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Python toolkit for analysis, visualization, and comparison of spike sorting output

Project description

Build Status PyPI version


SpikeToolkit is a package of the SpikeInterface project is designed for efficient preprocessing, postprocessing, evaluation, and curation of extracellular datasets and spike sorting outputs.

Getting Started

To get started with SpikeToolkit, you can install it with pip:

pip install spiketoolkit

You can also get SpikeToolkit through the spikeinterface package:

pip install spikeinterface

You can also install SpikeToolkit locally by cloning the repo into your code base. If you install SpikeToolkit locally, you need to run the file.

git clone
cd spiketoolkit
python install


For more information about how to use SpikeToolkit, please checkout these examples.


All documentation for SpikeInterface can be found here:


Alessio Paolo Buccino - Center for Inegrative Neurolasticity (CINPLA), Department of Biosciences, Physics, and Informatics, University of Oslo, Oslo, Norway

Cole Hurwitz - The Institute for Adaptive and Neural Computation (ANC), University of Edinburgh, Edinburgh, Scotland

Jeremy Magland - Center for Computational Biology (CCB), Flatiron Institute, New York, United States

Matthias Hennig - The Institute for Adaptive and Neural Computation (ANC), University of Edinburgh, Edinburgh, Scotland

Samuel Garcia - Centre de Recherche en Neuroscience de Lyon (CRNL), Lyon, France

Josh Siegle - Allen Institute for Brain Science, Seattle, United States

For any correspondence, contact Alessio Buccino at

Project details

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Files for spiketoolkit, version 0.7.6
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