Understanding material transport regulation and traffic jam in neurons for biological neural circuits design

PI: Jessica Zhang

Co-PI(s): Victoria Webster-Wood

University: Carnegie Mellon University

Industry partner: HexSpline3D LLC

Biological neural circuits (BNCs) with patterned neurons have many applications in computational neuroscience, biohybrid robotics, and as a testbed for validating computational and machine learning paradigms. BNC design requires computational tools to fully understand the regulation of material transport in neural circuits. In this proposal, we aim to develop isogeometric analysis techniques to model the regulation of intracellular transport and traffic jams as well as quantify BNC dynamics in micropattern-constrained culture conditions. To achieve this goal, we propose to (1) develop an isogeometric analysis solver to simulate material transport regulation and traffic jams in neurons; and (2) quantify BNC dynamics in micropattern-constrained culture conditions and validate with simulation results. This project will yield new computational tools to enable realistic 3D modeling and simulation of material transport regulation and traffic jams in BNCs. These computational tools will provide important insights into the physiology and disease of neurons. The proposed computational tools and experimental validation are critical, leading to transformative advances in the prevention and treatment of neurodegenerative diseases (e.g. Alzheimer’s disease), as well as biohybrid robotics applications. This industry-academy collaboration between a local startup and CMU will enable technology transfer and contribute to the economic prosperity of PA.