Network Topological Properties Research Articles

Structural and covariance network alterations of the hippocampus and amygdala in congenital hearing loss children

ObjectiveThe hippocampus and amygdala, as important components of the limbic system, play crucial roles in central remodeling in congenital hearing loss. This study aimed to investigate the morphological integrity and network properties of the subfields of hippocampus and amygdala in children with congenital hearing loss. MethodsA total of 24 children with congenital hearing loss and 17 age- and sex- matched healthy controls (HC) are included in the study. T1-weighted images are analyzed by segmenting the brain into cortical and subcortical regions. Intergroup difference of volumes were explored. Structural covariance networks for the whole brain and hippocampus-amygdala subregions were constructed. Between-group differences of network property are investigated by comparing area under a range of network sparsity. ResultsPatients with congenital hearing loss exhibited significantly larger volumes in the right dentate gyrus and CA3 of the hippocampus. However, there were no significant differences in total hippocampal or showed decreased global efficiency and increased characteristic path length, indicating reduced network integration. Lower betweenness centrality was observed in the left hippocampal fissure in the hearing loss group. The changes in volume and network topological properties are not affected by age and sex. ConclusionChildren with congenital hearing loss display specific volumetric increases in hippocampal subregions, suggesting compensatory adaptations to auditory deprivation. The hippocampus-amygdala network shows significant reorganization, potentially underpinning cognitive and behavioral development issues associated with congenital hearing loss. These findings highlight the importance of targeted neural substrates in understanding and addressing the developmental challenges faced by children with congenital hearing loss.

418 - Changes of topological properties of white matter network in schizophrenia with metabolic syndrome after risperidone and clozapine treatment

418 - Changes of topological properties of white matter network in schizophrenia with metabolic syndrome after risperidone and clozapine treatment

Adaptive microbiome responses to anthracnose in sorghum: Enhanced network complexity and disease resistance across plant niches

Anthracnose threatens sorghum productivity globally, with yield losses exceeding 50 % in some cases, making it crucial to understand plant-microbe-pathogen interactions to develop effective, sustainable control strategies. To probe deeper into the complexity of plant-microbe-pathogen relationships, this study used high-throughput sequencing to characterize microbial communities present in association with sorghum leaves and seeds harvested from both anthracnose infected and uninfected control plants. Our analysis shows that the variation in the diversity and composition of the microbiome due to anthracnose is indicative of an adaptive regulation by coexisting microbes with a plant for enhancing resistance against stresses. These changes were not only reflected by community composition, but also had remarkable effects on the topological properties of microbial ecological networks which further influence certain functions as well as key functional guilds related to plant growth. The presence of anthracnose significantly increased network complexity and resistance in the phyllosphere and leaf endosphere meta-microbiome, which may reflect an adaptive microbiome response to pathogen. The seed-associated microbiomes, however, had relatively no change in diversity and network properties indicating a stable background that may repel pathogen invasion. The study also suggests that anthracnose may facilitate its spread through the reorganization of microbial communities and the enrichment of specific beneficial microbes, aiding in plant defense against pathogens. This is achieved through an upregulation of siderophore production, antimicrobial compounds, phosphate solubilization and sulfur metabolism-specifically genes. Our work also uncovers the possibility for microbiome transfer through phyllosphere-and seed associated microbiomes, thereby indicating that pathogen spread between both above and below ground plant niches limit management options. To conclude, the present study reveals fresh insights into how plant-associated microbiomes respond to anthracnose stress and offers insight on their prospective in sustainable agriculture.

