Flat electrode contacts for vagus nerve stimulation

Vagal nerve stimulation dynamically alters anxiety-like behavior in rats

BACKGROUND

Electrical vagal nerve stimulation (VNS), at currents designed to target sensory, interoceptive neurons, decreases anxiety-like behavior.

OBJECTIVE/HYPOTHESIS

We hypothesized that different VNS current intensities would differentially alter anxiety-like behavior through the activation of distinct brainstem circuits.

METHODS

Electrodes were implanted to stimulate the left vagus nerve and to record diaphragm muscle and electrocardiogram activity. The VNS current required to elicit the A-fiber-mediated Hering-Breuer Reflex (HBR) was determined for each animal. Based on this threshold, animals received either sham stimulation or VNS at 1.5 (mid-intensity VNS) or 3 (higher-intensity VNS) times the threshold for HBR activation. Anxiety-like behavior was assessed using the elevated plus maze, open field test, and novelty-suppressed feeding test. Additionally, a place preference assay determined whether VNS is rewarding or aversive. Finally, a c-Fos assay was performed to evaluate VNS-driven neuronal activation within the brainstem.

RESULTS

Mid-intensity VNS reduced anxiety-like behavior in the elevated plus maze and open field test. Higher-intensity VNS was aversive during the place preference assay, confounding anxiety measures. Both intensities increased overall c-Fos expression in neurons within the nucleus of the solitary tract, but mid-intensity VNS specifically increased c-Fos expression in noradrenergic neurons within the nucleus of the solitary tract while decreasing it in the locus coeruleus. In contrast, higher-intensity VNS had no effect on c-Fos expression in noradrenergic neurons of either the nucleus of the solitary tract or locus coeruleus.

CONCLUSION

Delivery of VNS induced reproducible, current intensity-dependent, effects on anxiety-like and aversive behavior in rats.

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. Model-based optimization enabled design of electrode geometries and stimulation parameters for selective activation (across fiber locations or types). Growing efforts link models of neural activity to downstream physiological responses to represent more directly the therapeutic effects and side effects of stimulation. Thus, computational modeling is an increasingly important tool for analysis and design of bioelectronic therapies.

Multi-Channel Microscale Nerve Cuffs for Spatially Selective Neuromodulation

Peripheral nerve modulation via electrical stimulation shows promise for treating several diseases, but current approaches lack selectivity, leading to side effects. Exploring selective neuromodulation with commercially available nerve cuffs is impractical due to their high cost and limited spatial resolution. While custom cuffs reported in the literature achieve high spatial resolutions, they require specialized microfabrication equipment and significant effort to produce even a single design. This inability to rapidly and cost-effectively prototype novel cuff designs impedes research into selective neuromodulation therapies in acute studies. To address this, we developed a reproducible method to easily create multi-channel epineural nerve cuffs for selective fascicular neuromodulation. Leveraging commercial flexible printed circuit (FPC) technology, we created cuffs with high spatial resolution (50 μm) and customizable parameters like electrode size, channel count, and cuff diameter. We designed cuffs to accommodate adult mouse or rat sciatic nerves (300-1500 μm diameter). We coated the electrodes with PEDOT:PSS to improve the charge injection capacity. We demonstrated selective neuromodulation in both rats and mice, achieving preferential activation of the tibialis anterior (TA) and lateral gastrocnemius (LG) muscles. Selectivity was confirmed through micro-computed tomography (μCT) and quantified through a selectivity index. These results demonstrate the potential of this fabrication method for enabling selective neuromodulation studies while significantly reducing production time and costs compared to traditional approaches.

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.

