白质内在连接网络在静止状态和任务期间的证据:一项大规模研究和模板
Vaibhavi S Itkyal1,2,3, Armin Iraji2,4,5,6, Kyle M Jensen2,6
1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
Network neuroscience (Cambridge, Mass.)
|November 10, 2025
概括
这项研究引入了一个新的白质 (WM) 内在连接网络 (ICN) 模板,来自超过10万个fMRI扫描. 这个模板有助于理解大脑功能,并揭示了健康对照组和精神分裂症患者之间的连接差异.
科学领域:
- 神经成像是一种神经成像.
- 大脑的连接性 大脑的连接性
- 白物质研究 白物质研究
背景情况:
- 了解白质 (WM) 功能连接对于大脑功能和功能障碍研究至关重要.
- 现有的方法往往侧重于灰色物质,使WM连接的探索较少.
- 一个全面的理解需要分析WM和灰色物质 (GM) 网络.
研究的目的:
- 开发一个新的WM内在连接网络 (ICN) 模板.
- 使用静止状态和基于任务的fMRI数据分析WM和GM ICNs.
- 研究健康对照组和精神分裂症患者之间功能连接的差异.
主要方法:
- 在超过10万个fMRI扫描中使用空间约束的独立组件分析 (scICA) 开发了一个WM ICN模板.
- 组合WM模板与GM ICN模板进行分析.
- 将模板应用于静态fMRI (rs-fMRI) 和基于任务的fMRI数据集 (BSNIP2和MCIC).
主要成果:
- 与转基因ICN相比,确定了97个强大的WM ICN,具有独特的空间地图和更高的频率配置文件.
- 揭示了WM ICNs中的模块化结构以及WM和GM模块之间的相互作用.
- 在基于任务的fMRI期间观察到WM ICNs中的与事件相关的BOLD信号,以及健康对照组和精神分裂症患者之间的静态功能网络连接 (sFNC) 的显著差异.
结论:
- 新的WM NeuroMark模板和自动化管道为WM连接研究提供了强大的工具.
- 这些发现突出了明确的WM和GM网络特征及其在精神分裂症中的变化.
- 这种资源有助于在各种神经成像数据集中对WM连接的高级分析.
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