Abnormal Structural–Functional Coupling and MRI Alterations of Brain Network Topology in Progressive Supranuclear Palsy

BackgroundProgressive supranuclear palsy (PSP) can cause structural and functional brain reconstruction. There is a lack of knowledge about the consistency between structural–functional (S–F) connection networks in PSP, despite growing evidence of anomalies in various single brain network parameters.PurposeTo study the changes in the structural and functional networks of PSP, network's topological properties including degree, and the consistency of S–F coupling. The relationship with clinical scales was examined including the assessment of PSP severity, and so on.Study TypeRetrospective.SubjectsA total of 51 PSP patients (70.04 ± 7.46, 25 females) and 101 healthy controls (64.58 ± 8.84, 58 females).Field Strength/Sequence3‐T, resting‐state functional MRI, diffusion tensor imaging, and T1‐weighted images.AssessmentA graph‐theoretic approach was used to evaluate structural and functional network topology metrics. We used the S–F coupling changes to explore the consistency of structural and functional networks.Statistical TestsIndependent samples t tests were employed for continuous variables, χ2 tests were used for categorical variables. For network analysis, two‐sample t tests was used and implied an false discovery rate (FDR) correction. Pearson correlation analysis was used to explore the correlations. A P‐value <0.05 was considered statistically significant.ResultsPSP showed variations within and between modules. Specifically, PSP had decreased network properties changes (t = −2.0136; t = 2.5409; t = −2.5338; t = −2.4296; t = −2.5338; t = 2.8079). PSP showed a lower coupling in the thalamus and left putamen and a higher coupling in the visual, somatomotor, dorsal attention, and ventral attention network. S–F coupling was related to the number of network connections (r = 0.32, r = 0.22) and information transmission efficiency (r = 0.55, r = 0.28). S–F coupling was related to basic academic ability (r = 0.39) and disinhibition (r = 0.49).Data ConclusionPSP may show abnormal S–F coupling and intramodular and intermodular connectome in the structural and functional networks.Level of Evidence3Technical EfficacyStage 3

Transdiagnostic depression severity and its relationship to global and prefrontal-amygdala structural properties in people with major depression and post-traumatic stress disorder.

While some studies have used a transdiagnostic approach to relate depression to metabolic or functional brain alterations, the structural substrate of depression across clinical diagnostic categories is underexplored. In a cross-sectional study of 52 patients with major depressive disorder and 51 with post-traumatic stress disorder, drug-naïve, and spanning mild to severe depression severity, we examined transdiagnostic depressive correlates with regional gray matter volume and the topological properties of gray matter-based networks. Locally, transdiagnostic depression severity correlated positively with gray matter volume in the right middle frontal gyrus and negatively with nodal topological properties of gray matter-based networks in the right amygdala. Globally, transdiagnostic depression severity correlated positively with normalized characteristic path length, a measure implying brain integration ability. Compared with 62 healthy control participants, both major depressive disorder and post-traumatic stress disorder patients showed altered nodal properties in regions of the fronto-limbic-striatal circuit, and global topological organization in major depressive disorder in particular was characterized by decreased integration and segregation. These findings provide evidence for a gray matter-based structural substrate underpinning depression, with the prefrontal-amygdala circuit a potential predictive marker for depressive symptoms across clinical diagnostic categories.

Topological properties of psychopathological networks of healthy and disordered individuals across mental disorders

The identification of psychopathological markers has been the focus of several scientific fields. The results were inconsistent due to lack of a clear nosology. Network analysis, focusing on the interactions between symptoms, provided important insights into the nosology of mental disorders. These interactions originate several topological properties that could constitute markers of psychopathology. One of these properties is network connectivity, which has been explored in recent years. However, the results have been inconsistent, and the topological properties of psychopathological networks remain largely unexplored and unknown. We compared several topological properties (i.e., connectivity, average path length, assortativity, average degree, modularity, global clustering) of psychopathological networks of healthy and disordered participants across depression (N = 2830), generalized anxiety (N = 13,463), social anxiety (N = 12,814), and obsessive-compulsive disorder (N = 16,426). Networks were estimated using Bayesian Gaussian Graphical Models. The Janson-Shannon measure of divergence was used to identify differences between the network properties. Network connectivity distinguished healthy and disordered participants' networks in all disorders. However, in depression and generalized anxiety, network connectivity was higher in healthy participants. The presence and number of motifs also distinguished the networks of healthy and disordered participants. Other topological properties (i.e., modularity, clustering, average path length and average degree) seem to be disorder-specific. The psychopathological significance of network connectivity must be clarified. Some topological properties of psychopathological networks are promising markers of psychopathology and may contribute to clarifying the nosology of mental disorders.

