Top-down control: A unified principle of cortical learning.


Journal

Neuroscience research
ISSN: 1872-8111
Titre abrégé: Neurosci Res
Pays: Ireland
ID NLM: 8500749

Informations de publication

Date de publication:
Apr 2019
Historique:
received: 24 03 2018
revised: 30 06 2018
accepted: 13 08 2018
pubmed: 21 8 2018
medline: 2 5 2019
entrez: 21 8 2018
Statut: ppublish

Résumé

Cognitive control of the brain flexibly maps incoming sensory information onto execution of actions appropriate for the current goal. Learning is a process that enables the brain to estimate current states of the world by extracting its spatiotemporal structure and generate goal-directed motor outputs through selective association of events or movement refinement. Accumulating evidence suggests that top-down control from higher-order brain areas modulates downstream neural activity and changes local computations that are critical for the execution of learned behavior. Recent technological advances in multi-site recordings and optogenetic approaches are beginning to reveal more direct evidence of top-down cognitive control by monitoring and perturbing activity of top-down inputs and observing its causal consequences on behavior and downstream neural dynamics. Here I highlight that learning-related changes in neural circuits in distinct domains of learning converge onto a unified principle; namely recruitment of top-down control whether it involves sensory, motor or offline learning. Recruitment of top-down control may reflect experience-dependent adaptation and integration of internal models for refined state estimation and goal-directed optimal behavior.

Identifiants

pubmed: 30125609
pii: S0168-0102(18)30170-6
doi: 10.1016/j.neures.2018.08.004
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

23-28

Informations de copyright

Copyright © 2018 Elsevier B.V. and Japan Neuroscience Society. All rights reserved.

Auteurs

Hiroshi Makino (H)

Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, 308232, Singapore. Electronic address: hmakino@ntu.edu.sg.

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