Journal
ATTENTION PERCEPTION & PSYCHOPHYSICS
Volume 85, Issue 2, Pages 315-341Publisher
SPRINGER
DOI: 10.3758/s13414-022-02621-0
Keywords
Selective attention; Attention capture; Reward; Selection history
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Visual features associated with reward can capture attention even when irrelevant to the task, this is known as value-driven attention capture (VDAC). VDAC was found to persist without reinforcement and could be eliminated through extinction. Manipulation of factors in five experiments revealed that the presence or absence of VDAC depended on task relevance of the rewarded feature. VDAC was only observed when the rewarded feature remained task-relevant and extinction was also observed.
Visual features previously associated with reward can capture attention even when task-irrelevant, a phenomenon known as value-driven attention capture (VDAC). VDAC persists without reinforcement, unlike other forms of learning, where removing reinforcement typically leads to extinction. In five experiments, factors common to many studies were manipulated to examine their impact on VDAC and its extinction. All experiments included learning and test phases. During learning, participants completed a visual search task during which one of two target colors was associated with a reward, and the other with no reward. During test, 1 week later, participants completed another visual search task in which the reward association was not reinforced. When a rewarded feature remained task-relevant (Experiment 1), VDAC was observed. When the rewarded feature was made task-irrelevant (Experiments 2-5) there was no evidence of a VDAC effect, except when the target feature was physically salient and there was a reduction in the frequency of exposure to the reward-associated feature (Experiment 5). We failed to find evidence of VDAC in Experiments 2-4, suggesting that VDAC may depend on the demands of the task resulting in vulnerability to VDAC. When VDAC was observed, extinction was also observed. This indicates that VDAC is subject to extinction as would be expected from an effect driven by reinforcement learning.
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