Topological properties of white matter network in first untreated children and adolescents with obsessive-compulsive disorder

Objective: To investigate the topological properties of the white matter network in the drug-naive first-episode children and adolescent with obsessive-compulsive disorder (OCD). Methods: This study was a case-control study. First-episode OCD childhren and adolescents(OCD group) who were treated in the outpatient or inpatient department of the Second Affiliated Hospital of Xinxiang Medical University from July 2018 to October 2023 were collected as the research subjects. Healthy controls (control group)matched by gender, age and education level were used as controls. Deterministic tractography technique was used to construct the whole brain white matter structural network, and graph theory analysis method was used to analyze the topological attributes of the whole brain white matter structure network in OCD children and adolescents. A network-based statistical method was used to examine the inter-group differences in the functional connectivity strength of the whole brain network. Results: Finally, 31 cases were included in the obsessive-compulsive disorder group, including 22 males and 9 females, with an age of (13.5±1.6) years; There were 34 cases in the control group, including 22 males and 12 females, with an age of (12.7±1.4) years. The global efficiency and local efficiency of the OCD group (0.62±0.03, 0.70±0.07) were significantly higher than those of the control group (0.50±0.06, 0.54±0.21) [both P<0.01, false discovery rate(FDR)correction]; while the characteristic path length (1.77±0.08) was significantly smaller than that of the control group (2.10±0.23) (P<0.01, FDR correction).The centrality comparison of nodal betweenness centrality showed that in the OCD group, the connections were enhanced in the left lateral orbitofrontal gyrus, right dorsal agranular insula, left dorsal granular insula, right granular insula, right posterior central gyrus main area of parietal lobe, left ventral granular insula, granular insula, left ventral granulosa, left granular insula, and left dorsal agranular insula [all P<0.001, family wise error (FWE) correction], while the connection of right thalamic was weakened (P<0.001, FWE correction), There were sub-networks characterized by significantly enhanced connection strength of relevant nodes in subcortical, visual network, and default mode network (P<0.05, permutation test 5 000 times). Conclusions: The topological properties of the brain's functional network in children and adolescents with OCD exhibit abnormalities, indicating an immature state of brain functional connectivity.

Engineering Supramolecular Hydrogels via Reversible Photoswitching of Cucurbit[8]uril-Spiropyran Complexation Stoichiometry.

The integration of photoswitchable supramolecular units into hydrogels allows for spatiotemporal control over their nanoscale topological network and macroscale properties using light. Nevertheless, the current availability of photoswitchable supramolecular interactions for the development of such materials remains limited. Here, the molecular design of a novel photoswitchable cucurbit[8]uril-spiropyran host-guest complex exhibiting fast and reversible switching of binding ratios between 1:2 and 1:1 is reported. Photoswitchable complexation stoichiometries are rationally exploited as (de)crosslinking units in multiple polymers for the design of supramolecular hydrogels displaying highly dynamic and switchable features that are spatiotemporally controlled by light. The hydrogels exhibit rapid reversible mechanical softening-hardening upon alternating irradiation with blue and UV light, which is used to significantly accelerate and improve the efficiency of self-healing and shape-remolding of hydrogels. Furthermore, spiropyran endows such materials with unique reversible photochromic properties for reproducible patterning/erasing and information storage. Using a dual-light-assisted extrusion process, meter-scale hydrogel fibers with enhanced structural integrity and photoswitchable ionic conductivity are constructed and woven into various slidable knots and fluorescent shapes. This work represents an innovative molecular design strategy for advancing the development of spatiotemporally engineered supramolecular hydrogels using light and opens avenues for their prospective applications in dynamic materials and adaptive systems.

