Afnan Jawata, von Ellenrieder Nicolás, Lina Jean-Marc, Pellegrino Giovanni, Arcara Giorgio, Cai Zhengchen, Hedrich Tanguy, Abdallah Chifaou, Khajehpour Hassan, Frauscher Birgit, Gotman Jean, Grova Christophe
Integrated Program in Neuroscience, McGill University, Montréal, Québec H3A 1A1, Canada; Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec H3A 2B4, Canada; Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec H3A 2B4, Canada.
Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Québec H3A 2B4, Canada.
Neuroimage. 2023 Jul 1;274:120158. doi: 10.1016/j.neuroimage.2023.120158. Epub 2023 May 5.
Magnetoencephalography (MEG) is a widely used non-invasive tool to estimate brain activity with high temporal resolution. However, due to the ill-posed nature of the MEG source imaging (MSI) problem, the ability of MSI to identify accurately underlying brain sources along the cortical surface is still uncertain and requires validation.
We validated the ability of MSI to estimate the background resting state activity of 45 healthy participants by comparing it to the intracranial EEG (iEEG) atlas (https://mni-open-ieegatlas.
mcgill.ca/). First, we applied wavelet-based Maximum Entropy on the Mean (wMEM) as an MSI technique. Next, we converted MEG source maps into intracranial space by applying a forward model to the MEG-reconstructed source maps, and estimated virtual iEEG (ViEEG) potentials on each iEEG channel location; we finally quantitatively compared those with actual iEEG signals from the atlas for 38 regions of interest in the canonical frequency bands.
The MEG spectra were more accurately estimated in the lateral regions compared to the medial regions. The regions with higher amplitude in the ViEEG than in the iEEG were more accurately recovered. In the deep regions, MEG-estimated amplitudes were largely underestimated and the spectra were poorly recovered. Overall, our wMEM results were similar to those obtained with minimum norm or beamformer source localization. Moreover, the MEG largely overestimated oscillatory peaks in the alpha band, especially in the anterior and deep regions. This is possibly due to higher phase synchronization of alpha oscillations over extended regions, exceeding the spatial sensitivity of iEEG but detected by MEG. Importantly, we found that MEG-estimated spectra were more comparable to spectra from the iEEG atlas after the aperiodic components were removed.
This study identifies brain regions and frequencies for which MEG source analysis is likely to be reliable, a promising step towards resolving the uncertainty in recovering intracerebral activity from non-invasive MEG studies.
脑磁图（MEG）是一种广泛应用的非侵入性工具，用于以高时间分辨率估计大脑活动。然而，由于脑磁图源成像（MSI）问题的不适定性，MSI沿皮质表面准确识别潜在脑源的能力仍不确定，需要验证。
与内侧区域相比，外侧区域的MEG频谱估计更准确。ViEEG中振幅高于iEEG的区域恢复得更准确。在深部区域，MEG估计的振幅被大大低估，频谱恢复不佳。总体而言，我们的wMEM结果与使用最小范数或波束形成器源定位获得的结果相似。此外，MEG在很大程度上高估了α波段的振荡峰值，尤其是在前部和深部区域。这可能是由于α振荡在扩展区域的相位同步性更高，超过了iEEG的空间敏感性，但能被MEG检测到。重要的是，我们发现去除非周期性成分后，MEG估计的频谱与iEEG图谱的频谱更具可比性。
本研究确定了MEG源分析可能可靠的脑区和频率，这是朝着解决从非侵入性MEG研究中恢复脑内活动的不确定性迈出的有希望的一步。
