The research team, led by Hou-Ming Kan and colleagues working across institutions including Macau University of Science and Technology, the Affiliated Hospital of Xuzhou Medical University, and Peking University, cast an unusually wide net. They systematically searched five major databases, PubMed, Embase, the Cochrane Library, Web of Science, and Scopus, from their inception through July 1, 2025, hunting for randomized controlled trials that tested any neuromodulation technique against any form of neuropathic pain. Two reviewers independently extracted the data, and the team assessed the risk of bias in each trial using the Cochrane Risk of Bias 2 tool, the current gold standard for judging the methodological quality of randomized studies. The final harvest was remarkable: 115 randomized controlled trials evaluating 19 distinct neuromodulation techniques, spanning everything from implanted electrodes along the spinal cord to magnetic pulses aimed at the brain.

To make sense of this enormous body of evidence, the researchers turned to network meta-analysis, a statistical technique that has transformed how comparative medicine is done. Unlike a traditional meta-analysis, which can only pool trials that compare the same two treatments head to head, a network meta-analysis builds a web of comparisons across all trials simultaneously, allowing treatments that were never directly tested against each other to be ranked using both direct and indirect evidence. The team used Bayesian models, implemented in R 4.2.3 and Stata, to estimate the relative effectiveness of each technique. They then ranked the interventions using SUCRA, the surface under the cumulative ranking curve, a metric that assigns each treatment a score between zero and one hundred percent reflecting its probable position among all competitors.

Crucially, the authors did not stop at ranking. They recognized that a league table of treatments is only as trustworthy as the evidence beneath it, so they applied the Confidence in Network Meta-Analysis framework, known as CINeMA, which is built on the widely used GRADE system. This tool grades the certainty of each network estimate by considering factors such as the risk of bias in the contributing trials, the consistency between direct and indirect evidence, the precision of the estimates, and the possibility of publication bias. The conclusions were framed using a partially contextualised approach, meaning the authors weighed both the statistical strength of the findings and their practical importance for patients living with pain.

The headline result is that low-frequency spinal cord stimulation, often abbreviated LF-SCS, stood out as the neuromodulation technique with the most substantial supporting evidence for neuropathic pain, and the certainty of that evidence was rated as moderate. Spinal cord stimulation involves surgically implanting thin electrodes in the epidural space near the spinal cord, which deliver electrical pulses that interfere with pain signals ascending to the brain. Low-frequency stimulation, typically operating at rates below about 100 hertz, is the classic configuration that produces a mild tingling sensation known as paresthesia, and it has decades of clinical use behind it. What this new analysis adds is a formal, evidence-graded confirmation that among all the competing techniques, this established approach currently carries the strongest foundation of randomized trial data.

Close behind the leader, the analysis identified several other techniques with favorable analgesic effects, though the certainty of the evidence supporting them was rated as low. These included peripheral nerve stimulation, which targets individual nerves outside the brain and spinal cord; high-frequency spinal cord stimulation, which delivers rapid pulses at around 10 kilohertz and typically produces no tingling sensation at all; radiofrequency thermocoagulation, a technique that uses heat to selectively interrupt pain-carrying nerve fibers; dorsal root ganglion stimulation, which places electrodes on the clustered nerve-cell bodies where sensory fibers converge before entering the spinal cord; and two variants of pulsed radiofrequency, bipolar and high-voltage, which apply brief bursts of electrical energy to nerve tissue without generating destructive heat. The favorable signals for these methods are encouraging, but the authors are careful to note that low-certainty evidence means future research could materially change these conclusions.

Perhaps the most sobering findings concern the non-invasive transcranial techniques, the methods that aim electromagnetic or electrical stimulation at the brain from outside the skull. These include repetitive transcranial magnetic stimulation, which uses powerful magnetic pulses to excite neurons in the primary motor cortex or the dorsolateral prefrontal cortex, as well as transcranial direct current and alternating current stimulation, which pass weak currents through the scalp, and intermittent theta burst stimulation, a rapid patterned form of magnetic stimulation. The analysis found that these brain-directed approaches demonstrated only limited analgesic benefits, and the evidence behind even those modest effects was rated as low certainty. For patients drawn to the idea of pain relief without surgery, this is a reminder that non-invasive does not automatically mean proven, and the authors explicitly call for further studies before these techniques can be confidently recommended.

