Pollonini Luca, Bortfeld Heather, Oghalai John S
Department of Engineering Technology, University of Houston, 4734 Calhoun Road, Houston, TX 77204, USA.
Department of Psychological Sciences, University of California, Merced, 5200 N. Lake Road, Merced, CA 95343, USA.
Biomed Opt Express. 2016 Nov 15;7(12):5104-5119. doi: 10.1364/BOE.7.005104. eCollection 2016 Dec 1.
Recent functional near-infrared spectroscopy (fNIRS) instrumentation encompasses several dozen of optodes to enable reconstructing a hemodynamic image of the entire cerebral cortex. Despite its potential clinical applicability, widespread use of fNIRS with human subjects is currently limited by unresolved issues, namely the collection from the entirety of optical channels of signals with a signal-to-noise ratio (SNR) sufficient to carry out a reliable estimation of cortical hemodynamics, and the considerable amount of time that placing numerous optodes take with individuals for whom achieving good optical coupling to the scalp is difficult due to thick or dark hair. To address these issues, we developed a numerical method that: 1) at the channel level, computes an objective measure of the signal-to-noise ratio (SNR) related to its optical coupling to the scalp, akin to electrode conductivity used in electroencephalography (EEG), and 2) at the optode level, determines and displays the coupling status of all individual optodes in real time on a model of a human head. This approach aims to shorten the pre-acquisition preparation time by visually displaying which optodes require further adjustment for optimum scalp coupling, and to maximize the signal-to-noise ratio (SNR) of all optical channels contributing to the functional hemodynamic mapping. The methodology described in this paper has been implemented in a software tool named PHOEBE (placing headgear optodes efficiently before experimentation) that is freely available for use by the fNIRS community.
最近的功能近红外光谱（fNIRS）仪器包含几十个体积描记器，以实现对整个大脑皮层血流动力学图像的重建。尽管其具有潜在的临床适用性，但目前，fNIRS在人体受试者中的广泛应用受到一些尚未解决的问题的限制，即从所有光学通道收集具有足够信噪比（SNR）的信号，以便对皮层血流动力学进行可靠估计，以及由于头发浓密或颜色深，为那些难以实现与头皮良好光学耦合的个体放置大量体积描记器需要花费大量时间。为了解决这些问题，我们开发了一种数值方法，该方法：1）在通道层面，计算与其与头皮的光学耦合相关的信噪比（SNR）的客观度量，类似于脑电图（EEG）中使用的电极电导率；2）在体积描记器层面，在人头模型上实时确定并显示所有单个体积描记器的耦合状态。这种方法旨在通过直观显示哪些体积描记器需要进一步调整以实现最佳头皮耦合，从而缩短采集前的准备时间，并最大化所有有助于功能血流动力学映射的光学通道的信噪比（SNR）。本文所述的方法已在一个名为PHOEBE（实验前高效放置头戴式体积描记器）的软件工具中实现，该工具可供fNIRS社区免费使用。
