在当前和缓解的大型抑郁症中,特征和状态类同激活模式的动态
Chengwen Liu1, Emily L Belleau2, Daifeng Dong1
1Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China.
Journal of affective disorders
|May 28, 2023
概括
大型抑郁症 (MDD) 涉及到大脑网络动态的改变. 目前或过去患有MDD的未经药物治疗的个体在默认模式网络 (DMN) 和正面对面网络 (FPN) 连接中表现出明显的模式,表明具有特征性脆弱性.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
- 医疗成像医学成像
背景情况:
- 了解主要抑郁症 (MDD) 中的神经变化对于管理这种反复出现的疾病至关重要.
- 区分特征性 (持久性) 和状态性 (暂时性) 神经变化是关键.
- 本研究研究了当前或过去患有MDD的未经药物治疗的个体的动态功能连接.
研究的目的:
- 研究当前或过去MDD的未经药物治疗的个体的动态功能连接性改变.
- 识别与MDD漏洞相关的特征类神经网络动态.
- 探索大脑网络状态和临床特征 (如反) 之间的关系.
主要方法:
- 分析了当前MDD (cMDD),缓解MDD (rMDD) 和健康对照 (HCs) 患者的休息状态功能磁共振成像 (fMRI) 数据.
- 一种数据驱动的共识聚类技术确定了四个全脑功能连接状态.
- 与临床数据相比,分析了状态主导,入口和过渡频率等指标.
主要成果:
- 当前的MDD (cMDD) 与转移的MDD (rMDD) 和HCs.com相比,显示了默认模式网络 (DMN) 的主导地位和入口的增加,以及前端-平行网络 (FPN) 主导地位的下降.
- 状态1 (DMN主导) 条目与cMDD中的特征反相关.
- 转移性MDD (rMDD) 的特征是增加了FPN条目,MDD两组都表现出增加的FPN到DMN过渡,与特征反有关.
结论:
- 重度抑郁症 (MDD) 的特征是大脑网络动态发生变化,包括增加FPN到DMN的过渡.
- 观察到混合网络的优势减少和状态变化的动态.
- 这些类似特征的大脑网络动态可能表明对发展MDD的脆弱性增加.
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