在神经精神疾病中默认模式网络完整性及其与社会功能障碍的关系:规范型建模方法
Simon Braak1, Marianne Oldehinkel2, Maarten Mennes2
1Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Psychiatry, Boelelaan, 1117, Amsterdam, the Netherlands; Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress and Neurodegeneration programs, Amsterdam, the Netherlands.
概括
默认模式网络 (DMN) 的变化在神经精神疾病之间有所不同,但个体偏差不能预测社会功能障碍. 阿尔茨海默病和精神分裂症与健康对照组和严重抑郁症相比,显示出明显的DMN结构和功能差异.
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:
- 默认模式网络 (DMN) 的改变与神经精神疾病和社会功能障碍有关.
- 规范建模提供了一种方法来评估个别的DMN偏差.
研究的目的:
- 调查DMN在皮质厚度,表面积和功能连接性上的个体偏差,跨越精神分裂症,严重抑郁症,阿尔茨海默病和健康对照.
- 为了确定这些DMN偏差是否与社会功能障碍有跨诊断的关联.
主要方法:
- 利用了分别来自329名和317名参与者的结构性和静止状态fMRI数据.
- 使用皮层厚度,表面积和功能连接性的规范模型计算了个体DMN偏差得分.
- 通过社会功能尺度和De Jong-Gierveld孤独度量表来评估社会功能障碍.
主要成果:
- 在DMN偏差得分和社会功能障碍之间没有发现跨诊断关联.
- 与所有其他组相比,阿尔茨海默病患者在DMN皮层厚度上表现出更极端的负偏差.
- 阿尔茨海默病和精神分裂症患者在DMN功能连接中表现出比主要抑郁症和健康对照患者更极端的负面偏差.
结论:
- 规范性建模揭示了在神经精神疾病中明显的个体DMN完整性偏差.
- 这些DMN偏差似乎与社会功能障碍没有跨诊断的联系.
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