Table 1. Table of spike sorting algorithms currently included in the SpikeForest analysis.

Each algorithm is registered into the system via a Python wrapper. A Docker recipe defines the operating system and environment where the sorter is run. Algorithms with asterisks were updated and optimized using SpikeForest data. For the other algorithms, we used the default or recommended parameters.

Sorting algorithm	Language	Notes
HerdingSpikes2*	Python	Designed for large-scale, high-density multielectrode arrays. See Hilgen et al., 2017.
IronClust*	MATLAB and CUDA	Derived from JRCLUST. See Jun et al., in preparation.
JRCLUST	MATLAB and CUDA	Designed for high-density silicon probes. See Jun et al., 2017a.
KiloSort	MATLAB and CUDA	Template matching. See Pachitariu et al., 2016.
KiloSort2	MATLAB and CUDA	Derived from KiloSort. See Pachitariu et al., 2019.
Klusta	Python	Expectation-Maximization masked clustering. See Rossant et al., 2016.
MountainSort4	Python and C++	Density-based clustering via ISO-SPLIT. See Chung et al., 2017.
SpyKING CIRCUS*	Python and MPI	Density-based clustering and template matching. See Yger et al., 2018.
Tridesclous*	Python and OpenCL	See Garcia and Pouzat, 2019.
WaveClus	MATLAB	Superparamagnetic clustering. See Chaure et al., 2018; Quiroga et al., 2004.