Correlations of cortical Hebbian reverberations: theory versus experiment.

Published

Journal Article

Interpreting recent single-unit recordings of delay activities in delayed match-to-sample experiments in anterior ventral temporal (AVT) cortex of monkeys in terms of reverberation dynamics, we present a model neural network of quasi-realistic elements that reproduces the empirical results in great detail. Information about the contiguity of successive stimuli in the training sequence, representing the fact that training is done on a set of uncorrelated stimuli presented in a fixed temporal sequence, is embedded in the synaptic structure. The model reproduces quite accurately the correlations between delay activity distributions corresponding to stimulation with the uncorrelated stimuli used for training. It reproduces also the activity distributions of spike rates on sample cells as a function of the stimulating pattern. It is, in our view, the first time that a computational phenomenon, represented on the neurophysiological level, is reproduced in all its quantitative aspects. The model is then used to make predictions about further features of the physiology of such experiments. Those include further properties of the correlations, features of selective cells as discriminators of stimuli provoking different delay activity distributions, and activity distributions among the neurons in a delay activity produced by a given pattern. The model has predictive implications also for the dependence of the delay activities on different training protocols. Finally, we discuss the perspectives of the interplay between such models and neurophysiology as well as its limitations and possible extensions.

Full Text

Duke Authors

Cited Authors

  • Amit, DJ; Brunel, N; Tsodyks, MV

Published Date

  • November 1994

Published In

Volume / Issue

  • 14 / 11 Pt 1

Start / End Page

  • 6435 - 6445

PubMed ID

  • 7965048

Pubmed Central ID

  • 7965048

International Standard Serial Number (ISSN)

  • 0270-6474

Language

  • eng

Conference Location

  • United States