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Neurodegenerative diseases

 
 

AGING

Alzheimer’s disease (AD) is marked by cognitive dysfunction emerging from altered brain network activity. Alterations across similar brain networks are also implicated in cognitive impairments that accompany Parkinson’s disease (PD). Identification, development and validation of clinically relevant biomarkers specific to AD and PD is therefore needed. The goal of our research program is to understand neurodegenerative disorders from the perspective of dynamical network function.

While degenerative disease may affect certain brain regions, it is becoming clear that the impact and expression of the disease is best captured by changes in large-scale brain network dynamics. Intensive efforts are underway to build large empirical neuroimaging datasets specific to AD and PD, yet the framework to link these data with the brain function of individual patients is lacking. We provide a computational and theoretical framework for simulating whole-brain networks, TheVirtualBrain (TVB).

We will use structural and functional patient data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Sydney Memory and Ageing Study (Sydney MAS), and the Parkinson’s Progression Markers Initiative (PPMI) to set the initial constraints for estimation of the model parameters. The goal of the proposed research project is to understand the effects of clinical conditions on brain network dynamics at the level of the individual. In particular, we will characterize commonalities and differences in network dynamics across AD and PD and map the underlying biophysical substrates to individual clinical profiles. The first aim of this research project is to directly test the hypothesis that AD and PD can be differentiated by specific spatiotemporal patterns of local and distributed processing. The second aim of this research project is to test the hypothesis that disease-specific alterations in network communication can be detected in prodromal forms of AD and PD and used to prevent disease progression and predict clinical outcome. The third aim of this research project is to identify the underlying common and disease-specific biophysical substrates that lead to alterations in large-scale network dynamics. Importantly, we will identify the biophysical substrates that best predict an individual’s disease trajectory and clinical outcome. TVB can therefore be used to evaluate the clinical potential of therapeutic interventions early in development to help converge on targets that are most likely to have the best outcome.

funded by 

Weston Brain Institute

Brightfocus Foundation