Understanding the neural basis of natural intelligence.


Journal

Cell
ISSN: 1097-4172
Titre abrégé: Cell
Pays: United States
ID NLM: 0413066

Informations de publication

Date de publication:
17 Oct 2024
Historique:
received: 11 05 2024
revised: 26 07 2024
accepted: 26 07 2024
medline: 19 10 2024
pubmed: 19 10 2024
entrez: 18 10 2024
Statut: ppublish

Résumé

Understanding the neural basis of natural intelligence necessitates a paradigm shift: from strict reductionism toward embracing complexity and diversity. New tools and theories enable us to tackle this challenge, providing unprecedented access to neural dynamics and behavior across time, contexts, and species. Principles for intelligent behavior and learning in the natural world are now, more than ever, within reach.

Identifiants

pubmed: 39423802
pii: S0092-8674(24)00843-2
doi: 10.1016/j.cell.2024.07.049
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

5833-5837

Informations de copyright

Copyright © 2024 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests The authors declare no competing interests.

Auteurs

Angelo Forli (A)

Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA. Electronic address: aforli@berkeley.edu.

Michael M Yartsev (MM)

Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Neuroscience, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA, USA. Electronic address: myartsev@berkeley.edu.

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Classifications MeSH