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 toMassive 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.

Inhalt
to Nonlinear Oscillators.- Identical Oscillator Networks with Symmetry.- Bifurcating Neurones.- A Model for Low Threshold Oscillations in Neurons.- Information Processing by Oscillating Neurons.- Gamma Oscillations, Association and Consciousness.- Modelling of Cardiac Rhythm: From Single Cells to Massive Networks.