NeuroImage最新文献

{"title":"Dissociable effects of perceived control on reward-related neural dynamics under risk and ambiguity","authors":"Shiting Chen ,&nbsp;Menglin Wu ,&nbsp;Jianbiao Zhao ,&nbsp;Guanglong Liu ,&nbsp;Wendeng Yang ,&nbsp;Ya Zheng","doi":"10.1016/j.neuroimage.2025.121067","DOIUrl":"10.1016/j.neuroimage.2025.121067","url":null,"abstract":"<div><div>Perceived control plays a crucial role in risk-taking behavior, but its neural effect on reward dynamics in risky and ambiguous decision making remains unclear. Here, we addressed this issue by measuring participants’ (N = 40) EEG activity while they were performing a wheel-of-fortune task. Participants either made choices themselves (a high control condition) or followed the computer's choice (a low control condition) under risky or ambiguous decision contexts. Behavioral and rating data showed a stronger control effect in the risky compared to the ambiguous decision context. In parallel, we found an effect of perceived control on choice evaluation (indexed by the cue-P3) in the risky but not ambiguous context. However, the control effect was more pronounced during feedback anticipation (indexed by the stimulus-preceding negativity) and outcome appraisal (indexed by delta oscillation) in the ambiguous context compared to the risky context. Together, our findings suggest that experiencing control alters reward dynamics in uncertain decision making, with dissociable effects between risk and ambiguity.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121067"},"PeriodicalIF":4.7,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066666","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":"Caloric labels do not influence taste pleasantness and neural responses to erythritol and sucrose","authors":"Aleksandra Budzinska ,&nbsp;Laura Byl ,&nbsp;Fabienne Teysseire ,&nbsp;Emilie Flad ,&nbsp;Patrick Dupont ,&nbsp;Bettina Wölnerhanssen ,&nbsp;Anne Christin Meyer-Gerspach ,&nbsp;Lukas Van Oudenhove ,&nbsp;Nathalie Weltens","doi":"10.1016/j.neuroimage.2025.121061","DOIUrl":"10.1016/j.neuroimage.2025.121061","url":null,"abstract":"<div><h3>Introduction</h3><div>The beneficial effects of substituting sugar with non-caloric sweeteners (NCSs) remain uncertain due to the mismatch between their rewarding sweet taste and lack of energy content. Functional magnetic resonance imaging (fMRI) studies indicate an influence of cognitive processes (<em>e.g.</em>, beliefs, expectations) on reward system responses to NCSs, thereby changing their rewarding properties. We measured the impact of cognitive influences about the caloric content on brain responses and liking ratings to erythritol, a natural NCS with satiating properties, <em>versus</em> sugar (<em>i.e.</em>, sucrose).</div></div><div><h3>Methods</h3><div>We performed a within-subject, single-blind, counterbalanced fMRI study in 30 healthy males (mean ± SD: age 23 ± 0.6 years, BMI 22.5 ± 0.3 kg/m²). Concentrations of erythritol were individually titrated to match the perceived sweetness intensity of a 16 % sucrose solution. During the scan, sucrose and equisweet erythritol solutions were delivered as 1 mL sips with either correct or purposefully incorrect \"low-calorie\" or \"high-calorie\" labels. After each sip, participants rated sweetness liking. Water with a \"water\" label was used as the control condition.</div></div><div><h3>Results</h3><div>A 2 × 2 ANOVA revealed lower liking ratings for erythritol than sucrose (<em>p</em> &lt; 0.0001), but no main effect of the label, nor label-by-sweetener interaction. General Linear Model (GLM) analysis of brain responses at FDR <em>q</em> &lt; 0.05 showed no main effect of sweetener nor label, nor a label-by-sweetener interaction. However, several patterns of brain activity mediated the differences in subjective liking ratings between the sweeteners. Moreover, different neural responses were found for <em>sucrose vs. water</em> in parcel-wise, SVM, and ROI-based analyses, whereas for <em>erythritol vs. water</em>, only the latter two showed differences. Lastly, sucrose induced a stronger craving signature response compared to erythritol, driven by the pattern specific to drug craving.</div></div><div><h3>Conclusion</h3><div>Liking ratings were lower for erythritol than sucrose, and they were unaffected by the caloric label. There were no differences in neural responses between the sweeteners and labels, except in comparisons with water.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121061"},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066466","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 the content of frontal feedback in challenging object recognition","authors":"Nastaran Darjani ,&nbsp;Jalaledin Noroozi ,&nbsp;Mohammad-Reza A. Dehaqani","doi":"10.1016/j.neuroimage.2025.121058","DOIUrl":"10.1016/j.neuroimage.2025.121058","url":null,"abstract":"<div><div>Object recognition under challenging real-world conditions, including partial occlusion, remains an enduring focus of investigation in cognitive visual neuroscience. This study addresses the insufficiently elucidated neural mechanisms and temporal dynamics involved in this complex process, concentrating on the persistent challenge of recognizing objects obscured by occlusion. Through the analysis of human EEG data, we decode feedback characteristics within frontotemporal networks, uncovering intricate