NeuroImage最新文献

{"title":"Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing","authors":"Zeqiang Linli ,&nbsp;Xingcheng Liang ,&nbsp;Zhenhua Zhang ,&nbsp;Kang Hu ,&nbsp;Shuixia Guo","doi":"10.1016/j.neuroimage.2025.121184","DOIUrl":"10.1016/j.neuroimage.2025.121184","url":null,"abstract":"<div><div>Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the absence of uncertainty estimation may pose risks in clinical use. Moreover, current 3D brain age models are intricate, and using 2D slices hinders comprehensive dimensional data integration. Here, we introduced Spectral-normalized Neural Gaussian Process (SNGP) accompanied by 2.5D slice approach for seamless uncertainty integration in a single network with low computational expenses, and extra dimensional data integration without added model complexity. Subsequently, we compared different deep learning methods for estimating brain age uncertainty via the Pearson correlation coefficient, a metric that helps circumvent systematic underestimation of uncertainty during training. SNGP shows excellent uncertainty estimation and generalization on a dataset of 11 public datasets (<em>N</em> = 6327), with competitive predictive performance (MAE=2.95). Besides, SNGP demonstrates superior generalization performance (MAE=3.47) on an independent validation set (<em>N</em> = 301). Additionally, we conducted five controlled experiments to validate our method. Firstly, uncertainty adjustment in brain age estimation improved the detection of accelerated brain aging in adolescents with ADHD, with a 38% increase in effect size after adjustment. Secondly, the SNGP model exhibited OOD detection capabilities, showing significant differences in uncertainty across Asian and non-Asian datasets. Thirdly, the performance of DenseNet as a backbone for SNGP was slightly better than ResNeXt, attributed to DenseNet's feature reuse capability, with robust generalization on an independent validation set. Fourthly, site effect harmonization led to a decline in model performance, consistent with previous studies. Finally, the 2.5D slice approach significantly outperformed 2D methods, improving model performance without increasing network complexity. In conclusion, we present a cost-effective method for estimating brain age with uncertainty, utilizing 2.5D slicing for enhanced performance, showcasing promise for clinical applications.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121184"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143780730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dedifferentiation of brain functional gradient captures cognition performance and stroke occurrence: A UK Biobank study","authors":"Chenye Shen ,&nbsp;Chaoqiang Liu ,&nbsp;Nanguang Chen ,&nbsp;Anqi Qiu","doi":"10.1016/j.neuroimage.2025.121183","DOIUrl":"10.1016/j.neuroimage.2025.121183","url":null,"abstract":"<div><div>Brain functional dedifferentiation, marked by reduced specificity of brain activity or greater similarity of functional connectivity (FC) among networks, is a hallmark of aging. Traditionally, task functional magnetic resonance imaging studies have explored functional dedifferentiation within specific cognitive domains, while FC-based approaches have focused on regional connectivity patterns. Here, we leverage the principal functional gradient to provide a macro-scale and integrative perspective on functional dedifferentiation in aging, offering a novel framework for understanding its relationship with aging, cognition, and disease. We utilized brain images and clinical data from the UK Biobank, comprising 23,578 participants aged 44–82. Linear regression was employed to assess relationships between the network dedifferentiation along the principal functional gradient and age, and cognitive performance across six domains in a normal aging population. We tested interactions between age, sex, and education to assess their influence on age-related dedifferentiation. Logistic regression was applied to classify stroke in participants with stroke and matched normal aging participants. Our findings revealed a reduced principal functional gradient range with age, indicating reduced FC variability of all brain regions. At the network level, the dedifferentiation between the frontoparietal and other networks was strongly linked to aging and cognitive performance. Males exhibited faster dedifferentiation than females across multiple networks. The somatomotor network was most affected by stroke-related dedifferentiation. Validation via covariate-matched subgroups confirmed the robustness of these findings. This research provides macro-scale insights into age-related brain functional changes, highlighting dedifferentiation along the principal gradient as a network-sensitive indicator of aging and the development of stroke.