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Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts
Hyun-Chul Kim1, Seung-Schik Yoo2, Jong-Hwan Lee1
1Department of Brain and Cognitive Engineering, Korea University, Anam-dong 5-ga, Seongbuk-gu, Seoul 136-713, Republic of Korea.
Neuroimage
|October 7, 2014
Summary
A new recursive principal component analysis (rsPCA) method effectively removes helium-pump artifacts from simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) data. This technique enhances task-related gamma band activity and improves fMRI spatial resolution in motor areas.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Signal Processing
Background:
- Simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) is powerful for studying brain activity.
- Standard preprocessing removes gradient and ballistocardiographic artifacts but leaves residual helium-pump artifacts, especially in gamma band EEG.
- Existing methods for helium-pump artifact removal are limited.
Purpose of the Study:
- To introduce and validate a novel recursive EEG-segment-based principal component analysis (rsPCA) method for removing helium-pump artifacts.
- To assess the effectiveness of rsPCA in enhancing task-related gamma band activity in EEG-fMRI data.
- To evaluate the impact of rsPCA on the spatial localization of brain activity using fMRI.
Main Methods:
- Developed a recursive EEG-segment-based principal component analysis (rsPCA) approach.
- Applied rsPCA to simultaneously acquired EEG-fMRI data from hand clenching tasks.
- Extracted helium-pump artifact feature vectors as eigenvectors and removed reconstructed signals.
- Analyzed task-related gamma band activity and fMRI spatial patterns using general linear models (GLM).
Main Results:
- rsPCA significantly reduced helium-pump artifacts in EEG data.
- The method substantially enhanced task-related gamma band activity for both left-hand (p=0.0038) and right-hand (p=0.0363) tasks.
- fMRI analysis revealed significant activation in motor areas (post-/pre-central gyri) and superior temporal pole, exclusively with the rsPCA method.
- Improved spatial resolution of hemodynamic response function (HRF) models for gamma band activity.
Conclusions:
- The proposed rsPCA method is effective for removing helium-pump artifacts from simultaneous EEG-fMRI data.
- rsPCA enhances the detection and analysis of neural activity, particularly in the gamma frequency range.
- This technique improves the reliability and spatial accuracy of EEG-fMRI studies, especially for motor tasks.
Keywords:
ElectroencephalographyFunctional magnetic resonance imagingHelium-pump artifactIndependent component analysisPrincipal component analysisSimultaneous EEG–fMRI
