Past, present and future of spike sorting techniques

By H. Rey, Carlos Pedreira, R. Quian Quiroga. Brain Research Bulletin, 2015

446 citations recorded by the source corpus.

Spike sorting is a crucial step to extract information from extracellular recordings. With new recording opportunities provided by the development of new electrodes that allow monitoring hundreds of neurons simultaneously, the scenario for the new generation of algorithms is both exciting and challenging. However, this will require a new approach to the problem and the development of a common reference framework to quickly assess the performance of new algorithms. In this work, we review the basic concepts of spike sorting, including the requirements for different applications, together with the problems faced by presently available algorithms. We conclude by proposing a roadmap stressing the crucial points to be addressed to support the neuroscientific research of the near future.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/f032f145f06ffef9e60833e4f85700fb8a98a1d0

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

Citations in the corpus

SpikeInterface, a unified framework for spike sorting (2019, methodology): “To alleviate this issue, spike sorting has seen decades of algorithmic and software improvements to increase both the accuracy and automation of the process [62].”
Automated long-term recording and analysis of neural activity in behaving animals (2016, methodology): “These face three major challenges (Rey et al., 2015): First, they must reliably capture the activity of simultaneously recorded neurons whose firing rates can vary over many orders of magnitude (Hromádka et al., 2008; Mizuseki and Buzsáki, 2013).”