Computational models of compound nerve action potentials: Efficient filter-based methods to quantify effects of tissue conductivities, conduction distance, and nerve fiber parameters.

BACKGROUND: Peripheral nerve recordings can enhance the efficacy of neurostimulation therapies by providing a feedback signal to adjust stimulation settings for greater efficacy or reduced side effects. Computational models can accelerate the development of interfaces with high signal-to-noise ratio and selective recording. However, validation and tuning of model outputs against in vivo recordings remains computationally prohibitive due to the large number of fibers in a nerve. METHODS: We designed and implemented highly efficient modeling methods for simulating electrically evoked compound nerve action potential (CNAP) signals. The method simulated a subset of fiber diameters present in the nerve using NEURON, interpolated action potential templates across fiber diameters, and filtered the templates with a weighting function derived from fiber-specific conduction velocity and electromagnetic reciprocity outputs of a volume conductor model. We applied the methods to simulate CNAPs from rat cervical vagus nerve. RESULTS: Brute force simulation of a rat vagal CNAP with all 1,759 myelinated and 13,283 unmyelinated fibers in NEURON required 286 and 15,860 CPU hours, respectively, while filtering interpolated templates required 30 and 38 seconds on a desktop computer while maintaining accuracy. Modeled CNAP amplitude could vary by over two orders of magnitude depending on tissue conductivities and cuff opening within experimentally relevant ranges. Conduction distance and fiber diameter distribution also strongly influenced the modeled CNAP amplitude, shape, and latency. Modeled and in vivo signals had comparable shape, amplitude, and latency for myelinated fibers but not for unmyelinated fibers. CONCLUSIONS: Highly efficient methods of modeling neural recordings quantified the large impact that tissue properties, conduction distance, and nerve fiber parameters have on CNAPs. These methods expand the computational accessibility of neural recording models, enable efficient model tuning for validation, and facilitate the design of novel recording interfaces for neurostimulation feedback and understanding physiological systems.

Calcium image analysis in the moving gut.

BACKGROUND: The neural control of gastrointestinal muscle relies on circuit activity whose underlying motifs remain limited by small-sample calcium imaging recordings confounded by motion artifact, paralytics, and muscle dissections. We present a sequence of resources to register images from moving preparations and identify out-of-focus events in widefield fluorescent microscopy. METHODS: Our algorithm uses piecewise rigid registration with pathfinding to correct movements associated with smooth muscle contractions. We developed methods to identify loss-of-focus events and to simulate calcium activity to evaluate registration. KEY RESULTS: By combining our methods with principal component analysis, we found populations of neurons exhibit distinct activity patterns in response to distinct stimuli consistent with hypothesized roles. The image analysis pipeline makes deeper insights possible by capturing concurrently calcium dynamics from more neurons in larger fields of view. We provide access to the source code for our algorithms and make experimental and technical recommendations to increase data quality in calcium imaging experiments. CONCLUSIONS: These methods make feasible large population, robust calcium imaging recordings and permit more sophisticated network analyses and insights into neural activity patterns in the gut.

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.

Spatiotemporal parameters for energy efficient kilohertz-frequency nerve block with low onset response.

BACKGROUND: Electrical nerve conduction block has great potential for treatment of disease through reversible and local inactivation of somatic and autonomic nerves. However, the relatively high energy requirements and the presence of undesired excitation at the onset of the kilohertz-frequency (KHF) signals used for block pose obstacles to effective translation. Frequency, electrode geometry, and waveform shape are known to influence block threshold and onset response, but available data provide a limited understanding of how to select these parameters to optimize nerve block. METHODS: We evaluated KHF nerve block in rat tibial nerve across frequencies (5-60 kHz), electrode geometries (monopolar, bipolar, and tripolar), and waveform shapes. We present a novel Fourier-based method for constructing composite signals that systematically sample the KHF waveform design space. RESULTS: The lowest frequencies capable of blocking (5-16 kHz) were not the most energy-efficient among the tested frequencies. Further, bipolar cuffs required the largest current and power to block, monopolar cuffs required the lowest current, and both tripolar and monopolar cuffs required the lowest power. Tripolar cuffs produced the smallest onset response across frequencies. Composite signals comprised of a first harmonic sinusoid at fundamental frequency (f0) superposed on a second harmonic sinusoid at 2f0 could block at lower threshold and lower onset response compared to the constituent sinusoids alone. This effect was strongly dependent on the phase of the second harmonic and on the relative amplitudes of the first and second harmonics. This effect was also dependent on electrode geometry: monopolar and tripolar cuffs showed clear composite signal effects in most experiments; bipolar cuffs showed no clear effects in most experiments. CONCLUSIONS: Our data provide novel information about block threshold and onset response at the boundary of frequencies that can block. Our results also show an interaction between spatial (cuff geometry) and temporal (frequency and waveform shape) parameters. Finally, while previous studies suggested that temporal parameters could reduce onset response only in exchange for increased block threshold (or vice versa), our results show that waveform shape influences KHF response in ways that can be exploited to reduce both energy and onset responses.

