A Connectionist Model of Attentional Enhancement and Signal Buffering

Abstract

The connectionist/control simulation of attentional enhancement, signal maintenance, and buffering of information is described. The system implements a hybrid connectionist architecture incorporating auto-association in the hidden layer and gain control of the hidden and output layer. The structure of the model parallels major features of modular cortical structure. The attentional selection simulation show that as one channel is attenuated, the system exhibits attentional capture in which only the more intense stimulus is transmitted to higher levels. The signal maintenance simulations show that small levels of auto-associative feedback can faithfully maintain short bursts of input for extended periods of time. With high auto-associative feedback, one module can buffer information from a pervious transmission while the module blocks the interference resulting from concurrent transmissions. The combination of auto-associative feedback and gain control allow extensive control of information flow in a modular connectionist architecture. (kr)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1990
Accession Number
ADA225799

Entities

People

  • Judith Shedden
  • Walter Schneider

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Brain
  • Coding
  • Cognitive Science
  • Computer Science
  • Computer Vision
  • Computers
  • Identification
  • Neurons
  • Neurosciences
  • Notation
  • Parallel Computing
  • Parallel Processing
  • Psychology
  • Recognition
  • Simulations
  • Universities

Readers

  • Neural Network Machine Learning.
  • Neuroscience
  • Radio communications and signal processing.