Brain connectivity最新文献

{"title":"Connecting the Dots: How Adaptive Brain Networks Guide the Future of Clinical Neuroscience.","authors":"Roxane Hoyer, Steven Laureys","doi":"10.1089/brain.2025.0055","DOIUrl":"https://doi.org/10.1089/brain.2025.0055","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"15 4","pages":"151-152"},"PeriodicalIF":2.4,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143975115","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":"Dynamic Task-Related Changes in Electroencephalography Brain Connectivity During a Button-Press Task in Children with and Without Bilateral Cerebral Palsy.","authors":"Sang Wook Lee, Thomas C Bulea, Julia E Kline, Diane L Damiano","doi":"10.1089/brain.2024.0096","DOIUrl":"10.1089/brain.2024.0096","url":null,"abstract":"<p><p><b><i>Background:</i></b> Cerebral palsy (CP) often affects function of one or both arms. Resting-state magnetic resonance imaging studies identified abnormal neuronal connectivity related to functional deficits in CP, with few studies on dynamic, task-related changes in connectivity. Here, we compare connectivity in participants with CP and typical development (TD) during an upper limb task and relate these to motor performance. <b><i>Methods:</i></b> Children with CP (<i>n</i> = 15) and TD (<i>n</i> = 15) performed a button-press task with both arms, while recording 64-channel electroencephalography. Inter- and intrahemispheric connectivity between dominant and nondominant premotor, motor, and sensory regions were examined during rest, movement preparation, and execution using a normalized magnitude squared time-frequency coherence analysis (<i>α</i>-band: 8-12 Hz, <i>β</i>-band: 13-35 Hz, <i>γ</i>-band: 36-85 Hz). <b><i>Results:</i></b> The only group differences were in intrahemispheric connectivity during nondominant arm trials, with CP having higher frontal to central connectivity than TD in all frequency bands in the dominant hemisphere and higher central to parietal beta connectivity in the nondominant hemisphere. Significant main effects for period showed most differences between rest and movement phases. Group by period interactions were also only found during nondominant arm trials (interhemispheric: CP coherence increased more during execution in frontal, central, and parietal regions; intrahemispheric: CP coherence decreased less during execution in nondominant and dominant frontal to parietal regions). Clinical and movement scores were moderately related to connectivity in CP, with poorer nondominant arm function significantly correlated with higher inter- and intrahemispheric coherence. <b><i>Conclusions:</i></b> Group differences emerged mainly during intrahemispheric nondominant arm trials across frequency bands with higher coherence in CP associated with greater functional limitation. Impact Statement In contrast to assessing brain connectivity with MRI in children with CP, the use of EEG enables the investigation of this during a functional task, and the sample is not limited by head movements that preclude the attainment of high-quality MRI data in many with CP. The finding of increased task-specific intrahemispheric brain connectivity in bilateral CP, the magnitude of which was related to the degree of functional limitations, suggests a new target for rehabilitation as well as a sensitive outcome measure for clinical trials aimed at improving brain and motor function in CP.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"15 4","pages":"162-174"},"PeriodicalIF":2.4,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12223383/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143972415","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":"Distinct Brain Connectivity Patterns in Sickle Cell Disease: A Biomarker for Chronic Pain Severity.","authors":"Jamille E R S Santana, Maria Luiza Carvalho, Tiago da Silva Lopes, José G V Miranda, Pedro Montoya, Abrahão F Baptista, André Fonseca","doi":"10.1089/brain.2024.0087","DOIUrl":"10.1089/brain.2024.0087","url":null,"abstract":"<p><p><b><i>Background:</i></b> Central nervous system complications are common in sickle cell disease (SCD), and the defining associated biomarkers are becoming increasingly relevant for physicians in diagnostic and prognostic contexts. Recent studies have reported altered brain connectivity in pain processing, highlighting a new avenue for developing sensitive measures of SCD severity. <b><i>Method:</i></b> This cross-sectional study used graph theory concepts to analyze effective connectivity in individuals with SCD and healthy controls during rest and motor imagery tasks. The SCD group was further divided into two subgroups based on pain intensity (less pain or more pain) during the evaluation. <b><i>Results:</i></b> Individuals with SCD and chronic pain exhibited a distinct brain connectivity signature compared to healthy individuals and within pain sublevels. <b><i>Conclusion:</i></b> Chronic pain in SCD shows a unique brain connectivity pattern when compared to healthy subjects and across different pain levels. The results support the hypothesis that chronic pain condition is associated with decreased interhub connections and increased intrahub connections for specific brain rhythms. Furthermore, the small-world parameter can distinguish SCD individuals from controls and differentiate pain levels within SCD individuals, offering a promising biomarker for clinical assessment.