Network Neuroscience最新文献

Brain network reconfiguration during reward prediction error processing. 奖赏预测错误处理过程中的脑网络重构。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-08-28 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.544

Kamil Bonna, Oliver J Hulme, Simon R Steinkamp, David Meder, Maria E C van der Weij, Włodzisław Duch, Karolina Finc

{"title":"Brain network reconfiguration during reward prediction error processing.","authors":"Kamil Bonna, Oliver J Hulme, Simon R Steinkamp, David Meder, Maria E C van der Weij, Włodzisław Duch, Karolina Finc","doi":"10.1162/NETN.a.544","DOIUrl":"10.1162/NETN.a.544","url":null,"abstract":"Learning from experience is theorized to be driven by reward prediction error (RPE) signals that reflect updates to our expectations of reward. Despite numerous studies on the neural correlates of RPEs, the question of how large-scale networks (LSN) in the brain reconfigure in response to an RPE learning signal remains open. Here, we examine how functional networks change in response to RPEs depending on the context. In our study, participants performed a probabilistic reversal learning task while we acquired fMRI data in two experimental settings: reward-seeking and punishment-avoiding. Participants' behavior was best explained by models with different learning rates for positive and negative RPEs. Furthermore, no evidence was found for context-dependent learning rates. Using behaviorally fitted RPE models, we performed a whole-brain network analysis. This analysis revealed classical reward structures, where striatal reward networks emerge as modules when the community structure is examined at a finer resolution, and a ventromedial prefrontal network emerges at a coarser resolution. Using the same behavioral model, we found that, compared with negative RPEs, positive RPEs increased within-network integration and decreased between-community integration. This indicates that there are distinctly different neural processes for positive and negative RPEs.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"853-883"},"PeriodicalIF":3.4,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13569333/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148956997","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}

引用次数: 0

Effects of light on brain-state dynamics and energy landscape. 光对脑状态动力学和能量景观的影响。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-08-25 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.586

Rui Zhang, Nora D Volkow

{"title":"Effects of light on brain-state dynamics and energy landscape.","authors":"Rui Zhang, Nora D Volkow","doi":"10.1162/NETN.a.586","DOIUrl":"10.1162/NETN.a.586","url":null,"abstract":"Light influences human cognition and behavior, and neuroimaging studies show that brain activity is modulated by light intensity. However, how light affects temporal brain-state transitions and the control energy required for these transitions remains unclear. To investigate this, we applied a network control theory approach to fMRI data collected from 20 healthy participants who performed an auditory discrimination task under four light intensities. Despite similar task performance, higher light intensity increased the number of transitions between brain states. Increasing light intensity enhanced the occurrence of a visual network dominated brain state, while decreasing the occurrence of brain states characterized by suppressed default mode activity and elevated frontoparietal activity. Furthermore, light intensity affected transition probabilities among different brain states contributed by redistributions of energy demands with the dorso-posterior thalamus appearing to play a key role in mediating light-related effects. Regionally, higher light intensity was associated with a trend toward reduced control energy in the visual network; frontal, cingulate, and insular cortices; and caudate and task-related regions, while showing a trend toward increased control energy in the somatomotor network and temporal pole. These findings suggest that high-intensity light may enhance neural efficiency and flexibility by redistributing control energy demands across brain regions.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"838-852"},"PeriodicalIF":3.4,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13569334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148957014","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}

引用次数: 0

Functional connectivity is linked to symbolic BOLD patterns: Replication, extension, and clinical application of the human "Complexome". 功能连接与符号BOLD模式有关：人类“复杂体”的复制、扩展和临床应用。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-08-25 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.572

Amy Romanello, Nina von Schwanenflug, Michelle Franka, Friedemann Paul, Harald Prüss, Stephan Krohn, Carsten Finke

