Spatially selective stimulation of the pig vagus nerve to modulate target effect versus side effect

Towards enhanced functionality of vagus neuroprostheses through in silico optimized stimulation

Bioelectronic therapies modulating the vagus nerve are promising for cardiovascular, inflammatory, and mental disorders. Clinical applications are however limited by side-effects such as breathing obstruction and headache caused by non-specific stimulation. To design selective and functional stimulation, we engineered VaStim, a realistic and efficient in-silico model. We developed a protocol to personalize VaStim in-vivo using simple muscle responses, successfully reproducing experimental observations, by combining models with trials conducted on five pigs. Through optimized algorithms, VaStim simulated the complete fiber population in minutes, including often omitted unmyelinated fibers which constitute 80% of the nerve. The model suggested that all Aα-fibers across the nerve affect laryngeal muscle, while heart rate changes were caused by B-efferents in specific fascicles. It predicted that tripolar paradigms could reduce laryngeal activity by 70% compared to typically used protocols. VaStim may serve as a model for developing neuromodulation therapies by maximizing efficacy and specificity, reducing animal experimentation.

NRV: An open framework for in silico evaluation of peripheral nerve electrical stimulation strategies

Electrical stimulation of peripheral nerves has been used in various pathological contexts for rehabilitation purposes or to alleviate the symptoms of neuropathologies, thus improving the overall quality of life of patients. However, the development of novel therapeutic strategies is still a challenging issue requiring extensive in vivo experimental campaigns and technical development. To facilitate the design of new stimulation strategies, we provide a fully open source and self-contained software framework for the in silico evaluation of peripheral nerve electrical stimulation. Our modeling approach, developed in the popular and well-established Python language, uses an object-oriented paradigm to map the physiological and electrical context. The framework is designed to facilitate multi-scale analysis, from single fiber stimulation to whole multifascicular nerves. It also allows the simulation of complex strategies such as multiple electrode combinations and waveforms ranging from conventional biphasic pulses to more complex modulated kHz stimuli. In addition, we provide automated support for stimulation strategy optimization and handle the computational backend transparently to the user. Our framework has been extensively tested and validated with several existing results in the literature.

Vagus nerve stimulation for cardiovascular diseases: Is there light at the end of the tunnel?

Autonomic dysfunction and chronic inflammation contribute to the pathogenesis and progression of several cardiovascular diseases (CVD), such as heart failure with preserved ejection fraction, atherosclerotic CVD, pulmonary arterial hypertension, and atrial fibrillation. The vagus nerve provides parasympathetic innervation to the heart, vessels, and lungs, and is also implicated in the neural control of inflammation through a neuroimmune pathway involving the spleen. Stimulation of the vagus nerve (VNS) can in principle restore autonomic balance and suppress inflammation, with potential therapeutic benefits in these diseases. Although VNS ameliorated CVD in several animal models, early human studies have demonstrated variable efficacy. The purpose of this review is to discuss the rationale behind the use of VNS in the treatment of CVD, to critically review animal and human studies of VNS in CVD, and to propose possible means to overcome the challenges in the clinical translation of VNS in CVD.

Using neural biomarkers to personalize dosing of vagus nerve stimulation

BACKGROUND

Vagus nerve stimulation (VNS) is an established therapy for treating a variety of chronic diseases, such as epilepsy, depression, obesity, and for stroke rehabilitation. However, lack of precision and side-effects have hindered its efficacy and extension to new conditions. Achieving a better understanding of the relationship between VNS parameters and neural and physiological responses is therefore necessary to enable the design of personalized dosing procedures and improve precision and efficacy of VNS therapies.

METHODS

We used biomarkers from recorded evoked fiber activity and short-term physiological responses (throat muscle, cardiac and respiratory activity) to understand the response to a wide range of VNS parameters in anaesthetised pigs. Using signal processing, Gaussian processes (GP) and parametric regression models we analyse the relationship between VNS parameters and neural and physiological responses.

