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Proactive distractor suppression elicited by statistical regularities in visual search.

Changrun Huang1,2, Ana Vilotijević3,4, Jan Theeuwes3,4

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Statistical learning helps visual search by proactively suppressing distracting objects at frequently encountered locations. This proactive spatial suppression reduces interference before attention is even directed.

Keywords:
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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Visual Perception

Background:

  • Irrelevant salient objects can disrupt visual search by capturing attention.
  • Distraction is reduced when salient distractors appear more frequently at a specific location.
  • The mechanism behind this reduced interference (proactive vs. reactive suppression) is unclear.

Purpose of the Study:

  • To determine if reduced distractor interference results from proactive or reactive spatial suppression.
  • To investigate the role of statistical learning in modulating attentional processes during visual search.

Main Methods:

  • Participants performed a visual search task for a shape singleton amidst a salient color singleton distractor.
  • The distractor had a high probability of appearing at one location and low probability at others.
  • A probe task measured reaction times to detect a probe at different locations to assess suppression.

Main Results:

  • Reduced distractor interference was observed when the distractor appeared at the high-probability location.
  • Probe reaction times were significantly longer at the high-probability location compared to low-probability locations.
  • These findings support proactive suppression mechanisms.

Conclusions:

  • Statistical learning enables proactive spatial suppression of frequently encountered distractor locations before display onset.
  • This proactive suppression influences early visual processing by deprioritizing likely distractor locations in the spatial priority map.
  • Attention allocation during visual search is dynamically modulated by learned environmental statistics.