Competition between synaptic depression and facilitation in attractor neural networks.
Publication year
2007Source
Neural Computation, 19, 10, (2007), pp. 2739-55ISSN
Publication type
Article / Letter to editor
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Organization
Cognitive Neuroscience
Biophysics
Journal title
Neural Computation
Volume
vol. 19
Issue
iss. 10
Page start
p. 2739
Page end
p. 55
Subject
Biophysics; DCN 3: Neuroinformatics; UMCN 3.2: Cognitive neurosciencesAbstract
We study the effect of competition between short-term synaptic depression and facilitation on the dynamic properties of attractor neural networks, using Monte Carlo simulation and a mean-field analysis. Depending on the balance of depression, facilitation, and the underlying noise, the network displays different behaviors, including associative memory and switching of activity between different attractors. We conclude that synaptic facilitation enhances the attractor instability in a way that (1) intensifies the system adaptability to external stimuli, which is in agreement with experiments, and (2) favors the retrieval of information with less error during short time intervals.
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- Academic publications [238441]
- Electronic publications [122522]
- Faculty of Medical Sciences [90373]
- Faculty of Science [34986]
- Open Access publications [97517]
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