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Neurocomputing
Volumes 32-33, June 2000, Pages 365-370
 
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doi:10.1016/S0925-2312(00)00187-9    
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Copyright © 2000 Elsevier Science B.V. All rights reserved.

Chaos in neural networks with dynamic synapses

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Gideon [Reference to Dror]Corresponding Author Contact Information, E-mail The Corresponding Author, a and Misha [Reference to Tsodyks]b

a Department of Computer Science, The Academic College of Tel-Aviv-Yaffo, 4 Antokosky St., Tel-Aviv 64044, Israel

b Department of Neurobiology, Weizmann Institute, Rehovot 76100, Israel


Accepted 11 January 2000.
Available online 13 June 2000.

Abstract

We investigated the activity of localized excitatory and inhibitory populations coupled by dynamic synapses. Using numerical simulations, we analyzed the Liapunov exponents as well as fractal dimension of the network for various sets of parameters in order to find regimes of periodic and chaotic behavior. We found that chaotic behavior usually develops when external inputs are near threshold, and that chaos develops through a series of period doublings. It is robust and stable over considerable volume in parameter space. Within chaotic regimes intermittent behavior is exhibited. We investigated the average behavior of the network and shown that the response of the network is approximately linear to the excitatory input across various dynamical regimes.

Author Keywords: Dynamical synapses; Recurrent network; Population dynamics; Chaos; Period doubling

Corresponding Author Contact Information Corresponding author; email: gideon@server.mta.ac.il


Neurocomputing
Volumes 32-33, June 2000, Pages 365-370
 
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