Optimal stimulus coding by neural populations using rate codes.

Don H Johnson; Will Ray

doi:10.1023/b:jcns.0000014106.09948.83

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Optimal stimulus coding by neural populations using rate codes.

Don H Johnson·Will Ray

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Abstract

We create a framework based on Fisher information for determining the most effective population coding scheme for representing a continuous-valued stimulus attribute over its entire range. Using this scheme, we derive optimal single- and multi-neuron rate codes for homogeneous populations using several statistical models frequently used to describe neural data. We show that each neuron's discharge rate should increase quadratically with the stimulus and that statistically independent neural outputs provides optimal coding. Only cooperative populations can achieve this condition in an informationally effective way.

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Action Potentials Animals Electrophysiology Forms and Records Control Information Theory Models, Neurological Neural Networks, Computer Neural Pathways Neurons Population Comparative Study Journal Article Research Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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Don H Johnson, Will Ray. Optimal stimulus coding by neural populations using rate codes.. https://doi.org/10.1023/b%3Ajcns.0000014106.09948.83

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