Matter Structural Networks Research Articles

Impaired frontal-parietal control network in chronic prostatitis/chronic pelvic pain syndrome revealed by graph theoretical analysis: A DTI study.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is characterized by chronic pain in pelvic area and lower urinary tract symptoms (LUTS). Previous neuroimaging studies demonstrated that chronic pain was associated with the altered brain activity. However, the pathological mechanisms associated with altered brain control of CP/CPPS are not well-understood. Therefore, we sought to investigate the topological properties of white matter brain networks in patients with CP/CPPS and whether the topological configuration of frontal-parietal control network was disrupted. We collected 19 patients with CP/CPPS and 32 matched healthy controls (HCs). Diffusion tensor imaging data of all participates were used to map the white matter structural networks. Graph theoretical method was applied to investigate the alterations of topological properties of brain network in patients. Moreover, we also investigated whether the alerted brain regions might be correlated with any clinical features of patients by the method of Pearson correlation analysis. Both CP/CPPS patients and HCs exhibited a 'small-world' behavior or economical small-world architecture of the white matter brain networks. In addition, CP/CPPS had a lower global efficiency in the right middle frontal gyrus (orbital part) and a higher global efficiency in the left middle cingulate and paracingulate gyri. CP/CPPS also showed increased local efficiency in the left middle cingulate and paracingulate gyri and paracentral lobule. Moreover, the local efficiency of the left middle cingulate gyrus was positively correlated with the scores of the influence of symptoms on the quality of life. The local efficiency of the left precuneus and right supplementary motor area were positively correlated with the total scores of NIH-CPSI and the scores of pain and discomfort symptoms, respectively. Together, we found that patients with CP/CPPS had alterations of connections within the frontal-parietal control network, which suggested that the altered connectivity involved in the executive control processing procedures might contribute to the pathogenesis of the pelvic pain and LUTS in CP/CPPS. Thus these results provided new insights into the understanding of CP/CPPS.

White matter integrity and structural brain network topology in cerebral small vessel disease: The Hamburg city health study.

Cerebral small vessel disease is a common finding in the elderly and associated with various clinical sequelae. Previous studies suggest disturbances in the integration capabilities of structural brain networks as a mediating link between imaging and clinical presentations. To what extent cerebral small vessel disease might interfere with other measures of global network topology is not well understood. Connectomes were reconstructed via diffusion weighted imaging in a sample of 930 participants from a population based epidemiologic study. Linear models were fitted testing for an association of graph‐theoretical measures reflecting integration and segregation with both the Peak width of Skeletonized Mean Diffusivity (PSMD) and the load of white matter hyperintensities of presumed vascular origin (WMH). The latter were subdivided in periventricular and deep for an analysis of localisation‐dependent correlations of cerebral small vessel disease. The median WMH volume was 0.6 mL (1.4) and the median PSMD 2.18 mm2/s x 10−4 (0.5). The connectomes showed a median density of 0.880 (0.030), the median values for normalised global efficiency, normalised clustering coefficient, modularity Q and small‐world propensity were 0.780 (0.045), 1.182 (0.034), 0.593 (0.026) and 0.876 (0.040) respectively. An increasing burden of cerebral small vessel disease was significantly associated with a decreased integration and increased segregation and thus decreased small‐worldness of structural brain networks. Even in rather healthy subjects increased cerebral small vessel disease burden is accompanied by topological brain network disturbances. Segregation parameters and small‐worldness might as well contribute to the understanding of the known clinical sequelae of cerebral small vessel disease.