{"title":"Functional connectivity is linked to symbolic BOLD patterns: Replication, extension, and clinical application of the human \"Complexome\".","authors":"Amy Romanello, Nina von Schwanenflug, Michelle Franka, Friedemann Paul, Harald Prüss, Stephan Krohn, Carsten Finke","doi":"10.1162/NETN.a.572","DOIUrl":"10.1162/NETN.a.572","url":null,"abstract":"Functional connectivity (FC) quantifies the temporal coherence of blood-oxygen-level-dependent (BOLD) signals across brain regions. Recently, the information-theoretic \"complexome\" framework has linked FC to coinciding \"complexity drops\": transient moments in which regional BOLD signals simultaneously become regular. Here, we replicate this relationship in an independent dataset and extend the framework by (a) integrating it with signal cofluctuation analysis; (b) extending the previous binary concept of simultaneous complexity drops to a continuous, threshold-free calculation based on a temporal unwrapping procedure; (c) providing evidence of clinical relevance in the model disease of anti-N-methyl-D-aspartate-receptor encephalitis; and (d) deriving a new measure of pairwise dissimilarity in local BOLD patterns. This \"index of pattern incongruency\" (IPI) explains clinically relevant FC reductions and maps onto distinct associations with cognition beyond FC. These findings show that global FC is closely related to local patterns within underlying BOLD signals, strengthening the link between complexity dynamics and the brain's functional organization as a large-scale network.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"761-786"},"PeriodicalIF":3.4,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13569379/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148956980","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}

引用次数: 0

Parallel multilink group joint ICA (pmg-jICA): Fusion of 3D structural and 4D functional data across multiple resting fMRI networks. 平行多链接组关节ICA (pmg-jICA)：在多个静息fMRI网络中融合三维结构和四维功能数据。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-08-25 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.575

K M Ibrahim Khalilullah, Souvik Phadikar, Oktay Agcaoglu, Jing Sui, Marlena Duda, Tülay Adali, Vince D Calhoun

{"title":"Parallel multilink group joint ICA (pmg-jICA): Fusion of 3D structural and 4D functional data across multiple resting fMRI networks.","authors":"K M Ibrahim Khalilullah, Souvik Phadikar, Oktay Agcaoglu, Jing Sui, Marlena Duda, Tülay Adali, Vince D Calhoun","doi":"10.1162/NETN.a.575","DOIUrl":"10.1162/NETN.a.575","url":null,"abstract":"Integrating neuroimaging data enhances our understanding of the brain. Structural magnetic resonance imaging (sMRI) offers high-resolution anatomical detail, while functional MRI (fMRI) captures dynamic neural activity. Combining these modalities can reveal significant structure-function relationships in the brain. However, existing approaches typically link sMRI to only a single fMRI network, overlooking the spatial complexity of multiple networks and thereby missing distributed structure-function relationships. To address this limitation, we present parallel multilink group joint ICA (pmg-jICA), a data-driven framework that fuses gray matter images from sMRI with multiple intrinsic fMRI networks within a single model. pmg-jICA captures cross-network structure-function coupling, preserves subject-specific variability, and enables robust group-level statistical analyses. To demonstrate the approach, we applied pmg-jICA to an Alzheimer's disease (AD) dataset, recovering linked structural and functional components for 53 brain networks. Notably, patients with AD exhibited alterations in subcortical, cognitive control and visual regions. Importantly, the subject loadings enabled the computation of functional network connectivity, revealing additional alterations in subcortical, visual, and cognitive control systems. Overall, our results demonstrate that pmg-jICA overcomes key limitations of existing multimodal fusion techniques, yielding deeper insights into structure-function disruptions in AD and potentially offering a flexible framework for studying other neurological and psychiatric disorders.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"787-808"},"PeriodicalIF":3.4,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13569335/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148957051","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}

引用次数: 0

States of dynamic connectivity flow in temporal multiplex networks: A case study in human epilepsy and postictal aphasia. 时间多重网络的动态连接流状态：人类癫痫和后发失语症的案例研究。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-08-25 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.576

