Network Neuroscience最新文献

{"title":"An evaluation of the efficacy of single-echo and multi-echo fMRI denoising strategies.","authors":"Toby Constable, Jeggan Tiego, Kane Pavlovich, Arshiya Sangchooli, Priscilla Thalenberg Levi, Bree Hartshorn, Jessica Kwee, Kate Fortune, Kate Thompson, Sam Brown, James McLauchlan, Nancy Ong Tran, Rebecca O'Neill, Mark A Bellgrove, Alex Fornito","doi":"10.1162/NETN.a.547","DOIUrl":"https://doi.org/10.1162/NETN.a.547","url":null,"abstract":"<p><p>Resting-state functional magnetic resonance imaging (rsfMRI) is widely used to study brain-wide functional connectivity (FC). However, the resulting signals are highly noise sensitive, and the best strategies for mitigating this noise remains unclear. In 358 healthy individuals, we compared 60 multi-echo (ME) and 30 single-echo (SE) rsfMRI preprocessing pipelines across six measures of data quality and associated effect sizes in FC-based prediction models of personality and cognition (cross-validated kernel ridge regression). ME pipelines generally outperformed SE pipelines, but no single pipeline excelled at both denoising and behavioral prediction. Using a heuristic scheme to rank pipelines across benchmarks, ME optimum combination (OC) with ME independent component analysis (ICA), ICA-FMRIB's ICA-based Xnoiseifier (FIX), and with head motion, cerebrospinal fluid, and white matter and gray matter signal regression, performed best when only considering denoising efficacy metrics. ME OC with ICA-FIX and head motion parameter regression performed best when only considering behavioral prediction results. ME OC with Automatic Removal of Motion Artifacts (AROMA) ICA, head motion parameter regression and Regressor Interpolation at Progressive Time Delays (RIPTiDe) performed best when aggregating across all evaluation metrics. These results favor ME acquisitions but show that no single denoising pipeline should be considered optimal for all purposes.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"444-474"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108510/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786039","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":"Restoring oscillatory dynamics in Alzheimer's disease: A laminar whole-brain model of serotonergic psychedelic effects.","authors":"Jan C Gendra, Edmundo Lopez-Sola, Francesca Castaldo, Èlia Lleal-Custey, Roser Sanchez-Todo, Jakub Vohryzek, Ricardo Salvador, Ralph G Andrzejak, Giulio Ruffini","doi":"10.1162/NETN.a.540","DOIUrl":"https://doi.org/10.1162/NETN.a.540","url":null,"abstract":"<p><p>Classical serotonergic psychedelics show promise in addressing neurodegenerative disorders such as Alzheimer's disease by modulating pathological brain dynamics. However, the precise neurobiological mechanisms underlying their effects remain elusive. This study introduces a personalized whole-brain model built upon a laminar neural mass framework to elucidate these effects. Using multimodal neuroimaging data from 30 subjects diagnosed with mild to moderate Alzheimer's disease, we simulate the impact of serotonin 2A receptor activation, characteristic of psychedelics, on cortical dynamics. By modulating the excitability of layer 5 pyramidal neurons, our models reproduce hallmark changes in EEG power spectra observed under psychedelics, including alpha power suppression and gamma power enhancement. These spectral shifts are shown to correlate strongly with the regional distribution of serotonin 2A receptors. Furthermore, simulated EEG reveals increased complexity and entropy, suggesting restored network function. These findings underscore the potential of serotonergic psychedelics to reestablish healthy oscillatory dynamics in the prodromal and early phases of Alzheimer's disease and offer mechanistic insights into their potential therapeutic effects in neurodegenerative disorders.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"303-328"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786099","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":"Distributed cortical network dynamics of binocular convergent eye movements in humans.","authors":"Farzin Hajebrahimi, Suril Gohel, Michael W Cole, Tara L Alvarez","doi":"10.1162/NETN.a.549","DOIUrl":"https://doi.org/10.1162/NETN.a.549","url":null,"abstract":"<p><p>Neuroimaging studies in humans have localized brain functions to specific brain regions, but a recent shift toward distributed network-based models of brain function promises deeper insights into the network processes that generate brain functionality. Resting-state functional connectivity provides a rich mapping of the brain's network architecture, linking with both underlying structure and task-evoked responses across the whole brain. In this study, we utilized a model based on propagation of task-evoked activations over resting-state functional connectivity networks to identify cortical contributions to localized functional brain activations associated with binocular convergent eye movements. Binocular vision is crucial for daily routine activities, with its impairment leading to significant challenges in daily life. The distributed network-level mechanisms of binocular convergent eye movements remain unknown. Results showed that mapping activity flow over brain connections accurately generated brain activations associated with convergent eye movements, which were distinct from those observed during control tasks. The visual and dorsal attention networks dominated the propagation of activations through resting-state connections during convergent eye movements. In conclusion, highly distributed network pathways are involved in convergent eye movements, with some pathways contributing much more than others, providing important implications for future clinical models of binocular dysfunction.