White matter microarchitecture and structural network integrity correlate with children intelligence quotient

The neural substrate of high intelligence performances remains not well understood. Based on diffusion tensor imaging (DTI) which provides microstructural information of white matter fibers, we proposed in this work to investigate the relationship between structural brain connectivity and intelligence quotient (IQ) scores. Fifty-seven children (8–12 y.o.) underwent a MRI examination, including conventional T1-weighted and DTI sequences, and neuropsychological testing using the fourth edition of Wechsler Intelligence Scale for Children (WISC-IV), providing an estimation of the Full-Scale Intelligence Quotient (FSIQ) based on four subscales: verbal comprehension index (VCI), perceptual reasoning index (PRI), working memory index (WMI), and processing speed index (PSI). Correlations between the IQ scores and both graphs and diffusivity metrics were explored. First, we found significant correlations between the increased integrity of WM fiber-bundles and high intelligence scores. Second, the graph theory analysis showed that integration and segregation graph metrics were positively and negatively correlated with WISC-IV scores, respectively. These results were mainly driven by significant correlations between FSIQ, VCI, and PRI and graph metrics in the temporal and parietal lobes. In conclusion, these findings demonstrated that intelligence performances are related to the integrity of WM fiber-bundles as well as the density and homogeneity of WM brain networks.

Disrupted structural covariance network in first episode schizophrenia patients: Evidence from a large sample MRI-based morphometric study

BackgroundRecent progress in neuroscience research has provided evidence that schizophrenia is a disease that involves dysconnectivity of brain networks. Widespread gray matter loss was commonly observed but how these gray matter abnormalities are characterized at the large-scale network-level in schizophrenia, especially patients with first-episode (FE-SCZ) remains unclear. MethodsIn this study, gray matter structural network aberrations were investigated by applying structural covariance network analysis to 193 first episode schizophrenia patients and 178 age and gender-matched healthy controls (HCs). The mean gray matter volume in seed regions relating to eight specific networks (visual, auditory, sensorimotor, speech, semantic, default-mode, executive control, and salience) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain gray matter volume and each seed region for FE-SCZ and HCs. ResultsThe auditory network was less extended in FE-SCZ compared with HCs, with a significant decrease in the structural association between the Hesch's gyrus and the middle frontal gyrus and the superior frontal gyrus. Hyperconnectivity was observed in executive control network with a significant increase in the structural association between the dorsal lateral prefrontal cortex and the superior frontal gyrus and supplementary motor area. ConclusionOur research shows that seed based structural covariance analysis can well characterize multiple large-scale networks, the observed changes might underly the hallucinations and cognitive impairments observed in FE-SCZ. Given that these patients were experiencing their first episode of schizophrenia, our findings suggest that such structural network deficits are present at an early stage in this disorder.

Disrupted White Matter Integrity and Structural Brain Networks in Temporal Lobe Epilepsy With and Without Interictal Psychosis.

Background: Despite the importance of psychosis as a comorbidity of temporal lobe epilepsy (TLE), the underlying neural mechanisms are still unclear. We aimed to investigate abnormalities specific to psychosis in TLE, using diffusion MRI parameters and graph-theoretical network analysis.Material and Methods: We recruited 49 patients with TLE (20 with and 29 without interictal schizophrenia-like psychosis) and 42 age-/gender-matched healthy controls. We performed 3-tesla MRI scans including 3D T1-weighted imaging and diffusion tensor imaging in all participants. Among the three groups, fractional anisotropy (FA), mean diffusivity (MD), and global network metrics were compared by analyses of covariance. Regional connectivity strength was compared by network-based statistics.Results: Compared to controls, TLE patients showed significant temporal and extra-temporal changes in FA, and MD, which were more severe and widespread in patients with than without psychosis. We observed distinct differences between TLE patients with and without psychosis in the anterior thalamic radiation (ATR), inferior fronto-occipital fasciculus (IFOF), and inferior longitudinal fasciculus (ILF). Similarly, for network metrics, global, and local efficiency and increased path length were significantly reduced in TLE patients compared to controls, but with more severe changes in TLE with psychosis than without psychosis. Network-based statistics detected significant differences between TLE with and without psychosis mainly involving the left limbic and prefrontal areas.Conclusion: TLE patients with interictal schizophrenia-like psychosis showed more widespread and severe white matter impairment, involving the ATR, IFOF and ILF, as well as disrupted network connectivity, particularly in the left limbic and prefrontal cortex, than patients without psychosis.

Altered gray matter structural covariance networks at both acute and chronic stages of mild traumatic brain injury.

Cognitive and emotional impairments observed in mild traumatic brain injury (mTBI) patients may reflect variances of brain connectivity within specific networks. Although previous studies found altered functional connectivity (FC) in mTBI patients, the alterations of brain structural properties remain unclear. In the present study, we analyzed structural covariance (SC) for the acute stages of mTBI (amTBI) patients, the chronic stages of mTBI (cmTBI) patients, and healthy controls. We first extracted the mean gray matter volume (GMV) of seed regions that are located in the default-mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), and the visual network (VN). Then we determined and compared the SC for each seed region among the amTBI, the cmTBI and the healthy controls. Compared with healthy controls, the amTBI patients showed lower SC for the ECN, and the cmTBI patients showed higher SC for the both DMN and SN but lower SC for the SMN. The results revealed disrupted ECN in the amTBI patients and disrupted DMN, SN and SMN in the cmTBI patients. These alterations suggest that early disruptions in SC between bilateral insula and the bilateral prefrontal cortices may appear in amTBI and persist into cmTBI, which might be potentially related to the cognitive and emotional impairments.

White matter structural network disturbances in first-episode, drug-naïve adolescents with generalized anxiety disorder

BackgroundPrevious studies have suggested that individuals with generalized anxiety disorder (GAD) would show inefficient whole-brain communication and dysconnectivity in the fronto-parietal-subcortical sub-networks in the white matter (WM) structural network. However, these hypotheses have yet to be tested. MethodsIndividual WM structural networks were constructed based on diffusion MRI data and deterministic tractography in 34 first-episode, medication-naïve adolescents with GAD and 27 healthy controls (HCs). Graph theory was applied to investigate the topological organization alterations of the structural network. ResultsGAD patients showed disrupted small-world configurations (i.e., increased path length and decreased clustering coefficient) and hub organization (i.e., less connection strength in the feeder and local connections). A decreased connection strength was found in a GAD-related sub-network (mainly involving the frontal-subcortical circuits), which was able to distinguish GAD patients from HCs with higher accuracy (area under the curve of 0.96, sensitivity of 94%, specificity of 89%) than clinical scores and other topological alternations. LimitationsThe current study just compared GAD patients with HCs based on a small sample, leaving whether the alternations found here are specific to GAD still an open question. Future studies are recommended to recruit patients with other anxiety disorders (e.g., social anxiety disorder) and/or comorbid mood disorders to identify the GAD-specific WM alterations using a larger sample. ConclusionsOur findings highlight the disruption of the topological organization of the whole-brain WM structural network (especially the frontal-subcortical circuits) in GAD, and suggest the potential of using structural connectivity of the GAD-related sub-network as a biomarker for GAD patients.

Characteristics of White Matter Structural Networks in Chronic Schizophrenia Treated With Clozapine or Risperidone and Those Never Treated.

BackgroundDespite its benefits, a major concern regarding antipsychotic treatment is its possible impact on the brain’s structure and function. This study sought to explore the characteristics of white matter structural networks in chronic never-treated schizophrenia and those treated with clozapine or risperidone, and its potential association with cognitive function.MethodsDiffusion tensor imaging was performed on a unique sample of 34 schizophrenia patients treated with antipsychotic monotherapy for over 5 years (17 treated with clozapine and 17 treated with risperidone), 17 never-treated schizophrenia patients with illness duration over 5 years, and 27 healthy control participants. Graph theory and network-based statistic approaches were employed.ResultsWe observed a disrupted organization of white matter structural networks as well as decreased nodal and connectivity characteristics across the schizophrenia groups, mainly involving thalamus, prefrontal, and occipital regions. Alterations in nodal and connectivity characteristics were relatively milder in risperidone-treated patients than clozapine-treated patients and never-treated patients. Altered global network measures were significantly associated with cognitive performance levels. Structural connectivity as reflected by network-based statistic mediated the difference in cognitive performance levels between clozapine-treated and risperidone-treated patients.LimitationsThese results are constrained by the lack of random assignment to different types of antipsychotic treatment.ConclusionThese findings provide insight into the white matter structural network deficits in patients with chronic schizophrenia, either being treated or untreated, and suggest white matter structural networks supporting cognitive function may benefit from antipsychotic treatment, especially in those treated with risperidone.

