Terry Powley

Terry Powley Group

Address:
Terry T. Powley, Ph.D.
Distinguished Professor
School of Health and Human Sciences
703 3rd Street
West Lafayette, IN
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The Powley laboratory team has taken a leadership role in developing and refining the newest neuroscience and neuroanatomical protocols for characterizing the autonomic innervation of the GI tract. Much of their work has focused directly on the circuitry of the stomach.

The team has published a number of papers on adaptations of tracer techniques, immunohistochemistry, and microscopy, and it has used those methods to advance the understanding of the neural circuits which control the upper GI tract and provide brain-gut coordination. One illustration of the Powley laboratory’s contribution is the present understanding of vagal afferent receptors in the gut wall. When the team began its analyses of the extrinsic projections to the gut, only one type of vagal sensory ending in the GI tract wall was defined structurally and characterized morphologically; five have now been described. Of these five, the Powley team is responsible for isolating, characterizing, naming and mapping four of the five receptor types. Another example of the team’s progress, one focused on efferent innervation, is its recent characterization of the vagal motor units that execute the programs of esophageal peristalsis that are generated in the brainstem and projected directly to the muscle sheets of the esophagus.

Research agenda

Two series of experiments will close critical gaps in the current characterization of the autonomic connectome controlling stomach function, thus providing the needed foundation for next generation neuromodulation protocols that can correct shortcomings in past, first-generation open-loop bioelectronic attempts to ameliorate and monitor gastric disorders. Building on recent advances in mapping of vagal circuits, many reported by the research team, the investigators will complete inventories of the efferent and afferent terminal phenotypes, analyze their collateral connections and specializations, establish their regional distributions, and identify chemical taxonomies of their target tissues. To facilitate translational extrapolations, the team 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. The analyses will use a suite of high-definition neural tracing, immunohistochemical and molecular protocols, along with advanced imaging and morphometric techniques, and the research team will concentrate on those elements of gastric neural network that may be most relevant for identifying localized sites in the stomach wall where neuromodulation with state-of-the-art stimulator technologies will have strong therapeutic potential.

Selected publications

  • Wang F.B., Powley T.L. (2000). Topographic inventories of vagal afferents in gastrointestinal muscle. The Journal of Comparative Neurology. 421(3), 302-24. PMID: 10813789.
  • Powley T.L., Spaulding R.A., Haglof S.A. (2011). Vagal afferent innervation of the proximal gastrointestinal tract mucosa: chemoreceptor and mechanoreceptor architecture. The Journal of Comparative Neurology. 519(4), PMID: 21246548.
  • Powley T.L., Mittal R.K., Baronowsky E.A., Hudson C.N., Martin F.N., et al. (2013) Architecture of vagal motor units controlling striated muscle of esophagus: peripheral elements patterning peristalsis? Autonomic Neuroscience: Basic & Clinical. 179(1-2), 90-8. PMID: 24044976.
  • Powley, T.L., Hudson, C.N., McAdams, J.L., Baronowsky, E.A., Martin, F.N., Mason, J.K., & Phillips, R.J. (2014). Organization of vagal afferents in pylorus: mechanoreceptors arrayed for high sensitivity and fine spatial resolution? Autonomic Neuroscience 183, 36-48. PMCID: PMC4058399.
  • Powley, T.L., Hudson, C.N., McAdams, J.L., Baronowsky, E.A., & Phillips, R.J. (2015). Vagal Intramuscular Arrays: The specialized mechanoreceptor arbors that innervate the smooth muscle layers of the stomach examined in the rat. Journal of Comparative Neurology [Epub ahead of print]. PMID: 26355387.