RESULTS

Firstly, we illustrate how considering multiple stimulation parameters in VNS dosing can improve the efficacy and precision of VNS therapies. Secondly, we describe the relationship between different VNS parameters and the evoked fiber activity and show how spatially selective electrodes can be used to improve fiber recruitment. Thirdly, we provide a detailed exploration of the relationship between the activations of neural fiber types and different physiological effects. Finally, based on these results, we discuss how recordings of evoked fiber activity can help design VNS dosing procedures that optimize short-term physiological effects safely and efficiently.

CONCLUSION

Understanding of evoked fiber activity during VNS provide powerful biomarkers that could improve the precision, safety and efficacy of VNS therapies.

Selective intrafascicular stimulation of myelinated and unmyelinated nerve fibers through a longitudinal electrode: A computational study

Carbon nanotube (CNT) fiber electrodes have demonstrated exceptional spatial selectivity and sustained reliability in the context of intrafascicular electrical stimulation, as evidenced through rigorous animal experimentation. A significant presence of unmyelinated C fibers, known to induce uncomfortable somatosensory experiences, exists within peripheral nerves. This presence poses a considerable challenge to the excitation of myelinated Aβ fibers, which are crucial for tactile sensation. To achieve nuanced tactile sensory feedback utilizing CNT fiber electrodes, the selective stimulation of Aβ sensory afferents emerges as a critical factor. In confronting this challenge, the present investigation sought to refine and apply a rat sciatic-nerve model leveraging the capabilities of the COMSOL-NEURON framework. This approach enables a systematic evaluation of the influence exerted by stimulation parameters and electrode geometry on the activation dynamics of both myelinated Aβ and unmyelinated C fibers. The findings advocate for the utilization of current pulses featuring a pulse width of 600 μs, alongside the deployment of CNT fibers characterized by a diminutive diameter of 10 μm, with an exclusively exposed cross-sectional area, to facilitate reduced activation current thresholds. Comparative analysis under monopolar and bipolar electrical stimulation conditions revealed proximate activation thresholds, albeit with bipolar stimulation exhibiting superior fiber selectivity relative to its monopolar counterpart. Concerning pulse waveform characteristics, the adoption of an anodic-first biphasic stimulation modality is favored, taking into account the dual criteria of activation threshold and fiber selectivity optimization. Consequently, this investigation furnishes an efficacious stimulation paradigm for the selective activation of touch-related nerve fibers, alongside provisioning a comprehensive theoretical foundation for the realization of natural tactile feedback within the domain of prosthetic hand applications.

Importance of cardiac-synchronized vagus nerve stimulation parameters on the provoked chronotropic response for different levels of cardiac innervation

Introduction

The influence of vagus nerve stimulation (VNS) parameters on provoked cardiac effects in different levels of cardiac innervation is not well understood yet. This study examines the effects of VNS on heart rate (HR) modulation across a spectrum of cardiac innervation states, providing data for the potential optimization of VNS in cardiac therapies.

Materials and Methods

Utilizing previously published data from VNS experiments on six sheep with intact innervation, and data of additional experiments in five rabbits post bilateral rostral vagotomy, and four isolated rabbit hearts with additionally removed sympathetic influences, the study explored the impact of diverse VNS parameters on HR.

Results

Significant differences in physiological threshold charges were identified across groups: 0.09 ± 0.06 μC for intact, 0.20 ± 0.04 μC for vagotomized, and 9.00 ± 0.75 μC for isolated hearts. Charge was a key determinant of HR reduction across all innervation states, with diminishing correlations from intact (r = 0.7) to isolated hearts (r = 0.44). An inverse relationship was observed for the number of pulses, with its influence growing in conditions of reduced innervation (intact r = 0.11, isolated r = 0.37). Frequency and stimulation delay showed minimal correlations (r < 0.17) in all conditions.

Conclusion

Our study highlights for the first time that VNS parameters, including stimulation intensity, pulse width, and pulse number, crucially modulate heart rate across different cardiac innervation states. Intensity and pulse width significantly influence heart rate in innervated states, while pulse number is key in denervated states. Frequency and delay have less impact impact across all innervation states. These findings suggest the importance of customizing VNS therapy based on innervation status, offering insights for optimizing cardiac neuromodulation.

