Identification of Variables Determining Intrahemispheric Interference between Processing Demands

Abstract

This research note describes basic research aimed at understanding principles of brain hemisphere functioning which can be used to improve human performance. The research is most relevant for understanding performance based on visual information perceived by peripheral vision, and examines how intrahemispheric interference affects performance degradation when two task-related activities depend on the same hemisphere of the brain. It was found that even in apparently simple tasks, small changes increasing or decreasing the difficulty of cognitive decision making are very powerful in determining how interactions within hemispheres will affect performance. When intrahemispheric interference occurred, changes in response requirements simplifying the decisional processes necessary to organize the response served to reduce interference. Effects of intrahemispheric interference may reduce performance based on stimuli in a particular location, or reduce it by one hand relative to the other. There are individual differences in the magnitude of intrahemispheric interference and its effects degrading performance as well. Keywords: Experimental psychology, Cerebral hemisphere, Machine learning, Neuropsychology, Visual, Reaction time, Pilots, Man machine systems.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1989
Accession Number
ADA208435

Entities

People

  • Joanne Greene

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Classification
  • Cognitive Workload
  • Data Analysis
  • Data Displays
  • Data Science
  • Detection
  • Experimental Design
  • Human Factors Engineering
  • Information Processing
  • Information Science
  • Motor Skills
  • Peripheral Vision
  • Plastic Explosives
  • Psychology
  • Psychophysiology

Fields of Study

  • Psychology

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Neuroscience
  • Systems Analysis and Design

Technology Areas

  • AI & ML