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Optical Memory and Neural Networks : Volume 19, Issue 1, March 2010

Optical Memory and Neural Networks : Volume 18

Optical Memory and Neural Networks : Volume 17

Optical Memory and Neural Networks : Volume 16

Modified firing-rate model reproduces synchronization of a neuronal population receiving complex input

Content Provider	Springer Nature Link
Author	Buchin, A. Ju. Chizhov, A. V.
Copyright Year	2010
Abstract	Synchronization plays important role in generation of brain activity patterns. Experimental data show that neurons demonstrate more reproducible activity for noise-like input than for constant current injection, and that effect can not be reproduced by standard oversimplified Firing-Rate (FR) models. The paper proposes a modification of FR model which reproduces these kinds of activity. The FR model approximates the firing rate of an infinite number of leaky integrate-and-fire neurons, considered as a population, and in contrary to conventional models it accounts for not only a steady-state firing regime but a fast rising excitation as well. Comparison of our simulations with the experimental data shows that the synchronous firing of the neuronal population strongly depends on the synchrony of neuronal states just before spiking. This effect is reproduced by the proposed FR model in contrary to the conventional FR models and is in agreement with the direct Monte-Carlo simulation of individual neurons.
Starting Page	166
Ending Page	171
Page Count	6
File Format	PDF
ISSN	1060992X
Journal	Optical Memory and Neural Networks
Volume Number	19
Issue Number	2
e-ISSN	19347898
Language	English
Publisher	Allerton Press, Inc.
Publisher Date	2010-07-10
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	integrate-and-fire neurons firing-rate model synchronization noise Complexity Information Storage and Retrieval
Content Type	Text
Resource Type	Article
Subject	Computer Science Electronic, Optical and Magnetic Materials Electrical and Electronic Engineering

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