NeuroImage最新文献

{"title":"Retraction notice to \"Transcriptional Correlates of Frequency-Dependent Brain Functional Activity Associated with Symptom Severity in Degenerative Cervical Myelopathy\" [NeuroImage 284 (2023) 120451].","authors":"Xing Guo, Jie Li, Qian Su, Jiajun Song, Cai Cheng, Xu Chu, Rui Zhao","doi":"10.1016/j.neuroimage.2026.121936","DOIUrl":"10.1016/j.neuroimage.2026.121936","url":null,"abstract":"","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121936"},"PeriodicalIF":4.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147777164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of downsampling on data quality, univariate measurement and multivariate pattern analysis in event-related potential research.","authors":"Guanghui Zhang, Xinran Wang, Ying Xin, Fengyu Cong, Weiqi He, Wenbo Luo","doi":"10.1016/j.neuroimage.2026.121981","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.121981","url":null,"abstract":"<p><p>The choice of sampling rate is a critical preprocessing step in event-related potential (ERP) research, yet its impact on different analytic approaches remains underexplored. In this study, we systematically evaluated how downsampling affects data quality measured via Standardized Measurement Error (SME), conventional univariate ERP metrics (mean amplitude, peak amplitude, peak latency, and 50% area latency), and multivariate pattern analysis (MVPA; decoding). We analyzed seven commonly studied ERP components: P3, N400, N170, N2pc, mismatch negativity, error-related negativity, and lateralized readiness potential collected from neurotypical young adults. Across omnibus analyses, sampling rate did not produce significant global effects on data quality, conventional ERP metrics, or decoding performance within the tested range (64-1024 Hz). However, exploratory pairwise comparisons revealed selective, measure-specific differences at lower sampling rates. In particular, latency-based measures such as 50% area latency showed increased SME at 64 Hz, suggesting reduced temporal precision under coarse sampling. Effect sizes for most ERP measures remained stable at 128 Hz and above, with noticeable attenuation primarily at 64 Hz. In contrast, multivariate decoding performance was highly robust across sampling rates, with both classification accuracy and effect sizes remaining stable even at 64 Hz. Together, these findings indicate that sampling rate does not exert a systematic influence on ERP or decoding metrics within the commonly used range, although very low sampling rates may selectively affect latency-sensitive measures. For studies focusing on conventional ERP analyses, moderate-to-high sampling rates are advisable when precise temporal estimates are required. In contrast, lower sampling rates may be sufficient for decoding analyses when fine-grained temporal precision is not essential. For researchers analyzing ERP data with similar components, intra-individual variability levels, and participant populations as in this study, following these recommendations should yield robust statistical power.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121981"},"PeriodicalIF":4.5,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147841008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of attention mechanisms on cerebellar and basal ganglia activity during vocal emotion decoding.","authors":"Leonardo Ceravolo, Marine Thomasson, Ioana Medeleine Constantin, Emma Stiennon, Émilie Chassot, Jordan Pierce, Alexandre Cionca, Didier Grandjean, Lukas Sveikata, Frédéric Assal, Julie Péron","doi":"10.1016/j.neuroimage.2026.121980","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.121980","url":null,"abstract":"<p><p>Emotional prosody processing involves a widespread network of brain regions, but the specific roles of the cerebellum and basal ganglia in explicit and implicit tasks are not well known or understood. This study investigated how the cerebellum and basal ganglia contribute to explicit (emotion categorization) and implicit (gender categorization) processing of emotional prosody, namely when attention is directly versus implicitly oriented towards the emotion of the voice stimuli, respectively. Twenty-eight healthy French-speaking participants (average age: 65 years old) underwent high-resolution functional MRI while performing explicit and implicit vocal emotion processing tasks. Neuroimaging results revealed-and replicated-that both tasks recruited a widespread network, including the superior temporal cortex, inferior frontal cortex, primary motor and somatosensory cortices, basal ganglia, and cerebellum. The explicit task elicited stronger activations in the basal ganglia (caudate nucleus, putamen) and cerebellar regions (Crus I/II, lobules VI, VIIb, and X), consistent with higher cognitive control demands. In contrast, the implicit task was associated with activations in cerebellar lobules IV-V, VI, VIII, and IX, along with the thalamus. Regression-based functional connectivity analyses further illustrate connectivity between the right cerebellar lobule IX and the putamen, as well as the cerebellar vermis (XII), particularly during implicit processing. These findings highlight the distinct contributions of the cerebellum and basal ganglia to emotional prosody processing, with explicit tasks engaging associative and cognitive control networks, while implicit tasks rely more on sensorimotor and automatic neural processing mechanisms.