8 June 2007 Moment neuronal networks: stochastic computation in neuronal systems
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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.
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Jianfeng Feng, Jianfeng Feng, Yingchun Deng, Yingchun Deng, Enrico Rossoni, 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); doi: 10.1117/12.725533; https://doi.org/10.1117/12.725533
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