Brain structural connectome in relation to PRRT2 mutations in paroxysmal kinesigenic dyskinesia.

This study explored the topological characteristics of brain white matter structural networks in patients with Paroxysmal Kinesigenic Dyskinesia (PKD), and the potential influence of the brain network stability gene PRRT2 on the structural connectome in PKD. Thirty‐five PKD patients with PRRT2 mutations (PKD‐M), 43 PKD patients without PRRT2 mutations (PKD‐N), and 40 demographically‐matched healthy control (HC) subjects underwent diffusion tensor imaging. Graph theory and network‐based statistic (NBS) approaches were performed; the topological properties of the white matter structural connectome were compared across the groups, and their relationships with the clinical variables were assessed. Both disease groups PKD‐M and PKD‐N showed lower local efficiency (implying decreased segregation ability) compared to the HC group; PKD‐M had longer characteristic path length and lower global efficiency (implying decreased integration ability) compared to PKD‐N and HC, independently of the potential effects of medication. Both PKD‐M and PKD‐N had decreased nodal characteristics in the left thalamus and left inferior frontal gyrus, the alterations being more pronounced in PKD‐M patients, who also showed abnormalities in the left fusiform and bilateral middle temporal gyrus. In the connectivity characteristics assessed by NBS, the alterations were more pronounced in the PKD‐M group versus HC than in PKD‐N versus HC. As well as the white matter alterations in the basal ganglia‐thalamo‐cortical circuit related to PKD with or without PRRT2 mutations, findings in the PKD‐M group of weaker small‐worldness and more pronounced regional disturbance show the adverse effects of PRRT2 gene mutations on brain structural connectome.

Altered White Matter Structural Network in Frontal and Temporal Lobe Epilepsy: A Graph-Theoretical Study.

Temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE) are the largest subgroup of partial epilepsy, and focal cortical dysplasias (FCDs) are highly epileptogenic brain lesions and are a frequent cause for antiepileptic drug (AED)-resistant focal epilepsies that mostly occur in the temporal and frontal lobes. We performed a graph-theoretical study based on the diffusion tensor imaging (DTI) data of patients with FLE or TLE caused by FCDs or lesions with high suspicion of FCDs and evaluated their cognitive function by the Chinese version of the Montreal Cognitive Assessment-Basic (MoCA-BC). The construction of the white matter structural network and graph-theoretical analysis was performed by Pipeline for Analysing Brain Diffusion Images (PANDA) and Graph-theoretical Network Analysis (GRETNA). We used the nonparametric analysis of covariance to compare the differences in diffusion metrics, network attributes and nodal attributes among FLE, TLE, and healthy control (HC) groups and then performed post hoc pairwise comparisons. Nonparametric Spearman partial correlation analysis was performed to analyse the correlation of network attributes with the age of onset, duration of disease, and MoCA-BC scores in patients with FLE and TLE. The results showed that the white matter structural network in patients with FLE and TLE was impaired in a more extensive set of regions than the FCD location. The similarities in white matter alterations between FLE and TLE suggested that their epileptogenic network might affect the fronto-temporal white matter tracts and thalamo-occipital connections, which might be responsible for the overlapping cognitive deficits in FLE and TLE. The white matter impairments in patients with FLE were more severe than those in patients with TLE, which might be explained by more affected nodes in the areas of DMN in patients with FLE.

