Experiments to map physiological functions of autonomic nerves and the continued advance of bioelectronic therapies are limited by inadequate activation or block of targeted nerve fibers and unwanted co-activation or block of non-targeted nerve fibers. More fundamentally, the relationship between applied stimuli and the nerve fibers that are activated or blocked, how this relationship varies across individuals and species, and how these relationships can be controlled remain largely unknown. We will develop, implement and validate an efficient computational pipeline for simulation of electrical activation and block of different nerve fiber types within autonomic nerves. The pipeline will include segmentation of microanatomy from fixed nerve samples, three- dimensional finite-element models of electrodes positioned on nerves, and non-linear cable models of different nerve fiber types, enabling calculation of quantitative input-output maps of activation and block of specific nerve fibers. As key benchmarks of pipeline development and for the proposed analysis and design efforts, we will implement models of the cervical (VNc) and abdominal (VNa) vagus nerves in rat, in a SPARC-identified animal model, and in human. The VNc is an excellent test bed as it contains a broad spectrum of nerve fiber types, there are experimental data to facilitate model validation, and there are multiple applications of VNc stimulation where a lack of fiber selectivity limits the therapeutic window. The VNa is an excellent complement to the cervical VNc, as a prototypical autonomic nerve of a size comparable to many of the small autonomic nerves targeted by SPARC projects. We will use the models that emerge from the pipeline to achieve analysis and design goals to address critical gaps identified as SPARC priorities. Specifically, we will quantify of the effects of intra-species differences in nerve morphology on activation and block by building individual sample-specific models for each nerve and specie. These models will also be used to quantify inter-species differences in nerve fiber activation and block and to identify electrode designs and stimulation parameters that produce equivalent degrees of activation and block across species. We will combine the resulting models with engineering optimization to design approaches to increase the selectivity and efficiency of activation and block of different nerve fiber types. The outcomes will be a pipeline for modeling autonomic nerves, electrode geometries, and stimulation parameters, as well as tools that address the limitations of nerve stimulation selectivity and efficiency that hinder the continued advance of physiological mapping studies and the development of bioelectronic therapies.

Implanted pacemaker-like devices to stimulate or block autonomic nerves–bioelectronic medicines–offer promise to treat diverse diseases from heart failure to diabetes, but this approach is hindered by limited control over the specific nerve fibers that are activated or blocked. We will develop a computer-based system to quantify the activation and block of specific nerve fiber types, and use this system to engineer novel methods for more selective control thereby enabling the continued advance of bioelectronic medicines.