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An advantage of chaotic neural dynamics

Lookup NU author(s): Dr Peter Andras

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Abstract

One hypothesis about how biological neural systems work suggests that they use attractor dynamics to define their behaviour. Such behaviour can be modelled using recurrent neural network models. It has been shown that such systems can perform a wide range of computational tasks by learning abstract grammars. Here we show that chaotic neural dynamics in recurrent neural systems is advantageous in the sense that it facilitates the encoding of grammars describing complex behaviour. This result may explain why it is common the observation of chaotic dynamics in biological neural systems.

Publication metadata

Author(s): Andras P, Lycett S

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the International Joint Conference on Neural Networks (IJCNN)

Year of Conference: 2007

Pages: 1417-1422

ISSN: 1098-7576

Publisher: IEEE

URL: http://dx.doi.org/10.1109/IJCNN.2007.4371166

DOI: 10.1109/IJCNN.2007.4371166

Library holdings: Search Newcastle University Library for this item

ISBN: 9781424413805

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