Abnormal Structural Connectivity Research Articles

Exploring functional and structural connectivity disruptions in spinocerebellar ataxia type 3: Insights from gradient analysis.

Spinocerebellar Ataxia Type 3 (SCA3) is a rare genetic ataxia that impacts the entire brain and is characterized as a neurodegenerative disorder affecting the neural network. This study explores how alterations in the functional hierarchy, connectivity, and structural changes within specific brain regions significantly contribute to the heterogeneity of symptom manifestations in patients with SCA3. We prospectively recruited 51 patients with SCA3 and 59 age-and sex-matched healthy controls. All participants underwent comprehensive multimodal neuroimaging and clinical assessments. In SCA3 patients, an innovative approach utilizing gradients in resting-state functional connectivity (FC) was employed to examine atypical patterns of hierarchical processing topology from sensorimotor to supramodal regions in the cerebellum and cerebrum. Coupling analyses of abnormal FC and structural connectivity among regions of interest (ROIs) in the brain were also performed to characterize connectivity alterations. Additionally, relationships between quantitative ROI values and clinical variables were explored. Patients with SCA3 exhibited either compression or expansion within the primary sensorimotor-to-supramodal gradient through four distinct calculation methods, along with disruptions in FC and structural connectivity coupling. A comprehensive correlation was identified between the altered gradients and the clinical manifestations observed in patients. Notably, altered fractional anisotropy values were not significantly correlated with clinical variables. Abnormal gradients and connectivity in the cerebellar and cerebral cortices in SCA3 patients may contribute to disrupted motor-to-supramodal functions. Moreover, these findings support the potential utility of FCG analysis as a biomarker for diagnosing SCA3 and assessing treatment efficacy.

Altered morphometric similarity networks in insomnia disorder.

Previous studies on structural covariance network (SCN) suggested that patients with insomnia disorder (ID) show abnormal structural connectivity, primarily affecting the somatomotor network (SMN) and default mode network (DMN). However, evaluating a single structural index in SCN can only reveal direct covariance relationship between two brain regions, failing to uncover synergistic changes in multiple structural features. To cover this research gap, the present study utilized novel morphometric similarity networks (MSN) to examine the morphometric similarity between cortical areas in terms of multiple sMRI parameters measured at each area. With seven T1-weighted imaging morphometric features from the Desikan-Killiany atlas, individual MSN was constructed for patients with ID (N = 87) and healthy control groups (HCs, N = 84). Two-sample t-test revealed differences in MSN between patients with ID and HCs. Correlation analyses examined associations between MSNs and sleep quality, insomnia symptom severity, and depressive symptoms severity in patients with ID. The right paracentral lobule (PCL) exhibited decreased morphometric similarity in patients with ID compared to HCs, mainly manifested by its de-differentiation (meaning loss of distinctiveness) with the SMN, DMN, and ventral attention network (VAN), as well as its decoupling with the visual network (VN). Greater PCL-based de-differentiation correlated with less severe insomnia and fewer depressive symptoms in the patients group. Additionally, patients with less depressive symptoms showed greater PCL de-differentiation from the SMN. As an important pilot step in revealing the underlying morphometric similarity alterations in insomnia disorder, the present study identified the right PCL as a hub region that is de-differentiated with other high-order networks. Our study also revealed that MSN has an important potential to capture clinical significance related to insomnia disorder.

Limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is associated with abnormalities in white matter structural integrity and connectivity: An ex-vivo diffusion MRI and pathology investigation

Limbic predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) is common in older adults and is associated with neurodegeneration, cognitive decline and dementia. In this MRI and pathology investigation we tested the hypothesis that LATE-NC is associated with abnormalities in white matter structural integrity and connectivity of a network of brain regions typically harboring TDP-43 inclusions in LATE, referred to here as the “LATE-NC network”. Ex-vivo diffusion MRI and detailed neuropathological data were collected on 184 community-based older adults. Linear regression revealed an independent association of higher LATE-NC stage with lower diffusion anisotropy in a set of white matter connections forming a pattern of connectivity that is consistent with the stereotypical spread of this pathology in the brain. Graph theory analysis revealed an association of higher LATE-NC stage with weaker integration and segregation in the LATE-NC network. Abnormalities were significant in stage 3, suggesting that they are detectable in later stages of the disease. Finally, LATE-NC network abnormalities were associated with faster cognitive decline, specifically in episodic and semantic memory.

