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Little is known about the associations and dependencies of distinct brain lesions
on a regional level, which can be assessed in vivo using various neuroimaging methods.
Gaussian graphical models are a probabilistic framework that estimates the conditional
dependency between individual random variables and represents them by an undirected
graph. We applied this approach to study the inter-regional associations and dependencies
between multimodal imaging markers in prodromal Alzheimer’s disease.
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