Brain networks topology and dynamics capture neuropsychological heterogeneity in mild cognitive impairment

Motivation: A deeper understanding of the cellular mechanisms shaping brain network dynamics is crucial in heterogeneous clinical conditions such as mild cognitive impairment (MCI). Goal(s): We want to show that virtual brain modelling (TVB) can extract information hidden in brain network function and organization and, integrated with graph theory, contribute to the explanation of neuropsychological variance. Approach: Starting from structural and functional connectomes, TVB and graph theory were combined to investigate brain networks in healthy subjects and MCI at different disease stages. Results: Graph theory measures together with TVB parameters explained ~70% of neuropsychological scores variance, validating the clinical utility of this new approach. Impact: With its high correlation with neuropsychological scores, the subject-specific portrait of mild cognitive impairment patients, obtained combining virtual brain modelling and graph theory analysis, can contribute to the development of individualized early intervention.