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Unsupervised Spike Sorting for Large-Scale, High-Density Multielectrode Arrays

Authors: Hilgen, Gerrit; Sorbaro, Martino; Pirmoradian, Sahar; Muthmann, Jens-Oliver; Kepiro, Ibolya E.; Ullo, Simona; Juarez Ramirez, Cesar; +8 Authors
APC: 5,403.36 EUR

Unsupervised Spike Sorting for Large-Scale, High-Density Multielectrode Arrays

Abstract

Abstract A new method for automated spike sorting for recordings with high density, large scale multielectrode arrays is presented. Exploiting the dense sampling of single neurons by multiple electrodes, we obtain an efficient, low-dimensional representation of detected spikes consisting of estimated spatial spike locations and dominant spike shape features, which enables fast and reliable clustering into single units. Millions of events can be sorted in minutes, and the method is parallelized and scales better than quadratically with the number of detected spikes. We demonstrate this method using recordings with a 4,096 channel array, and present validation based on anatomical imaging, optogenetic stimulation and model-based quality control. A comparison with semi-automated, shape-based spike sorting exposes significant limitations of conventional methods. Our analysis shows that it is feasible to reliably isolate the activity of hundreds to thousands of neurons in a single recording, and that dense, multi-channel probes substantially aid reliable spike sorting.

Countries
Italy, United Kingdom, United Kingdom
Keywords

Retinal Ganglion Cells, retina, neural cultures, QH301-705.5, Models, Neurological, electrophysiology; high-density multielectrode array; neural cultures; retina; spike sorting; Action Potentials; Animals; Electrodes; Electrophysiology; Imaging, Three-Dimensional; Mice, Inbred C57BL; Models, Neurological; Optogenetics; Reproducibility of Results; Retinal Ganglion Cells, 610, Action Potentials, spike sorting, Imaging, Three-Dimensional, Animals, Biology (General), Electrodes, computer, neural culture, We present a method for automated spike sorting for recordings with high-density, large-scale multielectrode arrays. Exploiting the dense sampling of single neurons by multiple electrodes, an efficient, low-dimensional representation of detected spikes consisting of estimated spatial spike locations and dominant spike shape features is exploited for fast and reliable clustering into single units. Millions of events can be sorted in minutes, and the method is parallelized and scales better than quadratically with the number of detected spikes. Performance is demonstrated using recordings with a 4,096-channel array and validated using anatomical imaging, optogenetic stimulation, and model-based quality control. A comparison with semi-automated, shape-based spike sorting exposes significant limitations of conventional methods. Our approach demonstrates that it is feasible to reliably isolate the activity of up to thousands of neurons and that dense, multi-channel probes substantially aid reliable spike sorting., Reproducibility of Results, electrophysiology, C700, Electrophysiology, Mice, Inbred C57BL, Optogenetics, high-density multielectrode array, biological

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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
121
Top 1%
Top 10%
Top 1%
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gold