Automated spike sorter utilizing the super paramagnetic clustering algorithm.

TomSort is an automated spike sorter utilizing the super paramagnetic clustering (SPC) algorithm. We leveraged the SPC code implemented by the Quiroga lab at the University of Leicester (see the reference for further details). In the Turner lab at the University of Pittsburgh, we use TomSort for spike sorting, then convert the data into the next (NeuroExplorer, Plexon) file format. Subsequently, we curate the results using OfflineSorter (Plexon) and evaluate the quality of unit isolation. This repository contains the codes for TomSort and the conversion script. Data Structure The data file needs two variables: extracellular data names ad "signal" or "hp_cont" and the sampling rate (Hz) names as "samplerate" MatLab Requirements Parallel Computing Toolbox: https://www.mathworks.com/products/parallel-computing.html extrema.m function: https://www.mathworks.com/matlabcentral/fileexchange/12275-extrema-m-extrema2-m wave_clus (SPC): https://github.com/csn-le/wave_clus Code to read and write NeuroExplorer data files: https://www.neuroexplorer.com/downloadspage/ Reference Chaure, F. J. and Rey, H. G. and Quian Quiroga, R. "A novel and fully automatic spike sorting implementation with variable number of features", Journal of Neurophysiology, vol. 120-4, pg. 1859-1871, 2018 Funding Resource This research was funded in part by Aligning Science Across Parkinson’s (ASAP-020519) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF).