Temporal flow of hubs and connectivity in the human brain

Hubs in brain network connectivity have previously been observed using neuroimaging techniques and are generally believed to be of pivotal importance to establish and maintain a functional platform on which cognitively meaningful and energy-efficient neuronal communication can occur. However, little...

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Main Authors: Peter Fransson, William H. Thompson
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:NeuroImage
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S105381192030834X
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spelling doaj-48f86c2312a44d6a812c37161153fba02020-11-25T03:56:19ZengElsevierNeuroImage1095-95722020-12-01223117348Temporal flow of hubs and connectivity in the human brainPeter Fransson0William H. Thompson1Department of Clinical Neuroscience, Karolinska Institutet, Nobels väg 9, SE-171 77, Stockholm, Sweden; Corresponding author.Department of Clinical Neuroscience, Karolinska Institutet, Nobels väg 9, SE-171 77, Stockholm, Sweden; Department of Psychology, Stanford University, USAHubs in brain network connectivity have previously been observed using neuroimaging techniques and are generally believed to be of pivotal importance to establish and maintain a functional platform on which cognitively meaningful and energy-efficient neuronal communication can occur. However, little is known if hubs are static (i.e. a brain region is always a hub) or if these properties change over time (i.e. brain regions fluctuate in their ‘hubness’). To address this question, we introduce two new methodological concepts, the flow of brain connectivity and node penalized shortest paths which are then applied to time-varying functional connectivity fMRI BOLD data. We show that the constellations of active hubs change over time in a non-trivial way and that activity of hubs is dependent on the temporal scale of investigation. Slower fluctuations in the number of active hubs that exceeded the degree expected by chance alone were detected primarily in subcortical structures. Moreover, we observed faster fluctuations in hub activity residing predominately in the default mode network that suggests dynamic events in brain connectivity. Our results suggest that the temporal behavior of connectivity hubs is a multilayered and complex issue where method-specific properties of temporal sensitivity to time-varying connectivity must be taken into account. We discuss our results in relation to the on-going discussion of the existence of discrete and stable states in the resting-brain and the role of network hubs in providing a scaffold for neuronal communication across time.http://www.sciencedirect.com/science/article/pii/S105381192030834XTime-varying functional connectivityResting-statefMRIHubsBetweenness centralityBrain
collection DOAJ
language English
format Article
sources DOAJ
author Peter Fransson
William H. Thompson
spellingShingle Peter Fransson
William H. Thompson
Temporal flow of hubs and connectivity in the human brain
NeuroImage
Time-varying functional connectivity
Resting-state
fMRI
Hubs
Betweenness centrality
Brain
author_facet Peter Fransson
William H. Thompson
author_sort Peter Fransson
title Temporal flow of hubs and connectivity in the human brain
title_short Temporal flow of hubs and connectivity in the human brain
title_full Temporal flow of hubs and connectivity in the human brain
title_fullStr Temporal flow of hubs and connectivity in the human brain
title_full_unstemmed Temporal flow of hubs and connectivity in the human brain
title_sort temporal flow of hubs and connectivity in the human brain
publisher Elsevier
series NeuroImage
issn 1095-9572
publishDate 2020-12-01
description Hubs in brain network connectivity have previously been observed using neuroimaging techniques and are generally believed to be of pivotal importance to establish and maintain a functional platform on which cognitively meaningful and energy-efficient neuronal communication can occur. However, little is known if hubs are static (i.e. a brain region is always a hub) or if these properties change over time (i.e. brain regions fluctuate in their ‘hubness’). To address this question, we introduce two new methodological concepts, the flow of brain connectivity and node penalized shortest paths which are then applied to time-varying functional connectivity fMRI BOLD data. We show that the constellations of active hubs change over time in a non-trivial way and that activity of hubs is dependent on the temporal scale of investigation. Slower fluctuations in the number of active hubs that exceeded the degree expected by chance alone were detected primarily in subcortical structures. Moreover, we observed faster fluctuations in hub activity residing predominately in the default mode network that suggests dynamic events in brain connectivity. Our results suggest that the temporal behavior of connectivity hubs is a multilayered and complex issue where method-specific properties of temporal sensitivity to time-varying connectivity must be taken into account. We discuss our results in relation to the on-going discussion of the existence of discrete and stable states in the resting-brain and the role of network hubs in providing a scaffold for neuronal communication across time.
topic Time-varying functional connectivity
Resting-state
fMRI
Hubs
Betweenness centrality
Brain
url http://www.sciencedirect.com/science/article/pii/S105381192030834X
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AT williamhthompson temporalflowofhubsandconnectivityinthehumanbrain
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