Behavioral and Health Correlates of Resting-State Metastability in the Human Connectome Project

Won Hee Lee; Dominik Andreas Moser; Alex Ing; Gaelle Eve Doucet; Sophia Frangou

doi:10.1007/s10548-018-0672-5

Behavioral and Health Correlates of Resting-State Metastability in the Human Connectome Project

Won Hee Lee, Dominik Andreas Moser, Alex Ing, Gaelle Eve Doucet, Sophia Frangou

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Metastability is currently considered a fundamental property of the functional configuration of brain networks. The present study sought to generate a normative reference framework for the metastability of the major resting-state networks (RSNs) (resting-state metastability dataset) and discover their association with demographic, behavioral, physical and cognitive features (non-imaging dataset) from 818 participants of the Human Connectome Project. Using sparse canonical correlation analysis, we found that the metastability and non-imaging datasets showed significant but modest interdependency. Notable associations between the metastability variate and the non-imaging features were observed for higher-order cognitive ability and indicators of physical well-being. The intra-class correlation coefficient between the sibling pairs in the sample was very low which argues against a significant familial influence on RSN metastability.

Original language	English (US)
Pages (from-to)	80-86
Number of pages	7
Journal	Brain Topography
Volume	32
Issue number	1
DOIs	https://doi.org/10.1007/s10548-018-0672-5
State	Published - Jan 30 2019
Externally published	Yes

Keywords

Body mass index
Canonical correlation analysis
Human Connectome Project
Metastability
Resting-state fMRI

ASJC Scopus subject areas

Anatomy
Radiological and Ultrasound Technology
Radiology Nuclear Medicine and imaging
Neurology
Clinical Neurology

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title = "Behavioral and Health Correlates of Resting-State Metastability in the Human Connectome Project",

abstract = "Metastability is currently considered a fundamental property of the functional configuration of brain networks. The present study sought to generate a normative reference framework for the metastability of the major resting-state networks (RSNs) (resting-state metastability dataset) and discover their association with demographic, behavioral, physical and cognitive features (non-imaging dataset) from 818 participants of the Human Connectome Project. Using sparse canonical correlation analysis, we found that the metastability and non-imaging datasets showed significant but modest interdependency. Notable associations between the metastability variate and the non-imaging features were observed for higher-order cognitive ability and indicators of physical well-being. The intra-class correlation coefficient between the sibling pairs in the sample was very low which argues against a significant familial influence on RSN metastability.",

keywords = "Body mass index, Canonical correlation analysis, Human Connectome Project, Metastability, Resting-state fMRI",

author = "Lee, {Won Hee} and Moser, {Dominik Andreas} and Alex Ing and Doucet, {Gaelle Eve} and Sophia Frangou",

note = "Funding Information: Acknowledgements Data were provided by the WU-Minn Human Connectome Project Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Dr. Frangou received support from the National Institutes of Health (R01 MH104284-01A1) and European Unit FP7 program (IMAGEMEND 602450; IMAging GEnetics for MENtal Disorders) projects. Dr. Moser received support from the Swiss National Science Foundation (P2GEP3_162104, P300PB_171584).",

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N1 - Funding Information: Acknowledgements Data were provided by the WU-Minn Human Connectome Project Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Dr. Frangou received support from the National Institutes of Health (R01 MH104284-01A1) and European Unit FP7 program (IMAGEMEND 602450; IMAging GEnetics for MENtal Disorders) projects. Dr. Moser received support from the Swiss National Science Foundation (P2GEP3_162104, P300PB_171584).

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