Oscillations and avalanches coexist in brain networks close to criticality

We propose a minimal and analytically tractable class of neural networks, the adaptive Ising class. By inferring the model ' s parameters from resting-state brain activity recordings, we show that scale-specific oscillations and scale-free avalanches can coexist in resting brains close to a non-equilibrium critical point at the onset of self-sustained oscillations.