Brain connectivity最新文献

{"title":"Enhanced Functional Connectivity of Executive Functions and Attention Networks During Reading Versus Narrative Comprehension in Dyslexia.","authors":"Rola Farah, Raya Meri, Tzipi Horowitz-Kraus","doi":"10.1177/21580014251358735","DOIUrl":"10.1177/21580014251358735","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Executive functions (EF) are cognitive processes supporting language and reading. Children with dyslexia show reading difficulties primarily due to phonological processing, with additional reported deficits in EF. This study aimed to determine the differences in EF involvement during written (reading) versus oral language (narrative) comprehension in children with dyslexia versus typical readers neurobiologically and behaviorally. <b><i>Methods:</i></b> Reading, language, and EF behavioral measures and functional MRI data were collected from 55 typical readers (TR) and 65 English-speaking children with dyslexia ages 8-12 years during reading and narrative comprehension tasks. Differences within and between functional connectivity of EF and attention networks were calculated and then compared between groups and tasks using Fisher Z-transformation. <b><i>Results:</i></b> Children with dyslexia showed higher functional connectivity values in EF and attention networks in both reading and narrative comprehension tasks, whereas TR showed higher functional connectivity in narrative versus reading comprehension. Within groups, analysis showed higher functional connectivity within dorsal attention functional brain network (DAN) and between DAN-fronto-parietal (FP), cingulo-opercular (CO)-FP, and ventral attention functional brain network (VAN)-DAN, in the reading versus narrative comprehension task in the dyslexia group. TR showed higher functional connectivity within VAN, and between VAN-FP in the narrative compared to the reading comprehension tasks. <b><i>Discussion:</i></b> Children with dyslexia seem to greatly utilize EF and attention-related networks in narrative and reading comprehension tasks and demonstrate a greater network integration for the written versus oral comprehension task. TR, however, utilize these networks only during oral comprehension, which may point to a greater reliance on memory and processing effort in the absence of written information.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"229-242"},"PeriodicalIF":2.3,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13345194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612081","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":"Revisiting the Multilayer Network Framework for Electrophysiological Networks.","authors":"Prejaas K B Tewarie, Steven Laureys, Rikkert Hindriks","doi":"10.1089/brain.2025.0010","DOIUrl":"10.1089/brain.2025.0010","url":null,"abstract":"<p><p><b><i>Background:</i></b> The multilayer network framework has emerged as an innovative approach for analyzing electrophysiological networks, providing insights into complex neuronal interactions by integrating connectivity across different frequency bands in electroencephalography (EEG) and magnetoencephalography (MEG) data. <b><i>Current Limitations:</i></b> Traditionally, multilayer networks have treated canonical frequency bands (e.g., delta, theta, alpha, beta, gamma) as distinct layers. Recent findings could raise potential concerns regarding this approach, emphasizing the need to incorporate the distinction between periodic (oscillatory) and aperiodic (broadband) signal components. <b><i>Conceptual Advance:</i></b> Aperiodic signals may reflect excitation-inhibition balance and scale-free dynamics, while periodic signals capture oscillatory rhythms, both contributing uniquely to brain network interactions. A multilayer network framework in the current context could be applicable in the case of genuine coupling between these components, termed \"aperiodic-to-periodic coupling.\" This necessitates novel connectivity metrics and analytical methods that can handle broadband data. Furthermore, challenges remain in decomposing these components in the time domain and developing robust metrics for broadband connectivity that account for signal leakage. <b><i>Outlook:</i></b> Addressing these issues will enhance multilayer frameworks, enabling better insights into brain network integrity, cognitive dysfunction, and neurological conditions.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"189-194"},"PeriodicalIF":2.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144172847","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":"Changes in the Functional Connectivity of Cerebellar Subregions in Anti-<i>N</i>-Methyl-d-Aspartate Receptor Encephalitis.","authors":"Muzi Li, Zijun Liu, Jingwen Li, Guang Xu, Junzhang Tian, Xiaofen Ma","doi":"10.1089/brain.2024.0102","DOIUrl":"10.1089/brain.2024.0102","url":null,"abstract":"<p><p><b><i>Background:</i></b> In anti-<i>N</i>-methyl-d-aspartate receptor (anti-NMDAR) encephalitis, the cerebellum, a characteristic brain region, exhibits abnormal functioning and structure. However, the relationship between resting-state activities in the cerebellar subregions and core symptoms of cognitive dysfunction is unclear. <b><i>Methods:</i></b> In this study, a total of 23 patients with anti-NMDAR encephalitis and 23 healthy controls were included, and 19 patients (mean age 30.05 ± 13.03 years) and 21 healthy controls (mean age 28.42 ± 9.47 years) were enrolled based on image quality and head movement. Seed-based functional connectivity (FC) analysis was used to investigate changes in FC of cerebellar subregions, and the association between changes in cerebellar subregion FC and cognitive dysfunction was explored in conjunction with cognitive scales. <b><i>Results:</i></b> Patients with anti-NMDAR encephalitis exhibited poorer cognitive performance than the healthy controls did. In the patient group, the FC between the right cerebellar Crus I and the left thalamus was significantly reduced and showed a negative correlation with disease duration (<i>p</i> < 0.05); however, it showed positive correlations with attention and information processing speed according to Symbol Digit Modalities Test (<i>p</i> < 0.01), as well as with verbal learning and memory (according to California Verbal Learning Test (CVLT; <i>p</i> < 0.05). The FCs between the left cerebellar Crus Ia and the right medial superior frontal gyrus, as well as between the left cerebellar Crus Ib and the right middle temporal gyrus, were decreased. The connectivity between the cerebellar vermis Crus II and the left putamen, along with the opercular part of the inferior frontal gyrus, showed a significant reduction. Decreased FC between the left cerebellar X lobule and the left putamen showed positive correlation with CVLT (<i>p</i> < 0.01). <b><i>Conclusion:</i></b> Cerebellar subregion and brain abnormalities FC in patients with anti-NMDAR encephalitis are linked to cognitive deficits. These results provide insights into the neurophysiological mechanisms underlying cognitive impairment in these patients.