal = {Frontiers in Psychology},
  volume = {7},
  issn = {1664-1078},
  doi = {10.3389/fpsyg.2016.00907},
  annotation = {00032},
  file = {/Users/morteza/Documents/Zotero/storage/J7J7EH32/wang2016.pdf}
}

@article{wang2018,
  title = {Transcranial Direct Current Stimulation over the Right {{DLPFC}} Selectively Modulates Subprocesses in Working Memory},
  author = {Wang, Jiarui and Tian, Jinhua and Hao, Renning and Tian, Lili and Liu, Qiang},
  year = {2018},
  month = may,
  journal = {PeerJ},
  volume = {6},
  pages = {e4906},
  issn = {2167-8359},
  doi = {10.7717/peerj.4906},
  abstract = {Background               Working memory, as a complex system, consists of two independent components: manipulation and maintenance process, which are defined as executive control and storage process. Previous studies mainly focused on the overall effect of transcranial direct current stimulation (tDCS) on working memory. However, little has been known about the segregative effects of tDCS on the sub-processes within working memory.                                         Method                                Transcranial direct current stimulation, as one of the non-invasive brain stimulation techniques, is being widely used to modulate the cortical activation of local brain areas. This study modified a spatial                 n                 -back experiment with anodal and cathodal tDCS exertion on the right dorsolateral prefrontal cortex (DLPFC), aiming to investigate the effects of tDCS on the two sub-processes of working memory: manipulation (updating) and maintenance. Meanwhile, considering the separability of tDCS effects, we further reconfirmed the causal relationship between the right DLPFC and the sub-processes of working memory with different tDCS conditions.                                                        Results               The present study showed that cathodal tDCS on the right DLPFC selectively improved the performance of the modified 2-back task in the difficult condition, whereas anodal tDCS significantly reduced the performance of subjects and showed an speeding-up tendency of response time. More precisely, the results of discriminability index and criterion showed that only cathodal tDCS enhanced the performance of maintenance in the difficult condition. Neither of the two tDCS conditions affected the performance of manipulation (updating).                                         Conclusion               These findings provide evidence that cathodal tDCS of the right DLPFC selectively affects maintenance capacity. Besides, cathodal tDCS also serves as an interference suppressor to reduce the irrelevant interference, thereby indirectly improving the working memory capacity. Moreover, the right DLPFC is not the unique brain regions for working memory manipulation (updating).},
  langid = {english},
  annotation = {00001}
}

@article{west2015,
  title = {Habitual Action Video Game Playing Is Associated with Caudate Nucleus-Dependent Navigational Strategies},
  author = {West, Greg L. and Drisdelle, Brandi Lee and Konishi, Kyoko and Jackson, Jonathan and Jolicoeur, Pierre and Bohbot, Veronique D.},
  year = {2015},
  month = jun,
  journal = {Proceedings of the Royal Society B: Biological Sciences},
  volume = {282},
  number = {1808},
  pages = {20142952},
  issn = {0962-8452, 1471-2954},
  doi = {10.1098/rspb.2014.2952},
  abstract = {The habitual playing of video games is associated with increased grey matter and activity in the striatum. Studies in humans and rodents have shown an inverse relationship between grey matter in the striatum and hippocampus. We investigated whether action video game playing is also associated with increased use of response learning strategies during navigation, known to be dependent on the caudate nucleus of the striatum, when presented in a dual solution task. We tested 26 action video game players (actionVGPs) and 33 non-action video game players (nonVGPs) on the 4-on-8 virtual maze and a visual attention event-related potential (ERP) task, which elicits a robust N-2-posterior-controlateral (N2pc) component. We found that actionVGPs had a significantly higher likelihood of using a response learning strategy (80.76\%) compared to nonVGPs (42.42\%). Consistent with previous evidence, actionVGPs and nonVGPs differed in the way they deployed visual attention to central and peripheral targets as observed in the elicited N2pc component during an ERP visual attention task. Increased use of the response strategy in actionVGPs is consistent with previously observed increases in striatal volume in video game players (VGPs). Using response strategies is associated with decreased grey matter in the hippocampus. Previous studies have shown that decreased volume in the hippocampus precedes the onset of many neurological and psychiatric disorders. If actionVGPs have lower grey matter in the hippocampus, as response learners normally do, then these individuals could be at increased risk of developing neurological and psychiatric disorders during their lifetime.},
  langid = {english},
  annotation = {71 citations (Semantic Scholar/DOI) [2022-12-09]},
  file = {/Users/morteza/Documents/Zotero/storage/4VMHPX3E/West et al. - 2015 - Habitual action video game playing is associated w.pdf}
}

