RT Journal Article
SR Electronic
T1 SpikeInterface, a unified framework for spike sorting
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 796599
DO 10.1101/796599
A1 Alessio P. Buccino
A1 Cole L. Hurwitz
A1 Jeremy Magland
A1 Samuel Garcia
A1 Joshua H. Siegle
A1 Roger Hurwitz
A1 Matthias H. Hennig
YR 2019
UL http://biorxiv.org/content/early/2019/10/07/796599.abstract
AB Given the importance of understanding single-neuron activity, much development has been directed towards improving the performance and automation of spike sorting. These developments, however, introduce new challenges, such as file format incompatibility and reduced interoperability, that hinder benchmarking and preclude reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to standardize extracellular data file operations. With a few lines of code and regardless of the underlying data format, researchers can: run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs; and more. In this paper, we provide an overview of SpikeInterface and, with applications to both real and simulated extracellular datasets, demonstrate how it can improve the accessibility, reliability, and reproducibility of spike sorting in preparation for the widespread use of large-scale electrophysiology.