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Objective. Transcutaneous auricular vagus nerve stimulation (taVNS), a non-invasive method of stimulating the vagus nerve, simultaneously affects the autonomic nervous system (ANS) and central nervous system (CNS) through efferent and afferent pathways. The purpose of this study is to analyze the effect of taVNS on the ANS and CNS through heart rate variability (HRV) and electroencephalography (EEG) parameters of identified responders. Approach. Two sets of data were collected from each of 10 healthy adult male subjects in their 20 s, and five HRV parameters from the time domain (RMSSD, pNN50, pNN30, pNN20, ppNNx) and two EEG parameters (power of alpha band, power of delta band) were extracted. Main results. Based on pNN50, responders to taVNS were identified; among them, pNN50 ( p = 0.0041) and ppNNx ( p = 0.0037) showed significant differences before and after taVNS. At the same time, for alpha power and delta power of EEG, significant difference ( p < 0.05) was observed in most channels after taVNS compared to before stimulation. Significance. This study demonstrated the validity of identifying responders using pNN50 and the influence of taVNS on both the ANS and CNS. We conclude that taVNS can be used to treat a variety of diseases and as a tool to help control the ANS and CNS., (© 2024 IOP Publishing Ltd.)

Objective . Vagus nerve stimulation (VNS) is being investigated as a potential therapy for cardiovascular diseases including heart failure, cardiac arrhythmia, and hypertension. The lack of a systematic approach for controlling and tuning the VNS parameters poses a significant challenge. Closed-loop VNS strategies combined with artificial intelligence (AI) approaches offer a framework for systematically learning and adapting the optimal stimulation parameters. In this study, we presented an interactive AI framework using reinforcement learning (RL) for automated data-driven design of closed-loop VNS control systems in a computational study. Approach. Multiple simulation environments with a standard application programming interface were developed to facilitate the design and evaluation of the automated data-driven closed-loop VNS control systems. These environments simulate the hemodynamic response to multi-location VNS using biophysics-based computational models of healthy and hypertensive rat cardiovascular systems in resting and exercise states. We designed and implemented the RL-based closed-loop VNS control frameworks in the context of controlling the heart rate and the mean arterial pressure for a set point tracking task. Our experimental design included two approaches; a general policy using deep RL algorithms and a sample-efficient adaptive policy using probabilistic inference for learning and control. Main results. Our simulation results demonstrated the capabilities of the closed-loop RL-based approaches to learn optimal VNS control policies and to adapt to variations in the target set points and the underlying dynamics of the cardiovascular system. Our findings highlighted the trade-off between sample-efficiency and generalizability, providing insights for proper algorithm selection. Finally, we demonstrated that transfer learning improves the sample efficiency of deep RL algorithms allowing the development of more efficient and personalized closed-loop VNS systems. Significance. We demonstrated the capability of RL-based closed-loop VNS systems. Our approach provided a systematic adaptable framework for learning control strategies without requiring prior knowledge about the underlying dynamics., (Creative Commons Attribution license.)

Objective. In bioelectronic medicine, neuromodulation therapies induce neural signals to the brain or organs, modifying their function. Stimulation devices capable of triggering exogenous neural signals using electrical waveforms require a complex and multi-dimensional parameter space to control such waveforms. Determining the best combination of parameters (waveform optimization or dosing) for treating a particular patient's illness is therefore challenging. Comprehensive parameter searching for an optimal stimulation effect is often infeasible in a clinical setting due to the size of the parameter space. Restricting this space, however, may lead to suboptimal therapeutic results, reduced responder rates, and adverse effects. Approach . As an alternative to a full parameter search, we present a flexible machine learning, data acquisition, and processing framework for optimizing neural stimulation parameters, requiring as few steps as possible using Bayesian optimization. This optimization builds a model of the neural and physiological responses to stimulations, enabling it to optimize stimulation parameters and provide estimates of the accuracy of the response model. The vagus nerve (VN) innervates, among other thoracic and visceral organs, the heart, thus controlling heart rate (HR), making it an ideal candidate for demonstrating the effectiveness of our approach. Main results. The efficacy of our optimization approach was first evaluated on simulated neural responses, then applied to VN stimulation intraoperatively in porcine subjects. Optimization converged quickly on parameters achieving target HRs and optimizing neural B-fiber activations despite high intersubject variability. Significance. An optimized stimulation waveform was achieved in real time with far fewer stimulations than required by alternative optimization strategies, thus minimizing exposure to side effects. Uncertainty estimates helped avoiding stimulations outside a safe range. Our approach shows that a complex set of neural stimulation parameters can be optimized in real-time for a patient to achieve a personalized precision dosing., (© 2024 IOP Publishing Ltd.)

