Pierre Yger: Fast and accurate spike sorting for thousands of channels

 

Inserm, Paris

 

Abstract

Understanding how assemblies of neurons encode information requires recording of large populations of cells in the brain. In recent years, multi-electrode arrays and large silicon probes have been developed to record simultaneously from thousands of electrodes packed with a high density. To tackle the fact that these new devices challenge the classical way to perform spike sorting, we developed a fast and accurate spike sorting algorithm, validated both with in vivo and in vitro ground truth experiments. The software, performing a smart clustering of the spike waveforms followed by a greedy template-matching reconstruction of the signal, is able to scale to up to 4225 channels in parallel, solving the problem of temporally overlapping spikes. It thus appears as a general semi-automated solution to sort, offline, spikes from large-scale extracellular recordings. In addition, a refined implementation can be used to perform online spike sorting, and therefore paves the way towards future closed-loop experiments involving recordings with hundreds of electrodes.

Organized by

Joram Keijser, Filip Vercruysse, Henning Sprekeler

Location

BCCN Berlin, lecture hall, Philippstr. 13 Haus 6, 10115 Berlin