默认模式网络功能与结构的低调整与压缩和化相关
Paul J Thomas1, Alex Leow1, Heide Klumpp2
1Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois.
概括
默认模式网络 (DMN) 中的大脑信号对齐在内化障碍患者中减少,并与抑郁症和反有关. 这项研究使用图形信号处理来分析这些条件下的大脑网络功能.
科学领域:
- 神经科学是一个神经科学.
- 图形信号处理 图形信号处理
- 精神病学是一个精神病学.
背景情况:
- 图形信号处理 (GSP) 工具量化大脑功能与白质结构的对齐.
- 这一框架应用于具有内化精神病理 (情绪和焦虑障碍) 的跨诊断队列.
- 这项研究研究了默认模式网络 (DMN) 调整与抑郁症/反症状之间的关系.
研究的目的:
- 应用GSP来分析DMN信号对齐在内部化精神病理.
- 为了确定DMN信号对齐是否与抑郁和反有关.
- 探索DMN功能连接和结构网络拓之间的联系.
主要方法:
- 从60名患者和19名健康对照中获得了扩散权重和静止状态功能性MRI数据.
- 参与者接受了12周的治疗 (SSRI或CBT),并重新评估症状.
- GSP方法量化了与白质结构网络的功能信号对齐.
主要成果:
- 与对照组相比,在内化精神病理的患者中,后部DMN信号对齐性下降.
- 降低信号对齐与基线抑郁和反得分负相关.
- 后部DMN信号对齐与DMN内部与DMN外功能连接的比率相关.
结论:
- 这些发现支持以前关于内化障碍后部DMN连接的文献.
- 这是第一个GSP分析在一个跨诊断队列与内化精神病理.
- 改变的DMN信号对齐可能是抑郁症和反的神经标记.
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