White Matter Structural Networks Research Articles

Topological alterations in white matter anatomical networks in cervical dystonia

BackgroundAccumulating neuroimaging evidence indicates that patients with cervical dystonia (CD) have changes in the cortico-subcortical white matter (WM) bundle. However, whether these patients’ WM structural networks undergo reorganization remains largely unclear. We aimed to investigate topological changes in large-scale WM structural networks in patients with CD compared to healthy controls (HCs), and explore the network changes associated with clinical manifestations.MethodsDiffusion tensor imaging (DTI) was conducted in 30 patients with CD and 30 HCs, and WM network construction was based on the BNA-246 atlas and deterministic tractography. Based on the graph theoretical analysis, global and local topological properties were calculated and compared between patients with CD and HCs. Then, the AAL-90 atlas was used for the reproducibility analyses. In addition, the relationship between abnormal topological properties and clinical characteristics was analyzed.ResultsCompared with HCs, patients with CD showed changes in network segregation and resilience, characterized by increased local efficiency and assortativity, respectively. In addition, a significant decrease of network strength was also found in patients with CD relative to HCs. Validation analyses using the AAL-90 atlas similarly showed increased assortativity and network strength in patients with CD. No significant correlations were found between altered network properties and clinical characteristics in patients with CD.ConclusionOur findings show that reorganization of the large-scale WM structural network exists in patients with CD. However, this reorganization is attributed to dystonia-specific abnormalities or hyperkinetic movements that need further identification.

Vascular Risk Factors and Brain Health in Aging: Insights from a Community-Based Cohort Study.

The aging population and high rates of Alzheimer's disease (AD) create significant medical burdens, prompting a need for early prevention. Targeting modifiable risk factors like vascular risk factors (VRFs), closely linked to AD, may provide a promising strategy for intervention. This study investigates how VRFs influence cognitive performance and brain structures in a community-based cohort. In this cross-sectional study, 4,667 participants over 50 years old, drawn from the Beijing Ageing Brain Rejuvenation Initiative project, were meticulously examined. Cognitive function and VRFs (diabetes mellitus, hypertension, hyperlipidemia, obesity, and smoking), were comprehensively assessed through one-to-one interviews. Additionally, a subset of participants (n = 719) underwent MRI, encompassing T1-weighted and diffusion-weighted scans, to elucidate gray matter volume and white matter structural network organization. The findings unveil diabetes as a potent detriment to memory, manifesting in atrophy within the right supramarginal gyrus and diminished nodal efficiency and degree centrality in the right inferior parietal lobe. Hypertension solely impaired memory without significant structural changes. Intriguingly, individuals with comorbid diabetes and hypertension exhibited the most pronounced deficits in both brain structure and cognitive performance. Remarkably, hyperlipidemia emerged as a factor associated with enhanced cognition, and preservation of brain structure. This study illuminates the intricate associations between VRFs and the varied patterns of cognitive and brain structural damage. Notably, the synergistic effect of diabetes and hypertension emerges as particularly deleterious. These findings underscore the imperative to tailor interventions for patients with distinct VRF comorbidities, especially when addressing cognitive decline and structural brain changes.

Altered topological structure of the brain white matter in maltreated children through topological data analysis.

Childhood maltreatment may adversely affect brain development and consequently influence behavioral, emotional, and psychological patterns during adulthood. In this study, we propose an analytical pipeline for modeling the altered topological structure of brain white matter in maltreated and typically developing children. We perform topological data analysis (TDA) to assess the alteration in the global topology of the brain white matter structural covariance network among children. We use persistent homology, an algebraic technique in TDA, to analyze topological features in the brain covariance networks constructed from structural magnetic resonance imaging and diffusion tensor imaging. We develop a novel framework for statistical inference based on the Wasserstein distance to assess the significance of the observed topological differences. Using these methods in comparing maltreated children with a typically developing control group, we find that maltreatment may increase homogeneity in white matter structures and thus induce higher correlations in the structural covariance; this is reflected in the topological profile. Our findings strongly suggest that TDA can be a valuable framework to model altered topological structures of the brain. The MATLAB codes and processed data used in this study can be found at https://github.com/laplcebeltrami/maltreated.