A Review on Implantable Neuroelectrodes

The efficacy of every neuromodulation modality depends upon the characteristics of the electrodes used to stimulate the chosen target. The geometrical, chemical, mechanical and physical configuration of electrodes used in neurostimulation affects several performance attributes like stimulation efficiency, selectivity, tissue response, etc. The efficiency of stimulation in relation to electrode impedance is influenced by the electrode material and/or its geometry. The nature of the electrode material determines the charge transfer across the electrode-tissue interface, which also relates to neuronal tissue damage. Electrode morphology or configuration pattern can facilitate the modulation of extracellular electric field (field shaping). This enables selective activation of neurons and minimizes side effects. Biocompatibility and biostability of the electrode materials or electrode coating have a role in glial formation and tissue damage. Mechanical and electrochemical stability (corrosion resistance) determines the long-term efficacy of any neuromodulation technique. Here, a review of electrodes typically used for implantable neuromodulation is discussed. Factors affecting the performance of electrodes like stimulation efficiency, selectivity and tissue responses to the electrode-tissue interface are discussed. Technological advancements to improve electrode characteristics are also included.

Nonlinear Closed-Loop Predictive Control of Heart Rate and Blood Pressure Using Vagus Nerve Stimulation: An In Silico Study

We propose a nonlinear model-based control technique for regulating the heart rate and blood pressure using vagus nerve neuromodulation. The closed-loop framework is based on an in silico model of the rat cardiovascular system for the simulation of the hemodynamic response to multi-location vagal nerve stimulation. The in silico model is derived by compartmentalizing the various physiological components involved in the closed-loop cardiovascular system with intrinsic baroreflex regulation to virtually generate nominal and hypertension-related heart dynamics of rats in rest and exercise states. The controller, using a reduced cycle-averaged model, monitors the outputs from the in silico model, estimates the current state of the reduced model, and computes the optimum stimulation locations and the corresponding parameters using a nonlinear model predictive control algorithm. The results demonstrate that the proposed control strategy is robust with respect to its ability to handle setpoint tracking and disturbance rejection in different simulation scenarios.

Modulating individual axons and axonal populations in the peripheral nerve using transverse intrafascicular multichannel electrodes

Objective.A transverse intrafascicular multichannel electrode (TIME) may offer advantages over more conventional cuff electrodes including higher spatial selectivity and reduced stimulation charge requirements. However, the performance of TIME, especially in the context of non-conventional stimulation waveforms, remains relatively unexplored. As part of our overarching goal of investigating stimulation efficacy of TIME, we developed a computational toolkit that automates the creation and usage ofin siliconerve models with TIME setup, which solves nerve responses using cable equations and computes extracellular potentials using finite element method.Approach.We began by implementing a flexible and scalable Python/MATLAB-based toolkit for automatically creating models of nerve stimulation in the hybrid NEURON/COMSOL ecosystems. We then developed a sciatic nerve model containing 14 fascicles with 1,170 myelinated (A-type, 30%) and unmyelinated (C-type, 70%) fibers to study fiber responses over a variety of TIME arrangements (monopolar and hexapolar) and stimulation waveforms (kilohertz stimulation and cathodic ramp modulation).Main results.Our toolkit obviates the conventional need to re-create the same nerve in two disparate modeling environments and automates bi-directional transfer of results. Our population-based simulations suggested that kilohertz stimuli provide selective activation of targeted C fibers near the stimulating electrodes but also tended to activate non-targeted A fibers further away. However, C fiber selectivity can be enhanced by hexapolar TIME arrangements that confined the spatial extent of electrical stimuli. Improved upon prior findings, we devised a high-frequency waveform that incorporates cathodic DC ramp to completely remove undesirable onset responses.Conclusion.Our toolkit allows agile, iterative design cycles involving the nerve and TIME, while minimizing the potential operator errors during complex simulation. The nerve model created by our toolkit allowed us to study and optimize the design of next-generation intrafascicular implants for improved spatial and fiber-type selectivity.

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.

