Theory for the Development of Neuron Selectivity: Orientation Specificity and Binocular Interaction in Visual Cortex.

Abstract

Development of stimulus selectivity in primary sensory cortex of higher vertebrates is considered in a general mathematical framework. A synaptic evolution scheme of a new kind is proposed in which incoming patterns rather than converging afferents compete. The change in efficacy of a given synapse depends not only on instantaneous pre and postsynaptic activities but also on a slowly varying time-averaged value of the postsynaptic activity. Assuming an appropriate nonlinear form for this dependence, development of selectivity is obtained under quite general conditions on the sensory environment. One does not require nonlinearity of the neuron's integrative power nor does one need to assume any particular form for intracortical circuitry. This is illustrated in simple cases, e.g. when the environment consists of only two different stimuli presented alternately in a random manner. The following formal statement then holds: the state of the system converges with probability 1 to points of maximum selectivity in the state space. We next consider the problem of early development of orientation selectivity and binocular interaction in primary visual cortex. Giving the environment an appropriate form, we obtain orientation tuning curves and ocular dominance comparable to what is observed in normally reared adult cats or monkeys. Simulations with binocular input and various types of normal or altered environments show good agreement with relevant experimental data.

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Document Details

Document Type
Technical Report
Publication Date
Jun 05, 1981
Accession Number
ADA099982

Entities

People

  • Elie L. Bienenstock
  • Leon Cooper
  • Paul W. Munro

Organizations

  • Brown University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Brain
  • Classification
  • Computational Science
  • Differential Equations
  • Equations
  • Experimental Data
  • Geometry
  • Mathematical Analysis
  • Neurons
  • New York
  • Numerical Analysis
  • Plastic Properties
  • Probability
  • Random Variables
  • Stationary Processes
  • Stochastic Processes
  • Theorems

Fields of Study

  • Biology

Readers

  • Calculus or Mathematical Analysis
  • Human-Computer Interaction (HCI).
  • Neuroscience

Technology Areas

  • Space