Brain connectivity最新文献

{"title":"Hypermetabolic Cerebellar Connectome in Alzheimer's Disease.","authors":"Vinay Gupta, Samuel Booth, Ji Hyun Ko","doi":"10.1089/brain.2020.0937","DOIUrl":"10.1089/brain.2020.0937","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Regional hypermetabolism in Alzheimer's disease (AD), especially in the cerebellum, has been consistently observed but often neglected as an artefact produced by the commonly used proportional scaling procedure in the statistical parametric mapping. We hypothesize that the hypermetabolic regions are also important in disease pathology in AD. <b><i>Methods:</i></b> Using fluorodeoxyglucose (FDG)-positron emission tomography (PET) images from 88 AD subjects and 88 age-sex matched normal controls (NL) from the publicly available Alzheimer's Disease Neuroimaging Initiative database, we developed a general linear model-based classifier that differentiated AD patients from normal individuals (sensitivity = 87.50%, specificity = 82.95%). We constructed region-region group-wise correlation matrices and evaluated differences in network organization by using the graph theory analysis between AD and control subjects. <b><i>Results:</i></b> We confirmed that hypermetabolism found in AD is not an artefact by replicating it using white matter as the reference region. The role of the hypermetabolic regions has been further investigated by using the graph theory. The differences in betweenness centrality (BC) between AD and NL network were correlated with region weights of FDG PET-based AD classifier. In particular, the hypermetabolism in cerebellum was accompanied with higher BC. The brain regions with higher BC in AD network showed a progressive increase in FDG uptake over 2 years in prodromal AD patients (<i>n</i> = 39). <b><i>Discussion:</i></b> This study suggests that hypermetabolism found in AD may play an important role in forming the AD-related metabolic network. In particular, hypermetabolic cerebellar regions represent a good candidate for further investigation in altered network organization in AD.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 6","pages":"356-366"},"PeriodicalIF":2.4,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10494901/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10566181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Static and Dynamic Functional Connectivity Alterations in Alzheimer's Disease and Neuropsychiatric Diseases.","authors":"Teppei Matsui,&nbsp;Ken-Ichiro Yamashita","doi":"10.1089/brain.2022.0044","DOIUrl":"https://doi.org/10.1089/brain.2022.0044","url":null,"abstract":"<p><p><b><i>Background:</i></b> To date, numerous studies have documented various alterations in resting brain activity in Alzheimer's disease (AD) and other neuropsychiatric diseases. In particular, disease-related alterations of functional connectivity (FC) in the resting state networks (RSN) have been documented. Altered FC in RSN is useful not only for interpreting the phenotype of diseases but also for diagnosing the diseases. More recently, several studies proposed the dynamics of resting-brain activity as a useful marker for detecting altered RSNs related to AD and other diseases. <b><i>Objectives:</i></b> In this article, we review recent studies exploring alterations of static and dynamic functional connectivity in AD and other neuropsychiatric diseases. We then discuss how to utilize and interpret dynamics of FC for studying resting brain activity in diseases. <b><i>Results:</i></b> In contrast to previous studies, which focused on FC calculated using an entire fMRI scan (static FC), newer studies focused on the temporal dynamics of FC within the scan (dynamic FC) to provide more sensitive measures to characterize RSNs. However, despite the increasing popularity of dynamic FC, several statistical investigations of dynamic FC cautioned that the results obtained in commonly used analyses for dynamic FC require careful interpretation. <b><i>Conclusions:</i></b> Although static and dynamic FC are likely to be a useful tool to detect altered RSN in patients affected by AD and other neuropsychiatric disorders, interpretation of altered dynamic FC in patients require special care. Impact statement We review recent studies of static and dynamic functional connectivity (dFC) in Alzheimer's disease and discuss interpretation of dFC.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"307-314"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10019566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional Network Alterations Associated with Cognition in Pre-Clinical Alzheimer's Disease.","authors":"Stephanie Fountain-Zaragoza, Hesheng Liu, Andreana Benitez","doi":"10.1089/brain.2022.0032","DOIUrl":"10.1089/brain.2022.0032","url":null,"abstract":"<p><p><b><i>Objective:</i></b> Accumulation of cerebral amyloid-β (Aβ) is a risk factor for cognitive decline and defining feature of Alzheimer's disease (AD). Aβ is implicated in brain network disruption, but the extent to which these changes correspond with observable cognitive deficits in pre-clinical AD has not been tested. This study utilized individual-specific functional parcellations to sensitively evaluate the relationship between network connectivity and cognition in adults with and without Aβ deposition. <b><i>Participants and Methods:</i></b> Cognitively unimpaired adults ages 45-85 completed amyloid positron emission tomography, resting-state-functional magnetic resonance imaging (fMRI), and neuropsychological tests of episodic memory and executive function (EF). Participants in the upper tertile of mean standard uptake value ratio were considered Aβ+ (<i>n</i> = 50) while others were Aβ- (<i>n</i> = 99). Individualized functional network parcellations were generated from resting-state fMRI data. We examined the effects of group, network, and group-by-network interactions on memory and EF. <b><i>Results:</i></b> We observed several interactions such that within the Aβ+ group, preserved network integrity (i.e., greater connectivity <i>within</i> specific networks) was associated with better cognition, whereas network desegregation (i.e., greater connectivity <i>between</i> relative to <i>within</i> networks) was associated with worse cognition. This dissociation was most apparent for cognitive networks (frontoparietal, dorsal and ventral attention, limbic, and default mode), with connectivity relating to EF in the Aβ+ group specifically. <b><i>Conclusions:</i></b> Using an innovative approach to constructing individual-specified resting-state functional connectomes, we were able to detect differences in brain-cognition associations in pre-clinical AD. Our findings provide novel insight into specific functional network alterations occurring in the presence of Aβ that relate to cognitive function in asymptomatic individuals. Impact statement Elevated cerebral amyloid-β is a biomarker of pre-clinical Alzheimer's disease (AD). Associations between amyloidosis, functional network disruption, and cognitive impairment are evident in the later stages of AD, but these effects have not been substantiated in pre-clinical AD. Using individual-specific parcellations that maximally localize functional networks, we identify network alterations that relate to cognition in pre-clinical AD that have not been previously reported. We demonstrate that these effects localize to networks implicated in cognition. Our findings suggest that there may be subtle, amyloid-related alterations in the functional connectome that are detectable in pre-clinical AD, with potential implications for cognition in asymptomatic individuals.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"275-286"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9695814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain Connectivity: <i>A Journal of Clinical Neurology, Neuroscience, & Neuroimaging Advancing the Field of Neurology</i>.","authors":"Paul Edison","doi":"10.1089/brain.2023.29050.editorial","DOIUrl":"10.1089/brain.2023.29050.editorial","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"265"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9656729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlative Chemical Imaging Identifies Amyloid Peptide Signatures of Neuritic Plaques and Dystrophy in Human Sporadic Alzheimer's Disease.","authors":"Srinivas Koutarapu, Junyue Ge, Durga Jha, Kaj Blennow, Henrik Zetterberg, Tammaryn Lashley, Wojciech Michno, Jörg Hanrieder","doi":"10.1089/brain.2022.0047","DOIUrl":"10.1089/brain.2022.0047","url":null,"abstract":"<p><p><b><i>Objective:</i></b> Alzheimer's disease (AD) is the most common neurodegenerative disease. The predominantly sporadic form of AD is age-related, but the underlying pathogenic mechanisms remain not fully understood. Current efforts to combat the disease focus on the main pathological hallmarks, in particular beta-amyloid (Aβ) plaque pathology. According to the amyloid cascade hypothesis, Aβ is the critical early initiator of AD pathogenesis. Plaque pathology is very heterogeneous, where a subset of plaques, neuritic plaques (NPs), are considered most neurotoxic rendering their in-depth characterization essential to understand Aβ pathogenicity. <b><i>Methods:</i></b> To delineate the chemical traits specific to NP types, we investigated senile Aβ pathology in the postmortem, human sporadic AD brain using advanced correlative biochemical imaging based on immunofluorescence (IF) microscopy and mass spectrometry imaging (MSI). <b><i>Results:</i></b> Immunostaining-guided MSI identified distinct Aβ signatures of NPs characterized by increased Aβ1-42(ox) and Aβ2-42. Moreover, correlation with a marker of dystrophy (reticulon 3 [RTN3]) identified key Aβ species that both delineate NPs and display association with neuritic dystrophy. <b><i>Conclusion:</i></b> Together, these correlative imaging data shed light on the complex biochemical architecture of NPs and associated dystrophic neurites. These in turn are obvious targets for disease-modifying treatment strategies, as well as novel biomarkers of Aβ pathogenicity.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"297-306"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398722/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10293545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in Alzheimer's Disease.","authors":"Michael Schöll","doi":"10.1089/brain.2023.29049.editorial","DOIUrl":"10.1089/brain.2023.29049.editorial","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"266-268"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9650719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Default-Mode Network Connectivity Changes During the Progression Toward Alzheimer's Dementia: A Longitudinal Functional Magnetic Resonance Imaging Study.","authors":"Vincent Malotaux,&nbsp;Laurence Dricot,&nbsp;Lisa Quenon,&nbsp;Renaud Lhommel,&nbsp;Adrian Ivanoiu,&nbsp;Bernard Hanseeuw","doi":"10.1089/brain.2022.0008","DOIUrl":"https://doi.org/10.1089/brain.2022.0008","url":null,"abstract":"<p><p><b><i>Background/Purpose:</i></b> Brain function changes with Alzheimer's disease (AD) progression. Evaluating those changes longitudinally is important to understand the complex relationships between brain pathologies and cognition. We aimed (1) to identify longitudinal changes in functional connectivity in patients with mild cognitive impairment (MCI) characterized for amyloid-β (Aβ) status and (2) to relate these functional changes to clinical progression. <b><i>Methods:</i></b> Forty-four patients with MCI were followed using serial functional magnetic resonance imaging (fMRI) over 1.2 years (three sessions) and cognitive testing over 3.1 years (five sessions). Intra and inter-network connectivities were computed to assess changes in brain connectivity using a network atlas adapted for late adulthood. Sixteen low-Aβ clinically normal older adults underwent a single fMRI session for group comparisons at baseline. Linear mixed-effects models with random intercept and slope were used to predict changes in connectivity based on Aβ status and progression to dementia. <b><i>Results:</i></b> At baseline, intra and inter-network resting-state fMRI connectivities did not differ by baseline clinical diagnosis, Aβ status, or clinical progression to dementia. At the final imaging session, progressive MCI had significantly higher connectivity compared with stable MCI, specifically within the default-mode network (DMN). Longitudinally, progressive MCI had increasing intra-DMN connectivity over time compared with stable MCI, and the rate of changes in connectivity was significantly associated with the rate of cognitive decline. <b><i>Conclusions:</i></b> Intra-DMN connectivity increases in MCI patients progressing toward dementia, suggesting aberrant synchronization in the symptomatic stages of AD. Impact statement Changes in functional connectivity occur in the course of Alzheimer's disease. We observed a progressive increase over time in resting-state functional connectivity within the default-mode network in patients with mild cognitive impairment who progressed to dementia. The rate of connectivity increase was significantly associated with the rate of cognitive decline. The observation of increased functional connectivity during the progression to dementia, and not only in the pre-clinical stage, is interpreted as an aberrant synchronization rather than a compensation mechanism.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"287-296"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10002762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cholinesterase Inhibitors Response Might Be Related to Right Hippocampal Functional Connectivity in Mild Alzheimer's Disease.","authors":"Liara Rizzi,&nbsp;Thamires Naela Cardoso Magalhães,&nbsp;Natalie Lecce,&nbsp;Adriel Dos Santos Moraes,&nbsp;Raphael Fernandes Casseb,&nbsp;Camila Vieira Ligo Teixeira,&nbsp;Brunno Machado de Campos,&nbsp;Thiago Junqueira Ribeiro de Rezende,&nbsp;Leda Leme Talib,&nbsp;Orestes Vicente Forlenza,&nbsp;Fernando Cendes,&nbsp;Marcio Luiz Figueredo Balthazar","doi":"10.1089/brain.2022.0026","DOIUrl":"https://doi.org/10.1089/brain.2022.0026","url":null,"abstract":"<p><p><b><i>Background:</i></b> The response to cholinesterase inhibitors (ChEIs) treatment is variable in patients with Alzheimer's disease (AD). Patients and physicians would benefit if these drugs could be targeted at those most likely to respond in a clinical setting. Therefore, this study aimed to evaluate the ability of cerebrospinal fluid (CSF) AD biomarkers, hippocampal volumes, and Default Mode Network functional connectivity to predict clinical response to ChEIs treatment in mild AD. <b><i>Methods:</i></b> We followed up on 39 mild AD patients using ChEIs at therapeutic doses. All subjects underwent clinical evaluation, neuropsychological assessment, magnetic resonance imaging examination, and CSF biomarkers quantification at the first assessment. The Mini-Mental Status Examination (MMSE) was used to measure the global cognitive status before and after the follow-up. \"Responders\" were considered as those who have remained stable or improved the MMSE score between evaluations and \"Nonresponders\" as those who have worsened the MMSE score. We performed univariate and multivariate logistic regressions to predict the clinical response from each biomarker. <b><i>Results:</i></b> About 35.89% of patients were classified as \"Responders\" to ChEIs treatment after the follow-up. The multivariate model with measures of Right Hippocampus (RHIPPO), adjusted for gender and interval between assessments, was significant (odds ratio: 1.09 [95% confidence interval, 1.00-1.19], <i>p</i> = 0.0392). This model achieved an accuracy of 77.60%. <b><i>Conclusion:</i></b> Our findings suggest that the functional connectivity of RHIPPO might be an early imaging biomarker to predict clinical response to ChEIs drugs in mild AD. Impact statement The functional connectivity of the right hippocampus showed a direct relationship with the clinical response to cholinesterase inhibitors (ChEIs) treatment in patients with mild Alzheimer's disease. Transposing our findings to clinical settings could allow physicians to prescribe ChEIs for patients for whom treatment would be most beneficial.