Impaired Structural Network Properties Caused by White Matter Hyperintensity Related to Cognitive Decline.

Purpose: There is a high correlation between white matter hyperintensity (WMH) and cognitive impairment (CI) in elderly people. However, not all WMH will develop into CI, and the potential mechanism of WMH-related CI is still unclear. This study aimed to investigate the topological properties of white matter structural network in WMH-related CI.Methods: Forty-one WMH subjects with CI (WMH-CI), 42 WMH subjects without CI (WMH-no-CI), and 52 elderly healthy controls (HC) were recruited. Diffusion tensor imaging (DTI) fiber tractography and graph theoretical analysis were applied to construct the structural network. We compared network properties and clinical features among the three groups. Multiple linear regression analysis was performed to investigate the relationships among WMH volumes, impaired network properties, and cognitive functions in the WMH-CI group.Results: Compared with the controls, both WMH groups showed decreased network strength, global efficiency, and increased characteristic path length (Lp) at the level of the whole brain. The WMH-CI group displayed more profound impairments of nodal efficiency and nodal path length (NLp) within multiple regions including precentral, cingulate, and medial temporal gyrus. The disrupted network properties were associated with CI and WMH burdens in the WMH-CI group. Furthermore, a mediation effect of NLp in the left inferior frontal gyrus was observed for the association between periventricular WMH (PWMH) and memory deficit.Conclusions: Brain structural network in WMH-CI is significantly disturbed, and this disturbance is related to the severity of WMH and CI. Increased NLp in the left opercular part of inferior frontal gyrus (IFGoperc.L) was shown to be a mediation framework between PWMH and WMH-related memory, which shed light on investigating the underlying mechanisms of CI caused by WMH.

Altered white matter structural networks in drug-naïve patients with obsessive-compulsive disorder.

White matter (WM) alteration is considered to be a vital neurological mechanism of obsessive-compulsive disorder (OCD). However, little is known regarding the changes in topological organization of WM structural network in OCD. We acquired diffusion tensor imaging (DTI) datasets from 28 drug-naïve OCD patients and 28 well-matched healthy controls (HC). A deterministic fiber tracking approach was used to construct the whole-brain structural connectome. Group differences in global and nodal topological properties as well as rich-club organizations were compared by using graph theory analysis. The relationship between the altered network metrics and the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) was calculated. Compared with controls, OCD patients exhibited a significantly decreased small-worldness (σ), normalized clustering coefficient (γ) and shortest path length (Lp), as well as an increased global efficiency (Eglob). The nodal efficiency (Enodal) was found to be reduced in the left middle frontal gyrus, and increased in the right parahippocampal gyrus and bilateral putamen in OCD patients. Besides, OCD patients showed increased rich-club, feeder and local connection strength, and the connection strength of the rich-club was positively correlated with the total Y-BOCS score. Our findings emphasized a central role for the complicatedly changed topological architecture of brain structural networks in the pathological mechanism underlying OCD.

Impaired Topological Properties of Gray Matter Structural Covariance Network in Epilepsy Children With Generalized Tonic-Clonic Seizures: A Graph Theoretical Analysis.

Modern network science has provided exciting new opportunities for understanding the human brain as a complex network of interacting regions. The improved knowledge of human brain network architecture has made it possible for clinicians to detect the network changes in neurological diseases. Generalized tonic–clonic seizure (GTCS) is a subtype of epilepsy characterized by generalized spike-wave discharge involving the bilateral hemispheres during seizure. Network researches in adults with GTCS exhibited that GTCS can be conceptualized as a network disorder. However, the overall organization of the brain structural covariance network in children with GTCS remains largely unclear. Here, we used a graph theory method to assess the gray matter structural covariance network organization of 14 pediatric patients diagnosed with GTCS and 29 healthy control children. The group differences in regional and global topological properties were investigated. Results revealed significant changes in nodal betweenness locating in brain regions known to be abnormal in GTCS (the right thalamus, bilateral temporal pole, and some regions of default mode network). The network hub analysis results were in accordance with the regional betweenness, which presented a disrupted regional topology of structural covariance network in children with GTCS. To our knowledge, the present study is the first work reporting the changes of structural topological properties in children with GTCS. The findings contribute new insights into the understanding of the neural mechanisms underlying GTCS and highlight critical regions for future neuroimaging research in children with GTCS.

