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Large coefficient of variation of inter-spike intervals induced by noise current in the resonate-and-fire model neuron

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Abstract

Neuronal spike variability is a statistical property associated with the noise environment. Considering a linearised Hodgkin–Huxley model, we investigate how large spike variability can be induced in a typical stellate cell when submitted to constant and noise current amplitudes. For low noise current, we observe only periodic firing (active) or silence activities. For intermediate noise values, in addition to only active or inactive periods, we also identify a single transition from an initial spike-train (active) to silence dynamics over time, where the spike variability is low. However, for high noise current, we find intermittent active and silence periods with different values. The spike intervals during active and silent states follow the exponential distribution, which is similar to the Poisson process. For non-maximal noise current, we observe the highest values of inter-spike variability. Our results suggest sub-threshold oscillations as a possible mechanism for the appearance of high spike variability in a single neuron due to noise currents.

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Acknowledgements

This work was possible by partial financial support from the following Brazilian government agencies: São Paulo Research Foundation (FAPESP) under Grant Nos. 2020/04624-2 and 2018/03211-6, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) under Grant Nos. 407299/2018-1 and 302665/2017-0.

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Correspondence to P. R. Protachevicz.

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Protachevicz, P.R., Bonin, C.A., Iarosz, K.C. et al. Large coefficient of variation of inter-spike intervals induced by noise current in the resonate-and-fire model neuron. Cogn Neurodyn 16, 1461–1470 (2022). https://doi.org/10.1007/s11571-022-09789-z

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