A Network Diffusion Model of Disease Progression in Dementia

By Ashish Raj, Amy Kuceyeski, Michael W. Weiner. Neuron, 2012

711 citations recorded by the source corpus.

SUMMARY 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.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/60ca1a6cb6a0c91391c95a2f7c5d7d63d825981c

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In Cognitive Neuroscience

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Citations in the corpus

The role of the posterior cingulate cortex in cognition and disease. (2014, background): “In the case of Alzheimer’s disease, patterns of atrophy are predicted by the topology of white matter connectivity (Raj et al., 2012), providing an explanation for why the highly connected PCC is affected early in the course of the disease.”
Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer's disease. (2016, background): “Similarly, the bilateral (18)F-AV1451 pattern associated with worse language performance could be associated with transneuronal spread of tau (Clavaguera et al., 2009; de Calignon et al., 2012; Raj et al., 2012; Zhou et al., 2012) from left hemisphere to right, or with a selective vulnerability of l”
Cognitive Network Neuroscience (2015, background): “, 2010), disease progression (Raj et al., 2012; Zhou et al., 2012), and potential receptivity for neurorehabilitation efforts (Bassett et al.”
Structural connectomics in brain diseases (2013, positive): “(Raj et al., 2012) built on the characterization of the structural connectome and formulated mathematical models of diseases progression in brain tissues, proposing the idea that pathologies could spread along network pathways.”
Two’s company, three (or more) is a simplex (2016, background): “Interestingly, this type of filtration is also a natural way in which to probe and reason about models of neurodegenerative disease such as the recently posited diffusion model of fronto-temporal dementia (Raj et al. 2012; Zhou et al. 2012).”
Small-World Brain Networks Revisited (2016, background): “But what have we learnt more speciﬁ-cally about brain small-worldness since 2006, and what do we still have to learn?”
Proteopathic tau seeding predicts tauopathy in vivo (2014, neutral): “Neurobiol Aging 16(3):271–278, discussion 278–284.”
Activity Dependent Degeneration Explains Hub Vulnerability in Alzheimer's Disease (2012, background): “Several recent studies support the notion that node properties such as degree and centrality may play a crucial role in the pathophysiology of degenerative brain disease [60–62].”
Communication dynamics in complex brain networks (2017, methodology): “This principle has been implemented in various random-walk models 52,122,123 , threshold models 22,124–127 , epidemic-spreading models 128–130 and avalanche models 131 .”