Information Extraction from Visual Displays and the Event-Related Brain Potential

Abstract

Three experiments, of increasing levels of complexity, are reported which examine two questions: (1) Will subjects extract more information from progressively more information stimuli in a probabilistic state-estimation task, as inferred from reaction time measures? (2) Will the amplitude of the P300 component of the event-related brain potential, reflect the amount of information extracted? The three experiments used different versions of a process monitoring task in which the process could be in one of two states, and information bearing on the expectancy of one state or the other was conveyed by discrete informative cues. Occasional probes signalled imperative responses to the expected or unexpected states. The data indicated that in the simplest version of the task with only two levels of information value (Experiment 1), both questions were answered affirmatively. Keywords: Displays, Decision heuristics, Attention, Event-related potentials, Information integration, Medicine.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1990
Accession Number
ADA227063

Entities

People

  • Amir Mane
  • Arthur Kramer
  • Carla Bosco
  • Christopher Dow Wickens
  • Emanual Donchin
  • Michael Coles

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Amplitude
  • Analysis Of Variance
  • Business Administration
  • Data Science
  • Databases
  • Information Processing
  • Information Science
  • Monitoring
  • Psychology
  • Psychophysiology
  • Reaction Time
  • Reliability
  • Social Sciences
  • Statistical Analysis
  • Test And Evaluation

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval