Cooperative behavior in a jump diffusion model for a simple network of spiking neurons
Author(s) -
Roberta Sirovich,
Laura Sacerdote,
Alessandro E. P. Villa
Publication year - 2013
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2014.11.385
Subject(s) - jump , interval (graph theory) , simple (philosophy) , computer science , biological system , sequence (biology) , jump diffusion , diffusion , transmission (telecommunications) , signal (programming language) , statistical physics , spike (software development) , biological neural network , algorithm , mathematics , physics , telecommunications , biology , machine learning , combinatorics , philosophy , genetics , software engineering , epistemology , quantum mechanics , programming language , thermodynamics
The distribution of time intervals between successive spikes generated by a neuronal cell --the interspike intervals (ISI)-- may reveal interesting features of the underlying dynamics. In this study we analyze the ISI sequence --the spike train-- generated by a simple network of neurons whose output activity is modeled by a jump-diffusion process. We prove that, when specific ranges of the involved parameters are chosen, it is possible to observe multimodal ISI distributions which reveal that the modeled network fires with more than one single preferred time interval. Furthermore, the system exhibits resonance behavior, with modulation of the spike timings by the noise intensity. We also show that inhibition helps the signal transmission between the units of the simple network.
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