Complex patterns arise through spontaneous symmetry breaking in dense homogeneous networks of neural oscillators

There has been much interest in understanding collective dynamics in networks of brain regions due to their role in behavior and cognitive function. Here we show that a simple, homogeneous system of densely connected oscillators, representing the aggregate activity of local brain regions, can exhibit a rich variety of dynamical patterns emerging via spontaneous breaking of permutation or translational symmetries. Upon removing just a few connections, we observe a striking departure from the mean-field limit in terms of the collective dynamics, which implies that the sparsity of these networks may have very important consequences. Our results suggest that the origins of some of the complicated activity patterns seen in the brain may be understood even with simple connection topologies.

Thermo-optic Degradation of Single-Modedness in Active LMA fibers and Simple Compensation Mechanisms

We demonstrate significant thermo-optic degradation of single-modedness in active large mode area fibers due to heat generation in the fiber. We propose and demonstrate through simulations, simple compensation mechanisms using custom length dependent fiber coiling.