Alterations of the cerebral microstructure in patients with noise-induced hearing loss: A diffusion tensor imaging study.

To explore the changes in the cerebral microstructure of patients with noise-induced hearing loss (NIHL) using diffusion tensor imaging (DTI). Overall, 122 patients with NIHL (mild [MP, n=79], relatively severe patients [including moderate and severe; RSP, n=32], and undetermined [lost to follow-up, n=11]) and 84 healthy controls (HCs) were enrolled. All clinical data, including age, education level, hearing threshold, occupation type, noise exposure time, and some scale scores (including the Mini-Mental State Examination [MMSE], tinnitus handicap inventory [THI], and Hamilton Anxiety Scale [HAMA]), were collected and analyzed. All participants underwent T1WI3DFSPGR and DTI, and tract-based spatial statistics and region of interest (ROI) analysis were used for assessment. The final sample included 71 MP, 28 RSP, and 75 HCs. The HAMA scores of the three groups were significantly different (p<.05). The noise exposure times, hearing thresholds, and HAMA scores of the MP and RSP were significantly different (p<.05). The noise exposure time was positively correlated with the hearing threshold and negatively correlated with the HAMA scores (p<.05), whereas the THI scores were positively correlated with the hearing threshold (p<.05). DTI analysis showed that all DTI parameters (fractional anisotropy [FA], axial diffusivity [AD], mean diffusivity [MD], and radial diffusivity [RD]) were significantly different in the left inferior longitudinal fasciculus (ILF) and left inferior fronto-occipital fasciculus (IFOF) for the three groups (p<.05). In addition, the FA values were significantly lower in the bilateral corticospinal tract (CST), right fronto-pontine tract (FPT), right forceps major, left superior longitudinal fasciculus (temporal part) (SLF), and left cingulum (hippocampus) (C-H) of the MP and RSP than in those of the HCs (p<.05); the AD values showed diverse changes in the bilateral CST, left IFOF, right anterior thalamic radiation, right external capsule (EC), right SLF, and right superior cerebellar peduncle (SCP) of the MP and RSP relative to those of the HC (p<.05). However, there were no significant differences among the bilateral auditory cortex ROIs of the three groups (p>.05). There was a significant negative correlation between the FA and HAMA scores for the left IFOF/ILF, right FPT, left SLF, and left C-H for the three groups (p<.05). There was a significant positive correlation between the AD and HAMA scores for the left IFOF/ILF and right EC of the three groups (p<.05). There were significantly positive correlations between the RD/MD and HAMA scores in the left IFOF/ILF of the three groups (p<.05). There was a significant negative correlation between the AD in the right SCP and noise exposure time of the MP and RSP groups (p<.05). The AD, MD, and RD in the left ROI were significantly positively correlated with hearing threshold in the MP and RSP groups (p<.05), whereas FA in the right ROI was significantly positively correlated with the HAMA scores for the three groups (p<.05). The changes in the white matter (WM) microstructure may be related to hearing loss caused by noise exposure, and the WM structural abnormalities in patients with NIHL were mainly located in the syndesmotic fibers of the temporooccipital region, which affected the auditory and language pathways. This confirmed that the auditory pathways have abnormal structural connectivity in patients with NIHL.

Structural and functional connectivity of the whole brain and subnetworks in individuals with mild traumatic brain injury: predictors of patient prognosis.

