Analyzing Cognitive Patterns in Gifted Children Using MRI and Morphometric Similarity Networks

Shuning Han, Feng Duan, Gemma Vilaseca, Núria Vilaró, Cesar F. Caiafa, Zhe Sun, Jordi Solé-Casals

Abstract: Advances in non-invasive neuroimaging, such as structural magnetic resonance imaging (sMRI), have enabled the construction of structural brain networks (SBNs), allowing in vivo mapping of anatomical connections. This study investigates brain network structural differences linked to different intelligence levels in children by individual morphometric similarity networks (MSNs) derived from sMRI data. Through group- and individual-level analyses, we aim to uncover key topological features associated with cognitive performance and to identify a suitable connection density for SBN analysis. Connection density strongly affects global and nodal topological features, with a range of p = 0.05 to 0.15 recommended for stable and optimal results. Gifted individuals exhibit stronger intra-hemispheric and intra-modular connectivity, a more balanced distribution of left-to-right intra-hemispheric connections, and lower mean versatility, supporting efficient and stable cognitive processing. Moreove