Lid closure mimics head movement in fMRI

Area of Science:

• Neuroimaging
• Functional Magnetic Resonance Imaging (fMRI)
• Biomedical Engineering

Background:

• Functional Magnetic Resonance Imaging (fMRI) relies on accurate motion correction for reliable data.
• Involuntary head movements are a common source of artifacts in fMRI.
• Existing motion correction algorithms may be susceptible to signal changes from physiological sources.

Purpose of the Study:

• To investigate the impact of eye lid closure on signal intensity in EPI-fMRI.
• To identify if eye movements and lid closure introduce motion artifacts.
• To propose a method to mitigate these artifacts in fMRI data analysis.

Main Methods:

• Utilized Echo-Planar Imaging (EPI) sequences in fMRI.
• Quantified signal intensity changes in the eye region during transitions from eyes open to eyes closed.
• Analyzed head motion parameters (translations and rotations) derived from fMRI data.
• Implemented an eye-masking strategy during motion parameter estimation.

Main Results:

• Lid closure increased eye signal intensity by 1.6 to 2 times in EPI-fMRI.
• Transitions between open and closed eyes were associated with erroneous detection of head translations (z-axis) and rotations (x-axis).
• Masking the eyes during motion parameter estimation successfully avoided these artifacts.

Conclusions:

• Eye lid closure is a significant confound in fMRI, mimicking head motion.
• Standard motion correction may be compromised by physiological signal changes like lid closure.
• Masking the ocular regions during motion estimation is a crucial step for accurate fMRI data processing.