A new type of self-organization associated with chaotic dynamics in neural networks

International Journal of Neural Systems
I Tsuda

Abstract

A new type of self-organized dynamics is presented, in relation with chaos in neural networks. One is chaotic itinerancy and the other is chaos-driven contraction dynamics. The former is addressed as a universal behavior in high-dimensional dynamical systems. In particular, it can be viewed as one possible form of memory dynamics in brain. The latter gives rise to singular-continuous nowhere-differentiable attractors. These dynamics can be related to each other in the context of dimensionality and of chaotic information processings. Possible roles of these complex dynamics in brain are also discussed.

Citations

Sep 17, 2010·Bulletin of Mathematical Biology·Minoru Tsukada, Yasuhiro Fukushima
Dec 26, 2003·Comptes rendus biologies·Henri Korn, Philippe Faure
Dec 16, 2003·Neural Networks : the Official Journal of the International Neural Network Society·Iku Nemoto, Kei Saito
Mar 29, 2003·Neural Networks : the Official Journal of the International Neural Network Society·Ichiro Tsuda, Akihiro Yamaguchi
Feb 13, 2001·Journal of Physiology, Paris·W J Freeman
Mar 11, 2004·Journal of Integrative Neuroscience·Peter Andras
Jan 23, 2010·Neural Networks : the Official Journal of the International Neural Network Society·Magnus Jändel
Nov 3, 2001·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·J K RyeuI Tsuda
Aug 10, 2021·Cognitive Neurodynamics·Yasuhiro FukushimaMinoru Tsukada

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