Ph.D. Physics, University of Illinois at Urbana-Champaign
Life Sciences Building
Office: Room 548
I earned my B.Sc. in Physics at Simon Fraser University in British Columbia, Canada, and went on to do my Ph.D. studies in non-equilibrium statistical physics at the University of Illinois at Urbana-Champaign. My graduate research focused on systems displaying avalanche-like behavior, including magnetic-domain flipping in magnets with impurities, earthquake faults, and of course neuronal networks. For my postdoctoral work I decided to concentrate on applications of techniques from statistical physics and information theory to understanding coding and computation in networks of neurons. I joined the labs of Eric Shea-Brown in Applied Math and Fred Rieke in Physiology and Biophysics at the University of Washington, where I was a postdoctoral researcher from Sept 2013- Jan 2018.
We have entered a new era in neuroscience. Experiments can now monitor neural activity on increasingly large spatial and temporal scales, presenting unprecedented opportunities to close major gaps in our understanding of how large populations of neurons coordinate to perform computations underlying behavior. However, this flood of data has dramatically outpaced our theoretical understanding. New tools are necessary to refine experiments, properly interpret data, and solidify our understanding of neural coding and computation. My research program seeks to develop such tools and models, and thereby determine universal principles underlying how collective neural activity represents, transmits, and combines information across a larger range of spatial and temporal scales than any individual neuron can access. I am especially interested in elucidating how network structure and dynamics determine a circuit’s computational capabilities, and how pathologies in structure or dynamics may manifest as diseases like epilepsy—and how we might be able to use our theoretical frameworks to design principled interventions to treat diseased networks.
- “Effective synaptic interactions in subsampled nonlinear networks with strong coupling”, Braden A. W. Brinkman, Fred Rieke, Eric Shea-Brown, and Michael Buice, submitted (2017). (preprint on biorXiv). (cross-posted preprint on arXiv).
- “How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?”, Braden A. W. Brinkman*, Alison I. Weber*, Fred Rieke**, and Eric Shea-Brown**, PLOS Computational Biology, 12(10): e1005150 (2016) (open access). *,** = equal contributions.