The network nature of the brain is gradually becoming a consensus in the neuroscience field. A set of highly connected regions in the brain network called \"rich-club\" are crucial high efficiency communication hubs in the brain. The abnormal rich-club organization can reflect underlying abnormal brain function and metabolism, which receives increasing attention. Diabetes is one of the risk factors for neurological diseases, and most individuals with prediabetes will develop overt diabetes within their lifetime. However, the gradual impact of hyperglycemia on brain structures, including rich-club organization, remains unclear. We hypothesized that the brain follows a special disrupted pattern of rich-club organization in prediabetes and diabetes. We used cross-sectional baseline data from the population-based PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study, which included 2218 participants with a mean age of 61.3 ± 6.6 years and 54.1% females comprising 1205 prediabetes, 504 diabetes, and 509 normal control subjects. The rich-club organization and network properties of the structural networks derived from diffusion tensor imaging data were investigated using a graph theory approach. Linear mixed models were used to assess associations between rich-club organization disruptions and the subjects\' glucose status. Based on the graphical analysis methods, we observed the disrupted pattern of rich-club organization was from peripheral regions mainly located in frontal areas to rich-club regions mainly located in subcortical areas from prediabetes to diabetes. The rich-club organization disruptions were associated with elevated glucose levels. These findings provided more details of the process by which hyperglycemia affects the brain, contributing to a better understanding of the potential neurological consequences. Furthermore, the disrupted pattern observed in rich-club organization may serve as a potential neuroimaging marker for early detection and monitoring of neurological disorders in individuals with prediabetes or diabetes.

We investigated age-related trends in the topology and hierarchical organization of brain structural and functional networks using diffusion-weighted imaging and resting-state fMRI data from a large cohort of healthy aging adults. At the cross-modal level, we explored age-related patterns in the RC involvement of different functional subsystems using a high-resolution functional parcellation. We further assessed age-related differences in the structure-function coupling as well as the network vulnerability to damage to rich club connectivity. Regardless of age, the structural and functional brain networks exhibited a rich club organization and small-world topology. In older individuals, we observed reduced integration and segregation within the frontal-occipital regions and the cerebellum along the brain\'s medial axis. Additionally, functional brain networks displayed decreased integration and increased segregation in the prefrontal, centrotemporal, and occipital regions, and the cerebellum. In older subjects, structural networks also exhibited decreased within-network and increased between-network RC connectivity. Furthermore, both within-network and between-network RC connectivity decreased in functional networks with age. An age-related decline in structure-function coupling was observed within sensory-motor, cognitive, and subcortical networks. The structural network exhibited greater vulnerability to damage to RC connectivity within the language-auditory, visual, and subcortical networks. Similarly, for functional networks, increased vulnerability was observed with damage to RC connectivity in the cerebellum, language-auditory, and sensory-motor networks. Overall, the network vulnerability decreased significantly in subjects older than 70 in both networks. Our findings underscore significant age-related differences in both brain functional and structural RC connectivity, with distinct patterns observed across the adult lifespan.

BACKGROUND: Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure-function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ).
METHODS: We quantified the dynamic structure-function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure-function coupling with the topological features of functional networks to examine how the structure-function relationship facilitates brain information communication over time.
RESULTS: The dynamic structure-function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure-function coupling and the topological features of functional networks are altered in a manner indicative of state specificity.
CONCLUSIONS: These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure-function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Facial palsy therapies based on cortical plasticity are in development, but facial synkinesis progress is limited. Studying neural plasticity characteristics, especially network organization and its constitutive elements (nodes/edges), is the key to overcome the bottleneck. We studied 55 participants (33 facial synkinesis patients, 22 healthy controls) with clinical assessments, functional magnetic resonance imaging (fMRI), and diffusion tensor imaging (DTI). We analyzed rich-club organization and metrics of structural brain networks (rich-club coefficients, strength, degree, density, and efficiency). Functional brain network metrics, including functional connectivity and its coupling with the structural network, were also computed. Patients displayed reduced strength and density of rich-club nodes and edges, as well as decreased global efficiency. All nodes exhibited decreased nodal efficiency in patients. Patients had significantly increased functional connectivity and decreased structural-functional coupling strength in rich-club nodes, rich-club edges, and feeder edges. Our study indicates that facial synkinesis patients have weakened structural connections but enhanced functional transmission from rich-club nodes. The loss of connections and efficiency in structural network may trigger compensatory increases in functional connectivity of rich-club nodes. Two potential biomarkers, rich-club edge density and structural-functional coupling strength, may serve as indicators of disease outcome. These findings provide valuable insights into synkinesis mechanisms and offer potential targets for cortical intervention.

