Computational modeling of autonomic nerve stimulation: Vagus et al.

Computational models of electrical stimulation, block and recording of autonomic nerves enable analysis of mechanisms of action underlying neural responses and design of optimized stimulation parameters. We reviewed advances in computational modeling of autonomic nerve stimulation, block, and recording over the past five years, with a focus on vagus nerve stimulation, including both implanted and less invasive approaches. Few models achieved quantitative validation, but integrated computational pipelines increase the reproducibility, reusability, and accessibility of computational modeling.

Reverse-engineered models reveal differential membrane properties of autonomic and cutaneous unmyelinated fibers.

Unmyelinated C-fibers constitute the vast majority of axons in peripheral nerves and play key roles in homeostasis and signaling pain. However, little is known about their ion channel expression, which controls their firing properties. Also, because of their small diameters (~ 1 μm), it has not been possible to characterize their membrane properties using voltage clamp.

Highly efficient modeling and optimization of neural fiber responses to electrical stimulation.

Peripheral neuromodulation has emerged as a powerful modality for controlling physiological functions and treating a variety of medical conditions including chronic pain and organ dysfunction. The underlying complexity of the nonlinear responses to electrical stimulation make it challenging to design precise and effective neuromodulation protocols. Computational models have thus become indispensable in advancing our understanding and control of neural responses to electrical stimulation.

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.

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.

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.

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.

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

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.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.

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

. 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.

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).

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.

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

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).We collected eight mid-cVN specimens from five fixed cadavers (three left nerves, five right nerves).

Visualization of Pig Vagus Nerve "Vagotopy" Using Ultrasound.

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. 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.

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.

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.

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.

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.

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.

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 pig—an animal model with vagus anatomy similar to human—using the bipolar helical lead deployed clinically.

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.

On the parameters used in finite element modeling of compound peripheral nerves.

Objective: Computational modeling is an important tool for developing and optimizing implantable neural stimulation devices, but requires accurate electrical and geometrical parameter values to improve predictive value. We quantified the effects of perineurial (resistive sheath around each fascicle) and endoneurial (within each fascicle) parameter values for modeling peripheral nerve stimulation.

Approach: We implemented 3D finite element models of compound peripheral nerves and cuff electrodes to quantify activation and block thresholds of model axons.

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.

Modeling Current Sources for Neural Stimulation in COMSOL.

Computational modeling provides an important toolset for designing and analyzing neural stimulation devices to treat neurological disorders and diseases. Modeling enables efficient exploration of large parameter spaces, where preclinical and clinical studies would be infeasible. Current commercial finite element method software packages enable straightforward calculation of the potential distributions, but it is not always clear how to implement boundary conditions to appropriately represent metal stimulating electrodes.