Lateralization of dorsal fiber tract targeting Broca’s area concurs with language skills during development

Language is bounded to the left hemisphere in the adult brain and the functional lateralization can already be observed early during development. Here we investigate whether this is paralleled by a lateralization of the white matter structural language network. We analyze the strength and microstructural properties of language-related fiber tracts connecting temporal and frontal cortices with a separation of two dorsal tracts, one targeting the posterior Broca’s area (BA44) and one targeting the precentral gyrus (BA6). In a large sample of young children (3–6 years), we demonstrate that, in contrast to the BA6-targeting tract, the microstructural asymmetry of the BA44-targeting fiber tract significantly correlates locally with different aspects of development. While the asymmetry in its anterior segment reflects age, the asymmetry in its posterior segment is associated with the children’s language skills. These findings demonstrate a fine-grained structure-to-function mapping in the lateralized network and go beyond our current view of language-related human brain maturation.

White matter structural changes before and after microvascular decompression for hemifacial spasm.

Hemifacial spasm (HFS) is a syndrome characterized by involuntary contractions of the facial muscles innervated by the ipsilateral facial nerve. Currently, microvascular decompression (MVD) is an effective treatment for HFS. Diffusion weighted imaging (DWI) is a non-invasive advanced magnetic resonance technique that allows us to reconstruct white matter (WM) virtually based on water diffusion direction. This enables us to model the human brain as a complex network using graph theory. In our study, we recruited 32 patients with HFS and 32 healthy controls to analyze and compare the topological organization of whole-brain white matter networks between the groups. We also explored the potential relationships between altered topological properties and clinical outcomes. Compared to the HC group, the white matter network was disrupted in both preoperative and postoperative groups of HFS patients, mainly located in the somatomotor network, limbic network, and default network (All P < 0.05, FDR corrected). There was no significant difference between the preoperative and postoperative groups (P > 0.05, FDR corrected). There was a correlation between the altered topological properties and clinical outcomes in the postoperative group of patients (All P < 0.05, FDR corrected). Our findings indicate that in HFS, the white matter structural network was disrupted before and after MVD, and that these alterations in the postoperative group were correlated with the clinical outcomes. White matter alteration here described may subserve as potential biomarkers for HFS and may help us identify patients with HFS who can benefit from MVD and thus can help us make a proper surgical patient selection.

Disrupted Structural Brain Networks and Structural-Functional Decoupling in First-Episode Drug-Naïve Adolescent Major Depressive Disorder

PurposeMajor depressive disorder (MDD) tends to emerge during adolescence, but the neurobiology of adolescent MDD is still poorly understood. This study aimed to explore the topological organization of white matter structural networks and the relationship between structural and functional connectivity in adolescent MDD. MethodsStructural and functional magnetic resonance imaging data were acquired from 94 first-episode drug-naïve adolescent MDD patients and 78 healthy adolescents. Whole brain structural and functional brain networks were constructed for each subject. Then, the topological organization of structural brain networks and the coupling strength between structural and functional connectivity were analyzed. ResultsCompared with controls, adolescent MDD patients showed disrupted small-world, rich-club, and modular organizations. Nodal centralities in the medial part of bilateral superior frontal gyrus, bilateral hippocampus, right superior occipital gyrus, right angular gyrus, bilateral precuneus, left caudate nucleus, bilateral putamen, right superior temporal gyrus, and right temporal pole part of superior temporal gyrus were significantly lower in adolescent MDD patients compared with controls. The coupling strength between structural and functional connectivity was significantly lower in adolescent MDD patients compared with controls. DiscussionOur findings suggest widespread disruption of structural brain networks and structural-functional decoupling in adolescent MDD, potentially leading to reduced network communication capacity.

