Brain functional and structural reorganization in chronic stroke: a network approach

Ph.D. ; Human brain can be viewed as a complex system which evolves dynamics based on the anatomical fiber connections. After stroke, although the damage on the structural connection in brain is relatively focal, the effect is brainwide and can spread to remote areas. Through the neuroplastic processes, the lesioned brain can reorganize its structure, function, and connections to adapt to such damage. Understanding how brain structure and function reorganize after stroke is crucial in managing stroke recovery. The natural characteristics of brain mechanisms, with statistical dependence or anatomical connections as edges and brain regions as nodes, enable us to investigate the neural processing through a network view. This study explored the structural and functional reorganization in chronic stroke via this graphical approach, which provides us a solid framework to understand the lesioned brain topology. ; First, this work investigated the relationship between the structural and functional reorganization in chronic stroke. Resting-state functional magnetic resonance imaging (rs-fMRI) was collected to characterize the functional synchronization lag between homotopic regions in chronic stroke as well as a group of healthy comparison individuals. Diffusion MRI data was used to map the structural brain network (connectome), with pairwise connection representing the white matter fascicles among brain areas. We explored the network communication efficiency under two schemes, shortest paths and navigation, to explain the functional lag profile found in stroke individuals. We found that interindividual variation in synchronization lags was inversely associated with communication efficiency under both schemes. While interregional variation in lag was only related to navigation efficiency and navigation distance. This study for the first time indicates the structural basis for the altered neural information transformation after stroke. ; Based on the promising potential of network neuroscience, we extended the theory to ...