Objective . Neurostimulation is emerging as treatment for several diseases of the brain and peripheral organs. Due to variability arising from placement of stimulation devices, underlying neuroanatomy and physiological responses to stimulation, it is essential that neurostimulation protocols are personalized to maximize efficacy and safety. Building such personalized protocols would benefit from accumulated information in increasingly large datasets of other individuals' responses. Approach . To address that need, we propose a meta-learning family of algorithms to conduct few-shot optimization of key fitting parameters of physiological and neural responses in new individuals. While our method is agnostic to neurostimulation setting, here we demonstrate its effectiveness on the problem of physiological modeling of fiber recruitment during vagus nerve stimulation (VNS). Using data from acute VNS experiments, the mapping between amplitudes of stimulus-evoked compound action potentials (eCAPs) and physiological responses, such as heart rate and breathing interval modulation, is inferred. Main results . Using additional synthetic data sets to complement experimental results, we demonstrate that our meta-learning framework is capable of directly modeling the physiology-eCAP relationship for individual subjects with much fewer individually queried data points than standard methods. Significance . Our meta-learning framework is general and can be adapted to many input-response neurostimulation mapping problems. Moreover, this method leverages information from growing data sets of past patients, as a treatment is deployed. It can also be combined with several model types, including regression, Gaussian processes with Bayesian optimization, and beyond., (© 2024 IOP Publishing Ltd.)

Objective. This study aims to develop a comprehensive decoding framework to create a multivariate physiological model of vagus nerve transmission that reveals the complex interactions between the nervous and metabolic systems. Approach. Vagus nerve activity was recorded in female Sprague-Dawley rats using gold hook microwires implanted around the left cervical vagus nerve. The rats were divided into three experimental cohorts (intact nerve, ligation nerve for recording afferent activation, and ligation for recording efferent activation) and metabolic challenges were administered to change glucose levels while recording the nerve activity. The decoding methodology involved various techniques, including continuous wavelet transformation, extraction of breathing rate (BR), and correlation of neural metrics with physiological signals. Main results. Decrease in glucose level was consistently negatively correlated with an increase in the firing activity of the intact vagus nerve that was found to be conveyed by both afferent and efferent pathways, with the afferent response being more similar to the one on the intact nerve. A larger variability was observed in the sensory and motor responses to hyperglycaemia. A novel strategy to extract the BR over time based on inter-burst-interval is also presented. The vagus afferent was found to encode breathing information through amplitude and firing rate modulation. Modulations of the signal amplitude were also observed due to changes in heart rate in the intact and efferent recordings, highlighting the parasympathetic control of the heart. Significance. The analytical framework presented in this study provides an integrative understanding that considers the relationship between metabolic, cardiac, and breathing signals and contributes to the development of a multivariable physiological model for the transmission of vagus nerve signals. This work progresses toward the development of closed-loop neuro-metabolic therapeutic systems for diabetes., (Creative Commons Attribution license.)

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., (© 2023 IOP Publishing Ltd.)

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 of in vivo thresholds across all measured nerve and physiological responses (i.e. heart rate, A δ /B fibers, A γ fibers, electromyography, and A α fibers). 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., (© 2023 IOP Publishing Ltd.)