@article{west2018,
  title = {Impact of Video Games on Plasticity of the Hippocampus},
  author = {West, G. L. and Konishi, K. and Diarra, M. and {Benady-Chorney}, J. and Drisdelle, B. L. and Dahmani, L. and Sodums, D. J. and Lepore, F. and Jolicoeur, P. and Bohbot, V. D.},
  year = {2018},
  month = jul,
  journal = {Molecular Psychiatry},
  volume = {23},
  number = {7},
  pages = {1566--1574},
  publisher = {{Nature Publishing Group}},
  issn = {1476-5578},
  doi = {10.1038/mp.2017.155},
  abstract = {The hippocampus is critical to healthy cognition, yet results in the current study show that action video game players have reduced grey matter within the hippocampus. A subsequent randomised longitudinal training experiment demonstrated that first-person shooting games reduce grey matter within the hippocampus in participants using non-spatial memory strategies. Conversely, participants who use hippocampus-dependent spatial strategies showed increased grey matter in the hippocampus after training. A control group that trained on 3D-platform games displayed growth in either the hippocampus or the functionally connected entorhinal cortex. A third study replicated the effect of action video game training on grey matter in the hippocampus. These results show that video games can be beneficial or detrimental to the hippocampal system depending on the navigation strategy that a person employs and the genre of the game.},
  copyright = {2018 Springer Nature Limited},
  langid = {english},
  keywords = {Behavioral Sciences,Biological Psychology,general,Medicine/Public Health,Neurosciences,Pharmacotherapy,Psychiatry},
  annotation = {79 citations (Semantic Scholar/DOI) [2022-12-07]},
  file = {/Users/morteza/Documents/Zotero/storage/FNYR64I6/West et al_2018_Impact of video games on plasticity of the hippocampus.pdf;/Users/morteza/Documents/Zotero/storage/W6GDZEEP/mp2017155.html}
}

@article{west2020,
  title = {The {{Contrasting Effects}} of an {{Action Video Game}} on {{Visuo-Spatial Processing}} and {{Proactive Cognitive Control}}},
  author = {West, Robert and Swing, Edward L. and Anderson, Craig A. and Prot, Sara},
  year = {2020},
  month = jul,
  journal = {International Journal of Environmental Research and Public Health},
  volume = {17},
  number = {14},
  pages = {5160},
  issn = {1660-4601},
  doi = {10.3390/ijerph17145160},
  abstract = {First person shooter or action video games represent one of the most popular genres within the gaming industry. Studies reveal that action gaming experience leads to enhancements of visuo-spatial processing. In contrast, some correlational evidence reveals that experience with action video games may be associated with reduced proactive cognitive control. The two primary goals of the current study were to test the causal nature of the effect of action gaming on proactive cognitive control and to examine whether an increase in visuo-spatial processing and a decrease in proactive cognitive control arise from the same amount of experience playing an action video game. Participants completed tasks measuring visuo-spatial processing and cognitive control before and after 10 practice sessions involving one of three video games or were assigned to a no gaming experience control group. The data revealed the typical increase in visuo-spatial processing and a decrease in proactive, but not reactive, cognitive control following action game training. The sizes of these two training effects were similar in magnitude, but interpretation of the effects was constrained by baseline differences between the four groups of subjects. The possibility of a causal effect of action gaming on proactive cognitive control is interesting within the context of correlational evidence linking greater action gaming experience to reduced cognitive control, poor decision making, and increased impulsivity.},
  langid = {english},
  annotation = {5 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/QTHA6EFC/West et al. - 2020 - The Contrasting Effects of an Action Video Game on.pdf}
}

@article{whitbourne2013,
  title = {Reasons for {{Playing Casual Video Games}} and {{Perceived Benefits Among Adults}} 18 to 80 {{Years Old}}},
  author = {Whitbourne, Susan Krauss and Ellenberg, Stacy and Akimoto, Kyoko},
  year = {2013},
  month = dec,
  journal = {Cyberpsychology, Behavior, and Social Networking},
  volume = {16},
  number = {12},
  pages = {892--897},
  issn = {2152-2715, 2152-2723},
  doi = {10.1089/cyber.2012.0705},
  langid = {english},
  annotation = {00027}
}