The Application of Carbon-Based Fertilizer Changed the Microbial Composition and Co-Occurrence Network Topological Properties of Vineyard Soil

Charcoal-based fertilizer could be used extensively and is environmentally friendly. An experiment was designed to investigate the effects of different charcoal-based fertilizer application methods on soil microbiology and grape quality in a vineyard to guide the cultivation of ‘Shine-Muscat’. A control treatment without fertilization and six other treatments were set up. Four treatments applied carbon-based fertilizer as a base fertilizer with or without potassium fulvic acid, a complex microbial agent, or Bacillus subtilis, and two treatments were only applied with two applications of carbon-based fertilizer or compound fertilizer during the expansion period. The results showed that the bacterial phyla were mainly Proteobacteria and Bacteroidetes. Ascomycota, Basidiomycota, and Mortierellomycota dominated the fungal community. At the genus level, the composition of fungi, compared to bacteria, varied significantly, while the dominant flora differed among fertilization practices. Application of charcoal-based fertilizer enriched beneficial microorganisms, while chemical fertilizers enriched pathogenic microorganisms. The addition of microbial fungicides and biostimulants for a period reduced the size of the microbial network, lowered positive correlations, and enhanced resistance to adverse conditions and diseases and there was no significant correlation between agronomic traits and microbial network topology. A combination of soil microbial and grape agronomic traits suggests that a charcoal-based fertilizer base, with microbial fungicides applied, is the optimal fertilization regimen for grape.

Altered structural network in temporal lobe epilepsy with focal to bilateral tonic-clonic seizures.

This study aims to investigate whether alterations in white matter topological networks are associated with focal to bilateral tonic-clonic seizures (FBTCS) in temporal lobe epilepsy (TLE). Additionally, we investigated the variables contributing to memory impairment in TLE. This cross-sectional study included 88 unilateral people with TLE (45 left/43 right), and 42 healthy controls. Graph theory analysis was employed to compare the FBTCS (+) group (n = 51) with the FBTCS (-) group (n = 37). The FBTCS (+) group was subcategorized into current-FBTCS (n = 31) and remote-FBTCS (n = 20), based on the history of FBTCS within 1 year or longer than 1 year before scanning, respectively. We evaluated the discriminatory power of topological network properties by receiver operating characteristic (ROC) analysis. Generalized linear models (GLMs) were employed to investigate variables associated with memory impairment in TLE. Global efficiency (Eg) was significantly reduced in the FBTCS (+) group, especially in the current-FBTCS subgroup. Greater disruption of regional properties in the ipsilateral occipital and temporal association cortices was observed in the FBTCS (+) group. ROC analysis revealed that Eg, normalized characteristic shortest path length, and nodal efficiency of the ipsilateral middle temporal gyrus could distinguish between FBTCS (+) and FBTCS (-) groups. Additionally, GLMs linked the occurrence of current FBTCS with poorer verbal memory outcomes in TLE. Our study suggests that abnormal networks could be the structural basis of seizure propagation in FBTCS. Strategies aimed at reducing the occurrence of FBTCS could potentially improve the memory outcomes in people with TLE.

Distinct brain network patterns in complete and incomplete spinal cord injury patients based on graph theory analysis.

To compare the changes in brain network topological properties and structure-function coupling in patients with complete spinal cord injury (CSCI) and incomplete spinal cord injury (ICSCI), to unveil the potential neurobiological mechanisms underlying the different effects of CSCI and ICSCI on brain networks and identify objective neurobiological markers to differentiate between CSCI and ICSCI patients. Thirty-five SCI patients (20 CSCI and 15 ICSCI) and 32 healthy controls (HCs) were included in the study. Here, networks were constructed using resting-state functional magnetic resonance imaging to analyze functional connectivity (FC) and diffusion tensor imaging for structural connectivity (SC). Then, graph theory analysis was used to examine SC and FC networks, as well as to estimate SC-FC coupling values. Compared with HCs, CSCI patients showed increased path length (Lp), decreased global efficiency (Eg), and local efficiency (Eloc) in SC. For FC, ICSCI patients exhibited increased small-worldness, clustering coefficient (Cp), normalized clustering coefficient, and Eloc. Also, ICSCI patients showed increased Cp and Eloc than CSCI patients. Additionally, ICSCI patients had reduced SC-FC coupling values compared to HCs. Moreover, in CSCI patients, the SC network's Lp and Eg values were significantly correlated with motor scores, while in ICSCI patients, the FC network's Cp, Eloc, and SC-FC coupling values were related to sensory/motor scores. These results suggest that CSCI patients are characterized by decreased efficiency in the SC network, while ICSCI patients are distinguished by increased local connections and SC-FC decoupling. Moreover, the differences in network metrics between CSCI and ICSCI patients could serve as objective biological markers, providing a basis for diagnosis and treatment strategies.