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121980"},"PeriodicalIF":4.5,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147840959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nonlinear shift along the sensorimotor-association-axis in brain responses to task performance.","authors":"Yuqi Yuan, Bohan Zhang, Kyle Perkins, Fan Cao","doi":"10.1016/j.neuroimage.2026.121978","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.121978","url":null,"abstract":"<p><p>In the literature of cognitive neuroscience, researchers tend to assume a linear relationship between brain activation level and task performance; however, conflicting findings have been reported in different studies. Therefore, there may be a non-linear relationship between task performance and brain activation if a full range of task performance is considered. In the current study, using the Human Connectome Project (HCP) dataset, we examined the relationship between brain activation (i.e., beta values) and working memory performance in four conditions (i.e., faces, body parts, tools and places). We found a gradual change along the sensorimotor-association (S-A) axis, with the higher-rank regions showing greater concavity (an inverted U-shaped curve) than the lower-rank regions only in the face and body part conditions. In the tool and place condition, very few high-order regions show a relationship with performance; therefore, the association with S-A ranking is missing. Instead, in the place condition, many regions showed a convex pattern with task performance. Moreover, the inflection point is above the average performance in the concave regions and below the average in the convex regions. In summary, our study revealed a novel functional property of the brain in response to task performance along the S-A axis.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"334 ","pages":"121978"},"PeriodicalIF":4.5,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147840447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graded prefrontal-sensory connectivity underlies cross-modal hierarchical control.","authors":"Taehyun Yoo, Hyeon-Ae Jeon","doi":"10.1016/j.neuroimage.2026.121977","DOIUrl":"10.1016/j.neuroimage.2026.121977","url":null,"abstract":"<p><p>Does the rostro-caudal architecture of the prefrontal cortex (PFC) generalize to support hierarchical control across sensory modalities? To address this question, we used functional magnetic resonance imaging while participants performed three cue-based tasks integrating auditory and visual modalities, requiring policy abstraction from auditory cues to motor responses, visual features, or visual dimensions. Behaviorally, increasing abstraction and complexity produced robust costs in accuracy and reaction time, underscoring the computational demands of cross-modal control. Univariate analyses revealed complexity-modulated effects within each level of abstraction and a corresponding anterior shift in PFC activation paralleling the hierarchical gradient. Multivoxel pattern analysis further demonstrated a representational shift, where caudal PFC encoded concrete motor responses, whereas rostral PFC represented abstract dimensions. Functional connectivity analyses revealed a complementary dissociation: caudal subregions showed selective, complexity-modulated coupling with primary sensory cortices during lower-level control, whereas rostral PFC exhibited functional independence from direct sensory coupling at the highest level of abstraction. Instead, increasing abstraction was associated with enhanced coupling among higher-order association areas, particularly between the superior temporal and intraparietal regions. Together, these findings extend prior unimodal research by demonstrating that hierarchical control is instantiated along a rostro-caudal gradient that flexibly reconfigures prefrontal-sensory interactions to meet multiple sensory demands. This cross-modal hierarchical architecture enables a transition from direct sensorimotor mappings to abstract regulation, providing a neural basis for adaptive cognition in the complex, multisensory environments of everyday life.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121977"},"PeriodicalIF":4.5,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147841023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equivalence of modified k-means and tensor decomposition in EEG microstates: Implications for analysis and interpretation.","authors":"Zuzana Rošťáková, Roman Rosipal","doi":"10.1016/j.neuroimage.2026.121962","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.121962","url":null,"abstract":"<p><p>In the resting state, the human brain quickly transitions among a limited set of quasi-stable states known as EEG microstates, which characterize brain spatio-temporal activity with high temporal resolution. EEG microstates are typically identified using a clustering algorithm that analyzes peaks in the EEG global field power. In this study, we focus on the modified k-means algorithm (modKM), one of the most commonly employed methods for detecting EEG microstates. We demonstrate, both theoretically and through simulation and real EEG data, its equivalence with a different method known as the Implicit Slice Canonical Decomposition (IMSCAND), which is a special kind of tensor decomposition for symmetric higher order arrays. This relationship opens new avenues for EEG microstate detection, interpretation, and analysis by utilizing tensor decomposition methods and related techniques.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"334 ","pages":"121962"},"PeriodicalIF":4.5,"publicationDate":"2026-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147840310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lifespan Exposure to Hormone Therapies and Structural Brain Morphometry in Older Women.","authors":"Robyn A Honea, Amber Watts, Shannon D Donofry, Cristina Molina-Hidalgo, Hayley S Ripperger, Sarah L Aghjayan, Chaeryon Kang, Swathi Gujral, Lauren E Oberlin, George Grove, Haiqing Huang, Bradley P Sutton, Jeffrey M Burns, Eric D Vidoni, Arthur F Kramer, Edward McAuley, Charles H Hillman, Anna L Marsland, M Ilyas Kamboh, Kirk I Erickson","doi":"10.1016/j.neuroimage.2026.121974","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.121974","url":null,"abstract":"<p><strong>Background: </strong>Although many studies support a neuroprotective role for estrogens and other ovarian hormones in women, findings across imaging studies remain mixed. Few studies have explored both early- and midlife- hormone exposures simultaneously or incorporated whole-brain, voxel-wise approaches. This study examined the effects of early- and midlife exposure to ovarian hormones- via hormonal birth control (BC), menopausal hormone therapy (MHT)- and their timing on brain health in older women. We also studied the relationship of age of menopause (i.e., greater endogenous exposure to ovarian hormones) to brain health in older adulthood.