  Neurodegenerative diseases, such as Alzheimer's or Parkinson's disease, show
characteristic degradation of structural brain networks. This degradation
eventually leads to changes in the network dynamics and degradation of
cognitive functions. Here, we model the progression in terms of coupled
physical processes: The accumulation of toxic proteins, given by a nonlinear
reaction-diffusion transport process, yields an evolving brain connectome
characterized by weighted edges on which a neuronal-mass model evolves. The
progression of the brain functions can be tested by simulating the
resting-state activity on the evolving brain network. We show that while the
evolution of edge weights plays a minor role in the overall progression of the
disease, dynamic biomarkers predict a transition over a period of 10 years
associated with strong cognitive decline.
