静态和动态的跨网络功能连接显示了精神分裂症患者的升
Natalia Maksymchuk1, Juan R Bustillo2, Daniel H Mathalon3,4
1Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
bioRxiv : the preprint server for biology
|July 1, 2024
概括
精神分裂症患者表现出改变的大脑连接模式. 一种新的方法,网络间连接 (ICE),显示SZ患者的随机性更高.
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.
- 计算生物学 计算生物学
背景情况:
- 精神分裂症 (SZ) 的特征是大脑中异常的静态和动态功能连接.
- 了解大脑网络的改变对于诊断和治疗SZ至关重要.
- 现有的方法可能无法完全捕捉大脑连接的复杂,动态性质.
研究的目的:
- 引入和验证一种新的方法,即网络间连接 (ICE),用于评估大脑连接.
- 调查SZ患者和健康对照 (HC) 之间的静态和动态ICE差异.
- 探索ICE作为心理健康状况诊断工具的潜力.
主要方法:
- 对151名SZ患者和160名HC患者的fMRI数据的分析.
- 在多个大脑网络中计算静态和动态的网络间连接 (ICE).
- 应用C-平均值模糊集群和k-平均值集群来分析ICE模式.
主要成果:
- 在SZ患者和HC患者之间在各种大脑网络 (SC,AUD,SM,VIS,CC,DMN,CB) 中发现了连接异质性的显著差异.
- 与HC相比,SZ患者表现出较高的ICE,这表明与HC相比,时间变化的连接性具有更高的随机性.
- 聚类分析揭示了SZ患者和HC患者之间功能相关性和占用率的独特模式.
结论:
- 拟议的ICE措施为了解健康和疾病中的大脑状态提供了一个新的框架.
- 动态ICE分析表明,SZ患者很难过渡到更专注的大脑连接模式.
- 作为一种先进的精神健康状况诊断方法,ICE具有前途.
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