UNASSIGNED: Alzheimer\'s disease (AD) is more prevalent in women than in men; however, there is a discrepancy in research on sex differences in AD. The human brain is a large-scale network with hub regions forming a central core, the rich-club, which is vital to cognitive functions. However, it is unknown whether alterations in the rich-clubs in AD differ between men and women. We aimed to investigate sex differences in the rich-club organization in the brains of patients with AD.
UNASSIGNED: In total, 260 cognitively unimpaired individuals with negative amyloid positron emission tomography (PET) scans, 281 with prodromal AD (mild cognitive impairment due to AD) and 285 with AD dementia who confirmed with positive amyloid PET scans participated in the study. We obtained high-resolution T1-weighted and diffusion tensor images and performed network analysis.
UNASSIGNED: We observed sex differences in the rich-club and feeder connections in patients with AD, suggesting lower structural connectivity strength in women than in men. We observed a significant group-by-sex interaction in the feeder connections, particularly in the thalamus. In addition, the connectivity strength of the thalamus in the feeder connections was significantly correlated with general cognitive function in only men with prodromal AD and women with AD dementia.
UNASSIGNED: Our findings provide important evidence for sex-specific alterations in the structural brain network related to AD.

UNASSIGNED: Convergent evidence has demonstrated a shared rich-club reorganization across multiple major psychiatric conditions. However, previous studies assessing altered functional couplings between rich-club regions have typically focused on the mean time series from entire functional magnetic resonance imaging (fMRI) scanning session, neglecting their time-varying properties.
UNASSIGNED: In this study, we aim to explore the common and/or unique alterations in the temporal variability of rich-club organization among schizophrenia (SZ), bipolar disorder (BD), and attention deficit/hyperactivity disorder (ADHD). We employed a temporal rich-club (TRC) approach to quantitatively assess the propensity of well-connected nodes to form simultaneous and stable structures in a temporal network derived from resting-state fMRI data of 156 patients with major psychiatric disorders (SZ/BD/ADHD = 71/45/40) and 172 healthy controls. We executed the TRC workflow at both whole-brain and subnetwork scales across varying network sparsity, sliding window strategies, lengths and steps of sliding windows, and durations of TRC coefficients.
UNASSIGNED: The SZ and BD groups displayed significantly decreased TRC coefficients compared to corresponding HC groups at the whole-brain scale and in most subnetworks. In contrast, the ADHD group exhibited reduced TRC coefficients in longer durations, as opposed to shorter durations, which markedly differs from the SZ and BD groups. These findings reveal both transdiagnostic and illness-specific patterns in temporal variability of rich-club organization across SZ, BD, and ADHD.
UNASSIGNED: TRC may serve as an effective metric for detecting brain network disruptions in particular states, offering novel insights and potential biomarkers into the neurobiological basis underpinning the behavioral and cognitive deficits observed in these disorders.

BACKGROUND: Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy has been implemented as a therapeutic alternative for the treatment of drug-refractory essential tremor (ET). However, its impact on the brain structural network is still unclear.
OBJECTIVE: To investigate both global and local alterations of the white matter (WM) connectivity network in ET after MRgFUS thalamotomy.
METHODS: Retrospective.
METHODS: Twenty-seven ET patients (61 ± 11 years, 19 males) with MRgFUS thalamotomy and 28 healthy controls (HC) (61 ± 11 years, 20 males) were recruited for comparison.
UNASSIGNED: A 3 T/single shell diffusion tensor imaging by using spin-echo-based echo-planar imaging, three-dimensional T1 weighted imaging by using gradient-echo-based sequence.
RESULTS: Patients were undergoing MRgFUS thalamotomy and their clinical data were collected from pre-operation to 6-month post-operation. Network topological metrics, including rich-club organization, small-world, and efficiency properties were calculated. Correlation between the topological metrics and tremor scores in ET groups was also calculated to assess the role of neural remodeling in the brain.
METHODS: Two-sample independent t-tests, chi-squared test, ANOVA, Bonferroni test, and Spearman\'s correlation. Statistical significance was set at P < 0.05.
RESULTS: For ET patients, the strength of rich-club connection and clustering coefficient significantly increased vs. characteristic path length decreased at 6-month post-operation compared with pre-operation. The distribution pattern of rich-club regions was different in ET groups. Specifically, the order of the rich-club regions was changed according to the network degree value after MRgFUS thalamotomy. Moreover, the altered nodal efficiency in the right temporal pole of the superior temporal gyrus (R = 0.434-0.596) and right putamen (R = 0.413-0.436) was positively correlated with different tremor improvement.
CONCLUSIONS: These findings might improve understanding of treatment-induced modulation from a network perspective and may work as an objective marker in the assessment of ET tremor control with MRgFUS thalamotomy.
METHODS: 3 TECHNICAL EFFICACY: Stage 4.

