Revisiting correlation-based functional connectivity and its relationship with structural connectivity.

Netw Neurosci

Institute of Bioengineering, Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Switzerland; Centre for Informatics and Systems, University of Coimbra, Portugal.

Published: December 2020

Patterns of brain structural connectivity (SC) and functional connectivity (FC) are known to be related. In SC-FC comparisons, FC has classically been evaluated from between functional time series, and more recently from or their unnormalized version encoded in the matrix. The latter FC metrics yield more meaningful comparisons to SC because they capture 'direct' statistical dependencies, that is, discarding the effects of mediators, but their use has been limited because of estimation issues. With the rise of high-quality and large neuroimaging datasets, we revisit the relevance of different FC metrics in the context of SC-FC comparisons. Using data from 100 unrelated Human Connectome Project subjects, we first explore the amount of functional data required to reliably estimate various FC metrics. We find that precision-based FC yields a better match to SC than correlation-based FC when using 5 minutes of functional data or more. Finally, using a linear model linking SC and FC, we show that the SC-FC match can be used to further interrogate various aspects of brain structure and function such as the timescales of functional dynamics in different resting-state networks or the intensity of anatomical self-connections.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781609PMC
http://dx.doi.org/10.1162/netn_a_00166DOI Listing

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