Human Brain Mapping最新文献

{"title":"Neural Assimilation and Accommodation in Trilinguals: An fMRI Study at 7 T","authors":"Dinh Ha Duy Thuy,&nbsp;Naoya Oishi,&nbsp;Thai Akasaka,&nbsp;Tomohisa Okada,&nbsp;Takashi Hanakawa","doi":"10.1002/hbm.70620","DOIUrl":"https://doi.org/10.1002/hbm.70620","url":null,"abstract":"<p>Understanding how multiple languages are represented in the multilingual brain is critical to theories of multilingual assimilation and accommodation. Whether a second language (L2) recruits native-like networks (assimilation) or engages additional neural resources (accommodation) depends partly on the linguistic distance between L1 and L2. However, it remains unclear whether multilinguals can flexibly modulate assimilation and accommodation mechanisms when dealing with different L2 systems. Using 7 T-fMRI, we investigated brain activation patterns during a covert picture-naming task involving one-back phonological retrieval in 15 native Chinese speakers highly proficient in Japanese and English. Whole-brain univariate analysis revealed a common fronto-parieto-occipital network across all three languages (Chinese, Japanese, and English), supporting a shared core language system. However, the Japanese task elicited greater activation in the left lingual and middle occipital gyri, suggesting increased implicit visual-lexical demands. Representational Similarity Analysis (RSA) showed greater pattern similarity between Chinese and English than between Chinese and Japanese, indicating differential neural representation across L2 languages. VOI-based RSA showed a trend toward correlations between Japanese proficiency and representational similarity in the executive regions (pars triangularis and anterior cingulate gyrus), although these correlations did not reach statistical significance. These findings demonstrated that the trilingual brain relied on both assimilation and accommodation, with the level of each modulated by differences in linguistic structure and language experience. Language with a distinct writing system (English) seemed to be assimilated into the dominant L1 Chinese neural framework, whereas orthographically related language (Japanese) rather drove neural accommodation, probably due to script-driven interference. This study highlighted multi-level neural adaptation processes underlying multilingual lexical processing and provided a neurocognitive basis for tailor-made educational strategies considering each student's linguistic background.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70620","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617151","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":"Methodological Choices Strongly Modulate the Sensitivity and Specificity of Lesion-Symptom Mapping Analyses","authors":"Margaret Jane Moore,&nbsp;Chris Rorden,&nbsp;Gail A. Robinson,&nbsp;Jason B. Mattingley,&nbsp;Nele Demeyere","doi":"10.1002/hbm.70619","DOIUrl":"https://doi.org/10.1002/hbm.70619","url":null,"abstract":"<p>Lesion-symptom mapping results can vary substantially as a function of specific analysis parameters, but the extent to which individual methodological choices interact to modulate the sensitivity and specificity of results is not clear. Here, we employed a large-scale simulation approach to inform practical recommendations for lesion-symptom mapping studies. Routine clinical imaging from 959 stroke survivors (mean age = 72.5, 49.3% female) was used to conduct 384,780 lesion-symptom mapping analyses based on simulated behavioural data. Each simulated analysis used different combinations of plausible sample inclusion criteria, analysis parameters (e.g., correction factors), analysis types (e.g., univariate vs. multivariate), and underlying target correlates. Simulated analysis accuracy (percent coverage of target correlates, Dice similarity coefficient, and false positives) was compared across designs. Overall, analysis accuracy varied widely and was substantially modulated by the specific design used. Analyses that maximised lesion coverage by including large and diverse samples reliably outperformed analyses using more restricted samples. Analyses using direct total lesion volume controls outperformed analyses using other (or no) volume corrections across all accuracy measures. False discovery rate corrections yielded the best performance in terms of target coverage, while permutation corrections yielded the best Dice coefficients. While multivariate approaches were more accurate than univariate analyses in terms of Dice coefficient, univariate analyses generated higher target hit rates and percent target coverage. These results identify specific analysis designs suitable for studies aiming to maximise their sensitivity and/or specificity to underlying critical correlates, while highlighting the inferential strengths and weaknesses of these complementary approaches.