Department of Microtechnology and Nanoscience, Chalmers University of Technology, Gothenburg, Sweden.
NatMEG, Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
PLoS One. 2018 May 10;13(5):e0191111. doi: 10.1371/journal.pone.0191111. eCollection 2018.
Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject's head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject's head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method.
准确估计脑磁图 (MEG) 信号背后的神经活动需要配准,即确定传感器相对于头部的位置和方向。在现代 MEG 系统中,使用数百个低温超导量子干涉仪 (SQUID) 传感器的阵列来定位一组附在受试者头部的小的、类似磁偶极子的 (头位置指示器,HPI) 线圈。通过准确地了解传感器彼此之间的位置和方向,可以高精度地定位 HPI 线圈,从而确定传感器相对于头部的位置。随着磁场感应技术的进步,例如高温超导量子干涉仪和光泵磁力仪 (OPM),这些技术比低温超导量子干涉仪传感器需要的工作温度更低,头皮上的 MEG 即将出现。为了充分利用头皮上的 MEG 潜力,灵活的传感器阵列是首选。对于此类系统,传统的配准方法是不切实际的,因为传感器之间的相对位置和方向是特定于个体的,因此无法事先知道。在此,我们提出了一种头皮 MEG 传感器配准的方法。我们建议反转传统的配准方法,相对于受试者头部上的 HPI 线圈阵列来定位传感器。我们表明,只要准确地预先了解 HPI 线圈彼此之间的位置,就可以高精度地定位传感器。我们使用传感器和线圈阵列的现实参数和布局对我们的方法进行了模拟。结果表明,配准可以达到亚毫米级的精度,但性能强烈取决于许多因素。准确校准线圈和精确确定线圈相对于彼此的位置和方向至关重要。最后,我们提出了一些方法来解决实际挑战,以进一步改进该方法。