TY - JOUR
T1 - A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources
AU - Piastra, Maria Carla
AU - Nüßing, Andreas
AU - Vorwerk, Johannes
AU - Clerc, Maureen
AU - Engwer, Christian
AU - Wolters, Carsten H.
N1 - Funding Information:
This work was supported by EU project ChildBrain (Marie Curie innovative training network, grant No. 641652), by the Deutsche Forschungsgemeinschaft (DFG), project WO1425/7‐1, by the DFG priority program SPP1665, project WO1425/5‐2, by the Deutscher Akademischer Austauschdienst (PPP Finland 2020, project No. 57523877), by the Austrian Wissenschaftsfonds (FWF), project I 3790‐B27, and the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (ERC Advanced Grant agreement No. 694665: CoBCoM—Computational Brain Connectivity Mapping). The authors thank Andreas Wollbrink, Karin Wilken, Hildegard Deitermann, Ute Trompeter, and Harald Kugel for their help with the acquisition of the EEG/MEG/MRI data. Open access funding enabled and organized by Projekt DEAL.
Funding Information:
Austrian Wissenschaftsfonds I 3790‐B27 Childbrain, Marie Curie Innovative Training Network: 641652 CoBCoM‐Computational Brain Connectivity Mapping, ERC Advanced, Grant/Award Number: 694665; Deutsche Forschungsgemeinschaft WO1425/7‐1 SPP: 1665, Grant/Award Number: WO1425/5‐2; Deutscher Akademischer Austauschdienst, Grant/Award Number: 57523877 Funding information
Publisher Copyright:
© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
PY - 2021/3
Y1 - 2021/3
N2 - 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.
AB - 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.
KW - electroencephalography
KW - finite element method
KW - magnetoencephalography
KW - sensitivity map
KW - signal-to-noise ratio
KW - subcortical sources
KW - volume conduction modeling
UR - http://www.scopus.com/inward/record.url?scp=85096761610&partnerID=8YFLogxK
U2 - 10.1002/hbm.25272
DO - 10.1002/hbm.25272
M3 - Article
C2 - 33156569
AN - SCOPUS:85096761610
SN - 1065-9471
VL - 42
SP - 978
EP - 992
JO - Human brain mapping
JF - Human brain mapping
IS - 4
ER -