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70619","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148617225","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":"External Source Monitoring and Reality Monitoring: Meta-Analysis of fMRI Studies","authors":"Beatriz Martín-Luengo,&nbsp;Oksana Zinchenko,&nbsp;Aleksandra Dolgoarshinnaia","doi":"10.1002/hbm.70614","DOIUrl":"https://doi.org/10.1002/hbm.70614","url":null,"abstract":"<p>Being able to remember the origin of a particular memory is for times even more important than the memory itself. Yet, although memory for the information and memory for the source are intrinsically connected, the particular neural underpinnings for the source-memory monitoring remains unclear. We run an fMRI meta-analysis to help to clarify the brain structures necessary for source memory monitoring. Source monitoring (SM) relates to distinguishing the origin of the information of two external sources, whereas reality monitoring (RM) refers to distinguishing between one internal (e.g., thoughts) and one external source, or two internal sources. We used PRISMA to select the manuscripts and Ginger ALE to analyze the data of the final 51 eligible selected articles. Most of the articles referred to external SM paradigms (34), but the number of articles on RM (17) allowed us to run a separate analysis to identify brain regions active during this specific process. The SM and RM contrasts showed concordance in 10 clusters, being the largest cluster with the highest ALE value found in the left claustrum and middle Frontal Gyrus (BA 46, 9 and 10). SM contrasts show concordance in seven clusters that include the largest cluster centered in the left middle frontal (BA 9) and inferior frontal gyrus (BA 45). Five suprathreshold clusters were detected for RM contrasts. The largest one was detected in the parietal lobe, centered in the left inferior parietal lobule (BA 40) and left angular gyrus (BA 39). The results support the neural differentiation, as well as a partial overlapping, for the two different types of monitoring. Moreover, they help to understand the divergent results in fMRI studies most likely due to the stimuli characteristics.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70614","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148616784","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":"Estimating Task-Evoked Neurovascular Coupling Using Mutual Information Between BOLD and Perfusion-Weighted fMRI Signals","authors":"Alexander D. Cohen,&nbsp;Yang Wang","doi":"10.1002/hbm.70610","DOIUrl":"10.1002/hbm.70610","url":null,"abstract":"<div>\u0000 \u0000 <p>Understanding neurovascular coupling (NVC) is essential for interpreting functional MRI (fMRI) data, particularly in task-based paradigms. BOLD–ASL coupling studies, where simultaneously collected blood oxygenation dependent (BOLD) and arterial spin labeling (ASL) signals are correlated, have shown widespread coupling during the resting state. While prior work has demonstrated widespread BOLD–ASL coupling at rest, less is known about how this coupling behaves during tasks and whether nonlinear dependencies contribute to NVC. This study investigates BOLD–ASL coupling during a visual checkerboard task and a finger-tapping motor task. Coupling was evaluated at zero lag and at the lag of maximum dependence. Spatial correspondence with task activation was quantified using Dice coefficients within Yeo 17-network regions. Coupling was evaluated using traditional Pearson correlation (corr) and mutual information (MI), a model-free approach capable of detecting both linear and nonlinear dependencies. Results showed strong spatial correspondence between task activation and BOLD–ASL coupling for both tasks, particularly in expected visual, sensory, and motor regions. Notably, MI showed more overlap with traditional GLM-based task activation models compared to corr. This suggests that MI may provide additional insights into the complexity of NVC beyond traditional linear methods. These findings reinforce the importance of using multimodal fMRI approaches to characterize NVC more comprehensively.