Coupled Oscillating Neurons (Perspectives in Neural Computing) - Softcover

Taylor, J.G.

 
9783540197447: Coupled Oscillating Neurons (Perspectives in Neural Computing)

Inhaltsangabe

This volume contains the proceedings of a day conference on coupled neuronal oscillators (CNO '90, London), an important aspect of neural network research, which may hold the key to a clearer appreciation of the manner in which neural networks can control complex behaviour. The contributors to the conference looked at the physiological properties of neurons in terms of electrochemical features, using these to consider possible directions for future research. The papers cover a range of areas, including an introduction to non-linear oscillators, bifurcating neurons, the modelling of cardiac rhythm, gamma oscillations, association and consciousness, and a model for low threshold oscillations in neurons. The papers also include new explanations and models of the phenomena of coupled oscillatory neural assemblies, ranging from those for the multi-phasic response of single neurons, to possible models of image segmentation.

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Reseña del editor

This volume consists of proceedings of the one-day conference on "Coupled Oscillating Neurons" held at King's College, London on December 13th, 1990. The subject is currently of increasing interest to neurophysiologists, neural network researchers, applied mathematicians and physicists. The papers attempt to cover the major areas of the subject, as the titles indicate. It is hoped that the appearance of the papers (some of which have been updated since their original presentation) indicates why the subject is becoming of great excitement. A better understanding of coupled oscillating neurons may well hold the key to a clearer appreciation of the manner in which neural networks composed of such elements can control complex behaviour from the heart to consciousness. December 1991 J.G. Taylor King's College, London C.L.T. Mannion CONTENTS Contributors....... ..................... .......... .......................... .................... ix Introduction to Nonlinear Oscillators I. Stewart ....................................................................................... . Identical Oscillator Networks with Symmetry P.B. Ashwin .................................................................................... 21 Bifurcating Neurones AV. Holden, J. Hyde, M.A Muhamad, H.G. Zhang....................... 41 A Model for Low Threshold Oscillations in Neurons J.L. Hindmarsh, R.M. Rose ............................................................ 81 Information Processing by Oscillating Neurons C.L. T. Mannion, J.G. Taylor ........................................................... 100 Gamma Oscillations, Association and Consciousness R.M.J. Cotterill, C. Nielsen ............................................................. 117 Modelling of Cardiac Rhythm: From Single Celis to Massive Networks D. Noble, J. C. Denyer, H.F. Brown, R. Winslow, A Kimball .......... 1 32 CONTRIBUTORS Ashwin, P.B. Mathematics Institute, University of Warwick, Coventry, CV4 7 AL, UK Brown, H.F.

Reseña del editor

This volume contains the proceedings of a day conference on coupled neuronal oscillators (CNO '90, London), an important aspect of neural network research, which may hold the key to a clearer appreciation of the manner in which neural networks can control complex behaviour. The contributors to the conference looked at the physiological properties of neurons in terms of electrochemical features, using these to consider possible directions for future research. The papers cover a range of areas, including an introduction to non-linear oscillators, bifurcating neurons, the modelling of cardiac rhythm, gamma oscillations, association and consciousness, and a model for low threshold oscillations in neurons. The papers also include new explanations and models of the phenomena of coupled oscillatory neural assemblies, ranging from those for the multi-phasic response of single neurons, to possible models of image segmentation.

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ISBN 10:  0387197443 ISBN 13:  9780387197449
Softcover