neural mechanisms during occlusion coding, with a specific emphasis on processing complex stimuli such as occluded faces. Our findings elucidate the critical role of frontal feedback in the late processing stage of occluded face recognition, contributing to enhanced accuracy in identification. Temporal dynamics reveal distinct characteristics in both early and late processing stages, allowing the discernment of two unique types of occlusion processing that go beyond visual features, incorporating higher-order associations. The increased synchronized activity between frontal and temporal areas during the processing of occluded stimuli underscores the importance of frontotemporal coordination in challenging real-world conditions. A comparative analysis with macaque IT cortex recordings validates the contribution of the frontal cortex in the late stage of occluded face processing. Notably, the observed disparity between human EEG and two deep computational models, both with and without the consideration of feedback connection, emphasize the necessity for expanding models to accurately simulate frontal feedback.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121058"},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066795","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":"In-vivo high-resolution χ-separation at 7T","authors":"Jiye Kim ,&nbsp;Minjun Kim ,&nbsp;Sooyeon Ji ,&nbsp;Kyeongseon Min ,&nbsp;Hwihun Jeong ,&nbsp;Hyeong-Geol Shin ,&nbsp;Chungseok Oh ,&nbsp;Robert J. Fox ,&nbsp;Ken E. Sakaie ,&nbsp;Mark J. Lowe ,&nbsp;Se-Hong Oh ,&nbsp;Sina Straub ,&nbsp;Seong-Gi Kim ,&nbsp;Jongho Lee","doi":"10.1016/j.neuroimage.2025.121060","DOIUrl":"10.1016/j.neuroimage.2025.121060","url":null,"abstract":"<div><div>A recently introduced quantitative susceptibility mapping (QSM) technique, <em>χ</em>-separation, offers the capability to separate paramagnetic (<em>χ_para</em>) and diamagnetic (<em>χ_dia</em>) susceptibility distribution within the brain. <em>In-vivo</em> high-resolution mapping of iron and myelin distribution, estimated by <em>χ</em>-separation, could provide a deeper understanding of brain substructures, assisting the investigation of their functions and alterations. This can be achieved using 7T MRI, which benefits from a high signal-to-noise ratio and susceptibility effects. However, applying <em>χ</em>-separation at 7T presents difficulties due to the requirement of an R₂ map, coupled with issues such as high specific absorption rate (SAR), large B₁ transmit field inhomogeneities, and prolonged scan time. To address these challenges, we developed a novel deep neural network, R2PRIMEnet_7T, designed to convert a 7T R₂* map into a 3T R₂′ map. Building on this development, we present a new pipeline for <em>χ</em>-separation at 7T, enabling us to generate high-resolution <em>χ</em>-separation maps from multi-echo gradient-echo data. The proposed method is compared with alternative pipelines, such as an end-to-end network and linearly-scaled R₂′, and is validated against <em>χ</em>-separation maps at 3T, demonstrating its accuracy. The 7T <em>χ</em>-separation maps generated by the proposed method exhibit similar contrasts to those from 3T, while 7T high-resolution maps offer enhanced clarity and detail. Quantitative analysis confirms that the proposed method surpasses the alternative pipelines. The proposed method results well delineate the detailed brain structures associated with iron and myelin. This new pipeline holds promise for analyzing iron and myelin concentration changes in various neurodegenerative diseases through precise structural examination.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121060"},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066887","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":"Fiber length distribution characterizes the brain network maturation during early school-age","authors":"Yanlin Yu ,&nbsp;Qing Cai ,&nbsp;Longnian Lin ,&nbsp;Chu-Chung Huang","doi":"10.1016/j.neuroimage.2025.121066","DOIUrl":"10.1016/j.neuroimage.2025.121066","url":null,"abstract":"<div><div>Environmental and social changes during early school age have a profound impact on brain development. However, it remains unclear how the brains of typically-developing children adjust white matter to optimize network topology during this period. This study proposes fiber length distribution as a novel nodal metric to capture the continuous maturation of brain network. We acquired dMRI data from N = 30 typically developing children in their first year of primary school and a one-year follow-up. We assessed the longitudinal changes in fiber length distribution, characterized by the median length of connected fibers for each brain region. The length median was positively correlated with degree and betweenness centrality, while negatively correlated with clustering coefficient and local efficiency. From ages 7 to 8, we observed significant decreases in length median in the temporal, superior parietal, anterior cingulate, and medial prefrontal cortices, accompanied by a reduction in long-range connections and an increase in short-range connections. Meta-analytic decoding revealed that the widespread decrease in length median occurred in regions responsible for sensory processing, whereas a more localized increase in length median was observed in regions involved in memory and cognitive control. Finally, simulation tests on healthy adults further supported that the decrease in long-range connections and increase in short-range connections contributed to enhanced network segregation and integration, respectively. Our results suggest that the dual process of short- and long-range fiber changes reflects a cost-efficient strategy for optimizing network organization during this critical developmental stage.