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121183"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Boosting proactive motor control via statistical learning with brain stimulation","authors":"Giulia Ellena ,&nbsp;Federica Contò ,&nbsp;Michele Tosi ,&nbsp;Lorella Battelli","doi":"10.1016/j.neuroimage.2025.121181","DOIUrl":"10.1016/j.neuroimage.2025.121181","url":null,"abstract":"<div><div>Visual statistical regularities are nested patterns of information extracted to build a predictive internal model that guides attentional and motor decisions. Here, we sought to understand the contributions of the left and right frontoparietal areas in modulating the effect of this expectancy implementation on premotor preparation. Healthy subjects were asked to detect a high-contrast stimulus target presented simultaneously with a distractor, with preceding color cues indicating, trial by trial, the pairing between the response hand and the upcoming stimuli locations. Performance was measured at baseline, and immediately after a one-session training on the task. During the training target locations appeared 75% of the time to the right of the distractor, a regularity unnoticed by participants. The training session was paired with unilateral transcranial random noise stimulation (tRNS) or sham stimulation over the left or right frontoparietal cortex in a counterbalanced design. Results showed a significant response bias in reaction times after training, with faster responses for targets to the right of the distractor. This bias was enhanced by right, but not left, frontoparietal stimulation, highlighting a hemispheric asymmetry in proactive motor control. The implicit nature of learning, as evidenced by subjects’ unawareness of probability distributions, underscores how proactive motor control quickly adapts to statistical regularities. Results suggest a dominant role for the right hemisphere in mediating attentional learning effects, with implications for understanding lateralized functions in adaptation of the motor control.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121181"},"PeriodicalIF":4.7,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of electrical conductivity changes during brain functional activity in 3T MRI","authors":"Kyu-Jin Jung ,&nbsp;Chuanjiang Cui ,&nbsp;Soo-Hyung Lee ,&nbsp;Chan-Hee Park ,&nbsp;Ji-Won Chun ,&nbsp;Dong-Hyun Kim","doi":"10.1016/j.neuroimage.2025.121174","DOIUrl":"10.1016/j.neuroimage.2025.121174","url":null,"abstract":"<div><div>Blood oxygenation level-dependent functional magnetic resonance imaging (fMRI) is widely used to visualize brain activation regions by detecting hemodynamic responses associated with increased metabolic demand. Although alternative MRI methods have been employed to monitor functional activities, the investigation of <em>in-vivo</em> electrical property changes during brain function remains limited. In this study, the relationship between fMRI signals and electrical conductivity (measured at the Larmor frequency) changes was explored using phase-based electrical property tomography. Results revealed consistent patterns: conductivity changes showed negative correlations, with conductivity decreasing in functionally active regions whereas <span><math><msub><mi>B</mi><mn>1</mn></msub></math></span> phase mapping exhibited positive correlations around the activation regions. These observations were consistent across the motor and visual cortex activations To further substantiate these findings, electromagnetic radio-frequency simulations that modeled activation states with varying conductivities were conducted, demonstrating trends similar to <em>in-vivo</em> results for <span><math><msub><mi>B</mi><mn>1</mn></msub></math></span> phase and conductivity. Notably, we observed that false-positive activation signals could occur depending on the level of noise and the reconstruction method applied. These findings suggested that <em>in-vivo</em> electrical conductivity changes can indeed be measured during brain activity. However, further investigation is needed to fully understand the underlying mechanisms driving these measurements.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121174"},"PeriodicalIF":4.7,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The cortical architecture representing the linguistic hierarchy of the conversational speech","authors":"Ruhuiya Aili ,&nbsp;Siyuan Zhou ,&nbsp;Xinran Xu ,&nbsp;Xiangyu He ,&nbsp;Chunming Lu","doi":"10.1016/j.neuroimage.2025.121180","DOIUrl":"10.1016/j.neuroimage.2025.121180","url":null,"abstract":"<div><div>Recent studies demonstrate that the brain parses natural language into smaller units represented in lower-order regions and larger units in higher-order regions. Most of these studies, however, have been conducted on unidirectional narrative speech, leaving the linguistic hierarchy and its cortical representation in bidirectional conversational speech unexplored. To address this gap, we simultaneously measured brain activity from two individuals using functional near-infrared spectroscopy (fNIRS) hyperscanning while they engaged in a naturalistic conversation. Using a Pre-trained Language Model (PLM) and Representational Similarity Analysis (RSA), we demonstrated that conversational speech, jointly produced by two interlocutors in a turn-taking manner, exhibits a linguistic hierarchy, characterized by a boundary effect between linguistic units and an incremental context effect. Furthermore, a gradient pattern of shared cortical representation of the linguistic hierarchy was identified at the dyadic rather than the individual level. Interpersonal neural synchronization (INS) in the left superior temporal cortex was associated with turn representation, whereas INS in the medial prefrontal cortex was linked to topic representation. These findings further validated the distinctiveness of linguistic units of different sizes. Together, our results provide original evidence for the linguistic hierarchy and the underlying cortical architecture during a naturalistic conversation, extending the hierarchical nature of natural language from unidirectional narrative speech to bidirectional conversational speech.