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arXiv · 1001.0663

Self-organized chaos through polyhomeostatic optimization

Dimitrije Markovic·Claudius Gros
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Abstract

The goal of polyhomeostatic control is to achieve a certain target distribution of behaviors, in contrast to polyhomeostatic regulation which aims at stabilizing a steady-state dynamical state. We consider polyhomeostasis for individual and networks of firing-rate neurons, adapting to achieve target distributions of firing rates maximizing information entropy. We show that any finite polyhomeostatic adaption rate destroys all attractors in Hopfield-like network setups, leading to intermittently bursting behavior and self-organized chaos. The importance of polyhomeostasis to adapting behavior in general is discussed.

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Dimitrije Markovic, Claudius Gros. 2010-05-28. Self-organized chaos through polyhomeostatic optimization. https://doi.org/10.1103/physrevlett.105.068702

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