Abstract JOURNAL/nrgr/04.03/01300535-202407000-00035/figure1/v/2023-11-20T171125Z/r/image-tiff Patients with mild traumatic brain injury have a diverse clinical presentation, and the underlying pathophysiology remains poorly understood. Magnetic resonance imaging is a non-invasive technique that has been widely utilized to investigate neurobiological markers after mild traumatic brain injury. This approach has emerged as a promising tool for investigating the pathogenesis of mild traumatic brain injury. Graph theory is a quantitative method of analyzing complex networks that has been widely used to study changes in brain structure and function. However, most previous mild traumatic brain injury studies using graph theory have focused on specific populations, with limited exploration of simultaneous abnormalities in structural and functional connectivity. Given that mild traumatic brain injury is the most common type of traumatic brain injury encountered in clinical practice, further investigation of the patient characteristics and evolution of structural and functional connectivity is critical. In the present study, we explored whether abnormal structural and functional connectivity in the acute phase could serve as indicators of longitudinal changes in imaging data and cognitive function in patients with mild traumatic brain injury. In this longitudinal study, we enrolled 46 patients with mild traumatic brain injury who were assessed within 2 weeks of injury, as well as 36 healthy controls. Resting-state functional magnetic resonance imaging and diffusion-weighted imaging data were acquired for graph theoretical network analysis. In the acute phase, patients with mild traumatic brain injury demonstrated reduced structural connectivity in the dorsal attention network. More than 3 months of follow-up data revealed signs of recovery in structural and functional connectivity, as well as cognitive function, in 22 out of the 46 patients. Furthermore, better cognitive function was associated with more efficient networks. Finally, our data indicated that small-worldness in the acute stage could serve as a predictor of longitudinal changes in connectivity in patients with mild traumatic brain injury. These findings highlight the importance of integrating structural and functional connectivity in understanding the occurrence and evolution of mild traumatic brain injury. Additionally, exploratory analysis based on subnetworks could serve a predictive function in the prognosis of patients with mild traumatic brain injury.

Complementary structural and functional abnormalities to localise epileptogenic tissue

When investigating suitability for epilepsy surgery, people with drug-refractory focal epilepsy may have intracranial EEG (iEEG) electrodes implanted to localise seizure onset. Diffusion-weighted magnetic resonance imaging (dMRI) may be acquired to identify key white matter tracts for surgical avoidance. Here, we investigate whether structural connectivity abnormalities, inferred from dMRI, may be used in conjunction with functional iEEG abnormalities to aid localisation of the epileptogenic zone (EZ), improving surgical outcomes in epilepsy. We retrospectively investigated data from 43 patients (42% female) with epilepsy who had surgery following iEEG. Twenty-five patients (58%) were free from disabling seizures (ILAE 1 or 2) at one year. Interictal iEEG functional, and dMRI structural connectivity abnormalities were quantified by comparison to a normative map and healthy controls. We explored whether the resection of maximal abnormalities related to improved surgical outcomes, in both modalities individually and concurrently. Additionally, we suggest how connectivity abnormalities may inform the placement of iEEG electrodes pre-surgically using a patient case study. Seizure freedom was 15 times more likely in patients with resection of maximal connectivity and iEEG abnormalities (p=0.008). Both modalities separately distinguished patient surgical outcome groups and when used simultaneously, a decision tree correctly separated 36 of 43 (84%) patients. Our results suggest that both connectivity and iEEG abnormalities may localise epileptogenic tissue, and that these two modalities may provide complementary information in pre-surgical evaluations. This research was funded by UKRI, CDT in Cloud Computing for Big Data, NIH, MRC, Wellcome Trust and Epilepsy Research UK.

Study of structural network connectivity using DTI tractography in insomnia disorder

Most of tractography studies on insomnia disorder (ID) have reported decreased structural connectivity between cortical and subcortical structures. Tractography based on standard diffusion tensor imaging (DTI) can generate high number of false-positive streamlines connections between gray matter regions. In the present study, we employed the convex optimization modeling for microstructure informed tractography-2 (COMMIT2) to improve the accuracy of the reconstructed whole-brain connectome and filter implausible brain connections in 28 patients with ID and compared with 27 healthy controls. Then, we used NBS-predict (a prediction-based extension to the network-based statistic method) in the COMMIT2-weighted connectome. Our results revealed decreased structural connectivity between subregions of the left somatomotor, ventral attention, frontoparietal, dorsal attention and default mode networks in the insomnia group. Moreover, there is a negative correlation between sleep efficiency and structural connectivity within the left frontoparietal, visual, default mode network, limbic, dorsal attention, right dorsal attention as well as right default mode networks. By comparing with standard connectivity analysis, we showed that by removing of false-positive streamlines connections after COMMIT2 filtering, abnormal structural connectivity was reduced in patients with ID compared to controls. Our results demonstrate the importance of improving the accuracy of tractography for understanding structural connectivity networks in ID.

