Direct Assessment of Synaptic Modification Rules

Abstract

We have spent considerable time reprogramming our computer programs for data acquisition and evaluation. This is an important effort since we were previously unable to study simultaneously the synaptic response and the cell discharge. This improvement has become particularly critical since the ongoing evaluation of data gathered last year shows strong support for the existence of two distinct adaptive processes. One process modifies the synaptic response, and another adaptive process modifies the conversion of synaptic current into cell firing. Note that this improvement in data gathering is an on-going task. We are continuing our study (i.e., data gathering and evaluation) of the quantitative manner in which asymptotic changes are induced independently at neighboring synapses. This study has at least two important implications. First, it corroborates our earlier claims that we are studying a process of individual synaptic modification. Second, it helps to establish the experimental conditions which allow us to distinguish a variety of adaptive modification processes. Finally, we have continued our theoretical work which considers various interpretations of the adaptive processes we have experimentally observed. The context of this interpretation now centers on optimally performing, adaptive pattern recognition systems. We are encouraged by the performance shown by multiplicative, recursive neural networks.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA217198

Entities

People

  • William B. Levy

Organizations

  • University of Virginia

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Adaptive Systems
  • Air Force
  • Application Software
  • Computer Programs
  • Computers
  • Conversion
  • Data Acquisition
  • Neural Networks
  • Pattern Recognition
  • Recognition
  • Security
  • Technicians
  • Test And Evaluation

Readers

  • Mathematical Modeling and Probability Theory.
  • Neuroscience
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks