Analysis and Synthesis of Adaptive Neural Elements and Assembles

Abstract

The overall objectives of this research were to analyze the properties of identified neurons and neural circuits in Aplysia that exhibit nonassociative and associative plasticity and to examine the role of neuronal plasticity in learning. Two interrelated approaches were used, one empirical and the other modeling. Between August 1, 1987 and September 30, 1990, progress was made in six areas. First, experiments examined the modulation of membrane currents and critical second messengers that contribute to neuronal plasticity in the sensory neurons that mediate nonassociative learning and classical conditioning of the tail withdrawal reflex. Second, mathematical formalisms of the cellular processes that underlie plasticity in sensory neurons were developed and incorporated into a real-time model of a neuron-like adaptive element. This single-cell model demonstrated the ability to simulate features of nonassociative learning and classical conditioning. Third, this single-cell model was incorporated into small neural networks that simulated some higher-order features of classical conditioning. Fourth, a form of the single cell model was incorporated into a small pattern generating neural network that simulated features of operant conditioning. Fifth, a Hodgkin-Huxley type of model of biophysical and cellular processes underlying rhythmic bursting patterns of activity in the neuron R15 was developed. Sixth, experiments have identified neurons that are elements of the central pattern generator that controls feeding behavior and that may mediate operant conditioning behavior.

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Document Details

Document Type
Technical Report
Publication Date
Dec 12, 1990
Accession Number
ADA231569

Entities

People

  • John H. Byrne

Organizations

  • McGovern Medical School

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Analogs
  • Artificial Intelligence
  • Cells
  • Computational Neuroscience
  • Computational Science
  • Computers
  • Generators
  • Human Behavior
  • Mathematical Models
  • Medical Personnel
  • Nerve Net
  • Nervous System
  • Neural Networks
  • Neurons
  • Neurosciences
  • Plastic Properties
  • Simulations

Fields of Study

  • Biology
  • Psychology

Readers

  • Computational Modeling and Simulation
  • Neuroscience

Technology Areas

  • AI & ML
  • Biotechnology