Feature-based attentional weighting and spreading in visual working memory
Attention can be directed at features and feature dimensions to facilitate perception. Here, we investigated whether feature-based-attention (FBA) can also dynamically weight feature-specific representations within multi-feature objects held in visual working memory (VWM). Across three experiments,...
| Główni autorzy: | , , |
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| Format: | Journal article |
| Język: | English |
| Wydane: |
Springer Nature
2017
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| _version_ | 1826303166171316224 |
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| author | Niklaus, M Nobre, A van Ede, F |
| author_facet | Niklaus, M Nobre, A van Ede, F |
| author_sort | Niklaus, M |
| collection | OXFORD |
| description | Attention can be directed at features and feature dimensions to facilitate perception. Here, we investigated whether feature-based-attention (FBA) can also dynamically weight feature-specific representations within multi-feature objects held in visual working memory (VWM). Across three experiments, participants retained coloured arrows in working memory and, during the delay, were cued to either the colour or the orientation dimension. We show that directing attention towards a feature dimension (1) improves the performance in the cued feature dimension at the expense of the uncued dimension, (2) is more efficient if directed to the same rather than to different dimensions for different objects, and (3) at least for colour, automatically spreads to the colour representation of non-attended objects in VWM. We conclude that FBA also continues to operate on VWM representations (with similar principles that govern FBA in the perceptual domain) and challenge the classical view that VWM representations are stored solely as integrated objects. |
| first_indexed | 2024-03-07T05:58:31Z |
| format | Journal article |
| id | oxford-uuid:eb5bb430-58b3-4b81-95e8-3183ae562f18 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:58:31Z |
| publishDate | 2017 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:eb5bb430-58b3-4b81-95e8-3183ae562f182022-03-27T11:09:07ZFeature-based attentional weighting and spreading in visual working memoryJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:eb5bb430-58b3-4b81-95e8-3183ae562f18EnglishSymplectic Elements at OxfordSpringer Nature2017Niklaus, MNobre, Avan Ede, FAttention can be directed at features and feature dimensions to facilitate perception. Here, we investigated whether feature-based-attention (FBA) can also dynamically weight feature-specific representations within multi-feature objects held in visual working memory (VWM). Across three experiments, participants retained coloured arrows in working memory and, during the delay, were cued to either the colour or the orientation dimension. We show that directing attention towards a feature dimension (1) improves the performance in the cued feature dimension at the expense of the uncued dimension, (2) is more efficient if directed to the same rather than to different dimensions for different objects, and (3) at least for colour, automatically spreads to the colour representation of non-attended objects in VWM. We conclude that FBA also continues to operate on VWM representations (with similar principles that govern FBA in the perceptual domain) and challenge the classical view that VWM representations are stored solely as integrated objects. |
| spellingShingle | Niklaus, M Nobre, A van Ede, F Feature-based attentional weighting and spreading in visual working memory |
| title | Feature-based attentional weighting and spreading in visual working memory |
| title_full | Feature-based attentional weighting and spreading in visual working memory |
| title_fullStr | Feature-based attentional weighting and spreading in visual working memory |
| title_full_unstemmed | Feature-based attentional weighting and spreading in visual working memory |
| title_short | Feature-based attentional weighting and spreading in visual working memory |
| title_sort | feature based attentional weighting and spreading in visual working memory |
| work_keys_str_mv | AT niklausm featurebasedattentionalweightingandspreadinginvisualworkingmemory AT nobrea featurebasedattentionalweightingandspreadinginvisualworkingmemory AT vanedef featurebasedattentionalweightingandspreadinginvisualworkingmemory |