Featured Speaker

Despite the ongoing focus on mapping the central nervous system (CNS) connectome, the peripheral nervous system (PNS) architecture in general, and enteric nervous system (ENS) in particular, has been largely disregarded. Besides the studies performed using simple biological models, not much effort has been directed towards describing, quantifying, modeling, and understanding the topology and architecture of the PNS. This presentation will describe the work on mathematical characterization and generative modeling of PNS, focusing on modeling interganglionic networks in the colon and arrangements of axons in the vagus nerve. The study uses data from images of human and mouse tissue samples obtained through optical (confocal) and electron microscopy. The developed models use spatial point pattern analysis and graph generation tools to characterize the spatial and topological properties of the nerve fascicles in the vagus as well as ganglia (clusters of neurons and glial cells) and the inter-ganglionic connections in the colon. Specifically, the introduced approach employed a hybrid hardcore-Strauss process for describing and modeling spatial patterns and a planar random graph generation for constructing the spatially embedded network. The results show that proposed generative models may be helpful in both basic and translational studies and are sufficiently expressive to describe the nerve architectures of animals and humans who vary in age and health status. An increased understanding of the PNS architecture and connectome will lead to the advancement of neuromodulation strategies in treatment. It will also clarify anatomic diagnostic criteria for people with bowel and stomach motility disorders.