Journal article

Temporal complexity of fMRI is reproducible and correlates with higher order cognition

Amir Omidvarnia, Andrew Zalesky, Sina L Mansour, Dimitri Van de Ville, Graeme D Jackson, Mangor Pedersen

NEUROIMAGE | ACADEMIC PRESS INC ELSEVIER SCIENCE | Published : 2021

Abstract

It has been hypothesized that resting state networks (RSNs), extracted from resting state functional magnetic resonance imaging (rsfMRI), likely display unique temporal complexity fingerprints, quantified by their multiscale entropy patterns (McDonough and Nashiro, 2014). This is a hypothesis with a potential capacity for developing digital biomarkers of normal brain function, as well as pathological brain dysfunction. Nevertheless, a limitation of McDonough and Nashiro (2014) was that rsfMRI data from only 20 healthy individuals was used for the analysis. To validate this hypothesis in a larger cohort, we used rsfMRI datasets of 987 healthy young adults from the Human Connectome Project (HC..

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Grants

Awarded by European Commission


Awarded by National Health and Medical Research Council (NHMRC) of Australia


Awarded by NHMRC practitioner's fellowship


Awarded by 16 National Institutes of Health (NIH) institutes and centers


Awarded by McDonnell Center for Systems Neuroscience at Washington University


Funding Acknowledgements

AO acknowledges financial support through the Eurotech Postdoc Program, co-funded by the European Commission under its framework program Horizon 2020 (Grant Agreement number 754462). This study was supported by the National Health and Medical Research Council (NHMRC) of Australia (no. 628952). The Florey Institute of Neuroscience and Mental Health acknowledges the strong support from the Victorian Government and in particular the funding from the Operational Infrastructure Support Grant. We also acknowledge the facilities, and the scientific and technical assistance of the National Imaging Facility (NIF) at the Florey node and The Victorian Biomedical Imaging Capability (VBIC). GJ is supported by an NHMRC practitioner's fellowship (no 1060312). The primary rsfMRI data in this study was provided by the Human Connectome Project, WUMinn Consortium (1U54MH091657; Principal Investigators: David Van Essen and Kamil Ugurbil) funded by the 16 National Institutes of Health (NIH) institutes and centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.