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"531-566"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108499/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786003","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":"High-resolution Bayesian Virtual Epileptic Patient using neural field models.","authors":"Anirudh Nihalani Vattikonda, Meysam Hashemi, Marmaduke M Woodman, Jean-Didier Lemarechal, Daniele Daini, Fabrice Bartolomei, Viktor Jirsa","doi":"10.1162/NETN.a.543","DOIUrl":"https://doi.org/10.1162/NETN.a.543","url":null,"abstract":"<p><p>Epilepsy remains a significant medical challenge, particularly in drug-resistant cases where surgical intervention may be the only viable treatment option. Identifying the epileptogenic zone, the brain region responsible for seizure initiation, is a critical step in surgical planning. Combining dynamical system models, machine learning, and the neuroimaging data of epileptic patients in the so-called Bayesian Virtual Epileptic Patient (VEP) framework has previously been shown to be a promising approach for identifying the epileptogenic zone. However, previous studies employed coupled neural mass models to describe the whole-brain seizure dynamics and, hence, could only provide a highly coarse spatial estimate of the epileptogenic zone. In this study, we propose an extension of the Bayesian VEP to a neural field model, which can improve the spatial resolution by several orders. Performing model inversion using neural field models is a challenging task as the parameter space is very high dimensional, and it becomes computationally expensive to compute gradients. We demonstrate that by using pseudospectral methods and spherical harmonic transforms, it is feasible to perform model inversion on a neural field extension. We found that the high-resolution Bayesian VEP not only improves the spatial resolution but also significantly reduces the number of false positives.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"374-399"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786075","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":"High brain network system segregation is differentially linked with cognitive performance across the life span.","authors":"Cameron N Calder, Carl Helmick, Javeria Ali Hashmi","doi":"10.1162/NETN.a.542","DOIUrl":"https://doi.org/10.1162/NETN.a.542","url":null,"abstract":"<p><p>Healthy aging is marked by changes in both cognitive performance and the organization of brain networks. Declines in cognition have been linked to reductions in system segregation (SS), as older adults typically exhibit less segregated functional networks than younger adults. While lower segregation has been associated with diminished cognitive abilities, it remains unclear how individual variability in SS contributes to cognitive outcomes across the lifespan. Here, we examine relationships between SS and three cognitive domains (semantic, executive, episodic memory) using resting-state fMRI data from 179 younger (18-29 years) and 117 older adults (60-89 years). SS was measured globally and for specific networks using Schaefer's 7-network parcellation. Our findings confirmed a global age-related reduction in SS, particularly impacting the somatomotor, ventral attention, and frontoparietal networks. This reduction in global SS mediated negative effects of age group on semantic and executive performance. When examining younger and older groups separately, we found that higher SS was associated with better semantic performance in both groups, while observing a similar positive association with executive performance only in older adults, suggesting that executive function becomes increasingly dependent on preserved network architecture with age. Maintaining SS may therefore be critical for supporting healthy cognitive aging.