Selective Vulnerability of the Brain Regions in Neurodegenerative Disorders

Motivation: Understanding neurodegenerative diseases requires considering selective brain region vulnerability and progressive atrophy. Goal(s): We seek to develop a computational method to identify dynamic, selectively vulnerable brain regions affected by specific diseases. Approach: This study introduces a novel graph theory-based technique focusing on functional interactions in atrophy progression. Results: In Parkinson's disease, our approach demonstrated widespread chronological atrophy across motor and non-motor brain regions, showcasing its effectiveness. Impact: This pioneering study reveals selective vulnerability in functional brain networks, by employing graph theory and computational methods, advancing neurodegenerative disease understanding. These findings hold promise for tracking disease-specific atrophy patterns, enabling longitudinal assessment and the development of effective therapeutic strategies.