Learning to suppress a location is configuration-dependent
Main Author: | |
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Publication Date: | 2023 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10400.12/9850 |
Summary: | Where and what we attend is very much determined by what we have encountered in the past. Recent studies have shown that people learn to extract statistical regularities in the environment resulting in attentional suppression of locations that were likely to contain a distractor, efectively reducing the amount of attentional capture. Here, we asked whether this suppression efect due to statistical learning is dependent on the specifc confguration within which it was learned. The current study employed the additional singleton paradigm using search arrays that had a confguration consisting of set sizes of either four or 10 items. Each confguration contained its own high probability distractor location. If learning would generalize across set size confgurations, both high probability locations would be suppressed equally, regardless of set size. However, if learning to suppress is dependent on the confguration within which it was learned, one would expect only suppression of the high probability location that matched the confguration within which it was learned. The results show the latter, suggesting that implicitly learned suppression is confguration-dependent. Thus, we conclude that the high probability location is learned within the confguration context within which it is presented |
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Learning to suppress a location is configuration-dependentVisual searchAttentional captureWhere and what we attend is very much determined by what we have encountered in the past. Recent studies have shown that people learn to extract statistical regularities in the environment resulting in attentional suppression of locations that were likely to contain a distractor, efectively reducing the amount of attentional capture. Here, we asked whether this suppression efect due to statistical learning is dependent on the specifc confguration within which it was learned. The current study employed the additional singleton paradigm using search arrays that had a confguration consisting of set sizes of either four or 10 items. Each confguration contained its own high probability distractor location. If learning would generalize across set size confgurations, both high probability locations would be suppressed equally, regardless of set size. However, if learning to suppress is dependent on the confguration within which it was learned, one would expect only suppression of the high probability location that matched the confguration within which it was learned. The results show the latter, suggesting that implicitly learned suppression is confguration-dependent. Thus, we conclude that the high probability location is learned within the confguration context within which it is presentedSpringer New YorkRepositório do ISPAGao, YaDe Waard, JasperTheeuwes, Jan2024-07-12T15:33:45Z20232023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.12/9850eng1943393X10.3758/s13414-023-02732-2info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-07T14:59:35Zoai:repositorio.ispa.pt:10400.12/9850Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:04:17.509197Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Learning to suppress a location is configuration-dependent |
title |
Learning to suppress a location is configuration-dependent |
spellingShingle |
Learning to suppress a location is configuration-dependent Gao, Ya Visual search Attentional capture |
title_short |
Learning to suppress a location is configuration-dependent |
title_full |
Learning to suppress a location is configuration-dependent |
title_fullStr |
Learning to suppress a location is configuration-dependent |
title_full_unstemmed |
Learning to suppress a location is configuration-dependent |
title_sort |
Learning to suppress a location is configuration-dependent |
author |
Gao, Ya |
author_facet |
Gao, Ya De Waard, Jasper Theeuwes, Jan |
author_role |
author |
author2 |
De Waard, Jasper Theeuwes, Jan |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Repositório do ISPA |
dc.contributor.author.fl_str_mv |
Gao, Ya De Waard, Jasper Theeuwes, Jan |
dc.subject.por.fl_str_mv |
Visual search Attentional capture |
topic |
Visual search Attentional capture |
description |
Where and what we attend is very much determined by what we have encountered in the past. Recent studies have shown that people learn to extract statistical regularities in the environment resulting in attentional suppression of locations that were likely to contain a distractor, efectively reducing the amount of attentional capture. Here, we asked whether this suppression efect due to statistical learning is dependent on the specifc confguration within which it was learned. The current study employed the additional singleton paradigm using search arrays that had a confguration consisting of set sizes of either four or 10 items. Each confguration contained its own high probability distractor location. If learning would generalize across set size confgurations, both high probability locations would be suppressed equally, regardless of set size. However, if learning to suppress is dependent on the confguration within which it was learned, one would expect only suppression of the high probability location that matched the confguration within which it was learned. The results show the latter, suggesting that implicitly learned suppression is confguration-dependent. Thus, we conclude that the high probability location is learned within the confguration context within which it is presented |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023 2023-01-01T00:00:00Z 2024-07-12T15:33:45Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.12/9850 |
url |
http://hdl.handle.net/10400.12/9850 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1943393X 10.3758/s13414-023-02732-2 |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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Springer New York |
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Springer New York |
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