Network topology and machine learning analyses reveal microstructural white matter changes underlying Chinese medicine Dengzhan Shengmai treatment on patients with vascular cognitive impairment

With the increasing incidence of cerebrovascular diseases and dementia, considerable efforts have been made to develop effective treatments on vascular cognitive impairment (VCI), among which accumulating practice-based evidence has shown great potential of the traditional Chinese medicine (TCM). Current randomized double-blind controlled trial has been designed to evaluate the 6-month treatment effects of Dengzhan Shengmai (DZSM) capsules, one TCM herbal preparations on VCI, and to explore the underlying neural mechanisms with graph theory-based analysis and machine learning method based on diffusion tensor imaging (DTI) data. A total of 82 VCI patients were recruited and randomly assigned to drug (45 with DZSM) and placebo (37 with placebo) groups, and neuropsychological and neuroimaging data were acquired at baseline and after 6-month treatment. After treatment, compared to the placebo group, the drug groups showed significantly improved performance in Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-cog) score (p < 0.001) and the other cognitive domains. And with the reconstruction of white matter structural network, there were more streamlines connecting the left thalamus and right hippocampus in the drug groups (p < 0.001 uncorrected), with decreasing nodal efficiency of the right olfactory associated with slower decline in the general cognition (r = −0.364, p = 0.048). Moreover, support vector machine classification analyses revealed significant white matter network alterations after treatment in the drug groups (accuracy of baseline vs. 6-month later, 68.18 %). Taking together, the present study showed significant efficacy of DZSM treatment on VCI, which might result from white matter microstructure alterations and the topological changes in brain structural network.

Altered Rich-Club Organization and Regional Topology Are Associated With Cognitive Decline in Patients With Frontal and Temporal Gliomas.

ObjectivesGliomas are widely considered to be related to the altered topological organization of functional networks before operations. Tumors are usually thought to cause multimodal cognitive impairments. The structure is thought to form the basics of function, and the aim of this study was to reveal the rich-club organization and topological patterns of white matter (WM) structural networks associated with cognitive impairments in patients with frontal and temporal gliomas.MethodsGraph theory approaches were utilized to reveal the global and regional topological organization and rich-club organization of WM structural networks of 14 controls (CN), 13 frontal tumors (FTumor), and 18 temporal tumors (TTumor). Linear regression was used to assess the relationship between cognitive performances and altered topological parameters.ResultsWhen compared with CN, both FTumor and TTumor showed no alterations in small-world properties and global network efficiency, but instead showed altered local network efficiency. Second, FTumor and TTumor patients showed similar deficits in the nodal shortest path in the left rolandic operculum and degree centrality (DC) of the right dorsolateral and medial superior frontal gyrus (SFGmed). Third, compared to FTumor patients, TTumor patients showed a significantly higher DC in the right dorsolateral and SFGmed, a higher level of betweenness in the right SFGmed, and higher nodal efficiency in the left middle frontal gyrus and right SFGmed. Finally, rich-club organization was disrupted, with increased structural connectivity among rich-club nodes and reduced structural connectivity among peripheral nodes in FTumor and TTumor patients. Altered local efficiency in TTumor correlated with memory function, while altered local efficiency in FTumor correlated with the information processing speed.ConclusionBoth FTumor and TTumor presented an intact global topology and altered regional topology related to cognitive impairment and may also share the convergent and divergent regional topological organization of WM structural networks. This suggested that a compensatory mechanism plays a key role in global topology formation in both FTumor and TTumor patients, and as such, development of a structural connectome for patients with brain tumors would be an invaluable medical resource and allow clinicians to make comprehensive preoperative planning.