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.

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.

Measuring and modeling the effects of vagus nerve stimulation on heart rate and laryngeal muscles.

BACKGROUND: Reduced heart rate (HR) during vagus nerve stimulation (VNS) is associated with therapy for heart failure, but stimulation frequency and amplitude are limited by patient tolerance. An understanding of physiological responses to parameter adjustments would allow differential control of therapeutic and side effects. To investigate selective modulation of the physiological responses to VNS, we quantified the effects and interactions of parameter selection on two physiological outcomes: one related to therapy (reduced HR) and one related to side effects (laryngeal muscle EMG). METHODS: We applied a broad range of stimulation parameters (mean pulse rates (MPR), intra-burst frequencies, and amplitudes) to the vagus nerve of anesthetized mice. We leveraged the in vivo recordings to parameterize and validate computational models of HR and laryngeal muscle activity across amplitudes and temporal patterns of VNS. We constructed a finite element model of excitation of fibers within the mouse cervical vagus nerve. RESULTS: HR decreased with increased amplitude, increased MPR, and decreased intra-burst frequency. EMG increased with increased MPR. Preferential HR effects over laryngeal EMG effects required combined adjustments of amplitude and MPR. The model of HR responses highlighted contributions of ganglionic filtering to VNS-evoked changes in HR at high stimulation frequencies. Overlap in activation thresholds between small and large modeled fibers was consistent with the overlap in dynamic ranges of related physiological measures (HR and EMG). CONCLUSION: The present study provides insights into physiological responses to VNS required for informed parameter adjustment to modulate selectively therapeutic effects and side effects.

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

Electrical stimulation of the cervical vagus nerve using implanted electrodes (VNS) is FDA-approved for the treatment of drug-resistant epilepsy, treatment-resistant depression, and most recently, chronic ischemic stroke rehabilitation. However, VNS is critically limited by the unwanted stimulation of nearby neck muscles-a result of non-specific stimulation activating motor nerve fibers within the vagus. Prior studies suggested that precise placement of small epineural electrodes can modify VNS therapeutic effects, such as cardiac responses. However, it remains unclear if placement can alter the balance between intended effect and limiting side effect. We used an FDA investigational device exemption approved six-contact epineural cuff to deliver VNS in pigs and quantified how epineural electrode location impacts on- and off-target VNS activation. Detailed post-mortem histology was conducted to understand how the underlying neuroanatomy impacts observed functional responses. Here we report the discovery and characterization of clear neuroanatomy-dependent differences in threshold and saturation for responses related to both effect (change in heart rate) and side effect (neck muscle contractions). The histological and electrophysiological data were used to develop and validate subject-specific computation models of VNS, creating a well-grounded quantitative framework to optimize electrode location-specific activation of nerve fibers governing intended effect versus unwanted side effect.

Fascicles split or merge every ∼560 microns within the human cervical vagus nerve.

