调查功能近红外光谱信号变性:处理管道的作用和任务复杂性
Joshua Dugdale1, Garrett Scott Black1, Jordan Alexander Borrell2
1Bioengineering Program, The University of Kansas - Lawrence Campus, 1450 Jayhawk Blvd, Lawrence, Kansas, 66045, UNITED STATES.
功能近红外光谱 (fNIRS) 分析管道影响大脑激活检测. 在神经康复应用中,区块平均 (BA) 显示出比通用线性模型 (GLM) 更强大的结果.
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:
- 功能近红外光谱 (fNIRS) 是一种非侵入性脑成像技术,越来越多地用于神经康复.
- fNIRS数据中的信号变化,通常是由于不同的处理管道造成的,阻碍了临床翻译.
研究的目的:
- 为了比较两个常见的fNIRS数据处理管道的稳定性:通用线性模型 (GLM) 和块平均化 (BA).
- 评估这些管道在健康成年人中如何检测皮质激活在不同复杂性的任务中.
主要方法:
- 18名健康成年人在简单的手握和复杂的粗体手工灵巧任务中进行了fnirs记录.
- fNIRS数据使用GLM和BA分析管道进行处理.
- 血液动力学反应 (氧化和脱氧血红蛋白) 分析了显著差异.
主要成果:
- 处理管道和任务复杂性都显著影响了血液动力学反应.
- 与一般线性模型 (GLM) 相比,区块平均化 (BA) 产生了更大的激活幅度.
- 复杂的任务比简单的任务引起了更大的皮质激活,BA-Complex显示了不同的结果.
结论:
- 选择fNIRS数据处理管道对与任务相关的大脑活动的检测有很大影响.
- 与GLM相比,区块平均化 (BA) 在检测血液动力学变化方面似乎更敏感.
- 标准化分析管道对于提高fNIRS在神经康复中的可靠性和临床采用至关重要.
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