Hemispheric Differences in Local Morphology of Functional Networks During Visual Word Recognition: Evidence from Multiple AAL Atlases

This study investigates the topological differences between functional networks in the left and right hemispheric regions during visual word processing using task-based fMRI data from 45 subjects in the OpenfMRI project. The analysis employs Automated Anatomical Labeling (AAL) atlases to construct functional networks under two experimental conditions: word processing and consonant string processing. Four key topological metrics are systematically compared between hemispheres: degree centrality, global efficiency, clustering coefficient, and local efficiency. Significant hemispheric differences in local efficiency occurred between 13–19% of the sparsity levels in the AAL versions (p<0.05), while global efficiency ( \(\le \) 1%), the clustering coefficient ( \(\le \) 1%) and the centrality of the degree ( \(\le \) 4%) showed negligible asymmetry. This robust local efficiency divergence highlights its unique role in functional network specialization. The results reveal significant local topological differences between the hemispheres during word processing, with particularly pronounced contrasts in clustering coefficient and local efficiency. These differences persist across multiple versions of the AAL atlas, demonstrating robust hemispheric specialization. The consonant string condition shows markedly different patterns, suggesting language-specific network organization.