Disrupted small-world white matter networks in patients with major depression and recent suicide plans or attempts.

Suicide is a major concern for health, and depression is an established proximal risk factor for suicide. This study aimed to investigate white matter features associated with suicide. We constructed white matter structural networks by deterministic tractography via diffusion tensor imaging in 51 healthy controls, 47 depressed patients without suicide plans or attempts and 56 depressed patients with suicide plans or attempts. Then, graph theory analysis was used to measure global and nodal network properties. We found that local efficiency was decreased and path length was increased in suicidal depressed patients compared to healthy controls and non-suicidal depressed patients; moreover, the clustering coefficient was decreased in depressed patients compared to healthy controls; and the global efficiency and normalized characteristic path length was increased in suicidal depressed patients compared to healthy controls. Similarly, compared with those in non-suicidal depressed patients, nodal efficiency in the thalamus, caudate, medial orbitofrontal cortex, hippocampus, olfactory cortex, supplementary motor area and Rolandic operculum was decreased. In summary, compared with those of non-suicidal depressed patients, the structural connectome of suicidal depressed patients exhibited weakened integration and segregation and decreased nodal efficiency in the fronto-limbic-basal ganglia-thalamic circuitry. These alterations in the structural networks of depressed suicidal brains provide insights into the underlying neurobiology of brain features associated with suicide.

Specific Alterations in Brain White Matter Networks and Their Impact on Clinical Function in Pediatric Patients With Thoracolumbar Spinal Cord Injury.

The alternation of brain white matter (WM) network has been studied in adult spinal cord injury (SCI) patients. However, the WM network alterations in pediatric SCI patients remain unclear. To evaluate WM network changes and their functional impact in children with thoracolumbar SCI (TSCI). Prospective. Thirty-five pediatric patients with TSCI (8.94 ± 1.86 years, 8/27 males/females) and 34 age- and gender-matched healthy controls (HCs) participated in this study. 3.0 T/DTI imaging using spin-echo echo-planar and T1-weighted imaging using 3D T1-weighted magnetization-prepared rapid gradient-echo sequence. Pediatric SCI patients were evaluated for motor and sensory scores, injury level, time since injury, and age at injury. The WM network was constructed using a continuous tracing method, resulting in a 90 × 90 matrix. The global and regional metrics were obtained to investigate the alterations of the WM structural network. topology. Two-sample independent t-tests, chi-squared test, Mann-Whitney U-test, and Spearman correlation. Statistical significance was set at P < 0.05. Compared with HCs, pediatric TSCI patients displayed decreased shortest path length (Lp = 1.080 ± 0.130) and normalized Lp (λ = 5.020 ± 0.363), and increased global efficiency (Eg = 0.200 ± 0.015). Notably, these patients also demonstrated heightened regional properties in the orbitofrontal cortex, limbic system, default mode network, and several audio-visual-related regions. Moreover, the λ and Lp values negatively correlated with sensory scores. Conversely, nodal efficiency values in the right calcarine fissure and surrounding cortex positively correlated with sensory scores. The age at injury positively correlated with node degree in the left parahippocampal gyrus and nodal efficiency in the right posterior cingulate gyrus. Reorganization of the WM networks in pediatric SCI patients is indicated by increased global and nodal efficiency, which may provide promising neuroimaging biomarkers for functional assessment of pediatric SCI. 2 TECHNICAL EFFICACY: Stage 5.

White matter fiber integrity and structural brain network topology: implications for balance function in postischemic stroke patients.