Characterization, number, and spatial organization of nerve fibers in the human cervical vagus nerve and its superior cardiac branch

BACKGROUND

Electrical stimulation of the vagus nerve (VN) is a therapy for epilepsy, obesity, depression, and heart diseases. However, whole nerve stimulation leads to side effects. We examined the neuroanatomy of the mid-cervical segment of the human VN and its superior cardiac branch to gain insight into the side effects of VN stimulation and aid in developing targeted stimulation strategies.

METHODS

Nerve specimens were harvested from eight human body donors, then subjected to immunofluorescence and semiautomated quantification to determine the signature, quantity, and spatial distribution of different axonal categories.

RESULTS

The right and left cervical VN (cVN) contained a total of 25,489 ± 2781 and 23,286 ± 3164 fibers, respectively. Two-thirds of the fibers were unmyelinated and one-third were myelinated. About three-quarters of the fibers in the right and left cVN were sensory (73.9 ± 7.5 % versus 72.4 ± 5.6 %), while 13.2 ± 1.8 % versus 13.3 ± 3.0 % were special visceromotor and parasympathetic, and 13 ± 5.9 % versus 14.3 ± 4.0 % were sympathetic. Special visceromotor and parasympathetic fibers formed clusters. The superior cardiac branches comprised parasympathetic, vagal sensory, and sympathetic fibers with the left cardiac branch containing more sympathetic fibers than the right (62.7 ± 5.4 % versus 19.8 ± 13.3 %), and 50 % of the left branch contained sensory and sympathetic fibers only.

CONCLUSION

The study indicates that selective stimulation of vagal sensory and motor fibers is possible. However, it also highlights the potential risk of activating sympathetic fibers in the superior cardiac branch, especially on the left side.

Computational modeling of dorsal root ganglion stimulation using an Injectrode

Objective.Minimally invasive neuromodulation therapies like the Injectrode, which is composed of a tightly wound polymer-coated Platinum/Iridium microcoil, offer a low-risk approach for administering electrical stimulation to the dorsal root ganglion (DRG). This flexible electrode is aimed to conform to the DRG. The stimulation occurs through a transcutaneous electrical stimulation (TES) patch, which subsequently transmits the stimulation to the Injectrode via a subcutaneous metal collector. However, it is important to note that the effectiveness of stimulation through TES relies on the specific geometrical configurations of the Injectrode-collector-patch system. Hence, there is a need to investigate which design parameters influence the activation of targeted neural structures.Approach.We employed a hybrid computational modeling approach to analyze the impact of Injectrode system design parameters on charge delivery and neural response to stimulation. We constructed multiple finite element method models of DRG stimulation, followed by the implementation of multi-compartment models of DRG neurons. By calculating potential distribution during monopolar stimulation, we simulated neural responses using various parameters based on prior acute experiments. Additionally, we developed a canonical monopolar stimulation and full-scale model of bipolar bilateral L5 DRG stimulation, allowing us to investigate how design parameters like Injectrode size and orientation influenced neural activation thresholds.Main results.Our findings were in accordance with acute experimental measurements and indicate that the minimally invasive Injectrode system predominantly engages large-diameter afferents (Aβ-fibers). These activation thresholds were contingent upon the surface area of the Injectrode. As the charge density decreased due to increasing surface area, there was a corresponding expansion in the stimulation amplitude range before triggering any pain-related mechanoreceptor (Aδ-fibers) activity.Significance.The Injectrode demonstrates potential as a viable technology for minimally invasive stimulation of the DRG. Our findings indicate that utilizing a larger surface area Injectrode enhances the therapeutic margin, effectively distinguishing the desired Aβactivation from the undesired Aδ-fiber activation.

