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Abstract #0662

Comparison of multi-echo denoising techniques for auditory brainstem fMRI in the presence of task-correlated motion

Michelle C. Medina1,2, Neha A. Reddy1,2, Kevin R. Sitek3, and Molly G. Bright1,2
1Biomedical Engineering, Northwestern Univeristy, Evanston, IL, United States, 2Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States, 3Communication Sciences and Disorders, Northwestern Univeristy, Evanston, IL, United States

Synopsis

Keywords: fMRI Analysis, fMRI (task based), Brainstem

Motivation: Task-based brainstem fMRI mapping is crucial to understand whole-brain system-level functioning, but data are plagued by low tSNR and task-correlated artifacts.

Goal(s): We tested multi-echo denoising techniques in auditory brainstem data with and without task-correlated noise.

Approach: Nine healthy individuals received passive auditory stimuli with (Audio+Motor) and without (Audio-only) a simultaneous shoulder abduction motor task during multi-echo fMRI.

Results: Both single-echo and multi-echo techniques revealed clusters of significant activation in the inferior colliculus in Audio-only and Audio+Motor data. Despite greater t-statistics with single-echo data in the Audio+Motor dataset, multi-echo ICA yielded higher tSNR without a dependence on motion, suggesting more robust data quality.

Impact: Task-based brainstem fMRI is greatly impacted by numerous confounds, including task-correlated motion. Understanding the capabilities of multi-echo denoising techniques in the brainstem will allow more reliable and robust data quality in clinical cohorts that exhibit higher levels of motion.

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