精神病临床高风险的个体中异常的大脑动态
Jochen Kindler1, Takuya Ishida2, Chantal Michel1
1University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
Schizophrenia bulletin open
|April 12, 2024
概括
患有精神病的临床高风险 (CHR) 个体表现出大脑网络动态的改变,与认知缺陷相关的异常相互作用的时间更长,频率更高. 这些发现凸显了时大脑动态作为精神病发作的潜在预测因素.
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.
- 计算神经科学是一种神经科学.
背景情况:
- 休息状态网络 (RSN) 的功能连接对于理解精神病和临床高风险 (CHR) 状态至关重要.
- 传统的RSN分析侧重于静态网络属性,忽视时间动态.
- 需要新的方法来评估大脑网络相互作用的动态性质.
研究的目的:
- 研究精神病临床高风险 (CHR) 个体的大脑网络的时间动态.
- 为了比较CHR个体和健康对照 (HC) 之间的大脑状态动态.
- 检查神经动力学与CHR个体认知功能之间的关系.
主要方法:
- 在休息状态的功能性MRI数据上对50名CHR个人和33名HC进行了利用能源景观分析.
- 采用双向最大模型来描述大脑状态的持续时间,频率和过渡.
- 在CHR组中评估了神经心理测量和神经动态之间的关联.
主要成果:
- 与HC相比,CHR个体的罕见大脑状态持续时间显著更长,频率更高.
- CHR参与者表现出更高的过渡率到这种异常的大脑状态,包括突出,边缘,默认模式和体运动RSN.
- 从这个大脑状态的过渡与CHR个体的处理速度有显著的相关性.
结论:
- 患有精神病临床高风险的个体表现出改变的时间大脑动态,有利于异常网络协作激活的罕见大脑状态.
- 这种异常的大脑状态与默认模式,突出和边缘网络之间的更频繁和更长时间的相互作用有关.
- 这些动态变化与认知功能障碍有关,并可能预测未来的精神病发作.
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