Topological network analysis and virtual brain modelling combined to portray subject-specific profiles of dementia stages.

Abstract

Motivation: The high level of heterogeneity typical of mild cognitive impairment (MCI) condition currently hinders the selection of a personalized effective therapy. Goal(s): Our goal is to obtain a personalized profile exploring not only structural and functional topology but also diving in subject-specific physiological parameters. Approach: Starting from structural and functional connectomes, we combined graph theoretical analysis with virtual brain models in the default mode network of healthy subjects, MCI and Alzheimer's disease patients. Results: Our results offer a detailed description of alterations at single-subject level, illustrating differences between dementia stages based on topology and subject-specific physiological parameters. Impact: The personalized profile obtained combining graph theory and virtual brain models portray dementia stages at single-subject level, capturing the wide heterogeneity of mild cognitive impairment and opening new perspectives for personalized effective interventions.