Objective.Vagus nerve stimulation (VNS) is Food and Drug Administration-approved for epilepsy, depression, and obesity, and stroke rehabilitation; however, the morphological anatomy of the vagus nerve targeted by stimulatation is poorly understood. Here, we used microCT to quantify the fascicular structure and neuroanatomy of human cervical vagus nerves (cVNs).Approach.We collected eight mid-cVN specimens from five fixed cadavers (three left nerves, five right nerves). Analysis focused on the 'surgical window': 5 cm of length, centered around the VNS implant location. Tissue was stained with osmium tetroxide, embedded in paraffin, and imaged on a microCT scanner. We visualized and quantified the merging and splitting of fascicles, and report a morphometric analysis of fascicles: count, diameter, and area.Main results.In our sample of human cVNs, a fascicle split or merge event was observed every ∼560µm (17.8 ± 6.1 events cm-1). Mean morphological outcomes included: fascicle count (6.6 ± 2.8 fascicles; range 1-15), fascicle diameter (514 ± 142µm; range 147-1360µm), and total cross-sectional fascicular area (1.32 ± 0.41 mm2; range 0.58-2.27 mm).Significance.The high degree of fascicular splitting and merging, along with wide range in key fascicular morphological parameters across humans may help to explain the clinical heterogeneity in patient responses to VNS. These data will enable modeling and experimental efforts to determine the clinical effect size of such variation. These data will also enable efforts to design improved VNS electrodes.

In vivo Visualization of Pig Vagus Nerve "Vagotopy" Using Ultrasound.

Background: Placement of the clinical vagus nerve stimulating cuff is a standard surgical procedure based on anatomical landmarks, with limited patient specificity in terms of fascicular organization or vagal anatomy. As such, the therapeutic effects are generally limited by unwanted side effects of neck muscle contractions, demonstrated by previous studies to result from stimulation of (1) motor fibers near the cuff in the superior laryngeal and (2) motor fibers within the cuff projecting to the recurrent laryngeal. Objective: Conventional non-invasive ultrasound, where the transducer is placed on the surface of the skin, has been previously used to visualize the vagus with respect to other landmarks such as the carotid and internal jugular vein. However, it lacks sufficient resolution to provide details about the vagus fascicular organization, or detail about smaller neural structures such as the recurrent and superior laryngeal branch responsible for therapy limiting side effects. Here, we characterize the use of ultrasound with the transducer placed in the surgical pocket to improve resolution without adding significant additional risk to the surgical procedure in the pig model. Methods: Ultrasound images were obtained from a point of known functional organization at the nodose ganglia to the point of placement of stimulating electrodes within the surgical window. Naïve volunteers with minimal training were then asked to use these ultrasound videos to trace afferent groupings of fascicles from the nodose to their location within the surgical window where a stimulating cuff would normally be placed. Volunteers were asked to select a location for epineural electrode placement away from the fascicles containing efferent motor nerves responsible for therapy limiting side effects. 2-D and 3-D reconstructions of the ultrasound were directly compared to post-mortem histology in the same animals. Results: High-resolution ultrasound from the surgical pocket enabled 2-D and 3-D reconstruction of the cervical vagus and surrounding structures that accurately depicted the functional vagotopy of the pig vagus nerve as confirmed via histology. Although resolution was not sufficient to match specific fascicles between ultrasound and histology 1 to 1, it was sufficient to trace fascicle groupings from a point of known functional organization at the nodose ganglia to their locations within the surgical window at stimulating electrode placement. Naïve volunteers were able place an electrode proximal to the sensory afferent grouping of fascicles and away from the motor nerve efferent grouping of fascicles in each subject (n = 3). Conclusion: The surgical pocket itself provides a unique opportunity to obtain higher resolution ultrasound images of neural targets responsible for intended therapeutic effect and limiting off-target effects. We demonstrate the increase in resolution is sufficient to aid patient-specific electrode placement to optimize outcomes. This simple technique could be easily adopted for multiple neuromodulation targets to better understand how patient specific anatomy impacts functional outcomes.

ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds): A pipeline for sample-specific computational modeling of electrical stimulation of peripheral nerves.

Electrical stimulation and block of peripheral nerves hold great promise for treatment of a range of disease and disorders, but promising results from preclinical studies often fail to translate to successful clinical therapies. Differences in neural anatomy across species require different electrodes and stimulation parameters to achieve equivalent nerve responses, and accounting for the consequences of these factors is difficult. We describe the implementation, validation, and application of a standardized, modular, and scalable computational modeling pipeline for biophysical simulations of electrical activation and block of nerve fibers within peripheral nerves. The ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds) pipeline provides a suite of built-in capabilities for user control over the entire workflow, including libraries for parts to assemble electrodes, electrical properties of biological materials, previously published fiber models, and common stimulation waveforms. We validated the accuracy of ASCENT calculations, verified usability in beta release, and provide several compelling examples of ASCENT-implemented models. ASCENT will enable the reproducibility of simulation data, and it will be used as a component of integrated simulations with other models (e.g., organ system models), to interpret experimental results, and to design experimental and clinical interventions for the advancement of peripheral nerve stimulation therapies.