The significance of this work lies partly in what it exposes about the field itself. The authors point out that high-quality comparative evidence on the analgesic effects of different neuromodulation techniques has been lacking for most neuropathic pain subtypes, with the notable exception of well-defined conditions such as complex regional pain syndrome, a severe chronic pain condition that usually affects a limb after injury. This gap has left clinicians with limited guidance on optimal technique selection in most everyday clinical scenarios, where decisions about whether to implant a spinal cord stimulator, target a dorsal root ganglion, or try a course of transcranial magnetic stimulation have often rested on convention, local expertise, and device marketing rather than on graded comparative evidence. By assembling 115 trials into a single analytical framework, the review converts a fragmented literature into an interpretable map.

The methodological rigor of the study also deserves attention. Bayesian network meta-analyses rely on Markov Chain Monte Carlo sampling to explore the space of possible treatment effects, and the authors monitored convergence using standard diagnostics, including the Brooks-Gelman-Rubin statistic and potential scale reduction factors, to confirm that their models had stabilized. Standardized mean differences served as the effect measure, allowing trials that scored pain on different scales to be pooled on a common metric. The inclusion of credible intervals rather than simple confidence intervals reflects the Bayesian underpinning, expressing the range within which the true effect most plausibly lies. None of this statistical machinery guarantees truth, but combined with the CINeMA certainty grading, it gives readers a transparent account of how much confidence each conclusion deserves.

For patients and clinicians, the practical message is nuanced. The evidence now most strongly supports low-frequency spinal cord stimulation as a neuromodulation option for neuropathic pain, while several invasive alternatives show promise that awaits confirmation through better-designed trials. Non-invasive brain stimulation, despite its appeal, cannot yet be considered a reliably effective stand-alone therapy. The review, which received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors and declared no competing interests, is positioned by its authors as a basis for future research and clinical decision-making. In a field where implanted devices can cost tens of thousands of dollars and failed trials leave patients with scars and disappointment, an evidence-graded ranking of 19 techniques is more than an academic exercise. It is a compass for a specialty that has, until now, been navigating largely by instinct.

Subject of Research: Comparative efficacy of neuromodulation techniques for neuropathic pain

Article Title: Effects of neuromodulation techniques on neuropathic pain: a systematic review and network meta-analysis

Article References: Kan, H.-M., Hong, H.-Y., Hu, Y.-J., Qin, Y.-Y., Zhang, S., Bai, Y.-Y., Wang, C., Wang, R.-Y., Ding, X.-T., Shen, W., & Chen, L.-P. (2026). Effects of neuromodulation techniques on neuropathic pain: a systematic review and network meta-analysis. BMC Medicine. https://doi.org/10.1186/s12916-026-05300-1

Image Credits: AI Generated

DOI: 10.1186/s12916-026-05300-1

Keywords: neuropathic pain, neuromodulation, spinal cord stimulation, network meta-analysis, dorsal root ganglion stimulation, pulsed radiofrequency, transcranial magnetic stimulation, peripheral nerve stimulation, randomized controlled trials, GRADE, pain medicine, BMC Medicine

The software, described in the journal SoftwareX by David Lung, Yuting Jia, Andrea Moro, Matteo Fachino and Max Haberbusch of the Medical University of Vienna, packages the entire workflow of nerve stimulation modeling into a single graphical application. Users can import a micro-computed tomography image of a nerve, segment its internal fascicles with an integrated promptable artificial intelligence engine, reconstruct a three-dimensional geometry, mesh it, solve the electromagnetic field problem, populate the nerve with realistic fiber populations, and compute activation thresholds. Every step that can be performed through the browser-based interface is mirrored in a Python API and a command-line interface, so the same study can be run interactively on a laptop or batch-submitted to a high-performance computing cluster.

The technical core of golgi is a finite-element solver built on the open-source FEniCSx/DOLFINx stack with the PETSc linear algebra library. The software solves the quasi-static volume-conductor equation for the electric potential in the tissue, treating the endoneurium as an anisotropic conducting medium and the perineurium, the thin sheath that wraps each fascicle, as a contact impedance that couples the interior and exterior subproblems. A conforming tetrahedral mesh generated by Gmsh, with TetGen as a fallback, resolves every anatomical region separately: endoneurium, epineurium, electrode contacts, insulating cuff, saline gap and surrounding muscle. Because the coupled block system is factorized once with the direct solver MUMPS, the per-contact lead fields can be computed a single time and superposed, meaning that multi-contact electrode montages and current-steering experiments require no additional field solves.