Simulated brain networks reflecting progression of Parkinson’s disease

Abstract Neurodegenerative progression of Parkinson’s disease affects brain structure and function and, concomitantly, alters the topological properties of brain networks. The network alteration accompanied by motor impairment and the duration of the disease has not yet been clearly demonstrated in the disease progression. In this study, we aim to resolve this problem with a modeling approach using the reduced Jansen-Rit model applied to large-scale brain networks derived from cross-sectional MRI data. Optimizing whole-brain simulation models allows us to discover brain networks showing unexplored relationships with clinical variables. We observe that simulated brain networks exhibit significant differences between healthy controls (n = 51) and patients with Parkinson’s disease (n = 60) and strongly correlate with disease severity and disease duration of the patients. Moreover, the modeling results outperform the empirical brain networks in these clinical measures. Consequently, this study demonstrates that utilizing simulated brain networks provides an enhanced view of network alterations in the progression of motor impairment and identifies potential biomarkers for clinical indices.

Topological properties of interfacial hydrogen bond networks

Topological properties of interfacial hydrogen bond networks

EEG Ictal Power Dynamics, Function-Structure Associations, and Epilepsy Surgical Outcomes.

Postoperative seizure control in drug-resistant temporal lobe epilepsy (TLE) remains variable, and the causes for this variability are not well understood. One contributing factor could be the extensive spread of synchronized ictal activity across networks. Our study used novel quantifiable assessments from intracranial EEG (iEEG) to test this hypothesis and investigated how the spread of seizures is determined by underlying structural network topological properties. We evaluated iEEG data from 157 seizures in 27 patients with TLE: 100 seizures from 17 patients with postoperative seizure control (Engel score I) vs 57 seizures from 10 patients with unfavorable surgical outcomes (Engel score II-IV). We introduced a quantifiable method to measure seizure power dynamics within anatomical regions, refining existing seizure imaging frameworks and minimizing reliance on subjective human decision-making. Time-frequency power representations were obtained in 6 frequency bands ranging from theta to gamma. Ictal power spectrums were normalized against a baseline clip taken at least 6 hours away from ictal events. Electrodes' time-frequency power spectrums were then mapped onto individual T1-weighted MRIs and grouped based on a standard brain atlas. We compared spatiotemporal dynamics for seizures between groups with favorable and unfavorable surgical outcomes. This comparison included examining the range of activated brain regions and the spreading rate of ictal activities. We then evaluated whether regional iEEG power values were a function of fractional anisotropy (FA) from diffusion tensor imaging across regions over time. Seizures from patients with unfavorable outcomes exhibited significantly higher maximum activation sizes in various frequency bands. Notably, we provided quantifiable evidence that in seizures associated with unfavorable surgical outcomes, the spread of beta-band power across brain regions is significantly faster, detectable as early as the first second after seizure onset. There was a significant correlation between beta power during seizures and FA in the corresponding areas, particularly in the unfavorable outcome group. Our findings further suggest that integrating structural and functional features could improve the prediction of epilepsy surgical outcomes. Our findings suggest that ictal iEEG power dynamics and the structural-functional relationship are mechanistic factors associated with surgical outcomes in TLE.

Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning.

Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter brain networks and provide new insights from a graph theory perspective. In this study, we extracted and normalized single-subject gray matter networks and calculated each network's topological properties. The heterogeneity through discriminative analysis (HYDRA) method was utilized to subtype all patients based on network properties. Next, we explored the differences among ASD subtypes in terms of network properties and clinical measures. Our investigation identified three distinct ASD subtypes. In the case-control study, these subtypes exhibited significant differences, particularly in the precentral gyrus, lingual gyrus, and middle frontal gyrus. In the case analysis, significant differences in global and nodal properties were observed between any two subtypes. Clinically, subtype 1 showed lower VIQ and PIQ compared to subtype 3, but exhibited higher scores in ADOS-Communication and ADOS-Total compared to subtype 2. The results highlight the distinct brain network properties and behaviors among different subtypes of male patients with ASD, providing valuable insights into the neural mechanisms underlying ASD heterogeneity.

