Space-Time-Frequency Multi-Sensor Analysis for Motor Cortex Localization Using Magnetoencephalography
Space-Time-Frequency Multi-Sensor Analysis for Motor Cortex Localization Using Magnetoencephalography
复制标题
DOI：
10.3390/s20092706
复制
发表时间：
2020-05-01
期刊：
影响因子：
3.9
通讯作者：
Aksenova, Tetiana
中科院分区：
文献类型：
--
作者：
Auboiroux, Vincent;Larzabal, Christelle;Aksenova, Tetiana
脑源成像和时频图（TFM）是磁/脑电图（M/EEG）成像中常用的方法。然而，这些方法受到重要的限制。源成像是基于一个不适定的反问题，导致不稳定的源定位解决方案，具有有限的能力，本地化高频振荡，并失去其鲁棒性的诱导响应（定义不清的触发）。TFM的缺点是它涉及对来自多个频带和来自共定位传感器的信号的独立分析。在本文中，基于回归的多传感器空间-时间-频率分析（MSA）的方法，它集成了共定位的传感器和/或多频信息，提出。为了估计任务特定的大脑激活，MSA使用交叉验证的，移位的，多个皮尔逊相关性，从时频转换的大脑信号和刺激的二进制信号计算。结果从传感器空间投射到皮质表面上。为了评估MSA性能，所提出的方法进行了比较，加权最小范数估计（wMNE）源成像方法，在空间选择性和鲁棒性对一个不明确的触发。对14名受试者进行了两种运动任务（手指敲击和肘部屈曲/伸展）的脑磁图（MEG）记录。特别是，我们的研究结果表明，MSA的方法提供了良好的定位性能相比，wMNE和统计上显着的改善对定义不清的触发器的鲁棒性。
Brain source imaging and time frequency mapping (TFM) are commonly used in magneto/electro encephalography (M/EEG) imaging. However, these methods suffer from important limitations. Source imaging is based on an ill-posed inverse problem leading to instability of source localization solutions, has a limited capacity to localize high frequency oscillations and loses its robustness for induced responses (ill-defined trigger). The drawback of TFM is that it involves independent analysis of signals from a number of frequency bands, and from co-localized sensors. In the present article, a regression-based multi-sensor space-time-frequency analysis (MSA) approach, which integrates co-localized sensors and/or multi-frequency information, is proposed. To estimate task-specific brain activations, MSA uses cross-validated, shifted, multiple Pearson correlation, calculated from the time-frequency transformed brain signal and the binary signal of stimuli. The results are projected from the sensor space onto the cortical surface. To assess MSA performance, the proposed method was compared to the weighted minimum norm estimate (wMNE) source imaging method, in terms of spatial selectivity and robustness against an ill-defined trigger. Magnetoencephalography (MEG) recordings were performed in fourteen subjects during two motor tasks: finger tapping and elbow flexion/extension. In particular, our results show that the MSA approach provides good localization performance when compared to wMNE and statistically significant improvement of robustness against ill-defined trigger.