Moment neuronal networks: stochastic computation in neuronal systems

Jianfeng Feng; Yingchun Deng; Enrico Rossoni

doi:10.1117/12.725533

8 June 2007 Moment neuronal networks: stochastic computation in neuronal systems

Jianfeng Feng, Yingchun Deng, Enrico Rossoni

Proceedings Volume 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems; 66021E (2007) https://doi.org/10.1117/12.725533
Event: SPIE Fourth International Symposium on Fluctuations and Noise, 2007, Florence, Italy

Abstract

Spike trains recorded in cortical neurons in vivo can be approximated by renewal processes, but are generally not Poisson. Besides, the spiking activity of neighboring neurons display small yet not negligible correlations. The Artificial Neuronal Network theory has traditionally neglected such observations, assuming that neurons could simply be described by their mean firing rate. Here we present a theoretical framework in which the dynamics of a system of neurons is specified in terms of higher-order moments of their spiking activity beyond the mean firing rate.

Citation Download Citation

Jianfeng Feng, Yingchun Deng, and Enrico Rossoni "Moment neuronal networks: stochastic computation in neuronal systems", Proc. SPIE 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems, 66021E (8 June 2007); https://doi.org/10.1117/12.725533

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