精神分裂症和情绪障碍中大规模功能网络的异常大脑动态
Takuya Ishida1, Shinichi Yamada1, Kasumi Yasuda2
1Department of Neuropsychiatry, Graduate School of Wakayama Medical University, Wakayama 641-8509, Japan.
NeuroImage. Clinical
|February 12, 2024
概括
与主要抑郁症 (MDD) 和健康对照相比,精神分裂症 (SZ) 显示大脑网络动态受损. 能源景观分析揭示了改变的大脑活动模式和SZ中的过渡,影响认知功能.
科学领域:
- 神经科学是一个神经科学.
- 精神疾病 精神疾病
- 计算精神病学是一种计算精神病学.
背景情况:
- 大规模的大脑网络对于人类的情绪和认知过程至关重要.
- 这些网络中断与精神疾病有关,但具体的作用尚不清楚.
- 研究异常网络动态是理解病理生理学的关键.
研究的目的:
- 阐明精神分裂症 (SZ) 和严重抑郁症 (MDD) 的大规模网络中异常的大脑动态.
- 为了比较SZ,MDD和健康对照 (HC) 之间的网络动态.
- 探索SZ中异常动态和认知功能之间的关联.
主要方法:
- 对大脑活动模式应用的能量景观分析.
- 涉及50名HC患者,36名SZ患者和42名MDD患者.
- 量化持续时间,发生率和在已识别的大脑状态之间轻松过渡.
主要成果:
- 根据默认模式网络 (DMN) 和视觉网络 (VIN) 激活,确定了四个主要的大脑活动模式.
- 与HC和MDD相比,SZ组表现出某些状态的持续时间/发生时间较短,而其他状态的持续时间较长.
- SZ显示了国家之间的过渡容易度增加,与口语流性负面相关.
结论:
- 能源景观分析揭示了SZ和MDD中明显的异常大脑动态.
- 这些发现提供了超越传统分析的SZ和情绪障碍的病理生理机制的见解.
- SZ中的异常动态与认知缺陷有关,特别是口头流.
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