Topological changes in white matter connectivity network in patients with Parkinson's disease and depression.

Depression is the most common non-motor symptom accompanying Parkinson's disease (PD) with high prevalence but unclear pathophysiological mechanism. Relatively little is known about the topological patterns of white matter structural networks in depressed patients with PD. In this study, we used diffusion-tensor imaging (DTI) and graph theory approaches to explore the brain structural connectome in non-depressed patients with PD (n = 47), depressed patients with PD (n = 20) and healthy controls (n = 46). All three groups exhibited small-world topology. Compared with healthy controls, non-depressed patients with PD and depressed patients with PD showed a significant reduction of network efficiency in the cortico-subcortical circuits. Moreover, depressed patients with PD exhibited higher network efficiency in fronto-limbic system, compared to non-depressed patients with PD. To sum up, our data indicated a disrupted integrity in the large-scale brain systems in depressed patients with PD patients. The structural connectome provided a basis for functional alterations in depressed patients with PD that may advance our current understanding of pathophysiological mechanism underlying Parkinson's disease.

Altered properties of brain white matter structural networks in patients with nasopharyngeal carcinoma after radiotherapy.

Previous neuroimaging studies revealed radiation-induced brain injury in patients with nasopharyngeal carcinoma (NPC) in the years after radiotherapy (RT). These injuries may be associated with structural and functional alterations. However, differences in the brain structural connectivity of NPC patients at different times after RT, especially in the early-delayed period, remain unclear. We acquired diffusion tensor imaging (DTI) data from three groups of NPC patients, 25 in the pre-RT (before RT) group, 22 in the early-delayed (1-6months) period (post-RT-ED) group, and 33 in the late-delayed (>6months) period (post-RT-LD) group. Then, we constructed brain white matter (WM) structural networks and used graph theory to compare their between-group differences. The NPC patients in the post-RT-ED group showed decreased global properties when compared with the pre-RT group. We also detected the nodes with between-group differences in nodal parameters. The nodes that differed between the post-RT-ED and pre-RT groups were mainly located in the default mode (DMN) and central executive networks (CEN); those that differed between the post-RT-LD and pre-RT groups were located in the limbic system; and those that differed between the post-RT-LD and post-RT-ED groups were mainly in the DMN. These findings may indicate that radiation-induced brain injury begins in the early-delayed period and that a reorganization strategy begins in the late-delayed period. Our findings may provide new insight into the pathogenesis of radiation-induced brain injury in normal-appearing brain tissue from the network perspective.

Variation in Brain Subcortical Network Topology Between Men With and Without PE: A Diffusion Tensor Imaging Study

IntroductionPremature ejaculation (PE) is a highly prevalent male sexual dysfunction. Previous studies have found abnormal activity in the sympathetic nervous system and penile sensory pathway of PE. Few studies have investigated the neural mechanisms underlying PE. AimThe aim of this study was to examine whether the altered cortico-subcortical network topological properties of the brain white matter structural network could be used to differentiate patients with PE from healthy control (HC) subjects. MethodsDiffusion tensor images data were collected from 32 patients with PE and 35 HC participants. Then, brain white matter structural networks were reconstructed from image acquisition. Main Outcome MeasureFurthermore, nodal measures were calculated and hub regions were identified using the graph-theoretical methods. ResultsFor cortical brain regions, increased strength, global efficiency, and decreased shortest path length were found in the right superior frontal gyrus (medial), and superior frontal gyrus (medial orbital) were found in patients with PE. In addition, patients with PE also showed decreased strength in the right rolandic operculum and decreased shortest path length, and increased global efficiency in the right inferior frontal gyrus (triangular part). For subcortical brain structures, patients with PE were associated with decreased shortest path length and increased global efficiency in the left insula and right caudate nucleus. Finally, the results showed that 9 PE-specific hub regions were identified in patients compared with HCs, including 7 cortical regions and 2 subcortical regions. Clinical ImplicationsOur results provide new understanding about the pathology of PE and enhances the understanding of PE pathology. Strength & LimitationsOur results offer biological markers for understanding the physiopathology of PE. However, our study is a cross-sectional design, longitudinal design studies need to explore the causal relationships between aberrant topological characteristics and PE. ConclusionOur results provide new insights into the neural mechanism of PE involving cortico-subcortical network changes, which could serve as a potential biomarker to differentiate individuals with PE from HCs.Chen J, Yang J, Huang X, et al. Variation in Brain Subcortical Network Topology Between Men With and Without PE: A Diffusion Tensor Imaging Study. J Sex Med 2020;17:48–59.

