STATISTICAL MECHANICS OF NEURAL NETWORKS,

Abstract

A mathematical model is developed of the activity of networks of model nerve-cells or neurons. A nonlinear delay operator is introduced to represent the transfer characteristics of neurons. This operator is a continuous function that represents the mean neuronal response to stimulating currents. The mathematics used is not the Boolean algebra of switching circuits, but Differential equations. The dynamics is examined of certain model brain circuits, some of which are shown to exhibit undamped responses to stimuli, but only for a few levels of activity. The techniques of Hamiltonian mechanics and of Gibbsian statistical mechanics are used to connect these models with experimental data. A preliminary explanation is given for the existence of preferred states found in the firing patterns of neurons in animal nervous systems. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1967
Accession Number
AD0658886

Entities

People

  • Jack D. Cowan

Organizations

  • University of Chicago

Tags

DTIC Thesaurus Topics

  • Boolean Algebra
  • Differential Equations
  • Equations
  • Experimental Data
  • Mathematical Models
  • Mathematics
  • Mechanics
  • Models
  • Nervous System
  • Neural Networks
  • Neurons
  • Probabilistic Models
  • Statistical Mechanics
  • Switching
  • Switching Circuits

Fields of Study

  • Biology
  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Neuroscience
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference