The inferior parietal lobule (IPL) is one of the most expanded cortical regions in humans relative to other primates. It is also among the most structurally and functionally asymmetric regions in the human cerebral cortex. Whether the structural and connectional asymmetries of IPL subdivisions differ across primate species and how this relates to functional asymmetries remain unclear. We identified IPL subregions that exhibited positive allometric in both hemispheres, scaling across rhesus macaque monkeys, chimpanzees, and humans. The patterns of IPL subregions asymmetry were similar in chimpanzees and humans, but no IPL asymmetries were evident in macaques. Among the comparative sample of primates, humans showed the most widespread asymmetric connections in the frontal, parietal, and temporal cortices, constituting leftward asymmetric networks that may provide an anatomical basis for language and tool use. Unique human asymmetric connectivity between the IPL and primary motor cortex might be related to handedness. These findings suggest that structural and connectional asymmetries may underlie hemispheric specialization of the human brain.

During the preadolescent period, when the cerebral thickness, curvature, and myelin are constantly changing, the brain's regionalization patterns underwent persistent development, contributing to the continuous improvements of various higher cognitive functions. Using a brain atlas to study the development of these functions has attracted much attention. However, the brains of children do not always have the same topological patterns as those of adults. Therefore, age-specific brain mapping is particularly important, serving as a basic and indispensable tool to study the normal development of children. In this study, we took advantage of longitudinal data to create the brain atlas specifically for preadolescent children. The resulting human Child Brainnetome Atlas, with 188 cortical and 36 subcortical subregions, provides a precise period-specific and cross-validated version of the brain atlas that is more appropriate for adoption in the preadolescent period. In addition, we compared and illustrated for regions with different topological patterns in the child and adult atlases, providing a topologically consistent reference for subsequent research studying child and adolescent development.

Brain atlas is an important tool in the diagnosis and treatment of neurological disorders. However, due to large variations in the organizational principles of individual brains, many challenges remain in clinical applications. Brain atlas individualization network (BAI-Net) is an algorithm that subdivides individual cerebral cortex into segregated areas using brain morphology and connectomes. The presented method integrates group priors derived from a population atlas, adjusts areal probabilities using the context of connectivity fingerprints derived from the fiber-tract embedding of tractography, and provides reliable and explainable individualized brain areas across multiple sessions and scanners. We demonstrate that BAI-Net outperforms the conventional iterative clustering approach by capturing significantly heritable topographic variations in individualized cartographies. The topographic variability of BAI-Net cartographies has shown strong associations with individual variability in brain morphology, connectivity as well as higher relationship on individual cognitive behaviors and genetics. This study provides an explainable framework for individualized brain cartography that may be useful in the precise localization of neuromodulation and treatments on individual brains.

Individual brains vary greatly in morphology, connectivity and organization. Individualized brain parcellation is capable of precisely localizing subject-specific functional regions. However, most individualization approaches examined single modality of data and have not generalized to nonhuman primates. The present study proposed a novel multimodal connectivity-based individual parcellation (MCIP) method, which optimizes within-region homogeneity, spatial continuity and similarity to a reference atlas with the fusion of personal functional and anatomical connectivity. Comprehensive evaluation demonstrated that MCIP outperformed state-of-the-art multimodal individualization methods in terms of functional and anatomical homogeneity, predictability of cognitive measures, heritability, reproducibility and generalizability across species. Comparative investigation showed a higher topographic variability in humans than that in macaques. Therefore, MCIP provides improved accurate and reliable mapping of brain functional regions over existing methods at an individual level across species, and could facilitate comparative and translational neuroscience research.

WMH, a neuroimaging marker of cerebral small vessel disease, is closely associated with cognitive decline and structural brain changes. However, the precise mechanisms through which WMH-associated GMV changes ultimately translate to cognitive decline remain unclear, particularly regarding propagation patterns and causal interactions within affected neural circuits. To investigate the progressive structural changes in WMH patients based on disease severity, we recruited 185 patients with cerebral small vessel disease and 40 healthy controls, who underwent magnetic resonance imaging scans. First, voxel-based morphometry analysis was performed to compare GMV differences between WMH patients and healthy controls, followed by subgroup analyses across different disease stages to identify key regions with significant morphological changes. Subsequently, causal structural covariance network analysis, modularity analysis and functional decoding were employed to map the causal relationships of GMV changes, the hierarchical topography and functional characteristics of the structural network throughout the WMH progression. Finally, mediation analysis was conducted to explore the relationships between WMH volume, GMV, and cognition, providing insights into the underlying causal pathways. The results revealed that GMV reductions originated in the right insula and progressively extended to cortical and subcortical regions with increasing disease severity. Causal structural covariance network analysis identified the right insula as a central hub, exerting causal effects on GMV reductions in regions associated with executive function and attention. Modularity analysis and functional decoding further highlighted key pathways linking the right insula to cortico-subcortical networks involved in cognitive regulation and motor coordination. Additionally, compensatory GMV increases were observed in specific regions, suggesting neuroplastic responses to WMH-related damage. Mediation analysis demonstrated that GMV reductions significantly mediated the relationship between WMH volume and cognitive impairments, particularly in executive function and processing speed. Overall, the right insula acts as a critical hub driving hierarchical GMV atrophy and network disruption in WMH. Its early involvement and causal influence highlight its importance as a potential target for interventions to mitigate cognitive decline.