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How to Calculate and Validate Inter-brain Synchronization in a fNIRS Hyperscanning Study
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对fNIRS-fMRI可靠性评估的基于表面的整合方法.

Augusto Bonilauri1, Alice Pirastru1, Francesca Sangiuliano Intra2

  • 1Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy; IRCCS Fondazione Don Carlo Gnocchi ONLUS, 20148 Milan, Italy.

Journal of neuroscience methods
|August 25, 2023
PubMed
概括

这项研究引入了一种新方法,用于整合功能近红外光谱 (fNIRS) 和功能MRI (fMRI) 数据. 这种新的方法显示了fNIRS和fMRI之间的良好的空间和时间一致性,支持其在生态环境中的使用.

关键词:
功能性磁共振成像技术 功能性磁共振成像技术功能性近红外光谱学近红外光谱学康复 康复 康复 康复空间协议 空间协议基于表面的集成.时间相关性 时间相关性

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科学领域:

  • 神经科学是一个神经科学.
  • 生物医学工程 生物医学工程

背景情况:

  • 整合功能近红外光谱 (fNIRS) 和功能核磁共振 (fMRI) 对于全面的脑活动分析至关重要.
  • 目前的整合方法缺乏标准化,导致空间协议和时间相关性评估中的可重复性问题.

研究的目的:

  • 提出和验证一种用于整合fNIRS和fMRI数据在皮层表面的新方法.
  • 提高fNIRS和fMRI之间的空间协议和时间相关性分析的可复制性.

主要方法:

  • 开发了一种新的方法,将主体和组级的源地图投射到皮质表面的网格上.
  • 定义的解剖学上受限制的功能性兴趣区域 (acfROI) 用于数据集成.
  • 使用子系数量化空间安排,使用皮尔森相关系数量化时间相关性.

主要成果:

  • 对主体层面的分析显示,BOLD与HbO2.2的空间一致性为中等至实质性 (子系数0.43-0.64).
  • 组级结果显示出强烈的时间相关性 (0.95-0.98对于BOLD与HbO2; -0.91到-0.94对于BOLD与HbR).
  • 一些实例显示,在主题层面上,BOLD与HbR之间缺乏空间协议.

结论:

  • 拟议的方法有效地整合了fNIRS和fMRI数据,通过将源地图投射到皮质表面.
  • 结果表明fNIRS和fMRI信号之间存在显著的空间和时间对应.
  • 这种方法支持在生态环境中使用fNIRS,例如纵向监测大脑活动.