Abstract TMP63: Structural Network Changes In Children With Moyamoya Disease Prior To Surgical Intervention

Purpose: Moyamoya disease/syndrome (MMD) is a progressive steno-occlusive disease involving the intracranial arterial circulation. Long term stenosis/hypoperfusion can lead to intellectual disability and cognitive impairment even in the absence of documented infarct. We aim investigate any underlying network abnormalities in MMD patients with no apparent ischemic injury. Materials and Methods: We retrospectively reviewed children with MMD with normal appearing parenchyma on conventional MRI. Control patients were selected from our existing database. Clinical, surgical and demographic data, including degree of stenosis as measured semi-quantitatively on MRA, were collected. Patients with documented infarcts, low quality DTI, and NF1 were excluded from the analysis. Group and correlational connectometry with degree of stenosis were performed. Results: A total of 28 patients were reviewed with 16 patients included in the study. Median (and interquartile range) age was 10.5 (8.5 - 13.5). Between group connectometry analysis identified infratentorial and supratentorial decreased connectivity in patients compared to controls, specifically in: middle cerebellar peduncle, corpus callosum, right parietopontine tract, superior cerebellar peduncle, left inferior fronto-occipital fasciculus. (Figure 1) In addition, we found negative correlation between the degree of stenosis and structural connectivity of multiple white matter pathways. Conclusion: Our findings reveal abnormal structural connectivity in children with MMD in the absence of infarcts on conventional MRI. Connectomics offers a unique opportunity to study the effect of long-term stenosis/hypoperfusion on cerebellar-cerebral networks and provide new insights into the mechanism of the structural plasticity/reorganization in these patients before bypass surgery. Future research is needed to determine longitudinal network changes before and after surgery.

Progressive structural and covariance connectivity abnormalities in patients with Alzheimer's disease.

Alzheimer's disease (AD) is one of most prevalent neurodegenerative diseases worldwide and characterized by cognitive decline and brain structure atrophy. While studies have reported substantial grey matter atrophy related to progression of AD, it remains unclear about brain regions with progressive grey matter atrophy, covariance connectivity, and the associations with cognitive decline in AD patients. This study aims to investigate the grey matter atrophy, structural covariance connectivity abnormalities, and the correlations between grey matter atrophy and cognitive decline during AD progression. We analyzed neuroimaging data of healthy controls (HC, n = 45) and AD patients (n = 40) at baseline (AD-T1) and one-year follow-up (AD-T2) obtained from the Alzheimer's Disease Neuroimaging Initiative. We investigated AD-related progressive changes of grey matter volume, covariance connectivity, and the clinical relevance to further understand the pathological progression of AD. The results showed clear patterns of grey matter atrophy in inferior frontal gyrus, prefrontal cortex, lateral temporal gyrus, posterior cingulate cortex, insula, hippocampus, caudate, and thalamus in AD patients. There was significant atrophy in bilateral superior temporal gyrus (STG) and left caudate in AD patients over a one-year period, and the grey matter volume decrease in right STG and left caudate was correlated with cognitive decline. Additionally, we found reduced structural covariance connectivity between right STG and left caudate in AD patients. Using AD-related grey matter atrophy as features, there was high discrimination accuracy of AD patients from HC, and AD patients at different time points.

