A network diffusion model of disease progression in dementia

Neuron. 2012 Mar 22;73(6):1204-15. doi: 10.1016/j.neuron.2011.12.040. Epub 2012 Mar 21.


Patterns of dementia are known to fall into dissociated but dispersed brain networks, suggesting that the disease is transmitted along neuronal pathways rather than by proximity. This view is supported by neuropathological evidence for "prion-like" transsynaptic transmission of disease agents like misfolded tau and beta amyloid. We mathematically model this transmission by a diffusive mechanism mediated by the brain's connectivity network obtained from tractography of 14 healthy-brain MRIs. Subsequent graph theoretic analysis provides a fully quantitative, testable, predictive model of dementia. Specifically, we predict spatially distinct "persistent modes," which, we found, recapitulate known patterns of dementia and match recent reports of selectively vulnerable dissociated brain networks. Model predictions also closely match T1-weighted MRI volumetrics of 18 Alzheimer's and 18 frontotemporal dementia subjects. Prevalence rates predicted by the model strongly agree with published data. This work has many important implications, including dimensionality reduction, differential diagnosis, and especially prediction of future atrophy using baseline MRI morphometrics.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Alzheimer Disease / pathology
  • Alzheimer Disease / physiopathology
  • Atrophy
  • Biophysics
  • Brain / pathology*
  • Brain Mapping*
  • Case-Control Studies
  • Dementia / pathology*
  • Dementia / physiopathology*
  • Disease Progression*
  • Female
  • Frontotemporal Dementia / pathology
  • Frontotemporal Dementia / physiopathology
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging
  • Male
  • Middle Aged
  • Models, Neurological*
  • Neural Pathways / pathology
  • Predictive Value of Tests
  • Psychiatric Status Rating Scales
  • ROC Curve
  • Reproducibility of Results
  • Statistics as Topic
  • Young Adult