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Phys Rev Lett. 2009 Jun 26;102(25):258102. Epub 2009 Jun 22.

Self-tuned critical anti-Hebbian networks.

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Laboratory of Mathematical Physics, Rockefeller University, 1230 York Avenue, New York, New York 10065, USA.


It is widely recognized that balancing excitation and inhibition is important in the nervous system. When such a balance is sought by global strategies, few modes remain poised close to instability, and all other modes are strongly stable. Here we present a simple abstract model in which this balance is sought locally by units following "anti-Hebbian" evolution: all degrees of freedom achieve a close balance of excitation and inhibition and become "critical" in the dynamical sense. At long time scales, a complex "breakout" dynamics ensues in which different modes of the system oscillate between prominence and extinction; the model develops various long-tailed statistical behaviors and may become self-organized critical.

[Indexed for MEDLINE]

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