A computational account of transsaccadic attentional allocation based on visual gain fields.
active vision
classification images
gain fields
observer models
visual stability
Journal
Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876
Informations de publication
Date de publication:
02 Jul 2024
02 Jul 2024
Historique:
medline:
28
6
2024
pubmed:
28
6
2024
entrez:
28
6
2024
Statut:
ppublish
Résumé
Coordination of goal-directed behavior depends on the brain's ability to recover the locations of relevant objects in the world. In humans, the visual system encodes the spatial organization of sensory inputs, but neurons in early visual areas map objects according to their retinal positions, rather than where they are in the world. How the brain computes world-referenced spatial information across eye movements has been widely researched and debated. Here, we tested whether shifts of covert attention are sufficiently precise in space and time to track an object's real-world location across eye movements. We found that observers' attentional selectivity is remarkably precise and is barely perturbed by the execution of saccades. Inspired by recent neurophysiological discoveries, we developed an observer model that rapidly estimates the real-world locations of objects and allocates attention within this reference frame. The model recapitulates the human data and provides a parsimonious explanation for previously reported phenomena in which observers allocate attention to task-irrelevant locations across eye movements. Our findings reveal that visual attention operates in real-world coordinates, which can be computed rapidly at the earliest stages of cortical processing.
Identifiants
pubmed: 38941277
doi: 10.1073/pnas.2316608121
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2316608121Subventions
Organisme : DHAC | National Health and Medical Research Council (NHMRC)
ID : APP1091257
Organisme : Department of Education and Training | Australian Research Council (ARC)
ID : DE190100136
Organisme : DHAC | National Health and Medical Research Council (NHMRC)
ID : GNT2010141
Déclaration de conflit d'intérêts
Competing interests statement:The authors declare no competing interest.