Brain connectivity最新文献

{"title":"Local Interaction Rules Drive Global Organization of the Human Connectome.","authors":"Arturo Tozzi","doi":"10.1177/21580014261479958","DOIUrl":"10.1177/21580014261479958","url":null,"abstract":"<p><strong>Introduction: </strong>The human connectome exhibits nontrivial large-scale organization despite emerging from decentralized local biological interactions. Most existing generative models reproduce connectomic features through global optimization principles, predefined wiring targets, or developmental templates, leaving unresolved which properties arise from locality alone and which require additional nonlocal mechanisms.</p><p><strong>Methods: </strong>We implemented a simulation framework showing that global coherence can emerge from local compatibility constraints. Networks were generated exclusively through bounded spatial interactions, probabilistic local edge formation, and suppression of incompatible configurations, without global objectives, target topologies, or long-range coordination. Simulated ensembles were analyzed using graph-theoretical metrics, scaling relationships, and rule-based structural classification relative to published reference values of human connectome descriptors.</p><p><strong>Results: </strong>Simulations consistently generated mesoscopic organization characterized by high clustering, modular structure, motif enrichment, and strong short-range connectivity bias. Degree distributions were broad and right-skewed, while edge-length distributions showed pronounced spatial localization. In contrast, several higher-order integrative properties were not reproduced, including empirical connectivity scale, rich-club organization, and long-range hub-to-hub connectivity. Although global metrics displayed substantial quantitative divergence from reported empirical values, several structural regimes and scaling relationships were preserved across parameter ranges.</p><p><strong>Discussion: </strong>Our results distinguish connectome properties structurally compatible with local compatibility constraints from those underdetermined under locality alone. We provide a diagnostic framework designed to isolate the explanatory contribution of local interaction rules to connectome organization through simulations that identify which structural properties emerge directly from locality and which require additional mechanisms beyond local constraints.Impact StatementWe introduce a constraint-based framework for determining which features of human connectome organization can emerge from local interaction rules alone and which require additional mechanisms. By treating divergence from empirical connectomes as evidence of underdetermination rather than simply model error, we shift emphasis from reproducing network statistics to identifying their mechanistic requirements. Our results distinguish locally generated properties, including clustering, modular organization, motif enrichment and short-range wiring bias, from features associated with large-scale integration and hub organization. This framework provides a systematic baseline for evaluating when more complex developmental, anatomical or global mechanisms are necessary to ex","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"274-283"},"PeriodicalIF":2.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148808063","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 Fusion of Structural and Functional Connectivity via Joint Connectivity-Matrix ICA.","authors":"Lei Wu, Marlena Duda, Armin Iraji, Vince D Calhoun","doi":"10.1177/21580014261479990","DOIUrl":"10.1177/21580014261479990","url":null,"abstract":"<p><strong>Introduction: </strong>Integrating functional MRI (fMRI) and diffusion MRI (dMRI) advances neuroimaging by merging complementary perspectives on brain networks, with fMRI measuring functional activity and dMRI capturing structural connectivity (SC). However, combining them dynamically remains challenging due to their drastically different data characteristics.</p><p><strong>Methods: </strong>We propose a novel framework, \"dynamic fusion,\" which extends joint component analysis via connectivity-matrix ICA to integrate static SC with dynamic functional connectivity (FC). It evaluates how joint components relate across temporal states to capture both static and time-varying connectivity features. As a proof-of-concept, and in contrast to more systematic approaches for modeling true temporal dynamics, we defined two temporal states from the first and last thirds of the fMRI time series. We applied this to fMRI and dMRI from control subjects previously analyzed with a static-only model and to a comparable schizophrenia group from the same study.</p><p><strong>Results: </strong>Results revealed heterogeneous temporal dynamics in FC and, importantly, showed that SC representations differ across the two functional time segments, reflecting functional-context-dependent decomposition rather than anatomical change. It also detected joint dynamic SC-FC differences between schizophrenia and control groups, indicating sensitivity to group-level effects that may be missed in static analyses.