Previous studies have suggested that ischemic stroke can result in white matter fiber injury and modifications in the structural brain network. However, the relationship with balance function scores remains insufficiently explored. Therefore, this study aims to explore the alterations in the microstructural properties of brain white matter and the topological characteristics of the structural brain network in postischemic stroke patients and their potential correlations with balance function. We enrolled 21 postischemic stroke patients and 21 age, sex, and education-matched healthy controls (HC). All participants underwent balance function assessment and brain diffusion tensor imaging. Tract-based spatial statistics (TBSS) were used to compare the fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity of white matter fibers between the two groups. The white matter structural brain network was constructed based on the automated anatomical labeling atlas, and we conducted a graph theory-based analysis of its topological properties, including global network properties and local node properties. Additionally, the correlation between the significant structural differences and balance function score was analyzed. The TBSS results showed that in comparison to the HC, postischemic stroke patients exhibited extensive damage to their whole-brain white matter fiber tracts (P < 0.05). Graph theory analysis showed that in comparison to the HC, postischemic stroke patients exhibited statistically significant reductions in the values of global efficiency, local efficiency, and clustering coefficient, as well as an increase in characteristic path length (P < 0.05). In addition, the degree centrality and nodal efficiency of some nodes in postischemic stroke patients were significantly reduced (P < 0.05). The white matter fibers of the entire brain in postischemic stroke patients are extensively damaged, and the topological properties of the structural brain network are altered, which are closely related to balance function. This study is helpful in further understanding the neural mechanism of balance function after ischemic stroke from the white matter fiber and structural brain network topological properties.

1 Network Efficiency as Structural Reserve: Pre- And Post-Operative Associations Between Network Organization and Memory in Temporal Lobe Epilepsy

Objective:Memory impairment is a common comorbidity in individuals with temporal lobe epilepsy (TLE). Further, in medication-resistant epilepsy the frontline option, neurosurgical epileptogenic zone destruction, places memory at significant risk. Research has highlighted that TLE causes whole-brain network efficiency disruption, but it is not established how this may explain pre- and post-surgical cognition. Here we examine whether white matter structural network organization predicts pre-operative memory function and/or risk for post-operative memory decline.Participants and Methods:Patients with drug-resistant TLE were recruited from two epilepsy centers in a prospective longitudinal study. The pre-operative sample included 51 individuals with left TLE (L-TLE), 52 with right TLE (R-TLE), and 57 healthy controls who underwent T1- and diffusion-weighted MRI (dMRI), and neuropsychological tests of verbal and visual memory. Forty-four patients (n=21 L-TLE) subsequently underwent temporal lobe surgery (36 anterior temporal lobectomy; 7 stereotactic laser amygdalohippocampectomy; 1 amygdalohippocampectomy) and completed post-operative memory testing. Whole-brain connectomes were generated via diffusion tractography and analyzed using graph theory, focusing on network integration (path length) and specialization (transitivity). In the preoperative dataset, first we compared TLE versus controls with analysis of covariance (ANCOVAs) controlling for age. Next, linear regressions examined the association between memory scores and network efficiency between L-TLE, R-TLE and controls. In the post-operative sample, bivariate correlations examined the association between pre- to post-operative memory change and 1) global network efficiency and 2) asymmetry of mesial temporal efficiency (i.e., local efficiency of the hippocampal, parahippocampal, and entorhinal nodes). Finally, efficiency metrics were entered into stepwise regressions along with established predictors of memory decline.Results:Compared to controls, TLE showed longer path length (p &lt; .05; ηp2 = .03) and lower transitivity (p = .01; ηp2 = .04). Pre-operatively, better verbal learning and memory were associated with both shorter path length (β = -0.23 to -0.32; psadjusted &lt; .05) and increased transitivity (β = 0.20 to 0.31; psadjusted &lt; .05). These associations were greater in L-TLE than R-TLE (i.e., a significant interaction; β = -0.29 to 0.25; psadjusted &lt;.05). Post-operatively, global metrics predicted decline on list learning for LTLEs (rs = -.57 to .58; ps &lt; .01), and were marginal on list recall (rs = -.42 to .40; ps &lt; .10). Leftward asymmetry of mesial temporal local efficiency predicted greater decline across most verbal memory measures for L-TLE (rs -.47 to -59; psadjusted &lt;.05), but not R-TLE. Asymmetry of mesial network efficiency uniquely explained at least 20 to 43% of the variance in list learning, recall, and story learning for L-TLE, outperforming hippocampal asymmetry and preoperative score (psadjusted &lt;.05).Conclusions:Our findings suggest that global white matter network abnormalities contribute to verbal memory impairment pre-operatively and vulnerability to decline post-operatively in L-TLE. Asymmetry of a predefined mesial temporal sub-network may help predict post-operative memory function following left temporal lobe surgery, such that greater efficiency in the to-beresected mesial temporal network may be an important risk factor for decline. Our findings extend the importance of network approaches in TLE to include the relationships between neurobiological networks and memory function.