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"352-373"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786113","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":"Intrinsic brain network dynamics modulated by neural stimulation to cerebellum.","authors":"Kanika Bansal, Zaira Cattaneo, Viola Oldrati, Chiara Ferrari, Emily D Grossman, Javier O Garcia","doi":"10.1162/NETN.a.541","DOIUrl":"https://doi.org/10.1162/NETN.a.541","url":null,"abstract":"<p><p>The cerebellum, with its distinctive architecture and extensive cortical connections, has long been recognized for its highly structured interconnectivity with the cortex and has been proposed as part of a larger circuit that shapes brain network dynamics. Here, we evaluate dynamic network reconfigurations in resting-state fMRI connectivity pre- and post-noninvasive inhibitory repetitive transcranial magnetic stimulation targeting the right Crus I of the cerebellum. Using dynamic community detection to evaluate the stimulation's effect on modular network structures, we characterize the network properties by which cerebellar stimulation spreads through the cortex. We find that: (a) the <i>flexibility</i>, or the likelihood of network nodes to change module allegiances, increased post stimulation; (b) the dynamic patterns by which module allegiances emerged and evolved were highly individual and did not follow a single functional prototype; and (c) the cerebellar nodes had connectivity properties of integrators for distinct network modules. These results are consistent with the idea that cerebellum is pivotal in modulating distributed cortical activity by restructuring the integration and segregation of neural networks. This integrative capacity of the cerebellum may underlie its proposed role in coordinating neural systems, including those supporting higher cognitive function.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"329-351"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786146","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":"Structure-function multilayer network integration and cognition in multiple sclerosis.","authors":"Lucas C Breedt, Giuseppe Pontillo, Fernando A N Santos, Chris Vriend, Ferran Prados, Alle Meije Wink, Alvino Bisecco, Alessandro Cagol, Massimiliano Calabrese, Marco Castellaro, Sara Collorone, Rosa Cortese, Nicola De Stefano, Christian Enzinger, Massimo Filippi, Michael A Foster, Antonio Gallo, Gabriel Gonzalez-Escamilla, Cristina Granziera, Sergiu Groppa, Einar A Høgestøl, Sara Llufriu, Eloy Martinez-Heras, Elisabeth Solana, Silvia Messina, Marcello Moccia, Gro O Nygaard, Jacqueline Palace, Daniela Pinter, Mara A Rocca, Ahmed Toosy, Paola Valsasina, Olga Ciccarelli, Eva M Strijbis, Frederik Barkhof, Menno M Schoonheim, Linda Douw","doi":"10.1162/NETN.a.545","DOIUrl":"https://doi.org/10.1162/NETN.a.545","url":null,"abstract":"<p><p>People with multiple sclerosis (MS) often present with cognitive deficits that cannot fully be attributed to focal brain alterations. Whole-brain network changes show stronger relations, but MS network insights have mostly focused on either structural or functional (single-layer) networks, while recent work has shown the importance of multilayer frontoparietal network integration for cognition. Here, we explored the cognitive relevance of multilayer integration of the frontoparietal network in relapsing-remitting MS (<i>n</i> = 780) using diffusion and resting-state fMRI. Cognitive relations were first assessed for nodal multilayer eigenvector centrality, averaged over frontoparietal network nodes as a measure of integration, and post hoc for mean eccentricity for both single layer and multilayers. Higher multilayer frontoparietal network centrality was associated with worse Symbol Digit Modalities Test (SDMT) performance (<i>β</i> = -.117, <i>p</i> = .005). Mean eccentricity of single-layer diffusion (<i>β</i> = -.123, <i>p</i> < .001) and multilayer networks (<i>β</i> = .085, <i>p</i> = .018) were associated with SDMT performance. However, results could not be replicated using a different anatomical parcellation. This study showed that cognition in MS is related to multilayer network parameters. Nevertheless, correlations were weak and atlas specific, suggesting that a binary structure-function multilayer network approach is not particularly relevant as a correlate of cognition in MS.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"400-417"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108497/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786111","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":"Metastability of resting-state bold fMRI as a reliable biomarker of individual brain dynamics: An interrogation of within-subject variability as a function of total acquisition time.","authors":"Hiba Sheheitli, Robert Hermosillo, Gracie Grimsrud, Thomas Madison, Oscar Miranda Dominguez, Steven Nelson, Damien Fair, Ziad Nahas","doi":"10.1162/NETN.a.537","DOIUrl":"https://doi.org/10.1162/NETN.a.537","url":null,"abstract":"<p><p>Metastability of BOLD fMRI signals is a commonly used proxy of brain dynamics in behavioral and clinical studies. To date, little has been done to assess the confidence with which we can use estimates of metastability as reliable biomarkers of individual brain state. We analyze whole-brain and network-specific metastability for a highly sampled individual brain (84 sessions taken over 18 months) and quantify the within-subject reliability for the metrics as a function of the amount of data used, which we find to be comparable to that seen for static functional connectivity. As considerable variability is observed across networks in the required amount of data, we combine the networks' metrics in one novel feature vector that exhibits an order of magnitude improvement in reliability. We then test reproducibility by analyzing the Midnight Scan Club dataset (10 subjects imaged over 10 consecutive days). Finally, we examine the susceptibility to change of the proposed metastability measure in another dataset examining brain dynamics under the effect of psilocybin. We conclude that the networks' metastability feature vector exhibits strong within-subject reliability that renders it a promising candidate for the study of individual-specific biomarkers of brain dynamics and potential targets for precision neuromodulation.