Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.
Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy.
Sci Rep. 2019 Sep 6;9(1):12813. doi: 10.1038/s41598-019-49256-0.
Recent studies have highlighted the importance of an accurate individual head model for reliably using high-density electroencephalography (hdEEG) as a brain imaging technique. Correct identification of sensor positions is fundamental for accurately estimating neural activity from hdEEG recordings. We previously introduced a method of automated localization and labelling of hdEEG sensors using an infrared colour-enhanced 3D scanner. Here, we describe an extension of this method, the spatial positioning toolbox for head markers using 3D scans (SPOT3D), which integrates a graphical user interface (GUI). This enables the correction of imprecisions in EEG sensor positioning and the inclusion of additional head markers. The toolbox was validated using 3D scan data collected in four participants wearing a 256-channel hdEEG cap. We quantified the misalignment between the 3D scan and the head shape, and errors in EEG sensor locations. We assessed these parameters after using the automated approach and after manually adjusting its results by means of the GUI. The GUI overcomes the main limitations of the automated method, yielding enhanced precision and reliability of head marker positioning.
最近的研究强调了准确的个体头部模型对于可靠地使用高密度脑电图(hdEEG)作为脑成像技术的重要性。正确识别传感器位置是从 hdEEG 记录中准确估计神经活动的基础。我们之前介绍了一种使用红外彩色增强 3D 扫描仪自动定位和标记 hdEEG 传感器的方法。在这里,我们描述了该方法的扩展,即使用 3D 扫描的头部标记空间定位工具箱(SPOT3D),它集成了图形用户界面(GUI)。这使得可以纠正 EEG 传感器定位的不精确性,并包含其他头部标记。该工具包使用在四名佩戴 256 通道 hdEEG 帽的参与者身上采集的 3D 扫描数据进行了验证。我们量化了 3D 扫描和头部形状之间的不匹配以及 EEG 传感器位置的误差。我们在使用自动方法之后,并通过 GUI 手动调整其结果之后评估了这些参数。GUI 克服了自动方法的主要限制,提高了头部标记定位的精度和可靠性。