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Cognitive abilities are associated with specific conjunctions of structural and functional neural subnetworks.
Kristanto, Daniel; Hildebrandt, Andrea; Sommer, Werner; Zhou, Changsong.
Afiliação
  • Kristanto D; Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China; Department of Psychology, Carl von Ossietz
  • Hildebrandt A; Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Germany.
  • Sommer W; Department of Psychology, Humboldt University at Berlin, Berlin, Germany; Department of Psychology, Zhejiang Normal University, Jin Hua, China; Department of Physics, Hong Kong Baptist University, Hong Kong, China. Electronic address: werner.sommer@cms.hu-berlin.de.
  • Zhou C; Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China; Life Science Imaging Centre, Hong Kong Bap
Neuroimage ; 279: 120304, 2023 10 01.
Article em En | MEDLINE | ID: mdl-37536528
Cognitive neuroscience assumes that different mental abilities correspond to at least partly separable brain subnetworks and strives to understand their relationships. However, single-task approaches typically revealed multiple brain subnetworks to be involved in performance. Here, we chose a bottom-up approach of investigating the association between structural and functional brain subnetworks, on the one hand, and domain-specific cognitive abilities, on the other. Structural network was identified using machine-learning graph neural network by clustering anatomical brain properties measured in 838 individuals enroled in the WU-Minn Young Adult Human Connectome Project. Functional network was adapted from seven Resting State Networks (7-RSN). We then analyzed the results of 15 cognitive tasks and estimated five latent abilities: fluid reasoning (Gf), crystallized intelligence (Gc), memory (Mem), executive functions (EF), and processing speed (Gs). In a final step we determined linear associations between these independently identified ability and brain entities. We found no one-to-one mapping between latent abilities and brain subnetworks. Analyses revealed that abilities are associated with properties of particular combinations of brain subnetworks. While some abilities are more strongly associated to within-subnetwork connections, others are related with connections between multiple subnetworks. Importantly, domain-specific abilities commonly rely on node(s) as hub(s) to connect with other subnetworks. To test the robustness of our findings, we ran the analyses through several defensible analytical decisions. Together, the present findings allow a novel perspective on the distinct nature of domain-specific cognitive abilities building upon unique combinations of associated brain subnetworks.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Conectoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Humans Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2023 Tipo de documento: Article País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Conectoma Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adult / Humans Idioma: En Revista: Neuroimage Assunto da revista: DIAGNOSTICO POR IMAGEM Ano de publicação: 2023 Tipo de documento: Article País de publicação: Estados Unidos