The functional connectome predicts feeling of stress on regular days and during the COVID-19 pandemic

被引:16
|
作者
Liu, Peiduo [1 ,2 ,3 ]
Yang, Wenjing [1 ,2 ]
Zhuang, Kaixiang [1 ,2 ]
Wei, Dongtao [1 ,2 ]
Yu, Rongjun [4 ]
Huang, Xiting [1 ,2 ]
Qiu, Jiang [1 ,2 ]
机构
[1] Minist Educ, Key Lab Cognit & Personal SWU, Chongqing 400715, Peoples R China
[2] Southwest Univ SWU, Fac Psychol, 2 TianSheng Rd, Chongqing 400715, Peoples R China
[3] Southwest Univ, Res Ctr Psychol & Social Dev, Chongqing 400715, Peoples R China
[4] Natl Univ Singapore, Dept Psychol, Singapore, Singapore
来源
NEUROBIOLOGY OF STRESS | 2021年 / 14卷
基金
中国国家自然科学基金;
关键词
Perceived stress; Perceived stress scale; COVID-19; Connectome-based predictive modeling; Resting-state functional connectivity; SCALE BRAIN NETWORKS; PSYCHOSOCIAL STRESS; SUSTAINED ATTENTION; PERCEIVED STRESS; CONNECTIVITY; ANXIETY; CORTEX; NEUROMARKER; DISORDERS; RELEVANCE;
D O I
10.1016/j.ynstr.2020.100285
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Although many studies have explored the neural mechanism of the feeling of stress, to date, no effort has been made to establish a model capable of predicting the feeling of stress at the individual level using the resting-state functional connectome. Although individuals may be confronted with multidimensional stressors during the coronavirus disease 2019 (COVID-19) pandemic, their appraisal of the impact and severity of these events might vary. In this study, connectome-based predictive modeling (CPM) with leave-one-out cross-validation was conducted to predict individual perceived stress (PS) from whole-brain functional connectivity data from 817 participants. The results showed that the feeling of stress could be predicted by the interaction between the default model network and salience network, which are involved in emotion regulation and salience attribution, respectively. Key nodes that contributed to the prediction model comprised regions mainly located in the limbic systems and temporal lobe. Critically, the CPM model of PS based on regular days can be generalized to predict individual PS levels during the COVID-19 pandemic, which is a multidimensional, uncontrollable stressful situation. The stability of the results was demonstrated by two independent datasets. The present work not only expands existing knowledge regarding the neural mechanism of PS but also may help identify high-risk individuals in healthy populations.
引用
收藏
页数:8
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