title: Stochastic synchronization of neural activity waves.
abstract: We demonstrate that waves in distinct layers of a neuronal network can become phase locked by common spatiotemporal noise. This phenomenon is studied for stationary bumps, traveling waves, and breathers. A weak noise expansion is used to derive an effective equation for the position of the wave in each layer, yielding a stochastic differential equation with multiplicative noise. Stability of the synchronous state is characterized by a Lyapunov exponent, which we can compute analytically from the reduced system. Our results extend previous work on limit-cycle oscillators, showing common noise can synchronize waves in a broad class of models.
authors.affiliation: Department of Mathematics, University of Houston, Houston, Texas 77204, USA.
authors.forename: Zachary P
authors.initials: ZP
authors.lastname: Kilpatrick
mesh_terms: D016571:Neural Networks, Computer; D013269:Stochastic Processes