Kimberly J Hemmerling

Abstract Upper extremity motor paradigms during spinal cord functional magnetic resonance imaging (fMRI) can provide insight into the functional organization of the cord. Hand-grasping is an important daily function with clinical significance, but previous studies of similar squeezing movements have not reported consistent areas of activity and are limited by sample size and simplistic analysis methods. Here, we study spinal cord fMRI activation using a unimanual isometric hand-grasping task that is calibrated to participant maximum voluntary contraction (MVC). Two task modeling methods were considered: (1) a task regressor derived from an idealized block design (Ideal) and (2) a task regressor based on the recorded force trace normalized to individual MVC (%MVC). Across these two methods, group motor activity was highly lateralized to the hemicord ipsilateral to the side of the task. Activation spanned C5–C8 and was primarily localized to the C7 spinal cord segment. Specific differences in spatial distribution are also observed, such as an increase in C8 and dorsal cord activity when using the %MVC regressor. Furthermore, we explored the impact of data quantity and spatial smoothing on sensitivity to hand-grasp motor task activation. This analysis shows a large increase in number of active voxels associated with the number of fMRI runs, sample size, and spatial smoothing, demonstrating the impact of experimental design choices on motor activation.

Functional magnetic resonance imaging (fMRI) is an extensively used neuroimaging technique to non-invasively detect neural activity. Data quality is highly variable, and fMRI analysis typically consists of a number of complex processing steps. It is crucial to visually assess images throughout analysis to ensure that data quality at each step is satisfactory. For fMRI analysis of the brain, there is a simple tool to visualize four-dimensional data on a two-dimensional plot for qualitative analysis. Despite the practicality of this method, it cannot be directly applied to fMRI data of the spinal cord, and a comparable approach does not exist for spinal cord fMRI analysis. The additional challenges encountered in spinal cord imaging, including the small size of the cord and the influence of physiological noise sources, drive the importance of developing a similar visualization technique for spinal cord fMRI. Here, we introduce a highly versatile image analysis tool to visualize spinal cord fMRI data as a simple heatmap and to co-visualize relevant traces such as physiological or motion timeseries. We present multiple variations of the plot, data features that can be identified with the heatmap, and examples of the useful qualitative analyses that can be performed using this method. The spinal cord plot can be easily integrated into an fMRI analysis pipeline and can streamline visual inspection and qualitative analysis of functional imaging data.Clinical Relevance— Implementation of this data visualization method is a simple addition to spinal cord fMRI analysis that could be used to identify normal vs. abnormal signal variation in pathologies that impact the cord, such as spinal cord injury or multiple sclerosis.