Klein Franziska, Lührs Michael, Benitez-Andonegui Amaia, Roehn Pauline, Kranczioch Cornelia
Carl von Ossietzky University of Oldenburg, Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Oldenburg, Germany.
Maastricht University, Faculty of Psychology and Neuroscience, Maastricht, The Netherlands.
Neurophotonics. 2023 Jan;10(1):013503. doi: 10.1117/1.NPh.10.1.013503. Epub 2022 Oct 12.
Functional near-infrared spectroscopy (fNIRS) is a promising tool for neurofeedback (NFB) or brain-computer interfaces (BCIs). However, fNIRS signals are typically highly contaminated by systemic activity (SA) artifacts, and, if not properly corrected, NFB or BCIs run the risk of being based on noise instead of brain activity. This risk can likely be reduced by correcting for SA, in particular when short-distance channels (SDCs) are available. Literature comparing correction methods with and without SDCs is still sparse, specifically comparisons considering single trials are lacking. This study aimed at comparing the performance of SA correction methods with and without SDCs. Semisimulated and real motor task data of healthy older adults were used. Correction methods without SDCs included a simple and a more advanced spatial filter. Correction methods with SDCs included a regression approach considering only the closest SDC and two GLM-based methods, one including all eight SDCs and one using only two selected SDCs as regressors. All methods were compared with data uncorrected for SA and correction performance was assessed with quality measures quantifying signal improvement and spatial specificity at single trial level. All correction methods were found to improve signal quality and enhance spatial specificity as compared with the uncorrected data. Methods with SDCs usually outperformed methods without SDCs. Correction methods without SDCs tended to overcorrect the data. However, the exact pattern of results and the degree of differences observable between correction methods varied between semisimulated and real data, and also between quality measures. Overall, results confirmed that both and are affected by SA and that correction methods with SDCs outperform methods without SDCs. Nonetheless, improvements in signal quality can also be achieved without SDCs and should therefore be given priority over not correcting for SA.
功能近红外光谱技术（fNIRS）是用于神经反馈（NFB）或脑机接口（BCI）的一种很有前景的工具。然而，fNIRS信号通常受到全身活动（SA）伪迹的严重污染，如果不进行适当校正，NFB或BCI就有可能基于噪声而非大脑活动。通过校正SA，这种风险可能会降低，特别是在有短距离通道（SDC）的情况下。比较有无SDC的校正方法的文献仍然很少，特别是缺乏考虑单次试验的比较。本研究旨在比较有无SDC的SA校正方法的性能。使用了健康老年人的半模拟和真实运动任务数据。没有SDC的校正方法包括一个简单的和一个更先进的空间滤波器。有SDC的校正方法包括仅考虑最接近的SDC的回归方法和两种基于广义线性模型（GLM）的方法，一种包括所有八个SDC，另一种仅使用两个选定的SDC作为回归变量。所有方法都与未校正SA的数据进行了比较，并通过在单次试验水平上量化信号改善和空间特异性的质量指标来评估校正性能。与未校正的数据相比，所有校正方法都能提高信号质量并增强空间特异性。有SDC的方法通常优于没有SDC的方法。没有SDC的校正方法往往会过度校正数据。然而，结果的具体模式以及校正方法之间可观察到的差异程度在半模拟数据和真实数据之间以及质量指标之间都有所不同。总体而言，结果证实了两者都受到SA的影响，并且有SDC的校正方法优于没有SDC的方法。尽管如此，没有SDC也可以实现信号质量的改善，因此应该优先于不校正SA。
Zotero 插件