Nicola Pedreschi, Agnès Trebuchon, Alain Barrat, Demian Battaglia

{"title":"States of dynamic connectivity flow in temporal multiplex networks: A case study in human epilepsy and postictal aphasia.","authors":"Nicola Pedreschi, Agnès Trebuchon, Alain Barrat, Demian Battaglia","doi":"10.1162/NETN.a.576","DOIUrl":"10.1162/NETN.a.576","url":null,"abstract":"We present a methodological framework for analyzing multifrequency dynamic functional connectivity (dFC) in electrophysiological recordings. The approach characterizes not only the magnitude of network reconfiguration over time but also whether these changes are spatially random or, instead, spatially organized in ways that drive a slower reconfiguration of modular structure. We define a generative null model of multiscale connectivity fluctuations that differ in their degree of spatiotemporal organization, and we describe dFC flows through the joint assessment of (a) instantaneous reconfiguration speed and (b) the extent and quality of ongoing modular reorganization. Different combinations of these features delineate distinct \"flow styles,\" ranging from more liquid to more frozen dynamics. As a case study, we apply this framework to stereo-electroencephalography recordings from epileptic patients. We identify transitions between dynamic \"allegiance states,\" whose flow styles closely mirror those of the null model. Seizure onset is associated with a pronounced slowing of dFC speed, while a specific postictal regime combines low speed with highly frozen allegiance and aligns most strongly with clinician-annotated aphasia. These pilot results suggest that temporal multiplex network analyses can reveal transient, frequency-specific network regimes linked to symptom expression and offers a generalizable tool for dissecting fast network dynamics in intracranial recordings.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"809-837"},"PeriodicalIF":3.4,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13569336/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148957012","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}

引用次数: 0

Higher-order statistics for constructing centered edge functional connectivity. 构造中心边函数连通性的高阶统计量。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-07-27 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.570

Junting Wang, Youngheun Jo, Junwei Lu, Richard Betzel, Ji Zhu, Kean Ming Tan

{"title":"Higher-order statistics for constructing centered edge functional connectivity.","authors":"Junting Wang, Youngheun Jo, Junwei Lu, Richard Betzel, Ji Zhu, Kean Ming Tan","doi":"10.1162/NETN.a.570","DOIUrl":"10.1162/NETN.a.570","url":null,"abstract":"Functional connectivity is often constructed to understand functional organizations in neural systems, where the brain regions and their pairwise interactions are viewed as nodes and edges, respectively. In practice, functional connectivity is commonly estimated via the correlation of pairs of brain regions. One limitation is that the correlation coefficient captures only the pairwise linear dependence relationship between pairs of nodes and may fail to capture complex higher-order relationships. Recently, a novel concept known as edge-centric functional connectivity (eFC) has been introduced to measure interactions between pairs of edges based on the cofluctuation of two nodal time series, offering a new perspective for understanding brain networks. Nevertheless, eFC considers the absolute levels of edge time series, that is, their mean values, in estimation. If the parameter of interest is the covariation between a pair of edges, incorporating mean values of edge time series can introduce bias or deviation, resulting in a skewed estimation. In this manuscript, we propose an alternative approach to estimate the unbiased covariation between pairs of edges, termed centered edge functional connectivity (ceFC), with theoretical foundations. We demonstrate that the proposed estimator is consistent with a sufficient sample size or number of time frames. Additionally, we develop a multiple hypothesis testing framework with a controlled false discovery rate to evaluate the strength of the unbiased covariation among edges. Furthermore, we employ thresholding to obtain a thresholded estimator that has been shown to converge to the true ceFC matrix in high-dimensional settings in which the number of nodes is much larger than the number of samples or time frames. We validate the finite sample performance of the proposed methods via numerical studies and a data application using the Midnight Scan Club dataset.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"706-737"},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13418521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148622165","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}

引用次数: 0

Neural dynamics of mindfulness training: A longitudinal EEG network analysis of focused attention and open monitoring meditation. 正念训练的神经动力学：集中注意力和开放监测冥想的纵向脑电图网络分析。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-07-27 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.555