Wireless optoelectronic devices for vagus nerve stimulation in mice

Objective.Vagus nerve stimulation (VNS) is a promising approach for the treatment of a wide variety of debilitating conditions, including autoimmune diseases and intractable epilepsy. Much remains to be learned about the molecular mechanisms involved in vagus nerve regulation of organ function. Despite an abundance of well-characterized rodent models of common chronic diseases, currently available technologies are rarely suitable for the required long-term experiments in freely moving animals, particularly experimental mice. Due to challenging anatomical limitations, many relevant experiments require miniaturized, less invasive, and wireless devices for precise stimulation of the vagus nerve and other peripheral nerves of interest. Our objective is to outline possible solutions to this problem by using nongenetic light-based stimulation.Approach.We describe how to design and benchmark new microstimulation devices that are based on transcutaneous photovoltaic stimulation. The approach is to use wired multielectrode cuffs to test different stimulation patterns, and then build photovoltaic stimulators to generate the most optimal patterns. We validate stimulation through heart rate analysis.Main results.A range of different stimulation geometries are explored with large differences in performance. Two types of photovoltaic devices are fabricated to deliver stimulation: photocapacitors and photovoltaic flags. The former is simple and more compact, but has limited efficiency. The photovoltaic flag approach is more elaborate, but highly efficient. Both can be used for wireless actuation of the vagus nerve using light impulses.Significance.These approaches can enable studies in small animals that were previously challenging, such as long-termin vivostudies for mapping functional vagus nerve innervation. This new knowledge may have potential to support clinical translation of VNS for treatment of select inflammatory and neurologic diseases.

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.

Short-pulsed micro-magnetic stimulation of the vagus nerve

Vagus nerve stimulation (VNS) is commonly used to treat drug-resistant epilepsy and depression. The therapeutic effect of VNS depends on stimulating the afferent vagal fibers. However, the vagus is a mixed nerve containing afferent and efferent fibers, and the stimulation of cardiac efferent fibers during VNS may produce a rare but severe risk of bradyarrhythmia. This side effect is challenging to mitigate since VNS, via electrical stimulation technology used in clinical practice, requires unique electrode design and pulse optimization for selective stimulation of only the afferent fibers. Here we describe a method of VNS using micro-magnetic stimulation (µMS), which may be an alternative technique to induce a focal stimulation, enabling a selective fiber stimulation. Micro-coils were implanted into the cervical vagus nerve in adult male Wistar rats. For comparison, the physiological responses were recorded continuously before, during, and after stimulation with arterial blood pressure (ABP), respiration rate (RR), and heart rate (HR). The electrical VNS caused a decrease in ABP, RR, and HR, whereas µM-VNS only caused a transient reduction in RR. The absence of an HR modulation indicated that µM-VNS might provide an alternative technology to VNS with fewer heart-related side effects, such as bradyarrhythmia. Numerical electromagnetic simulations helped estimate the optimal coil orientation with respect to the nerve to provide information on the electric field’s spatial distribution and strength. Furthermore, a transmission emission microscope provided very high-resolution images of the cervical vagus nerve in rats, which identified two different populations of nerve fibers categorized as large and small myelinated fibers.

Latest Views on the Mechanisms of Action of Surgically Implanted Cervical Vagal Nerve Stimulation in Epilepsy

BACKGROUND

Vagus nerve stimulation (VNS) is approved as an adjunctive treatment for drug-resistant epilepsy. Although there is a substantial amount of literature aiming at unraveling the mechanisms of action of VNS in epilepsy, it is still unclear how the cascade of events triggered by VNS leads to its antiepileptic effect.

OBJECTIVE

In this review, we integrated available peer-reviewed data on the effects of VNS in clinical and experimental research to identify those that are putatively responsible for its therapeutic effect. The topic of transcutaneous VNS will not be covered owing to the current lack of data supporting the differences and commonalities of its mechanisms of action in relation to invasive VNS.

