By Karin Dahmen (Urbana-Champaign, IL).
The tasks of neural computation are remarkably diverse. To function optimally, neuronal networks have been hypothesized to operate near a nonequilibrium critical point. We use the framework of nonequilibrium phase transitions to describe the statistics and the dynamics of neuron avalanches in the brain. Measured scaling exponents, exponent relations, and scaling functions agree with the predictions of our models. We discuss connections to avalanches in materials, including dynamical effects that can lead to unusually large avalanches, and possible implications for the dynamics of the brain.
Collaborators
Tyler Salners, Karina E. Avila, Benjamin Nicholson, Christopher R. Myers, John Beggs, Nir Friedman, Shinya Ito, Braden A. W. Brinkman, Masanori Shimono, R. E. Lee DeVille, and Thomas C. Butler.