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Learning-Induced Changes in Attentional Allocation during Categorization: A Sizable Catalog of Attention Change as Measured by Eye Movements

Learning how to allocate attention properly is essential for success at many categorization tasks. Advances in our understanding of learned attention are stymied by a chicken-and-egg problem: there are no theoretical accounts of learned attention that predict patterns of eye movements, making data c...

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Detalles Bibliográficos
Autores principales: McColeman, Caitlyn M., Barnes, Jordan I., Chen, Lihan, Meier, Kimberly M., Walshe, R. Calen, Blair, Mark R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3908863/
https://www.ncbi.nlm.nih.gov/pubmed/24497915
http://dx.doi.org/10.1371/journal.pone.0083302