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Scaling of vagus nerve stimulation parameters does not achieve equivalent nerve responses across species

BIOELECTRONIC MEDICINE 2025年第1期11卷 1-17页

作者： Musselman, Eric D. Raha, Ishani Pelot, Nicole A. Grill, Warren M. Duke Univ Dept Biomed Engn Durham NC 27708 USA Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA Duke Univ Dept Neurobiol Durham NC 27708 USA Duke Univ Dept Neurosurg Durham NC 27708 USA

Background Previous efforts to translate vagus nerve stimulation (VNS) therapies from preclinical studies to human clinical applications (e.g., for stroke, heart failure, and inflammatory diseases) did not account for individual- or species-specific differences in nerve responses when selecting stimulation parameters. Lack of explicit consideration for producing equivalent nerve responses could contribute to clinical outcomes not replicating promising results from preclinical animal studies. Methods We used models of VNS built with ASCENT (Musselman, PLoS Comput Biol 17:e1009285, 2021) to quantify nerve responses across species and simulate translation of VNS therapies via either recycling or linear scaling of stimulation parameters. For humans (n = 9) and pigs (n = 12), we used previously validated computational models with the standard clinical helical cuff electrode on individual-specific nerve morphologies (Musselman, J neural Eng 20:acda64, 2023b). We also modeled rat VNS (n = 9) with the Micro-Leads Neuro bipolar cuff. We calculated thresholds for fiber activation (A-, B-, and C-fibers) with biphasic rectangular pulses (0.13, 0.25, 0.5 ms). We defined "K" as the ratio of activation thresholds between a pair of individuals. We used a mixed model ANOVA on the natural logarithm of K to test for differences in inter-species Ks across fiber types and pulse widths. Lastly, using the same nerve morphologies and application-specific device design (cuff and waveform), we developed models to predict nerve responses in chronic human and rat VNS studies for treatment of stroke, inflammation, and heart failure. Results Depending on the individual and species, the activation amplitude required to produce a given nerve response varied widely. Thus, applying the same VNS parameters across individuals within a species produced a large range of nerve responses. Further, applying the same or linearly scaled stimulation amplitudes across species also produced highly variable resp

关键词： Vagus nerve stimulation neural computational modeling Peripheral nerve stimulation Translation

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

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JOURNAL OF neural ENGINEERING 2023年第2期20卷 026032-026032页

作者： Davis, Christopher J. Musselman, Eric D. Grill, Warren M. Pelot, Nicole A. Duke Univ Dept Biomed Engn Durham NC 27708 USA Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA Duke Univ Dept Neurobiol Durham NC 27708 USA Duke Univ Dept Neurosurg Durham NC 27708 USA

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 (V (e)), and activation thresholds across cuff geometries and stimulation waveforms. Using V (e) from 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 peak V (e). Thicker perineurium also inhibited current from leaving the fascicle, causing more constant longitudinal current density, broadening V (e). With increasing endoneurial diameter, intrafascicular volume increased faster than surface area, thereby decreasing intrafascicular current density and peak V (e). Additionally, larger fascicles have greater cross-sectional area, thereby facilitating longitudinal intrafascicular current flow and broadening V (e). 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 pse

关键词： neural computational modeling peripheral nerve stimulation finite element method neuroengineering neural engineering vagus nerve stimulation neural prosthetics

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

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JOURNAL OF neural ENGINEERING 2023年第3期20卷 036032-036032页

作者： Musselman, Eric D. Pelot, Nicole A. Grill, Warren M. Duke Univ Dept Biomed Engn Durham NC 27708 USA Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA Duke Univ Dept Neurobiol Durham NC 27708 USA Duke Univ Dept Neurosurg Durham NC 27708 USA

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 delta/B fibers, A gamma fibers, electromyography, and A alpha 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 mechanis

关键词： vagus nerve stimulation neural computational modeling peripheral nerve stimulation

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Rethinking the role of continuous dopaminergic stimulation in Parkinson disease therapy

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Parkinsonism and Related Disorders 2025年 107354页

作者： LeWitt, Peter A. From the Department of Neurology Wayne State University School of Medicine United States

This Viewpoint will examine continuous dopaminergic stimulation (CDS), a concept that has long been invoked as the optimal treatment strategy for improving symptomatic control of Parkinson disease (PD) patients experiencing motor fluctuations. The appeal of CDS has always seemed intuitive and is based, in part, on preclinical investigations implicating pulsatile dopaminergic stimulation as causing motor fluctuations and dyskinesia from levodopa (LD) treatment. However, four large-scale randomized controlled clinical trials testing infused drug delivery have demonstrated only partial effectiveness of CDS at reducing daily OFF time. Other clinical trial data has offered evidence that a reduction in OFF time also can be accomplished from targeting sites in motor pathways downstream from the basal ganglia. neural plasticity and a CNS calcium receptor signaling compound, ophthalmate, may also hold answers to the regulation of OFF time. Finally, insights derived from neural computational modeling of PD motor pathway pharmacology and the involved electrophysiological connections may guide future understanding of motor fluctuations in PD and their management. © 2025

关键词： Continuous dopaminergic stimulation Hauser diary Motor fluctuations neural computational modeling OFF time Parkinson disease

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modeling the Effects of Bipolar Helical Cuff Electrodes in Vagus Nerve Stimulation

Modeling the Effects of Bipolar Helical Cuff Electrodes in V...

