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-diusion process. We prove that, when specific ranges of the involved parameters are chosen, it is possible to observe multi-modal 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.

COOPERATIVE BEHAVIOR IN A JUMP DIFFUSION MODEL FOR A SIMPLE NETWORK OF SPIKING NEURONS

SIROVICH, ROBERTA;SACERDOTE, Laura Lea;
2014

Abstract

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-diusion process. We prove that, when specific ranges of the involved parameters are chosen, it is possible to observe multi-modal 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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http://aimsciences.org/journals/contentsListnew.jsp?pubID=639
Neural Networks; Jump Diffusion process; Stochastic Resonance; Stochastic leaky integrate and fire model
R. Sirovich; L. Sacerdote; A.E.P. Villa
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/139697
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