Once the field is known, golgi generates populations of nerve fibers drawn from species- and nerve-specific statistics of diameter and fiber type, covering myelinated A and B fibers as well as unmyelinated C fibers. Unusually for software in this field, the fibers need not run straight along the nerve axis. The package integrates streamlines of a quasi-static field through the branching endoneurium, producing smooth curved trajectories that follow fascicles through bifurcations. The extracellular potential sampled along each trajectory then drives validated biophysical axon models, including the widely used MRG model for myelinated fibers and the Sundt and Tigerholm models for unmyelinated ones, executed through the NEURON simulation environment via the PyFibers package. Activation thresholds are found by bisection on the stimulus amplitude, and an optional GPU-accelerated surrogate called AxonML can replace NEURON for high-throughput parameter sweeps.

Reproducibility receives unusual attention. Every stage of a golgi study is recorded in a directed acyclic graph of inputs and outputs, each hashed with SHA-256. When a study is exported, the resulting self-contained bundle carries a manifest listing the hash of every file, the software version and a frozen dependency list. A recipient can run a single command, golgi replay, which re-hashes the bundle and either certifies that the results are the unmodified outputs of the recorded inputs and environment or names the first file that differs. The developers are careful to note that this is an integrity and provenance check rather than a re-execution of the computation, since bitwise identity of finite-element and NEURON outputs across different machines is not guaranteed.

Performance figures reported for a reference study, a synthetic monofascicular nerve meshed with 2.88 million tetrahedra and simulated with twelve MRG fibers, show a total wall time of roughly ten minutes on an Apple silicon desktop workstation, with mesh generation and the direct factorization dominating the cost. The threshold sweep scales linearly with fiber count at about ten seconds per fiber, so a ninety-nine-fiber population requires around sixteen minutes of fiber simulation. Models with tens of millions of elements are intended for the high-performance computing path, where heavy stages can be submitted as SLURM jobs while the interface remains responsive.

The validation results are striking for a fully open stack. Against an analytic solution for a current monopole in a grounded saline cylinder, golgi’s field solver achieved a near-field mean error of 0.5 percent, actually outperforming the commercial COMSOL solver at 1.3 percent. For an idealized cuff electrode with anisotropic endoneurium and perineurium contact impedance, and for an image-derived swine cervical vagus nerve with a multi-contact cuff, point-wise deviations from COMSOL lead fields were 2.6 percent and 1.9 percent respectively, with coefficients of determination of at least 0.98. Simulated conduction velocities of MRG fibers between 5.7 and 16 micrometers fell within 3 percent of the published values across all eight diameters tested, and the computed strength-duration relation yielded a rheobase of 48 microamps and a chronaxie of 151 microseconds, consistent with the classical Weiss-Lapicque law.

Comparisons with experimental data reinforce the picture. For a dog cervical vagus nerve stimulated with a bipolar cuff, golgi reproduced the correct in vivo recruitment order across A, B and C fiber classes, with A and C fiber thresholds falling within the experimentally recorded range, although B fiber thresholds were underestimated by roughly a factor of two. For longitudinal intrafascicular electrodes, simulated fifty-percent recruitment currents of 53 and 90 microamps at pulse durations of 50 and 20 microseconds landed within both the in vivo bands and the predictions of the scriptable NRV framework, with a strength-duration ratio of 2.0 against experimental values of 2.1. A five-fascicle nerve with a circumferential cuff produced per-fascicle thresholds inside the published 0.1 to 1.5 milliamp range.

The practical implications extend beyond convenience. Because golgi reconstructs three-dimensional nerves with curved, fascicle-following trajectories through bifurcations, it can address questions that straight-fiber, cross-section-only tools cannot, such as whether a specific branch of the vagus nerve, for example the cardiac branch, can be selectively engaged. A companion study applying the pipeline to cohorts of image-derived swine and human vagus nerves, along with branching rabbit and human nerves, found that selective activation of a vagal cardiac branch depends on subject-specific anatomy, a finding with direct relevance to bioelectronic medicine. The software is released under the AGPL-3.0 license, with a Docker image and pinned conda environment ensuring that any recipient can recreate the exact computational stack.

The developers are candid about the limitations. Golgi is research software, not a clinical diagnostic or treatment-planning tool, and its predictions inherit the assumptions of the underlying models. The promptable segmentation engine is a third-party model whose accuracy on nerve imaging has not been characterized by the team, so segmentations should be reviewed by an expert before meshing. Tissue conductivities are literature values with substantial spread, and their uncertainty is not propagated to the computed thresholds, meaning sensitivity analyses remain the user’s responsibility. Absolute activation thresholds depend on the chosen axon model and are least reliable outside its calibration range, even though recruitment order is robust. Still, with its graphical interface, verified exports and open solver stack, golgi lowers a barrier that has kept anatomically realistic nerve modeling out of reach for many of the researchers who need it most.

