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Temporal Processing in Brain Activity

  • Conference paper
Neural Network Dynamics

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

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Abstract

A framework is presented in terms of which models of temporal sequence storage, attention, consciousness and self-consciousness are given. The framework incorporates various features of neurons — stochasticity, short, and long-term temporal processes — together with simple forms of net architecture.

The sequence storage uses topographic or coupled feedback networks and local learning rules, and leads to context sensitivity. The attention and consciousness modelling is at systems level, and uses various known cortical and sub-cortical structures involved in the subject as well as new results from magnetoencephalography. The models are related to a relational automata approach to consciousness and to plant modelling in control theory.

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Authors and Affiliations

  1. Centre for Neural Networks, Department of Mathematics, King’s College London, London, UK

    J. G. Taylor

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  1. J. G. Taylor
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Editors and Affiliations

  1. Centre for Neural Networks, Department of Mathematics, King’s College, Strand, London, WC2R 2LS, UK

    J. G. Taylor BA, BSc, MA, PhD, FlnstP (Director) (Director)

  2. Dipartimento di Fisica Teorica, Università di Salerno, Via S. Allende, 84081, Baronissi (SA), Italy

    E. R. Caianiello

  3. Department of Biophysics, The Technical University of Denmark, Building 307, DK-2800, Lyngby, Denmark

    R. M. J. Cotterill BSc, MS, PhD, DSc, FlnstP, C.Phys.

  4. Department of Physics, Washington University, St Louis, Missouri, 63130, USA

    J. W. Clark

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© 1992 Springer-Verlag London Limited

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Taylor, J.G. (1992). Temporal Processing in Brain Activity. In: Taylor, J.G., Caianiello, E.R., Cotterill, R.M.J., Clark, J.W. (eds) Neural Network Dynamics. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-2001-8_19

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  • DOI: https://doi.org/10.1007/978-1-4471-2001-8_19

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19771-3

  • Online ISBN: 978-1-4471-2001-8

  • eBook Packages: Springer Book Archive

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