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121066"},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066673","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":"Specialization for different memory dimensions in brain activity evoked by cued recollection","authors":"Federica Procida ,&nbsp;Matteo Frisoni ,&nbsp;Maria Giulia Tullo ,&nbsp;Annalisa Tosoni ,&nbsp;Mauro Gianni Perrucci ,&nbsp;Piero Chiacchiaretta ,&nbsp;Roberto Guidotti ,&nbsp;Carlo Sestieri","doi":"10.1016/j.neuroimage.2025.121068","DOIUrl":"10.1016/j.neuroimage.2025.121068","url":null,"abstract":"<div><div>Cued recollection involves the retrieval of different features of the encoded event. Previous research has shown that the recollection of complex events jointly recruits the Default Mode and the Frontoparietal Control networks, but the degree to which activity within these networks varies as a function of the particular memory dimension (e.g., the “when-what-where” information) remains largely unknown. In the present functional Magnetic Resonance Imaging (fMRI) study, human participants retrieved specific information about a previously encoded TV show to assess the veracity of detailed sentences along four memory dimensions (i.e., object and character details, spatial layouts, temporal sequences, verbal dialogues). A common activity for all dimensions was observed in a left-lateralized network of regions that largely overlaps with the Frontoparietal Control Network (FPCN), including the lateral prefrontal, lateral superior parietal, and lateral temporal cortex. Instead, a larger degree of specialization for different memory dimensions was observed within the Default Mode Network (DMN), particularly in its posterior nodes. Dimension-related specificity in both networks was associated with memory performance across subjects. Finally, a clear leftward asymmetry was observed in the DMN for all dimensions except for the temporal one, whereas the FPCN showed a bilateral activation across dimensions. The present results generally support the view that specific memory information is processed by a mosaic of regions within large portions of the associative cortex involved in higher-order mnemonic functions.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121068"},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066889","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":"Corrigendum to “Extended homogeneous field correction method based on oblique projection in OPM-MEG” [NeuroImage 306(2025) 120991]","authors":"Fulong Wang ,&nbsp;Fuzhi Cao ,&nbsp;Yujie Ma ,&nbsp;Ruochen Zhao ,&nbsp;Ruonan Wang ,&nbsp;Nan An ,&nbsp;Min Xiang ,&nbsp;Dawei Wang ,&nbsp;Xiaolin Ning","doi":"10.1016/j.neuroimage.2025.121044","DOIUrl":"10.1016/j.neuroimage.2025.121044","url":null,"abstract":"","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121044"},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059839","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":"Clinical and neurophysiological predictors of the functional outcome in right-hemisphere stroke","authors":"Francesco Di Gregorio ,&nbsp;Giada Lullini ,&nbsp;Silvia Orlandi ,&nbsp;Valeria Petrone ,&nbsp;Enrico Ferrucci ,&nbsp;Emanuela Casanova ,&nbsp;Vincenzo Romei ,&nbsp;Fabio La Porta","doi":"10.1016/j.neuroimage.2025.121059","DOIUrl":"10.1016/j.neuroimage.2025.121059","url":null,"abstract":"<div><h3>Objective</h3><div>The aim of the present study is to examine the relationship between EEG measures and functional recovery in right-hemisphere stroke patients.</div></div><div><h3>Methods</h3><div>Participants with stroke (PS) and neurologically unimpaired controls (UC) were enrolled. At enrolment, all participants were assessed for motor and cognitive functioning with specific scales (motricity index, trunk control test, Level of Cognitive Functioning, and Functional Independence Measure (FIM). Moreover, EEG data were recorded. At discharge, participants were re-tested with the FIM</div></div><div><h3>Results</h3><div>Powers in the delta, theta, alpha, and beta bands and connectivity within the fronto-parietal network were compared between groups. Then, the between-group discriminative EEG measures and the motor/cognitive scales were used to feed a machine learning algorithm to predict FIM scores at discharge and the length of hospitalization (LoH). Higher delta, theta, and beta and impaired connectivity were found in PS compared to UC. Moreover, motor/cognitive functioning, beta power, and fronto-parietal connectivity predicted the FIM score at discharge and the LoH (accuracy=73.2 % and 85.2 % respectively).</div></div><div><h3>Conclusions</h3><div>Results show that the integration of motor/cognitive scales and EEG measures can reveal the rehabilitative potentials of PS predicting their functional outcome and LoH.</div></div><div><h3>Significance</h3><div>Synergistic clinical and electrophysiological models can support rehabilitative decision-making.