Miniature Brain Decision Making in Complex Visual Environments

Abstract

The grantee investigated, using the honeybee (Apis mellifera) as a model, how decisions are learnt in complex visual environments. In particular, the grantee investigated the problem of face invariance to understand the role that experience with stimuli can play in permitting a brain to learn how to reliably recognize target stimuli independent of factors including angle of view and contrast variability. The grantee also investigated how signal detection theory (SDT) can be used to model complex behaviors in bees.

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Document Details

Document Type
Technical Report
Publication Date
Jul 18, 2008
Accession Number
ADA485283

Entities

People

  • Adrian G Dyer

Organizations

  • Monash University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Biological Sciences
  • Biology
  • Brain
  • Computer Vision
  • Detection
  • Environment
  • Interpolation
  • Mobile Phones
  • Nervous System
  • Object Recognition
  • Pilot Studies
  • Radiation
  • Recognition
  • Signal Detection
  • Statistical Analysis
  • Target Recognition
  • Training

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