Diffusion kurtosis imaging tractography reveals disrupted white matter structural networks in children with obstructive sleep apnea syndrome.

To assess the disruptions of brain white matter (WM) structural network in children with obstructive sleep apnea (OSA) using diffusion kurtosis imaging (DKI). We use DKI tractography to construct individual whole-brain, region-level WM networks in 40 OSA and 28 healthy children. Then, we apply graph theory approaches to analyze whether OSA children would show altered global and regional network topological properties and whether these alterations would significantly correlate with the clinical characteristics of OSA. We found that both OSA and healthy children showed an efficient small-world organization and highly similar hub distributions in WM networks. However, characterized by kurtosis fractional anisotropy (KFA) weighted networks, OSA children exhibited decreased global and local efficiency, increased shortest path length compared with healthy children. For regional topology, OSA children exhibited significant decreased nodal betweenness centrality (BC) in the bilateral medial orbital superior frontal gyrus (ORBsupmed), right orbital part superior frontal gyrus (ORBsup), insula, postcentral gyrus, left middle temporal gyrus (MTG), and increased nodal BC in the superior parietal gyrus, pallidum. Intriguingly, the altered nodal BC of multiple regions (right ORBsupmed, ORBsup and left MTG) within default mode network showed significant correlations with sleep parameters for OSA patients. Our results suggest that children with OSA showed decreased global integration and local specialization in WM networks, typically characterized by DKI tractography and KFA metric. This study may advance our current understanding of the pathophysiological mechanisms of impaired cognition underlying OSA.

Topological alterations in white matter structural networks in fibromyalgia.

Neuroimaging studies employing analyses dependent on regional assumptions and specific neuronal circuits could miss characteristics of whole-brain structural connectivity critical to the pathophysiology of fibromyalgia (FM). This study applied the whole-brain graph-theoretical approach to identify whole-brain structural connectivity disturbances in FM. This cross-sectional study used probabilistic diffusion tractography and graph theory analysis to evaluate the topological organization of brain white matter networks in 20 patients with FM and 20 healthy controls (HCs). The relationship between brain network metrics and clinical variables was evaluated. Compared with HCs, FM patients had lower clustering coefficient, local efficiency, hierarchy, synchronization, and higher normalized characteristic path length. Regionally, patients demonstrated a significant reduction in nodal efficiency and centrality; these regions were mainly located in the prefrontal, temporal cortex, and basal ganglia. The network-based statistical analysis (NBS) identified decreased structural connectivity in a subnetwork of prefrontal cortex, basal ganglia, and thalamus in FM. There was no correlation between network metrics and clinical variables (false discovery rate corrected). The current research demonstrated disrupted topological architecture of white matter networks in FM. Our results suggested compromised neural integration and segregation and reduced structural connectivity in FM.

