A Study Program of Chaotic Dynamics Applied to Information Processing

Author(s):  
J. S. Nicolis
2004 ◽  
Vol 14 (02) ◽  
pp. 737-760 ◽  
Author(s):  
CARLOS LOURENÇO

We review a neural network model based on chaotic dynamics [Babloyantz & Lourenço, 1994, 1996] and provide a detailed discussion of its biological and computational relevance. Chaos can be viewed as a "reservoir" containing an infinite number of unstable periodic orbits. In our approach, the periodic orbits are used as coding devices. By considering a large enough number of them, one can in principle expand the information processing capacity of small or moderate-size networks. The system is most of the time in an undetermined state characterized by a chaotic attractor. Depending on the type of an external stimulus, the dynamics is stabilized into one of the available periodic orbits, and the system is then ready to process information. This corresponds to the system being driven into an "attentive" state. We show that, apart from static pattern processing, the model is capable of dealing with moving stimuli. We especially consider in this paper the case of transient visual stimuli, which has a clear biological relevance. The advantages of chaos over more regular regimes are discussed.


1986 ◽  
Vol 49 (10) ◽  
pp. 1109-1196 ◽  
Author(s):  
J S Nicolis

2016 ◽  
Vol 39 ◽  
Author(s):  
Giosuè Baggio ◽  
Carmelo M. Vicario

AbstractWe agree with Christiansen & Chater (C&C) that language processing and acquisition are tightly constrained by the limits of sensory and memory systems. However, the human brain supports a range of cognitive functions that mitigate the effects of information processing bottlenecks. The language system is partly organised around these moderating factors, not just around restrictions on storage and computation.


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