Non-monotonic kilohertz frequency neural block thresholds arise from amplitude- and frequency-dependent charge imbalance.

Reversible block of nerve conduction using kilohertz frequency electrical signals has substantial potential for treatment of disease. However, the ability to block nerve fibers selectively is limited by poor understanding of the relationship between waveform parameters and the nerve fibers that are blocked. Previous in vivo studies reported non-monotonic relationships between block signal frequency and block threshold, suggesting the potential for fiber-selective block. However, the mechanisms of non-monotonic block thresholds were unclear, and these findings were not replicated in a subsequent in vivo study. We used high-fidelity computational models and in vivo experiments in anesthetized rats to show that non-monotonic threshold-frequency relationships do occur, that they result from amplitude- and frequency-dependent charge imbalances that cause a shift between kilohertz frequency and direct current block regimes, and that these relationships can differ across fiber diameters such that smaller fibers can be blocked at lower thresholds than larger fibers. These results reconcile previous contradictory studies, clarify the mechanisms of interaction between kilohertz frequency and direct current block, and demonstrate the potential for selective block of small fiber diameters.

Excitation properties of computational models of unmyelinated peripheral axons.

Biophysically based computational models of nerve fibers are important tools for designing electrical stimulation therapies, investigating drugs that affect ion channels, and studying diseases that affect neurons. Although peripheral nerves are primarily composed of unmyelinated axons (i.e., C-fibers), most modeling efforts focused on myelinated axons. We implemented the single-compartment model of vagal afferents from Schild et al. (1994) (Schild JH, Clark JW, Hay M, Mendelowitz D, Andresen MC, Kunze DL. J Neurophysiol 71: 2338-2358, 1994) and extended the model into a multicompartment axon, presenting the first cable model of a C-fiber vagal afferent. We also implemented the updated parameters from the Schild and Kunze (1997) model (Schild JH, Kunze DL. J Neurophysiol 78: 3198-3209, 1997). We compared the responses of these novel models with those of three published models of unmyelinated axons (Rattay F, Aberham M. IEEE Trans Biomed Eng 40: 1201-1209, 1993; Sundt D, Gamper N, Jaffe DB. J Neurophysiol 114: 3140-3153, 2015; Tigerholm J, Petersson ME, Obreja O, Lampert A, Carr R, Schmelz M, Fransén E. J Neurophysiol 111: 1721-1735, 2014) and with experimental data from single-fiber recordings. Comparing the two models by Schild et al. (1994, 1997) revealed that differences in rest potential and action potential shape were driven by changes in maximum conductances rather than changes in sodium channel dynamics. Comparing the five model axons, the conduction speeds and strength-duration responses were largely within expected ranges, but none of the models captured the experimental threshold recovery cycle-including a complete absence of late subnormality in the models-and their action potential shapes varied dramatically. The Tigerholm et al. (2014) model best reproduced the experimental data, but these modeling efforts make clear that additional data are needed to parameterize and validate future models of autonomic C-fibers.NEW & NOTEWORTHY Peripheral nerves are primarily composed of unmyelinated axons, and there is growing interest in electrical stimulation of the autonomic nervous system to treat various diseases. We present the first cable model of an unmyelinated vagal nerve fiber and compare its ion channel isoforms and conduction responses with other published models of unmyelinated axons, establishing important tools for advancing modeling of autonomic nerves.

Quantified Morphology of the Cervical and Subdiaphragmatic Vagus Nerves of Human, Pig, and Rat.