@article{white2018,
  title = {Testing the Validity of Conflict Drift-Diffusion Models for Use in Estimating Cognitive Processes: {{A}} Parameter-Recovery Study},
  shorttitle = {Testing the Validity of Conflict Drift-Diffusion Models for Use in Estimating Cognitive Processes},
  author = {White, Corey N. and Servant, Mathieu and Logan, Gordon D.},
  year = {2018},
  month = feb,
  journal = {Psychonomic Bulletin \& Review},
  volume = {25},
  number = {1},
  pages = {286--301},
  issn = {1531-5320},
  doi = {10.3758/s13423-017-1271-2},
  abstract = {Researchers and clinicians are interested in estimating individual differences in the ability to process conflicting information. Conflict processing is typically assessed by comparing behavioral measures like RTs or error rates from conflict tasks. However, these measures are hard to interpret because they can be influenced by additional processes like response caution or bias. This limitation can be circumvented by employing cognitive models to decompose behavioral data into components of underlying decision processes, providing better specificity for investigating individual differences. A new class of drift-diffusion models has been developed for conflict tasks, presenting a potential tool to improve analysis of individual differences in conflict processing. However, measures from these models have not been validated for use in experiments with limited data collection. The present study assessed the validity of these models with a parameter-recovery study to determine whether and under what circumstances the models provide valid measures of cognitive processing. Three models were tested: the dual-stage two-phase model (H\"ubner, Steinhauser, \& Lehle, Psychological Review, 117(3), 759\textendash 784, 2010), the shrinking spotlight model (White, Ratcliff, \& Starns, Cognitive Psychology, 63(4), 210\textendash 238, 2011), and the diffusion model for conflict tasks (Ulrich, Schr\"oter, Leuthold, \& Birngruber, Cogntive Psychology, 78, 148\textendash 174, 2015). The validity of the model parameters was assessed using different methods of fitting the data and different numbers of trials. The results show that each model has limitations in recovering valid parameters, but they can be mitigated by adding constraints to the model. Practical recommendations are provided for when and how each model can be used to analyze data and provide measures of processing in conflict tasks.},
  langid = {english},
  keywords = {Cognitive modeling,Conflict tasks,Drift-diffusion model,Parameter validity},
  annotation = {68 citations (Semantic Scholar/DOI) [2022-12-13]},
  file = {/Users/morteza/Documents/Zotero/storage/T5CDQE9V/White et al_2018_Testing the validity of conflict drift-diffusion models for use in estimating.pdf}
}

@article{wickham2014,
  title = {Tidy {{Data}}},
  author = {Wickham, Hadley},
  year = {2014},
  journal = {Journal of Statistical Software},
  volume = {59},
  number = {10},
  issn = {1548-7660},
  doi = {10.18637/jss.v059.i10},
  langid = {english}
}

@article{wickham2019,
  title = {Welcome to the {{Tidyverse}}},
  author = {Wickham, Hadley and Averick, Mara and Bryan, Jennifer and Chang, Winston and McGowan, Lucy and Fran{\c c}ois, Romain and Grolemund, Garrett and Hayes, Alex and Henry, Lionel and Hester, Jim and Kuhn, Max and Pedersen, Thomas and Miller, Evan and Bache, Stephan and M{\"u}ller, Kirill and Ooms, Jeroen and Robinson, David and Seidel, Dana and Spinu, Vitalie and Takahashi, Kohske and Vaughan, Davis and Wilke, Claus and Woo, Kara and Yutani, Hiroaki},
  year = {2019},
  month = nov,
  journal = {Journal of Open Source Software},
  volume = {4},
  number = {43},
  pages = {1686},
  issn = {2475-9066},
  doi = {10.21105/joss.01686},
  annotation = {4860 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/9STPVRTI/Wickham et al. - 2019 - Welcome to the Tidyverse.pdf}
}

