The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke

Q4 Neuroscience
Erin L. Meier , Lisa D. Bunker , Hana Kim , Alexandra Zezinka Durfee , Victoria Tilton-Bolowsky , Voss Neal , Argye E. Hillis
{"title":"The effects of protocol factors and participant characteristics on functional near-infrared spectroscopy data quality after stroke","authors":"Erin L. Meier ,&nbsp;Lisa D. Bunker ,&nbsp;Hana Kim ,&nbsp;Alexandra Zezinka Durfee ,&nbsp;Victoria Tilton-Bolowsky ,&nbsp;Voss Neal ,&nbsp;Argye E. Hillis","doi":"10.1016/j.ynirp.2025.100276","DOIUrl":null,"url":null,"abstract":"<div><div>Functional Near-Infrared Spectroscopy (fNIRS) is an emerging neurotechnology that has several advantages over fMRI, but questions remain about factors that affect data quality and activity in stroke survivors. We examined the effect of protocol factors (Aim 1) and participant characteristics (Aim 2) on raw fNIRS signal quality and tested associations between quality control metrics and brain activity and connectivity (Aim 3) in a sample of 107 individuals with a history of left or right hemisphere stroke. Participants completed tasks that varied by cognitive and motor speech demands (from low to high): Resting State, Discourse Comprehension, and Picture Naming. Scalp-coupling indices, peak spectral power values, and number of bad channels from each task were extracted from the Quality Testing of Near Infrared Scans (QT-NIRS) toolbox (Montero-Hernandez and Pollonini, 2020) and used to index raw data quality. Data quality did not vary by session location or protocol experience, but all data quality metrics from Picture Naming were significantly lower than those from the other tasks. fNIRS signals were generally worse for Black women compared to Black men and White individuals regardless of gender. No significant associations between the raw fNIRS signal quality and Resting State functional connectivity were found. However, relative changes in Picture Naming hemoglobin concentrations were associated with scalp-coupling indices for certain channels. These results highlight the need for careful data preprocessing of already collected data and a systematic approach in future studies to mitigate inherent biases of optical instruments, thereby enhancing the inclusion of underrepresented groups in neuroscience research.</div></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"5 3","pages":"Article 100276"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroimage. Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666956025000443","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Neuroscience","Score":null,"Total":0}
引用次数: 0

Abstract

Functional Near-Infrared Spectroscopy (fNIRS) is an emerging neurotechnology that has several advantages over fMRI, but questions remain about factors that affect data quality and activity in stroke survivors. We examined the effect of protocol factors (Aim 1) and participant characteristics (Aim 2) on raw fNIRS signal quality and tested associations between quality control metrics and brain activity and connectivity (Aim 3) in a sample of 107 individuals with a history of left or right hemisphere stroke. Participants completed tasks that varied by cognitive and motor speech demands (from low to high): Resting State, Discourse Comprehension, and Picture Naming. Scalp-coupling indices, peak spectral power values, and number of bad channels from each task were extracted from the Quality Testing of Near Infrared Scans (QT-NIRS) toolbox (Montero-Hernandez and Pollonini, 2020) and used to index raw data quality. Data quality did not vary by session location or protocol experience, but all data quality metrics from Picture Naming were significantly lower than those from the other tasks. fNIRS signals were generally worse for Black women compared to Black men and White individuals regardless of gender. No significant associations between the raw fNIRS signal quality and Resting State functional connectivity were found. However, relative changes in Picture Naming hemoglobin concentrations were associated with scalp-coupling indices for certain channels. These results highlight the need for careful data preprocessing of already collected data and a systematic approach in future studies to mitigate inherent biases of optical instruments, thereby enhancing the inclusion of underrepresented groups in neuroscience research.
方案因素和参与者特征对脑卒中后功能近红外光谱数据质量的影响
功能近红外光谱(fNIRS)是一种新兴的神经技术,与功能磁共振成像相比有许多优势,但影响中风幸存者数据质量和活动的因素仍然存在问题。我们研究了方案因素(Aim 1)和参与者特征(Aim 2)对原始fNIRS信号质量的影响,并测试了质量控制指标与大脑活动和连通性(Aim 3)之间的关联,样本包括107名有左半球或右半球卒中史的个体。参与者完成了由认知和运动语言需求(从低到高)不同的任务:静息状态、话语理解和图片命名。从近红外扫描质量测试(QT-NIRS)工具箱(Montero-Hernandez and Pollonini, 2020)中提取每个任务的头皮耦合指数、峰值光谱功率值和坏通道数量,并用于索引原始数据质量。数据质量不会因会话位置或协议经验而变化,但是来自图片命名的所有数据质量指标明显低于来自其他任务的数据质量指标。与黑人男性和白人相比,黑人女性的近红外光谱信号普遍较差,无论性别如何。未发现原始fNIRS信号质量与静息状态功能连接之间存在显著关联。然而,图像命名血红蛋白浓度的相对变化与某些通道的头皮偶联指数有关。这些结果强调了在未来的研究中需要对已经收集的数据进行仔细的数据预处理,并采用系统的方法来减轻光学仪器的固有偏差,从而增强神经科学研究中代表性不足群体的纳入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Neuroimage. Reports
Neuroimage. Reports Neuroscience (General)
CiteScore
1.90
自引率
0.00%
发文量
0
审稿时长
87 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信