Cortical structural and functional coupling during development and implications for attention deficit hyperactivity disorder

Group-common and individual-specific effects of structure-function coupling in human brain networks with graph neural networks

The human cerebral cortex is organized into functionally segregated but synchronized regions bridged by the structural connectivity of white matter pathways. While structure-function coupling has been implicated in cognitive development and neuropsychiatric disorders, studies yield inconsistent findings. The extent to which the structure-function coupling reflects reliable individual differences or primarily group-common characteristics remains unclear, at both the global and regional brain levels. By leveraging two independent, high-quality datasets, we found that the graph neural network accurately predicted unseen individuals' functional connectivity from structural connectivity, reflecting a strong structure-function coupling. This coupling was primarily driven by network topology and was substantially stronger than that of the linear models. Moreover, we observed that structure-function coupling was dominated by group-common effects, with subtle yet significant individual-specific effects. The regional group and individual effects of coupling were hierarchically organized across the cortex along a sensorimotor-association axis, with lower group and higher individual effects in association cortices. These findings emphasize the importance of considering both group and individual effects in understanding cortical structure-function coupling, suggesting insights into interpreting individual differences of the coupling and informing connectivity-guided therapeutics.

Structural and functional connectome relationships in early childhood

There is strong evidence that the functional connectome is highly related to the white matter connectome in older children and adults, though little is known about structure-function relationships in early childhood. We investigated the development of cortical structure-function coupling in children longitudinally scanned at 1, 2, 4, and 6 years of age (N = 360) and in a comparison sample of adults (N = 89). We also applied a novel graph convolutional neural network-based deep learning model with a new loss function to better capture inter-subject heterogeneity and predict an individual's functional connectivity from the corresponding structural connectivity. We found regional patterns of structure-function coupling in early childhood that were consistent with adult patterns. In addition, our deep learning model improved the prediction of individual functional connectivity from its structural counterpart compared to existing models.

Pituitary adenylate cyclase-activating polypeptide deficient mice show length abnormalities of the axon initial segment

We previously found that pituitary adenylate cyclase-activating polypeptide (PACAP)-deficient (PACAP-/-) mice exhibit dendritic spine morphology impairment and neurodevelopmental disorder (NDD)-like behaviors such as hyperactivity, increased novelty-seeking behavior, and deficient pre-pulse inhibition. Recent studies have indicated that rodent models of NDDs (e.g., attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder) show abnormalities in the axon initial segment (AIS). Here, we revealed that PACAP-/- mice exhibited a longer AIS length in layer 2/3 pyramidal neurons of the primary somatosensory barrel field compared with wild-type control mice. Further, we previously showed that a single injection of atomoxetine, an ADHD drug, improved hyperactivity in PACAP-/- mice. In this study, we found that repeated treatments of atomoxetine significantly improved AIS abnormality along with hyperactivity in PACAP-/- mice. These results suggest that AIS abnormalities are associated with NDDs-like behaviors in PACAP-/- mice. Thus, improvement in AIS abnormalities will be a novel drug therapy for NDDs.