Fast spike sorting by template matching
A fast and scalable solution for spike sorting of large-scale extracellular recordings
SpyKING CIRCUS is a python code to allow fast spike sorting on multi channel recordings. A publication on the algorithm can be found at https://elifesciences.org/articles/34518 It has been tested on datasets coming from in vitro retina with 252 electrodes MEA, from in vivo hippocampus with tetrodes, in vivo and in vitro cortex data with 30 and up to 4225 channels, with good results. Synthetic tests on these data show that cells firing at more than 0.5Hz can be detected, and their spikes recovered with error rates at around 1%, even resolving overlapping spikes and synchronous firing. It seems to be compatible with optogenetic stimulation, based on experimental data obtained in the retina.
SpyKING CIRCUS is currently still under development. Please do not hesitate to report issues with the issue tracker
- Documentation can be found at http://spyking-circus.rtfd.org
- A Google group can be found at http://groups.google.com/forum/#!forum/spyking-circus-users
- A bug tracker can be found at https://github.com/spyking-circus/spyking-circus/issues
- Open source ground-truth datasets used in the paper https://zenodo.org/record/1205233#.WrTFtXXwaV4
|copyright:||Copyright 2006-2018 by the SpyKING CIRCUS team, see AUTHORS.|
|license:||CeCILL, see LICENSE for details.|
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