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• W4387472571 abstract "Visual working memory has severe capacity limits, creating a bottleneck for active processing. A key way of mitigating this limitation is by chunking, i.e. compressing several pieces of information into one visual working memory representation. However, despite decades of research, chunking efficiency remains debated because of mixed evidence. We propose that there are actually 2 integration mechanisms: Grouping combines several objects to one representation, and object-unification merges the parts of a single object. Critically, we argue that the fundamental distinction between the 2 processes is their differential use of the pointer system, the indexing process connecting visual working memory representations with perception. In grouping, the objects that are represented together still maintain independent pointers, making integration costly but highly flexible. Conversely, object-unification fuses the pointers as well as the representations, with the single pointer producing highly efficient integration but blocking direct access to individual parts. We manipulated integration cues via task-irrelevant movement, and monitored visual working memory's online electrophysiological marker. Uniquely colored objects were flexibly grouped and ungrouped via independent pointers (experiment 1). If objects turned uniformly black, object-integration could not be undone (experiment 2), requiring visual working memory to reset before re-individuation. This demonstrates 2 integration levels (representational-merging versus pointer-compression) and establishes the dissociation between visual working memory representations and their underlying pointers." @default.
• W4387472571 created "2023-10-11" @default.
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• W4387472571 date "2023-10-09" @default.
• W4387472571 modified "2023-10-16" @default.
• W4387472571 title "Dissociable online integration processes in visual working memory" @default.
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• W4387472571 doi "https://doi.org/10.1093/cercor/bhad378" @default.
• W4387472571 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37814362" @default.
• W4387472571 hasPublicationYear "2023" @default.
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