@article{winkler2010,
  title = {Cortical {{Thickness}} or {{Grey Matter Volume}}? {{The Importance}} of {{Selecting}} the {{Phenotype}} for {{Imaging Genetics Studies}}},
  shorttitle = {Cortical {{Thickness}} or {{Grey Matter Volume}}?},
  author = {Winkler, Anderson M. and Kochunov, Peter and Blangero, John and Almasy, Laura and Zilles, Karl and Fox, Peter T. and Duggirala, Ravindranath and Glahn, David C.},
  year = {2010},
  month = nov,
  journal = {NeuroImage},
  volume = {53},
  number = {3},
  pages = {1135--1146},
  issn = {1053-8119},
  doi = {10.1016/j.neuroimage.2009.12.028},
  abstract = {Choosing the appropriate neuroimaging phenotype is critical to successfully identify genes that influence brain structure or function. While neuroimaging methods provide numerous potential phenotypes, their role for imaging genetics studies are unclear. Here we examine the relationship between brain volume, grey matter volume, cortical thickness and surface area, from a genetic standpoint. Four hundred and eighty-six individuals from randomly ascertained extended pedigrees with high-quality T1-weighted neuroanatomic MRI images participated in the study. Surface-based and voxel-based representations of brain structure were derived, using automated methods, and these measurements were analysed using a variance-components method to identify the heritability of these traits and their genetic correlations. All neuroanatomic traits were significantly influenced by genetic factors. Cortical thickness and surface area measurements were found to be genetically and phenotypically independent. While both thickness and area influenced volume measurements of cortical grey matter, volume was more closely related to surface area than cortical thickness. This trend was observed for both the volume-based and surface-based techniques. The results suggest that surface area and cortical thickness measurements should be considered separately and preferred over gray matter volumes for imaging genetic studies.},
  pmcid = {PMC2891595},
  pmid = {20006715},
  annotation = {00000},
  file = {/Users/morteza/Documents/Zotero/storage/767AKMVP/Winkler et al. - 2010 - Cortical Thickness or Grey Matter Volume The Impo.pdf}
}

@article{wiradhany2017,
  title = {Cognitive Control in Media Multitaskers: {{Two}} Replication Studies and a Meta-{{Analysis}}},
  shorttitle = {Cognitive Control in Media Multitaskers},
  author = {Wiradhany, Wisnu and Nieuwenstein, Mark R.},
  year = {2017},
  month = nov,
  journal = {Attention, Perception, \& Psychophysics},
  volume = {79},
  number = {8},
  pages = {2620--2641},
  issn = {1943-3921, 1943-393X},
  doi = {10.3758/s13414-017-1408-4},
  langid = {english},
  annotation = {57 citations (Semantic Scholar/DOI) [2022-12-14]},
  file = {/Users/morteza/Documents/Zotero/storage/VZKTGYD6/Wiradhany and Nieuwenstein - 2017 - Cognitive control in media multitaskers Two repli.pdf}
}

@article{wu2012,
  title = {Playing a {{First-person Shooter Video Game Induces Neuroplastic Change}}},
  author = {Wu, Sijing and Cheng, Cho Kin and Feng, Jing and D'Angelo, Lisa and Alain, Claude and Spence, Ian},
  year = {2012},
  month = jun,
  journal = {Journal of Cognitive Neuroscience},
  volume = {24},
  number = {6},
  pages = {1286--1293},
  issn = {0898-929X, 1530-8898},
  doi = {10.1162/jocn_a_00192},
  langid = {english},
  annotation = {00000}
}

@article{wu2013,
  title = {Playing Shooter and Driving Videogames Improves Top-down Guidance in Visual Search},
  author = {Wu, Sijing and Spence, Ian},
  year = {2013},
  month = may,
  journal = {Attention, Perception, \& Psychophysics},
  volume = {75},
  number = {4},
  pages = {673--686},
  issn = {1943-3921, 1943-393X},
  doi = {10.3758/s13414-013-0440-2},
  langid = {english},
  annotation = {00072},
  file = {/Users/morteza/Documents/Zotero/storage/ZJ8SVURN/Wu and Spence - 2013 - Playing shooter and driving videogames improves to.pdf}
}

