About
Neo is an object model for handling electrophysiology data in multiple formats. It is suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. Neo has been implemented as a Python package for working with electrophysiology data, together with support for reading a wide range of neurophysiology file formats (including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock, Plexon, Tdt, Igor Pro), and support for writing to a subset of these formats plus non-proprietary formats including Kwik and HDF5.
Learn more: Neo documentation
Links
Commentaries on endorsed standards
https://f1000research.com/documents/11-658Supporting software
Data analysis
- Elephant. An open-source, community centered library for the analysis of electrophysiological data in the Python programming language http://neuralensemble.org/elephant
- SpykeViewer. A multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets https://spyke-viewer.readthedocs.org/en/latest/
Visualization
- SpykeViewer. A multi-platform GUI application for navigating, analyzing and visualizing electrophysiological datasets https://spyke-viewer.readthedocs.org/en/latest/
- Ephyviewer. A Python library based on pyqtgraph for building custom viewers for electrophysiological signals, video, events, epochs, spike trains, data tables, and time-frequency representations of signals. https://github.com/NeuralEnsemble/ephyviewer
Simulations
- PyNN. A simulator-independent language for building neuronal network models http://neuralensemble.org/PyNN
Spike sorting
- Tridesclous. A toolkit to teach good practices in spike sorting techniques https://github.com/tridesclous/tridesclous
Additional URL
Usage scenario
Use NEO if you want to:
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Recording multiple trials from multiple channels
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Recording spikes from multiple tetrodes
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Spike sorting