Adler Amir, Wax Mati, Pantazis Dimitrios
Braude College of Enginnering and with the McGovern Institute for Brain Research at MIT.
Technion.
Biomed Signal Process Control. 2024 Apr;90. doi: 10.1016/j.bspc.2023.105796. Epub 2023 Dec 9.
A popular approach for modeling brain activity in MEG and EEG is based on a small set of current dipoles, where each dipole represents the combined activation of a local area of the brain. Here, we address the problem of multiple dipole localization with a novel solution called Alternating Projection (AP). The AP solution is based on minimizing the least-squares (LS) criterion by transforming the multi-dimensional optimization required for direct LS solution, to a sequential and iterative solution in which one source at a time is localized, while keeping the other sources fixed. Results from simulated, phantom, and human MEG data demonstrated the high accuracy of the AP method, with superior localization results than popular scanning methods from the multiple-signal classification (MUSIC) and beamformer families. In addition, the AP method was more robust to forward model errors resulting from head rotations and translations, as well as different cortex tessellation grids for the forward and inverse solutions, with consistently higher localization accuracy in low SNR and highly correlated sources.
一种用于对脑磁图（MEG）和脑电图（EEG）中的大脑活动进行建模的常用方法基于一小组电流偶极子，其中每个偶极子代表大脑局部区域的联合激活。在此，我们用一种名为交替投影（AP）的新解决方案来解决多偶极子定位问题。AP解决方案基于通过将直接最小二乘（LS）解所需的多维优化转换为一种顺序迭代解来最小化最小二乘（LS）准则，在该迭代解中，一次定位一个源，同时保持其他源固定。来自模拟、模型和人体MEG数据的结果证明了AP方法的高精度，其定位结果优于多信号分类（MUSIC）和波束形成器家族中的常用扫描方法。此外，AP方法对因头部旋转和平移以及正反解的不同皮质细分网格而产生的正向模型误差更具鲁棒性，在低信噪比和高度相关源的情况下始终具有更高的定位精度。
