Spatial and Temporal Recruitment of Nerve Fibers by Wavelet-based Waveforms

Introduction: Peripheral Nerve stimulation (PNS) or Spinal Cord Stimulation (SCS) typically employ conventional square/pulse waveforms that, when amplitude increases, tend to recruit more nerve fibers indiscriminately and thereby amplify the perceived intensity of sensation. In contrast, we introduce novel wavelet-based waveforms that not only recruit additional fibers but also modulate their firing rates in a structured, patterned manner, thereby offering the potential for more nuanced and distinctive sensory percepts. This approach exploits two complementary neural encoding strategies: 1) frequency (rate) coding, in which stimulus intensity is conveyed through the firing rate of individual neurons-greater stimulus intensity corresponds to faster action potential firing and 2) population coding, where stimuli are represented by the collective activity of many nerve fibers, allowing the stimulus to be decoded from a spatial pattern of responses. Whereas conventional waveforms primarily leverage population coding (simply an expanding pool of activated fibers), our wavelet-based waveform harnesses both rate and population coding by carefully orchestrating which fibers are activated and how they fire as amplitude varies. This dual modulation may enrich PNS or SCS sensations, moving beyond blunt intensity scaling toward more sophisticated sensory encoding.

Methods: We evaluated our hypothesis using computational simulations that employed the McIntyre-Richardson-Grill (MRG) model of myelinated axons within the NEURON simulation environment, a widely-used platform for realistic neural modeling. Wavelet-based stimulation waveforms were generated in MATLAB and applied as time-varying extracellular inputs in NEURON. Stimulation intensity was varied incrementally from 90% to 400% of the activation threshold for 16 µm diameter fibers to assess recruitment dynamics. Evoked compound action potentials (ECAPs) were recorded at a site 30 mm distal to the stimulation location, allowing analysis of downstream neural responses across intensities.

Results: We found that wavelet-based waveforms, configured with varying parameters, can selectively recruit nerve fibers in distinct spatial and temporal firing patterns. Unlike conventional square/pulse stimulation, wavelet-based waveforms could be configured to control both which fibers are activated and how they fire over time, offering a rich, patterned neural response. Such dual modulation using just the wavelet complex holds promise for evoking unique sensory percepts or therapeutic effects when applied across PNS, SCS, or DBS.

Conclusion: By leveraging the flexibility of wavelet-based designs, clinicians and researchers may tailor stimulation to target specific neural populations or firing motifs, potentially enhancing precision in sensation restoration, pain management, or motor control. This approach represents a paradigm shift - from blunt intensity scaling toward sophisticated, structured neural encoding - opening new avenues for personalized neuromodulation therapies.