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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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 |
work_keys_str_mv |
AT peterfransson temporalflowofhubsandconnectivityinthehumanbrain AT williamhthompson temporalflowofhubsandconnectivityinthehumanbrain |
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