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Abstract
This dissertation employs magnetic resonance imaging (MRI) to investigate functional and structural connectivity of in vivo brains. The study involves a range of MRI techniques—functional MRI (fMRI) for brains’ temporal dynamics analysis, diffusion tensor imaging (DTI) for structural connectivity mapping, and a machine learning approach for functional/structural data integration and connectome matrix fusion. All MRI data was acquired from brains of a porcine model, which has demonstrated its utility as a surrogate model for studying human brains. Chapter 2 focuses on using fMRI to study brain recovery mechanisms post-traumatic brain injury (TBI). A temporal analysis compares TBI subjects with a sham group where only craniotomy surgery was operated to assess brain function recovery. This analysis yields a deeper understanding of brain activity over time enhanced by sparse dictionary learning and independent component analysis. Combined with application of cerebral blood flow mapping, this method introduces a novel approach for evaluating the efficacy of treatments like fecal microbial transplants in TBI recovery, evidenced by increased correlation within the executive control and salience networks.
In Chapter 3, the investigation shifts to DTI to develop a new white matter atlas tract model for piglets. This approach shifts from conventional surface-based methodologies to a voxel-based structural connectivity analysis, providing a detailed view of the brain's organizational complexity. The structural connectome blueprints generated facilitate a deeper comprehension of neurodevelopmental processes and the impact of therapeutic interventions on brain structure.
Chapter 4 synthesizes learnings from the preceding chapters and introduced the Connectome Matrix Fusion methodology. This approach integrates structural and functional connectivity data and provides a comprehensive view of the brain's connectome. The method markedly enhances the differentiation of effect on brains following nutritional interventions, underscoring its significance for neuroscience research.
Chapter 5 summarizes contributions of this dissertation and presents future research directions. The dissertation underscores the pig model's contribution to neurological research by integrating advanced MRI methodologies, laying the groundwork for future studies on brain connectivity and recovery mechanisms. This comprehensive analysis elucidates the brain's structural and functional complexities, advancing our understanding of brain health and disease and setting a new course for neurological research advancements.