Disrupted white matter structural networks in individuals with alcohol dependence

Previous diffusion tensor imaging (DTI) studies have demonstrated widespread white matter microstructure damage in individuals with alcoholism. However, very little is known about the alterations in the topological architecture of white matter structural networks in alcohol dependence (AD). This study included 67 AD patients and 69 controls. The graph theoretical analysis method was applied to examine the topological organization of the white matter structural networks, and network-based statistics (NBS) were employed to detect structural connectivity alterations. Compared to controls, AD patients exhibited abnormal global network properties characterized by increased small-worldness, normalized clustering coefficient, clustering coefficient, and shortest path length; and decreased global efficiency and local efficiency. Further analyses revealed decreased nodal efficiency and degree centrality in AD patients mainly located in the default mode network (DMN), including the precuneus, anterior cingulate and paracingulate gyrus, median cingulate and paracingulate gyrus, posterior cingulate gyrus, and medial part of the superior frontal gyrus. Furthermore, based on NBS approaches, patients displayed weaker subnetwork connectivity mainly located in the region of the DMN. Additionally, altered network metrics were correlated with intelligence quotient (IQ) scores and global assessment function (GAF) scores. Our results may reveal the disruption of whole-brain white matter structural networks in AD individuals, which may contribute to our comprehension of the underlying pathophysiological mechanisms of alcohol addiction at the level of white matter structural networks.

Altered White Matter Structural Network Connectivity Associated with Cognitive Declines in Psychogenic Erectile Dysfunction.

It has been reported that individuals with psychogenic erectile dysfunction (pED) potentially suffer from cognitive declines. Despite that increasing neuroimaging studies have demonstrated abnormalities of cerebral structural changes in pED, the association between altered white matter (WM) structural network and cognitive impairments remains unclear. Hence, this study aimed to explore the relationship between WM structural network connectivity and cognitive performance in patients with pED. Forty pED patients and 33 healthy controls (HCs) were recruited to perform cognitive assessments, and diffusion tensor imaging scans. We firstly constructed the WM structural network and applied the machine learning method to identify the important features. Then, we examined group differences in cognitive assessments, WM structural network connectivity within the identified features, and associations between altered WM structural network connectivity and cognitive scores in pED patients. From 26,896 features of DTI data, 24 important features were identified by K-Nearest Neighbor classification with a satisfactory accuracy (78%). Compared with HCs, we found that pED patients showed higher fractional anisotropy (FA) values between left transverse temporal sulcus and left supramarginal gyrus, and lower FA values between left suborbital sulcus and left para-hippocampal part of the medial occipito-temporal gyrus in pED patients. Furthermore, the increased FA between left transverse temporal sulcus and left supramarginal gyrus was observed to be negatively associated with impaired delayed memory. Overall, our findings provide new insights into WM network alterations associated with impaired cognitive functions in pED, which may unravel the potential neural mechanisms underlying the cognitive impairments of pED patients.

Structural connectome combining DTI features predicts postoperative language decline and its recovery in glioma patients.

A decline in language function is a common complication after glioma surgery, affecting patients' quality of life and survival. This study predicts the postoperative decline in language function and whether it can be recovered based on the preoperative white matter structural network. Eighty-one right-handed patients with glioma involving the left hemisphere were retrospectively included. Their language function was assessed using the Western Aphasia Battery before and 1 week and 3 months after surgery. Structural connectome combining DTI features was selected to predict postoperative language decline and recovery. Nested cross-validation was used to optimize the models, evaluate the prediction performance of the models, and identify the most predictive features. Five, seven, and seven features were finally selected as the predictive features in each model and used to establish predictive models for postoperative language decline (1 week after surgery), long-term language decline (3 months after surgery), and language recovery, respectively. The overall accuracy of the three models in nested cross-validation and overall area under the receiver operating characteristic curve were 0.840, 0.790, and 0.867, and 0.841, 0.778, and 0.901, respectively. We used machine learning algorithms to establish models to predict whether the language function of glioma patients will decline after surgery and whether postoperative language deficit can recover, which may help improve the development of treatment strategies. The difference in features in the non-language decline or the language recovery group may reflect the structural basis for the protection and compensation of language function in gliomas. Models can predict the postoperative language decline and whether it can recover in glioma patients, possibly improving the development of treatment strategies. The difference in selected features may reflect the structural basis for the protection and compensation of language function. • Structural connectome combining diffusion tensor imaging features predicted glioma patients' language decline after surgery. • Structural connectome combining diffusion tensor imaging features predicted language recovery of glioma patients with postoperative language disorder. • Diffusion tensor imaging and connectome features related to language function changes imply plastic brain regions and connections.

