A large-scale neurocomputational model of spatial cognition integrating memory with vision.
Brain-inspired neural networks
Parietal cortex
Spatial memory and imagery
Spatial reference transformation
Visual attention
Journal
Neural networks : the official journal of the International Neural Network Society
ISSN: 1879-2782
Titre abrégé: Neural Netw
Pays: United States
ID NLM: 8805018
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
15
02
2023
revised:
29
06
2023
accepted:
20
08
2023
medline:
23
10
2023
pubmed:
10
9
2023
entrez:
9
9
2023
Statut:
ppublish
Résumé
We introduce a large-scale neurocomputational model of spatial cognition called 'Spacecog', which integrates recent findings from mechanistic models of visual and spatial perception. As a high-level cognitive ability, spatial cognition requires the processing of behaviourally relevant features in complex environments and, importantly, the updating of this information during processes of eye and body movement. The Spacecog model achieves this by interfacing spatial memory and imagery with mechanisms of object localisation, saccade execution, and attention through coordinate transformations in parietal areas of the brain. We evaluate the model in a realistic virtual environment where our neurocognitive model steers an agent to perform complex visuospatial tasks. Our modelling approach opens up new possibilities in the assessment of neuropsychological data and human spatial cognition.
Identifiants
pubmed: 37688954
pii: S0893-6080(23)00455-0
doi: 10.1016/j.neunet.2023.08.034
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
473-488Informations de copyright
Copyright © 2023 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.