Exploring Tonic and Burst Stimulation in Neural Fibers: A Computational Modeling Approach.

Spinal cord stimulation (SCS) is an effective therapy for chronic pain, yet conventional approaches often cause paresthesia due to synchronized activation of neural fibers. This study computationally investigates the mechanisms underlying paresthesia reduction by evaluating activation thresholds and short-term fidelity across conventional, FAST, and burst waveforms. Using a modified McIntyre-Richardson-Grill (MRG) axon model implemented via the PyFibers python package, we simulated neural responses to bipolar stimulation with two pulse widths (0.2 ms, 1 ms) and charge-balancing methods (active and passive). Burst waveforms exhibited lower activation thresholds than conventional and FAST paradigms, particularly for smaller fiber diameters. However, fidelity increased gradually for burst stimulation, reaching only 43-53% fidelity at 150% of threshold amplitude, compared to 100% fidelity for conventional and FAST waveforms at amplitudes of 116% and 124% of activation thresholds, respectively. Voltage heat maps demonstrated irregular intraburst action potential patterns in burst stimulation, with bi- and uni-directional propagation and de-synchronized activation, compared to consistent, pulse-locked responses of conventional and FAST waveforms. These irregular firing patterns, coupled with lower fidelity, suggest a mechanistic basis for reduced paresthesia in burst SCS. The results underscore the trade-off between stimulation efficacy and neural synchronization, providing insights for optimizing waveform design to balance analgesia and patient comfort.Clinical relevance- Burst SCS reduces paresthesia by desynchronizing axonal firing, evidenced by lower fidelity and irregular activation. Although higher amplitudes are needed for activation, the burst responses may provide a paresthesia-free alternative for pain management.