Cognitive neurophysiology of the prefrontal cortex.

Activity-silent coding Cognitive control Cross-frequency coupling Dynamic coding Electrocorticography Human single unit recordings Intracranial EEG Mixed selectivity Neuronal oscillations Population coding

Journal

Handbook of clinical neurology
ISSN: 0072-9752
Titre abrégé: Handb Clin Neurol
Pays: Netherlands
ID NLM: 0166161

Informations de publication

Date de publication:
2019
Historique:
entrez: 9 10 2019
pubmed: 9 10 2019
medline: 27 2 2020
Statut: ppublish

Résumé

The prefrontal cortex (PFC) provides the structural basis for complex rule-guided goal-directed behavior. However, the functional mechanisms that underlie cognitive control and flexibility are not as well understood. Over the last decade, novel electrophysiological methods and analysis techniques have begun to elucidate the neural mechanisms underlying higher cognitive functions. Here we review how electrophysiology and, in particular, intracranial recordings in humans and primates enable imaging of cognitive processing with an unprecedented spatiotemporal resolution. Convergent evidence from multiple species and across several spatial scales suggests that cell assemblies and transient synchronized network activity constitute the functional units of PFC implementation of organized behavior. These observations indicate that the functional architecture of cognition is inherently rhythmic and not static. We highlight that prefrontal neurons exhibit a mixed selectivity to various task-relevant aspects and code information in a time-varying dynamic population code and not at the level of individual neurons or in stable coding schemes. We argue that network neuroscience and network neurology are emergent paradigms to understand complex behavior and mental diseases.

Identifiants

pubmed: 31590740
pii: B978-0-12-804281-6.00003-3
doi: 10.1016/B978-0-12-804281-6.00003-3
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

35-59

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Randolph F Helfrich (RF)

Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States; Department of Psychology, University of Oslo, Oslo, Norway.

Robert T Knight (RT)

Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States; Department of Psychology, University of California Berkeley, Berkeley, CA, United States. Electronic address: rtknight@berkeley.edu.

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Classifications MeSH