Correction for pulse height variability reduces physiological noise in functional MRI when studying spontaneous brain...

Area of Science:

• Neuroimaging
• Biomedical Engineering
• Physiology

Background:

• Electroencephalography correlated functional magnetic resonance imaging (EEG-fMRI) detects spontaneous brain activity.
• fMRI analysis is susceptible to spurious correlations from physiological processes like cardiac and respiratory functions.

Purpose of the Study:

• To reduce falsely detected activated areas in EEG-fMRI by incorporating physiological variations.
• To improve the accuracy of brain activity mapping by accounting for physiological noise.

Main Methods:

• Utilized photoplethysmogram (PPG) signals, which reflect arterial blood oxygenation.
• Derived a variation in pulse height (VIPH) regressor from PPG data.
• Integrated the VIPH regressor into the general linear model (GLM) for fMRI analysis.

Main Results:

• VIPH explained a significant portion of fMRI signal variance in epilepsy patients and healthy volunteers.
• VIPH as a confounder reduced activated voxels by 30% in healthy subjects studying alpha rhythm.
• Enhanced identification of the epileptogenic zone in one out of five epilepsy patients.

Conclusions:

• VIPH effectively diminishes physiological noise in EEG-fMRI data.
• This method allows for a more reliable interpretation of fMRI results.
• VIPH integration offers improved accuracy in mapping brain activity and identifying neurological conditions.