SUMMARY OF THE MAIN FINDINGS

There is compelling evidence that the effect is obtained through the stimulation of large-diameter afferent myelinated fibers that project to the solitary tract nucleus, then to the parabrachial nucleus, which in turn alters the activity of the limbic system, thalamus, and cortex. VNS-induced catecholamine release from the locus coeruleus in the brainstem plays a pivotal role. Functional imaging studies tend to point toward a common vagal network that comes into play, made up of the amygdalo-hippocampal regions, left thalamus, and insular cortex.

CONCLUSIONS

Even though some crucial pieces are missing, neurochemical, molecular, cellular, and electrophysiological changes occur within the vagal afferent network at three main levels (the brainstem, the limbic system [amygdala and hippocampus], and the cortex). At this final level, VNS notably alters functional connectivity, which is known to be abnormally high within the epileptic zone and was shown to be significantly decreased by VNS in responders. The effect of crucial VNS parameters such as frequency or current amplitude on functional connectivity metrics is of utmost importance and requires further investigation.

Strategies for precision vagus neuromodulation

The vagus nerve is involved in the autonomic regulation of physiological homeostasis, through vast innervation of cervical, thoracic and abdominal visceral organs. Stimulation of the vagus with bioelectronic devices represents a therapeutic opportunity for several disorders implicating the autonomic nervous system and affecting different organs. During clinical translation, vagus stimulation therapies may benefit from a precision medicine approach, in which stimulation accommodates individual variability due to nerve anatomy, nerve-electrode interface or disease state and aims at eliciting therapeutic effects in targeted organs, while minimally affecting non-targeted organs. In this review, we discuss the anatomical and physiological basis for precision neuromodulation of the vagus at the level of nerve fibers, fascicles, branches and innervated organs. We then discuss different strategies for precision vagus neuromodulation, including fascicle- or fiber-selective cervical vagus nerve stimulation, stimulation of vagal branches near the end-organs, and ultrasound stimulation of vagus terminals at the end-organs themselves. Finally, we summarize targets for vagus neuromodulation in neurological, cardiovascular and gastrointestinal disorders and suggest potential precision neuromodulation strategies that could form the basis for effective and safe therapies.

A finite element method framework to model extracellular neural stimulation

OBJECTIVE

Increasing complexity in extracellular stimulation experiments and neural implant design also requires realistic computer simulations capable of modeling the neural activity of nerve cells under the influence of an electrical stimulus. Classical model approaches are often based on simplifications, are not able to correctly calculate the electric field generated by complex electrode designs, and do not consider electrical effects of the cell on its surrounding. A more accurate approach is the finite element method (FEM), which provides necessary techniques to solve the Poisson equation for complex geometries under consideration of electrical tissue properties. Especially in situations where neurons experience large and non-symmetric extracellular potential gradients, a FEM solution that implements the cell membrane model can improve the computer simulation results. To investigate the response of neurons in an electric field generated by complex electrode designs, a FEM framework for extracellular stimulation was developed in COMSOL.

APPROACH

Methods to implement morphologically- and biophysically-detailed neurons including active Hodgkin-Huxley (HH) cell membrane dynamics as well as the stimulation setup are described in detail. Covered methods are (i) development of cell and electrode geometries including meshing strategies, (ii) assignment of physics for the conducting spaces and the realization of active electrodes, (iii) implementation of the HH model, and (iv) coupling of the physics to get a fully described model.

MAIN RESULTS

Several implementation examples are briefly presented: (i) a full FEM implementation of a HH model cell stimulated with a honeycomb electrode, (ii) the electric field of a cochlear electrode placed inside the cochlea, and (iii) a proof of concept implementation of a detailed double-cable cell membrane model for myelinated nerve fibers.

SIGNIFICANCE

The presented concepts and methods provide basic and advanced techniques to realize a full FEM framework for innovative studies of neural excitation in response to extracellular stimulation.

