The impact of T1 versus EPI spatial normalization templates for fMRI data analyses

Area of Science:

• Neuroimaging
• Functional Magnetic Resonance Imaging (fMRI)
• Brain Mapping

Background:

• Spatial normalization is crucial for group fMRI studies.
• Echo planar imaging (EPI) data present challenges due to signal dropout and distortions.
• Existing template-based normalization strategies include EPInorm and T1norm.

Purpose of the Study:

• To compare the efficacy of EPInorm and T1norm spatial normalization strategies for fMRI data.
• To evaluate the impact of omitting echo planar imaging (EPI) distortion correction on normalization performance.
• To determine which strategy offers superior results in terms of subject variability and statistical power.

Main Methods:

• Empirical comparison of EPInorm and T1norm strategies across four large fMRI datasets.
• Analysis of subject variability, coregistration distances, and statistical (T) values.
• Assessment of performance with and without EPI distortion correction.

Main Results:

• EPInorm consistently demonstrated reduced inter-subject variability compared to T1norm.
• EPInorm yielded lower coregistration distances, indicating higher within-dataset similarity.
• The EPInorm approach showed increased T values in a task-based fMRI dataset, suggesting enhanced statistical power.
• EPInorm boosted effective sample size by 12-25% when distortion correction was not applied.

Conclusions:

• The EPInorm strategy is recommended over T1norm when echo planar imaging (EPI) distortion correction is not utilized.
• EPInorm improves the reliability and statistical power of fMRI group studies.
• This finding is particularly relevant for optimizing neuroimaging analysis pipelines where distortion correction is often bypassed.