Cross-Species and Clinical Insights into Brain Network Architecture: A Structural and Functional Connectivity Study

Abstract

Understanding how brain networks are organized is essential for explaining species differences in cognition and for identifying early indicators of neurological disease. This thesis applies graph-theoretic approaches to study large-scale brain networks, focusing on the organization of structural connectivity in healthy primate brains (study 1) and functional network alterations following neurological insult (study 2). In study 1, we investigate the mesoscale organization of the structural connectome in humans, macaques, and marmosets using modularity-based community detection and graph centrality measures. Analysis of diffusion MRI–derived human connectomes from the Human Connectome Project revealed a robust and reproducible modular architecture, with eight dominant communities consistently identified across individuals and test–retest sessions. Eigenvector centrality highlighted a strongly integrative community localized to occipital cortex, encompassing primary and higher-order visual regions. To assess the dependence of these findings on edge-weight interpretation, we repeated community detection and centrality analyses using reciprocal edge weights, such that strong connections correspond to short paths. Under this transformation, modular structure was substantially weakened and spatial coherence reduced, indicating that the canonical modules observed in the human connectome are driven by concentrated anatomical connectivity rather than shortest-path topology. Additional comparisons of eigenvector, betweenness, and closeness centrality demonstrated that these metrics capture complementary but distinct aspects of network organization. Cross-species analyses showed that while modular organization is broadly conserved across primates, the dominance of an occipital hub community is specific to humans, suggesting species-dependent specialization in integrative network architecture. In study 2, we examine functional connectome organization using resting-state and movie-driven fMRI data from individuals following a first unprovoked seizure. Network analysis revealed altered centrality patterns in limbic, prefrontal, and insular regions relative to matched controls, even after a single seizure event. These results point to early and distributed changes in functional network organization that may relate to seizure vulnerability. Together, this thesis demonstrates that graph-theoretic measures provide a sensitive framework for characterizing both stable features of brain network architecture and early functional alterations associated with neurological disease. The findings highlight shared organizational principles across species, as well as uniquely human specializations in structural network integration.Esther Yartey, 202