@article{xiong2019,
  title = {Effects of {{Exergaming}} on {{Preschoolers}}' {{Executive Functions}} and {{Perceived Competence}}: {{A Pilot Randomized Trial}}},
  shorttitle = {Effects of {{Exergaming}} on {{Preschoolers}}' {{Executive Functions}} and {{Perceived Competence}}},
  author = {Xiong, Shanying and Zhang, Peng and Gao, Zan},
  year = {2019},
  month = apr,
  journal = {Journal of Clinical Medicine},
  volume = {8},
  number = {4},
  issn = {2077-0383},
  doi = {10.3390/jcm8040469},
  abstract = {Purpose: This study aimed to evaluate the effects of a child-centered exergaming program and a traditional teacher-led physical activity (PA) program on preschoolers' executive functions and perceived competence. Methods: Sixty children aged 4{$^-$}5 years from an urban childcare center in China completed an 8-week exergaming/traditional PA intervention. After baseline measurements of executive functions and perceived competence (i.e., perceived physical competence and social acceptance), children were randomly assigned to either an exergaming group or traditional PA group (30 children per group). Exergaming and traditional PA programs were offered 20 min/session by trained instructors for 8 weeks. Post-intervention measures were identical to baseline measures. Results: In general, children's executive functions, perceived physical competence, and perceived social acceptance were enhanced over time. Analysis of variance revealed significant time by group interaction effects for executive functions, F(1, 58) = 12.01, p = 0.01, and perceived social acceptance, F(1, 58) = 6.04, p = 0.02, indicating that the exergaming intervention group displayed significantly greater increases in executive functions and perceived social acceptance in comparison with traditional PA children. In addition, children's executive functions and perceived physical and social competence significantly improved from baseline to post-intervention. However, there was no significant difference in the increase of children's perceived physical competence across groups over time. Conclusion: The results suggested exergaming to be beneficial in enhancing young children's executive functions and perceived social acceptance compared to the traditional PA program. More diverse samples with a longer intervention duration in preschool children in urban areas are warranted.},
  langid = {english},
  pmid = {30959860},
  keywords = {active video games,cognitive functions,perceived physical competence,perceived social acceptance,preschool children},
  file = {/Users/morteza/Documents/Zotero/storage/HT3DSIDV/Xiong et al. - 2019 - Effects of Exergaming on Preschoolers' Executive F.pdf}
}

@article{yang2019,
  title = {Task Representations in Neural Networks Trained to Perform Many Cognitive Tasks},
  author = {Yang, Guangyu Robert and Joglekar, Madhura R. and Song, H. Francis and Newsome, William T. and Wang, Xiao-Jing},
  year = {2019},
  month = feb,
  journal = {Nature Neuroscience},
  volume = {22},
  number = {2},
  pages = {297--306},
  issn = {1546-1726},
  doi = {10.1038/s41593-018-0310-2},
  abstract = {The brain has the ability to flexibly perform many tasks, but the underlying mechanism cannot be elucidated in traditional experimental and modeling studies designed for one task at a time. Here, we trained single network models to perform 20 cognitive tasks that depend on working memory, decision making, categorization, and inhibitory control. We found that after training, recurrent units can develop into clusters that are functionally specialized for different cognitive processes, and we introduce a simple yet effective measure to quantify relationships between single-unit neural representations of tasks. Learning often gives rise to compositionality of task representations, a critical feature for cognitive flexibility, whereby one task can be performed by recombining instructions for other tasks. Finally, networks developed mixed task selectivity similar to recorded prefrontal neurons after learning multiple tasks sequentially with a continual-learning technique. This work provides a computational platform to investigate neural representations of many cognitive tasks.},
  langid = {english},
  pmid = {30643294},
  keywords = {Brain,Cognition,Computer Simulation,Decision Making,Humans,Learning,Memory; Short-Term,Models; Neurological,Neural Networks; Computer,Neurons}
}

@article{yeo2011,
  title = {The Organization of the Human Cerebral Cortex Estimated by Intrinsic Functional Connectivity},
  author = {Yeo, B. T. Thomas and Krienen, Fenna M. and Sepulcre, Jorge and Sabuncu, Mert R. and Lashkari, Danial and Hollinshead, Marisa and Roffman, Joshua L. and Smoller, Jordan W. and Z{\"o}llei, Lilla and Polimeni, Jonathan R. and Fischl, Bruce and Liu, Hesheng and Buckner, Randy L.},
  year = {2011},
  month = sep,
  journal = {Journal of Neurophysiology},
  volume = {106},
  number = {3},
  pages = {1125--1165},
  issn = {0022-3077, 1522-1598},
  doi = {10.1152/jn.00338.2011},
  abstract = {Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.},
  langid = {english},
  annotation = {03223}
}