</p>\u0000 </div>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148602380","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":"Epigenetic and Brain Structure Covariation Patterns in Typical and Atypical Development","authors":"Valentine Chirokoff,&nbsp;Jo Wrigglesworth,&nbsp;Peter Daniel Fransquet,&nbsp;Yen Ting Wong,&nbsp;Jeffrey M. Craig,&nbsp;Tim J. Silk","doi":"10.1002/hbm.70587","DOIUrl":"10.1002/hbm.70587","url":null,"abstract":"<p>By studying changes in gene expression that occur without altering the DNA sequence, epigenetics offers a promising lead in unraveling how biological factors interact with the environment to shape brain development. However, prior developmental studies have focused on candidate brain or epigenetic regions, limiting our understanding of brain- and epigenome-wide links during childhood. This study explored associations between brain-wide structural imaging (T1-weighted, diffusion-weighted) and epigenome-wide DNA methylation in 144 children with and without ADHD, using parallel Independent Component Analysis (pICA) to identify linked patterns. We identified five significantly linked brain–epigenome components, in which methylation explains a significant proportion of variance in associated brain components, and further pinpointed 908 CpGs as part of the strongest epigenetic–brain associations using multivariate random forest analysis. Genes linked to these CpGs were enriched in neuronal development and associated with psychiatric/neurodevelopmental disorders, underscoring their functional relevance. Exploratory analyses suggested that ADHD diagnosis and demographic variables may modulate these brain–epigenome associations. Our study links brain anatomy to DNA methylation patterns in functionally relevant genes involved in neuronal development and psychiatric disorders, highlighting potential biological insights through which genetic and environmental factors may influence brain development. We further provide epigenetic to brain cluster mappings and a companion script to extract epigenetic–brain links, offering resources for future neurodevelopmental studies.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70587","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148602323","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 Cortical Morphological Brain Networks and Their Diagnostic Classification Utility in Major Depressive Disorder","authors":"Xuetian Sun,&nbsp;Yuhao Shen,&nbsp;Xiao Chen,&nbsp;Bin Lu,&nbsp;Xue-Ying Li,&nbsp;Zi-Han Wang,&nbsp;Li-Ping Cao,&nbsp;Guan-Mao Chen,&nbsp;Jian-Shan Chen,&nbsp;Tao Chen,&nbsp;Tao-Lin Chen,&nbsp;Yu-Qi Cheng,&nbsp;Zhao-Song Chu,&nbsp;Shi-Xian Cui,&nbsp;Xi-Long Cui,&nbsp;Zhao-Yu Deng,&nbsp;Qi-Yong Gong,&nbsp;Wen-Bin Guo,&nbsp;Can-Can He,&nbsp;Zheng-Jia-Yi Hu,&nbsp;Qian Huang,&nbsp;Xin-Lei Ji,&nbsp;Feng-Nan Jia,&nbsp;Li Kuang,&nbsp;Bao-Juan Li,&nbsp;Feng Li,&nbsp;Hui-Xian Li,&nbsp;Tao Li,&nbsp;Tao Lian,&nbsp;Yi-Fan Liao,&nbsp;Xiao-Yun Liu,&nbsp;Yan-Song Liu,&nbsp;Zhe-Ning Liu,&nbsp;Yi-Cheng Long,&nbsp;Jian-Ping Lu,&nbsp;Jiang Qiu,&nbsp;Xiao-Xiao Shan,&nbsp;Tian-Mei Si,&nbsp;Peng-Feng Sun,&nbsp;Chuan-Yue Wang,&nbsp;Hua-Ning Wang,&nbsp;Xiang Wang,&nbsp;Ying Wang,&nbsp;Yu-Wei Wang,&nbsp;Xiao-Ping Wu,&nbsp;Xin-Ran Wu,&nbsp;Yan-Kun Wu,&nbsp;Chun-Ming Xie,&nbsp;Guang-Rong Xie,&nbsp;Peng Xie,&nbsp;Xiu-Feng Xu,&nbsp;Zhen-Peng Xue,&nbsp;Hong Yang,&nbsp;Hua Yu,&nbsp;Min-Lan Yuan,&nbsp;Yong-Gui Yuan,&nbsp;Ai-Xia Zhang,&nbsp;Jing-Ping Zhao,&nbsp;Ke-Rang Zhang,&nbsp;Wei Zhang,&nbsp;Zi-Jing Zhang,&nbsp;Chao-Gan Yan,&nbsp;the DIRECT Consortium,&nbsp;Jiajia Zhu,&nbsp;Yongqiang Yu","doi":"10.1002/hbm.70612","DOIUrl":"10.1002/hbm.70612","url":null,"abstract":"<p>Major depressive disorder (MDD) has been increasingly characterized as a network dysconnectivity syndrome. Although single-subject morphological networks are advantageous in studying the brain connectome, extant research on MDD is limited by either small samples or a lack of integration of multi-feature across different morphological features. We used the largest structural MRI data from 1442 MDD patients and 1277 controls to construct individual-level cortical morphological networks based on cortical thickness (CT), cortical volume (CV), surface area (SA), and sulcal depth (SD). Group comparisons in interregional morphological connectivity (MC) and graph-theoretical nodal properties were performed. Furthermore, support vector machine (SVM) was applied to evaluate whether the network alterations could distinguish patients from controls. As a result, MDD patients presented widespread alterations in MC, with distinct alteration patterns observed across four morphological networks. Specifically, CT-based networks exhibited reduced MC primarily within and between higher-order networks involving the default mode and frontoparietal networks, whereas CV-based networks showed increased MC predominantly within the default mode network. By contrast, both SA- and SD-based networks demonstrated enhanced MC mainly within and between lower-order networks implicating the somatomotor and visual networks. Similar patterns of MC alterations were observed in first-episode, drug-naive MDD patients. Concurrently, nodal property analysis revealed increased betweenness centrality in multiple cortical regions in MDD. Moreover, SVM models based on the altered MC achieved moderate-to-good classification performance in distinguishing patients from controls. Overall, our findings of individual-level morphological network alterations in depressed patients may corroborate the dysconnectivity hypothesis of MDD and could further inform its more accurate diagnosis.