DocumentCode :
540200
Title :
Analogies of brain function in neural network models
Author :
Mpitsos, G.J. ; Burton, R.M. ; Hatfield, M.O.
fYear :
1990
fDate :
17-21 June 1990
Firstpage :
181
Abstract :
This research arises from studies into several interrelated experimental questions into adaptive multicomponent systems, namely: given that information is distributed among many individuals within groups, (a) how does globally coherent activity arise, (b) how do individuals influence the functioning of the group, and, in turn (c) how does the group influence the responses of the individuals? These questions are examined in the nervous systems of simple invertebrate animals, such as the sea slug Pleurobranchaea californica. The goal is, as indicated by the scale-independence of the questions themselves, to identify dynamical principles that apply to adaptive systems generally, systems composed of molecules, cells, or even societies of organisms. It is proposed that variation constitutes one such principle. Variations may arise by a variety of mechanisms. Two variations that are discussed are low-dimensional deterministic ones, such as chaos, and nondeterministic ones, such as Gaussian noise
Keywords :
biocybernetics; brain models; neural nets; Gaussian noise; adaptive multicomponent systems; brain function; cells; chaos; invertebrate animals; molecules; nervous systems; neural network models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1990., 1990 IJCNN International Joint Conference on
Conference_Location :
San Diego, CA, USA
Type :
conf
DOI :
10.1109/IJCNN.1990.137565
Filename :
5726526
Link To Document :
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