Chiara Matti

Project Summary: Alzheimer’s Disease is the most common cause of dementia, with global cases projected to increase from 50 million in 2010 to 113 million by 2050. It is caused by the accumulation of β-amyloid plaques and tau protein neurofibrillary tangles in the brain, which lead to neuronal death and brain atrophy. The result is a spectrum of cognitive impairments, including deficits in memory, language, visuospatial abilities, and executive functions. However, the network-level mechanisms causing these symptoms and their link to the accumulation of tau and amyloid are still poorly understood.

Neuroimaging studies, particularly those employing resting state functional Magnetic Resonance Imaging (rsfMRI), have explored these questions. While traditional methods analyze network connectivity through pairwise interactions between brain regions, in recent years novel approaches have focused on higher-order dynamical interactions that capture more complex network dynamics.

This project aims to develop a framework to study higher-order connections in Alzheimer’s Disease and Mild Cognitive Impairment patients, as well as in healthy controls. It will integrate three innovative approaches that investigate the spatiotemporal organization of brain networks at multiple levels starting from rsfMRI data. The resulting characterization of network complexity will then be correlated with amyloid and tau accumulation measured through PET imaging, as well as with cognitive performance assessed through neuropsychological tests. This work seeks to gain new insights into patient stratification and the role of network complexity in disease progression.