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"125-138"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143662465","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":"Task-radMBNet: An Improved Task-Driven Dynamic Graph Sparsity Pattern Radiomics-Based Morphological Brain Network for Alzheimer's Disease Characterization.","authors":"Limei Song, Zhiwei Song, Pengzhi Nan, Qiang Zheng","doi":"10.1089/brain.2024.0053","DOIUrl":"10.1089/brain.2024.0053","url":null,"abstract":"<p><p><b><i>Background:</i></b> The study of task-driven dynamic adaptive graph sparsity patterns in Alzheimer's disease (AD) analysis is of great importance, as it allows for better focus on regions and connections of interest and enhances task sensitivity. <b><i>Methods:</i></b> In this study, we introduced a task-driven dynamic adaptive graph sparsity model (called task-driven radiomics-based morphological brain network [Task-radMBNet]) for AD diagnosis based on radiomics-based morphological brain network (radMBN). Specifically, the Task-radMBNet was established by devising a connectivity feature-based graph convolutional network (GCN) channel (called a connectivity-GCN channel) and a radiomics feature-based GCN channel (called a radiomics-GCN channel), where the two GCN channels shared a same dynamic sparse brain network in graph convolution but worked for different aims separately. The connectivity-GCN channel dynamically learned the graph's sparse topology that best suits the target task, while the radiomics-GCN channel combined radiomics node features and dynamic topology to improve AD diagnostic accuracy. <b><i>Results:</i></b> The Task-radMBNet achieved superior classification accuracy of 87.8% and 86.0% in early AD diagnosis across a total of 1273 subjects within the AD Neuroimaging Initiative and European Diffusion Tensor Imaging (DTI) Study on Dementia databases. We also visualized the topology heat map and important connectivity under different network sparse settings. <b><i>Conclusions:</i></b> The results demonstrated significant promise in the diagnosis of neurological disorders by integrating Task-radMBNet with radMBN.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"139-149"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143802495","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":"From Dyadic to Higher-Order Interactions: Enhanced Representation of Homotopic Functional Connectivity Through Control of Intervening Variables.","authors":"Behdad Khodabandehloo, Payam Jannatdoust, Babak Nadjar Araabi","doi":"10.1089/brain.2024.0056","DOIUrl":"10.1089/brain.2024.0056","url":null,"abstract":"<p><p><b><i>Background:</i></b> The brain's complex functionality emerges from network interactions that go beyond dyadic connections, with higher-order interactions significantly contributing to this complexity. Homotopic functional connectivity (HoFC) is a key neurophysiological characteristic of the human brain, reflecting synchronized activity between corresponding regions in the brain's hemispheres. <b><i>Materials and Methods:</i></b> Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we evaluate dyadic and higher-order interactions of three functional connectivity (FC) parameterizations-bivariate correlation, partial correlation, and tangent space embedding-in their effectiveness at capturing HoFC through the inter-hemispheric analogy test. <b><i>Results:</i></b> Higher-order feature vectors are generated through node2vec, a random walk-based node embedding technique applied to FC networks. Our results show that higher-order feature vectors derived from partial correlation most effectively represent HoFC, while tangent space embedding performs best for dyadic interactions. <b><i>Discussion:</i></b> These findings validate HoFC and underscore the importance of the FC construction method in capturing intrinsic characteristics of the human brain.