Cited by 753Functional Brain Connectivity StudiesNeural dynamics and brain functionAdvanced Neuroimaging Techniques and Applications

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Time-resolved resting-state brain networks

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Zalesky, Andrew, Fornito, Alex, Cocchi, Luca, Gollo, Leonardo L., Breakspear, Michael·2014·Proceedings of the National Academy of Sciences

DOI 10.1073/pnas.1400181111PMC PMC4104861

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Abstract

Neuronal dynamics display a complex spatiotemporal structure involving the precise, context-dependent coordination of activation patterns across a large number of spatially distributed regions. Functional magnetic resonance imaging (fMRI) has played a central role in demonstrating the nontrivial spatial and topological structure of these interactions, but thus far has been limited in its capacity to study their temporal evolution. Here, using high-resolution resting-state fMRI data obtained from the Human Connectome Project, we mapped time-resolved functional connectivity across the entire brain at a subsecond resolution with the aim of understanding how nonstationary fluctuations in pairwise interactions between regions relate to large-scale topological properties of the human brain. We report evidence for a consistent set of functional connections that show pronounced fluctuations in their strength over time. The most dynamic connections are intermodular, linking elements from topologically separable subsystems, and localize to known hubs of default mode and fronto-parietal systems. We found that spatially distributed regions spontaneously increased, for brief intervals, the efficiency with which they can transfer information, producing temporary, globally efficient network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time, possibly achieving a balance between efficient information-processing and metabolic expenditure.

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Authors: Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., & Breakspear, M.
Affiliations: The University of Melbourne (AU)
The University of Queensland (AU)
QIMR Berghofer Medical Research Institute (AU)
ORCID: Zalesky, Andrew
Fornito, Alex
Cocchi, Luca
Gollo, Leonardo L.
Breakspear, Michael
Venue: Proceedings of the National Academy of Sciences
Publisher: National Academy of Sciences
Published: 2014-06-30
Volume: 111
Issue: 28
Pages: 10341-10346
ISSN: 0027-8424 (ISSN-L)
1091-6490
DOI: 10.1073/pnas.1400181111
PMC: PMC4104861
OpenAlex: W1996196481
Cited by: 753
References: 79
Citations by year: 2026: 18 · 2025: 57 · 2024: 49 · 2023: 49 · 2022: 58 · 2021: 82 · 2020: 74 · 2019: 74 · 2018: 65 · 2017: 98 · 2016: 64 · 2015: 51 · 2014: 13
FWCI: 42.01
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Proceedings of the National Academy of Sciences (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Minerva Access (University of Melbourne) (submittedVersion)
Funders: National Institutes of Health (5u54mh091657-05)
National Institute of Mental Health (1U54 MH091657, U54-MH091657)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords: resting-state brain networks, dynamic functional connectivity, brain network topology, default mode network, frontoparietal network, network hubs, information transmission efficiency, metabolic cost, brain dynamics, Human Connectome Project
MeSH terms: Adult, Brain, Humans, Magnetic Resonance Imaging, Male, Mental Processes, Nerve Net, Radiography

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