Na Luo1,2 · Zhengyi Yang1,2 · Ming Song1,2 · Shiqi Di1,2 · Congying Chu1  · Weiyang Shi1  · Weihua Yue3,4 · Yuyanan Zhang3,4 · Hao Yan3,4 · Xiao Zhang3,4 · Dai Zhang3,4 · Jing Sui5  · Vince Calhoun6  · Tianzi Jiang1,2,7,8

1 Beijing Key Laboratory of Brainnetome and Brain‑Computer Interface, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 

2 School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China 

3 Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China 

4 Key Laboratory of Mental Health, Ministry of Health, National Clinical Research Center for Mental Disorders, Peking University, Beijing 100191, China 

5 IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China 

6 Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA 

7 Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 

8 Xiaoxiang Institute for Brain Health, Yongzhou 425002, China

Abstract

While urbanicity increases the risk of mental health issues, its effects on brain networks are heterogeneous and underexplored in relation to different exposome factors. Using a coordinate network mapping strategy termed exposure network mapping (ENM) across eight datasets, this study first consolidated heterogeneous findings of urbanicity to a significant, replicable network involving the middle frontal gyrus, orbital gyrus, and anterior cingulate gyrus. Afterwards, among the other factors examined (air pollution, noise, income, stress, green space), only stress converged into a distinct common network, highlighting the orbital gyrus, caudate, anterior/middle cingulate gyrus, hippocampus, and middle frontal gyrus. This ENM-stress map exhibited the highest correlation with both the ENM-urbanicity map (r = 0.77) and a transdiagnostic map (r = 0.72). In addition, sleep-related coordinates also formed a consistent network, involving the middle cingulate gyrus, orbital gyrus, caudate, and putamen, which correlated strongly with urbanicity (r = 0.75), stress (r = 0.80), and the transdiagnostic pattern (r = 0.55). Collectively, this study highlights the potential risks of urbanicity and stress, as well as the protective role of sleep on brain networks, which may offer new insights for preventing mental health issues in urban environments.

keywords

Urbanicity; Exposome; Human brain networks; Stress; Sleep; Psychiatry

[SpringerLink]