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Ballistocardiogram artifact correction taking into account physiological signal preservation in simultaneous EEG-fMRI
- Source :
- NeuroImage, Vol. 135 (2016) pp. 45-63
- Publication Year :
- 2015
-
Abstract
- The ballistocardiogram (BCG) artifact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artifacts and/or deterioration of the physiological signals of interest. In this paper, we propose a family of methods whereby the EEG is decomposed using Independent Component Analysis (ICA) and a novel approach for the selection of BCG-related independent components (ICs) is used (PROJection onto Independent Components, PROJIC). Three ICA-based strategies for BCG artifact correction are then explored: 1) BCG-related ICs are removed from the back-reconstruction of the EEG (PROJIC); and 2-3) BCG-related ICs are corrected for the artifact occurrences using an Optimal Basis Set (OBS) or Average Artifact Subtraction (AAS) framework, before back-projecting all ICs onto EEG space (PROJIC-OBS and PROJIC-AAS, respectively). A novel evaluation pipeline is also proposed to assess the methods performance, which takes into account not only artifact but also physiological signal removal, allowing for a flexible weighting of the importance given to physiological signal preservation. This evaluation is used for the group-level parameter optimization of each algorithm on simultaneous EEG-fMRI data acquired using two different setups at 3T and 7T. Comparison with state-of-the-art BCG correction methods showed that PROJIC-OBS and PROJIC-AAS outperformed the others when priority was given to artifact removal or physiological signal preservation, respectively, while both PROJIC-AAS and AAS were in general the best choices for intermediate trade-offs. The impact of the BCG correction on the quality of event-related potentials (ERPs) of interest was assessed in terms of the relative reduction of the standard error (SE) across trials: 26/66%, 32/62% and 18/61% were achieved by, respectively, PROJIC, PROJIC-OBS and PROJIC-AAS, for data collected at 3T/7T. Although more significant improvements were achieved at 7T, the results were qualitatively comparable for both setups, which indicate the wide applicability of the proposed methodologies and recommendations.
- Subjects :
- Male
Computer science
Cognitive Neuroscience
Speech recognition
Cardiac-Gated Imaging Techniques
Electroencephalography
EEG-fMRI
Signal
Brain mapping
Multimodal Imaging
Sensitivity and Specificity
050105 experimental psychology
Ballistocardiography
03 medical and health sciences
Motion
Young Adult
0302 clinical medicine
medicine
Humans
0501 psychology and cognitive sciences
Diagnosis, Computer-Assisted
Projection (set theory)
Child
Multimodal imaging
CIBM-AIT
Artifact (error)
Brain Mapping
medicine.diagnostic_test
business.industry
05 social sciences
Subtraction
Reproducibility of Results
Magnetic resonance imaging
Pattern recognition
Image Enhancement
Independent component analysis
Magnetic Resonance Imaging
ddc:128.37
Neurology
Subtraction Technique
Female
Artificial intelligence
business
Artifacts
030217 neurology & neurosurgery
Algorithms
Subjects
Details
- ISSN :
- 10959572 and 10538119
- Volume :
- 135
- Database :
- OpenAIRE
- Journal :
- NeuroImage
- Accession number :
- edsair.doi.dedup.....6d5e6f343d31a1d69e3bd0c417f85a9e