Associations between brain structural networks and neurological soft signs in healthy adults

Neurological soft signs (NSS), as minor neurological deficits, have been identified in several psychiatric disorders, especially in schizophrenia. However, it's unclear how the neuropathological processes of the disease affect NSS related brain morphological changes and whether it is confounded by the use of medication. As NSS also exist in healthy people, the potential confounding effects of psychopathology or medication will be excluded if NSS are investigated in healthy people. Therefore, we applied a novel multivariate approach, source-based morphometry (SBM), to study structural networks in relation to NSS in healthy adults based on structural magnetic resonance imaging (MRI) data. The Heidelberg Scale was applied to evaluate NSS. Using SBM, we constructed structural networks and investigated their associations with NSS in healthy adults. Six grey matter (GM) structural networks were identified. Sensory integration subscores were associated with the cerebellar component and the cortico-basal ganglia-thalamic component. Motor coordination subscores and total NSS scores were associated with the sensorimotor component. The present findings indicated that structural network abnormalities in cerebellar, subcortical and cortical sensorimotor areas contribute to NSS performance in healthy adults.

Abnormal Gray Matter Structural Covariance Networks in Children With Bilateral Cerebral Palsy.

Bilateral cerebral palsy (BCP) is a common movement disorder in children, which often results in lifelong motor disability. One main symptom of BCP is the limitation of hand function in everyday activities. However, the neuroanatomical basis of this prominent hand impairment is yet to discover. Recent advances mainly focus on the lesions of BCP, but the views on the atypical development of cortical parcellations are extremely lacking. Here, in our study, neuroimaging with network analysis was employed to evaluate the changes of structural covariance networks (SCNs) in BCP children. We aimed to elucidate the alteration of SCNs based on cortical thickness (CT), and to reveal the relationship of CT and hand function in the participants with BCP. SCNs were constructed using covariance between regional CT, which was acquired from T1-weighted images of 19 children with BCP and 19 demographically matched healthy controls (HCs). Compared with HCs, BCP children showed increased CT in several regions involving the bilateral areas (lateral occipital, lingual, and fusiform) and right areas (cuneus, pericalcarine, inferior temporal, middle temporal, superior temporal, and insula). Decreased CT was found in the left superior temporal and right superior parietal cortices. Global network analyses revealed significantly decreased normalized clustering and small-worldness in the BCP network. The area under the curve (AUC) of global network measures varied slightly between the BCP and HC networks. The resistance of the both SCNs to the target and random attack showed no significant difference. Also, the BCP foci (right superior temporal and subtemporal cortex) showed a significantly negative correlation between the CT and manual ability. In this work, we identified the CT-based SCNs changes in children with BCP. The abnormal topological organization of SCNs was revealed, indicating abnormal CT, incongruous development of structural wiring, destructive nodal profiles of betweenness, and moved hub distribution in BCP children. This may provide a neuroanatomical hallmark of BCP in the developing brain. Therefore, our results may not only reflect neurodevelopmental aberrations but also compensatory mechanisms.