Abnormal white matter structural network topological property in patients with temporal lobe epilepsy.

Diffusion tensor imaging (DTI) studies have demonstrated white matter (WM) abnormalities in patients with temporal lobe epilepsy (TLE). However, alterations in the topological properties of the WM structural network in patients with TLE remain unclear. Graph theoretical analysis provides a new perspective for evaluating the connectivity of WM structural networks. DTI was used to map the structural networks of 18 patients with TLE (10 males and 8 females) and 29 (17 males and 12 females) age- and gender-matched normal controls (NC). Graph theory was used to analyze the whole-brain networks and their topological properties between the two groups. Finally, partial correlation analyses were performed on the weighted network properties and clinical characteristics, namely, duration of epilepsy, verbal intelligence quotient (IQ), and performance IQ. Patients with TLE exhibited reduced global efficiency and increased characteristic path length. A total of 31 regions with nodal efficiency alterations were detected in the fractional anisotropy_ weighted network of the patients. Communication hubs, such as the middle temporal gyrus, right inferior temporal gyrus, left calcarine, and right superior parietal gyrus, were also differently distributed in the patients compared with the NC. Several node regions showed close relationships with duration of epilepsy, verbal IQ, and performance IQ. Our results demonstrate the disruption of the WM structural network in TLE patients. This study may contribute to the further understanding of the pathological mechanism of TLE.

Default Mode Network Hypoalignment of Function to Structure Correlates With Depression and Rumination

BackgroundRecent studies have begun to examine how signals in the brain correspond to the underlying white matter structure using tools from the field of graph signal processing to quantify brain function alignment to brain network topology. Here, we applied this framework for the first time toward a transdiagnostic cohort of individuals with internalizing psychopathologies, including mood and anxiety disorders, to uncover how such alignment within the default mode network (DMN) is related to depression and rumination symptoms. MethodsBoth diffusion-weighted and resting-state functional magnetic resonance imaging were obtained from participants at baseline (n = 60 patients, n = 19 healthy control participants). Patients were randomized to 12 weeks of treatment with either a selective serotonin reuptake inhibitor or cognitive behavioral therapy, and symptom scales were readministered posttreatment (n = 46 patients at follow-up). Using graph signal processing methodology, we quantified the alignment of functional signals to their underlying white matter structural networks. ResultsWe found that signal alignment within the posterior DMN was decreased in patients with internalizing psychopathologies compared with healthy control participants and was inversely (negatively) correlated with baseline depression and rumination scales. Signal alignment within the posterior DMN was also correlated with the ratio of total within-DMN to extra-DMN functional connectivity for these regions. ConclusionsThese findings are consistent with previous literature regarding pathological promiscuity of posterior DMN connectivity and provide the first graph signal processing–based analyses in a transdiagnostic cohort of patients with internalizing psychopathologies.

Disrupted topological organization of white matter structural networks in high myopia patients revealed by diffusion kurtosis imaging and tractography.

