SpikeInterface is a Python module to analyze extracellular electrophysiology data.
With a few lines of code, SpikeInterface enables you to load and pre-process the recording, run several state-of-the-art spike sorters, post-process and curate the output, compute quality metrics, and visualize the results.
SpikeInterface is made of several modules to deal with different aspects of the analysis pipeline:
- read/write many extracellular file formats.
- pre-process extracellular recordings.
- run many popular, semi-automatic spike sorters (also in Docker/Singularity containers).
- post-process spike sorted data.
- compare and benchmark spike sorting outputs.
- compute quality metrics to validate and curate spike sorting outputs.
- visualize recordings and spike sorting outputs.
- export a report and/or export to Phy.
- offer a powerful Qt-based viewer in a separate package spikeinterface-gui
- have some powerful sorting components to build your own sorter.
- have a full motion/drift correction framework (See
motion_correction)
overview installation modules/index how_to/index modules_gallery/index install_sorters viewers development/development api whatisnew authors
To get started with SpikeInterface, you can take a look at the following additional resources:
- spiketutorials is a collection of basic and advanced
tutorials. It includes links to videos to dive into the SpikeInterface framework. - SpikeInterface Reports contains several notebooks to reproduce analysis
figures of SpikeInterface-based papers and to showcase the latest features of SpikeInterface. - The 2020 eLife paper introduces the concept and motivation and
performs an in-depth comparison of multiple sorters (spoiler alert: they strongly disagree with each other!).
Note: the code-base and implementation have changed a lot since the "paper" version published in 2020.
For detailed documentation we therefore suggest more recent resources, like this documentation andspiketutorials.