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Revealing the Relevant Spatiotemporal Scale Underlying Whole-Brain Dynamics.

ABSTRACT: The brain rapidly processes and adapts to new information by dynamically transitioning between whole-brain functional networks. In this whole-brain modeling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100-900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify the richness of the dynamic repertoire at each spatiotemporal scale by computing the entropy of transitions between whole-brain functional networks. The results show that the optimal relevant spatial scale is around 300 regions and a temporal scale of around 150 ms. Overall, this study provides much needed evidence for the relevant spatiotemporal scales and recommendations for analyses of brain dynamics.

SUBMITTER: Kobeleva X

PROVIDER: S-EPMC8569182 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Revealing the Relevant Spatiotemporal Scale Underlying Whole-Brain Dynamics.

Kobeleva Xenia X López-González Ane A Kringelbach Morten L ML Deco Gustavo G

Frontiers in neuroscience 20211022

The brain rapidly processes and adapts to new information by dynamically transitioning between whole-brain functional networks. In this whole-brain modeling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100-900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify the ...[more]

PMID: 34744605

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