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Complementarity of spike- and rate-based dynamics of neural systems
Complementarity of spike- and rate-based dynamics of neural systems
Abstract
Relationships between spiking-neuron and rate-based approaches to the dynamics of neural assemblies are explored by analyzing a model system that can be treated by both methods, with the rate-based method further averaged over multiple neurons to give a neural-field approach. The system consists of a chain of neurons, each with simple spiking dynamics that has a known rate-based equivalent. The neurons are linked by propagating activity that is described in terms of a spatial interaction strength with temporal delays that reflect distances between neurons; feedback via a separate delay loop is also included because such loops also exist in real brains. These interactions are described using a spatiotemporal coupling function that can carry either spikes or rates to provide coupling between neurons. Numerical simulation of corresponding spike- and rate-based methods with these compatible couplings then allows direct comparison between the dynamics arising from these approaches. The rate-based dynamics can reproduce two different forms of oscillation that are present in the spike-based model: spiking rates of individual neurons and network-induced modulations of spiking rate that occur if network interactions are sufficiently strong. Depending on conditions either mode of oscillation can dominate the spike-based dynamics and in some situations, particularly when the ratio of the frequencies of these two modes is integer or half-integer, the two can both be present and interact with each other.
Type
Journal Article
Type of thesis
Series
Citation
Wilson, M. T., Robinson, P. A., O Neill, B., & Steyn-Ross, D. A. (2012). Complementarity of spike- and rate-based dynamics of neural systems. (V. K. Jirsa, Ed.) PLoS Computational Biology, 8(6), e1002560.
Date
2012
Publisher
Public Library of Science
Degree
Supervisors
Rights
© 2012 Wilson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are redited.