Electrospinography for non-invasively recording spinal sensorimotor networks in humans

Objective. Currently, few non-invasive measures exist for directly measuring spinal sensorimotor networks. Electrospinography (ESG) is one non-invasive method but is primarily used to measure evoked responses or for monitoring the spinal cord during surgery. Our objectives were to evaluate the feasibility of ESG to measure spinal sensorimotor networks by determining spatiotemporal and functional connectivity changes during single-joint movements at the spinal and cortical levels. Approach. We synchronously recorded electroencephalography (EEG), electromyography, and ESG in ten neurologically intact adults while performing one of three lower-limb tasks (no movement, plantar-flexion and knee flexion) in the prone position. A multi-pronged approach was applied for removing artifacts using H-infinity filtering, artifact subspace reconstruction and independent component (IC) analysis. Next, data were segmented by task and ICs of EEG were clustered across participants. Within-participant analysis of ICs and ESG data was conducted, and ESG was characterized in the time and frequency domains. Generalized partial directed coherence analysis was performed within ICs and between ICs and ESG data by participant and task. Results. K-means clustering resulted in five clusters of ICs at Brodmann areas (BAs) 9, BA 8, BA 39, BA 4, and BA 22. Areas associated with motor planning, working memory, visual processing, movement, and attention, respectively. Time-frequency analysis of ESG data found localized changes during movement execution when compared to no movement. Lastly, we found bi-directional changes in functional connectivity (p < 0.05, adjusted for multiple comparisons) within IC's and between IC's and ESG sensors during movement when compared to the no movement condition. Significance. To our knowledge this is the first report using high density ESG for characterizing single joint lower limb movements. Our findings provide support that ESG contains information about efferent and afferent signaling in neurologically intact adults and suggests that we can utilize ESG to directly study the spinal cord.