Vagus nerve bundle stimulation using 1505-nm laser irradiation in an in-vivo rat model

Laser nerve stimulation using near-infrared laser irradiation has recently been studied in the peripheral nervous system as an alternative method to conventional electrical nerve stimulation. Bringing this method to the vagus nerve model could leverage this emerging stimulation approach to be tested in broader preclinical applications. Here, we report the capability of the laser nerve stimulation method on the rat vagus nerve bundle with a 1505-nm diode laser operated in continuous-wave mode. Studies of the stimulation threshold and laser-induced acute thermal injury to the nerve bundle were also performed to determine a temperature window for safe, reliable and reproducible laser stimulation of the rat vagus nerve bundle. The results show that laser stimulation of the vagus nerve bundle provides reliable and reproducible nerve stimulation in a rat model. These results also confirm a threshold temperature of >42°C with acute nerve damage observed above 46°C. A strong correlation was obtained between the laser time required to raise the nerve temperature above the stimulation threshold and the mean arterial pressure response. Advantages of the method such as non-contact delivery of external stimulus signals at mm scaled distance in air, enhanced spatial selectivity and electrical artefact-free measurements may indicate its potential to counteract the side effects of conventional electrical vagus nerve stimulation.

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.

Despite promising results from preclinical studies, novel therapies using electrical stimulation of peripheral nerves often fail to produce successful clinical outcomes due to differences in neural anatomy across species. These differences often require different electrodes to interface with the nerves and/or different stimulation parameters to achieve equivalent nerve responses. Further, differences in nerve anatomy across a population contribute to differences in nerve responses to stimulation. These inter-species and inter-individual differences can be studied using computational modeling of individual-specific peripheral nerve morphology and biophysical properties. To accelerate the process of computational modeling of individual nerve anatomy, we developed ASCENT, a software platform for simulating the responses of sample-specific nerves to electrical stimulation with custom electrodes and stimulation parameters. ASCENT automates the complex, multi-step process required to build computational models of preclinical and clinical studies and to design novel stimulation protocols using biophysically realistic simulations. The ASCENT pipeline will be used to develop technologies that increase the selectivity and efficiency of stimulation and to accelerate the translation of novel peripheral nerve stimulation therapies to the clinic.

Assessment of the Use of Multi-Channel Organic Electrodes to Record ENG on Small Nerves: Application to Phrenic Nerve Burst Detection

Effective closed-loop neuromodulation relies on the acquisition of appropriate physiological control variables and the delivery of an appropriate stimulation signal. In particular, electroneurogram (ENG) data acquired from a set of electrodes applied at the surface of the nerve may be used as a potential control variable in this field. Improved electrode technologies and data processing methods are clearly needed in this context. In this work, we evaluated a new electrode technology based on multichannel organic electrodes (OE) and applied a signal processing chain in order to detect respiratory-related bursts from the phrenic nerve. Phrenic ENG (pENG) were acquired from nine Long Evans rats in situ preparations. For each preparation, a 16-channel OE was applied around the phrenic nerve’s surface and a suction electrode was applied to the cut end of the same nerve. The former electrode provided input multivariate pENG signals while the latter electrode provided the gold standard for data analysis. Correlations between OE signals and that from the gold standard were estimated. Signal to noise ratio (SNR) and ROC curves were built to quantify phrenic bursts detection performance. Correlation score showed the ability of the OE to record high-quality pENG. Our methods allowed good phrenic bursts detection. However, we failed to demonstrate a spatial selectivity from the multiple pENG recorded with our OE matrix. Altogether, our results suggest that highly flexible and biocompatible multi-channel electrode may represent an interesting alternative to metallic cuff electrodes to perform nerve bursts detection and/or closed-loop neuromodulation.