Despite numerous research showing the association between brain network abnormalities and autism spectrum disorder (ASD), contrasting findings have been reported from broad functional underconnectivity to broad overconnectivity. Thus, the significance of rich-hub organizations in the brain functional connectome of individuals with ASD remains largely unknown. High-quality data subset of ASD (n = 45) and healthy controls (HC; n = 47) children (7-15 years old) were retrieved from the ABIDE data set, and rich-club organization and network-based statistic (NBS) were assessed from resting-state functional magnetic resonance imaging (rs-fMRI). The rich-club organization functional network (normalized rich-club coefficients >1) was observed in all subjects under a range of thresholds. Compared with HC, ASD patients had higher degree of feeder connections and lower degree of local connections (degree of feeder connections: ASD = 259.20 ± 32.97, HC = 244.98 ± 30.09, p = 0.041; degree of local connections: ASD = 664.02 ± 39.19, HC = 679.89 ± 34.05, p = 0.033) but had similar in rich-club connections. Further, nonparametric NBS analysis showed the presence of abnormal connectivity in the functional network of ASD individuals. Our findings indicated that local connection might be more vulnerable, and feeder connection may compensate for its disruption in ASD, enhancing our understanding on the mechanism of functional connectome dysfunction in ASD.

BACKGROUND: Alterations in white matter microstructure and functional activity have been demonstrated to be involved in the central nervous system mechanism of classic trigeminal neuralgia (CTN). However, the rich-club organization and related topological alterations in the CTN brain networks remain unclear.
METHODS: We simultaneously collected diffusion-tensor imaging (DTI) and resting state functional magnetic resonance imaging (rs-fMRI) data from 29 patients with CTN (9 males, mean age = 54.59 years) and 34 matched healthy controls (HCs) (12 males, mean age = 54.97 years) to construct structural networks (SNs) and functional networks (FNs). Rich-club organization was determined separately based on each group\'s SN and different kinds of connections. For both network types, we calculated the basic connectivity properties (network density and strength) and topological properties (global/local/nodal efficiency and small worldness). Moreover, SN-FN coupling was obtained. The relationships between all those properties and clinical measures were evaluated.
RESULTS: Compared to their FN, the SN of CTN patients was disrupted more severely, including its topological properties (reduced network efficiency and small-worldness), and a decrease in network density and strength was observed. Patients showed reorganization of the rich-club architecture, wherein the nodes with decreased nodal efficiency in the SN were mainly non-hub regions, and the local connections were closely related to altered global efficiency and whole brain coupling. While the cortical-subcortical connections of feeder were found to be strengthened in the SN of patients, the coupling between networks increased in all types of connections. Finally, disease severity (duration, pain intensity, and affective alterations) was negatively correlated with coupling (rich-club, feeder, and whole brain) and network strength (the rich-club of the SN and local connections of the FN). A positive correlation was only found between pain intensity and the coupling of local connections.
CONCLUSIONS: The SN of patients with CTN may be more vulnerable. Accompanied by the reorganization of the rich-club, the less efficient network communication and the impaired functional dynamics were largely attributable to the dysfunction of non-hub regions. As compensation, the pain transmission pathway of feeder connections involving in pain processing and emotional regulation may strengthen. The local and feeder sub-networks may serve as potential biomarkers for diagnosis or prognosis.

Rich-club organization is key to efficient global neuronal signaling and integration of information. Alterations interfere with higher-order cognitive processes, and are common to several psychiatric and neurological conditions. A few studies examining the structural connectome in obsessive-compulsive disorder (OCD) suggest lower efficiency of information transfer across the brain. However, it remains unclear whether this is due to alterations in rich-club organization. In the current study, the structural connectome of 28 unmedicated OCD patients, 8 of their unaffected siblings and 28 healthy controls was reconstructed by means of diffusion-weighted imaging and probabilistic tractography. Topological and weighted measures of rich-club organization and connectivity were computed, alongside global and nodal measures of network integration and segregation. The relationship between clinical scores and network properties was explored. Compared to healthy controls, OCD patients displayed significantly lower topological and weighted rich-club organization, allocating a smaller fraction of all connection weights to the rich-club core. Global clustering coefficient, local efficiency, and clustering of nonrich club nodes were significantly higher in OCD patients. Significant three-group differences emerged, with siblings displaying highest and lowest values in different measures. No significant correlation with any clinical score was found. Our results suggest weaker structural connectivity between rich-club nodes in OCD patients, possibly resulting in lower network integration in favor of higher network segregation. We highlight the need of looking at network-based alterations in brain organization and function when investigating the neurobiological basis of this disorder, and stimulate further research into potential familial protective factors against the development of OCD.