@incollection{yeung2013,
  title = {Conflict {{Monitoring}} and {{Cognitive Control}}},
  booktitle = {The {{Oxford Handbook}} of {{Cognitive Neuroscience}}: {{Volume}} 2: {{The Cutting Edges}}},
  author = {Yeung, Nicholas},
  editor = {Ochsner, Kevin N. and Kosslyn, Stephen},
  year = {2013},
  month = dec,
  pages = {0},
  publisher = {{Oxford University Press}},
  doi = {10.1093/oxfordhb/9780199988709.013.0018},
  abstract = {Neural mechanisms of cognitive control are hypothesized to support flexible, goal-directed behavior by representing task-relevant information in order to guide thought and action. The conflict monitoring theory proposes that anterior cingulate cortex (ACC) contributes to cognitive control by detecting conflicts in information processing and signaling when increased top-down control is required. This theory provides a computationally specified framework for understanding how cognitive control is recruited and explains a large literature of human neuroimaging studies reporting ACC activity in conditions of increased cognitive demand. Predictions from the theory have been tested and consistently confirmed in behavioral and neuroimaging experiments with human subjects. However, challenging findings from patients with ACC lesions and from studies of ACC function in nonhuman primates suggest that conflict monitoring may be just one facet of the broader role of ACC in performance monitoring and the optimization of behavior.},
  isbn = {978-0-19-998870-9}
}

@article{yung2015,
  title = {Methods to {{Test Visual Attention Online}}},
  author = {Yung, Amanda and {Cardoso-Leite}, Pedro and Dale, Gillian and Bavelier, Daphne and Green, C. Shawn},
  year = {2015},
  month = feb,
  journal = {Journal of Visualized Experiments},
  number = {96},
  issn = {1940-087X},
  doi = {10.3791/52470},
  langid = {english},
  annotation = {00007},
  file = {/Users/morteza/Documents/Zotero/storage/DKJLSSU3/Yung et al. - 2015 - Methods to Test Visual Attention Online.pdf}
}

@article{zelazo2017,
  title = {Executive Function: {{Implications}} for Education},
  author = {Zelazo, Philip David and Blair, Clancy B. and Willoughby, Michael T.},
  year = {2017}
}

@article{zhang2015,
  title = {Higher Integrity of the Motor and Visual Pathways in Long-Term Video Game Players},
  author = {Zhang, Yang and Du, Guijin and Yang, Yongxin and Qin, Wen and Li, Xiaodong and Zhang, Quan},
  year = {2015},
  month = mar,
  journal = {Frontiers in Human Neuroscience},
  volume = {9},
  pages = {695},
  doi = {10.3389/fnhum.2015.00098},
  annotation = {00014},
  file = {/Users/morteza/Documents/Zotero/storage/K8XXZEUD/zhang2015.pdf}
}

@article{zink2021,
  title = {A New Era for Executive Function Research: {{On}} the Transition from Centralized to Distributed Executive Functioning},
  shorttitle = {A New Era for Executive Function Research},
  author = {Zink, Nicolas and Lenartowicz, Agatha and Markett, Sebastian},
  year = {2021},
  month = may,
  journal = {Neuroscience \& Biobehavioral Reviews},
  volume = {124},
  pages = {235--244},
  issn = {01497634},
  doi = {10.1016/j.neubiorev.2021.02.011},
  abstract = {Executive functions'' (EFs) is an umbrella term for higher cognitive control functions such as working memory, inhibition, and cognitive flexibility. One of the most challenging problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but illdefined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to a breakthrough in understanding how the brain controls and regulates itself. We propose to reconceptualize EFs as emergent consequences of highly distributed brain processes that communicate with a pool of highly connected hub regions, thus precluding the need for a central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and helps to refine our understanding of the mecha\- nisms underlying EFs by providing new, testable hypotheses and resolves empirical and theoretical in\- consistencies in the EF literature.},
  langid = {english},
  keywords = {Brain,Brain networks,Central executive,Cognitive control,Distributed networks,Executive Function,Executive functions,Flexibility,Humans,Inhibition,Inhibition; Psychological,Memory; Short-Term,Working memory},
  file = {/Users/morteza/Documents/Zotero/storage/7JZT5GGE/Zink et al. - 2021 - A new era for executive function research On the .pdf;/Users/morteza/Documents/Zotero/storage/S75T5VVS/Zink et al. - 2021 - A new era for executive function research On the .pdf}
}