Abstract
Spinal Cord Stimulation (SCS) is a procedure used extensively in neurosurgery. It has demonstrable therapeutic benefits for an assortment of sensorimotor disorders, notably intractable neuropathic pain of the limbs and lower back. Although SCS is known to stimulate the A-β afferent fibers of the dorsal columns (DCs), it remains unclear precisely how this leads to the appropriate neuromodulation resulting in analgesia. Attaining a greater understanding of this process is imperative, as it would allow for more rational design, placement, and programming of the stimulating electrodes, thereby informing SCS and potentially enhancing its efficacy in pain management. Yet the absence of a comprehensive model of the underlying neural circuitry and dynamics poses a significant challenge. An additional obstacle is the dearth of detailed information on the interaction of this circuitry with applied electric fields. We created a biologically-constrained computational model of the circuitry present in the L1 segment of the adult human spinal cord. The model is scaled such that the number of neurons forms a ratio of 1:50 to the developmentally average adult. Replication of standard motor reflexes (e.g., monosynaptic H-reflex) served as an initial validation and calibration. When we generated a virtual “pain” signal, C afferents excited a set of wide dynamic range (WDR) neurons to fire. We subsequently activated SCS electrodes, which stimulated certain DC A-β afferents. This resulted in WDR inhibition, blocking pain transmission to the brain. Pain relief hypotheses were developed and tested using this model, and clinical predictions were made based on the results.