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"113-124"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613335","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":"Distinct Neural Connectivity Patterns During Music Listening and Imagination: An Electroencephalography Study.","authors":"Kiarash Fouladi, Hessam Ahmadi, Ali Motie-Nasrabadi","doi":"10.1089/brain.2024.0042","DOIUrl":"10.1089/brain.2024.0042","url":null,"abstract":"<p><p><b><i>Background:</i></b> The brain's function changes during various activities, and numerous studies have explored this field. An intriguing and significant area of research is the brain's functioning during imagination and periods of inactivity. <b><i>Objective:</i></b> This study explores the differences in brain connectivity during music listening and imagination: by identifying distinct neural connectivity patterns and providing insights into the cognitive mechanisms underlying auditory imagination. <b><i>Methods:</i></b> Effective connectivity matrices were generated using generalized partial directed coherence (GPDC) and directed Directed Transfer Function (dDTF) methods applied to non-invasive electroencephalography data from these two conditions. Statistical tests were performed to illustrate the differences in brain connectivity, followed by the creation of brain graphs and the application of a non-parametric permutation test to demonstrate statistical significance. Data classification between listening to music and imagining it was performed using an Support Vector Machine (SVM) classifier with different feature vectors. <b><i>Results:</i></b> Combining features extracted from GPDC and dDTF achieved an accuracy of 71.3% while using GPDC and dDTF features individually yielded accuracies of 60% and 62.1%, respectively. Among all the graph's global features, only modularity and small-worldness showed statistically significant differences in dDTF and GPDC. Overall, findings reveal that information flows from the left hemisphere to the right hemisphere increases during music imagination compared with listening, highlighting distinct neural connectivity patterns associated with imaginative processes. <b><i>Conclusion:</i></b> The study provides novel insights into the distinct neural connectivity patterns during music listening and imagination, contributing to the broader understanding of cognitive processes associated with auditory imagination and perception.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"59-70"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142799394","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":"Developmental Mismatch Across Brain Modalities in Young Children.","authors":"Xiangyu Long, Madison Long, Jamie Roeske, Jess E Reynolds, Catherine Lebel","doi":"10.1089/brain.2024.0046","DOIUrl":"10.1089/brain.2024.0046","url":null,"abstract":"<p><p><b><i>Background:</i></b> Brain development during the preschool period is complex and extensive and underlies ongoing behavioral and cognitive maturation. Increasing understanding of typical brain maturation during this time is critical to early identification of atypical development and could inform treatments and interventions. Previous studies have suggested mismatches between brain structural and functional development in later childhood and adolescence. The current study aimed to delineate the developmental matches and mismatches between brain measures from multiple magnetic resonance imaging modalities in young children. <b><i>Methods:</i></b> Brain volume, cortical thickness, fractional anisotropy, cerebral blood flow (CBF), amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and eigenvector centrality mapping (ECM) were included. Multi-modal neuroimages for 159 datasets from 67 typically developing preschoolers (2.0-7.6 years old) were collected and analyzed. <b><i>Results:</i></b> Functional measures (CBF, ECM, ReHo, ALFF) had similar developmental trajectories across regions, whereas development trajectories for brain volumes and cortical thickness were more heterogeneous. Furthermore, within individuals, brain volumes and cortical thickness were very good at predicting individual scans from prior longitudinal scans. <b><i>Conclusions:</i></b> These findings provide a more detailed characterization of the complex interplay of different types of brain development in the early years, laying the foundation for future studies on the impact of environmental factors and neurodevelopmental disorders on the development matches/mismatches patterns between brain areas and modalities.