On a Gaussian neuronal field model
Lu, Wenlian, Rossoni, Enrico and Feng, Jianfeng. (2010) On a Gaussian neuronal field model. NeuroImage, Vol.52 (No.3). pp. 913-933. ISSN 1053-8119Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.neuroimage.2010.02.075
Can we understand the dynamic behaviour of leaky integrate-and-fire (LIF) networks, which present the major, and possibly the only, analytically tractable tool we employ in computational neuroscience? To answer this question, here we present a theoretical framework on the spike activities of LIF networks by including the first order moment (mean firing rate) and the second order moment statistics (variance and correlation), based on a moment neuronal network (MNN) approach. The spike activity of a LIF network is approximated as a Gaussian random field and can reduce to the classical Wilson-Cowan-Amari (WCA) neural field if the variances vanish. Our analyses reveal several interesting phenomena of LIF networks. With a small clamped correlation and strong inhibition, the firing rate response function could be non-monotonic (not sigmoidal type), which can lead to interesting dynamics. For a feedforward and recurrent neuronal network, our setup allows us to prove that all neuronal spike activities rapidly synchronize, a well-known fact observed in both experiments and numerical simulations. We also present several examples of wave propagations in this field model. Finally, we test our MNN with the content-dependent working memory setting. The potential application of this random neuronal field idea to account for many experimental data is also discussed. (C) 2010 Elsevier Inc. All rights reserved.
|Item Type:||Journal Article|
|Subjects:||R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
|Divisions:||Faculty of Science > Centre for Scientific Computing
Faculty of Science > Computer Science
|Journal or Publication Title:||NeuroImage|
|Official Date:||September 2010|
|Number of Pages:||21|
|Page Range:||pp. 913-933|
|Access rights to Published version:||Restricted or Subscription Access|
|Funder:||National Natural Sciences Foundation of China, Shanghai Pujiang Program, Engineering and Physical Sciences Research Council (EPSRC), European Commission|
|Grant number:||60804044, 08PJ14019, 213219|
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