Progressive brain abnormalities in schizophrenia across different illness periods: a structural and functional MRI study

Schizophrenia is a chronic brain disorder, and neuroimaging abnormalities have been reported in different stages of the illness for decades. However, when and how these brain abnormalities occur and evolve remains undetermined. We hypothesized structural and functional brain abnormalities progress throughout the illness course at different rates in schizophrenia. A total of 115 patients with schizophrenia were recruited and stratified into three groups of different illness periods: 5-year group (illness duration: ≤5 years), 15-year group (illness duration: 12–18 years), and 25-year group (illness duration: ≥25 years); 230 healthy controls were matched by age and sex to the three groups, respectively. All participants underwent resting-state MRI scanning. Each group of patients with schizophrenia was compared with the corresponding controls in terms of voxel-based morphometry (VBM), fractional anisotropy (FA), global functional connectivity density (gFCD), and sample entropy (SampEn) abnormalities. In the 5-year group we observed only SampEn abnormalities in the putamen. In the 15-year group, we observed VBM abnormalities in the insula and cingulate gyrus and gFCD abnormalities in the temporal cortex. In the 25-year group, we observed FA abnormalities in nearly all white matter tracts, and additional VBM and gFCD abnormalities in the frontal cortex and cerebellum. By using two structural and two functional MRI analysis methods, we demonstrated that individual functional abnormalities occur in limited brain areas initially, functional connectivity and gray matter density abnormalities ensue later in wider brain areas, and structural connectivity abnormalities involving almost all white matter tracts emerge in the third decade of the course in schizophrenia.

An End-to-End Deep Learning Model for EEG-Based Major Depressive Disorder Classification

Major depressive disorder (MDD) is a prevalent mental illness associated with abnormalities in structural and functional brain connectivity, and it has become a global public health problem. Early diagnosis is important and challenging for the treatment of MDD. Previous studies proposed the classification methods for MDD based on brain connectivity features through functional connectivity (FC) or effective connectivity (EC) measures. However, it requires prior knowledge and experience to manually select a algorithm to calculate the brain connectivity features. Given that the representation learning capabilities of deep learning (DL) models and the ability to capture correlations between data of self-attention mechanism, we proposed an end-to-end integrated DL model for classifying MDD patients and healthy controls (HCs) based on resting-state electroencephalography (EEG) data. This model first automatically learned the potential connectivity relationships among EEG channels through a multi-head self-attention mechanism, and then extracted higher-level features through a parallel two-branch convolution neural network (CNN) module, and finally completed the classification through a fully connected layer. A public resting-state EEG dataset was utilized to evaluate the validity of the proposed model. The experimental results indicated that the proposed model achieved 91.06% average accuracy that was better than those of comparison methods using the leave-one-subject-out cross-validation (LOSOCV) method. This study may provide a novel approach for brain connectivity modeling of MDD detection.

Discovery of early schizophrenia through neuroimaging

In order to understand the pathophysiology of schizophrenia we carried out a number of brain imaging studies in both medicated and unmedicated patients. In addition, to help unravel the pathophysiological mechanisms without the confound of prior exposure to antipsychotic medication or chronicity, we enrolled a large group of antipsychotic medication-naïve first episode psychosis patients at first treatment contact, and performed longitudinal multimodal neuroimaging studies over several months.In unmedicated patients we found both functional and structural connectivity alterations. Similarly, in medication-naïve patients we replicated many of our prior findings, suggesting that functional and structural connectivity alterations are core pathological features of the illness. We found that a longer duration of untreated psychosis, i.e. the time between first symptom onset and initial treatment contact, was associated with greater structural and functional connectivity abnormalities, which in turn was associated with worse subsequent clinical response to treatment.These results underscore the critical importance of early identification and treatment in patients with psychosis spectrum disorders.

Altered topological organization of resting-state functional networks in children with infantile spasms.

