Dinh Christoph, Esch Lorenz, Rühle Johannes, Bollmann Steffen, Güllmar Daniel, Baumgarten Daniel, Hämäläinen Matti S, Haueisen Jens
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital - Massachusetts Institute of Technology - Harvard Medical School, 149 13th St., Charlestown, MA, 02129, USA.
Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany.
Brain Topogr. 2018 Jan;31(1):125-128. doi: 10.1007/s10548-017-0586-7. Epub 2017 Sep 6.
Magnetoencephalography (MEG) and electroencephalography provide a high temporal resolution, which allows estimation of the detailed time courses of neuronal activity. However, in real-time analysis of these data two major challenges must be handled: the low signal-to-noise ratio (SNR) and the limited time available for computations. In this work, we present real-time clustered multiple signal classification (RTC-MUSIC) a real-time source localization algorithm, which can handle low SNRs and can reduce the computational effort. It provides correlation information together with sparse source estimation results, which can, e.g., be used to identify evoked responses with high sensitivity. RTC-MUSIC clusters the forward solution based on an anatomical brain atlas and optimizes the scanning process inherent to MUSIC approaches. We evaluated RTC-MUSIC by analyzing MEG auditory and somatosensory data. The results demonstrate that the proposed method localizes sources reliably. For the auditory experiment the most dominant correlated source pair was located bilaterally in the superior temporal gyri. The highest activation in the somatosensory experiment was found in the contra-lateral primary somatosensory cortex.
脑磁图（MEG）和脑电图提供了高时间分辨率，这使得能够估计神经元活动的详细时间进程。然而，在对这些数据进行实时分析时，必须应对两个主要挑战：低信噪比（SNR）和有限的计算时间。在这项工作中，我们提出了实时聚类多重信号分类（RTC-MUSIC），一种实时源定位算法，它可以处理低信噪比并减少计算量。它提供相关信息以及稀疏源估计结果，例如可用于以高灵敏度识别诱发反应。RTC-MUSIC基于解剖学脑图谱对正向解进行聚类，并优化MUSIC方法固有的扫描过程。我们通过分析MEG听觉和体感数据对RTC-MUSIC进行了评估。结果表明，所提出的方法能够可靠地定位源。在听觉实验中，最主要的相关源对双侧位于颞上回。在体感实验中，最高激活出现在对侧初级体感皮层。
