Article (Scientific journals)
A Connectivity-Based Psychometric Prediction Framework for Brain-Behavior Relationship Studies.
Wu, Jianxiao; Eickhoff, Simon B.; Hoffstaedter, Felix et al.
2021In Cerebral Cortex (New York, N.Y. : 1991), 31 (8), p. 3732–3751
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Keywords :
Human Connectome Project; behavior prediction; brain–behavior relationships; machine learning; resting-state functional connectivity
Abstract :
[en] The recent availability of population-based studies with neuroimaging and behavioral measurements opens promising perspectives to investigate the relationships between interindividual variability in brain regions' connectivity and behavioral phenotypes. However, the multivariate nature of connectivity-based prediction model severely limits the insight into brain-behavior patterns for neuroscience. To address this issue, we propose a connectivity-based psychometric prediction framework based on individual regions' connectivity profiles. We first illustrate two main applications: 1) single brain region's predictive power for a range of psychometric variables and 2) single psychometric variable's predictive power variation across brain region. We compare the patterns of brain-behavior provided by these approaches to the brain-behavior relationships from activation approaches. Then, capitalizing on the increased transparency of our approach, we demonstrate how the influence of various data processing and analyses can directly influence the patterns of brain-behavior relationships, as well as the unique insight into brain-behavior relationships offered by this approach.
Disciplines :
Neurosciences & behavior
Author, co-author :
Wu, Jianxiao
Eickhoff, Simon B.
Hoffstaedter, Felix
Patil, Kaustubh R.
Schwender, Holger
Yeo, B. T. Thomas
Genon, Sarah ;  Université de Liège - ULiège > Département des sciences cliniques > Neuroimagerie des troubles de la mémoire et revalid. cogn.
Language :
English
Title :
A Connectivity-Based Psychometric Prediction Framework for Brain-Behavior Relationship Studies.
Publication date :
2021
Journal title :
Cerebral Cortex (New York, N.Y. : 1991)
ISSN :
1047-3211
eISSN :
1460-2199
Volume :
31
Issue :
8
Pages :
3732–3751
Peer reviewed :
Peer reviewed
Commentary :
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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since 06 May 2021

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