Anatomical and functional organization of cardiac fibers in the porcine cervical vagus nerve allows spatially selective efferent neuromodulation

Cardiac disease progression reflects the dynamic interaction between adversely remodeled neurohumoral control systems and an abnormal cardiac substrate. Vagal nerve stimulation (VNS) is an attractive neuromodulatory option to dampen this dynamic interaction; however, it is limited by off-target effects. Spatially-selective VNS (sVNS) offers a promising solution to induce cardioprotection while mitigating off-target effects by specifically targeting pre-ganglionic parasympathetic efferent cardiac fibers. This approach also has the potential to enhance therapeutic outcomes by eliminating time-consuming titration required for optimal VNS. Recent studies have demonstrated the independent modulation of breathing rate, heart rate, and laryngeal contraction through sVNS. However, the spatial organization of afferent and efferent cardiac-related fibers within the vagus nerve remains unexplored. By using trial-and-error sVNS in vivo in combination with ex vivo micro-computed tomography fascicle tracing, we show the significant spatial separation of cardiac afferent and efferent fibers (179±55° SD microCT, p<0.05 and 200±137° SD, p<0.05 sVNS - degrees of separation across a cross-section of nerve) at the mid-cervical level. We also show that cardiac afferent fibers are located in proximity to pulmonary fibers consistent with recent findings of cardiopulmonary convergent neurons and circuits. We demonstrate the ability of sVNS to selectively elicit desired scalable heart rate decrease without stimulating afferent-related reflexes. By elucidating the spatial organization of cardiac-related fibers within the vagus nerve, our findings pave the way for more targeted neuromodulation, thereby reducing off-target effects and eliminating the need for titration. This, in turn, will enhance the precision and efficacy of VNS therapy in treating cardiac pathology, allowing for improved therapeutic efficacy.

Vagus nerve stimulation using an endovascular electrode array

Objective. Vagus nerve stimulation (VNS), which involves a surgical procedure to place electrodes directly on the vagus nerve (VN), is approved clinically for the treatment of epilepsy, depression, and to facilitate rehabilitation in stroke. VNS at surgically implanted electrodes is often limited by activation of motor nerve fibers near and within the VN that cause neck muscle contraction. In this study we investigated endovascular VNS that may allow activation of the VN at locations where the motor nerve fibers are not localized.Approach. We used endovascular electrodes within the nearby internal jugular vein (IJV) to electrically stimulate the VN while recording VN compound action potentials (CAPs) and neck muscle motor evoked potentials (MEPs) in an acute intraoperative swine experiment.Main Results. We show that the stimulation electrode position within the IJV is critical for efficient activation of the VN. We also demonstrate use of fluoroscopy (cone beam CT mode) and ultrasound to determine the position of the endovascular stimulation electrode with respect to the VN and IJV. At the most effective endovascular stimulation locations tested, thresholds for VN activation were several times higher than direct stimulation of the nerve using a cuff electrode; however, this work demonstrates the feasibility of VNS with endovascular electrodes and provides tools to optimize endovascular electrode positions for VNS.Significance. This work lays the foundation to develop endovascular VNS strategies to stimulate at VN locations that would be otherwise too invasive and at VN locations where structures such as motor nerve fibers do not exist.

Fully Customizable, Low-Cost, Multi-Contact Nerve Cuffs for Spatially Selective Neuromodulation

Selective neuromodulation of peripheral nerves is an emerging treatment for neurological diseases that are resistant to traditional drug therapy. While nerve cuffs with multichannel stimulation can be made by many varied methods, they usually require specialized microfabrication or additive manufacturing equipment. A truly low-cost and effective method of creating a custom cuff has not been accessible to researchers to prototype new methodologies and therapies in acute studies. Here, we present an inexpensive, highly repeatable method to create multi-contact nerve cuffs that require a simple postproduction PEDOT:PSS coating to improve the tissue/electrode interface. We demonstrate spatially selective neuromodulation with the proposed cuff design on the rat sciatic by preferentially activating the tibialis anterior (TA) and the lateral gastrocnemius (LG) in longitudinal and transverse stimulation patterns. This demonstrates that the proposed cuff fabrication method was not only effective for selective neuromodulation, but it is also significantly lower in cost, fully-customizable, and easily manufactured for future selective neuromodulation studies.