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121059"},"PeriodicalIF":4.7,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066665","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":"Beyond averaging: A transformer approach to decoding event related brain potentials","authors":"Philipp Zelger ,&nbsp;Manuel Arnold ,&nbsp;Sonja Rossi ,&nbsp;Josef Seebacher ,&nbsp;Franz Muigg ,&nbsp;Simone Graf ,&nbsp;Antonio Rodríguez-Sánchez","doi":"10.1016/j.neuroimage.2025.121049","DOIUrl":"10.1016/j.neuroimage.2025.121049","url":null,"abstract":"<div><div>The objective of this study is to assess the potential of a transformer-based deep learning approach applied to event-related brain potentials (ERPs) derived from electroencephalographic (EEG) data. Traditional methods involve averaging the EEG signal of multiple trials to extract valuable neural signals from the high noise content of EEG data. However, this averaging technique may conceal relevant information. Our investigation focuses on determining whether a transformer-based deep learning approach, specifically utilizing attention maps, an essential component of transformer networks, can provide deeper insights into ERP data compared to traditional averaging-based analyses.</div><div>We investigated the data of an experiment on loudness perception. In the study, 29 normal-hearing participants between 18 and 30 years were presented with acoustic stimuli at five different sound levels between 65 and 95 dB and provided their subjective loudness rating, which was categorized as ”too loud” and ”not too loud”. During the sound presentation, EEG signals were recorded.</div><div>A convolutional transformer was trained to categorize the EEG data into the two classes (”not too loud” and ”too loud”). The classifier exhibited exceptional performance, achieving over 86 % accuracy and an Area under the Curve (AUC) of up to 0.95.</div><div>Through the utilization of the trained networks, attention maps were generated. Those attention maps provided insights into the time windows relevant for classification within the EEG data. The attention maps above all showed a focus on the time window around 150 to 200 ms, where the average based analysis did not indicate relevant potentials.</div><div>Employing these attention maps, we were able to gain new perspectives on the ERPs, discovering the attention maps potential as a tool for delving deeper into the analysis of event-related potentials.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121049"},"PeriodicalIF":4.7,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143047387","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 brain-gut microbiota network (BGMN) is correlated with symptom severity and neurocognition in patients with schizophrenia","authors":"Runlin Peng ,&nbsp;Wei Wang ,&nbsp;Liqin Liang ,&nbsp;Rui Han ,&nbsp;Yi Li ,&nbsp;Haiyuan Wang ,&nbsp;Yuran Wang ,&nbsp;Wenhao Li ,&nbsp;Shixuan Feng ,&nbsp;Jing Zhou ,&nbsp;Yuanyuan Huang ,&nbsp;Fengchun Wu ,&nbsp;Kai Wu","doi":"10.1016/j.neuroimage.2025.121052","DOIUrl":"10.1016/j.neuroimage.2025.121052","url":null,"abstract":"<div><div>The association between the human brain and gut microbiota, known as the “brain-gut-microbiota axis”, is involved in the neuropathological mechanisms of schizophrenia (SZ); however, its association patterns and correlations with symptom severity and neurocognition are still largely unknown. In this study, 43 SZ patients and 55 normal controls (NCs) were included, and resting-state functional magnetic resonance imaging (rs-fMRI) and gut microbiota data were acquired for each participant. First, the brain features of brain images and functional brain networks were computed from rs-fMRI data; the gut features of gut microbiota abundance and the gut microbiota network were computed from gut microbiota data. Second, we propose a novel methodology to construct an individual brain-gut microbiota network (BGMN) for each participant by combining the brain and gut features via multiple strategies. Third, discriminative models between SZ patients and NCs were built using the connectivity matrices of the BGMN as input features. Moreover, the correlations between the most discriminative features and the scores of symptom severity and neurocognition were analyzed in SZ patients. The results showed that the best discriminative model between SZ patients and NCs was achieved using the connectivity matrices of the BGMN when all the brain and gut features were integrated, with an accuracy of 0.90 and an area under the curve value of 0.97. The most discriminative features were related primarily to the genera <em>Faecalibacterium</em> and <em>Collinsella</em>, in which the genus <em>Faecalibacterium</em> was linked to the visual system and subcortical cortices and the genus <em>Collinsella</em> was linked to the default network and subcortical cortices. Furthermore, parts of the most discriminative features were significantly correlated with the scores of neurocognition in the SZ patients. The methodology for constructing individual BGMNs proposed in this study can help us reveal the associations between the brain and gut microbiota and understand the neuropathology of SZ.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"308 ","pages":"Article 121052"},"PeriodicalIF":4.7,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059841","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}