Network Neuroscience最新文献

{"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":"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":3.4,"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":"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":3.4,"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":"Phase-dependent stimulation response is shaped by the brain's dynamic functional connectivity.","authors":"Sophie Benitez Stulz, Samy Castro, Boris Gutkin, Matthieu Gilson, Demian Battaglia","doi":"10.1162/NETN.a.548","DOIUrl":"10.1162/NETN.a.548","url":null,"abstract":"<p><p>External brain stimulation is a promising tool for investigating and altering cognitive processes, with potential clinical applications to the restoration of dysfunctional neural dynamics. In line with experimental observations, we study how the effects of stimulation crucially depend on the ongoing dynamics of the brain, at the local level of the stimulated region but also of global coordinated brain activity. Specifically, we use connectome-based whole-brain computational modeling to explore how the effects of single-pulse stimulation to different regions strongly depend on both the phase of regional oscillatory activity and on the transiently occurring network of functional connectivity at the time of the applied stimulation. Importantly, we show that stimulation has not only state-dependent effects but can also induce global state switching. Lastly, predicting the effect of stimulation by using machine learning shows that functional network-aware measures (i.e., knowledge of either a discrete state of functional connectivity or of a detailed functional connectivity matrix) can increase the performance by up to 40%. Our results suggest that a fine characterization of intrinsic functional connectivity dynamics is essential for improving the reliability of exogenous stimulation.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"475-507"},"PeriodicalIF":3.4,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147786057","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":"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":3.4,"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}

{"title":"Cortical similarity networks in the rat brain: Postnatal development and sensitivity to early life stress.","authors":"Rachel L Smith, Stephen J Sawiak, Lena Dorfschmidt, Ethan G Dutcher, Jolyon A Jones, Joel D Hahn, Olaf Sporns, Larry W Swanson, Paul A Taylor, Daniel R Glen, Jeffrey W Dalley, Francis J McMahon, Armin Raznahan, Petra E Vértes, Edward T Bullmore","doi":"10.1162/NETN.a.546","DOIUrl":"10.1162/NETN.a.546","url":null,"abstract":"<p><p>Network models are a key tool in human neuroscience, and translation into animal models is essential for interrogating mechanistic drivers of network organization. Using magnetic resonance imaging (MRI), we present the first in vivo network representation of the individual rat brain, a key animal model in neuroscience. We measured magnetization transfer ratio (MTR) at each of 53 distinct cortical areas and estimated a cortical similarity network for each scan across two independent cohorts. We characterized normative network development in rats scanned repeatedly between postnatal days 20 (weanling) and 290 (mid-adulthood; <i>N</i> = 47) and then contrasted these findings with a cohort exposed to early life stress (repeated maternal separation [RMS]; <i>N</i> = 40). The normative rat cortical similarity network exhibited biologically meaningful organization, consistent with cytoarchitectonic and tract-tracing data, and displayed complex topological features. Developmental analyses revealed increasing interregional similarity during early postnatal and adolescent periods, followed by divergence in mid-adulthood, particularly within fronto-hippocampal systems. RMS disrupted these trajectories, especially between frontal and parahippocampal regions that were also most dynamic during development and aging. These findings introduce a new network-based methodology for studying cortical organization in a model organism, providing a translational framework to understand how environmental risk factors alter brain network development.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 2","pages":"418-443"},"PeriodicalIF":3.4,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13108504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147785996","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":"The motion sensitivity and predictive utility of different estimates of interregional functional coupling in resting-state functional MRI.","authors":"Kane Pavlovich, James C Pang, Alex Fornito","doi":"10.1162/NETN.a.534","DOIUrl":"10.1162/NETN.a.534","url":null,"abstract":"<p><p>Numerous methods exist for quantifying statistical dependencies, termed \"functional coupling\" (FC), between regional brain activity recorded with resting-state functional magnetic resonance imaging (rs-fMRI). However, their efficacy in mitigating the effects of known sources of noise, such as those induced by participant head motion, and in augmenting effect sizes for brain-wide association studies (BWAS), remains unclear. Here we compared 10 different measures of FC, including correlations, partial correlations, coherence, mutual information, and partial information decomposition, and one measure of effective connectivity (EC; regression dynamic causal modeling), across two independent datasets comprising a total of 1,797 participants (867 males). Each method was evaluated for its ability to mitigate motion-related confounds in FC/EC estimates (assessed via framewise-displacement - edgewise FC correlations) and for its utility in predicting 94 behavioral measures (assessed via cross-validated kernel ridge regression). Our analyses showed that EC was most resistant to motion artifacts but had the weakest behavioral predictions. Conversely, traditional correlation-based methods showed the highest sensitivity to motion, but offered the strongest behavioral prediction across most domains and datasets. Nonetheless, relative differences in predictive accuracies were small, indicating that the use of different FC or EC metrics in rs-fMRI does not significantly impact BWAS effect sizes.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 1","pages":"221-243"},"PeriodicalIF":3.4,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13008380/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515726","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":"Disrupted intrathalamic and thalamocortical structural covariance networks in posttraumatic stress disorder.","authors":"Nick Steele, Ahmed Hussain, Delin Sun, C Lexi Baird, Courtney Russell, Neda Jahanshad, Lauren E Salminen, Miranda Olff, Jessie L Frijling, Dick J Veltman, Saskia B J Koch, Laura Nawijn, Mirjam van Zuiden, Li Wang, Ye Zhu, Gen Li, Dan J Stein, Jonathan Ipser, Sheri Koopowitz, Yuval Neria, Xi Zhu, Orren Ravid, Sigal Zilcha-Mano, Amit Lazarov, Benjamin Suarez-Jimenez, Ashley A Huggins, Jennifer Stevens, Kerry Ressler, Tanja Jovanovic, Sanne J H van Rooij, Negar Fani, Emily L Dennis, David F Tate, David X Cifu, William C Walker, Elisabeth A Wilde, Ivan Rektor, Pavel Říha, Milissa L Kaufman, Lauren A M Lebois, Justin T Baker, Anthony King, Israel Liberzon, Mike Angstadt, Nicholas D Davenport, Seth G Disner, Scott R Sponheim, Thomas Straube, David Hofmann, Guang Ming Lu, Rongfeng Qi, Amit Etkin, Adi Maron-Katz, Xin Wang, Austin Kunch, Hong Xie, Yann Quidé, Wissam El-Hage, Shmuel Lissek, Hannah Berg, Steven E Bruce, Josh Cisler, Marisa Ross, Ryan Herringa, Daniel W Grupe, Jack B Nitschke, Richard J Davidson, Christine Larson, Terri A deRoon-Cassini, Carissa W Tomas, Jacklynn M Fitzgerald, Brandee Feola, Jennifer U Blackford, Bunmi O Olatunji, Geoffrey May, Steven M Nelson, Evan M Gordon, Chadi G Abdallah, Ruth Lanius, Maria Densmore, Jean Théberge, Richard W J Neufeld, Paul M Thompson, Rajendra A Morey","doi":"10.1162/NETN.a.535","DOIUrl":"10.1162/NETN.a.535","url":null,"abstract":"<p><p>The thalamus is a heterogeneous structure crucial for corticocortical communication, affective-perceptual integration, motor preparation, and memory-related functions. Posttraumatic stress disorder (PTSD) is characterized by various symptoms that likely relate to thalamic functions. Group-level and individual differential structural covariance (SC) analyses were conducted on intrathalamic, thalamocortical, and thalamosubcortical volumetric networks by segmenting structural MRI data from 2,784 subjects (PTSD <i>n</i> = 1,306; controls <i>n</i> = 1,478) into 25 thalamic nuclei per hemisphere. We found that PTSD was associated with stronger intrathalamic and thalamocortical network strength and stronger SC between the limbic thalamus and the somatomotor and auditory thalamus. PTSD severity was related to specific regional alterations in the intrathalamic network involving the lateral pulvinar. Comorbid depression severity positively correlated with global intrathalamic alterations, while avoidance symptoms positively correlated with global thalamosubcortical alterations. Hyperarousal symptoms related to altered SC in the thalamocortical network between the reuniens, central medial, paratenial, centromedian, and limitans-suprageniculate nuclei and lateral cortical regions spanning the occipital, temporal, and orbitofrontal cortices. Differential associations between avoidance, hyperarousal, and comorbid depression symptoms and thalamic SC in PTSD suggest that specific thalamic covariance patterns may be involved in unique facets of PTSD symptomatology.