University of Illinois at Urbana-Champaign, Department of Psychology, Champaign, United States.
Boston University, Department of Psychological and Brain Sciences, Boston, United States.
Neuroimage. 2022 Nov 1;261:119520. doi: 10.1016/j.neuroimage.2022.119520. Epub 2022 Jul 25.
Functional near-infrared spectroscopy (fNIRS) is increasingly used to study brain function in infants, but the development and standardization of analysis techniques for use with infant fNIRS data have not paced other technical advances. Here we quantify and compare the effects of different methods of analysis of infant fNIRS data on two independent fNIRS datasets involving 6-9-month-old infants and a third simulated infant fNIRS dataset. With each, we contrast results from a traditional, fixed-array analysis with several functional channel of interest (fCOI) analysis approaches. In addition, we tested the effects of varying the number and anatomical location of potential data channels to be included in the fCOI definition. Over three studies we find that fCOI approaches are more sensitive than fixed-array analyses, especially when channels of interests were defined within-subjects. Applying anatomical restriction and/or including multiple channels in the fCOI definition does not decrease and in some cases increases sensitivity of fCOI methods. Based on these results, we recommend that researchers consider employing fCOI approaches to the analysis of infant fNIRS data and provide some guidelines for choosing between particular fCOI approaches and settings for the study of infant brain function and development.
功能近红外光谱（fNIRS）越来越多地用于研究婴儿的大脑功能，但用于婴儿 fNIRS 数据的分析技术的开发和标准化并没有跟上其他技术的进步。在这里，我们量化并比较了不同的婴儿 fNIRS 数据分析方法对两个独立的婴儿 fNIRS 数据集（涉及 6-9 个月大的婴儿）和第三个模拟婴儿 fNIRS 数据集的影响。对于每个数据集，我们将传统的固定阵列分析与几种功能通道感兴趣（fCOI）分析方法的结果进行对比。此外，我们还测试了在 fCOI 定义中包含不同数量和解剖位置的潜在数据通道的效果。通过三项研究，我们发现 fCOI 方法比固定阵列分析更敏感，尤其是在感兴趣的通道在个体内定义时。应用解剖限制和/或在 fCOI 定义中包含多个通道不会降低，在某些情况下甚至会增加 fCOI 方法的敏感性。基于这些结果，我们建议研究人员考虑采用 fCOI 方法来分析婴儿 fNIRS 数据，并为研究婴儿大脑功能和发育提供一些选择特定 fCOI 方法和设置的指南。