Covering neuroimaging evidence has demonstrated that epileptic symptoms are associated with the disrupted topological architecture of the brain network. Infantile spasms (IS) as an age-specific epileptic encephalopathy also showed abnormal structural or functional connectivity in specific brain regions or specific networks. However, little is known about the topological alterations of whole-brain functional networks in patients with IS. To fill this gap, we used the graph theoretical analysis to investigate the topological properties (whole-brain small-world property and modular interaction) in 17 patients with IS and 34 age- and gender-matched healthy controls. The functional networks in both groups showed efficient small-world architecture over the sparsity range from 0.05 to 0.4. While patients with IS showed abnormal global properties characterized by significantly decreased normalized clustering coefficient, normalized path length, small-worldness, local efficiency, and significantly increased global efficiency, implying a shift toward a randomized network. Modular analysis revealed decreased intra-modular connectivity within the default mode network (DMN) and fronto-parietal network but increased inter-modular connectivity between the cingulo-opercular network and occipital network. Moreover, the decreased intra-modular connectivity in DMN was significantly negatively correlated with seizure frequency. The inter-modular connectivity between the cingulo-opercular and occipital network also showed a significant correlation with epilepsy frequency. Together, the current study revealed the disrupted topological organization of the whole-brain functional network, which greatly advances our understanding of neuronal architecture in IS and may contribute to predict the prognosis of IS as disease biomarkers.

Cell-type-specific genes associated with cortical structural abnormalities in pediatric bipolar disorder.

Pediatric bipolar disorder (PBD) has been proven to be related to abnormal brain structural connectivity, but how the abnormalities in PBD correlate with gene expression is debated. This study aims at identification of cell-type-specific gene modules based on cortical structural differences in PBD. Morphometric similarity networks (MSN) were computed as a marker of interareal cortical connectivity based on MRI data from 102 participants (59 patients and 43 controls). Partial least squares (PLS) regression was used to calculate MSN differences related to transcriptomic data in AHBA. The biological processes and cortical cell types associated with this gene expression profile were determined by gene enrichment tools. MSN analysis results demonstrated differences of cortical structure between individuals diagnosed with PBD and healthy control participants. MSN differences were spatially correlated with the PBD-related weighted genes. The weighted genes were enriched for "trans-synaptic signaling" and "regulation of ion transport", and showed significant specific expression in excitatory and inhibitory neurons. This study identified the genes that contributed to structural network aberrations in PBD. It was found that transcriptional changes of excitatory and inhibitory neurons might be associated with abnormal brain structural connectivity in PBD.

Structural and functional connectivity abnormalities of the default mode network in patients with Alzheimer's disease and mild cognitive impairment within two independent datasets.

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive dementia, and amnestic mild cognitive impairment (aMCI) has been defined as a transitional stage between normal aging and AD. Accumulating evidence has shown that altered functional connectivity (FC) and structural connectivity (SC) in the default mode network (DMN) is the prominent hallmarks of AD. However, the relationship between the changes in SC and FC of the DMN is not yet clear. In the present study, we derived the FC and SC matrices of the DMN with functional magnetic resonance imaging (fMRI) and diffusion-weighted imaging (DWI) data and further assessed FC and SC abnormalities within a discovery dataset of 120 participants (39 normal controls, 34 patients with aMCI and 47 patients with AD), as well as a replication dataset of 122 participants (43 normal controls, 37 patients with aMCI and 42 patients with AD). Disrupted SC and FC were found among DMN components (e.g., the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), and hippocampus) in patients in the aMCI and AD groups in the discovery dataset; most of the disrupted connections were also identified in the replication dataset. More importantly, some SC and FC elements were significantly correlated with the cognitive ability of patients with aMCI and AD. In addition, we found structural-functional decoupling between the PCC and the right hippocampus in patients in the aMCI and AD groups. These findings of the alteration of DMN connectivity in neurodegenerative cohorts deepen our understanding of the pathophysiological mechanisms of AD.

Pedunculopontine Nucleus Dysconnectivity Correlates With Gait Impairment in Parkinson's Disease: An Exploratory Study.

