fNIRS的可复制性因数据质量,分析管道和研究人员经验而有所不同
Meryem A Yücel1,2, Robert Luke3,4, Rickson C Mesquita5,6
1Boston University, Neurophotonics Center, Boston, MA, USA. mayucel@bu.edu.
Communications biology
|August 4, 2025
概括
功能近红外光谱 (fNIRS) 研究的可复制性正在改善,大多数团队都同意组结果. 然而,个人层面的协议有所不同,这突显出需要在脑成像中更清晰的分析和报告标准.
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
- 认知科学 认知科学
背景情况:
- 脑成像中的复杂数据分析管道需要了解对结果的方法影响.
- 功能近红外光谱 (fNIRS) 是一个不断发展的大脑成像技术,缺乏标准化分析方法,影响可重现性.
- 确保透明度和可重复性对于推进脑成像研究至关重要.
研究的目的:
- 在不同研究小组中评估功能近红外光谱 (fNIRS) 数据分析的可重复性.
- 确定fNIRS数据分析管道中变化的关键来源.
- 为提高fNIRS研究的透明度和可靠性提供建议.
主要方法:
- fNIRS复制性研究中心 (FRESH) 计划涉及38个国际研究小组,分析相同的fNIRS数据集.
- 团队使用自己的分析管道独立处理数据.
- 对团队层面和个人层面的结果的协议被量化.
主要成果:
- 近80%的团队在小组级fNIRS结果上达成共识,特别是在得到充分支持的假设方面.
- 个人级别的协议较低,但随着数据质量提高而有所改善.
- 可变性驱动因素包括处理质量差的数据,响应建模和统计分析方法.
结论:
- 虽然fNIRS分析显示了良好的群体级别可重现性,但存在变化,特别是在个人层面.
- 更高的分析信心和fNIRS经验与更大的协议相关.
- 建立更清晰的方法和报告标准对于提高fNIRS可重现性和可靠性至关重要.
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