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 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.
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