Title
Stability of asynchronous firing states in networks with synaptic adaptation Stability of asynchronous firing states in networks with synaptic adaptation
Author
Publication type
article
Publication
Amsterdam :Elsevier science bv ,
Subject
Computer. Automation
Source (journal)
Neurocomputing: an international journal. - Amsterdam
Source (book)
9th Annual Computational Neuroscience Meeting (CNS*00), JUL, 2000, BRUGGE, BELGIUM
Volume/pages
38(2001) , p. 915-920
ISSN
0925-2312
ISI
000169129200122
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Abstract
We construct a mean field theory for low-rate asynchronous firing states in networks consisting of excitatory and inhibitory populations of integrate-and-fire neurons with synaptic depression or facilitation. The theory is exact when each neuron receives input from K randomly chosen ones, with 1 much less than K much less than N, where N is the total number of neurons. Changes in firing rates produce changes in synaptic strengths and vice-versa, potentially leading to instabilities. We prove that depression of synapses within a population (excitatory or inhibitory) always tends to stabilize the asynchronous state against such fluctuations, while depression acting between populations destabilizes it. Facilitation has the opposite effect. (C) 2001 Elsevier Science B.V. All rights reserved.
E-info
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