Fast and accurate spike sorting of high-channel count probes with KiloSort

By Marius Pachitariu, Nicholas A. Steinmetz, Shabnam N. Kadir, Matteo Carandini, Kenneth D. Harris. Neural Information Processing Systems, 2016

451 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2b9785e12b82baf67b185b6c2b0220514797c442

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Mengsen Zhang
2. F. Frohlich
3. E. Esposito
4. G. Zeck
5. Pierre Yger
6. Marcel Stimberg
7. Olivier Marre
8. Christophe Gardella

Citations in the corpus

• A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo (2018, methodology): “Kilosort used 32 GB of RAM for a maximal number of 500 neurons, while our algorithm had a much lower memory footprint, because of design choices.”
• Cell type-specific excitability probed by optogenetic stimulation depends on the phase of the alpha oscillation (2022, methodology): “Kilosort2 [55], a toolbox based on a template matching 176 algorithm, was used for initial spike extraction and sorting from raw electrophysiology data.”