Organ- and Function-Specific Anatomical Organization and Bioelectronic Modulation of the Vagus Nerve

Jayaprakash, Naveen; Tóth, Viktor; Song, Weiguo; Vardhan, Avantika; Levy, Todd; Tomaio, Jacquelyn N.; Qanud, Khaled; Mughrabi, Ibrahim; Saperstein, Yiela; Chang, Yao-Chuan; Rob, Moontahinaz; Daytz, Anna; Abbas, Adam; Ashville, Jason; Vikatos, Anna; Ahmed, Umair; Vegesna, Anil K.; Nassrallah, Zeinab; Volpe, Bruce T.; Tracey, Kevin J.; Al‐Abed, Yousef; Datta-Chaudhuri, Timir; Miller, Larry S.; Barbe, Mary F.; Lee, Sunhee C.; Zanos, Theodoros P.; Zanos, Stavros

doi:10.2139/ssrn.4097124

Cited by 10 publications

(16 citation statements)

References 51 publications

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“…2) and the fact that fibres associated with side effects tend to respond to stimulation more readily than those associated with desirable therapeutic effects (Fitchett, Mastitskaya, and Aristovich, 2021). While fascicles are organized at least partially by the organs they innervate and the functions they mediate (Jayaprakash et al, 2022), the vagus nerve exhibits extensive branching and merging. Additionally, nerve morphology is unique for each patient and VNS parameter settings need to be adjusted accordingly.…”

Section: Introduction 1therapeutic Potential and Biological Problemmentioning

confidence: 99%

Using neural biomarkers to personalize dosing of vagus nerve stimulation

Berthon,

Wernisch,

Stoukidi

et al. 2023

Preprint

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Background: Vagus nerve stimulation (VNS) is an established therapy for treating a variety of chronic diseases, such as epilepsy, depression, obesity, and for stroke rehabilitation. However, lack of precision and side-effects have hindered its efficacy and extension to new conditions. Objective: To achieve a better understanding of the relationship between VNS parameters and neural and physiological responses to enable the design of personalized dosing procedures to improve precision and efficacy of VNS therapies. Methods: We used biomarkers from recorded evoked neural activity and short-term physiological responses (throat muscle, cardiac and respiratory activity) to understand the response to a wide range of VNS parameters in anaesthetised pigs. Using signal processing, Gaussian processes (GP) and parametric regression models we analyse the relationship between VNS parameters and neural and physiological responses. Results: Firstly, we observe inter-subject variability for both neural and physiological responses. Secondly, we illustrate how considering multiple stimulation parameters in VNS dosing can improve the efficacy and precision of VNS therapies. Thirdly, we describe the relationship between different VNS parameters and the evoked neural activity and show how spatially selective electrodes can be used to improve fibre recruitment. Fourthly, we provide a detailed exploration of the relationship between the activations of neural fibre types and different physiological effects, and show that recordings of evoked neural activity are powerful biomarkers for predicting the short-term physiological effects of VNS. Finally, based on these results, we discuss how recordings of evoked neural activity can help design VNS dosing procedures that optimize short-term physiological effects safely and efficiently. Conclusion: Understanding of evoked neural activity during VNS provide powerful biomarkers that could improve the precision, safety and efficacy of VNS therapies.

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Section: Introduction 1therapeutic Potential and Biological Problemmentioning

confidence: 99%

Using neural biomarkers to personalize dosing of vagus nerve stimulation

Berthon,

Wernisch,

Stoukidi

et al. 2023

Preprint

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“…We would be able to test our localization methods by observing a substantial spatial overlap between the inferred spatial maps for a given physiological function during baseline activity and the corresponding altered state for the given function. In a similar manner, recent stimulation protocols to test organ- and function-specific organization of the pig VN 11 could also be applied to test the efficiency of our localization method by comparing spontaneous localization maps and electrically induced functional maps for a given physiological function. Finally, structural information could also be employed by following a procedure developed previously 22 to visualize the fascicular organization of the pig VN in vivo and build animal-specific structural-functional maps.…”

Section: Discussionmentioning

confidence: 99%

“…For each nerve section, we populated half of the fascicles with Aβ fibers and the remaining fascicles with Aα fibers ( Figure S2 ), this approximately respects the proportion between afferent and efferent fascicles observed in functional vagotopy. 8 , 11 To respect the proportion of fibers from the two populations observed physiologically, but limiting computational effort, we imposed the average number of fibers per fascicle equal to a quarter of the true value (766 fibers/fascicle afferently and 335 fibers/fascicle efferently 11 ), resulting in a fiber density equal to 1,367 fibers/mm 2 in the afferent fascicles and 598 fibers/mm 2 in the efferent ones. Fiber models were implemented in NEURON using Python.…”

Section: Methodsmentioning

confidence: 99%

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A method to establish functional vagus nerve topography from electro-neurographic spontaneous activity

et al. 2022

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“…While the potential of VNS is widely recognized, important challenges remain in developing effective stimulation protocols. Notably, there is substantial patient-to-patient variation in the distribution and arrangement of fibres in the VN (Upadhye et al, 2021; Jayaprakash et al, 2022), as well as in the coupling of these fibre groups and stimulation electrodes (Qiao, Stieglitz, and Yoshida, 2016). This necessitates a personalized optimization process.…”

Section: Introductionmentioning

confidence: 99%

Online Bayesian Optimization of Nerve Stimulation

Wernisch,

Edwards,

Berthon

et al. 2023

Preprint

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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 wave forms, require a complex and multi-dimensional parameter space in order to control such wave forms. Determining the best combination of parameters (wave form 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 sub-optimal 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. Such optimization builds a model of the neural and physiological responses to stimulations enabling it to optimize stimulation parameters and to provide estimates of the accuracy of the response model. The vagus nerve innervates, among other thoracic and visceral organs, the heart, thus con- trolling hear rate and is therefore ideal 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 vagus nerve stimulation intraoperatively in porcine subjects. Optimization converged quickly on parameters achieving target heart rates and optimizing neural B-fibre 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.

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Organ- and Function-Specific Anatomical Organization and Bioelectronic Modulation of the Vagus Nerve

Cited by 10 publications

References 51 publications

Using neural biomarkers to personalize dosing of vagus nerve stimulation

Using neural biomarkers to personalize dosing of vagus nerve stimulation

A method to establish functional vagus nerve topography from electro-neurographic spontaneous activity

Online Bayesian Optimization of Nerve Stimulation

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