Objective. Although electrical vagus nerve stimulation has been shown to augment parasympathetic control of the heart, the effects of electrical conduction block have been less rigorously characterized. Previous experiments have demonstrated that direct current (DC) nerve block can be applied safely and effectively in the autonomic system, but additional information about the system dynamics need to be characterized to successfully deploy DC nerve block to clinical practice. Approach. The dynamics of the heart rate (HR) from DC nerve block of the vagus nerve were measured by stimulating the vagus nerve to lower the HR, and then applying DC block to restore normal rate. DC block achieved rapid, complete block, as well as partial block at lower amplitudes. Main Results . Complete block was also achieved using lower amplitudes, but with a slower induction time. The time for DC to induce complete block was significantly predicted by the amplitude; specifically, the amplitude expressed as a percentage of the current required for a rapid, 60 s induction time. Recovery times after the cessation of DC block could occur both instantly, and after a significant delay. Both blocking duration and injected charge were significant in predicting the delay in recovery to normal conduction. Significance . While these data show that broad features such as induction and recovery can be described well by the DC parameters, more precise features of the HR, such as the exact path of the induction and recoveries, are still undefined. These findings show promise for control of the cardiac autonomic nervous system, with potential to expand to the sympathetic inputs as well., (© 2023 IOP Publishing Ltd.)

Objective. Our previous study has shown that low-intensity focused ultrasound stimulation (FUS) of the vagus nerve could modulate blood pressure (BP), but its underlying mechanisms remain unclear. We hypothesized that low-intensity FUS of the vagus nerve would regulate autonomic function and thus BP. Approach. 17 anesthetized spontaneously hypertensive rats were treated with low-intensity FUS of the left vagus nerve for 15 min each trial. Continuous BP, heart rate, respiration rate (RR), and core body temperature were simultaneously recorded to evaluate the effects on BP and other physiological parameters. Heart rate variability (HRV), systolic BP variability, and baroreflex sensitivity were computed to evaluate the autonomic modulation function. A Control-sham group without stimulation and another Control-FUS group with non-target stimulation were also examined to exclude the influence of potential confounding factors on autonomic modulation. Main results. A prolonged significant decrease in BP, pulse pressure, RR, the normalized low-frequency power of HRV, and the low-to-high frequency power ratio of HRV were found after the low-intensity FUS of the left vagus nerve in comparison with the baseline and those of the control groups, demonstrating that activities of the sympathetic nervous system were inhibited. The prolonged significant increase of the normalized high-frequency power of HRV suggested the activation of parasympathetic activity. Significance. Low-intensity FUS of the left vagus nerve effectively improved the autonomic function by activating parasympathetic efferent and inhibiting sympathetic efferent, which contributes to BP reduction. The findings shed light on the hypotensive mechanism underlying FUS., (Creative Commons Attribution license.)

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 ∼560 µ m (17.8 ± 6.1 events cm -1 ). Mean morphological outcomes included: fascicle count (6.6 ± 2.8 fascicles; range 1-15), fascicle diameter (514 ± 142 µ m; range 147-1360 µ m), and total cross-sectional fascicular area (1.32 ± 0.41 mm 2 ; 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., (Creative Commons Attribution license.)