Validation of a parameterized, open-source model of nerve stimulation

Peripheral nerve stimulation is an effective treatment for various neurological disorders. The method of activation and stimulation parameters used impact the efficacy of the therapy, which emphasizes the need for tools to model this behavior. Computational modeling of nerve stimulation has proven to be a useful tool for estimating stimulation thresholds, optimizing electrode design, and exploring previously untested stimulation methods. Despite their utility, these tools require access to and familiarity with several pieces of specialized software. A simpler, streamlined process would increase accessibility significantly. We developed an open-source, parameterized model with a simple online user interface that allows user to adjust up to 36 different parameters (https://nervestimlab.utdallas.edu). The model accurately predicts fiber activation thresholds for nerve and electrode combinations reported in literature. Additionally, it replicates characteristic differences between stimulation methods, such as lower thresholds with monopolar stimulation as compared to tripolar stimulation. The model predicted that the difference in threshold between monophasic and biphasic waveforms, a well-characterized phenomenon, is not present during stimulation with bipolar electrodes.In vivotesting on the rat sciatic nerve validated this prediction, which has not been previously reported. The accuracy of the model when compared to previous experiments, as well as the ease of use and accessibility to generate testable hypotheses, indicate that this software may represent a useful tool for a variety of nerve stimulation applications.

Implant- and anesthesia-related factors affecting cardiopulmonary threshold intensities for vagus nerve stimulation

Objective.Vagus nerve stimulation (VNS) is typically delivered at increasing stimulus intensity until a neurological or physiological response is observed ('threshold') for dose calibration, preclinically and therapeutically. Factors affecting VNS thresholds have not been studied systematically. In a rodent model of VNS we measured neural and physiological responses to increasing VNS intensity, determined neurological and physiological thresholds and examined the effect of implant- and anesthesia-related factors on thresholds.Approach.In acute and chronic vagus implants (45 and 20 rats, respectively) VNS was delivered under isoflurane, ketamine-xylazine, or awake conditions. Evoked compound action potentials (CAPs) were recorded and activation of different fiber types was extracted. Elicited physiological responses were registered, including changes in heart rate (HR), breathing rate (BR), and blood pressure (BP). CAP and physiological thresholds were determined.Main results. The threshold for evoking discernable CAPs (>10µV) (CAP threshold) is significantly lower than what elicits 5%-10% drop in heart rate (heart rate threshold, HRT) (25µA ± 1.8 vs. 80µA ± 5.1, respectively; mean ± SEM). Changes in BP and small changes in BR (bradypnea) occur at lowest intensities (70µA ± 8.3), followed by HR changes (80µA ± 5.1) and finally significant changes in BR (apnea) (310μA ± 32.5). HRT and electrode impedance are correlated in chronic (Pearson correlationr= 0.47;p< 0.001) but not in acute implants (r= -0.34;pNS); HRT and impedance both increase with implant age (r= 0.44;p< 0.001 andr= 0.64;p< 0.001, respectively). HRT is lowest when animals are awake (200µA ± 35.5), followed by ketamine-xylazine (640µA ± 151.5), and isoflurane (1000µA ± 139.5). The sequence of physiological responses with increasing VNS intensity is the same in anesthetized and awake animals. Pulsing frequency affects physiological responses but not CAPs.Significance. Implant age, electrode impedance, and type of anesthesia affect VNS thresholds and should be accounted for when calibrating stimulation dose.

