Transient information flow in a network of excitatory and inhibitory model neurons: role of noise and signal autocorrelation

• Published in: Journal of Physiology (Paris), vol. 98, num. 4-6, p. 417-428
• Publication date: 2004

We 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 of the role of non-oscillatory population activity in a simplified model of cortical micro-circuits.

Note: article

Keywords: Recurrent integrate-and-fire neuron networks ; Sparse connectivity ; Population dynamics ; Information processing

Reference

• LCN-ARTICLE-2004-004
• doi:10.1016/j.jphysparis.2005.09.009
• View record in Web of Science

Record created on 2006-12-12, modified on 2012-03-21