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Katherine Moore, Jaimie Jasina, Ariel Kershner, Aziza Ransome; Set size matters when capturing attention in a hybrid visual-memory search. Journal of Vision 2018;18(10):465. doi: 10.1167/18.10.465.
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In a hybrid visual-memory search, increasing the number of concurrently searched for targets (i.e. "memory" set size) has a logarithmic effect on slowing search speed. Visual search is also impaired by the presence of distractors that resemble targets, a phenomenon called contingent attentional capture (e.g., it is harder to find a particular "camera," when a different camera appears). Set-specific capture, a more dramatic distraction cost, occurs when the presence of a goal-related distractor (e.g. the wrong camera) causes an internal shift of attention to the related goal state ("camera"), away from other search goals (e.g. "laptop"). Though we understand how visual search speeds are modulated by the memory set size, it is not clear how or whether distraction is affected by set size. In the present study, we investigated whether attentional capture and set-specific capture are modulated by the number of concurrently maintained search goals. Participants memorized a set of target objects, and then searched a rapid serial visual presentation for the memorized objects. On some trials, a distractor appeared 1-2 frames prior to a target object, and the distractor was either from the same object category as the target (measuring contingent attentional capture) or a different object category as the target (measuring set-specific capture). Participants completed the task for set sizes 2, 4, and 16. Display speed was calibrated to maintain uniform accuracy across participants and set sizes. Replicating other hybrid visual-memory search results, search speed increased logarithmically with memory set size. Contingent attentional capture effects were greatest at larger set sizes, whereas set-specific capture effects were greatest at smaller set sizes. This finding supports the notion that these phenomena represent distinct mechanisms. It also speaks to how search goals are maintained and used in a visual-memory hybrid search, as well as what occurs during distraction.
Meeting abstract presented at VSS 2018
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