Validated computational models predict vagus nerve stimulation thresholds in preclinical animals and humans

Objective.We demonstrated how automated simulations to characterize electrical nerve thresholds, a recently published open-source software for modeling stimulation of peripheral nerves, can be applied to simulate accurately nerve responses to electrical stimulation.Approach.We simulated vagus nerve stimulation (VNS) for humans, pigs, and rats. We informed our models using histology from sample-specific or representative nerves, device design features (i.e. cuff, waveform), published material and tissue conductivities, and realistic fiber models.Main results.Despite large differences in nerve size, cuff geometry, and stimulation waveform, the models predicted accurate activation thresholds across species and myelinated fiber types. However, our C fiber model thresholds overestimated thresholds across pulse widths, suggesting that improved models of unmyelinated nerve fibers are needed. Our models of human VNS yielded accurate thresholds to activate laryngeal motor fibers and captured the inter-individual variability for both acute and chronic implants. For B fibers, our small-diameter fiber model underestimated threshold and saturation for pulse widths >0.25 ms. Our models of pig VNS consistently captured the range ofin vivothresholds across all measured nerve and physiological responses (i.e. heart rate, Aδ/B fibers, Aγfibers, electromyography, and Aαfibers). In rats, our smallest diameter myelinated fibers accurately predicted fast fiber thresholds across short and intermediate pulse widths; slow unmyelinated fiber thresholds overestimated thresholds across shorter pulse widths, but there was overlap for pulse widths >0.3 ms.Significance.We elevated standards for models of peripheral nerve stimulation in populations of models across species, which enabled us to model accurately nerve responses, demonstrate that individual-specific differences in nerve morphology produce variability in neural and physiological responses, and predict mechanisms of VNS therapeutic and side effects.

Deep-learning segmentation of fascicles from microCT of the human vagus nerve

Introduction

MicroCT of the three-dimensional fascicular organization of the human vagus nerve provides essential data to inform basic anatomy as well as the development and optimization of neuromodulation therapies. To process the images into usable formats for subsequent analysis and computational modeling, the fascicles must be segmented. Prior segmentations were completed manually due to the complex nature of the images, including variable contrast between tissue types and staining artifacts.

Methods

Here, we developed a U-Net convolutional neural network (CNN) to automate segmentation of fascicles in microCT of human vagus nerve.

Results

The U-Net segmentation of ~500 images spanning one cervical vagus nerve was completed in 24 s, versus ~40 h for manual segmentation, i.e., nearly four orders of magnitude faster. The automated segmentations had a Dice coefficient of 0.87, a measure of pixel-wise accuracy, thus suggesting a rapid and accurate segmentation. While Dice coefficients are a commonly used metric to assess segmentation performance, we also adapted a metric to assess fascicle-wise detection accuracy, which showed that our network accurately detects the majority of fascicles, but may under-detect smaller fascicles.

Discussion

This network and the associated performance metrics set a benchmark, using a standard U-Net CNN, for the application of deep-learning algorithms to segment fascicles from microCT images. The process may be further optimized by refining tissue staining methods, modifying network architecture, and expanding the ground-truth training data. The resulting three-dimensional segmentations of the human vagus nerve will provide unprecedented accuracy to define nerve morphology in computational models for the analysis and design of neuromodulation therapies.

Vagus nerve stimulation in the non-human primate: implantation methodology, characterization of nerve anatomy, target engagement and experimental applications

BACKGROUND

Vagus nerve stimulation (VNS) is a FDA approved therapy regularly used to treat a variety of neurological disorders that impact the central nervous system (CNS) including epilepsy and stroke. Putatively, the therapeutic efficacy of VNS results from its action on neuromodulatory centers via projections of the vagus nerve to the solitary tract nucleus. Currently, there is not an established large animal model that facilitates detailed mechanistic studies exploring how VNS impacts the function of the CNS, especially during complex behaviors requiring motor action and decision making.

METHODS

We describe the anatomical organization, surgical methodology to implant VNS electrodes on the left gagus nerve and characterization of target engagement/neural interface properties in a non-human primate (NHP) model of VNS that permits chronic stimulation over long periods of time. Furthermore, we describe the results of pilot experiments in a small number of NHPs to demonstrate how this preparation might be used in an animal model capable of performing complex motor and decision making tasks.

RESULTS

VNS electrode impedance remained constant over months suggesting a stable interface. VNS elicited robust activation of the vagus nerve which resulted in decreases of respiration rate and/or partial pressure of carbon dioxide in expired air, but not changes in heart rate in both awake and anesthetized NHPs.

