A Connectivity-Based Psychometric Prediction Framework for Brain-Behavior Relationship Studies.
Cereb Cortex
; 31(8): 3732-3751, 2021 07 05.
Article
em En
| MEDLINE
| ID: mdl-33884421
ABSTRACT
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Psicometria
/
Comportamento
/
Encéfalo
/
Conectoma
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
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Female
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Humans
/
Male
Idioma:
En
Revista:
Cereb Cortex
Assunto da revista:
CEREBRO
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Alemanha