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Shared and unique brain network features predict cognition, personality and mental health in childhood

View ORCID ProfileJianzhong Chen, View ORCID ProfileAngela Tam, View ORCID ProfileValeria Kebets, View ORCID ProfileCsaba Orban, Leon Qi Rong Ooi, Scott Marek, Nico Dosenbach, View ORCID ProfileSimon Eickhoff, Danilo Bzdok, View ORCID ProfileAvram J Holmes, View ORCID ProfileB.T. Thomas Yeo
doi: https://doi.org/10.1101/2020.06.24.168724
Jianzhong Chen
1Department of Electrical and Computer Engineering & N.1 Institute for Health, National University of Singapore, Singapore
2Clinical Imaging Research Centre, National University of Singapore, Singapore
3Centre for Sleep and Cognition, National University of Singapore, Singapore
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  • ORCID record for Jianzhong Chen
Angela Tam
1Department of Electrical and Computer Engineering & N.1 Institute for Health, National University of Singapore, Singapore
2Clinical Imaging Research Centre, National University of Singapore, Singapore
3Centre for Sleep and Cognition, National University of Singapore, Singapore
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Valeria Kebets
1Department of Electrical and Computer Engineering & N.1 Institute for Health, National University of Singapore, Singapore
2Clinical Imaging Research Centre, National University of Singapore, Singapore
3Centre for Sleep and Cognition, National University of Singapore, Singapore
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Csaba Orban
1Department of Electrical and Computer Engineering & N.1 Institute for Health, National University of Singapore, Singapore
2Clinical Imaging Research Centre, National University of Singapore, Singapore
3Centre for Sleep and Cognition, National University of Singapore, Singapore
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Leon Qi Rong Ooi
1Department of Electrical and Computer Engineering & N.1 Institute for Health, National University of Singapore, Singapore
2Clinical Imaging Research Centre, National University of Singapore, Singapore
3Centre for Sleep and Cognition, National University of Singapore, Singapore
4NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
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Scott Marek
6Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
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Nico Dosenbach
6Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
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Simon Eickhoff
7Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
8Institute of Neuroscience and Medicine, Brain & Behaviours (INM-7), Research Center Jülich, Jülich, Germany
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Danilo Bzdok
9Department of Biomedical Engineering, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
10Mila - Quebec AI Institute, Montreal, Canada
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Avram J Holmes
11Yale University, Departments of Psychology and Psychiatry, New Haven, CT, USA
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B.T. Thomas Yeo
1Department of Electrical and Computer Engineering & N.1 Institute for Health, National University of Singapore, Singapore
2Clinical Imaging Research Centre, National University of Singapore, Singapore
3Centre for Sleep and Cognition, National University of Singapore, Singapore
4NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
5Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
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  • For correspondence: thomas.yeo@nus.edu.sg
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Abstract

The manner through which individual differences in brain network organization track population-level behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, the focus of most studies on single behavioral traits has come at the expense of capturing broader relationships across behaviors. Here, we utilized a large-scale dataset of 1858 typically developing children to estimate whole-brain functional network organization that is predictive of individual differences in cognition, impulsivity-related personality, and mental health during rest and task states. Predictive network features were distinct across the broad behavioral domains: cognition, personality and mental health. On the other hand, traits within each behavioral domain were predicted by highly similar network features. This is surprising given decades of research emphasizing that distinct brain networks support different mental processes. Although tasks are known to modulate the functional connectome, we found that predictive network features were similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood, yet are unique to different behavioral domains.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted June 24, 2020.
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Shared and unique brain network features predict cognition, personality and mental health in childhood
Jianzhong Chen, Angela Tam, Valeria Kebets, Csaba Orban, Leon Qi Rong Ooi, Scott Marek, Nico Dosenbach, Simon Eickhoff, Danilo Bzdok, Avram J Holmes, B.T. Thomas Yeo
bioRxiv 2020.06.24.168724; doi: https://doi.org/10.1101/2020.06.24.168724
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Shared and unique brain network features predict cognition, personality and mental health in childhood
Jianzhong Chen, Angela Tam, Valeria Kebets, Csaba Orban, Leon Qi Rong Ooi, Scott Marek, Nico Dosenbach, Simon Eickhoff, Danilo Bzdok, Avram J Holmes, B.T. Thomas Yeo
bioRxiv 2020.06.24.168724; doi: https://doi.org/10.1101/2020.06.24.168724

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