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"71-83"},"PeriodicalIF":2.5,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142871334","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":"Charting the Frontiers of Brain Connectivity: From Rehabilitation to Imagination.","authors":"Minji Lee, Steven Laureys","doi":"10.1089/brain.2025.0020","DOIUrl":"https://doi.org/10.1089/brain.2025.0020","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"15 2","pages":"57-58"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143656194","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":"Abnormal Brain State in Major Depressive Disorder: A Resting-State Magnetic Resonance Study.","authors":"Siyu Fan, Rui Qian, Nanxue Duan, Hongping Wang, Yue Yu, Yang Ji, Xiaohui Xie, Yue Wu, Yanghua Tian","doi":"10.1089/brain.2024.0062","DOIUrl":"10.1089/brain.2024.0062","url":null,"abstract":"<p><p><b><i>Background:</i></b> Respective changes in resting-state linear and nonlinear measures in major depressive disorder (MDD) have been reported. However, few studies have used integrated measures of linear and nonlinear brain dynamics to explore the pathological mechanisms underlying MDD. <b><i>Method:</i></b> Forty-two patients with MDD and 42 sex- and age-matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging to calculate multiscale entropy (MSE) and regional homogeneity (ReHo). The MSE-ReHo coupling of the whole gray matter and the MSE/ReHo ratio (the complexity of intensity homogeneity per unit time series) of each voxel were compared between the two groups. To evaluate the discriminative capacity of ratio features between patients with MDD and HC, we employed the support vector machine (SVM) learning method. <b><i>Results:</i></b> We observed that patients with MDD displayed increased MSE/ReHo ratio mainly in the orbitofrontal cortex, sensorimotor areas, and visual cortex. Moreover, significant correlations were observed between MSE/ReHo ratio and clinical indicators, including depression severity and cognitive function tests. The SVM model demonstrated high accuracy in differentiating patients with MDD from HC, highlighting the potential of the MSE/ReHo ratio as a diagnostic and prognostic tool. <b><i>Conclusions:</i></b> The aberrant MSE/ReHo ratio implicated the underlying mechanisms of depressive symptoms and cognitive impairment in patients with MDD. It may represent a critical state of the brain region, reflecting the degree of chaos and order in the brain region. Integrating linear and nonlinear combinations of brain signals holds promise for diagnosing psychiatric disorders.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"84-97"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078528","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":"Effect of Parallel Cognitive-Motor Training Tasks on Hemodynamic Responses in Robot-Assisted Rehabilitation.","authors":"Duojin Wang, Jiankang Zhou, Yanping Huang, Qingyun Meng","doi":"10.1089/brain.2024.0043","DOIUrl":"10.1089/brain.2024.0043","url":null,"abstract":"<p><p><b><i>Objective:</i></b> Previous studies suggest that the combination of robot-assisted training with other concurrent tasks may promote the functional recovery and improvement better than the single task. It is well-established that robot-assisted rehabilitation training is effective. This study aims to characterize the neural mechanisms and inter-regional connectivity changes associated with robot-assisted parallel interactive training tasks. <b><i>Methods:</i></b> Twenty-five healthy young adults (12 females and 13 males) participated in three number-related cognitive-motor parallel interactive training tasks categorized by difficulty: low difficulty (LD), medium difficulty (MD), and high difficulty (HD). Functional near-infrared spectroscopy was used to measure neural responses in the primary sensorimotor cortex (SM1), supplementary motor area (SMA), and prefrontal cortex (PFC). Activation maps and functional connectivity (FC) correlation matrix maps were applied to assess cortical response and connectivity among channels and regions of interest. <b><i>Results:</i></b> Significant differences were observed in both activation and connectivity results across the three training conditions. Stronger activation (<i>p</i> < 0.01) in oxy-hemoglobin was found in the MD conditions, with activation in the HD condition being stronger than in the LD condition. The FC in the PFC increased linearly with rising training difficulty. Trends in FC for SM1 and SMA were consistent with the activation results. <b><i>Conclusions:</i></b> In parallel training tasks of varying difficulty, MD stimulates more neural activity and promotes stronger network connections in the brain. This study enhances the understanding of the neurological processes involved in robot-assisted parallel interactive tasks and may inform more effective robot-assisted rehabilitation therapies.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"98-111"},"PeriodicalIF":2.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143456899","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}