基于多模态磁共振影像单双相抑郁情感环路的神经机制研究

The major depression disorders (MDD) and bipolar disorders (BD) are common psychiatric disorders in our society. However, the absence of validated biomarkers has resulted in significant clinical issues, including high misdiagnosis rate and poor treatment outcome. Recent studies suggested that the distinct abnormal patterns in emotional circuit might be a crucial “window” for differentiating MDD and BD patients. Thus, in current project, we segmented and located the core brain areas in emotional circuit by using novel neuroimaging approaches. Then, emotion-related tasks, emotional scales, combined with multi-model MRI image data were used to explore the interactions and regulatory mechanism between the critical nodes in emotional circuit, and the abnormal function mechanism, structure mechanism and the relationship between them. Moreover, we conducted the machine learning and the connectome-base predictive modeling, to accurately distinguish BD from MDD, and to predict emotional function in individual level, respectively. This project might shed light on the specific neural deficit of emotional circuit in MDD and BD, which would benefit current clinical diagnosis and treatment system.

单相抑郁和双相抑郁是常见的情绪障碍。由于没有公认的生物学标记可以作为研究和应用的金标准，导致目前单双相抑郁的临床误诊率高，且治疗效果参差不齐。已有研究表明，情感环路的异常模式很可能是区分单双相抑郁的重要“窗口”。为此，本项目使用最新的方法进行情感环路核心脑区的精确分割与定位。在此基础上，结合多模态磁共振影像、情感量表和情感功能任务的测查，探索单双相抑郁情感环路中关键节点的相互作用和调节机制，情感环路异常的功能机制、结构机制以及它们之间的相互关系。同时基于机器学习方法和神经网络预测模型，尝试实现对抑郁类型的准确区分和个体情感功能的预测。本项目将进一步揭示单、双相抑郁情感环路相关的特异性神经缺陷，为临床客观诊断和精准治疗提供影像学依据。

现阶段抑郁症情感环路的研究得到了广泛关注。然而，单一模态磁共振影像数据的使用缺乏系统性的环路研究，情感环路上非精确的脑区定位等因素限制了对单相、双相抑郁特异性神经机制的发掘。本项目结合神经影像技术与临床评定、量表测量，利用多模态影像技术多角度探寻单双相抑郁的神经环路特性。通过研究情感环路的异常表征，情感环路的结构连接和功能连接间的相互作用，情感环路关键脑区的相互作用，进而识别区分单相抑郁和双相抑郁患者的特异性的新的神经影像学标记，揭示了单相、双相抑郁情感环路异常神经病理基础的异同点。研究结果有助于解析抑郁障碍的神经环路作用机制，为单、双相抑郁症患者的诊断和治疗提供理论基础。