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121180"},"PeriodicalIF":4.7,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing cognitive abilities through transcutaneous auricular vagus nerve stimulation: Findings from prefrontal functional connectivity analysis and virtual brain simulation","authors":"Sora An ,&nbsp;Se Jin Oh ,&nbsp;Shinhee Noh ,&nbsp;Sang Beom Jun ,&nbsp;Jee Eun Sung","doi":"10.1016/j.neuroimage.2025.121179","DOIUrl":"10.1016/j.neuroimage.2025.121179","url":null,"abstract":"<div><div>Recent studies have indicated the potential of transcutaneous auricular vagus nerve stimulation (taVNS) as an intervention for cognitive decline. In this study, we systematically analyzed the effects of taVNS on cognitive enhancement from the perspective of brain networks, by combining functional near-infrared spectroscopy (fNIRS) signal analysis with virtual brain simulations. Behavioral experiments with older adults demonstrated that participants with low baseline performance experienced significant improvements in working memory performance following taVNS, while those with high baseline performance tended to decline. This pattern was closely associated with functional connectivity (FC) in the prefrontal cortex (PFC) concurrently measured during the behavioral tasks, i.e., task performance correlated with FC in the PFC, particularly in the medial PFC (mPFC). Moreover, the changes in performance due to taVNS, which varied based on baseline performance, exhibited a notable alignment with the FC changes in the mPFC. These findings were further explored through virtual brain simulations. The simulation results demonstrated that the brain's functional state could vary depending on the network coupling parameter—capable of reflecting loss of structural brain connectivity associated with aging—and that the modulation effects induced by taVNS may also differ based on those functional states. Current results indicate that the efficacy of taVNS interventions for cognitive enhancement may vary according to the pre-intervention structural and functional states of individual brains. Therefore, the development of personalized optimization strategies for taVNS intervention is crucial, and digital brain research holds significant promise in advancing this field.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121179"},"PeriodicalIF":4.7,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling complex brain dynamics during movie viewing via deep recurrent autoencoder model","authors":"Kexin Wang ,&nbsp;Limei Song ,&nbsp;Zhaowei Li ,&nbsp;Liting Wang ,&nbsp;Xiaowei He ,&nbsp;Yudan Ren ,&nbsp;Jinglei Lv","doi":"10.1016/j.neuroimage.2025.121177","DOIUrl":"10.1016/j.neuroimage.2025.121177","url":null,"abstract":"<div><div>Naturalistic stimuli have become an effective tool to uncover the dynamic functional brain networks triggered by cognitive and emotional real-life experiences through multimodal and dynamic stimuli. However, current research predominantly focused on exploring dynamic functional connectivity generated via chosen templates under resting-state paradigm, with relatively limited investigation into the dynamic functional interactions among large-scale brain networks. Moreover, these studies might overlook the longer time-scale adaptability and information transmission that occur over extended periods during naturalistic stimuli. In this study, we introduced an unsupervised deep recurrent autoencoder (DRAE) model combined with a sliding window approach, effectively capturing the brain's long-term temporal dependencies, as measured in functional magnetic resonance imaging (fMRI), when subjects viewing a long-duration and emotional film. The experimental results revealed that naturalistic stimuli can induce dynamic large-scale brain networks, of which functional interactions covary with the development of the film's narrative. Furthermore, the dynamic interactions among brain networks were temporally synchronized with specific features of the movie, especially with the emotional arousal and valence. Our study provided novel insight to the underlying neural mechanisms of dynamic functional interactions among brain regions in an ecologically valid sensory experience.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"310 ","pages":"Article 121177"},"PeriodicalIF":4.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143743077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An interaction-centric approach for quantifying eye-to-eye reciprocal interaction","authors":"Ray Lee ,&nbsp;Paul Sajda ,&nbsp;Nim Tottenham","doi":"10.1016/j.neuroimage.2025.121175","DOIUrl":"10.1016/j.neuroimage.2025.121175","url":null,"abstract":"<div><div>This study presents an interaction-centric framework for analytically investigating brain-to-brain dynamics during eye contact, advancing beyond the traditional spectator model. The foundation of the interactor approach is to delineate the interaction. To achieve this, simultaneous brain activity engaged in eye contact was captured using hyperscanning fMRI. The BOLD responses were first divided into eye-to-eye reciprocal interaction and eye-to-face non-reciprocal communication based on the experimental design; then the reciprocal interaction response was further differentiated into sensory-based (exogenous) and mind-based (endogenous) components to characterize agentic interaction. The proposed interactor approach not only determines interaction from dyadic brain states but also computes emergent interactive brain states arising from the interaction. To achieve these, reciprocal interactive fMRI responses were quantified into an interaction matrix, from which interaction-induced communication channels were identified using Correspondence Analysis, and information flow within those channels was measured with Mutual Information. The advantage of the interactor approach is its ability to reveal emergent dyadic brain states that a spectator approach cannot fully unravel. When applied to parent-child eye contact, this method confirmed existing developmental findings, clarified previous inconsistencies, and uncovered new insights into how reciprocal social engagement shapes brain function.