Lin Fa-Hsuan, Witzel Thomas, Hämäläinen Matti S., Nummenmaa Aapo
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada
Magnetoencephalography (MEG) is directly sensitive to postsynaptic neuronal activity with the millisecond temporal resolution. MEG is ideally to complement functional MRI (fMRI), which measures hemodynamic responses secondary to neuronal activity with the millimeter spatial resolution, for noninvasive imaging of human brain function. Here, using the Minimum-Norm Estimate as an example, we review how fMRI can be integrated with MEG (and electroencephalography, EEG) source modeling and summarize potential advantages and pitfalls of this data fusion technique. Neurovascular coupling as the physiological basis for MEG/EEG/fMRI integration is also discussed. Ultimately, we expect to develop multimodal MEG/EEG/fMRI neuroimaging methodology for characterizing spatiotemporal functional connectivity in large-scale neural networks of the human brain with high sensitivity and accuracy.
脑磁图（MEG）对突触后神经元活动具有直接敏感性，具有毫秒级的时间分辨率。MEG非常适合补充功能磁共振成像（fMRI），后者以毫米级的空间分辨率测量神经元活动继发的血液动力学反应，用于人脑功能的无创成像。在此，以最小范数估计为例，我们回顾了fMRI如何与MEG（以及脑电图，EEG）源建模相结合，并总结了这种数据融合技术的潜在优势和缺陷。还讨论了作为MEG/EEG/fMRI整合生理基础的神经血管耦合。最终，我们期望开发多模态MEG/EEG/fMRI神经成像方法，以高灵敏度和准确性表征人类大脑大规模神经网络中的时空功能连接。
