Non-Boltzmann Dynamics in Networks of Spiking Neurons

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We study networks of spiking neurons in which spikes are fired as a Poisson process. The state of a cell is determined by the instantaneous firing rate, and in the limit of high firing rates our model reduces to that studied by Hopfield. We find that the inclusion of spiking results in several new features, such as a noise-induced asymmetry between "on" and "off" states of the cells and probability currents which destroy the usual description of network dynamics in terms of energy surfaces. Taking account of spikes also allows us to calibrate network parameters such as "synaptic weights" against experiments on real synapses. Realistic forms of the post synaptic response alters the network dynamics, which suggests a novel dynamical learning mechanism.

Original languageEnglish (US)
Title of host publicationAdvances in Neural Information Processing Systems 2, NIPS 1989
EditorsDavid S. Touretzky
PublisherNeural information processing systems foundation
Pages109-116
Number of pages8
ISBN (Electronic)1558601007, 9781558601000
StatePublished - 1989
Event2nd Advances in Neural Information Processing Systems, NIPS 1989 - Denver, United States
Duration: Nov 27 1989Nov 30 1989

Publication series

NameAdvances in Neural Information Processing Systems
Volume2
ISSN (Print)1049-5258

Conference

Conference2nd Advances in Neural Information Processing Systems, NIPS 1989
Country/TerritoryUnited States
CityDenver
Period11/27/8911/30/89

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Computer Networks and Communications

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