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.
Bibliographical noteFunding Information:
This work was supported by the Engineering and Physical Sciences Research Council Grant No. EP/R020205/1 to A. G. and by the National Science Foundation Grant No. CMMI 1727268 to E. K.
© 2020 American Physical Society.
Copyright 2020 Elsevier B.V., All rights reserved.