Neurobiology & Behavior
Stony Brook University
United States of America
Braden Brinkman earned his B.Sc. in Physics at Simon Fraser University in British Columbia, Canada, and went on to do his Ph.D. studies in non-equilibrium statistical physics at the University of Illinois at Urbana-Champaign. His 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 his postdoctoral work he decided to concentrate on applications of techniques from statistical physics and information theory to understanding coding and computation in networks of neurons. He joined the labs of Eric Shea-Brown in Applied Math and Fred Rieke in Physiology and Biophysics at the University of Washington, where he was a postdoctoral researcher from Sept 2013- Jan 2018. He is excited to be joining the faculty of Neurobiology and Behavior at Stony Brook University, starting January 2018!
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.
“Universal Critical Dynamics in High Resolution Neuronal Avalanche Data”, Nir Friedman, Shinya Ito, Braden A. W. Brinkman, Masanori Shimono, R. E. Lee DeVille, Karin A. Dahmen, John M. Beggs, and Thomas C. Butler, Phys. Rev. Lett. 108, 208102 (2012). (pdf)
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.
“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).