Yanli Lin, Marne L White, Jihong Zhang, Todd S Braver

{"title":"Neural dynamics of mindfulness training: A longitudinal EEG network analysis of focused attention and open monitoring meditation.","authors":"Yanli Lin, Marne L White, Jihong Zhang, Todd S Braver","doi":"10.1162/NETN.a.555","DOIUrl":"10.1162/NETN.a.555","url":null,"abstract":"Neural oscillatory activity within the alpha and theta bands have long been considered putative markers of state mindfulness, yet understanding of their functional role has been limited by the challenges of linking objective brain indices with subjective experience. To address this gap, the current study applied longitudinal network analysis to a unique dataset from 16 novices who completed up to 24 laboratory training sessions of both focused attention (FA) and open monitoring (OM) meditation, during which both EEG and self-report measures of state mindfulness quality were collected. This approach enabled the parsimonious characterization of both cross-lagged temporal (across-session) and contemporaneous (within-session) influences of regional spectral power on state mindfulness. The analysis revealed distinguishable neurophenomenological network structures for each practice, providing data-driven support for their theoretical differentiation. These distinctions emerged alongside shared commonalities to both practices, including strong autoregressive effects for state mindfulness, consistent with training-related skill acquisition, and opposing regional influences of frontal versus posterior alpha power. Taken together, these findings challenge monolithic interpretations of meditation-related EEG activity, advancing a more nuanced neurophenomenological approach wherein the functional significance of neural activity is dynamically situated within the specific type and time course of training.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"655-682"},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13418251/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148622247","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}

引用次数: 0

Regional activity and interregional functional connectivity uniquely contribute to social cognitive judgments during movie-watching. 区域活动和区域间功能连接对观影过程中的社会认知判断有独特的贡献。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-07-27 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.571

Roberto C French, Haily Merritt, Colleen Hughes, Richard Betzel, Anne C Krendl

{"title":"Regional activity and interregional functional connectivity uniquely contribute to social cognitive judgments during movie-watching.","authors":"Roberto C French, Haily Merritt, Colleen Hughes, Richard Betzel, Anne C Krendl","doi":"10.1162/NETN.a.571","DOIUrl":"10.1162/NETN.a.571","url":null,"abstract":"Understanding how the brain gives rise to social cognition has been a key goal of neuroimaging research. Both changes in regional activation as well as functional connectivity have been implicated as potential mechanisms underlying social cognition, but the two have rarely been examined concurrently. Moreover, because the neural processes underlying social cognition are dynamic, developing approaches to capture dynamic changes in regional activity and functional connectivity are critical. Here, we describe a novel analysis approach that captures both regional activity and dynamic functional connectivity simultaneously during a naturalistic, socially focused movie-watching task. We found that both regional activation and functional connectivity were uniquely related to awkwardness, a judgment associated with social faux pas detection and theory of mind. Regional activation within sensorimotor networks was positively associated with awkwardness, whereas activation in the default network was negatively associated. Models including functional connectivity accounted for unique variance beyond models with activity alone. Specifically, dynamic functional connectivity between networks, primarily the frontoparietal control network, was positively associated with awkwardness. Together, these findings suggest that both dynamic regional brain activity and functional connectivity each uniquely contribute to complex and dynamic social judgments.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"738-760"},"PeriodicalIF":3.4,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13418520/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148621978","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}

引用次数: 0

NeuroMark-DyFICA: NeuroMark dynamic frequency-informed ICA with high-frequency spatial filtering for windowed fMRI analysis. NeuroMark- dyfica：带有高频空间滤波的NeuroMark动态频率信息ICA，用于带窗fMRI分析。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-07-20 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.551

