Computational Brain Dynamics Team, RIKEN Center for Advanced Intelligence Project, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619-0288, Japan; Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619-0288, Japan.
Technology Research Laboratory, Shimadzu Corporation, 3-9-4 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0237, Japan.
Neuroimage. 2023 Aug 15;277:120257. doi: 10.1016/j.neuroimage.2023.120257. Epub 2023 Jun 29.
An optically pumped magnetometer (OPM) is a new generation of magnetoencephalography (MEG) devices that is small, light, and works at room temperature. Due to these characteristics, OPMs enable flexible and wearable MEG systems. On the other hand, if we have a limited number of OPM sensors, we need to carefully design their sensor arrays depending on our purposes and regions of interests (ROIs). In this study, we propose a method that designs OPM sensor arrays for accurately estimating the cortical currents at the ROIs. Based on the resolution matrix of minimum norm estimate (MNE), our method sequentially determines the position of each sensor to optimize its inverse filter pointing to the ROIs and suppressing the signal leakage from the other areas. We call this method the Sensor array Optimization based on Resolution Matrix (SORM). We conducted simple and realistic simulation tests to evaluate its characteristics and efficacy for real OPM-MEG data. SORM designed the sensor arrays so that their leadfield matrices had high effective ranks as well as high sensitivities to ROIs. Although SORM is based on MNE, the sensor arrays designed by SORM were effective not only when we estimated the cortical currents by MNE but also when we did so by other methods. With real OPM-MEG data we confirmed its validity for real data. These analyses suggest that SORM is especially useful when we want to accurately estimate ROIs' activities with a limited number of OPM sensors, such as brain-machine interfaces and diagnosing brain diseases.
光学泵浦磁强计（OPM）是新一代的脑磁图（MEG）设备，具有体积小、重量轻、工作在室温下等特点。由于这些特点，OPM 使 MEG 系统变得灵活和可穿戴。另一方面，如果我们的 OPM 传感器数量有限，我们需要根据我们的目的和感兴趣区域（ROI）仔细设计它们的传感器阵列。在这项研究中，我们提出了一种方法，用于设计 OPM 传感器阵列，以准确估计 ROI 处的皮质电流。基于最小范数估计（MNE）的分辨率矩阵，我们的方法依次确定每个传感器的位置，以优化其指向 ROI 的逆滤波器，并抑制来自其他区域的信号泄漏。我们称这种方法为基于分辨率矩阵的传感器阵列优化（SORM）。我们进行了简单而现实的模拟测试，以评估其特征和对真实 OPM-MEG 数据的功效。SORM 设计的传感器阵列使它们的导联矩阵具有较高的有效秩以及对 ROI 的较高灵敏度。虽然 SORM 是基于 MNE 的，但由 SORM 设计的传感器阵列不仅在我们通过 MNE 估计皮质电流时有效，而且在我们通过其他方法进行估计时也有效。通过真实的 OPM-MEG 数据，我们证实了它对真实数据的有效性。这些分析表明，当我们希望用有限数量的 OPM 传感器（如脑机接口和诊断脑疾病）准确估计 ROI 的活动时，SORM 特别有用。
