This study explored how the human cortical folding pattern composed of convex gyri and concave sulci affected single-subject morphological brain networks, which are becoming an important method for studying the human brain connectome. We found that gyri-gyri networks exhibited higher morphological similarity, lower small-world parameters, and lower long-term test-retest reliability than sulci-sulci networks for cortical thickness- and gyrification index-based networks, while opposite patterns were observed for fractal dimension-based networks. Further behavioral association analysis revealed that gyri-gyri networks and connections between gyral and sulcal regions significantly explained inter-individual variance in Cognition and Motor domains for fractal dimension- and sulcal depth-based networks. Finally, the clinical application showed that only sulci-sulci networks exhibited morphological similarity reductions in major depressive disorder for cortical thickness-, fractal dimension-, and gyrification index-based networks. Taken together, these findings provide novel insights into the constraint of the cortical folding pattern to the network organization of the human brain.
Humans ; Cerebral Cortex/anatomy & histology* ; Male ; Female ; Magnetic Resonance Imaging ; Adult ; Connectome/methods* ; Young Adult ; Nerve Net/anatomy & histology* ; Neural Pathways ; Depressive Disorder, Major/diagnostic imaging*

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

The rich club, as a community of highly interconnected nodes, serves as the topological center of the network. However, the similarities and differences in how the rich club supports functional integration and segregation in the brain across different species remain unknown. In this study, we first detected and validated the rich club in the structural networks of mouse, monkey, and human brains using neuronal tracing or diffusion magnetic resonance imaging data. Further, we assessed the role of rich clubs in functional integration, segregation, and balance using quantitative metrics. Our results indicate that the presence of a rich club facilitates whole-brain functional integration in all three species, with the functional networks of higher species exhibiting greater integration. These findings are expected to help to understand the relationship between brain structure and function from the perspective of brain evolution.
Animals ; Humans ; Brain/diagnostic imaging* ; Mice ; Male ; Nerve Net/diagnostic imaging* ; Macaca ; Female ; Neural Pathways/diagnostic imaging* ; Magnetic Resonance Imaging ; Biological Evolution ; Adult ; Diffusion Magnetic Resonance Imaging ; Brain Mapping ; Species Specificity ; Mice, Inbred C57BL

In this study, we systematically tested the hypothesis that during the critical developmental period of adolescence, on a macro scale, the concentrations of major excitatory and inhibitory neurotransmitters (glutamate/glutamine and γ‑aminobutyric acid [GABA]) in the dorsal and ventral lateral prefrontal cortex are associated with the brain's functional connectivity and an individual's psychopathology. Neurotransmitters were measured via magnetic resonance spectroscopy while functional connectivity was measured with resting-state fMRI (n = 121). Seed-based and network-based analyses revealed associations of neurotransmitter concentrations and functional connectivities between regions/networks that are connected to prefrontal cortices via structural connections that are thought to be under dynamic development during adolescence. These regions tend to be boundary areas between functional networks. Furthermore, several connectivities were found to be associated with individual's levels of internalizing psychopathology. These findings provide insights into specific neurochemical mechanisms underlying the brain's macroscale functional organization, its development during adolescence, and its potential associations with symptoms associated with internalizing psychopathology.
Humans ; Adolescent ; Glutamic Acid/metabolism* ; Prefrontal Cortex/diagnostic imaging* ; Male ; Glutamine/metabolism* ; Female ; gamma-Aminobutyric Acid/metabolism* ; Magnetic Resonance Imaging ; Magnetic Resonance Spectroscopy ; Nerve Net/metabolism* ; Neural Pathways ; Connectome

Connectome/methods* ; Magnetic Resonance Imaging/methods* ; Brain/diagnostic imaging* ; Head ; Brain Mapping/methods* ; Nerve Net

The purpose of this study was to explore the differences in interhemispheric functional connectivity in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) based on a triple network model consisting of the default mode network (DMN), salience network (SN), and executive control network (ECN). The technique of voxel-mirrored homotopic connectivity (VMHC) analysis was applied to explore the aberrant connectivity of all patients. The results showed that: (1) the statistically significant connections of interhemispheric brain regions included DMN-related brain regions (i.e. precuneus, calcarine, fusiform, cuneus, lingual gyrus, temporal inferior gyrus, and hippocampus), SN-related brain regions (i.e. frontoinsular cortex), and ECN-related brain regions (i.e. frontal middle gyrus and frontal inferior); (2) the precuneus and frontal middle gyrus in the AD group exhibited lower VMHC values than those in the aMCI and healthy control (HC) groups, but no significant difference was observed between the aMCI and HC groups; and (3) significant correlations were found between peak VMHC results from the precuneus and Mini Mental State Examination (MMSE) and Montreal Cognitive Scale (MOCA) scores and their factor scores in the AD, aMCI, and AD plus aMCI groups, and between the results from the frontal middle gyrus and MOCA factor scores in the aMCI group. These findings indicated that impaired interhemispheric functional connectivity was observed in AD and could be a sensitive neuroimaging biomarker for AD. More specifically, the DMN was inhibited, while the SN and ECN were excited. VMHC results were correlated with MMSE and MOCA scores, highlighting that VMHC could be a sensitive neuroimaging biomarker for AD and the progression from aMCI to AD.
Aged ; Aged, 80 and over ; Alzheimer Disease/physiopathology* ; Brain/diagnostic imaging* ; Brain Mapping ; Cognitive Dysfunction/physiopathology* ; Female ; Humans ; Magnetic Resonance Imaging ; Male ; Memory ; Middle Aged ; Models, Neurological ; Nerve Net