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MRI with and without a high-density EEG cap - what makes the difference?


Klein, Carina; Hänggi, Jürgen; Luechinger, Roger; Jäncke, Lutz (2015). MRI with and without a high-density EEG cap - what makes the difference? NeuroImage, 106:189-197.

Abstract

Besides the benefit of combining the imaging methods electroencephalography (EEG) and magnetic resonance imaging (MRI), much effort has been spent to develop algorithms aimed at successfully cleaning the EEG data from MRI-related gradient and ballistocardiological artefacts. However, previous studies have also shown a negative influence of the EEG on MRI data quality. Therefore, in the present study, we focussed for the first time on the influence of the EEG on morphometric measurements of T1-weighted MRI data (voxel- and surfaced-based morphometry). Our results delivered a strong influence of the EEG on cortical thickness, surface area, and volume as well as subcortical volumes due to local EEG-related inhomogeneities of the static magnetic (B0) and the gradient field (B1). In a second step, we analyzed the signal-to-noise ratios for both the anatomical and the functional data when recorded simultaneously with EEG and MRI and compared them to the ratios of the MRI data without simultaneous EEG measurements. These analyses revealed consistently lower signal-to-noise ratios for anatomical as well as functional MRI data during simultaneous EEG registration. In contrast, further analyses of T2*-weighted images provided reliable results independent of whether including the individuals' T1-weighted image with or without the EEG cap in the fMRI preprocessing stream. Based on our findings, we strongly recommend to not use the anatomical images obtained during simultaneous EEG-MRI recordings when there is an additional need or interest to focus on separate anatomical data analysis.

Abstract

Besides the benefit of combining the imaging methods electroencephalography (EEG) and magnetic resonance imaging (MRI), much effort has been spent to develop algorithms aimed at successfully cleaning the EEG data from MRI-related gradient and ballistocardiological artefacts. However, previous studies have also shown a negative influence of the EEG on MRI data quality. Therefore, in the present study, we focussed for the first time on the influence of the EEG on morphometric measurements of T1-weighted MRI data (voxel- and surfaced-based morphometry). Our results delivered a strong influence of the EEG on cortical thickness, surface area, and volume as well as subcortical volumes due to local EEG-related inhomogeneities of the static magnetic (B0) and the gradient field (B1). In a second step, we analyzed the signal-to-noise ratios for both the anatomical and the functional data when recorded simultaneously with EEG and MRI and compared them to the ratios of the MRI data without simultaneous EEG measurements. These analyses revealed consistently lower signal-to-noise ratios for anatomical as well as functional MRI data during simultaneous EEG registration. In contrast, further analyses of T2*-weighted images provided reliable results independent of whether including the individuals' T1-weighted image with or without the EEG cap in the fMRI preprocessing stream. Based on our findings, we strongly recommend to not use the anatomical images obtained during simultaneous EEG-MRI recordings when there is an additional need or interest to focus on separate anatomical data analysis.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Psychology
04 Faculty of Medicine > Institute of Biomedical Engineering
Dewey Decimal Classification:150 Psychology
170 Ethics
610 Medicine & health
Scopus Subject Areas:Life Sciences > Neurology
Life Sciences > Cognitive Neuroscience
Language:English
Date:2015
Deposited On:04 Dec 2014 09:11
Last Modified:26 Jan 2022 04:11
Publisher:Elsevier
ISSN:1053-8119
OA Status:Green
Publisher DOI:https://doi.org/10.1016/j.neuroimage.2014.11.053
PubMed ID:25482268
Project Information:
  • : FunderSNSF
  • : Grant IDCRSII3_136249
  • : Project TitleResting states of the brain and state dependent information processing in health and disease
  • Content: Accepted Version