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"195-203"},"PeriodicalIF":2.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198246","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":"Effects of Transcranial Magnetic Stimulation on Cognitive-Affective Task-Based Functional Connectivity.","authors":"Merideth A Addicott, Jonathan R Young, L Gregory Appelbaum","doi":"10.1089/brain.2024.0095","DOIUrl":"10.1089/brain.2024.0095","url":null,"abstract":"<p><p><b><i>Objective:</i></b> Repetitive transcranial magnetic stimulation (rTMS) uses electromagnetic fields to induce electrical currents in the superficial cortex, and this electric signal is believed to propagate to functionally connected distal brain regions. We previously reported that rTMS targeting the postcentral gyrus affected resting-state functional connectivity with the posterior insula. The current study investigated whether rTMS targeting the postcentral gyrus would affect task-based functional connectivity (TBFC) with the posterior insula during a cognitive-affective distress task. <b><i>Methods:</i></b> Twenty-five healthy participants were assigned to 10 Hertz (Hz) (<i>n</i> = 13) or 1 Hz (<i>n</i> = 12) rTMS groups. Participants received five consecutive days of once-daily rTMS and underwent pre- and post-rTMS magnetic resonance imaging (MRI) scans while completing a cognitive-affective distress task with negative auditory feedback. rTMS coil placement over the right postcentral gyrus was guided with neuronavigation, and TBFC analysis of the MRI data was performed using the bilateral auditory cortex as a seed region-of-interest. <b><i>Results:</i></b> There was an false discovery rate (FDR)-corrected significant group-by-session-by-condition interaction in a right putamen/posterior insula cluster: in the distress condition, the 1 Hz rTMS group had significantly weaker (i.e., smaller absolute value) negative TBFC following rTMS (<i>p</i> = 0.005), while the 10 Hz group had no significant effect. <b><i>Conclusion:</i></b> This preliminary, proof-of-concept study suggests that rTMS can modulate TBFC in distal brain regions implicated in the neural response to cognitive-affective negative feedback. Future research should investigate whether rTMS can both modulate insula-associated TBFC and improve cognitive-affective task performance or mood outcomes, potentially by increasing the number of rTMS sessions or using different rTMS pulse sequences. Impact Statement Clinical application of repetitive transcranial magnetic stimulation (rTMS) may exert a therapeutic effect by modulating the strength of functional connectivity between superficial cortical areas and deeper brain regions. These effects on functional connectivity are typically measured while participants are at rest. This proof-of-concept study suggests that rTMS can have a measurable effect on task-based functional connectivity as well. In the future, this could be an important means of understanding how rTMS exerts effects on cognitive-affective task performance and mood.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"15 4","pages":"153-161"},"PeriodicalIF":2.3,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13353791/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143980291","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":"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":"Direct Comparison of EEG Resting State and Task Functional Connectivity Patterns for Predicting Working Memory Performance Using Connectome-Based Predictive Modeling.","authors":"Anton Pashkov, Ivan Dakhtin","doi":"10.1089/brain.2024.0059","DOIUrl":"10.1089/brain.2024.0059","url":null,"abstract":"<p><p><b><i>Background:</i></b> The integration of machine learning with advanced neuroimaging has emerged as a powerful approach for uncovering the relationship between neuronal activity patterns and behavioral traits. While resting-state neuroimaging has significantly contributed to understanding the neural basis of cognition, recent fMRI studies suggest that task-based paradigms may offer superior predictive power for cognitive outcomes. However, this hypothesis has never been tested using electroencephalography (EEG) data. <b><i>Methods:</i></b> We conducted the first experimental comparison of predictive models built on high-density EEG data recorded during both resting-state and an auditory working memory task. Multiple data processing pipelines were employed to ensure robustness and reliability. Model performance was evaluated by computing the Pearson correlation coefficient between predicted and observed behavioral scores, supplemented by mean absolute error and root mean square error metrics for each model configuration. <b><i>Results:</i></b> Consistent with prior fMRI findings, task-based EEG data yielded slightly better modeling performance than resting-state data. Both conditions demonstrated high predictive accuracy, with peak correlations between observed and predicted values reaching r = 0.5. Alpha and beta band functional connectivity were the strongest predictors of working memory performance, followed by theta and gamma bands. Additionally, the choice of parcellation atlas and connectivity method significantly influenced results, highlighting the importance of methodological considerations. <b><i>Conclusion:</i></b> Our findings support the advantage of task-based EEG over resting-state data in predicting cognitive performance, aligning with. The study underscores the critical role of frequency-specific functional connectivity and methodological choices in model performance. These insights should guide future experimental designs in cognitive neuroscience. Impact Statement This study provides the first direct comparison of EEG-based functional connectivity during rest and task conditions for predicting working memory performance using connectome-based predictive modeling (CPM). It demonstrates that task-based EEG data slightly outperforms resting-state data, with alpha and beta bands being the most predictive. The findings highlight the critical influence of methodological choices, such as parcellation atlases and connectivity metrics, on model outcomes. By bridging gaps in EEG research and validating CPM's applicability, this work advances the optimization of neuroimaging protocols for cognitive assessment, offering insights for future studies in cognitive neuroscience.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":"15 4","pages":"175-187"},"PeriodicalIF":2.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143975072","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":2.3,"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":2.5,"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":"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":2.5,"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":"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":2.5,"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}