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70612","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148578328","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":"Multimodel Diffusion MRI Signatures in Atypical Parkinsonian Disorders","authors":"Yuqi Tian,&nbsp;Farwa Ali,&nbsp;Mary M. Machulda,&nbsp;Val. J. Lowe,&nbsp;Keith A. Josephs,&nbsp;Jennifer L. Whitwell","doi":"10.1002/hbm.70616","DOIUrl":"10.1002/hbm.70616","url":null,"abstract":"<p>Distinguishing atypical parkinsonian disorders (APS) from Parkinson's disease (PD) remains challenging due to overlapping clinical features, yet accurate differentiation is critical for prognosis and treatment. Here, we employed multimodel diffusion MRI (dMRI) analysis to characterize microstructural alterations across corticobasal syndrome (CBS), progressive supranuclear palsy-Richardson syndrome (PSP-RS), and PD, with the aim of identifying which dMRI model and regional metrics show the strongest group-level separation. We analyzed 25 CBS, 42 PSP-RS, and 21 PD participants compared to 35 age and sex-matched controls. Using a clinically feasible 3-shell high angular resolution diffusion imaging (HARDI) protocol, we applied 11 metrics from five complementary dMRI models—diffusion tensor imaging (DTI), free-water-eliminated model of DTI (FWE), neurite orientation dispersion and density imaging (NODDI), tissue-weighted NODDI, and fixel density (FD) in fixel-based analysis (FBA)—to comprehensively assess regional white and gray matter integrity. Group differentiation was quantified using covariate-adjusted Cohen's <i>d</i> effect sizes and spearman correlations were assessed between dMRI metrics and clinical scales. Distinct microstructural signatures were observed across disorders, and the sensitivity of the dMRI models differed. In group contrasts, DTI and NODDI-derived metrics consistently captured the strongest effects in midbrain and peduncular pathways for PSP-RS, whereas precentral and corticospinal alterations in CBS were most prominent using NODDI and FBA measures. Free-water-corrected metrics showed attenuated group differences. Across clinical-diffusion analyses, NODDI metrics exhibited the most robust associations with disease severity, while DTI and FWE measures detected more limited, regionally constrained effects. Together, these findings highlight complementary yet distinct sensitivities of tensor, free-water, multicompartment, and fixel-based models to APS-related neurodegeneration.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70616","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148578255","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":"A Multiscale Spatiotemporal Causal Mapping Algorithm for Revealing Neural Network Mechanisms of Transcutaneous Auricular Vagus Nerve Stimulation","authors":"Weiyi Wang,&nbsp;Ruimin Wang,&nbsp;Pan Lin,&nbsp;Yue Leng,&nbsp;Tianqi Huang,&nbsp;Sheng Ge","doi":"10.1002/hbm.70615","DOIUrl":"10.1002/hbm.70615","url":null,"abstract":"<p>Transcutaneous auricular vagus nerve stimulation (taVNS) has shown promise in enhancing cognitive and emotional functions, yet its neural mechanisms remain unclear largely because existing analytical methods cannot characterize multiscale functional connectivity nor reliably infer causal interactions between brain regions in the presence of hemodynamic delays in fMRI signals. To address these limitations, we propose a Multiscale Spatiotemporal Causal Mapping (MSTCM) algorithm that integrates community-aware multiscale functional connectivity with delay-compensated causal inference. This design enables MSTCM to characterize multiscale connectivity structure and infer directed information flow with enhanced robustness. In evaluations using simulated fMRI data, MSTCM significantly outperformed seven existing causal inference algorithms across multiple evaluation metrics, including precision, sensitivity, Matthews correlation coefficient (MCC), and area under the receiver operating characteristic curve (AUC). Applied to resting-state fMRI across four predefined large-scale cortical networks before and after taVNS, MSTCM revealed that taVNS reduced functional coupling between the left lateral sensorimotor cortex (L-LSMC) and the right intraparietal sulcus (R-IPS), increased global efficiency, enhanced causal integration within the salience network (SN), weakened causal connectivity within the dorsal attention network (DAN), and strengthened information flow from DAN to SN. These findings suggest that taVNS may enhance cognitive flexibility and emotional regulation by shifting information processing from exteroceptive toward interoceptive pathways and improving large-scale network efficiency. Consequently, this study provides not only a novel methodological approach but also new neuroimaging evidence supporting the clinical potential of taVNS.