Self-Organization of Hebbian Synapses on Hippocampal Neurons.

Abstract

To reverse-engineer the learning machinery of the brain it is necessary to determine the computations performed by biological neurons and neural circuits and to implement these on a fast platform. This requires defining the device characteristics of the individual neurons and the mechanisms of use-dependent synaptic plasticity. The research has produced numerous publications and abstracts plus presentations at several meetings. There have been major technical, theoretical, and experimental break-throughs. The new technology will result in commercia1 developments and significant scientific advances. Transitions to industry have been numerous. The near-term objective of this original proposal was to create models of the key types of hippocampal neurons and be able to implement these on a sufficiently fast platform that we could extract some of their key features.

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Document Details

Document Type
Technical Report
Publication Date
Sep 07, 1995
Accession Number
ADA299559

Entities

People

  • Thomas H. Brown

Organizations

  • Yale University

Tags

DTIC Thesaurus Topics

  • Brain
  • Circuits
  • Computations
  • Confocal Laser Scanning Microscopy
  • Confocal Microscopy
  • Information Processing
  • Information Systems
  • Learning
  • Microscopy
  • Neural Networks
  • Neurons
  • Plastic Properties
  • Psychology
  • Self Organizing Systems
  • Simulations
  • Technology Transfer

Readers

  • Neural Network Machine Learning.
  • Systems Analysis and Design