A spike-sorting method based on hierarchical clustering to discriminate extracellularly recorded simple spikes and complex spikes from cerebellar Purkinje cells

Michikawa, T.; Isobe, K.; Itohara, S.

doi:10.1101/2021.09.30.462526

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bioRxiv · 10.1101/2021.09.30.462526

A spike-sorting method based on hierarchical clustering to discriminate extracellularly recorded simple spikes and complex spikes from cerebellar Purkinje cells

Michikawa, T.·Isobe, K.·Itohara, S.

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Abstract

BackgroundIn the cerebellar cortex, Purkinje cells are the only output neurons and exhibit two types of discharge. Most Purkinje cell discharges are simple spikes, which are commonly appearing action potentials exhibiting a rich variety of firing patterns with a rate of up to 400 Hz. More infrequent discharges are complex spikes, which consist of a short burst of impulses accompanied by a massive increase in dendritic Ca2+ with a firing rate of around 1 Hz. The discrimination of these spikes in extracellular single-unit recordings is not always straightforward, as their waveforms vary depending on recording conditions and intrinsic fluctuations. New MethodTo discriminate complex spikes from simple spikes in the extracellular single-unit data, we developed a semiautomatic spike-sorting method based on divisive hierarchical clustering. ResultsQuantitative evaluation using parallel in vivo two-photon Ca2+ imaging of Purkinje cell dendrites indicated that 96.6% of the complex spikes were detected using our spike-sorting method from extracellular single-unit recordings obtained from anesthetized mice. Comparison with Existing Method(s)No reports have conducted a quantitative evaluation of spike-sorting algorithms used for the classification of extracellular spikes recorded from cerebellar Purkinje cells. ConclusionsOur method could be expected to contribute to research in information processing in the cerebellar cortex and the development of a fully automatic spike-sorting algorithm by providing ground-truth data useful for deep learning. HighlightsO_LIA spike-sorting algorithm on hierarchical clustering was developed. C_LIO_LIIt was applied to extracellular recordings from cerebellar Purkinje cells. C_LIO_LIComplex and simple spikes were discriminated based on their waveforms. C_LIO_LISpike-sorting performance was quantified using in vivo Ca2+ imaging data. C_LIO_LIThe algorithm isolated over 96.6% of complex spikes. C_LI

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Michikawa, T., Isobe, K., Itohara, S.. 2021-10-01. A spike-sorting method based on hierarchical clustering to discriminate extracellularly recorded simple spikes and complex spikes from cerebellar Purkinje cells. https://doi.org/10.1101/2021.09.30.462526

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