BackgroundGait impairment is a debilitating and progressive feature of Parkinson’s disease (PD). Increasing evidence suggests that gait control is partly mediated by cholinergic signaling from the pedunculopontine nucleus (PPN).ObjectiveWe investigated whether PPN structural connectivity correlated with quantitative gait measures in PD.MethodsTwenty PD patients and 15 controls underwent diffusion tensor imaging to quantify structural connectivity of the PPN. Whole brain analysis using tract-based spatial statistics and probabilistic tractography were performed using the PPN as a seed region of interest for cortical and subcortical target structures. Gait metrics were recorded in subjects’ medication ON and OFF states, and were used to determine if specific features of gait dysfunction in PD were related to PPN structural connectivity.ResultsTract-based spatial statistics revealed reduced structural connectivity involving the corpus callosum and right superior corona radiata, but did not correlate with gait measures. Abnormalities in PPN structural connectivity in PD were lateralized to the right hemisphere, with pathways involving the right caudate nucleus, amygdala, pre-supplementary motor area, and primary somatosensory cortex. Altered connectivity of the right PPN-caudate nucleus was associated with worsened cadence, stride time, and velocity while in the ON state; altered connectivity of the right PPN-amygdala was associated with reduced stride length in the OFF state.ConclusionOur exploratory analysis detects a potential correlation between gait dysfunction in PD and a characteristic pattern of connectivity deficits in the PPN network involving the right caudate nucleus and amygdala, which may be investigated in future larger studies.

Abnormal brain functional and structural connectivity between the left supplementary motor area and inferior frontal gyrus in moyamoya disease

BackgroundDisruption of brain functional connectivity has been detected after stroke, but whether it also occurs in moyamoya disease (MMD) is unknown. Impaired functional connectivity is always correlated with abnormal white matter fibers. Herein, we used multimodal imaging techniques to explore the changes in brain functional and structural connectivity in MMD patients.MethodsWe collected structural images, resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging for each subject. Cognitive functions of MMD patients were evaluated using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Trail Making Test parts A and B (TMT-A/-B). We calculated the functional connectivity for every paired region using 90 regions of interest from the Anatomical Automatic Labeling Atlas and then determined the differences between MMD patients and HCs. We extracted the functional connectivity of paired brain regions with significant differences between the two groups. Correlation analyses were then performed between the functional connectivity and variable cognitive functions. To explore whether the impaired functional connectivity and cognitive performances were attributed to the destruction of white matter fibers, we further analyzed fiber integrity using tractography between paired regions that were correlated with cognition.ResultsThere was lower functional connectivity in MMD patients as compared to HCs between the bilateral inferior frontal gyrus, between the bilateral supramarginal gyrus, between the left supplementary motor area (SMA) and the left orbital part of the inferior frontal gyrus (IFGorb), and between the left SMA and the left middle temporal gyrus (P < 0.01, FDR corrected). The decreased functional connectivity between the left SMA and the left IFGorb was significantly correlated with the MMSE (r = 0.52, P = 0.024), MoCA (r = 0.60, P = 0.006), and TMT-B (r = -0.54, P = 0.048) in MMD patients. White matter fibers were also injured between the SMA and IFGorb in the left hemisphere and were positively correlated with reduced functional connectivity.ConclusionsBrain functional and structural connectivity between the supplementary motor area and inferior frontal gyrus in the left hemisphere are damaged in MMD. These findings could be useful in the evaluation of disease progression and prognosis of MMD.

Strengthened and posterior-shifted structural rich-club organization in people who use cocaine

BackgroundPeople with cocaine use disorder (CUD) often have abnormal cognitive function and brain structure. Cognition is supported by brain networks that typically have characteristics like rich-club organization, which is a group of regions that are highly connected across the brain and to each other, and small worldness, which is a balance between local and long-distance connections. However, it is unknown whether there are abnormalities in structural brain network connectivity of CUD. MethodsUsing diffusion-weighted imaging, we measured structural connectivity in 37 people with CUD and 38 age-matched controls. We identified differences in rich-club organization and whether such differences related to small worldness and behavior. We also tested whether rich-club reorganization was associated with caudate and putamen structural connectivity due to the relevance of the dopamine system to cocaine use. ResultsPeople with CUD had a higher normalized rich-club coefficient than controls, more edges connecting rich-club nodes to each other and to non-rich-club nodes, and fewer edges connecting non-rich-club nodes. Rich-club nodes were shifted posterior and lateral. Rich-club reorganization was related to lower clustered connectivity around individual nodes found in CUD, to increased impulsivity, and to a decrease in caudate connectivity. ConclusionsThese findings are consistent with previous work showing increased rich-club connectivity in conditions associated with a hypofunctional dopamine system. The posterior shift in rich-club nodes in CUD suggests that the structural connectivity of posterior regions may be more impacted than previously recognized in models based on brain function and morphology.

