Noise Shaping in Neural Populations with Global Delayed Feedback

Issue		Math. Model. Nat. Phenom. Volume 5, Number 2, 2010 Mathematics and neuroscience


Page(s)		100 - 124
DOI		10.1051/mmnp/20105204
Published online		10 March 2010

Math. Model. Nat. Phenom. Vol. 5, No. 2, 2010, pp. 100-124

Noise Shaping in Neural Populations with Global Delayed Feedback

O. Ávila Åkerberg¹ and M. J. Chacron¹^,2^*

¹ Department of Physics, McGill University, Montreal, H3G 1Y6, Canada
² Department of Physiology, McGill University, Montreal , H3G 1Y6, Canada

^* Corresponding author. E-mail: maurice.chacron@mcgill.ca

Abstract

The interplay between intrinsic and network dynamics has been the focus of many investigations. Here we use a combination of theoretical and numerical approaches to study the effects of delayed global feedback on the information transmission properties of neural networks. Specifically, we compare networks of neurons that display intrinsic interspike interval correlations (nonrenewal) to networks that do not (renewal). We find that excitatory and inhibitory delays can tune information transmission by single neurons but not by the entire network. Most surprisingly, addition of a delay can change the dependence of the information on the coupling strength for renewal neurons and not for nonrenewal neurons. Our results show that intrinsic ISI correlations can have nontrivial interactions with network-induced phenomena.

Mathematics Subject Classification: 68P30 / 92B20 / 34K50

Key words: information theory / neural networks / nonrenewal / delay

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