More than just statics: temporal dynamics of intrinsic brain activity predicts the suicidal ideation in depressed patients

心理学 神经影像学 颞叶皮质 功能磁共振成像 神经科学 重性抑郁障碍 扣带回前部 自杀意念 颞叶 颞中回 大脑活动与冥想 内科学 听力学 毒物控制 医学 脑电图 认知 癫痫 伤害预防 环境卫生
作者
Jian Li,Xujun Duan,Qian Cui,Huafu Chen,Wei Liao
出处
期刊:Psychological Medicine [Cambridge University Press]
卷期号:49 (5): 852-860 被引量:171
标识
DOI:10.1017/s0033291718001502
摘要

Abstract Background Major depressive disorder (MDD) is associated with high risk of suicide. Conventional neuroimaging works showed abnormalities of static brain activity and connectivity in MDD with suicidal ideation (SI). However, little is known regarding alterations of brain dynamics. More broadly, it remains unclear whether temporal dynamics of the brain activity could predict the prognosis of SI. Methods We included MDD patients ( n = 48) with and without SI and age-, gender-, and education-matched healthy controls ( n = 30) who underwent resting-state functional magnetic resonance imaging. We first assessed dynamic amplitude of low-frequency fluctuation (dALFF) – a proxy for intrinsic brain activity (iBA) – using sliding-window analysis. Furthermore, the temporal variability (dynamics) of iBA was quantified as the variance of dALFF over time. In addition, the prediction of the severity of SI from temporal variability was conducted using a general linear model. Results Compared with MDD without SI, the SI group showed decreased brain dynamics (less temporal variability) in the dorsal anterior cingulate cortex, the left orbital frontal cortex, the left inferior temporal gyrus, and the left hippocampus. Importantly, these temporal variabilities could be used to predict the severity of SI ( r = 0.43, p = 0.03), whereas static ALFF could not in the current data set. Conclusions These findings suggest that alterations of temporal variability in regions involved in executive and emotional processing are associated with SI in MDD patients. This novel predictive model using the dynamics of iBA could be useful in developing neuromarkers for clinical applications.

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