Modeling experimental recordings of vagal afferent signaling of intestinal inflammation for neuromodulation.

OBJECTIVE: Artificial modulation of peripheral nerve signals (neuromodulation) by electrical stimulation is an innovation with potential to develop treatments that replace or supplement drugs. One function of the nervous system that can be exploited by neuromodulation is regulation of disease intensity. Optimal interfacing of devices with the nervous system requires suitable models of peripheral nerve systems so that closed-loop control can be utilized for therapeutic benefit. APPROACH: We use physiological data to model afferent signaling in the vagus nerve that carries information about inflammation in the small intestine to the brain. MAIN
RESULTS: The vagal nerve signaling system is distributed and complex; however, we propose a class of reductive models using a state-space formalism that can be tuned in a patient-specific manner. SIGNIFICANCE: These models provide excellent fits to a large range of nerve recording data but are computationally simple enough for feedback control in implantable neuromodulation devices.