Volume 115, Number 6, September 2016
|Number of page(s)||7|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||27 October 2016|
Noise-induced interspike interval correlations and spike train regularization in spike-triggered adapting neurons
División de Física Estadística e Interdisciplinaria, Centro Atómico Bariloche - Av. E. Bustillo Km 9.500, S. C. de Bariloche (8400), Río Negro, Argentina
Received: 23 March 2016
Accepted: 6 October 2016
Spike generation in neurons produces a temporal point process, whose statistics is governed by intrinsic phenomena and the external incoming inputs to be coded. In particular, spike-evoked adaptation currents support a slow temporal process that conditions spiking probability at the present time according to past activity. In this work, we study the statistics of interspike interval correlations arising in such non-renewal spike trains, for a neuron model that reproduces different spike modes in a small adaptation scenario. We found that correlations are stronger as the neuron fires at a particular firing rate, which is defined by the adaptation process. When set in a subthreshold regime, the neuron may sustain this particular firing rate, and thus induce correlations, by noise. Given that, in this regime, interspike intervals are negatively correlated at any lag, this effect surprisingly implies a reduction in the variability of the spike count statistics at a finite noise intensity.
PACS: 87.19.ll – Models of single neurons and networks / 87.10.Mn – Stochastic modeling / 87.19.lc – Noise in the nervous system
© EPLA, 2016
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