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Network Structure Shapes Spontaneous Functional Connectivity Dynamics
Open accessAbstract
The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture.
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“Within the brain, a highly dynamic functional landscape unfolds on a relatively fixed structural scaffold (Deco et al., 2015; Shen et al., 2015)”
From The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance (2016) · cites this paper as Shen et al., 2015
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“Mounting evidence suggests that the functional connectome exhibits temporal instability that allows it to flexibly switch between multiple different configurations within a scanning session (Allen et al., 2014; Chang and Glover, 2010; Kang et al., 2011; Shen et al., 2015).”
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Metadata
- Authors
- Shen, K., Hutchison, R. M., Bezgin, G., Everling, S., & McIntosh, A. R.
- Affiliations
- Rotman Research Institute (CA)
- Harvard University (US)
- Western University (CA)
- University of Toronto (CA)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2015-04-08
- Volume
- 35
- Issue
- 14
- Pages
- 5579-5588
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC6605321
- OpenAlex
- W2052061512
- Cited by
- 171
- References
- 63
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 9 · 2023: 8 · 2022: 13 · 2021: 19 · 2020: 15 · 2019: 13 · 2018: 25 · 2017: 25 · 2016: 20 · 2015: 16
- FWCI
- 17.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Scholarship@Western (Western University) (submittedVersion)
- Funders
- Canadian Institutes of Health Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- resting-state functional connectivity, dynamic functional connectivity, structural connectivity, brain network topology, macaque, functional hubs, polysynaptic pathways, reciprocal connections
- MeSH terms
- Animals, Brain, Brain Mapping, Female, Image Processing, Computer-Assisted, Macaca fascicularis, Magnetic Resonance Imaging, Male, Models, Neurological, Neural Pathways, Oxygen, Nonlinear Dynamics
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