Publications

Vagus nerve stimulation (VNS) is emerging as potential treatment for several chronic diseases. However, limited control of fiber activation, e.g., to promote desired effects over side effects, restricts clinical translation. Towards that goal, we describe a VNS method consisting of intermittent, interferential sinusoidal current stimulation (i2CS) through multi-contact epineural cuffs. In experiments in anesthetized swine, i2CS elicits nerve potentials and organ responses, from lungs and laryngeal muscles, that are distinct from equivalent non-interferential sinusoidal stimulation. Resection and micro-CT imaging of a previously stimulated nerve, to resolve anatomical trajectories of nerve fascicles, demonstrate that i2CS responses are explained by activation of organ-specific fascicles rather than the entire nerve. Physiological responses in swine and activity of single fibers in anatomically realistic, physiologically validated biophysical vagus nerve models indicate that i2CS reduces fiber activation at the interference focus. Experimental and modeling results demonstrate that current steering and beat and repetition frequencies predictably shape the spatiotemporal pattern of fiber activation, allowing tunable and precise control of nerve and organ responses. When compared to equivalent sinusoidal stimulation in the same animals, i2CS produces reduced levels of a side-effect by larger laryngeal fibers, while attaining similar levels of a desired effect by smaller bronchopulmonary fibers.

Bioelectronic therapies modulating the vagus nerve are promising for cardiovascular, inflammatory, and mental disorders, but clinical applications are limited by side-effects such as breathing obstruction and headache caused by non-specific stimulation. To design selective and functional stimulation, researchers engineered VaStim, a realistic and efficient in-silico model. They developed a protocol to personalize VaStim in-vivo using simple muscle responses, successfully reproducing experimental observations by combining models with trials 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. The complete realistic model is available as a free, publicly accessible tool with a web-based platform for optimizing VNS paradigms and electrode designs.

Background: Vagal nerve fibers traveling in distinct fascicles innervate different organs and regulate specific functions. Current vagus nerve stimulation (VNS) therapies activate vagal fibers non-selectively, often resulting in reduced efficacy and side effects. Objective: To characterize the anatomical organization of vagal fibers and demonstrate fascicle-selective VNS. Methods: We used quantified immunohistochemistry, micro-computed tomography imaging, and multi-contact cuff electrodes to map fascicular organization and perform selective stimulation in swine. Results: Myelinated afferents and efferents occupy separate fascicles. Larynx-, heart-, and lung-specific fascicles are spatially separated and progressively merge. Fascicle-selective VNS elicited organ-specific physiological responses with radially asymmetric compound action potentials. Conclusions: Fascicular VNS enables selective modulation of specific organs and functions, offering improved efficacy and reduced off-target effects compared to conventional non-selective VNS.

Quantitative descriptions of the morphology and structure of peripheral nerves is central in the development of bioelectronic devices interfacing nerves. While histological procedures and microscopy techniques yield high-resolution detailed images of individual axons, automated methods to extract relevant information at the single-axon level are not widely available. A segmentation algorithm was implemented that allows for feature extraction in immunohistochemistry (IHC) images of peripheral nerves at the single fiber scale. Features extracted include short and long cross-sectional diameters, area, perimeter, thickness of surrounding myelin and polar coordinates of single axons within a nerve or nerve fascicle. The algorithm was evaluated using manually annotated IHC images of 27 fascicles of the swine cervical vagus; the accuracy of single-axon detection was 82%, and the classification accuracy of fiber myelination was 89%.