Assessment of brain connectome alterations in male chronic smokers using structural and generalized q-sampling MRI.

An association has been shown between chronic cigarette smoking and structural abnormalities in the brain areas related to several functions relevant to addictive behavior. However, few studies have focused on the structural alternations of chronic smoking by using magnetic resonance imaging (MRI). Also, it remains unclear how structural alternations are associated with tobacco-dependence severity and the positive/negative outcome expectances. The q-sampling imaging (GQI) is an advanced diffusion MRI technique that can reconstruct more precise and consistent images of complex oriented fibers than other methods. We aimed to use GQI to evaluate the impact of the neurological structure caused by chronic smoking. Sixty-seven chronic smokers and 43 nonsmokers underwent a MRI scan. The tobacco dependence severity and the positive/negative outcome expectancies were assessed via self-report. We used GQI with voxel-based statistical analysis (VBA) to evaluate structural brain and connectivity abnormalities. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the structural network differences among groups. Chronic smokers had smaller GM and WM volumes in the bilateral frontal lobe and bilateral frontal region. The GM/WM volumes correlated with dependence severity and outcome expectancies in the brain areas involving high-level functions. Chronic smokers had shape changes in the left hippocampal head and tail and the inferior brain stem. Poorer WM integrity in chronic smokers was found in the left middle frontal region, the right superior fronto-occipital fasciculus, the right temporal region, the left parahippocampus, the left anterior internal capsule, and the right inferior parietal region. WM integrity correlated with dependence severity and outcome expectancies in brain areas involving high-level functions. Chronic smokers had decreased local segregation and global integration among the brain regions and networks. Our results provide further evidence indicating that chronic smoking may be associated with brain structure and connectivity changes.

Identifying Changes of Brain Regional Homogeneity and Cingulo-Opercular Network Connectivity in First-Episode, Drug-Naïve Depressive Patients With Suicidal Ideation.

ObjectiveAdult patients with major depressive disorder (MDD) may not actively reveal their suicidal ideation (SI). Therefore, this study is committed to finding the alterations in the cingulo-opercular network (CON) that are closely related to SI with multi-imaging methods, thus providing neuroimaging basis for SI.MethodA total of 198 participants (129 MDD patients and 69 healthy controls) were recruited and evaluated with the Montgomery–Asberg Depression Rating Scale (MADRS). The healthy individuals formed the HC group, while the MDD patients were subdivided into no SI MDD (NSI, n = 32), mild SI MDD (MSI, n = 64), and severe SI MDD (SSI, n = 33) according to their MADRS item 10. We obtained MRI data of all participants and applied regional homogeneity (ReHo) analysis to verify a previous finding that links CON abnormality to SI. In addition, we employed the structural covariance network (SCN) analysis to investigate the correlation between abnormal structural connectivity of CON and SI severity.ResultsCompared to those of the HC group, MDD ReHo values and gray matter volume (GMV) were consistently found abnormal in CON. ReHo values and GMV of the right orbital inferior frontal gyrus (ORBinf.R) in the MDD group decreased with the increase of SI. Compared to the HC group, the MDD patients showed enhanced structural connectivity of three pairs of brain regions in CON [ACC.L–left superior frontal gyrus (SFG.L), SFG.L–left middle temporal gyrus (MTG.L), and the SFG.L–left post-central gyrus (PoCG.L)]. Compared with that of the NSI and MSI groups, the structural connectivity of three pairs of brain regions in CON is enhanced in the SSI groups [ORBinf.L–right ventral posterior cingulate gyrus (VPCC.R), VPCC.R–SFG.R, and SFG.R–PoCG.R].ConclusionOur findings showed the distinctive ReHo, GMV, and SCN pattern of CON in MDD patients with SI; and with the severity of suicide, abnormal brain regions increased. Our finding suggested that MDD patients with different severity of SI have different neuroimaging changes.