Cognitive impairment and dementia are recognized as major threats to public health. Many studies have shown the important role played by challenges to the cerebral vasculature and the neurovascular unit. To investigate the structural and functional characteristics of the brain, MRI has proven an invaluable tool for visualizing the internal organs of patients and analyzing the parameters related to neuronal activation and blood flow in vivo. Different strategies of imaging can be combined to obtain various parameters: (i) measures of cortical and subcortical structures (cortical thickness, subcortical structures volume); (ii) evaluation of microstructural characteristics of the white matter (fractional anisotropy, mean diffusivity); (iii) neuronal activation and synchronicity to identify functional networks across different regions (functional connectivity between specific regions, graph measures of specific nodes); and (iv) structure of the cerebral vasculature and its efficacy in irrorating the brain (main vessel diameter, cerebral perfusion). The high amount of data obtainable from multi-modal sources calls for methods of advanced analysis, like machine-learning algorithms that allow the discrimination of the most informative features, to comprehensively characterize the cerebrovascular network into specific and sensitive biomarkers. By using the same techniques of human imaging in pre-clinical research, we can also investigate the mechanisms underlying the pathophysiological alterations identified in patients by imaging, with the chance of looking for molecular mechanisms to recover the pathology or hamper its progression.