It is necessary to understand the morphology of the vagus nerve (VN) to design and deliver effective and selective vagus nerve stimulation (VNS) because nerve morphology influences fiber responses to electrical stimulation. Specifically, nerve diameter (and thus, electrode-fiber distance), fascicle diameter, fascicular organization, and perineurium thickness all significantly affect the responses of nerve fibers to electrical signals delivered through a cuff electrode. We quantified the morphology of cervical and subdiaphragmatic VNs in humans, pigs, and rats: effective nerve diameter, number of fascicles, effective fascicle diameters, proportions of endoneurial, perineurial, and epineurial tissues, and perineurium thickness. The human and pig VNs were comparable sizes (∼2 mm cervically; ∼1.6 mm subdiaphragmatically), while the rat nerves were ten times smaller. The pig nerves had ten times more fascicles-and the fascicles were smaller-than in human nerves (47 vs. 7 fascicles cervically; 38 vs. 5 fascicles subdiaphragmatically). Comparing the cervical to the subdiaphragmatic VNs, the nerves and fascicles were larger at the cervical level for all species and there were more fascicles for pigs. Human morphology generally exhibited greater variability across samples than pigs and rats. A prior study of human somatic nerves indicated that the ratio of perineurium thickness to fascicle diameter was approximately constant across fascicle diameters. However, our data found thicker human and pig VN perineurium than those prior data: the VNs had thicker perineurium for larger fascicles and thicker perineurium normalized by fascicle diameter for smaller fascicles. Understanding these differences in VN morphology between preclinical models and the clinical target, as well as the variability across individuals of a species, is essential for designing suitable cuff electrodes and stimulation parameters and for informing translation of preclinical results to clinical application to advance the therapeutic efficacy of VNS.

Quantitative comparisons of block thresholds and onset responses for charge-balanced kilohertz frequency waveforms.

OBJECTIVE: There is growing interest in delivering kilohertz frequency (KHF) electrical signals to block conduction in peripheral nerves for treatment of various diseases. Previous studies used different KHF waveforms to achieve block, and it remains unclear how waveform affects nerve block parameters. APPROACH: We quantified the effects of waveform on KHF block of the rat tibial nerve in vivo and in computational models. We compared block thresholds and onset responses across current-controlled sinusoids and charge-balanced rectangular waveforms with different asymmetries and duty cycles. MAIN RESULTS: Sine waves had higher block thresholds than square waves, but used less power at block threshold. Block threshold had an inverse relationship with duty cycle of rectangular waveforms irrespective of waveform asymmetry. Computational model results were consistent with relationships measured in vivo, although the models underestimated the effect of duty cycle on increasing thresholds. The axonal membrane substantially filtered waveforms, the filter transfer function was strikingly similar across waveforms, and filtering resulted in post-filtered rms block thresholds that were approximately constant across waveforms in silico and in vivo. Onset response was not consistently affected by waveform shape, but onset response was smaller at amplitudes well above block threshold. Therefore, waveforms with lower block thresholds (e.g. sine waves or square waves) could be more readily increased to higher amplitudes relative to block threshold to reduce onset response. We also observed a reduction in onset responses across consecutive trials after initial application of supra-block threshold amplitudes. SIGNIFICANCE: Waveform had substantial effects on block thresholds, and the amplitude relative to block threshold had substantial effects on onset response. These data inform choice of waveform in subsequent studies and clinical applications, enhance effective use of block in therapeutic applications, and facilitate the design of parameters that achieve block with minimal onset responses.

Sources of off-target effects of vagus nerve stimulation using the helical clinical lead in domestic pigs.