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Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions, and modeling

作者： Ding, Alice K. Luo, Ma Miga, Michael, I Vanderbilt Inst Surg & Engn Nashville TN 37212 USA SyBBURE Searle Undergrad Res Program Nashville TN 37212 USA Vanderbilt Univ Dept Biomed Engn Nashville TN 37235 USA Vanderbilt Univ Dept Radiol & Radiol Sci Med Ctr Nashville TN 37235 USA Vanderbilt Univ Dept Neurol Surg Med Ctr Nashville TN 37235 USA Vanderbilt Univ Dept Otolaryngol Head & Neck Surg Med Ctr Nashville TN 37235 USA

ISBN: (纸本)9781510640269

While mainly used for reducing seizures in epileptic patients, vagus nerve stimulation (VNS) has been implied to be capable of treating various other diseases. However, the therapeutic extent and control of neuromodulation for these conditions are still uncertain and are limited by the ability to predict neural activation responses upon targeting certain fascicles. Generally, VNS is administered through a bipolar helical cuff electrode implanted around the left vagus nerve. The electrode delivers pulses of electricity to the nerve to recruit axons. This work focuses on predicting percent activation and regions of activation based on different adjustable factors such as injected current amplitude and pulse width of stimuli and the activated region of the electrode. To achieve, a simplified finite element model was created using cylindrical geometries as nerve components with an addition of helical cuff electrodes. All of these components were encased in surrounding tissue with assumed properties similar to adipose. Electric potential distribution in the model was processed with an activating function defined along the axonal length which estimates the injected current at the nodes of Ranvier (NoR). These values were then enforced in the neuron simulation as a current clamp approximation applied at the NoR and the likelihood of an action potential was determined. Presence of action potentials were then detected to determine which axons were recruited in VNS. This preliminary work determined that electrode configurations can target specific fascicles in the nerve while amplitudes and pulse widths of stimuli contribute to the percentage of the nerve activated. This demonstrates the ability for patient-specific control over targeting fascicles. Additionally, this work presents initial steps to improving the model by using histological data to create a geometric- specific approach.

关键词： Vagus nerve stimulation finite element modeling bipolar helical cuff neural computational modeling epilepsy

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

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JOURNAL OF neural ENGINEERING 2019年第1期16卷 016007-016007页

作者： Pelot, Nicole A. Behrend, Christina E. Grill, Warren M. Duke Univ Dept Biomed Engn Fitzpatrick CIEMAS Room 1427101 Sci DrCampus Box 90281 Durham NC 27708 USA Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA Duke Univ Dept Neurobiol Durham NC 27708 USA Duke Univ Sch Med Dept Neurosurg Durham NC 27708 USA

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. We also implemented a 2D finite element model of a bundle of axons to estimate the bulk transverse endoneurial resistivity;we compared numerical estimates to an analytical solution. Main results. Since the perineurium is highly resistive, potentials were approximately constant over the cross section of a fascicle, and the perineurium resistivity, longitudinal endoneurial resistivity, and fascicle diameter had important effects on thresholds. Activation thresholds increased up to similar to 130% for higher perineurium resistivity (similar to 400 versus 2200 Omega m) and by similar to 35%-250% for lower longitudinal endoneurial resistivity (3.5 versus 0.75 Omega m), with larger increases for smaller diameter axons and for axons in larger fascicles. Further, thresholds increased by similar to 30%-180% for larger fascicle radii, yielding a larger increase with higher perineurium resistivity. Thresholds were largely insensitive to the transverse endoneurial resistivity, but estimates of the bulk resistivity increased with extracellular resistivity and axonal area fraction;the numerical and analytical estimates were in strong agreement except at high axonal area fractions, where structured axon placements that achieved tighter packing produced electric field inhomogeneities. Significance. We performed a systematic investigation of the effects of values and methods for modeling the perineurium and endoneurium on thresholds

关键词： neural computational modeling peripheral nerve stimulation finite element method neuroengineering neural engineering vagus nerve stimulation

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Neurophysiological Vocal Source modeling for Biomarkers of Disease 17

Neurophysiological Vocal Source Modeling for Biomarkers of D...

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17th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2016)

作者： Ciccarelli, Gregory Quatieri, Thomas F. Ghosh, Satrajit S. MIT Lincoln Lab 244 Wood St Lexington MA 02173 USA MIT 77 Massachusetts Ave Cambridge MA 02139 USA Harvard Med Sch Dept Otolaryngol Boston MA USA

ISBN: (纸本)9781510833135

Speech is potentially a rich source of biomarkers for detecting and monitoring neuropsychological disorders. Current biomarkers typically comprise acoustic descriptors extracted from behavioral measures of source, filter, prosodic and linguistic cues. In contrast, in this paper, we extract vocal features based on a neurocomputational model of speech production, reflecting latent or internal motor control parameters that may be more sensitive to individual variation under neuropsychological disease. These features, which are constrained by neurophysiology, may be resilient to artifacts and provide an articulatory complement to acoustic features. Our features represent a mapping from a low-dimensional acoustics-based feature space to a high-dimensional space that captures the underlying neural process including articulatory commands and auditory and somatosensory feedback errors. In particular, we demonstrate a neurophysiological vocal source model that generates biomarkers of disease by modeling vocal source control. By using the fundamental frequency contour and a biophysical representation of the vocal source, we infer two neuromuscular time series whose coordination provides vocal features that are applied to depression and Parkinson's disease as examples. These vocal source coordination features alone, on a single held vowel, outperform or are comparable to other features sets and reflect a significant compression of the feature space.

关键词： depression Parkinson's neural computational modeling vocal biomarkers

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