</p><p><strong>Discussion: </strong>Although the current time segments are not intended to represent canonical or recurring brain states, the results suggest that multimodal fusion outcomes can depend on the functional context with which SC is fused. Overall, our dynamic fusion offers a promising approach for integrating SC and dynamic FC to better understand brain organization and neuropsychiatric disorders, while motivating more systematic definitions of dynamic states in future work.Impact StatementWe present a voxel-level framework for temporally sensitive fusion of structural and functional connectivity using joint cmICA, as an initial proof-of-concept applied to diffusion MRI and functional MRI data. This method reveals how structural connectivity adapts alongside temporally evolving functional states, uncovering novel patterns of brain organization and disruption in schizophrenia. By motivating future work on principled dynamic-state characterization in cross-modal fusion, this approach opens a path toward dynamic connectomics and multimodal biomarker discovery for investigating the complex interplay between brain structure and function in health and disease.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"258-273"},"PeriodicalIF":2.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148788223","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":"Quantitative Anisotropy of the White Matter Microstructure Underlying Language Tracts in Autism.","authors":"Smitha K A, Meagan E Beckerson, Fang-Cheng Yeh, Rajesh K Kana","doi":"10.1177/21580014261479964","DOIUrl":"10.1177/21580014261479964","url":null,"abstract":"<p><strong>Background and aim: </strong>Autism is a neurodevelopmental condition that involves differences in social communication and restricted behaviors, often accompanied by altered structural and functional brain connectivity. This preliminary study examined differences in structural connectivity of language-related white matter tracts between autistic and neurotypical (NT) children, exploring the impact of such differences on language comprehension.</p><p><strong>Method: </strong>Diffusion-weighted imaging data were acquired from 25 children (13 autistic and 12 NT) on a Siemens 3T MAGNETOM Prisma MRI scanner. Data were processed using DSIstudio. Using deterministic tractography, we mapped 16 white matter fiber tracts and assessed diffusion metrics. Correlational tractography examined whole-brain white matter differences, controlling for age, gender, and full-scale IQ. Reading comprehension was assessed using the Gray Oral Reading Test-Fifth Edition, and regression analyses were conducted to examine associations with quantitative anisotropy (QA).</p><p><strong>Results and conclusions: </strong>Autistic children showed significantly higher QA in 6 of the 16 language-related tracts and higher isotropic diffusion in 2 tracts, suggesting denser fiber bundles with more surrounding free water. In the autistic group, lower QA, particularly in the left arcuate fasciculus, was associated with better reading comprehension, whereas, in NT children, higher QA was associated with better reading. These findings suggest that autistic children may rely on different, more localized white matter pathways for reading compared with the more integrated language networks observed in NT children. Divergent QA-reading comprehension relationships across groups suggest that QA may serve as a candidate biomarker for stratifying language-based interventions.Statement of Importance:This study demonstrates that autistic children exhibit higher Quantitative Anisotropy (QA) in language-related white matter tracts and elevated isotropic diffusion, indicating dense fiber bundles with increased extracellular fluid. Importantly, while higher QA in the left arcuate fasciculus associated with better reading comprehension in neurotypical children, lower QA was associated with better comprehension in autistic children. These findings suggest that autistic individuals have distinct, localized neural pathways for reading rather than integrated canonical networks. QA serves as a promising biomarker to guide individualized language interventions and track neurostructural plasticity.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"245-257"},"PeriodicalIF":2.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148788221","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 Functional Connectivity: A Potential Therapeutic Target in Posttraumatic Stress Disorder.","authors":"Jony Sheynin","doi":"10.1177/21580014261479966","DOIUrl":"https://doi.org/10.1177/21580014261479966","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"21580014261479966"},"PeriodicalIF":2.3,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148788206","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":"<i>Corrigendum to:</i> A New Versatile System for 3D Steered LIFU Based on 2D Matrix Arrays.","authors":"","doi":"10.1177/21580014261438426","DOIUrl":"10.1177/21580014261438426","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"239"},"PeriodicalIF":2.