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13392224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148561844","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":"A Discovery and Replication Study of Dyslexia Does Not Reveal Reproducible Gray Matter Volume Differences","authors":"Alison K. Schug,&nbsp;Iria S. Gutierrez-Schieferl,&nbsp;Guinevere F. Eden","doi":"10.1002/hbm.70592","DOIUrl":"10.1002/hbm.70592","url":null,"abstract":"<p>Two decades of research have provided evidence for gray matter volume (GMV) differences in developmental dyslexia (or reading disability, RD) in the left perisylvian cortex. However, there are concerns about result inconsistencies, likely attributable to small sample sizes, lenient statistical thresholds, and insufficient accounting for demographic variables and global GMV. To address these concerns, we conducted a Discovery and Replication Study (<i>N</i> = 262) using data from the Adolescent Brain Cognitive Development^SM Study. We found GMV differences between the RD and Control Groups did not replicate across the Discovery and Replication Studies using voxel-based morphometry (VBM) in Statistical Parametric Mapping (SPM), and that a more conservative threshold yielded few results. We then conducted Reproducibility Studies and first found that when using surface-based morphometry in FreeSurfer instead of VBM, the Discovery and the Replication Study results again failed to converge. Second, we combined all groups in a factorial VBM/SPM analysis and the interaction analysis provided quantitative confirmation for diverging between-group difference results across the two studies. Third, we tested for the role of covariates of no interest and found that when total GMV is not controlled for, this divergence dissipates and group differences in RD (main effect of Reading Ability) are amplified. In conclusion, replication of GMV differences in RD is low, even when using large, well-matched groups, and analyses approaches play a modulating role. As such, results from prior studies using lenient statistical thresholds and not accounting for total GMV should be viewed with caution.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148446059","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":"Successful Single-Session Neural Self-Regulation Through Neurofeedback Varies Between Features","authors":"Syrjänen E,&nbsp;Silva J,&nbsp;Astrand E","doi":"10.1002/hbm.70611","DOIUrl":"10.1002/hbm.70611","url":null,"abstract":"<p>Neurofeedback (NFB) and Brain-Computer Interface (BCI) research seldom present within-session individual learning dynamics. This is even though a large proportion of NFB and BCI users cannot learn the neural self-regulation required to control the feedback. Understanding the time course and learning dynamics between subjects will enable us to design more effective NFB and BCI protocols that promote the learning of neural self-regulation. In this study, we aimed to analyze individual learning trajectories of self-regulation of four different cortical rhythms, in terms of both frequency and spatial selectivity. Twenty healthy subjects performed four sessions of NFB training, each session with feedback reflecting a different cortical rhythm as measured with an electroencephalogram. We specifically tested frontal midline (fm) Theta, occipital Alpha, unilateral centrotemporal sensorimotor rhythms (SMR), and central Beta. We show that all subjects were able to self-regulate at least two of these features; however, with varied specificity in the spatial and frequency domains. Unexpectedly, we show that none of the subjects succeeded in regulating fm Theta. Using a clustering approach, we identified two different learning dynamics among the learners across features: a linear increase/decrease and a non-linear plateau-like trajectory. This is the first NFB study employing an intra-subject cross-over experimental design, enabling the direct comparison of neural self-regulation between multiple features. Our results provide important insights into the “non-learner” problem, showing that it is not a feature-universal personal trait. We further show feature-specific spatial and frequency selectivity of neural self-regulation, providing important considerations for future NFB protocols.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 11","pages":""},"PeriodicalIF":4.0,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70611","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148455639","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}