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  Critical dynamics in associative memory networks

Uhlig, M., Levina, A., Geisel, T., & Herrmann, J. M. (2013). Critical dynamics in associative memory networks. Frontiers in Computational Neuroscience, 7: 87. doi:10.3389/fncom.2013.00087.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0029-0FBD-E Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0029-0FBE-C
Genre: Journal Article

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 Creators:
Uhlig, Maximilian1, Author              
Levina, Anna1, Author              
Geisel, Theo1, Author              
Herrmann, J. Michael1, Author              
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1Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063286              

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 Abstract: Critical behavior in neural networks is characterized by scale-free avalanche size distributions and can be explained by self-regulatory mechanisms. Theoretical and experimental evidence indicates that information storage capacity reaches its maximum in the critical regime. We study the effect of structural connectivity formed by Hebbian learning on the criticality of network dynamics. The network endowed with Hebbian learning only does not allow for simultaneous information storage and criticality. However, the critical regime is can be stabilized by short-term synaptic dynamics in the form of synaptic depression and facilitation or, alternatively, by homeostatic adaptation of the synaptic weights. We show that a heterogeneous distribution of maximal synaptic strengths does not preclude criticality if the Hebbian learning is alternated with periods of critical dynamics recovery. We discuss the relevance of these findings for the flexibility of memory in aging and with respect to the recent theory of synaptic plasticity.

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Language(s): eng - English
 Dates: 2013-07-24
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: eDoc: 673700
DOI: 10.3389/fncom.2013.00087
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Title: Frontiers in Computational Neuroscience
Source Genre: Journal
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Pages: - Volume / Issue: 7 Sequence Number: 87 Start / End Page: - Identifier: -