Objective . Auricular vagus nerve stimulation (aVNS) has recently emerged as a promising neuromodulation modality for blood pressure (BP) reduction due to its ease of use although its efficacy is still limited compared to direct baroreflex stimulation. Previous studies have also indicated that synaptic depression of nucleus tractus solitarius (NTS) in the baroreflex pathway depends on stimulus frequency. However, the nature of this frequency dependence phenomenon on antihypertensive effect has been unknown for aVNS. We aimed to investigate the antihypertensive effect of aVNS considering frequency-dependent depression characteristic in the NTS synapse. We explored NTS activation and BP reduction induced by aVNS and by direct secondary neuron stimulation (DS). Approach . Both protocols were performed with recording of NTS activation and BP response with stimulation for each frequency parameter (2, 4, 20, 50, and 80 Hz). Main results . The BP recovery time constant was significantly dependent on the frequency of DS and aVNS (DS-2 Hz: 8.17 ± 4.98; 4 Hz: 9.73 ± 6.3; 20 Hz: 6.61 ± 3.28; 50 Hz: 4.93 ± 1.65; 80 Hz: 4.00 ± 1.43, p < 0.001, Kruskal-Wallis (KW) H-test/aVNS-2 Hz: 4.02 ± 2.55; 4 Hz: 8.13 ± 4.05; 20 Hz: 6.40 ± 3.16; 50 Hz: 5.18 ± 2.37; 80 Hz: 3.13 ± 1.29, p < 0.05, KW H-test) despite no significant BP reduction at 2 Hz compared to sham groups ( p > 0.05, Mann-Whitney U-test). Significance . Our observations suggest that the antihypertensive effect of aVNS is influenced by the characteristics of frequency-dependent synaptic depression in the NTS neuron in terms of the BP recovery time. These findings suggest that the antihypertensive effect of aVNS can be improved with further understanding of the neurological properties of the baroreflex associated with aVNS, which is critical to push this new modality for clinical interpretation., (© 2022 IOP Publishing Ltd.)

Objective. Transcutaneous vagus nerve stimulation (tVNS) is a form of non-invasive brain stimulation that delivers a sequence of electrical pulses to the auricular branch of the vagus nerve and is used increasingly in the treatment of a number of health conditions such as epilepsy and depression. Recent research has focused on the efficacy of tVNS to treat different medical conditions, but there is little conclusive evidence concerning the optimal stimulation parameters. There are relatively few studies that have combined tVNS with a neuroimaging modality, and none that have attempted simultaneous magnetoencephalography (MEG) and tVNS due to the presence of large stimulation artifacts produced by the electrical stimulation which are many orders of magnitude larger than underlying brain activity. Approach. The aim of this study is to investigate the utility of MEG to gain insight into the regions of the brain most strongly influenced by tVNS and how variation of the stimulation parameters can affect this response in healthy participants. Main results. We have successfully demonstrated that MEG can be used to measure brain response to tVNS. We have also shown that varying the stimulation frequency can lead to a difference in brain response, with the brain also responding in different anatomical regions depending on the frequency. Significance. The main contribution of this paper is to demonstrate the feasibility of simultaneous pulsed tVNS and MEG recording, allowing direct investigation of the changes in brain activity that result from different stimulation parameters. This may lead to the development of customised therapeutic approaches for the targeted treatment of different conditions., (© 2022 IOP Publishing Ltd.)

Objective: Large-amplitude artifacts from vagus nerve stimulator (VNS) implants for refractory epilepsy affect magnetoencephalography (MEG) recordings and are difficult to reject, resulting in unusable data from this important population of patients who are frequently evaluated for surgical treatment of epilepsy. Here we compare the performance of two artifact removal algorithms for MEG data: dual signal subspace projection (DSSP) and temporally extended signal space separation (tSSS)., Approach: Each algorithm's performance was first evaluated in simulations. We then tested the performance of each algorithm on resting-state MEG data from patients with VNS implants. We also examined how each algorithm improved source localization of somatosensory evoked fields in patients with VNS implants., Main Results: DSSP and tSSS algorithms have a similar ability to reject interference in both simulated and real MEG data if the origin location for tSSS is appropriately set. If the origin set for tSSS is inappropriate, the signal after tSSS can be distorted due to a mismatch between the internal region and the actual source space. Both DSSP and tSSS are able to remove large-amplitude artifacts from outside the brain. DSSP might be a better choice than tSSS when the choice of origin location for tSSS is difficult., Significance: Both DSSP and tSSS algorithms can recover distorted MEG recordings from people with intractable epilepsy and VNS implants, improving epileptic spike identification and source localization of both functional activity and epileptiform activity.