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 5","pages":"269-274"},"PeriodicalIF":3.4,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10002755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Anatomical Pathway Models with Tractography Estimates of the Pallidothalamic, Cerebellothalamic, and Corticospinal Tracts.","authors":"Mikkel V Petersen, Cameron C McIntyre","doi":"10.1089/brain.2022.0068","DOIUrl":"10.1089/brain.2022.0068","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Models of structural connectivity in the human brain are typically simulated using tractographic approaches. However, the nonlinear fitting of anatomical pathway atlases to <i>de novo</i> subject brains represents a simpler alternative that is hypothesized to provide more anatomically realistic results. Therefore, the goal of this study was to perform a side-by-side comparison of the streamline estimates generated by either pathway atlas fits or tractographic reconstructions in the same subjects. <b><i>Methods:</i></b> Our analyses focused on reconstruction of the corticospinal tract (CST), cerebellothalamic (CBT), and pallidothalamic (PT) pathways using example datasets from the Human Connectome Project (HCP). We used MRtrix3 to explore whole brain, as well as manual seed-to-target, tractography approaches. In parallel, we performed nonlinear fits of an axonal pathway atlas to each HCP dataset using Advanced Normalization Tools (ANTs). <b><i>Results:</i></b> The different methods produced notably different estimates for each pathway in each subject. The fitted atlas pathways were highly stereotyped and exhibited low variability in their streamline trajectories. Manual tractography resulted in pathway estimates that generally corresponded with the fitted atlas pathways, but with a higher degree of variability in the individual streamlines. Pathway reconstructions derived from whole-brain tractography exhibited the highest degree of variability and struggled to create anatomically realistic representations for either the CBT or PT pathways. <b><i>Conclusion:</i></b> The speed, simplicity, reproducibility, and realism of anatomical pathway model fits makes them an appealing option for some forms of structural connectivity modeling in the human brain. Impact statement Axonal pathway modeling is an important component of deep brain stimulation (DBS) research studies that seek to identify the brain connections that are directly activated by stimulation. The corticospinal tract, cerebellothalamic (CBT), and pallidothalamic (PT) pathways are specifically relevant to the study of subthalamic DBS for the treatment of Parkinson's disease. Our results suggest that anatomical pathway model fits of the CBT and PT pathways to <i>de novo</i> subject brains represent a more anatomically realistic option than tractographic approaches when studying subthalamic DBS.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 4","pages":"237-246"},"PeriodicalIF":3.4,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10178936/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9588823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network Centrality and Modularity of Structural Covariance Networks in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study.","authors":"Gopalkumar Rakesh, Mark W Logue, Emily Clarke-Rubright, Courtney C Haswell, Paul M Thompson, Michael D De Bellis, Rajendra A Morey, Delin Sun","doi":"10.1089/brain.2022.0038","DOIUrl":"10.1089/brain.2022.0038","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCNs) are represented as graphs with brain regions as nodes and correlations between nodes as edges. <b><i>Methods:</i></b> We built SCNs for PTSD and control groups using 148 CT and SA measures that were harmonized for site in <i>n</i> = 3439 subjects from Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA)-Psychiatric Genomics Consortium (PGC) PTSD. We compared centrality between PTSD and controls as well as interactions of diagnostic group with age, sex, and comorbid major depressive disorder (MDD) status. We investigated associations between network modularity and diagnostic grouping. <b><i>Results:</i></b> Nodes with higher CT-based centrality in PTSD compared with controls included the left inferior frontal sulcus, left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. Children (<10 years) and adolescents (10-21) with PTSD showed greater centrality in frontotemporal areas compared with young (22-39) and middle-aged adults (40-59) with PTSD, who showed higher centrality in occipital areas. The PTSD diagnostic group interactions with sex and comorbid MDD showed altered centrality in occipital regions, along with greater visual network (VN) modularity in PTSD subjects compared with controls. <b><i>Conclusion:</i></b> Structural covariance in PTSD is associated with centrality differences in occipital areas and VN modularity differences in a large well-powered sample. In the context of extensive structural covariance remodeling taking place before and during adolescence, the present findings suggest a process of cortical remodeling that commences with trauma and/or the onset of PTSD but may also predate these events. Impact statement Centrality is a graph theory measure that offers insights into a node's relationship with all other nodes in the brain. Centrality pinpoints the drivers of brain communication within networks and nodes and may be a promising target for treatments such as neuromodulation. Modularity can pinpoint modules that exist within larger networks and quantify the connections between these modules. Centrality and modularity complement functional and structural connectivity measurements within specific brain networks.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"13 4","pages":"211-225"},"PeriodicalIF":3.4,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10325816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9761176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}