Noise Induces Spontaneous Synchronous Aperiodic Activity in EI Neural Networks View Full Text


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Chapter Info

DATE

2002-08-21

AUTHORS

Maria Marinaro , Silvia Scarpetta

ABSTRACT

We analyze the effect of noise on spontaneous activity of a excitatory-inhibitory neural network model. Analytically different regimes can be distinguished depending on the network parameters. In one of the regimes noise induces synchronous aperiodic oscillatory activity in the isolated network (regime B). The Coherent Stochastic Resonance phenomena occur. Activity is highly spatially correlated (synchrony), it’s oscillatory on short time scales and it decorrelates in time on long time scale (aperiodic). At zero noise the oscillatory activity vanishes in this regime. Changing parameters (for example increasing the excitatory-to-excitatory connection strength) we get spontaneous synchronous and periodic activity, even without noise (regime C). The model is in agreement with the measurements of spontaneous activity of two-dimensional cortical cell neural networks placed on multi-electrode arrays performed by Segev et.al [2]. More... »

PAGES

39-44

References to SciGraph publications

Book

TITLE

Artificial Neural Networks — ICANN 2002

ISBN

978-3-540-44074-1
978-3-540-46084-8

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-46084-5_7

DOI

http://dx.doi.org/10.1007/3-540-46084-5_7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1044111489


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