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
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

131-158

Subventions

Organisme : NEI NIH HHS
ID : R01 EY015545
Pays : United States

Auteurs

Richard A Andersen (RA)

Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA; email: andersen@vis.caltech.edu.
USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, California 90033, USA.

Tyson Aflalo (T)

Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA; email: andersen@vis.caltech.edu.

Luke Bashford (L)

Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA; email: andersen@vis.caltech.edu.

David Bjånes (D)

Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA; email: andersen@vis.caltech.edu.

Spencer Kellis (S)

Division of Biology and Biological Engineering and Tianqiao & Chrissy Chen Brain-Machine Interface Center, California Institute of Technology, Pasadena, California 91125, USA; email: andersen@vis.caltech.edu.
USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, California 90033, USA.
Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, California 90033, USA.

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Classifications MeSH