About Us

This website is under development. The content may change or disappear without warning.

Our project

Two series of complementary experiments, conducted by our exceptionally qualified team of 11 investigators from eight state-of-the-art laboratories at four institutions, will close critical gaps in the current characterization of the autonomic connectome controlling stomach function. These proposed synergistic anatomical and functional investigations will form the needed foundation for neuromodulation protocols that can correct shortcomings in past, first-generation bioelectronic attempts to ameliorate and monitor gastric disorders.

Building on recent advances in mapping of vagal circuits, many reported by our research team, Aim 1 will finish inventories of the efferent and afferent terminal phenotypes, analyze their collateral specializations, establish their regional distributions, and identify chemical taxonomies of their target tissues. We will also compare the neural circuitry of the human (and pig, an ideal large animal preclinical proof-of-principle model) stomach with that of the rat model to facilitate future translational extrapolations. The analyses of Aim 1 will use a suite of high-definition neural tracing, immunohistochemical and molecular protocols, along with advanced imaging and morphometric techniques, that our team has adapted to autonomic circuits.

The Aim 1 will focus on those elements in gastric neural network that may be most relevant to informing the Aim 2 and identify additional localized sites in the stomach wall where focal stimulation will have strong therapeutic potential. In functional assessments, the Aim 2 will identify optimal locations for both highly selective vagal stimulation (VNS) and precise surgical placement between the exit of the vagus from the brainstem and the target sites of the axons within the stomach wall and will determine the best stimulation protocols for augmenting gastric physiology.

The Aim 2 will use state-of-the-art closed-loop stimulator technologies, algorithms, and electrodes (previously designed and robustly proven by investigators on our research team) and assess the reliability, validity, and stability of the VNS by employing a battery (≥ 6) of acute, short-term, and long-term non-invasive endpoints. The team will use data archiving and resource sharing platforms that are universally accessible to all research and medical communities.