Exploring Cognition with Brain-Machine Interfaces.
brain–machine interface
cognition
learning
posterior parietal cortex
semantics
somatosensation
Journal
Annual review of psychology
ISSN: 1545-2085
Titre abrégé: Annu Rev Psychol
Pays: United States
ID NLM: 0372374
Informations de publication
Date de publication:
04 01 2022
04 01 2022
Historique:
entrez:
4
1
2022
pubmed:
5
1
2022
medline:
24
3
2022
Statut:
ppublish
Résumé
Traditional brain-machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in the human posterior parietal cortex during neuroprosthetic clinical trials. These signals are consistent with small regions of cortex having a diverse role in cognitive aspects of movement control and body monitoring, including sensorimotor integration, planning, trajectory representation, somatosensation, action semantics, learning, and decision making. These variables are encoded within the same population of cells using structured representations that bind related sensory and motor variables, an architecture termed partially mixed selectivity. Diverse cognitive signals provide complementary information to traditional motor commands to enable more natural and intuitive control of external devices.
Identifiants
pubmed: 34982594
doi: 10.1146/annurev-psych-030221-030214
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
131-158Subventions
Organisme : NEI NIH HHS
ID : R01 EY015545
Pays : United States