A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources. Issue 4 (6th November 2020) - Piastra, Maria Carla; Nüßing, Andreas; Vorwerk, Johannes; Clerc, Maureen; Engwer, Christian; Wolters, Carsten H.
Abstract: Signal‐to‐noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)‐based sensitivity maps for three different head models, namely an isotropic three and four‐compartment and an anisotropic six‐compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM‐based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively. Abstract : Signal‐to‐noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. In our work, we computed EEG and MEG sensitivity maps in a six‐compartment anisotropic head model. We show that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. For cortical sources, we found that radial and deep are more visible to EEG, tangential (the majority) more to MEG. Finally, our results show that MEG is not fully insensitive to subcortical sources.