Abstract
Efficacy of attentional selection in visual search is known to be rapidly modulated by the expected reward values associated with stimuli within an array. Neurophysiological evidence for increased attentional capture by high-valued stimuli has been found in the mean amplitude of the N2pc and PD, EEG components thought to reflect attentional target selection processes and suppression of attention to distractors, respectively. Visual search is enhanced with reward-associated targets in search arrays. The N2pc has been shown to be larger in amplitude for high- than low-reward targets, reflecting easier search due to larger attentional prioritization of high-valued stimuli. In contrast, reward-associated distractors in search arrays cause search costs. High-reward distractors elicit a reduced N2pc and larger PD, reflecting less effective distractor suppression. However, it is unclear whether prioritization of reward-associated stimuli persists when presented simultaneously with loss-associated stimuli. To test this, we first had participants engage in a simple choice task where they gained or lost money with high or low probability in response to choosing specific visual stimuli. After learning, value associated stimuli appeared as targets among novel distractors and, on some trials, a singleton value-associated distractor in 4-item visual search arrays (two on horizontal midline, two on vertical, on either side of fixation). Target-distractor pairings were constrained such that they were of opposite valence (one gain, one loss) and never appeared on the same midline. ERP results show a larger N2pc to reward-associated targets on the horizontal midline (with loss-associated distractor on vertical) than to loss-associated targets (with gain-associated distractor on vertical), most prominent when the target was previously paired with a high probability reward. Reward-associated stimuli appear to capture more attention over loss-associated distractors when competing for attention.
Meeting abstract presented at VSS 2018