Multimodal statistical analysis of brain connectome with application to alzheimer's disease

Clinical cognitive decline, often culminating in Alzheimer's Disease Dementia (ADD), has traditionally been viewed as a disconnection syndrome affecting the brain's structural and functional organization. Despite extensive research focusing on changes in brain connectome models, particularly in the functional domain, a coherent understanding of underlying mechanisms and robust biomarkers remains elusive. Evidence suggests that the brain undergoes spatially non-stationary and non-monotonous structural and functional changes across the clinical decline continuum. In this thesis, these changes across different stages of clinical cognitive decline were examined in the context of local structural and functional reorganization in the brain. For this purpose, nodal assortativity was used as a quantitative metric. The findings reveal statistically significant local reorganization patterns in both structural and functional domains, which transition with the progression of cognitive decline and differ in nature between structure and function. Specifically, hypo-assortativity tends to prevail in the initial phases for both structural and functional aspects, transitioning to hyper-assortativity in later stages. Notably, functional reorganization is more pronounced in the early stages, while structural reorganization becomes prominent later. Despite some common regions that undergo both structural and functional reorganization, a significant variation was observed in regions affected from functional and structural perspectives. It is underscored that analyzing both spatial and temporal dimensions is crucial for a comprehensive understanding of clinical cognitive decline leading to ADD. The preliminary findings suggest a complex and variable reorganization process, potentially indicative of simultaneous active degenerative and compensatory mechanisms.