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A Dynamic Core Network and Global Efficiency in the Resting Human Brain.

Authors
  • de Pasquale, F1
  • Della Penna, S1
  • Sporns, O2
  • Romani, G L1
  • Corbetta, M3
  • 1 Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University, Chieti, Italy. , (Italy)
  • 2 Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA. , (India)
  • 3 Departments of Neurology, Radiology, Anatomy and Neurobiology, Washington University School of Medicine, Saint Louis, MO, USA ITAB, University of Chieti, Chieti, Italy. , (Italy)
Type
Published Article
Journal
Cerebral Cortex
Publisher
Oxford University Press
Publication Date
Oct 01, 2016
Volume
26
Issue
10
Pages
4015–4033
Identifiers
DOI: 10.1093/cercor/bhv185
PMID: 26347485
Source
Medline
Keywords
License
Unknown

Abstract

Spontaneous brain activity is spatially and temporally organized in the absence of any stimulation or task in networks of cortical and subcortical regions that appear largely segregated when imaged at slow temporal resolution with functional magnetic resonance imaging (fMRI). When imaged at high temporal resolution with magneto-encephalography (MEG), these resting-state networks (RSNs) show correlated fluctuations of band-limited power in the beta frequency band (14-25 Hz) that alternate between epochs of strong and weak internal coupling. This study presents 2 novel findings on the fundamental issue of how different brain regions or networks interact in the resting state. First, we demonstrate the existence of multiple dynamic hubs that allow for across-network coupling. Second, dynamic network coupling and related variations in hub centrality correspond to increased global efficiency. These findings suggest that the dynamic organization of across-network interactions represents a property of the brain aimed at optimizing the efficiency of communication between distinct functional domains (memory, sensory-attention, motor). They also support the hypothesis of a dynamic core network model in which a set of network hubs alternating over time ensure efficient global communication in the whole brain.

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