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Science 25 March 1988:
Vol. 239. no. 4847, pp. 1513 - 1520
DOI: 10.1126/science.3281253
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Articles

Science, Vol 239, Issue 4847, 1513-1520
Copyright © 1988 by American Association for the Advancement of Science

articles

Dynamic pattern generation in behavioral and neural systems

G Schoner and JA Kelso

Center for Complex Systems, Florida Atlantic University, Boca Raton 33431.

In the search for principles of pattern generation in complex biological systems, an operational approach is presented that embraces both theory and experiment. The central mathematical concepts of self-organization in nonequilibrium systems (including order parameter dynamics, stability, fluctuations, and time scales) are used to show how a large number of empirically observed features of temporal patterns can be mapped onto simple low-dimensional (stochastic, nonlinear) dynamical laws that are derivable from lower levels of description. The theoretical framework provides a language and a strategy, accompanied by new observables, that may afford an understanding of dynamic patterns at several scales of analysis (including behavioral patterns, neural networks, and individual neurons) and the linkage among them.


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