Our laboratory produces freely available, open-source tools. We also share some data, and plan to share more in the near future.
One set of tools is devoted to “spike sorting”: detecting and clustering spikes obtained from multielectrode arrays, so that spikes are assigned to the correct neurons. For this purpose we use Kilosort, developed by Marius Pachitariu. The algorithm is described in a 2016 preprint in bioRxiv. It requires a desktop workstation with a MATLAB license and a consumer GPU. The code and installation instructions are in the GitHub repository. To view and curate the results of Kilosort we use Phy, developed by Cyrille Rossant.
Another set of tools is devoted to the analysis of data from two-photon imaging: image registration, detection of neurons and other regions of interest, manual curation, and deconvolution of fluorescence traces to infer spike timing. For this analysis we use Suite2P, a suite of tools developed by Marius Pachitariu. At its core is a clustering algorithm to find what pixels are correlated together and form a region of interest, complemented by additions to correct for neuropil contamination, avoid local minima, and maximize speed so it runs about as fast as real time data acquisition. The algorithm is described in a 2016 preprint in bioRxiv. It requires a desktop workstation with a MATLAB license, and for faster processing, a consumer GPU. A GUI is included for manually vetting the regions of interest. The code and installation instructions are in the GitHub repository.
Steering wheel setup
Our laboratory developed a steering wheel setup to probe mouse behavior (bioRxiv 2016). In this setup, a mouse indicates whether a visual stimulus appears to its left or to its right by turning a steering wheel with its front paws. The steering wheel is in turn coupled to the horizontal position of the visual stimulus, so that selecting a stimulus involves moving it to the center of the screen. To facilitate the deployment of this task to other laboratories, we provide instructions to build this steering wheel setup with components that are entirely off-the-shelf or 3D-printable.
Another set of tools is devoted to controlling experiments. For this we use an open-source package called Signals, developed by Chris Burgess. It uses a dataflow-style paradigm expressed in MATLAB to allow concise and intuitive specification of stimulus presentation, task structure, and control of data acquisition. The GitHub repository contains some information, more documentation to come.