Voxel-based texture similarity networks reveal individual variability and correlate with biological ontologies

The human brain is organized as a complex, hierarchical network. However, the structural covariance patterns among brain regions and the underlying biological substrates of such covariance networks remain to be clarified. The present study proposed a novel individualized structural covariance network termed voxel-based texture similarity networks (vTSNs) based on 76 refined voxel-based textural features derived from structural magnetic resonance images. Validated in three independent longitudinal healthy cohorts (40, 23, and 60 healthy participants, respectively) with two common brain atlases, we found that the vTSN could robustly resolve inter-subject variability with high test-retest reliability. In contrast to the regional-based texture similarity networks (rTSNs) that calculate radiomic features based on region-of-interest information, vTSNs had higher inter- and intra-subject variability ratios and test-retest reliability in connectivity strength and network topological properties. Moreover, the Spearman correlation indicated a stronger association of the gene expression similarity network (GESN) with vTSNs than with rTSNs (vTSN: r = 0.600, rTSN: r = 0.433, z = 39.784, P < 0.001). Hierarchical clustering identified 3 vTSN subnets with differential association patterns with 13 coexpression modules, 16 neurotransmitters, 7 electrophysiology, 4 metabolism, and 2 large-scale structural and 4 functional organization maps. Moreover, these subnets had unique biological hierarchical organization from the subcortex-limbic system to the ventral neocortex and then to the dorsal neocortex. Based on 424 unrelated, qualified healthy subjects from the Human Connectome Project, we found that vTSNs could sensitively represent sex differences, especially for connections in the subcortex-limbic system and between the subcortex-limbic system and the ventral neocortex. Moreover, a multivariate variance component model revealed that vTSNs could explain a significant proportion of inter-subject behavioral variance in cognition (80.0 %) and motor functions (63.4 %). Finally, using 494 healthy adults (aged 19–80 years old) from the Southwest University Adult Lifespan Dataset, the Spearman correlation identified a significant association between aging and vTSN strength, especially within the subcortex-limbic system and between the subcortex-limbic system and the dorsal neocortex. In summary, our proposed vTSN is robust in uncovering individual variability and neurobiological brain processes, which can serve as biologically plausible measures for linking biological processes and human behavior.

Dynamical changes of interaction across functional brain communities during propofol-induced sedation.

It is crucial to understand how anesthetics disrupt information transmission within the whole-brain network and its hub structure to gain insight into the network-level mechanisms underlying propofol-induced sedation. However, the influence of propofol on functional integration, segregation, and community structure of whole-brain networks were still unclear. We recruited 12 healthy subjects and acquired resting-state functional magnetic resonance imaging data during 5 different propofol-induced effect-site concentrations (CEs): 0, 0.5, 1.0, 1.5, and 2.0μg/ml. We constructed whole-brain functional networks for each subject under different conditions and identify community structures. Subsequently, we calculated the global and local topological properties of whole-brain network to investigate the alterations in functional integration and segregation with deepening propofol sedation. Additionally, we assessed the alteration of key nodes within the whole-brain community structure at each effect-site concentrations level. We found that global participation was significantly increased at high effect-site concentrations, which was mediated by bilateral postcentral gyrus. Meanwhile, connector hubs appeared and were located in posterior cingulate cortex and precentral gyrus at high effect-site concentrations. Finally, nodal participation coefficients of connector hubs were closely associated to the level of sedation. These findings provide valuable insights into the relationship between increasing propofol dosage and enhanced functional interaction within the whole-brain networks.

Abnormal dynamic functional connectivity and topological properties of cerebellar network in male obstructive sleep apnea.