Objective: Multipolar cuff electrode can selectively stimulate areas of peripheral nerves and therefore enable to control independent functions. However, the branching and fascicularization are known for a limited set of nerves and the specific organization remains subject-dependent. This paper presents general modeling and optimization methods in the context of multipolar stimulation using a cuff electrode without a priori knowledge of the nerve structure. Vagus nerve stimulation experiments based on the optimization results were then investigated., Approach: The model consisted of two independent components: a lead field matrix representing the transfer function from the applied current to the extracellular voltage present on the nodes of Ranvier along each axon, and a linear activation model. The optimization process consisted in finding the best current repartition (ratios) to reach activation of a targeted area depending on three criteria: selectivity, efficiency and robustness., Main Results: The results showed that state-of-the-art configurations (tripolar transverse, tripolar longitudinal) were part of the optimized solutions but new ones could emerge depending on the trade-off between the three criteria and the targeted area. Besides, the choice of appropriate current ratios was more important than the choice of the stimulation amplitude for a stimulation without a priori knowledge of the nerve structure. We successfully assessed the solutions in vivo to selectively induce a decrease in cardiac rhythm through vagus nerve stimulation while limiting side effects. Compared to the standard whole ring configuration, a selective solution found by simulation provided on average 2.6 less adverse effects., Significance: The preliminary results showed the rightness of the simulation, using a generic nerve geometry. It suggested that this approach will have broader applications that would benefit from multicontact cuff electrodes to elicit selective responses. In the context of the vagus nerve stimulation for heart failure therapy, we show that the simulation results were confirmed and improved the therapy while decreasing the side effects.

Objective: Numerous studies of vagal nerve stimulation (VNS) have been published showing it to be a potential treatment for chronic inflammation and other related diseases and disorders. Studies in recent years have shown that electrical stimulation of the vagal efferent fibers can artificially modulate cytokine levels and reduce systematic inflammation. Most VNS research in the treatment of inflammation have been acute studies on rodent subjects. Our study tested VNS on freely moving animals by stimulating and recording from the cervical vagus with nerve cuff electrodes over an extended period of time., Approach: We used methods of electrical stimulation, retrograde tracing (using Fluorogold) and post necropsy histological analysis of nerve tissue, flow cytometry to measure plasma cytokine levels, and MRI scanning of gastric emptying. This novel combination of methods allowed examination of physiological aspects of VNS previously unexplored., Main Results: Through our study of 53 rat subjects, we found that chronically cuffing the left cervical vagus nerve suppressed efferent Fluorogold transport in 43 of 44 animals (36 showed complete suppression). Measured cytokine levels and gastric emptying rates concurrently showed nominal differences between chronically cuffed rats and those tested with similar acute methods. Meanwhile, results of electrophysiological and histological tests of the cuffed nerves revealed them to be otherwise healthy, consistent with previous literature., Significance: We hypothesize that due to these unforeseen and unexplored physiological consequences of the chronically cuffed vagus nerve in a rat, that inflammatory modulation and other vagal effects by VNS may become unreliable in chronic studies. Given our findings, we submit that it would benefit the VNS community to re-examine methods used in previous literature to verify the efficacy of the rat model for chronic VNS studies.

Objective: Vagal nerve stimulation (VNS) has shown potential benefits for obesity treatment; however, current devices lack physiological feedback, which limit their efficacy. Changes in extracellular pH (pH e ) have shown to be correlated with neural activity, but have traditionally been measured with glass microelectrodes, which limit their in vivo applicability., Approach: Iridium oxide has previously been shown to be sensitive to fluctuations in pH and is biocompatible. Iridium oxide microelectrodes were inserted into the subdiaphragmatic vagus nerve of anaesthetised rats. Introduction of the gut hormone cholecystokinin (CCK) or distension of the stomach was used to elicit vagal nerve activity., Main Results: Iridium oxide microelectrodes have sufficient pH sensitivity to readily detect changes in pH e associated with both CCK and gastric distension. Furthermore, a custom-made Matlab script was able to use these changes in pH e to automatically trigger an implanted VNS device., Significance: This is the first study to show pH e changes in peripheral nerves in vivo. In addition, the demonstration that iridium oxide microelectrodes are sufficiently pH sensitive as to measure changes in pH e associated with physiological stimuli means they have the potential to be integrated into closed-loop neurostimulating devices.

