This publication presents graph-theoretical approaches for studying brain network plasticity across development, learning, injury, and rehabilitation. It explains how measures such as modularity, centrality, efficiency, and hub disruption can reveal large-scale changes in neural organization. The work emphasizes the importance of longitudinal data, multimodal validation, and cautious interpretation when translating network metrics into biological mechanisms.
Notable Contribution to Network Neuroscience
Recognized for applying graph-based methods to explain plasticity, adaptation, and large-scale organization in brain networks.
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