Surface-based functional magnetic resonance imaging analysis of partial brain echo planar imaging data at 1.5 T

Area of Science:

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

Background:

• Surface-based analysis offers higher sensitivity and accuracy in fMRI compared to volume-based methods.
• A resolution gap between echo planar imaging (EPI) data and cortical surface models limits practical surface-based fMRI analysis, especially with 1.5-T MRI scanners.
• High-resolution segmented EPI data is hypothesized to overcome this resolution gap, potentially revealing different activation patterns.

Purpose of the Study:

• To evaluate the impact of high-resolution segmented partial-brain EPI data on surface-based fMRI analysis.
• To compare activation patterns detected by low-resolution whole-brain EPI and high-resolution partial-brain EPI using both volume- and surface-based methods.
• To investigate the influence of factors like activation patterns, registration, and local distortions on surface-based fMRI results.

Main Methods:

• Comparison of activation maps derived from low-resolution whole-brain EPI and high-resolution segmented partial-brain EPI datasets.
• Utilized both volume-based and surface-based analysis techniques for fMRI data.
• Analyzed spatial patterns of activation clusters and distributions within specific brain regions (occipital lobes, motor areas, fusiform gyri).

Main Results:

• Demonstrated differences in detected neural activations between low-resolution whole-brain and high-resolution segmented partial-brain EPI data.
• Volume- and surface-based analyses revealed distinct activation patterns, particularly when using high-resolution segmented EPI data.
• Activation distributions varied between the two EPI resolutions and analysis approaches.

Conclusions:

• High-resolution segmented EPI data enhances the practical application of surface-based fMRI analysis by addressing the resolution gap.
• The choice of EPI resolution and analysis method (volume- vs. surface-based) significantly impacts the detection and spatial localization of neural activation.
• Further evaluation of factors influencing surface-based fMRI analysis with segmented EPI techniques is warranted for robust interpretation.