Cross-sectional exploration of brain functional connectivity in the triadic development model of adolescents
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ORIGINAL RESEARCH
Cross-sectional exploration of brain functional connectivity in the triadic development model of adolescents Wenjing Xu 1,2 & Fuxian Ying 3 & Yuejia Luo 4,5,6,7 & Xiao-Yong Zhang 1,2
&
Zhihao Li 3,4
# Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Adolescence represents a transitional stage with increased risk taking and mood dysregulation. These vulnerabilities are accountable by developmental dynamics in the triadic functional brain networks underlying reward seeking (REW), emotional avoidance (EMO), and cognitive regulation (COG). However, these triadic dynamics, though conceptually established, have yet been investigated directly. Capitalizing on public database of resting-state fMRI from 222 adolescents (8–18 years old, 89F133M), this study examined cross-sectional development profiles of functional connectivity (FC) by jointly considering bilateral seeds of the ventral striatum, amygdala, and dorsal lateral prefrontal cortex in probing the networks of REW, EMO, and COG, respectively. Positive and negative FCs were considered separately for clarification of synergetic and suppressive interactions. While the REW and EMO mostly exhibited quadratic FC changes across age, suggesting reduced reward sensitivity and risk avoidance, the COG exhibited both linear and quadratic FC changes, suggesting both protracted maturation of cognitive ability and lowered top-down regulation. Additional age × gender effects were identified in the precentral gyrus and superior medial prefrontal cortex, which may associate risky action and emotion dysregulation to boys and girls, respectively. These results provide network evidence in substantiating the “triadic model” and deepening existing insights into neurodevelopmental mechanisms associated with adolescent behavior. Keywords Adolescence . Resting-state fMRI . Functional connectivity . Development trajectory . Triadic model
These authors “Wenjing Xu and Fuxian Ying” contributed equally in this study Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11682-020-00379-3) contains supplementary material, which is available to authorized users. * Xiao-Yong Zhang [email protected]
4
Center for Brain Disorders and Cognitive Neuroscience, Shenzhen University, Shenzhen 518060, Guangdong, People’s Republic of China
5
Shenzhen Institute of Neuroscience, Shenzhen 518060, Guangdong, People’s Republic of China
6
Brain Science and Visual Cognition, Kunming University of Science and Technology, Kunming 650504, Yunnan, People’s Republic of China
7
The State Key Lab of Cognitive and Learning, Faculty of Psychology, Beijing Normal University, Beijing 100875, People’s Republic of China
* Zhihao Li [email protected] 1
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 220 Handan Road, Shanghai 200433, People’s Republic of China
2
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education
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