The Problem: Selective and Informed Delivery of Electrical Signals to Your Vagus Nerve
Peripheral nerves course throughout your body, sending signals from the brain and spinal cord to your muscles for that bicep curl and sending signals back from your skin to feel the sun’s warmth. This bidirectional neural signaling also exists for your inner functions, providing subconscious control of your heart, lungs, stomach, liver, and other organs.
Vagus nerve stimulation (VNS) is a type of bioelectronic medicine, where electricity is delivered to our biology, and offers 21st century medicine as an approach to treat a wide variety of diseases, from epilepsy to heart failure, from rheumatoid arthritis to obesity. But how do we know what electrical signals to deliver? The potential choices are almost limitless (Figure 1): the location of stimulation, the shape of the electrical pulses, their amplitude, the rate and pattern of delivery, their ON and OFF times during the day.
Figure 1. The right and left vagus nerves connect to the brainstem and innervate most of the thoracic and abdominal organs. Design of vagus nerve stimulation therapies must consider many parameters. Source of left-hand image: https://biofieldtuningstore.com/products/the-vagus-nerve
The direct responses to these electrical signals are changes in neural activity. Activity might be turned on in the nerve, or if there is ongoing activity, it might be changed or stopped by the electrical signals. These effects can be studied in the lab, but there are limitations. Recordings from the whole nerve indicate the bulk response, like listening to the whole orchestra, while recordings from individual nerve fibers provide detailed information from a very small portion of the population, like listening to only the French horns.
The Solution: Developing Computational Models of Nerve Responses
With the rapid growth of computer power, we can build anatomically accurate models of electrical nerve stimulation. In our SPARC program at Duke University, we are designing, building, and running next generation computational models. We developed the ASCENT (Automated Simulations to Characterize Electrical Nerve Thresholds) pipeline, which builds 3D models of nerves with cuff electrodes and simulates the responses of individual neurons to electrical signals (Figure 2). We also implemented and compared existing models of individual neurons, and we developed new models of the small unmyelinated neurons in peripheral nerves that reproduce experimental responses.
Figure 2. Using an image of the vagus nerve stained with tissue dye (left), we can build a 3D model of the nerve with a cuff electrode that delivers electrical signals (middle) and predicts the required signal amplitudes to activate the nerve fibers (right).
Impact and Collaborations: Computational Tools, Validated Models, Clinical Translation, and Therapeutic Mechanisms
We developed a suite of computational tools for simulating, optimizing, and understanding electrical therapies delivered to peripheral nerves. We mapped the vagus nerve structure in rats, pigs, and humans, collaborating with the UNC Research Histology Core. These tools and data allow us to compare the neural responses across individuals (for example, stimulating your vagus nerve versus my vagus nerve) and across species (how do the results in a laboratory animal translate to treating patients). We can also compare the neural responses across stimulation parameters, such as different shapes of the electrical signals. In addition, we are developing optimization tools to design improved therapies. The SPARC Data and Resource Center will be key for disseminating these computational toolkits.
Through the SPARC Initiative, we work with multiple research groups who study vagus nerve stimulation in lab experiments with different species and different target organs and diseases (Figure 3). These collaborations allow us to validate our models, and allow our collaborators to gain further insights into their experimental data and to define stimulation parameters to use during the limited experimental time. For example, our collaboration with the University of Wisconsin-Madison revealed key pathways for side effects of vagus nerve stimulation used to treat epilepsy; these results can then serve as a guide to reduce or avoid side effects and increase the therapeutic effects.
Figure 3. The SPARC Initiative has a strong culture of collaborative work. We build computational models of vagus nerve stimulation to complement experimental work conducted by our team members and by other research groups.
