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Pulse artifact detection in simultaneous EEG-fMRI recording based on EEG map topography
Giannina R Iannotti1, Francesca Pittau, Christoph M Michel
1Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, Geneva University Hospital, 1211, Geneva 14, Switzerland.
Brain Topography
|October 14, 2014
Summary
A new method improves pulse artifact (PA) detection in electroencephalogram (EEG) during functional MRI (fMRI) by analyzing electrode polarity. This enhances EEG quality for more reliable fMRI analysis, even with poor electrocardiogram (ECG) signals.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Signal Processing
Background:
- Pulse artifacts (PAs) significantly corrupt electroencephalogram (EEG) data acquired during functional magnetic resonance imaging (fMRI).
- These artifacts stem from head and electrode motion synchronized with the heartbeat within the magnetic field.
- Accurate PA detection is crucial for reliable EEG-fMRI analysis.
Purpose of the Study:
- To develop and validate a novel method for improved pulse artifact detection in EEG-fMRI.
- To assess the proposed method's accuracy compared to traditional electrocardiogram (ECG) R-peak detection.
- To evaluate the impact of the new artifact detection method on epileptic spike identification.
Main Methods:
- Acquisition of high-density EEG-fMRI (256 electrodes) and simultaneous ECG at 3 Tesla.
- Estimation of PA using the voltage difference between left and right electrodes with strong artifact signals (facial, temporal).
- Comparison of PA detection accuracy using standard deviation, kurtosis, and inter-peak interval confinement against ECG R-peaks.
Main Results:
- The novel PA estimation method improved artifact detection in 15 out of 17 analyzed cases compared to the ECG R-peak method.
- Epileptic spike identification remained unaffected by the proposed artifact correction method.
- The method demonstrated enhanced artifact detection, especially when ECG data quality is compromised.
Conclusions:
- The proposed method offers a robust and improved approach for detecting pulse artifacts in EEG-fMRI.
- This technique is particularly valuable in scenarios with poor or unavailable ECG recordings.
- Enhanced artifact detection will improve EEG signal quality, leading to more reliable EEG-informed fMRI analyses.