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"281-302"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108507/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786118","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":"Increased sensitivity in identifying language-related functional connectivity using jackknife resampling analyses.","authors":"Jinqing Liang, Divesh Thaploo, Adebiyi Sobitan, Kristen Wingert, Atsuko Kurosu, Stein Acker, Ahmad Shafiei, Ninet Sinaii, Nadia M Biassou","doi":"10.1162/NETN.a.536","DOIUrl":"https://doi.org/10.1162/NETN.a.536","url":null,"abstract":"<p><p>Functional connectivity (FC) analyses of task-based fMRI (tbfMRI) often rely on static correlation methods that average signal relationships over time. While widely used, these methods may miss transient but meaningful neural interactions. In this study, we investigated whether jackknife resampling-a technique that systematically omits one time point at a time-enhances sensitivity in detecting language-related FC networks during an auditory comprehension task. We analyzed surface-based FC networks in 172 healthy young adults from the Human Connectome Project. FC matrices were computed across 68 cortical regions of interest, and statistically significant edges were identified using Bonferroni correction. We compared FC networks derived from a traditional static correlation approach with those obtained using jackknife resampling, applying an edge consistency threshold to retain only the most stable connections across time points. The static method identified 75 significant language-related FCs. Jackknife-based analyses recovered all of these and revealed 24 additional connections or edges (eight left-hemispheric, five right-hemispheric, 11 interhemispheric; <i>p</i> < 0.001), including well-established language regions such as the middle temporal gyrus and posterior cingulate cortex. Jackknife resampling enhances detection of robust, task-relevant FCs, offering a promising alternative for modeling language networks and improving neurocomputational representations in both research and clinical settings.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"267-280"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786069","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":"Evaluating oscillatory mechanisms underlying flexible neural communication in the human brain.","authors":"Varun Madan Mohan, Thomas F Varley, Anthony M Harris, Robin F H Cash, Caio Seguin, Andrew Zalesky","doi":"10.1162/NETN.a.550","DOIUrl":"https://doi.org/10.1162/NETN.a.550","url":null,"abstract":"<p><p>How the brain orchestrates the flow of information between its multiple functional units flexibly, quickly, and accurately remains a fundamental question in neuroscience. Multiple theories identify neural oscillations as a likely basis for this process. However, a lack of empirical validation of proposed theories, particularly at the whole-brain scale, has hampered consensus on oscillatory principles governing neural communication, limiting our understanding of a process central to perception and cognition and its integration into experiments and clinical applications. Here, we empirically validate previously proposed neural-oscillatory communication mechanisms in the human brain-specifically involving power and inter-areal phase coherence-at the whole-brain scale. We do this by estimating the dependence of inferred communication on oscillatory measures that have been theorized to facilitate communication, in source-localized resting-state magnetoencephalography recordings. We find that power and phase coherence in the alpha, beta, and high-gamma bands track communication better than others. Crucially, the relation between communication and oscillatory measures varied across regions, indicating spatial heterogeneity in routing mechanisms. Notably, power and coherence-based principles tracked communication patterns of unimodal regions better than those of transmodal regions. In sum, these findings suggest that the human brain implements regionally specific communication mechanisms with complex neural-oscillatory dependence.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"508-530"},"PeriodicalIF":3.1,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108498/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786042","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}