Spatial fidelity of MEG/EEG source estimates: A general evaluation approach

Low spatial resolution is often cited as the most critical limitation of magneto- and electroencephalography (MEG and EEG), but a unifying framework for quantifying the spatial fidelity of M/EEG source estimates has yet to be established; previous studies have focused on linear estimation methods un...

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Main Authors: John G. Samuelsson, Noam Peled, Fahimeh Mamashli, Jyrki Ahveninen, Matti S. Hämäläinen
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:NeuroImage
Subjects:
SNR
MEG
EEG
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811920309150
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spelling doaj-743b46f638154c0c9221dc394a97e8212020-12-17T04:47:06ZengElsevierNeuroImage1095-95722021-01-01224117430Spatial fidelity of MEG/EEG source estimates: A general evaluation approachJohn G. Samuelsson0Noam Peled1Fahimeh Mamashli2Jyrki Ahveninen3Matti S. Hämäläinen4Harvard-MIT Division of Health Sciences and Technology (HST), Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USA; Corresponding author at: Harvard-MIT Division of Health Sciences and Technology (HST), Massachusetts Institute of Technology (MIT), Cambridge, 149 13th st, Boston, MA 02129, USA.Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Massachusetts General Hospital (MGH), Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USAAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Massachusetts General Hospital (MGH), Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USAAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Massachusetts General Hospital (MGH), Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USAAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA; Department of Radiology, Massachusetts General Hospital (MGH), Charlestown, MA 02129, USA; Harvard Medical School, Boston, MA 02115, USALow spatial resolution is often cited as the most critical limitation of magneto- and electroencephalography (MEG and EEG), but a unifying framework for quantifying the spatial fidelity of M/EEG source estimates has yet to be established; previous studies have focused on linear estimation methods under ideal scenarios without noise. Here we present an approach that quantifies the spatial fidelity of M/EEG estimates from simulated patch activations over the entire neocortex superposed on measured resting-state data. This approach grants more generalizability in the evaluation process that allows for, e.g., comparing linear and non-linear estimates in the whole brain for different signal-to-noise ratios (SNR), number of active sources and activation waveforms. Using this framework, we evaluated the MNE, dSPM, sLORETA, eLORETA, and MxNE methods and found that the spatial fidelity varies significantly with SNR, following a largely sigmoidal curve whose shape varies depending on which aspect of spatial fidelity that is being quantified and the source estimation method. We believe that these methods and results will be useful when interpreting M/EEG source estimates as well as in methods development.http://www.sciencedirect.com/science/article/pii/S1053811920309150Spatial resolutionSource estimationPatch analysisSNRMEGEEG
collection DOAJ
language English
format Article
sources DOAJ
author John G. Samuelsson
Noam Peled
Fahimeh Mamashli
Jyrki Ahveninen
Matti S. Hämäläinen
spellingShingle John G. Samuelsson
Noam Peled
Fahimeh Mamashli
Jyrki Ahveninen
Matti S. Hämäläinen
Spatial fidelity of MEG/EEG source estimates: A general evaluation approach
NeuroImage
Spatial resolution
Source estimation
Patch analysis
SNR
MEG
EEG
author_facet John G. Samuelsson
Noam Peled
Fahimeh Mamashli
Jyrki Ahveninen
Matti S. Hämäläinen
author_sort John G. Samuelsson
title Spatial fidelity of MEG/EEG source estimates: A general evaluation approach
title_short Spatial fidelity of MEG/EEG source estimates: A general evaluation approach
title_full Spatial fidelity of MEG/EEG source estimates: A general evaluation approach
title_fullStr Spatial fidelity of MEG/EEG source estimates: A general evaluation approach
title_full_unstemmed Spatial fidelity of MEG/EEG source estimates: A general evaluation approach
title_sort spatial fidelity of meg/eeg source estimates: a general evaluation approach
publisher Elsevier
series NeuroImage
issn 1095-9572
publishDate 2021-01-01
description Low spatial resolution is often cited as the most critical limitation of magneto- and electroencephalography (MEG and EEG), but a unifying framework for quantifying the spatial fidelity of M/EEG source estimates has yet to be established; previous studies have focused on linear estimation methods under ideal scenarios without noise. Here we present an approach that quantifies the spatial fidelity of M/EEG estimates from simulated patch activations over the entire neocortex superposed on measured resting-state data. This approach grants more generalizability in the evaluation process that allows for, e.g., comparing linear and non-linear estimates in the whole brain for different signal-to-noise ratios (SNR), number of active sources and activation waveforms. Using this framework, we evaluated the MNE, dSPM, sLORETA, eLORETA, and MxNE methods and found that the spatial fidelity varies significantly with SNR, following a largely sigmoidal curve whose shape varies depending on which aspect of spatial fidelity that is being quantified and the source estimation method. We believe that these methods and results will be useful when interpreting M/EEG source estimates as well as in methods development.
topic Spatial resolution
Source estimation
Patch analysis
SNR
MEG
EEG
url http://www.sciencedirect.com/science/article/pii/S1053811920309150
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