Objective: Neural reflexes regulate immune responses and homeostasis. Advances in bioelectronic medicine indicate that electrical stimulation of the vagus nerve can be used to treat inflammatory disease, yet the understanding of neural signals that regulate inflammation is incomplete. Current interfaces with the vagus nerve do not permit effective chronic stimulation or recording in mouse models, which is vital to studying the molecular and neurophysiological mechanisms that control inflammation homeostasis in health and disease. We developed an implantable, dual purpose, multi-channel, flexible 'microelectrode' array, for recording and stimulation of the mouse vagus nerve., Approach: The array was microfabricated on an 8 µm layer of highly biocompatible parylene configured with 16 sites. The microelectrode was evaluated by studying the recording and stimulation performance. Mice were chronically implanted with devices for up to 12 weeks., Main Results: Using the microelectrode in vivo, high fidelity signals were recorded during physiological challenges (e.g potassium chloride and interleukin-1β), and electrical stimulation of the vagus nerve produced the expected significant reduction of blood levels of tumor necrosis factor (TNF) in endotoxemia. Inflammatory cell infiltration at the microelectrode 12 weeks of implantation was limited according to radial distribution analysis of inflammatory cells., Significance: This novel device provides an important step towards a viable chronic interface for cervical vagus nerve stimulation and recording in mice.

Objective: Hypertension is the largest threat to patient health and a burden to health care systems. Despite various options, 30% of patients do not respond sufficiently to medical treatment. Mechanoreceptors in the aortic arch relay blood pressure (BP) levels through vagal nerve (VN) fibers to the brainstem and trigger the baroreflex, lowering the BP. Selective electrical stimulation of these nerve fibers reduced BP in rats. However, there is no technique described to localize and stimulate these fibers inside the VN without inadvertent stimulation of non-baroreceptive fibers causing side effects like bradycardia and bradypnea., Approach: We present a novel method for selective VN stimulation to reduce BP without the aforementioned side effects. Baroreceptor compound activity of rat VN (n = 5) was localized using a multichannel cuff electrode, true tripolar recording and a coherent averaging algorithm triggered by BP or electrocardiogram., Main Results: Tripolar stimulation over electrodes near the barofibers reduced the BP without triggering significant bradycardia and bradypnea. The BP drop was adjusted to 60% of the initial value by varying the stimulation pulse width and duration, and lasted up to five times longer than the stimulation., Significance: The presented method is robust to impedance changes, independent of the electrode's relative position, does not compromise the nerve and can run on implantable, ultra-low power signal processors.

Objective: Not fully understanding the type of axons activated during vagus nerve stimulation (VNS) is one of several factors that limit the clinical efficacy of VNS therapies. The main goal of this study was to characterize the electrical recruitment of both myelinated and unmyelinated fibers within the cervical vagus nerve., Approach: In anesthetized dogs, recording nerve cuff electrodes were implanted on the vagus nerve following surgical excision of the epineurium. Both the vagal electroneurogram (ENG) and laryngeal muscle activity were recorded in response to stimulation of the right vagus nerve., Main Results: Desheathing the nerve significantly increased the signal-to-noise ratio of the ENG by 1.2 to 9.9 dB, depending on the nerve fiber type. Repeated VNS following nerve transection or neuromuscular block (1) enabled the characterization of A-fibers, two sub-types of B-fibers, and unmyelinated C-fibers, (2) confirmed the absence of stimulation-evoked reflex compound nerve action potentials in both the ipsilateral and contralateral vagus nerves, and (3) provided evidence of stimulus spillover into muscle tissue surrounding the stimulating electrode., Significance: Given the anatomical similarities between the canine and human vagus nerves, the results of this study provide a template for better understanding the nerve fiber recruitment patterns associated with VNS therapies.