Revisiting the Functional Anatomy of the Human Brain : Toward a Meta-Networking Theory of Cerebral Functions
For more than one century, brain processing was mainly thought in a localizationist framework, in which one given function was underpinned by a discrete, isolated cortical area, and with a similar cerebral organization across individuals. However, advances in brain mapping techniques in humans have provided new insights into the organizational principles of anatomo-functional architecture. Here, we review recent findings gained from neuroimaging, electrophysiological, as well as lesion studies. Based on these recent data on brain connectome, we challenge the traditional, outdated localizationist view and propose an alternative meta-networking theory. This model holds that complex cognitions and behaviors arise from the spatiotemporal integration of distributed but relatively specialized networks underlying conation and cognition (e.g., language, spatial cognition). Dynamic interactions between such circuits result in a perpetual succession of new equilibrium states, opening the door to considerable interindividual behavioral variability and to neuroplastic phenomena. Indeed, a meta-networking organization underlies the uniquely human propensity to learn complex abilities, and also explains how postlesional reshaping can lead to some degrees of functional compensation in brain-damaged patients. We discuss the major implications of this approach in fundamental neurosciences as well as for clinical developments, especially in neurology, psychiatry, neurorehabilitation, and restorative neurosurgery.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2020 |
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Erschienen: |
2020 |
Enthalten in: |
Zur Gesamtaufnahme - volume:100 |
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Enthalten in: |
Physiological reviews - 100(2020), 3 vom: 01. Juli, Seite 1181-1228 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Herbet, Guillaume [VerfasserIn] |
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Links: |
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Themen: |
Central nervous system |
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Anmerkungen: |
Date Completed 20.08.2020 Date Revised 20.08.2020 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.1152/physrev.00033.2019 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM306725908 |
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