Objective: Clinical data suggest that efficacious vagus nerve stimulation (VNS) is limited by side effects such as cough and dyspnea that have stimulation thresholds lower than those for therapeutic outcomes. VNS side effects are putatively caused by activation of nearby muscles within the neck, via direct muscle activation or activation of nerve fibers innervating those muscles. Our goal was to determine the thresholds at which various VNS-evoked effects occur in the domestic pig­an animal model with vagus anatomy similar to human­using the bipolar helical lead deployed clinically. Approach: Intrafascicular electrodes were placed within the vagus nerve to record electroneurographic (ENG) responses, and needle electrodes were placed in the vagal-innervated neck muscles to record electromyographic (EMG) responses. Main results: Contraction of the cricoarytenoid muscle occurred at low amplitudes (~0.3 mA) and resulted from activation of motor nerve fibers in the cervical vagus trunk within the electrode cuff which bifurcate into the recurrent laryngeal branch of the vagus. At higher amplitudes (~1.4 mA), contraction of the cricoarytenoid and cricothyroid muscles was generated by current leakage outside the cuff to activate motor nerve fibers running within the nearby superior laryngeal branch of the vagus. Activation of these muscles generated artifacts in the ENG recordings that may be mistaken for compound action potentials representing slowly conducting Aδ-, B-, and C-fibers. Significance: Our data resolve conflicting reports of the stimulation amplitudes required for C-fiber activation in large animal studies (>10 mA) and human studies (<250 µA). After removing muscle-generated artifacts, ENG signals with post-stimulus latencies consistent with Aδ- and B-fibers occurred in only a small subset of animals, and these signals had similar thresholds to those that caused bradycardia. By identifying specific neuroanatomical pathways that cause off-target effects and characterizing the stimulation dose-response curves for on- and off-target effects, we hope to guide interpretation and optimization of clinical VNS.

Functional vagotopy in the cervical vagus nerve of the domestic pig: implications for the study of vagus nerve stimulation.

OBJECTIVE: Given current clinical interest in vagus nerve stimulation (VNS), there are surprisingly few studies characterizing the anatomy of the vagus nerve in large animal models as it pertains to on-and off-target engagement of local fibers. We sought to address this gap by evaluating vagal anatomy in the pig, whose vagus nerve organization and size approximates the human vagus nerve. APPROACH: Here we combined microdissection, histology, and immunohistochemistry to provide data on key features across the cervical vagus nerve in a swine model, and compare our results to other animal models (mouse, rat, dog, non-human primate) and humans. MAIN RESULTS: In a swine model we quantified the nerve diameter, number and diameter of fascicles, and distance of fascicles from the epineural surface where stimulating electrodes are placed. We also characterized the relative locations of the superior and recurrent laryngeal branches of the vagus nerve that have been implicated in therapy limiting side effects with common electrode placement. We identified key variants across the cohort that may be important for VNS with respect to changing sympathetic/parasympathetic tone, such as cross-connections to the sympathetic trunk. We discovered that cell bodies of pseudo-unipolar cells aggregate together to form a very distinct grouping within the nodose ganglion. This distinct grouping gives rise to a larger number of smaller fascicles as one moves caudally down the vagus nerve. This often leads to a distinct bimodal organization, or 'vagotopy'. This vagotopy was supported by immunohistochemistry where approximately half of the fascicles were immunoreactive for choline acetyltransferase, and reactive fascicles were generally grouped in one half of the nerve. SIGNIFICANCE: The vagotopy observed via histology may be advantageous to exploit in design of electrodes/stimulation paradigms. We also placed our data in context of historic and recent histology spanning multiple models, thus providing a comprehensive resource to understand similarities and differences across species.

Empirically Based Guidelines for Selecting Vagus Nerve Stimulation Parameters in Epilepsy and Heart Failure.

Vagus nerve stimulation (VNS) is a promising therapy to treat patients with epilepsy and heart failure. Outcomes of preclinical studies and clinical trials indicate that the selection of stimulation parameters has a direct impact on therapeutic efficacy and patient tolerability, suggesting that both the efficacy and tolerability of VNS could potentially be improved with a change in stimulation parameters. In this review, the success of translating stimulation parameters for epilepsy and heart failure from preclinical studies in animal models to human use in the clinic is evaluated on the basis of patient outcomes and stimulation-induced side effects. Data suggest that patients receiving VNS for epilepsy may experience improved seizure reduction by increasing the frequency and/or duty cycle of stimulation as well as incorporating closed-loop systems to deliver stimulation closer to seizure onset. Further, data suggest that VNS for heart failure is limited by the inability to activate the nerve fibers mediating therapeutic benefit without co-activation of side effect-inducing fibers. This may explain why pivotal trials of VNS for heart failure failed to meet primary efficacy outcomes despite promising preclinical outcomes in animal models. Improved characterization of the relationship between the stimulation parameter space and recruitment of the underlying fiber populations will likely expand the use of VNS to treat a variety of diseases and also improve upon current understanding of the mechanisms of action underlying VNS.