</p><p><strong>Methods: </strong>We analyzed baseline data from 459 women (ages 65-80) in the multi-site IGNITE study, a 12-month randomized aerobic exercise study. We examined retrospective self-report of BC and MHT use in relation to structural MRI metrics using voxel-based morphometry (VBM) for gray matter volume and surface-based morphometry (SBM) for cortical thickness.</p><p><strong>Findings: </strong>BC use compared to no BC use was associated with greater gray matter volume in temporal, occipital, and frontal regions in older adulthood. Longer BC duration was linked to larger fusiform gyrus volume. Combined BC and MHT use compared to no use was associated with greater volume in parietal and temporal areas and thicker cortex in the posterior cingulate and temporal gyri. Later menopause onset correlated with greater posterior cortical thickness. No associations were found for MHT timing or BC start age.</p><p><strong>Interpretations: </strong>Both endogenous and exogenous lifetime exposure to ovarian hormones were associated with structural brain measures generally consistent with preserved brain aging. These findings highlight the importance of exposure timing in women's brain health and AD risk prevention.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121974"},"PeriodicalIF":4.5,"publicationDate":"2026-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147841010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The predictive brain: Neural correlates of word expectancy align with large language model prediction probabilities.","authors":"Nikola Kölbl, Konstantin Tziridis, Andreas Maier, Thomas Kinfe, Ricardo Chavarriaga, Achim Schilling, Patrick Krauss","doi":"10.1016/j.neuroimage.2026.121966","DOIUrl":"10.1016/j.neuroimage.2026.121966","url":null,"abstract":"<p><p>Predictive coding theory suggests that the brain continuously anticipates upcoming words to optimize language processing, but the neural mechanisms remain unclear, particularly in naturalistic speech. Here, we simultaneously recorded EEG and MEG data from 29 participants while they listened to an audio book and assigned predictability scores to nouns using three LLMs: one BERT model and two multilingual LLaMA models. Our results show that higher predictability is associated with reduced neural responses during word recognition, as reflected in lower N400 amplitudes, and with increased anticipatory activity before word onset. EEG data revealed increased pre-activation in left fronto-temporal regions, while MEG showed a tendency for greater sensorimotor engagement in response to low-predictability words, suggesting a possible motor-related component to linguistic anticipation. These findings provide new evidence that the brain dynamically integrates top-down predictions with bottom-up sensory input to facilitate language comprehension. To our knowledge, this is the first study to demonstrate these effects using naturalistic speech stimuli, bridging computational language models with neurophysiological data. Our findings provide novel insights for cognitive computational neuroscience, advancing the understanding of predictive processing in language and inspiring the development of neuroscience-inspired AI.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121966"},"PeriodicalIF":4.5,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147818279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep-learning saturation transfer magnetic resonance fingerprinting (ST-MRF) in patients with Parkinson's disease.","authors":"Jannik Prasuhn, Munendra Singh, Sultan Z Mahmud, Nirbhay N Yadav, Ted M Dawson, Kelly A Mills, Peter van Zijl, Hye-Young Heo","doi":"10.1016/j.neuroimage.2026.121975","DOIUrl":"10.1016/j.neuroimage.2026.121975","url":null,"abstract":"<p><p>Parkinson's disease (PD) is marked by progressive neurodegeneration in the substantia nigra (SN). This study evaluated deep-learning saturation-transfer magnetic resonance fingerprinting (ST-MRF) to quantify molecular and microstructural changes in PD. We examined 23 patients with PD (PwPD) and 22 matched healthy controls (HCs) using multimodal imaging, including ST-MRF. ST-MRF detected significant molecular and microstructural alterations in the SN of PwPD compared to HCs, including increases in magnetization transfer ratio at 3.5 ppm (MTR(3.5ppm, 1.5 µT); 0.612 ± 0.022 vs. 0.597 ± 0.021, p = 0.014), MTR(-3.5ppm, 1.5 µT); 0.614 ± 0.021 vs. 0.586 ± 0.019, p = 0.008)), and decreases in T₂^w (51.9 ± 3.4 vs. 54.5 ± 1.3 ms, p = 0.005), suggesting disrupted protein homeostasis and iron accumulation. ST-MRF provides multiparametric insights into PD-related pathology and may serve as a candidate tool for future biomarker studies. Validation in larger, longitudinal cohorts will be essential to establish its clinical utility.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121975"},"PeriodicalIF":4.5,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147818283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Meta-analysis and Meta-regression of Hearing Loss fMRI Activity, Connectivity, and Fluctuation Alterations: Heterogeneity of auditory sensory impact across the lifespan.","authors":"Xuan Wang, Bo Ao, Yalda Yazdani, Condon Lau, Mehdi Abouzari, J Tilak Ratnanather, Francis A M Manno","doi":"10.1016/j.neuroimage.2026.121973","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.121973","url":null,"abstract":"","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"121973"},"PeriodicalIF":4.5,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147818267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}