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Lookup NU author(s): Dr Peter Andras
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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.
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
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