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<h1>Functional Near-Infrared Spectroscopy (fNIRS)</h1>
<p>Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive imaging technique used to measure brain activity by monitoring changes in blood oxygenation levels. It operates on the principle that near-infrared light (700-900 nm) can penetrate biological tissues, allowing the detection of oxygenated and deoxygenated hemoglobin in the brain. fNIRS is particularly useful for studying cortical activity as it provides a balance between temporal resolution and portability, making it an attractive option for various research settings.</p>
<h2>How fNIRS Works</h2>
<p>fNIRS involves the use of near-infrared light, which is emitted from sources placed on the scalp. This light penetrates the scalp, skull, and brain tissues, reaching the cortical regions. As the light interacts with hemoglobin molecules in the blood, it is absorbed differentially depending on whether the hemoglobin is oxygenated or deoxygenated. Detectors placed on the scalp then capture the light that is reflected back, and the intensity of the reflected light is used to calculate the concentration of oxygenated and deoxygenated hemoglobin.</p>
<h2>Applications of fNIRS</h2>
<p>fNIRS is widely used in cognitive neuroscience, neurodevelopmental studies, and clinical research due to its non-invasive nature and ability to monitor brain activity in naturalistic settings. Common applications include:</p>
<ul>
<li><strong>Cognitive Functioning:</strong> fNIRS is used to study brain regions involved in cognitive processes such as attention, memory, language, and decision-making.</li>
<li><strong>Developmental Studies:</strong> fNIRS is particularly useful in studying infants and young children, as it allows researchers to observe brain activity with minimal discomfort.</li>
<li><strong>Clinical Research:</strong> fNIRS is employed to assess brain function in patients with neurological conditions such as stroke, traumatic brain injury, and psychiatric disorders. It is also used in brain-computer interface research and rehabilitation settings.</li>
</ul>
<p>Here is a great article on <a href="https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2020.00724/full">Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions</a>.</p>
<h2>Advantages of fNIRS</h2>
<ul>
<li><strong>Portability:</strong> fNIRS devices are often portable, making them suitable for studies conducted in naturalistic environments or clinical settings.</li>
<li><strong>Safety:</strong> The use of near-infrared light, which is non-ionizing, makes fNIRS a safe option for repeated measurements, even in vulnerable populations like infants.</li>
<li><strong>Temporal Resolution:</strong> While not as fast as electroencephalography (EEG), fNIRS offers better temporal resolution than fMRI, making it suitable for studying dynamic brain processes.</li>
</ul>
<h2>Limitations of fNIRS</h2>
<ul>
<li><strong>Spatial Resolution:</strong> fNIRS has limited spatial resolution compared to fMRI, as it can only measure activity in cortical regions and cannot access deeper brain structures.</li>
<li><strong>Signal Interference:</strong> The signal may be affected by factors such as hair thickness, skin tone, and motion artifacts, requiring careful preprocessing and analysis.</li>
<li><strong>Depth Limitation:</strong> fNIRS is primarily limited to measuring cortical brain regions, as near-infrared light does not penetrate deeply enough to reach subcortical areas.</li>
</ul>
<h2>Conclusion</h2>
<p>fNIRS is a valuable tool in the field of neuroimaging, offering a non-invasive, portable, and relatively inexpensive way to measure brain activity. Its ability to provide real-time data in naturalistic settings makes it especially useful for studying cognitive functions and developmental processes. Despite its limitations in spatial resolution and depth penetration, fNIRS continues to be a widely used technique in both research and clinical settings.</p>
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<h2>Funding</h2>
<p> We would like to express our heartfelt gratitude to <strong>Neurohackademy</strong> at the <strong>University of Washington eScience Institute</strong> for providing invaluable training and support. This experience has significantly enriched our understanding of neuroimaging and data science. We also acknowledge the support of the National Institute of Mental Health (NIMH) grant number <strong>5R25MH112480-08</strong>, which made this opportunity possible.</p>
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