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121175"},"PeriodicalIF":4.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143742559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novelty modulates proactive and reactive cognitive control modes: Evidence from ERP and EEG data","authors":"Qianqian Li ,&nbsp;Tianlong Chen ,&nbsp;Lixia Wang ,&nbsp;Hongshan Gu ,&nbsp;Bi Ying Hu ,&nbsp;Chuanhua Gu ,&nbsp;Zongkui Zhou","doi":"10.1016/j.neuroimage.2025.121178","DOIUrl":"10.1016/j.neuroimage.2025.121178","url":null,"abstract":"<div><div>Novelty refers to the quality of an idea or product that is new or unusual. It has been shown to influence a broad range of cognitive processes, such as increasing arousal and facilitating working memory. However, no studies have directly investigated the effects of novelty on cognitive control, particularly on the trade-off between proactive and reactive cognitive control. The present study employed an adapted AX Continuous Performance Task (AX-CPT) combined with electroencephalography (EEG) to investigate the impact of novelty on proactive and reactive control modes. The behavioral results showed that reaction times in BX trials were longer under novel conditions than common conditions, indicating that participants may rely more on reactive control and/or rely less on proactive control when influenced by novelty. The EEG results showed smaller effects of cue-P3 and cue-locked theta-ERS under novelty, suggesting that novelty might decrease proactive control, including the decreased maintenance and utilization of contextual information. Moreover, in the novel conditions, the effect of probe-locked theta-ERS was greater, while the effect of probe-P3 was smaller. This indicates that novelty may enhance reactive control, including increased conflict monitoring and reduced response inhibition cost. The findings suggest that exposure to novelty can influence how individuals balance proactive and reactive control, potentially causing a bias towards reactive control.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"311 ","pages":"Article 121178"},"PeriodicalIF":4.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143742978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altered brain network dynamics during rumination in remitted depression","authors":"Su Shu ,&nbsp;Wenwen Ou ,&nbsp;Mohan Ma ,&nbsp;Hairuo He ,&nbsp;Qianqian Zhang ,&nbsp;Mei Huang ,&nbsp;Wentao Chen ,&nbsp;Aoqian Deng ,&nbsp;Kangning Li ,&nbsp;Zhenman Xi ,&nbsp;Fanyu Meng ,&nbsp;Hui Liang ,&nbsp;Sirui Gao ,&nbsp;Yilin Peng ,&nbsp;Mei Liao ,&nbsp;Li Zhang ,&nbsp;Mi Wang ,&nbsp;Jin Liu ,&nbsp;Bangshan Liu ,&nbsp;Yumeng Ju ,&nbsp;Yan Zhang","doi":"10.1016/j.neuroimage.2025.121176","DOIUrl":"10.1016/j.neuroimage.2025.121176","url":null,"abstract":"<div><div>Rumination is a known risk factor for depression relapse. Understanding its neurobiological mechanisms during depression remission can inform strategies to prevent relapse, yet the temporal dynamics of brain networks during rumination in remitted depression remain unclear. Here<strong>,</strong> we collected rumination induction fMRI data from 42 patients with remitted depression and 41 healthy controls (HCs). Using an energy landscape approach, we investigated the temporal dynamics of brain networks during rumination. The appearance frequency (AF) and transition frequency (TF) metrics were defined to quantify the dynamic properties of brain states. Patients during remission showed higher levels of rumination than HCs. Both groups exhibited four brain states during rumination, which consisted of complementary network group activation (states 1 and 2, states 3 and 4). In patients, the AFs of and reciprocal TFs between states 1 and 2 during rumination were significantly increased, while AFs of states 3 and 4 and reciprocal TFs involving states 1–3, 1–4, 2–3, and 2–4 were decreased, both when compared to HCs and relative to patients themselves during distraction. Moreover, we found that for patients, the AF of state 1 was negatively correlated with rumination levels and marginally positively associated with attention, while the AF of state 2 was negatively associated with performance on attention tasks. Our study revealed altered dynamic characteristics of brain states composed of network groups during rumination in remitted depression. Additionally, the findings suggest that heightened self-focus linked to rumination may impair the brain's ability to efficiently allocate attentional resources.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"310 ","pages":"Article 121176"},"PeriodicalIF":4.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143742148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}