CONCLUSIONS

We anticipate that this preparation will be very useful to study the mechanisms underlying the effects of VNS for the treatment of conditions such as epilepsy and depression, for which VNS is extensively used, as well as for the study of the neurobiological basis underlying higher order functions such as learning and memory.

Microneurography as a minimally invasive method to assess target engagement during neuromodulation

Objective.Peripheral neural signals recorded during neuromodulation therapies provide insights into local neural target engagement and serve as a sensitive biomarker of physiological effect. Although these applications make peripheral recordings important for furthering neuromodulation therapies, the invasive nature of conventional nerve cuffs and longitudinal intrafascicular electrodes (LIFEs) limit their clinical utility. Furthermore, cuff electrodes typically record clear asynchronous neural activity in small animal models but not in large animal models. Microneurography, a minimally invasive technique, is already used routinely in humans to record asynchronous neural activity in the periphery. However, the relative performance of microneurography microelectrodes compared to cuff and LIFE electrodes in measuring neural signals relevant to neuromodulation therapies is not well understood.Approach.To address this gap, we recorded cervical vagus nerve electrically evoked compound action potentials (ECAPs) and spontaneous activity in a human-scaled large animal model-the pig. Additionally, we recorded sensory evoked activity and both invasively and non-invasively evoked CAPs from the great auricular nerve. In aggregate, this study assesses the potential of microneurography electrodes to measure neural activity during neuromodulation therapies with statistically powered and pre-registered outcomes (https://osf.io/y9k6j).Main results.The cuff recorded the largest ECAP signal (p< 0.01) and had the lowest noise floor amongst the evaluated electrodes. Despite the lower signal to noise ratio, microneurography electrodes were able to detect the threshold for neural activation with similar sensitivity to cuff and LIFE electrodes once a dose-response curve was constructed. Furthermore, the microneurography electrodes recorded distinct sensory evoked neural activity.Significance.The results show that microneurography electrodes can measure neural signals relevant to neuromodulation therapies. Microneurography could further neuromodulation therapies by providing a real-time biomarker to guide electrode placement and stimulation parameter selection to optimize local neural fiber engagement and study mechanisms of action.

Fibers in smaller fascicles have lower activation thresholds with cuff electrodes due to thinner perineurium and smaller cross-sectional area

Objective. In nerve stimulation therapies, fibers in larger fascicles generally have higher activation thresholds, but the mechanisms are not well understood. We implemented and analyzed computational models to uncover the effects of morphological parameters on activation thresholds.Approach. We implemented finite element models of human vagus nerve stimulation to quantify the effects of morphological parameters on thresholds in realistic nerves. We also implemented simplified models to isolate effects of perineurium thickness, endoneurium diameter, fiber diameter, and fascicle location on current density, potential distributions (Ve), and activation thresholds across cuff geometries and stimulation waveforms. UsingVefrom each finite element model, we simulated activation thresholds in biophysical cable models of mammalian axons.Main results. Perineurium thickness increases with fascicle diameter, and both thicker perineurium and larger endoneurial diameter contributed to higher activation thresholds via lower peak and broader longitudinal potentials. Thicker perineurium caused less current to enter the fascicle transversely, decreasing peakVe. Thicker perineurium also inhibited current from leaving the fascicle, causing more constant longitudinal current density, broadeningVe. With increasing endoneurial diameter, intrafascicular volume increased faster than surface area, thereby decreasing intrafascicular current density and peakVe. Additionally, larger fascicles have greater cross-sectional area, thereby facilitating longitudinal intrafascicular current flow and broadeningVe. A large neighboring fascicle could increase activation thresholds, and for a given fascicle, fiber diameter had the greatest effect on thresholds, followed by fascicle diameter, and lastly, fascicle location within the epineurium. The circumneural cuff elicited robust activation across the nerve, whereas a bipolar transverse cuff with small contacts delivering a pseudo-monophasic waveform enabled more selective activation across fiber diameters and locations.Significance. Our computational studies provide mechanistic understanding of neural responses across relevant morphological parameters of peripheral nerves, thereby informing rational design of effective therapies.