Biophysics of Frequency-Dependent Variation in Paresthesia and Pain Relief during Spinal Cord Stimulation.

The neurophysiological effects of spinal cord stimulation (SCS) for chronic pain are poorly understood, resulting in inefficient failure-prone programming protocols and inadequate pain relief. Nonetheless, novel stimulation patterns are regularly introduced and adopted clinically. Traditionally, paresthetic sensation is considered necessary for pain relief, although novel paradigms provide analgesia without paresthesia. However, like pain relief, the neurophysiological underpinnings of SCS-induced paresthesia are unknown. Here, we paired biophysical modeling with clinical paresthesia thresholds (of both sexes) to investigate how stimulation frequency affects the neural response to SCS relevant to paresthesia and analgesia. Specifically, we modeled the dorsal column (DC) axonal response, dorsal column nucleus (DCN) synaptic transmission, conduction failure within DC fiber collaterals, and dorsal horn network output. Importantly, we found that high-frequency stimulation reduces DC fiber activation thresholds, which in turn accurately predicts clinical paresthesia perception thresholds. Furthermore, we show that high-frequency SCS produces asynchronous DC fiber spiking and ultimately asynchronous DCN output, offering a plausible biophysical basis for why high-frequency SCS is less comfortable and produces qualitatively different sensation than low-frequency stimulation. Finally, we demonstrate that the model dorsal horn network output is sensitive to SCS-inherent variations in spike timing, which could contribute to heterogeneous pain relief across patients. Importantly, we show that model DC fiber collaterals cannot reliably follow high-frequency stimulation, strongly affecting the network output and typically producing antinociceptive effects at high frequencies. Altogether, these findings clarify how SCS affects the nervous system and provide insight into the biophysics of paresthesia generation and pain relief.

Does high-frequency stimulation of sensory axons break the causal link between pain relief and paresthesia?

Neurostimulation produces unnatural cutaneous sensations with potent analgesic effects in pain syndromes. In this issue of Neuron, Sagalajev et al.1 demonstrate that these sensations are an epiphenomenon and explain how high-frequency stimulation can provide analgesia without these unnecessary sensations.

Model-based analysis of subthreshold mechanisms of spinal cord stimulation for pain.

Objective.Spinal cord stimulation (SCS) is a common treatment for chronic pain. For decades, SCS maximized overlap between stimulation-induced paresthesias and the patient's painful areas. Recently developed SCS paradigms relieve pain at sub-perceptible amplitudes, yet little is known about the neural response to these new waveforms or their analgesic mechanisms of action. Therefore, in this study, we investigated the neural response to multiple forms of paresthesia-free SCS.Approach.We used computational modeling to investigate the neurophysiological effects and the plausibility of commonly proposed mechanisms of three paresthesia-free SCS paradigms: burst, 1 kHz, and 10 kHz SCS. Specifically, in C- and Aß-fibers, we investigated the effects of different SCS waveforms on spike timing and activation thresholds, as well as how stochastic ion channel gating affects the response of dorsal column axons. Finally, we characterized membrane polarization of superficial dorsal horn neurons.Main results.We found that none of the SCS waveforms activate nor modulate spike timing in C-fibers. Spike timing was modulated in Aß-fibers only at suprathreshold amplitudes. Ion channel stochasticity had little effect on Aß-fiber activation thresholds but produced heterogeneous spike timings at suprathreshold amplitudes. Finally, local cells were preferentially polarized in their axon terminals, and the magnitude of this polarization was dependent on cellular morphology and position relative to the stimulation electrodes.Significance.Overall, the mechanisms of action of subparesthetic SCS remain unclear. Our results suggest that no SCS waveforms directly activate C-fibers, and modulation of spike timing is unlikely at subthreshold amplitudes. We conclude that potential subthreshold neuromodulatory effects of SCS on local cells are likely to be presynaptic in nature, as axons are preferentially depolarized during SCS.

An optimization framework for targeted spinal cord stimulation.