Subject of Research: Open-source computational modeling of electrical stimulation of peripheral nerves

Article Title: golgi: open-source software for automated nerve model generation and recruitment simulation

Article References: Lung, D., Jia, Y., Moro, A., Fachino, M., & Haberbusch, M. (2026). golgi: open-source software for automated nerve model generation and recruitment simulation. SoftwareX, 36, Article 103094. https://doi.org/10.1016/j.softx.2026.103094

Image Credits: AI Generated

DOI: 10.1016/j.softx.2026.103094

Keywords: peripheral nerve stimulation, computational modeling, open-source software, finite-element method, vagus nerve stimulation, neural engineering, bioelectronic medicine, axon models, reproducibility, FEniCSx, NEURON, nerve recruitment

The core problem with conventional peripheral nerve stimulation lies in its lack of selectivity. When a cuff electrode wrapped around a nerve delivers current, it activates many types of fibers at once: the large, heavily myelinated Aα and Aβ fibers that carry touch and proprioceptive signals toward the spinal cord, the thinner Aδ fibers associated with sharp pain, and the efferent motor fibers that drive muscles. For pain relief, clinicians generally want to activate only the large sensory Aα/Aβ fibers, which can suppress pain transmission through gating mechanisms in the spinal cord. But because electrical stimulation cannot reliably distinguish afferent sensory fibers from efferent motor fibers, the current must be capped at levels that avoid unwanted muscle contractions. That ceiling can leave the therapeutic target population under-activated, blunting the treatment’s analgesic effect.

Optogenetics has long been proposed as an elegant solution. By introducing light-sensitive proteins such as channelrhodopsin 2 (ChR2) into specific populations of neurons, researchers can activate precisely those cells with pulses of light while leaving neighboring fibers untouched. In the new study, the team used transgenic mice expressing ChR2 and recorded compound action potentials (CAPs), the summed electrical signature of many axons firing together, from the sciatic nerve of anaesthetized animals. The results confirmed the selectivity promise: optogenetic stimulation activated Aα/Aβ fibers with impressive precision and produced no motor response at all, something electrical stimulation cannot achieve. For a field struggling to silence pain without triggering twitching limbs or tingling side effects, that selectivity is a major prize.

But there was a catch, and it is a serious one. When the researchers delivered tonic optogenetic stimulation, continuous trains of light pulses lasting up to 60 seconds at clinically relevant frequencies ranging from 4 to 100 Hz, the nerve responses faded dramatically. The optically evoked compound action potentials, or oCAPs, declined in an exponential and strongly frequency-dependent manner, with the statistical analysis showing a highly significant frequency effect (p < 0.001). At stimulation rates above 20 Hz, the response often vanished entirely, leaving no detectable signal even while the light continued to flash. In other words, the very thing that makes optogenetics selective also makes it fragile: the light-activated channels and the fibers themselves fatigue quickly, and the technique as it currently stands is simply untenable for the sustained stimulation that real-world pain therapy demands, even at low frequencies.

Electrical stimulation did not escape unscathed either. The electrically evoked compound action potentials, or eCAPs, also declined over the course of the 60-second stimulation trains, and they did so in a frequency-dependent, dual-phase exponential pattern that the team captured statistically (p < 0.001). This biphasic decay suggests two overlapping processes: a rapid initial drop, likely reflecting activity-dependent changes in axonal excitability such as hyperpolarization or potassium accumulation, followed by a slower secondary decline. Clinicians and device engineers have long observed that nerve responses wane during continuous stimulation, and this study quantifies that phenomenon precisely in the large sensory fiber population that pain therapy seeks to recruit, across the exact frequency range used in clinical peripheral nerve stimulation devices.

The most striking findings emerged when the researchers combined the two modalities. Delivering light and electrical stimulation together produced what the team describes as a facilitated response: the combined electrically and optically evoked CAP, or cCAP, was larger than what either stimulus could achieve alone. Across the entire stimulation period, more than 85 percent of the recorded responses showed this facilitation, and critically, the effect was maintained regardless of stimulation frequency (p = 0.33). The rapid initial reduction in response amplitude for combined stimulation was actually greater than that seen with electrical stimulation alone (p < 0.05), but after that fast phase, the response settled into a similar secondary decline as the electrical-only condition (p = 0.10). The net result, however, was a response that stayed larger and more sustained than either modality could deliver on its own.

