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155

Title

Do task-irrelevant cross-modal statistical regularities induce distractor suppression in visual search?use asterix (*) to get italics

Authors

Kishore Kumar Jagini and Meera Mary SunnyPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year

2022

Picture

Abstract

<p>We are constantly bombarded with a vast number of multisensory stimuli in our daily lives. Our sensory systems are known to extract and utilize statistical regularities in the sensory inputs across space and time to optimize the attentional orienting in the multisensory environment. This registered report proposes to test a question that addresses whether participants learn to utilize task-irrelevant, cross-modal stimulus spatial (Experiment 1) and non-spatial regularities (Experiment 2) indicating the salient visual distractor’s likely location (color singleton distractor) in search displays to perceptually suppress them for optimizing task efficiency. Critically, the spatial location of a colour singleton distractor in each trial could be either predicted or unpredicted based on the task-irrelevant auditory statistical regularities simultaneously presented across search displays. If the auditory statistical regularities induce visual distractor location suppression, it would provide evidence that the visuospatial attentional priority map can flexibly be modified based on the learning of task-irrelevant, cross-modal stimulus statistical regularities. We also test participants’ awareness about the statistical regularities to determine whether the learning is implicit or not.</p>

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Keywords

attention, attention capture, distractor suppression, cross-modal, statistical regularities

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields

Humanities, Life Sciences, Social sciences

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Submission date

2021-12-21 15:23:20

Recommender

Zoltan Dienes

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