Objective. Spinal cord stimulation (SCS) is a common neurostimulation therapy to manage chronic pain. Technological advances have produced new neurostimulation systems with expanded capabilities in an attempt to improve the clinical outcomes associated with SCS. However, these expanded capabilities have dramatically increased the number of possible stimulation parameters and made it intractable to efficiently explore this large parameter space within the context of standard clinical programming procedures. Therefore, in this study, we developed an optimization approach to define the optimal current amplitudes or fractions across individual contacts in an SCS electrode array(s).Approach. We developed an analytic method using the Lagrange multiplier method along with smoothing approximations. To test our optimization framework, we used a hybrid computational modeling approach that consisted of a finite element method model and multi-compartment models of axons and cells within the spinal cord. Moreover, we extended our approach to multi-objective optimization to explore the trade-off between activating regions of interest (ROIs) and regions of avoidance (ROAs).Main results. For simple ROIs, our framework suggested optimized configurations that resembled simple bipolar configurations. However, when we considered multi-objective optimization, our framework suggested nontrivial stimulation configurations that could be selected from Pareto fronts to target multiple ROIs or avoid ROAs.Significance. We developed an optimization framework for targeted SCS. Our method is analytic, which allows for the fast calculation of optimal solutions. For the first time, we provided a multi-objective approach for selective SCS. Through this approach, we were able to show that novel configurations can provide neural recruitment profiles that are not possible with conventional stimulation configurations (e.g. bipolar stimulation). Most importantly, once integrated with computational models that account for sources of interpatient variability (e.g. anatomy, electrode placement), our optimization framework can be utilized to provide stimulation settings tailored to the needs of individual patients.

A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations.

Seventy years ago, Hodgkin and Huxley published the first mathematical model to describe action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously, with studies spanning from basic neuroscience to clinical applications for neuromodulation. Computer models of neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation. Spinal cord stimulation is a therapy widely used to treat chronic pain, with rapidly expanding indications, such as restoring motor function. In general, simulations contributed dramatically to improve lead designs, stimulation configurations, waveform parameters and programming procedures and provided insight into potential mechanisms of action of electrical stimulation. Although the implementation of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and, ultimately, for clinical efficacy. With this aim, we performed a systematic literature review and a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization and the use of medical imaging to capture realistic anatomy. Our review showed that increased model complexity and personalization improved both mechanistic and translational studies. More specifically, the use of medical imaging enabled the development of patient-specific models that can help to transform clinical practice in spinal cord stimulation. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for spinal cord stimulation.

Neural Recruitment During Conventional, Burst, and 10-kHz Spinal Cord Stimulation for Pain.

Spinal cord stimulation (SCS) is a popular neurostimulation therapy for severe chronic pain. To improve stimulation efficacy, multiple modes are now used clinically, including conventional, burst, and 10-kHz SCS. Clinical observations have produced speculation that these modes target different neural elements and/or work via distinct mechanisms of action. However, in humans, these hypotheses cannot be conclusively answered via experimental methods. Therefore, we utilized computational modeling to assess the response of primary afferents, interneurons, and projection neurons to conventional, burst, and 10-kHz SCS. We found that local cell thresholds were always higher than afferent thresholds, arguing against direct recruitment of these local cells. Furthermore, although we observed relative threshold differences between conventional, burst, and 10-kHz SCS, the recruitment order was the same. Finally, contrary to previous reports, axon collateralization produced complex changes in activation thresholds of primary afferents. These results motivate future work to contextualize clinical observations across SCS paradigms. PERSPECTIVE: This article presents the first computational modeling study to investigate neural recruitment during conventional, burst, and 10-kilohertz spinal cord stimulation for chronic pain within a single modeling framework. The results provide insight into these treatments' unknown mechanisms of action and offer context to interpreting clinical observations.

Neuromodulation using ultra low frequency current waveform reversibly blocks axonal conduction and chronic pain.

Chronic pain remains a leading cause of disability worldwide, and there is still a clinical reliance on opioids despite the medical side effects associated with their use and societal impacts associated with their abuse. An alternative approach is the use of electrical neuromodulation to produce analgesia. Direct current can block action potential propagation but leads to tissue damage if maintained. We have developed a form of ultra low frequency (ULF) biphasic current and studied its effects. In anesthetized rats, this waveform produced a rapidly developing and completely reversible conduction block in >85% of spinal sensory nerve fibers excited by peripheral stimulation. Sustained ULF currents at lower amplitudes led to a slower onset but reversible conduction block. Similar changes were seen in an animal model of neuropathic pain, where ULF waveforms blocked sensory neuron ectopic activity, known to be an important driver of clinical neuropathic pain. Using a computational model, we showed that prolonged ULF currents could induce accumulation of extracellular potassium, accounting for the slowly developing block observed in rats. Last, we tested the analgesic effects of epidural ULF currents in 20 subjects with chronic leg and back pain. Pain ratings improved by 90% after 2 weeks. One week after explanting the electrodes, pain ratings reverted to 72% of pretreatment screening value. We conclude that epidural spinal ULF neuromodulation represents a promising therapy for treating chronic pain.