Spatial sampling of MEG and EEG based on generalized spatial-frequency analysis and optimal design

NeuroImage

Antti J. Mäkinen¹  Joonas Iivanainen²  Lauri Parkkonen³  Rasmus Zetter³  Risto J. Ilmoniemi³  Matti Stenroos³ 

[1] Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland;Corresponding author.;Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto FI-00076, Finland;

关键词: Magnetoencephalography;    Electroencephalography;    On-scalp MEG;    Spatial sampling;    Optimal design;    Spatial frequency;   

DOI  :  

来源: DOAJ

【 摘 要 】

In this paper, we analyze spatial sampling of electro- (EEG) and magnetoencephalography (MEG), where the electric or magnetic field is typically sampled on a curved surface such as the scalp. By simulating fields originating from a representative adult-male head, we study the spatial-frequency content in EEG as well as in on- and off-scalp MEG. This analysis suggests that on-scalp MEG, off-scalp MEG and EEG can benefit from up to 280, 90 and 110 spatial samples, respectively. In addition, we suggest a new approach to obtain sensor locations that are optimal with respect to prior assumptions. The approach also allows to control, e.g., the uniformity of the sensor locations. Based on our simulations, we argue that for a low number of spatial samples, model-informed non-uniform sampling can be beneficial. For a large number of samples, uniform sampling grids yield nearly the same total information as the model-informed grids.

【 授权许可】

Unknown