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Complex Trade-Offs in a Dual-Target Visual Search Task Are Indexed by Lateralised ERP Components

aut.relation.articlenumber22839
aut.relation.issue1
aut.relation.journalScientific Reports
aut.relation.volume14
dc.contributor.authorHenare, Dion T
dc.contributor.authorTünnermann, Jan
dc.contributor.authorWagner, Ilja
dc.contributor.authorSchütz, Alexander C
dc.contributor.authorSchubö, Anna
dc.date.accessioned2024-10-06T23:19:15Z
dc.date.available2024-10-06T23:19:15Z
dc.date.issued2024-10-01
dc.description.abstractIn everyday tasks, the choices we make incorporate complex trade-offs between conflicting factors that affect how we will achieve our goals. Previous experimental research has used dual-target visual search to determine how people flexibly adjust their behaviour and make choices that optimise their decisions. In this experiment, we leveraged a visual search task that incorporates complex trade-offs, and electroencephalography (EEG), to understand how neural mechanisms of selective attention contribute to choice behaviour in these tasks. On each trial, participants could choose to respond to the gap location on either of two possible targets. Each target was colour coded such that colour indicated which of the two had the easier gap discrimination. Orthogonally, we manipulated the set size of coloured distractors to modulate how efficiently each target could be found. As a result, optimised task performance required participants to trade-off conflicts between the ease of finding a target given the current set size, and the ease of making its associated gap discrimination. Our results confirm that participants are able to flexibly adjust their behaviour, and trade-off these two factors to maintain their response speed and accuracy. Additionally, the N2pc and SPCN components elicited by search displays could reliably predict the choice that participants would ultimately make on a given trial. These results suggest that initial attentional processes may help to determine the choice participants make, highlighting the central role that attention may play in optimising performance on complex tasks.
dc.identifier.citationScientific Reports, ISSN: 2045-2322 (Online), Springer Science and Business Media LLC, 14(1). doi: 10.1038/s41598-024-72811-3
dc.identifier.doi10.1038/s41598-024-72811-3
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10292/18102
dc.languageen
dc.publisherSpringer Science and Business Media LLC
dc.relation.urihttps://www.nature.com/articles/s41598-024-72811-3
dc.rightsOpen 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/.
dc.rights.accessrightsOpenAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleComplex Trade-Offs in a Dual-Target Visual Search Task Are Indexed by Lateralised ERP Components
dc.typeJournal Article
pubs.elements-id570699

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