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.

尽管许多研究已经探索了压力感的神经机制，但迄今为止，尚未做出任何努力来建立能够使用静止状态功能连接体在个体水平上预测压力感的模型。尽管在2019年冠状病毒病（COVID-19）大流行期间，个体可能面临多维压力源，但他们对这些事件的影响和严重性的评估可能有所不同。在这项研究中，进行了基于连接组的预测模型（CPM）和留一法交叉验证，以根据817位参与者的全脑功能连接数据预测个人感知压力（PS）。结果表明，可以通过默认模型网络和显着网络之间的相互作用来预测压力感；它们分别涉及情绪调节和显着性归因。有助于预测模型的关键节点包括主要位于边缘系统和颞叶的区域。至关重要的是，可以将基于固定天数的PS的CPM模型推广到COVID-19大流行期间预测单个PS的水平，这是一个多维的，无法控制的压力状况。两个独立的数据集证明了结果的稳定性。目前的工作不仅扩大了有关PS神经机制的现有知识，而且还可能有助于确定健康人群中的高危人群。基于常规天数的PS的CPM模型可以推广到COVID-19大流行期间预测单个PS的水平，这是一个多维的，无法控制的压力情况。两个独立的数据集证明了结果的稳定性。目前的工作不仅扩大了有关PS神经机制的现有知识，而且还可能有助于确定健康人群中的高危人群。基于常规天数的PS的CPM模型可以推广到COVID-19大流行期间预测单个PS的水平，这是一个多维的，无法控制的压力情况。两个独立的数据集证明了结果的稳定性。目前的工作不仅扩展了有关PS神经机制的现有知识，而且还可能有助于确定健康人群中的高危人群。