CAREER: Mathematical Modeling and Computational Tools for in vivo Astrocyte Activity

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This project aims to develop new computational tools to interpret and analyze the activity of astrocytes. Astrocytes, one type of glial cells and the most populous cells in brain, have recently been found to have much more active functionality than previously thought. Astrocytes closely listen to and proactively regulate the nervous system, yet their exact roles in normal and pathological brains remain elusive. Recent technological progress makes it possible to monitor astrocyte activity with unprecedented spatial and temporal resolution, but considering the complexity and scale of astrocyte activity data, rigorous computational modeling is critically needed. This project will establish a solid foundation for quantitative analysis of astrocyte activity, enabling in vivo analysis, greater reproducibility, and benefits for understanding brain disorders. The computationally challenging problems formulated in this project are expected to be valuable for other areas of computer science, serving as examples to build new statistical models and develop powerful generic machine-learning theory and algorithms. The proposed research will develop a comprehensive data-driven framework to model astrocyte activity, with the specific goals of automatically detecting calcium events, identifying functional independent units and characterizing their individual and systems manifestation. Three research objectives include: (1) developing computational approaches to detect calcium events (2) systems modeling and quantification of astrocyte activity, and (3) application to in vivo astrocytes of mouse and other model animals to showcase the usefulness of the proposed methodology by addressing several different current biological questions. The educational objective is to help maintain the competitive vitality of the U.S. computational neuroscience workforce, and to deepen the understanding of core computational concepts, by incorporating cutting-edge computational neuroscience problems into the engineering curriculum, by improving the recruitment and retention of women and minority students, by reaching out to K-12 students to inspire their interest in this interdisciplinary field, and by interacting with undergraduate students to offer opportunities and encourage them to choose computational neuroscience as a career.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.