To investigate dynamic functional connectivity (dFC) within the cerebellar-whole brain network and dynamic topological properties of the cerebellar network in obstructive sleep apnea (OSA) patients. Sixty male patients and 60 male healthy controls were included. The sliding window method examined the fluctuations in cerebellum-whole brain dFC and connection strength in OSA. Furthermore, graph theory metrics evaluated the dynamic topological properties of the cerebellar network. Additionally, hidden Markov modeling validated the robustness of the dFC. The correlations between the abovementioned measures and clinical assessments were assessed. Two dynamic network states were characterized. State 2 exhibited a heightened frequency, longer fractional occupancy, and greater mean dwell time in OSA. The cerebellar networks and cerebrocerebellar dFC alterations were mainly located in the default mode network, frontoparietal network, somatomotor network, right cerebellar CrusI/II, and other networks. Global properties indicated aberrant cerebellar topology in OSA. Dynamic properties were correlated with clinical indicators primarily on emotion, cognition, and sleep. Abnormal dFC in male OSA may indicate an imbalance between the integration and segregation of brain networks, concurrent with global topological alterations. Abnormal default mode network interactions with high-order and low-level cognitive networks, disrupting their coordination, may impair the regulation of cognitive, emotional, and sleep functions in OSA.

Disrupted individual-level morphological brain network in spinal muscular atrophy types 2 and 3.

Spinal muscular atrophy (SMA) is one of the most common monogenic neuromuscular diseases, and the pathogenesis mechanisms, especially the brain network topological properties, remain unknown. This study aimed to use individual-level morphological brain network analysis to explore the brain neural network mechanisms in SMA. Individual-level gray matter (GM) networks were constructed by estimating the interregional similarity of GM volume distribution using both Kullback-Leibler divergence-based similarity (KLDs) and Jesen-Shannon divergence-based similarity (JSDs) measurements based on Automated Anatomical Labeling 116 and Hammersmith 83 atlases for 38 individuals with SMA types 2 and 3 and 38 age- and sex-matched healthy controls (HCs). The topological properties were analyzed by the graph theory approach and compared between groups by a nonparametric permutation test. Additionally, correlation analysis was used to assess the associations between altered topological metrics and clinical characteristics. Compared with HCs, although global network topology remained preserved in individuals with SMA, brain regions with altered nodal properties mainly involved the right olfactory gyrus, right insula, bilateral parahippocampal gyrus, right amygdala, right thalamus, left superior temporal gyrus, left cerebellar lobule IV-V, bilateral cerebellar lobule VI, right cerebellar lobule VII, and vermis VII and IX. Further correlation analysis showed that the nodal degree of the right cerebellar lobule VII was positively correlated with the disease duration, and the right amygdala was negatively correlated with the Hammersmith Functional Motor Scale Expanded (HFMSE) scores. Our findings demonstrated that topological reorganization may prioritize global properties over nodal properties, and disrupted topological properties in the cortical-limbic-cerebellum circuit in SMA may help to further understand the network pathogenesis underlying SMA.

Creative tendency with brain network efficiency: A graph theory analysis

Creativity is divided into two levels: cognition and affect. Existing brain neuroimaging research has analyzed the cognitive processes involved in creative products. Thus, the connection between creative tendency and brain structure remains limited. This study explored the connection between white matter network structure and creative tendency. The diffusion tensor images of brain white matter and the Creative Tendency Scale scores of 60 healthy adults were evaluated. Graph theory was used to analyze the topological properties of the brain white matter network. After excluding the influences of gender and age, the relationship between the connectivity efficiency (CE) of the brain white matter network and creative tendencies (risk-taking, curiosity, imagination, and preference for complexity) was calculated. Curiosity, imagination, and the total score of creative tendencies were positively correlated with standardized clustering efficiency and small-worldness. In terms of node efficiency, risk-taking was significantly negatively correlated with the left middle temporal gyrus, posterior central gyrus, and right inferior parietal lobe; curiosity was negatively correlated with the right inferior parietal lobe; imagination was negatively correlated with the left middle frontal gyrus; and preference for complexity was negatively correlated with the left cuneus. These findings show that the brain white matter networks affect creative tendencies differently.