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Cited by 386

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Attentional Templates in Visual Working Memory

Open access
Carlisle, N. B., Arita, J. T., Pardo, D., Woodman, G. F.·2011·Journal of Neuroscience

Abstract

Most theories of attention propose that we maintain attentional templates in visual working memory to control what information is selected. In the present study, we directly tested this proposal by measuring the contralateral-delay activity (CDA) of human event-related potentials during visual search tasks in which the target is cued on each trial. Here we show that the CDA can be used to measure the maintenance of attentional templates in visual working memory while processing complex visual scenes. In addition, this method allowed us to directly observe the shift from working memory to long-term memory representations controlling attention as learning occurred and experience accrued searching for the same target object. Our findings provide definitive support for several critical proposals made in theories of attention, learning, and automaticity.

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Crossref · 10.1523/jneurosci.1097-11.2011

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Metadata

Authors
Carlisle, N. B., Arita, J. T., Pardo, D., & Woodman, G. F.
Venue
Journal of Neuroscience
Published
2011-06-22
Volume
31
Issue
25
Pages
9315-9322
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
OpenAlex
W2063667579
Cited by
386
References
47
FWCI
6.63
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Attentional Templates in Visual Working Memory. https://app.cochat.ai/papers/10.1523/jneurosci.1097-11.2011
The paper
Carlisle, N. B., Arita, J. T., Pardo, D., & Woodman, G. F. (2011). Attentional Templates in Visual Working Memory. Journal of Neuroscience. https://doi.org/10.1523/jneurosci.1097-11.2011

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.