Hand-grasping is an important and clinically significant daily function, but more work is needed to understand the associated spinal cord neural activity. In this study, participants performed a hand-grasping task with both hands and spinal cord fMRI motor activation was modeled with two methods: (1) a typical idealized block design (Ideal) and (2) based on recorded grasp force normalized to individual maximum voluntary contraction (%MVC). Robust detection of hand-grasping activity was shown in the spinal cord, highly lateralized ipsilateral to the side of the task. In addition, the impact of sample size, number of fMRI runs, and spatial smoothing on activation estimates was explored. Overall, we emphasize the importance of a task that is well-controlled within and across participants. Using individually calibrated tasks in people with motor impairments will be especially beneficial to compare across groups.If you want to learn more, please check out the paper here!

How reliable are our current techniques for processing spinal cord fMRI data? In a recently published paper, Dr. Mark Hoggarth and Max Wang explore how person-to-person variability in the contouring of fMRI spinal cord masks affects downstream analyses. Using masks drawn by 8 raters of varying experience to inform co-registration to standard template space, they identify spatial differences in the accuracy of registration related to underlying image contrast and rater experience. At the group-level, spatial differences were present in activation maps although no systematic effect on overall activation level was identified. This work characterizes how variability in manually contoured masks propagates to results in spinal cord fMRI, demonstrating that standardization of processing pipelines and improving image acquisition should be prioritized.

This work was performed in collaboration with Dr. Kenneth Weber at the Stanford Systems Neuroscience and Pain Lab.

You can find the full access paper here!

A recent paper from the lab, led by Dr. Rachael Stickland, identifies a positive correlation between baseline cerebral blood flow (CBF) and Blood Oxygenation Level Dependent cerebrovascular reactivity (BOLD-CVR), measured with MRI. This positive correlation is seen between and within subjects and is strengthened by the addition of a breathing task to a resting-state acquisition and by optimizing for hemodynamic lag effects in CVR modeling. This work demonstrates how two analytical factors affect the observed relationship between baseline CBF and BOLD-CVR in healthy populations; the relationship becomes even more relevant to understand when interpreting results in
populations with altered vascular baselines or impaired cerebrovascular reserve.

This work was performed in collaboration with Dr. César Caballero-Gaudes’ lab at the Basque Center on Cognition, Brain and Language in Spain.

Check out the paper here!

Check out our conference paper that was presented at the IEEE Engineering in Medicine and Biology Conference and published online in December 2021! This paper details our method, developed by PhD candidate Kimberly Hemmerling, for visualization of complex spinal cord fMRI data as heatmaps. This work was inspired by a visualization technique designed for brain fMRI data (Power et al., 2017). Our heatmaps can be visualized alongside motion or physiological traces that may be used to identify coincidence of signal variation. The technique may be easily integrated into a preprocessing pipeline to visualize the effect of a preprocessing step, identify spatially or temporally varying artifacts, or to assess general data quality.Check out the work here, and our GitHub repository (BrightLab-ANVIL/spinalcordplot), which contains the code and example data necessary to generate the plots.