Journal article

Multilayer network switching rate predicts brain performance

Mangor Pedersen, Andrew Zalesky, Amir Omidvarnia, Graeme D Jackson

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | NATL ACAD SCIENCES | Published : 2018

Abstract

Large-scale brain dynamics are characterized by repeating spatiotemporal connectivity patterns that reflect a range of putative different brain states that underlie the dynamic repertoire of brain functions. The role of transition between brain networks is poorly understood, and whether switching between these states is important for behavior has been little studied. Our aim was to model switching between functional brain networks using multilayer network methods and test for associations between model parameters and behavioral measures. We calculated time-resolved fMRI connectivity in 1,003 healthy human adults from the Human Connectome Project. The time-resolved fMRI connectivity data were..

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Grants

Awarded by NIH Blueprint for Neuroscience Research


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


Awarded by NHMRC


Funding Acknowledgements

All fMRI data in this study have been made freely available by the Human Connectome Project, WUMinn Consortium (1U 54MH091657; Principal Investigators David Van Essen and Kamil Ugurbil) funded by the 16 NIH institutes and centers that support the NIH Blueprint for Neuroscience Research, the McDonnell Center for Systems Neuroscience at Washington University, and National Health and Medical Research Council (NHMRC) of Australia Grant APP628952. 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 at the Florey node and The Victorian Biomedical Imaging Capability. G.D.J. is supported by NHMRC Practitioner's Fellowship APP1060312. A.Z. is supported by NHMRC Senior Research Fellowship B (APP1136649).