Evaluation of individual-based morphological brain network alterations in children with attention-deficit/hyperactivity disorder: a multi-method investigation

Gray and white matter abnormalities in children with type 2 and 3 SMA: A morphological assessment

This study investigated the changes in brain gray and white matter structure in SMA patients and their correlation with the severity of the disease. A total of 43 SMA patients (including 22 type II and 21 type III SMA patients) and 37 healthy controls were evaluated by MRI. The gray matter volume, gray matter thickness, gray matter surface area, and white matter volume of designated brain regions automatically segmented by FreeSurfer, were compared. We evaluate clinical characteristics of SMA and study the correlation between clinical characteristics and structural changes. SMA showed significant bilateral cortical superficial area loss in the frontal, parietal, and temporal lobes and global white matter volume decreases. Moreover, these patients were also found with an increased mean thickness of entire brain and right gray matter. An increased right postcentral gyrus superficial area, right central sulcus volume, and white matter volume of the right postcentral were associated with higher HFMSE scores.

CONCLUSION

Type 2 and 3 children SMA had extensive, multifocal, symmetrical gray and white matter alterations. Postcentral gyrus degeneration of SMA was associated with the severity of muscular atrophy. The lack of SMN protein possibly interacted with cerebellar structural changes in somatosensory areas.

WHAT IS KNOWN

• MRI has found brain changes in SMA patients, however, there is no unified conclusion and lack of correlation with clinical degree in children SMA with type 2-3.

WHAT IS NEW

• Type II and II children SMA had extensive, multifocal, symmetrical gray and white matter alterations. Postcentral gyrus degeneration of SMA was associated with the severity of muscular atrophy. Cerebellar structural changes in somatosensory areas may attribute to the lack of SMN protein.

Toward individualized connectomes of brain morphology

The morphological brain connectome (MBC) delineates the coordinated patterns of local morphological features (such as cortical thickness) across brain regions. While classically constructed using population-based approaches, there is a growing trend toward individualized modeling. Currently, the methods for individualized MBCs are varied, posing challenges for method selection and cross-study comparisons. Here, we summarize how individualized MBCs are modeled through low-order methods (correlation-, divergence-, distance-, and deviation-based methods) describing relations in brain morphology, as well as high-order methods capturing similarities in these low-order relations. We discuss the merits and limitations of different methods, examining them in the context of robustness, reproducibility, and reliability. We highlight the importance of elucidating the cellular and molecular mechanisms underlying the individualized connectome, and establishing normative benchmarks to assess individual variation in development, aging, and neuropsychiatric disorders.

Aberrant Functional Connectivity in Core-Periphery Structure Based on WSBM in ADHD

OBJECTIVE

Brain network studies have revealed that the community structure of ADHD is altered. However, these studies have only focused on modular community structure, ignoring the core-periphery community structure.

METHOD

This paper employed the weighted stochastic block model to divide the functional connectivity (FC) into 10 communities. And we adopted core score to define the core-periphery structure of FC. Finally, connectivity strength (CS) and disruption index (DI) were used to evaluate the changes of core-periphery structure in ADHD.

RESULTS

The core community of visual network showed reduced CS and a positive value of DI, while the CS of periphery community was enhanced. In addition, the interaction between core communities (involving the sensorimotor and visual network) and periphery community of attention network showed increased CS and a negative valve of DI.

CONCLUSION

Anomalies in core-periphery community structure provide a new perspective for understanding the community structure of ADHD.

Individual-level brain morphological similarity networks: Current methodologies and applications

AIMS

The human brain is an extremely complex system in which neurons, clusters of neurons, or regions are connected to form a complex network. With the development of neuroimaging techniques, magnetic resonance imaging (MRI)-based brain networks play a key role in our understanding of the intricate architecture of human brain. Among them, the structural MRI-based brain morphological network approach has attracted increasing attention due to the advantages in data acquisition, image quality, and in revealing the structural organizing principles intrinsic to the brain. This review is to summarize the methodology and related applications of individual-level morphological networks.

BACKGROUND

There have been a growing number of studies related to brain morphological similarity networks. Conventional morphological networks are intersubject covariance networks constructed using a certain morphological indicator of a group of subjects; individual-level morphological networks, on the other hand, measure the morphological similarity between brain regions for individual brains and can reflect the morphological information of single subjects. In recent years, individual morphological networks have demonstrated significant worth in exploring the topological changes of the human brain under both normal and disease conditions. Such studies provided novel perspectives for understanding human brain development and exploring the pathological mechanisms of neuropsychiatric disorders.

CONCLUSION

This paper mainly focuses on the studies of brain morphological networks at the individual level, introduces several ways for network construction, reviews representative work in this field, and finally points out current problems and future directions.

Exploring the Potential "Brain-Cognition-Behavior" Relationship in Children With ADHD Based on Resting-State Brain Local Activation and Functional Connectivity

OBJECTIVE

Exploring how abnormal brain function in children with ADHD affects executive function and ultimately leads to behavioral impairment provides a theoretical basis for clinically targeted neurotherapy and cognitive training.

METHOD

Amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), and seed-based FC were analyzed in 53 ADHD and 52 healthy controls. The "brain-cognition-behavior" relationship was further explored using mediation analysis.

RESULTS

ADHD showed abnormal local activation in the middle temporal gyrus (MTG), inferior occipital gyrus and inferior frontal gyrus (IFG) and reduced FC between the IFG and the cerebellum. ADHD diagnosis may affect ALFF of MTG and further modulate shift and finally affect inattentive symptoms. It may also affect the total symptoms through the FC of the IFG with the cerebellum.

CONCLUSION

ADHD showed extensive spontaneous activity abnormalities and frontal-cerebellar FC impairments. Localized functional abnormalities in the MTG may affect the shift in EF, resulting in attention deficit behavior.