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Movement Retraining using Real-time Feedback of Performance
08:16

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Published on: January 17, 2013

Learning cue validity through performance feedback.

Jason A Droll1, Craig K Abbey, Miguel P Eckstein

  • 1Department of Psychology, University of California Santa Barbara, CA 93106, USA. jdroll@exponent.com

Journal of Vision
|March 11, 2009
PubMed
Summary
This summary is machine-generated.

This study shows that feedback significantly improves visual search performance by enhancing cue validity learning. However, explicit knowledge of cue validity did not improve with feedback, indicating unique learning constraints.

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Area of Science:

  • Cognitive Psychology
  • Visual Perception
  • Human-Computer Interaction

Background:

  • Visual search targets are often not random, exhibiting co-occurrence with scene elements.
  • Cue validity, the probability of a cue predicting a target, can improve search performance.
  • The mechanisms by which observers learn cue validity remain largely unknown.

Purpose of the Study:

  • To investigate if observers can learn cue validity probabilities.
  • To determine how different feedback conditions shape the learning of cue validity.
  • To compare learning rates to an ideal observer model.

Main Methods:

  • Participants performed a visual search task under three feedback conditions: unsupervised, response reinforcement, and supervised.
  • Cue validity was manipulated, and search performance (saccadic and perceptual decisions) was measured.
  • Explicit estimates of cue validity were collected after the search task.

Main Results:

  • Increased feedback information led to larger cueing effects in saccadic and perceptual decisions.
  • Response reinforcement feedback was sufficient for exploiting cue validity, unlike unsupervised feedback.
  • Explicit estimates of cue validity were independent of the feedback condition.

Conclusions:

  • Implicit learning of cue validity is enhanced by feedback, particularly reinforcement.
  • Explicit knowledge acquisition of cue validity is constrained and not influenced by feedback type.
  • Learning rates for cue validity were suboptimal compared to an ideal observer, potentially hindering initial performance.