Transient Information Flow in a Network of Excitatory and Inhibitory Model Neurons: Role of Noise and Signal Autocorrelation

dc.creatorMayor, Julien
dc.creatorGerstner, Wulfram
dc.date2005-02-23
dc.date.accessioned2026-07-07T05:58:56Z
dc.date.available2026-07-07T05:58:56Z
dc.descriptionWe investigate the performance of sparsely-connected networks of integrate-and-fire neurons for ultra-short term information processing. We exploit the fact that the population activity of networks with balanced excitation and inhibition can switch from an oscillatory firing regime to a state of asynchronous irregular firing or quiescence depending on the rate of external background spikes. We find that in terms of information buffering the network performs best for a moderate, non-zero, amount of noise. Analogous to the phenomenon of stochastic resonance the performance decreases for higher and lower noise levels. The optimal amount of noise corresponds to the transition zone between a quiescent state and a regime of stochastic dynamics. This provides a potential explanation on the role of non-oscillatory population activity in a simplified model of cortical micro-circuits.
dc.description27 pages, 7 figures, to appear in J. Physiology (Paris) Vol. 98
dc.identifierhttps://arxiv.org/abs/q-bio/0502030
dc.identifierhttp://arxiv.org/abs/q-bio/0502030
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/88549
dc.subjectNeurons and Cognition
dc.titleTransient Information Flow in a Network of Excitatory and Inhibitory Model Neurons: Role of Noise and Signal Autocorrelation
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