High myopia (HM) is a public health issue that can lead to severe visual impairment. Previous studies have exhibited widespread white matter (WM) integrity damage in HM patients. However, how these WM damages are topologically related, and the network-level structural disruptions underlying HM has not been fully defined. We aimed to assess the alterations of brain WM structural networks in HM patients using diffusion kurtosis imaging (DKI) and tractography in the present study. Individual whole-brain and ROI-level WM networks were constructed using DKI tractography in 30 HM patients and 33 healthy controls. Graph theory analysis was then applied to explore the altered global and regional network topological properties. Pearson correlations between regional properties and disease duration in the HM group were also assessed. For global topology, although both groups showed a small-world network organization, HM patients exhibited significant decreased local efficiency and clustering coefficient compared with controls. For regional topology, HM patients and controls showed highly similar hub distributions, except for three additional hub regions in HM patients including left insula, anterior cingulate and paracingulate gyri (ACG), and median cingulate and paracingulate gyri (DCG). In addition, HM patients showed significantly altered nodal betweenness centrality (BC) mainly in the bilateral inferior occipital gyrus (IOG), left superior occipital gyrus (SOG), caudate nucleus, rolandic operculum and right putamen, pallidum, and gyrus rectus compared with controls. Intriguingly, the nodal BC of left IOG was negatively correlated with disease duration in HM patients. Our findings suggest that HM exhibited alterations in WM structural networks as indicated by decreased local specialization. This study may advance the current understanding of the pathophysiological mechanisms underlying HM.

Aberrant topology of white matter networks in patients with methamphetamine dependence and its application in support vector machine-based classification

Brain white matter (WM) networks have been widely studied in neuropsychiatric disorders. However, few studies have evaluated alterations in WM network topological organization in patients with methamphetamine (MA) dependence. Therefore, using machine learning classification methods to analyze WM network topological attributes may give new insights into patients with MA dependence. In the study, diffusion tensor imaging-based probabilistic tractography was used to map the weighted WM networks in 46 MA-dependent patients and 46 control subjects. Using graph-theoretical analyses, the global and regional topological attributes of WM networks for both groups were calculated and compared to determine inter-group differences using a permutation-based general linear model. In addition, the study used a support vector machine (SVM) learning approach to construct a classifier for discriminating subjects with MA dependence from control subjects. Relative to the control group, the MA-dependent group exhibited abnormal topological organization, as evidenced by decreased small-worldness and modularity, and increased nodal efficiency in the right medial superior temporal gyrus, right pallidum, and right ventromedial putamen; the MA-dependent group had the higher hubness scores in 25 regions, which were mainly located in the default mode network. An SVM trained with topological attributes achieved classification accuracy, sensitivity, specificity, and kappa values of 98.09% ± 2.59%, 98.24% ± 4.00%, 97.94% ± 4.26%, and 96.18% ± 5.19% for patients with MA dependence. Our results may suggest altered global WM structural networks in MA-dependent patients. Furthermore, the abnormal WM network topological attributes may provide promising features for the construction of high-efficacy classification models.

Alterations in white matter integrity and network topological properties are associated with a decrease in global motion perception in older adults.

Previous studies have mainly explored the effects of structural and functional aging of cortical regions on global motion sensitivity in older adults, but none have explored the structural white matter (WM) substrates underlying the age-related decrease in global motion perception (GMP). In this study, random dot kinematogram and diffusion tensor imaging were used to investigate the effects of age-related reductions in WM fiber integrity and connectivity across various regions on GMP. We recruited 106 younger adults and 94 older adults and utilized both tract-based spatial statistics analysis and graph theoretical analysis to comprehensively investigate group differences in WM microstructural and network connections between older and younger adults at the microscopic and macroscopic levels. Moreover, partial correlation analysis was used to explore the relationship between alterations in WM and the age-related decrease in GMP. The results showed that decreased GMP in older adults was related to decreased fractional anisotropy (FA) of the inferior frontal-occipital fasciculus, inferior longitudinal fasciculus, anterior thalamic radiation, superior longitudinal fasciculus, and cingulum cingulate gyrus. Decreased global efficiency of the WM structural network and increased characteristic path length were closely associated with decreased global motion sensitivity. These results suggest that the reduced GMP in older adults may stem from reduced WM integrity in specific regions of WM fiber tracts as well as decreased efficiency of information integration and communication between distant cortical regions, supporting the "disconnection hypothesis" of cognitive aging.