Why does combining light and electricity boost the response? The mechanistic picture that emerges from this and earlier work is that the two stimuli act on the fibers through partially independent pathways. Electrical stimulation directly depolarizes the axonal membrane at the electrode, while optogenetic stimulation opens light-gated channels distributed along the ChR2-expressing sensory neurons. When both are applied, the depolarizations summate, preferentially boosting activation in the genetically targeted population of large sensory fibers. Because the electrical component does not fatigue in the same way as the optical one, it appears to prop up the response during the periods when the optically driven component would otherwise collapse. The consequence is a stimulus that retains the selectivity of the optogenetic approach, targeting only the Aα/Aβ fibers, while achieving the sustained responsiveness that pure light-based stimulation lacks.

The clinical implications are considerable. Peripheral nerve stimulation devices are already implanted in patients for chronic pain, but their efficacy is limited by the current ceilings imposed by motor fiber activation and by the inherent non-selectivity of electrical currents. If a hybrid device could deliver a small, safe electrical pulse alongside targeted optical activation of ChR2-expressing sensory fibers, it might achieve stronger and more sustained recruitment of the therapeutic fiber population without crossing into motor territory. The Melbourne team’s demonstration that facilitated responses persist across the full 4 to 100 Hz clinical frequency range, and throughout stimulation trains lasting a full minute, provides exactly the kind of preclinical evidence needed to justify pushing this approach toward translational development. This study adds to growing evidence that combined stimulation could improve the analgesic effect of existing peripheral nerve stimulation methods.

Significant hurdles remain before any such device reaches patients. Optogenetics in humans requires gene delivery, typically via adeno-associated viruses, to introduce light-sensitive proteins into the target neurons, and translating the transgenic mouse approach used here into a safe and durable human therapy is a formidable challenge involving dosing, immune responses and long-term expression. Light delivery to deep peripheral nerves also requires implanted LEDs or optical fibers, adding engineering complexity. The study itself was conducted in isoflurane-anaesthetized mice over relatively short stimulation windows, so questions about responses over hours, days or weeks of continuous use remain open. Ethical oversight was rigorous: all procedures were approved by the St Vincent’s Hospital Animal Ethics Committee in Melbourne and conducted under Australian animal welfare guidelines.

Nevertheless, the study represents a methodical and important step forward. By systematically comparing electrical, optogenetic and combined stimulation across clinically relevant frequencies and durations, and by quantifying the decay dynamics of each with rigorous statistical modeling, Ardren, Wrobel, Matarazzo, Thompson, Fallon, Richardson and their colleagues have given the neuromodulation field a clear-eyed assessment of what each approach can and cannot do. Optogenetics alone, however selective, cannot yet sustain the signals needed for therapy. Electrical stimulation alone, however durable, cannot select its targets. Together, the data suggest, they cover each other’s weaknesses. For the millions of chronic pain patients whose conditions resist every existing treatment, that combination, light and current working in concert, may be the most promising avenue yet for making nerve stimulation devices finally live up to their promise. The research was funded by the National Health and Medical Research Council and the Bionics Institute Incubation Fund, with support from the Victorian Government, and is published open access so that researchers worldwide can build on its findings immediately.

Subject of Research: How optogenetic, electrical and combined stimulation recruit large sensory nerve fibers in the mouse sciatic nerve during sustained neuromodulation for chronic pain treatment.

Article Title: Recruitment of Aα/Aβ fibers during tonic electrical, optogenetic and combined stimulation in the mouse sciatic nerve

Article References: Ardren, M. G., Wrobel, B., Matarazzo, J. V., Thompson, A. C., Fallon, J. B., & Richardson, R. T. (2026). Recruitment of Aα/Aβ fibers during tonic electrical, optogenetic and combined stimulation in the mouse sciatic nerve. BMC Neuroscience. https://doi.org/10.1186/s12868-026-01049-8

Image Credits: AI Generated

DOI: 10.1186/s12868-026-01049-8

Keywords: optogenetics, peripheral nerve stimulation, chronic pain, neuromodulation, sciatic nerve, A-alpha/A-beta fibers, compound action potential, channelrhodopsin, electrical stimulation, neuroengineering, BMC Neuroscience, pain therapy