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Joshua Cosman, Geoffrey Woodman; Electrophysiological indices of learned distractor suppression. Journal of Vision 2015;15(12):319. doi: 10.1167/15.12.319.
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The extent to which a salient distractor captures attention during visual search depends on a number of bottom-up and top-down factors. We have recently demonstrated that in order to effectively overcome attentional capture individuals must learn to ignore distractor-defining features, with behavioral capture effects decreasing as exposure to these features increases. In the current work, we examined the electrophysiological signature of this distractor-related learning process, examining ERP components related to both attentional selection (N2pc) and distractor suppression (Pd). Participants performed a simple visual search task in which they searched heterogeneous displays for a shape-defined target while ignoring a salient color singleton distractor that appeared on half of trials. Critically, we manipulated participants’ ability to learn distractor-defining features from block to block. In fixed distractor blocks distractor color was held constant throughout block, allowing participants the opportunity to learn and suppress the distractor-defining feature. Conversely, in random distractor blocks distractor color varied unpredictably from trial to trial, eliminating the ability of participants to learn a specific distractor-defining feature. In random distractor blocks we observed behavioral capture effects and an N2pc to the distractor item, suggesting that the distractor captured attention. In contrast, in fixed color blocks we observed a decrease in behavioral capture effects and a Pd to the distractor item, suggesting that participants were able to learn distractor-defining features and use this information to attenuate the influence of the distractor on performance. In addition, in fixed blocks the Pd emerged after ~15 trials of exposure to the distractor, suggesting a rapid learning process enabling distractor suppression. This is consistent with behavioral results showing that the effectiveness of top-down control over attentional capture relies on having sufficient exposure to distractor defining features, and underscores the importance of feature-based learning processes in attentional control.
Meeting abstract presented at VSS 2015
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