Daniel B. Forger III, Ph.D.
Professor of Mathematics
Research Professor of Computational Medicine and Bioinformatics
Michigan Institute for Data Science Core Faculty
University of Michigan
Visiting Scholar, NSF-Simons Center for Mathematical and Statistical Analysis of Biology
Whole-Brain Simulation on Desktop Computers
While tremendous knowledge has been gathered on parts of the brain, progress on understanding many of the major brain challenges (affective disorders, autism spectrum disorders, ...) has been slow. This may be due to the lack of mathematical and computational methods to understand the brain at scale. I will highlight three methods we are developing to address this. Studying one region of the brain responsible for daily timekeeping, I will discuss a new ansatz for coupled oscillators which is similar to the popular ansatz by Ott and Antonsen, but which gives better fits to biological data. Inspired by a course I took with Michael Shelley on population density methods in neuroscience, I will describe a new level-set Kalman Filter that can be used with particle methods to simulation regions of the brain. Finally, I will discuss how we are simulating the electrical (Hodgkin-Huxley type ionic) activity and paracrine signaling of millions of neurons, visualized by collaborators in wild-type and mutant mics, with GPUs. If time allows, I will show how these methods can link to ongoing work on genomics and wearables.