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147526741","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":"Cross-Subject Event-Related Potential Classification via Multi-View Based Contrastive Learning.","authors":"Chaochen Chen, Lugui Xia, Jie Zhuang, Qian Qian, HongFei Ji, Jie Li","doi":"10.1177/21580014261462127","DOIUrl":"10.1177/21580014261462127","url":null,"abstract":"<p><strong>Background: </strong>Event-related potentials (ERPs) provide implicit feedback and error-correction signals that are valuable for brain-computer interfaces (BCIs). However, models trained on source-domain subject data are vulnerable to inter-subject variability and acquisition noise, which substantially degrades generalization to unseen subjects.</p><p><strong>Objective: </strong>We propose a multi-view contrastive learning domain generalization (MVCLDG) method to improve cross-subject generalization in ERP recognition by jointly exploiting discriminative feature extraction and domain-invariant representation learning.</p><p><strong>Methods: </strong>MVCLDG employs a multi-view feature-extraction module that fuses raw electroencephalography with phase information derived from the Hilbert transform via multi-scale inception blocks, thereby capturing both amplitude and phase features. The model then applies domain-alignment and contrastive-learning constraints to reduce distributional discrepancy across domains, compact within-class representations, and enlarge between-class separability. The approach was evaluated on a public Error-Related Negativity (ERN) dataset and a self-collected semantic-syntactic violation dataset; performance was assessed in cross-subject settings, and ablation and visualization analyses were conducted to probe the contributions of components and neurophysiological interpretability.</p><p><strong>Results: </strong>MVCLDG outperformed baseline and representative domain generalization methods in cross-subject ERP recognition without requiring additional target-domain adaptation. Ablation experiments confirmed the effectiveness of each component. Eigen-Class Activation Maps visualizations indicate consistency between the model-attended electrodes and known neurophysiological scalp patterns, supporting both the model's generalization mechanism and its biological interpretability.</p><p><strong>Conclusions: </strong>MVCLDG offers an effective strategy for integrating phase-aware multi-view feature mining with contrastive domain generalization, yielding improved and interpretable cross-subject ERP recognition. The method advances the feasibility of ERP-based closed-loop BCIs that generalize across users.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"221-238"},"PeriodicalIF":2.3,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148338086","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":"Examining the Neural and Behavioral Impact of Accelerated Intermittent Theta Burst Stimulation in People with Opioid Use Disorder Who Smoke Tobacco Cigarettes: A Pilot Study.","authors":"Dylan H Ballard, Thomas G Adams, Rajendra A Morey, Rebika Khanal, Seth S Himelhoch, Gopalkumar Rakesh","doi":"10.1177/21580014261455379","DOIUrl":"10.1177/21580014261455379","url":null,"abstract":"<p><strong>Background: </strong>Novel therapies are needed to improve smoking cessation outcomes in people with opioid use disorder (OUD), as they are far more likely to smoke cigarettes (70-90%) compared to the general population (11.6%) and demonstrate a poorer response to smoking cessation interventions.</p><p><strong>Methods: </strong>This pilot study, intended to be a hypothesis-generating mechanistic investigation, is the first to explore the impact of a single day (four sessions) of accelerated intermittent theta burst stimulation (iTBS) (1800 pulses/session) versus sham iTBS applied to the left dorsolateral prefrontal cortex (L-dlPFC) in people with OUD who smoke tobacco cigarettes (<i>n</i> = 8 received iTBS, <i>n</i> = 7 received sham iTBS). Resting-state functional connectivity was acquired at baseline and after the fourth session. Attentional bias for cigarette and opioid cues, and craving assessments, were completed at baseline, and after the first and fourth sessions.</p><p><strong>Results: </strong>Connectivity between the L-dlPFC seed and a cluster comprising the left anterior supramarginal gyrus showed a significant group × time interaction, with planned comparisons showing a greater increase at follow-up in the iTBS compared with sham iTBS group (<i>t</i>₁₂ = 6.37, <i>β</i> = 0.40, <i>p</i> < 0.001). Cigarette cue attentional bias showed a significant group × session interaction (<i>t</i>₈₀ = 2.34<i>, p</i> = 0.02), with planned comparisons showing a decrease after iTBS and an increase following sham iTBS. No effect of iTBS was observed for opioid cue attentional bias. Cigarette craving decreased in both iTBS and sham groups but did not show a significant group × session interaction.</p><p><strong>Conclusions: </strong>These results are promising but should be interpreted with caution, given the limited sample size, which precluded analyses adjusting for sex or medications for OUD. This pilot study aims to identify neural and behavioral targets for future studies of accelerated iTBS in people with OUD who smoke cigarettes. Future trials could examine the effects of increased doses of iTBS (e.g., more days of accelerated iTBS) to identify dosing to promote smoking cessation among individuals with OUD effectively.