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Decoding load or selection in visuospatial working memory?

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dc.contributor.authorTortajada, Miriam
dc.contributor.authorFahrenfort, Johannes J.
dc.contributor.authorSandoval Lentisco, Alejandro
dc.contributor.authorPalmero, Lucía B.
dc.contributor.authorCastillo, Alejandro
dc.contributor.authorFuentes Melero, Luis José
dc.contributor.authorCampoy, Guillermo
dc.contributor.authorOlivers, Christian N. L.
dc.contributor.authorMartínez Pérez, Víctor
dc.contributor.departmentPsicología Básica y Metodología
dc.date.accessioned2025-01-23T11:23:15Z
dc.date.available2025-01-23T11:23:15Z
dc.date.issued2024-10
dc.description© 2024 The Author(s). This manuscript version is made available under the CC-BY 4.0 license http://creativecommons.org/licenses/by/4.0/ This document is the Published Manuscript version of a Published Work that appeared in final form in Psychophysiology. To access the final edited and published work see https://doi.org/10.1111/psyp.14636
dc.description.abstractFlexible updating of information in Visual Working Memory (VWM) is crucial to deal with its limited capacity. Previous research has shown that the removal of no longer relevant information takes some time to complete. Here, we sought to study the time course of such removal by tracking the accompanying drop in load through behavioral and neurophysiological measures. In the first experimental session, participants completed a visuospatial retro-cue task in which the Cue-Target Interval (CTI) was manipulated. The performance revealed that it takes about half a second to make full use of the retro-cue. In a second session, we sought to study the dynamics of load-related electroencephalographic (EEG) signals to track the removal of information. We applied Multivariate Pattern Analysis (MVPA) to EEG data from the same task. Right after encoding, results replicated previous research using MVPA to decode load. However, especially after the retro-cue, results suggested that classifiers were mainly sensitive to a selection component, and not so much to load per se. Additionally, visual cue variations, as well as eye movements that accompany load manipulations can also contribute to decoding. These findings advise caution when using MVPA to decode VWM load, as classifiers may be sensitive to confounding operations.
dc.formatapplication/pdfes
dc.format.extent20
dc.identifier.citationPsychophysiology, 2024, Vol. 61, Issue10 : e14636
dc.identifier.doihttps://doi.org/10.1111/psyp.14636
dc.identifier.issnPrint: 0048-5772
dc.identifier.issnElectronic: 1469-8986
dc.identifier.urihttp://hdl.handle.net/10201/149149
dc.languageenges
dc.publisherWiley
dc.relationMinisterio de Ciencia e Innovación. Grant Numbers: FPU17/00427, FPU18/00288, FPU19/06016, FPU19/06017 Agencia Estatal de Investigación. Grant Number: PID2021-125408NB-I00 Nederlandse Organisatie voor Wetenschappelijk Onderzoek. Grant Number: 453-16-002es
dc.relation.ispartofPID2021-125408NB-I00es
dc.relation.publisherversionhttps://onlinelibrary.wiley.com/doi/10.1111/psyp.14636
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectAttentional selection
dc.subjectWorking memory load
dc.subjectVisual working memory
dc.subjectMultivariate pattern analysis
dc.subjectElectroencephalography
dc.titleDecoding load or selection in visuospatial working memory?es
dc.typeinfo:eu-repo/semantics/articlees
dspace.entity.typePublicationes
relation.isAuthorOfPublication3030d976-ebc6-4695-b033-398d601b4659
relation.isAuthorOfPublication.latestForDiscovery3030d976-ebc6-4695-b033-398d601b4659
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