A cognitive neurogenetic approach to uncovering the structure of executive functions

Junjiao Feng, Liang Zhang, Chunhui Chen, Jintao Sheng, Zhifang Ye, Kanyin Feng, Jing Liu, Ying Cai, Bi Zhu, Zhaoxia Yu, Chuansheng Chen, Qi Dong and Gui Xue ()
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Junjiao Feng: Beijing Normal University
Liang Zhang: Beijing Normal University
Chunhui Chen: Beijing Normal University
Jintao Sheng: Beijing Normal University
Zhifang Ye: Beijing Normal University
Kanyin Feng: Beijing Normal University
Jing Liu: Beijing Normal University
Ying Cai: Zhejiang University
Bi Zhu: Beijing Normal University
Zhaoxia Yu: University of California
Chuansheng Chen: University of California
Qi Dong: Beijing Normal University
Gui Xue: Beijing Normal University

Nature Communications, 2022, vol. 13, issue 1, 1-19

Abstract: Abstract One central mission of cognitive neuroscience is to understand the ontology of complex cognitive functions. We addressed this question with a cognitive neurogenetic approach using a large-scale dataset of executive functions (EFs), whole-brain resting-state functional connectivity, and genetic polymorphisms. We found that the bifactor model with common and shifting-specific components not only was parsimonious but also showed maximal dissociations among the EF components at behavioral, neural, and genetic levels. In particular, the genes with enhanced expression in the middle frontal gyrus (MFG) and the subcallosal cingulate gyrus (SCG) showed enrichment for the common and shifting-specific component, respectively. Finally, High-dimensional mediation models further revealed that the functional connectivity patterns significantly mediated the genetic effect on the common EF component. Our study not only reveals insights into the ontology of EFs and their neurogenetic basis, but also provides useful tools to uncover the structure of complex constructs of human cognition.

Date: 2022
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DOI: 10.1038/s41467-022-32383-0

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