Comparison of volume-selective z-shim and conventional EPI in fMRI studies using face stimuli
Hu Cheng, Srikanth Padmala, Rena Fukunaga

TL;DR
This study compares volume-selective z-shim and conventional EPI in fMRI face studies, showing that z-shim improves activation detection in regions with susceptibility artifacts without reducing overall efficiency.
Contribution
It demonstrates that volume-selective z-shim enhances signal detection in problematic brain areas while maintaining scanning efficiency, offering a practical alternative to multi-shot EPI.
Findings
Volume-selective z-shim yields higher activation in amygdala, hippocampus, fusiform gyrus.
Fewer volumes are needed for z-shim to achieve comparable or better results.
Minimal differences are observed in regions unaffected by susceptibility artifacts.
Abstract
Single-shot gradient recalled echo planar imaging (EPI) is the primary tool for functional magnetic resonance imaging (fMRI). The image often suffers from signal drop near the air-tissue interface, such as the amygdala and regions of the orbitofrontal lobe. An effective way to correct for this type of artifact is by applying multi-shot EPI using different z-shimming. Unfortunately, the scanning efficiency is significantly lowered. More recently, a new technique called volume-selective z-shim was proposed to implement z-shim compensation to only specific slices with large susceptibility effects. The high imaging efficiency of volume selective z-shim makes it possible to substitute conventional EPI for whole brain studies. In this study two fMRI experiments were conducted to compare volume- selective z-shim and conventional EPI while subjects performed tasks on face stimuli. The…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFunctional Brain Connectivity Studies · Face Recognition and Perception · Advanced MRI Techniques and Applications
