Publication: BioSig: The Free and Open Source Software Library for Biomedical Signal Processing
Homepage: http://biosig.sourceforge.net
- A biomedical signal processing library with very broad applicability.
- Includes C/C++ librares, toolboxes for Octave/MATLAB, Python bindings and also and other components not relevant to this project.
- Not well suited for the neuroscience in particular.
- Poorly documented, supports neither Axon Binary File (.abf) nor Neuralynx (.ncs) data formats.
Publication: Neo: an object model for handling electrophysiology data in multiple formats
Homepage: http://neuralensemble.org/neo
- A language-independent, simple object model for representing electrophysiological data
- Does not have any built-in analysis functionality by design
- Has a Python implementation which supports many data formats
- For the neuroscience problem domain, the model is both simple, accurate and non-restrictive
- Documentation quality is good
- Performance is expected to be sufficient, due to NumPy with ATLAS/LINPACK
- Backwards-incompatible API changes in the upcoming version 0.4
It is promising to design and implement a data analysis framework on the top of Neo for common spike sorting pipeline. This framework can be used to experiment with different algorithms for different pipeline stages. Finally, it can be integrated with GUI data viewers built on top of Neo.
Homepage: http://sigviewer.sourceforge.net
- Biosignal viewer based on the BioSig library.
For our purposes, it has the same disadvantages as the BioSig library.
Publication: Stimfit: quantifying electrophysiological data with Python
Homepage: http://stimfit.org
- Old, stable software
- Has very unintuitive interface
- Has an interactive Python console
Publication: Spyke Viewer: a flexible and extensible platform for electrophysiological data analysis
Homepage: http://spyke-viewer.g-node.org
- Based on the Neo library
- Has a plugin system and an interactive console
- Very good GUI tool considering the Neo backend.
- GUI is not intuitive and reflects the underlying system architecture rather than providing easy-to-use interface for neuroscientists.
The best general-purpose viewer considering usage of the Neo model.
Publication: OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework
Homepage: http://neuralensemble.org/OpenElectrophy
- Based on the Neo library
- Has graphs in time and frequency domain
- Targets to storing electrophysiogical data in the database, managing collections of data
- Has spike sorting functionality
- Has a number of minor quality issues
Publication: Klusters, NeuroScope, NDManager: a free software suite for neurophysiological data processing and visualization no full-text article
Homepage: http://neurosuite.sourceforge.net
- Tools for data management, visualisation and clustering.
Looks quite good on screenshots, but doesn't support required data formats.
Publication: High-dimensional cluster analysis with the Masked EM Algorithm
Homepage: http://klusta-team.github.io
- Tools for spike detection, automatic batch clustering and refining clusters manually.
- Accepts it's own KWIK file format (based in HDF5) as well as raw recordings.
- Has a lot of configuration parameters for the detection and clustering algorithms.
Homepage: https://code.google.com/p/spikepy
A framework for spike sorting.
- Has a GUI
- Doesn't support required data formats
- Poorly documented
It can be used as an example for building our own pipeline.
Homepage: http://spikesort.org
Another framework for spike sorting.
- Documentation is good
- Doesn't support required data formats
- Implements several clutering methods
- Has limited visualisation functionality, but main work is done through the Python console
The best library for rapid prototyping and experimentation, assuming confidence with Python.
Homepage: https://code.google.com/p/caton
Yet another spike sorting library.
- Intended to work with KlustaKwik
- Doesn't support required data formats
Worth looking to the source code.