Neda Behzadfar, Armin Iraji, Najme Soleimani, Tulay Adali, Vince Calhoun

{"title":"NeuroMark-DyFICA: NeuroMark dynamic frequency-informed ICA with high-frequency spatial filtering for windowed fMRI analysis.","authors":"Neda Behzadfar, Armin Iraji, Najme Soleimani, Tulay Adali, Vince Calhoun","doi":"10.1162/NETN.a.551","DOIUrl":"10.1162/NETN.a.551","url":null,"abstract":"Fine-scale spatial dynamics within functional brain networks manifest as high spatial-frequency variations that conventional independent component analysis (ICA) methods fail to capture. These subtle changes may carry critical information about transient connectivity and disordered brain function. We developed NeuroMark-DyFICA (dynamic frequency-informed ICA), a novel framework to enhance detection of spatiotemporal variability in fMRI data. It integrates three stages: dynamic NeuroMark ICA across sliding windows to estimate time-varying, spatially constrained networks; high-pass spatial filtering to emphasize fine-scale spatial features; and group-level ICA to extract refined dynamic components with subject-specific mixing weights. Unlike prior NeuroMark applications or conventional dynamic ICA, NeuroMark-DyFICA establishes a reproducible latent space of high-frequency dynamics, uniquely capturing transient, fine-scale reconfigurations of network topography. Validation using a controlled 2D simulation demonstrated reliable detection of subtle spatial shifts mimicking pathology, which conventional ICA failed to recover. Applying to resting-state fMRI from schizophrenia patients and healthy controls, multiple networks were estimated. We highlight six representative systems (thalamus, auditory, visual/fusiform, middle frontal, default mode, cerebellum). Results revealed two complementary abnormalities in schizophrenia: an imbalance between inactive and hyper-engaged states and altered convergence among dynamic states. NeuroMark-DyFICA reveals fine-grained spatiotemporal disruptions in brain networks, offering mechanistic insights and potential biomarkers for psychiatric disorders.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"567-593"},"PeriodicalIF":3.4,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13418253/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148622197","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}

引用次数: 0

Microscale dysfunction and mesoscale compensation in degenerating neuronal networks. 退化神经网络的微尺度功能障碍和中尺度代偿。

IF 3.4 3区医学

Network Neuroscience Pub Date : 2026-07-20 eCollection Date: 2026-01-01 DOI: 10.1162/NETN.a.552

Vegard Fiskum, Nicolai Winter-Hjelm, Nicholas Christiansen, Axel Sandvig, Ioanna Sandvig

{"title":"Microscale dysfunction and mesoscale compensation in degenerating neuronal networks.","authors":"Vegard Fiskum, Nicolai Winter-Hjelm, Nicholas Christiansen, Axel Sandvig, Ioanna Sandvig","doi":"10.1162/NETN.a.552","DOIUrl":"10.1162/NETN.a.552","url":null,"abstract":"Progressive neurodegenerative diseases involve neuronal dysfunction across cellular, circuit, and whole-brain levels. Despite differences in anatomical origins, vulnerable neuronal subtypes, and specific misfolded proteins, these diseases share key features. In presymptomatic phases, neural networks engage compensatory processes to maintain function, including increased centralization and reliance on a rich-club of hub nodes. While such mechanisms have supporting evidence in some disorders, they remain less established in amyotrophic lateral sclerosis (ALS), limiting understanding of potential shared presymptomatic responses. To address this, we investigated structural and functional properties of ALS patient-derived motor neuron networks compared with healthy controls using longitudinal multielectrode array recordings and graph theory-based analysis. We observed microscale dysfunction marked by TAR DNA-binding protein 43 proteinopathy, hyperactivity, and reduced spike amplitude. Structurally, ALS networks exhibited neurite hypertrophy, suggesting attempts to form new connections. Mesoscale analyses revealed functional reconfigurations, including increased rich-club connectivity and network assortativity, indicating compensatory centralization. Our findings provide novel evidence that ALS network features can be recapitulated in in vitro models, and that these networks progressively become more centralized to preserve computational capacity, imposing growing demands on hub nodes and predisposing them to further damage. These results support models proposing common network reconfiguration mechanisms across neurodegenerative diseases.","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 3","pages":"594-612"},"PeriodicalIF":3.4,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13418254/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148622180","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}

引用次数: 0