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 1","pages":"244-266"},"PeriodicalIF":3.4,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13008379/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515913","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":"An entropic measure of diverse specialization highlights multifunctional neurons in annotated connectomes.","authors":"Sung Soo Moon, Lidia Ripoll-Sánchez, Petra Vértes, William R Schafer, Sebastian E Ahnert","doi":"10.1162/NETN.a.533","DOIUrl":"10.1162/NETN.a.533","url":null,"abstract":"<p><p>The creation and curation of synaptic-level neuronal networks, or connectomes, enables the study of the relationship between neuronal structure and function. Topological characteristics of neuronal networks have been studied extensively. Separately, there have been considerable efforts to classify the morphology, cell types, and lineages of neurons. Here, we introduce a network metric that combines topological analysis with node metadata. This entropic quantity measures the diversity of incoming or outgoing connections to a node in terms of the metadata distribution. We find that in <i>Caenorhabditis elegans</i>, the top-scoring neurons (PVR, RMGL/R, DVA, CEP, ADE, URXR, RIGL, BAG, SMBDL) have known functions that integrate and disseminate multimodal information involved in sensorimotor functions. In the nerve cord of <i>Drosophila melanogaster</i>, we find that top-scoring neurons are embryonic neurons located in the abdominal neuropil, where sensorimotor coordination is required for complex innate behavior such as mating.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 1","pages":"204-220"},"PeriodicalIF":3.4,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13008378/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147515875","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":"Spatiotemporal profiling of functional network overlapping modules in Alzheimer's disease.","authors":"Yue Gu, Ying Lin, Liangfang Li, Junji Ma, Sihan Wei, Zhengjia Dai","doi":"10.1162/NETN.a.516","DOIUrl":"10.1162/NETN.a.516","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is characterized by progressive neural network degradation. In brain functional networks, overlapping module structures provide more accurate representations of brain function than nonoverlapping structures. Since the involvement of overlapping nodes in multiple modules can vary over time, investigating dynamic functional changes in the brain may provide deeper insights into the structural characteristics of these overlapping modules. However, the spatiotemporal dynamics of overlapping modular brain organization remain unclear. We employed resting-state fMRI to explore the overlapping modular organization and dynamic multilayer modules in 64 AD (Age_mean = 74.04) and 61 healthy controls (HC, Age_mean = 74.86) from the Alzheimer's Disease Neuroimaging Initiative. Compared with HC, AD exhibited increased overlapping modules and decreased modularity, with altered nodal overlapping probability, particularly in the superior frontal cortex and hippocampus. Higher nodal overlapping probability correlated with greater flexibility and was associated with larger amyloid deposits. Lasso regression analysis further revealed strong correlations between overlapping nodal characteristics and cognitive performance. Our findings suggest that overlapping nodes are critical components in AD, demonstrating high amyloid deposition, significant functional flexibility, and strong associations to cognitive behavior. These alterations may enhance the understanding of AD pathology and contribute to the development of biomarkers for improved diagnosis and therapeutic strategies.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 1","pages":"185-203"},"PeriodicalIF":3.4,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12956295/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147357182","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":"Neural compensation in persons with HIV and marijuana use: Insights from a reorganized DMN.","authors":"Mohsen Bahrami, Paul J Laurienti, Sheri L Towe, Ryan P Bell, Heather M Shappell, Christina S Meade","doi":"10.1162/NETN.a.513","DOIUrl":"10.1162/NETN.a.513","url":null,"abstract":"<p><p>The interactive effects of HIV and marijuana (MJ) on the brain remain largely unknown, despite the prevalence of cognitive implications in this population. This study examined the impacts of HIV and MJ on brain networks crucial for normal cognitive function. Functional MRI data and a battery of neuropsychological tests from 237 HIV+ and HIV- adults aged 25-59 years, stratified by MJ use, were collected. The following hypotheses were then tested: (a) HIV is associated with widespread disruption of the small-world organization of the default mode network (DMN) that is exacerbated by MJ use; (b) observed differences are reflected in cognitive performance. Clustering coefficient and global efficiency were used to measure small-world organizations. We found significant differences in the DMN's clustering and efficiency between our control group (HIV-MJ-) and the other three groups (HIV+MJ-, HIV-MJ+, and HIV+MJ+). In those with HIV/MJ, the DMN reorganized toward a network explained by efficiency than clustering. Global cognitive performance was associated with this group difference. Unlike the control group, participants with HIV/MJ showed an integrated DMN across all cognitive scores. The higher integrity of the DMN in patients with HIV and MJ use (particularly when co-occurring) across cognitive scores could imply compensation to preserve cognitive function.</p>","PeriodicalId":48520,"journal":{"name":"Network Neuroscience","volume":"10 1","pages":"118-136"},"PeriodicalIF":3.4,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12956298/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147357126","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}