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Spatial suppression due to statistical regularities in a visual detection task

Increasing evidence demonstrates that observers can learn the likely location of salient singleton distractors during visual search. To date, the reduced attentional capture at high-probability distractor locations has typically been examined using so called compound search, in which by design a tar...

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Autores principales: van Moorselaar, Dirk, Theeuwes, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888488/
https://www.ncbi.nlm.nih.gov/pubmed/34773244
http://dx.doi.org/10.3758/s13414-021-02330-0
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author van Moorselaar, Dirk
Theeuwes, Jan
author_facet van Moorselaar, Dirk
Theeuwes, Jan
author_sort van Moorselaar, Dirk
collection PubMed
description Increasing evidence demonstrates that observers can learn the likely location of salient singleton distractors during visual search. To date, the reduced attentional capture at high-probability distractor locations has typically been examined using so called compound search, in which by design a target is always present. Here, we explored whether statistical distractor learning can also be observed in a visual detection task, in which participants respond target present if the singleton target is present and respond target absent when the singleton target is absent. If so, this allows us to examine suppression of the location that is likely to contain a distractor both in the presence, but critically also in the absence, of a priority signal generated by the target singleton. In an online variant of the additional singleton paradigm, observers had to indicate whether a unique shape was present or absent, while ignoring a colored singleton, which appeared with a higher probability in one specific location. We show that attentional capture was reduced, but not absent, at high-probability distractor locations, irrespective of whether the display contained a target or not. By contrast, target processing at the high-probability distractor location was selectively impaired on distractor-present displays. Moreover, all suppressive effects were characterized by a gradient such that suppression scaled with the distance to the high-probability distractor location. We conclude that statistical distractor learning can be examined in visual detection tasks, and discuss the implications for attentional suppression due to statistical learning.
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spelling pubmed-88884882022-03-08 Spatial suppression due to statistical regularities in a visual detection task van Moorselaar, Dirk Theeuwes, Jan Atten Percept Psychophys Article Increasing evidence demonstrates that observers can learn the likely location of salient singleton distractors during visual search. To date, the reduced attentional capture at high-probability distractor locations has typically been examined using so called compound search, in which by design a target is always present. Here, we explored whether statistical distractor learning can also be observed in a visual detection task, in which participants respond target present if the singleton target is present and respond target absent when the singleton target is absent. If so, this allows us to examine suppression of the location that is likely to contain a distractor both in the presence, but critically also in the absence, of a priority signal generated by the target singleton. In an online variant of the additional singleton paradigm, observers had to indicate whether a unique shape was present or absent, while ignoring a colored singleton, which appeared with a higher probability in one specific location. We show that attentional capture was reduced, but not absent, at high-probability distractor locations, irrespective of whether the display contained a target or not. By contrast, target processing at the high-probability distractor location was selectively impaired on distractor-present displays. Moreover, all suppressive effects were characterized by a gradient such that suppression scaled with the distance to the high-probability distractor location. We conclude that statistical distractor learning can be examined in visual detection tasks, and discuss the implications for attentional suppression due to statistical learning. Springer US 2021-11-12 2022 /pmc/articles/PMC8888488/ /pubmed/34773244 http://dx.doi.org/10.3758/s13414-021-02330-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
van Moorselaar, Dirk
Theeuwes, Jan
Spatial suppression due to statistical regularities in a visual detection task
title Spatial suppression due to statistical regularities in a visual detection task
title_full Spatial suppression due to statistical regularities in a visual detection task
title_fullStr Spatial suppression due to statistical regularities in a visual detection task
title_full_unstemmed Spatial suppression due to statistical regularities in a visual detection task
title_short Spatial suppression due to statistical regularities in a visual detection task
title_sort spatial suppression due to statistical regularities in a visual detection task
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8888488/
https://www.ncbi.nlm.nih.gov/pubmed/34773244
http://dx.doi.org/10.3758/s13414-021-02330-0
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