性情
心理学
脑岛
重性抑郁障碍
临床心理学
沉思
功能磁共振成像
发展心理学
精神科
心情
神经科学
认知
社会心理学
人格
作者
Huawang Wu,Yingjun Zheng,Qianqian Zhan,Jie Dong,Hongjun Peng,Jinguo Zhai,Jingping Zhao,Shenglin She,Chao Wu
标识
DOI:10.1017/s0033291719003647
摘要
Abstract Background Affective temperaments have been considered antecedents of major depressive disorder (MDD). However, little is known about how the covariation between alterations in brain activity and distinct affective temperaments work collaboratively to contribute to MDD. Here, we focus on the insular cortex, a critical hub for the integration of subjective feelings, emotions, and motivations, to examine the neural correlates of affective temperaments and their relationship to depressive symptom dimensions. Methods Twenty-nine medication-free patients with MDD and 58 healthy controls underwent magnetic resonance imaging scanning and completed the Temperament Evaluation of Memphis, Pisa, Paris and San Diego (TEMPS). Patients also received assessments of the Hamilton Depression Rating Scale (HDRS). We used multivariate analyses of partial least squares regression and partial correlation analyses to explore the associations among the insular activity, affective temperaments, and depressive symptom dimensions. Results A profile (linear combination) of increased fractional amplitude of low-frequency fluctuations (fALFF) of the anterior insular subregions (left dorsal agranular–dysgranular insula and right ventral agranuar insula) was positively associated with an affective-temperament (depressive, irritable, anxious, and less hyperthymic) profile. The covariation between the insula-fALFF profile and the affective-temperament profile was significantly correlated with the sleep disturbance dimension (especially the middle and late insomnia scores) in the medication-free MDD patients. Conclusions The resting-state spontaneous activity of the anterior insula and affective temperaments collaboratively contribute to sleep disturbances in medication-free MDD patients. The approach used in this study provides a practical way to explore the relationship of multivariate measures in investigating the etiology of mental disorders.
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