High intensity VNS disrupts VNS-mediated plasticity in motor cortex

Vagus nerve stimulation (VNS) paired with motor rehabilitation enhances recovery of function after neurological injury in rats and humans. This effect is ascribed to VNS-dependent facilitation of plasticity in motor networks. Previous studies document an inverted-U relationship between VNS intensity and cortical plasticity, such that moderate intensities increase plasticity, while low or high intensity VNS does not. We tested the interaction of moderate and high intensity VNS trains to probe the mechanisms that may underlie VNS-dependent plasticity. Rats performed a behavioral task where VNS was paired with jaw movement during chewing. For five days, subjects received 100 pairings of moderate intensity VNS (Standard VNS), 100 pairings alternating between moderate and high intensity VNS (Interleaved VNS), or 50 pairings of moderate intensity VNS (Short VNS) approximately every 8 s. After the final behavioral session, intracortical microstimulation (ICMS) was used to evaluate movement representations in motor cortex. 100 pairings of moderate intensity VNS enhanced motor cortex plasticity. Replacing half of moderate intensity stimulation with high intensity VNS blocked this enhancement of plasticity. Removing high intensity stimulation, leaving only 50 pairings of moderate intensity VNS, reinstated plasticity. These results demonstrate that there is a period for at least 8 s after high intensity stimulation in which moderate intensity VNS is not able to engage mechanisms required for synaptic reorganization. More importantly, this study demonstrates that changes in stimulation parameters are a critical determinant of the magnitude of plasticity and likely the efficacy of VNS-enhanced recovery.

Use of a physiological reflex to standardize vagal nerve stimulation intensity improves data reproducibility in a memory extinction assay

BACKGROUND

Modulating brainstem activity, via electrical vagus nerve stimulation (VNS), influences cognitive functions, including memory. However, controlling for changes in stimulus efficacy during chronic studies, and response variability between subjects, is problematic.

OBJECTIVE/HYPOTHESIS

We hypothesized that recruitment of an autonomic reflex, the Hering-Breuer reflex, would provide robust confirmation of VNS efficacy. We compared this to measurement of electrode resistance over time. We also examined whether VNS modulates contextual memory extinction.

METHODS

Electrodes for VNS and diaphragm electromyography recording were implanted into anesthetized Sprague Dawley rats. When conscious, we measured the electrode resistance as well as the minimum VNS current required to evoke the Hering-Breuer reflex, before, and after, an inhibitory avoidance assay - a two chamber, dark/light model, where the dark compartment was paired with an aversive foot shock. The extinction of this contextual memory was assessed in sham and VNS treated rats, with VNS administered for 30 s at 1.5 times the Hering-Breuer reflex threshold during extinction memory formation.

RESULTS

Assessment of VNS-evoked Hering-Breuer reflex successfully identified defective electrodes. VNS accelerated extinction memory and decreased multiple physiological metrics of fear expression. We observed an inverse relationship between memory extinction and respiratory rate during the behavioural assay. Additionally, no current - response relationship between VNS and extinction memory formation was established.

CONCLUSION

These data demonstrate that reliable, experimental VNS studies can be produced by verifying reflex initiation as a consequence of stimulation. Further, studies could be standardised by indexing stimulator efficacy to initiation of autonomic reflexes.

Optimizing Dosing of Vagus Nerve Stimulation for Stroke Recovery

Vagus nerve stimulation (VNS) paired with rehabilitative training enhances recovery of function in models of stroke and is currently under investigation for use in chronic stroke patients. Dosing is critical in translation of pharmacological therapies, but electrical stimulation therapies often fail to comprehensively explore dosing parameters in preclinical studies. Varying VNS parameters has non-monotonic effects on plasticity in the central nervous system, which may directly impact efficacy for stroke. We sought to optimize stimulation intensity to maximize recovery of motor function in a model of ischemic stroke. The study design was preregistered prior to beginning data collection (DOI: https://doi.org/10.17605/OSF.IO/BMJEK ). After training on an automated assessment of forelimb function and receiving an ischemic lesion in motor cortex, rats were separated into groups that received rehabilitative training paired with VNS at distinct stimulation intensities (sham, 0.4 mA, 0.8 mA, or 1.6 mA). Moderate-intensity VNS at 0.8 mA enhanced recovery of function compared with all other groups. Neither 0.4 mA nor 1.6 mA VNS was sufficient to improve functional recovery compared with equivalent rehabilitation without VNS. These results demonstrate that moderate-intensity VNS delivered during rehabilitation improves recovery and defines an optimized intensity paradigm for clinical implementation of VNS therapy.