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"204-214"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148161405","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":"Meditation Enhances Small-World Network Efficiency: MEG-Based Evidence from Attention and Control Systems.","authors":"Geeta Prem Chandoo Damisetti, C M Markan, Sona Ahuja, Manjari Tripathi","doi":"10.1177/21580014261455602","DOIUrl":"10.1177/21580014261455602","url":null,"abstract":"<p><strong>Introduction: </strong>Brain networks and meditation have recently gained attention, with studies suggesting that more efficiently organized meditation brain networks are linked to better cognitive performance. This efficiency is exemplified in small-world brain networks, which combine local segregation with global integration, facilitating optimal information processing. This study examines the small-world propensity (SWP), a marker of neural efficiency, among three functional brain networks: the default mode network (DMN), fronto-parietal network (FPN), and attention network (AN) in three groups: advanced meditators (AM), beginner meditators (BM), and control meditators (CM).</p><p><strong>Methods: </strong>Using magnetoencephalography (MEG), we recorded 10-min meditation sessions from AM and BM groups practicing Surat-Shabda-Yoga meditation at different stages. The CM (baseline group), with no formal training in meditation, had introductory exposure to \"four chakra meditation\" and practiced the same. SWP was computed using coherence-based connectivity measures across frequencies ranging from 4 to 45 Hz during stable meditative states.</p><p><strong>Results: </strong>Significant differences were observed between meditators and non-meditators, with AM and BM groups compared with the CM group. Specifically, the AN in the AM group compared with CM exhibited higher SWP at the beta frequency range (19 Hz), while the FPN in the BM group compared with the CM showed increased SWP at the theta frequency range (8 Hz).</p><p><strong>Discussion: </strong>These findings highlight how meditation engages the brain's intrinsic network architecture in a frequency- and stage-specific manner, supporting efficient information processing and offering a scientific basis for its cognitive and regulatory benefits.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"169-179"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148223347","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":"Fingerprints Beyond Averages: The Temporal Architecture of Individual Brain Connectivity.","authors":"Young-Eun Lee","doi":"10.1177/21580014261456833","DOIUrl":"10.1177/21580014261456833","url":null,"abstract":"","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"167-168"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148161370","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":"Tinnitus Brain: A Functional Reorganization?","authors":"Marie Detroz, Rajanikant Panda, Audrey Vanhaudenhuyse, Luaba Tshibanda, Steven Laureys, Philippe Lefebvre, Audrey Maudoux","doi":"10.1177/21580014261455378","DOIUrl":"10.1177/21580014261455378","url":null,"abstract":"<p><p><i>Background:</i> Tinnitus is an auditory phantom perception in the absence of any corresponding acoustic stimulus whose pathophysiology remains poorly understood. This study aimed to investigate alterations in the functional organization of the brain in individuals with tinnitus using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory analysis.<i>Methods:</i> We conducted a study including 44 individuals with tinnitus and 32 healthy controls. Using rs-fMRI and graph theory measures, we characterized whole-brain topological properties, including network segregation, integration, small-worldness, and global efficiency. In addition, regional segregation and integration were assessed using clustering coefficient and participation coefficient analyses to identify alterations in brain hub regions.<i>Results:</i> Our findings revealed altered topological properties in the tinnitus brain, particularly in the balance between cerebral segregation and integration, leading to deviations from optimal small-world architecture. We also observed alterations in the topology of specific auditory and nonauditory brain regions associated with phantom sound perception. Notably, patients with tinnitus exhibited a decreased nodal participation coefficient in the thalamus, suggesting reduced connectivity between this region and different functional modules as well as long-range connections.<i>Conclusions:</i> These results suggest that tinnitus is associated with alterations in the functional organization of the brain, leading to disrupted information processing and sensory integration.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"180-192"},"PeriodicalIF":2.3,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148216283","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}