Human Brain Mapping最新文献

{"title":"Transdiagnostic Profiles of BOLD Signal Variability in Autism and Schizophrenia Spectrum Disorders: Associations With Cognition and Functioning.","authors":"Maria T Secara, Zara Khan, Ayesha Rashidi, Lindsay D Oliver, Ju-Chi Yu, George Foussias, Erin W Dickie, Peter Szatmari, Pushpal Desarkar, Meng-Chuan Lai, Giulia Baracchini, Anil K Malhotra, Robert W Buchanan, Aristotle N Voineskos, Stephanie H Ameis, Colin Hawco","doi":"10.1002/hbm.70496","DOIUrl":"10.1002/hbm.70496","url":null,"abstract":"<p><p>Autism spectrum disorder (autism) and schizophrenia spectrum disorders (schizophrenia) exhibit overlapping social and neurocognitive impairment and considerable neurobiological heterogeneity. Blood-oxygen-level-dependent (BOLD) signal variability captures the brain's moment-to-moment fluctuations, offering a dynamic marker of neural flexibility that is sensitive to cognitive capacity. This study aimed to examine intra-regional BOLD signal variability during rest and task across schizophrenia, autism, and typically developing controls (TDC) to explore transdiagnostic patterns of brain signal variability and their relationship with cognitive and functional outcomes. Intra-regional BOLD variability, measured by mean squared successive difference (MSSD), was obtained from resting-state and empathic accuracy task fMRI in 176 SSD, 89 autism, and 149 TDC participants. ANCOVAs, controlling for age, sex, and motion, assessed group differences in intra-regional and network-level BOLD variability and dimensional associations with social cognition, neurocognition, social functioning, and symptom severity. Both autism and schizophrenia exhibited lower BOLD signal variability than TDC across rest and task, with reduced variability observed in somatomotor, visual, and auditory networks (pFDR < 0.01). Greater network variability was positively associated with better social cognitive, neurocognitive, and functional scores across the sample. Resting-state variability showed stronger group-based differences and cognitive associations than task-based variability. BOLD signal variability is positively associated with social cognition, neurocognition, and social functioning across groups, suggesting that variability impacts cognitive efficiency and behavior. Reduced variability in autism and schizophrenia may indicate similar patterns of neural rigidity among these related conditions, positioning BOLD variability as a potential biomarker for neural flexibility and a valuable target for future transdiagnostic clinical interventions.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":"e70496"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13084261/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147689458","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":"Multi-Centre Reproducibility of DTI and NODDI in White Matter Tracts Segmented Using TractFinder Across Three MRI Scanners of the Same Model","authors":"Agnieszka Sierhej,&nbsp;Marta M. Correia,&nbsp;C. John Evans,&nbsp;Kiran K. Seunarine,&nbsp;Jonathan D. Clayden,&nbsp;Nadia A. S. Smith,&nbsp;Matt G. Hall,&nbsp;Chris A. Clark","doi":"10.1002/hbm.70491","DOIUrl":"10.1002/hbm.70491","url":null,"abstract":"<p>Quantitative imaging biomarkers (QIBs) are objective measures derived from quantitative imaging that can differentiate pathological changes from healthy biological processes. Diffusion MRI parameters derived from Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) could serve as potential QIBs for studying both healthy neurodevelopment and various neurological conditions. However, quantitative neuroimaging studies often require large datasets collected across multiple scanners, which introduces variability. To ensure the reliability of multi-centre studies, the inter-centre reproducibility of DTI and NODDI parameters must be thoroughly assessed before data collection begins. Discrepancies between results reported by previous studies can be explained by other sources of variability. The inter-scanner reproducibility of diffusion parameters needs to be determined when the other sources of variability, such as differences in acquisition parameters, processing and ROI segmentation are controlled for. We assess the reproducibility of DTI and NODDI parameters in clinically relevant white matter (WM) tracts across three scanners of the same model, ensuring consistency in the acquisition scheme and pre-processing pipelines. WM tract regions of interest (ROIs) are automatically segmented to standardise the analysis. Additionally, we investigate ROI and signal-to-noise ratio differences to better understand the sources of variability in diffusion parameters. According to the Koo and Li classification system, our results demonstrate excellent reproducibility for fractional anisotropy and mean diffusivity across scanners of the same model (ICC ≥ 0.964) when using identical acquisition schemes, pre-processing pipelines and automated ROI segmentation. NODDI orientation dispersion index and neurite density index exhibit a similar level of reproducibility (ICC ≥ 0.942 and ICC ≥ 0.911, respectively), while free water fraction (FWF) has ICC ≥ 0.862. However, statistically significant variability was observed in the FWF, specifically within the left inferior fronto-occipital fasciculus (CoV 9.43%) and optic radiation (CoV 9.95%), even when scanning the same cohort across sites. If there is an error in the signal fraction in one compartment in the NODDI model, the signal fractions from other compartments may likely be misestimated. The reproducibility and variability of diffusion parameters reported in this study provide guidance for future QIB research involving datasets derived from multiple scanners. These findings can help determine whether observed changes in diffusion parameters reflect meaningful biological differences or are highly influenced by measurement variability.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70491","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147580503","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":"Differences of Gradient Connectivity and Ventricle Volumes in Long-Term Sensorineural Hearing Loss Related Cognitive Impairment Correlate With Transcriptional Signatures","authors":"Xiao-Min Xu,&nbsp;Zi-Huai Fang,&nbsp;Yuting Xia,&nbsp;Shuo Li,&nbsp;Yuan Feng,&nbsp;Yuanqing Wu,&nbsp;Richard Salvi,&nbsp;Xindao Yin,&nbsp;Yu-Chen Chen","doi":"10.1002/hbm.70521","DOIUrl":"10.1002/hbm.70521","url":null,"abstract":"<p>Long-term sensorineural hearing loss (SNHL) is a prevalent condition associated with an increased risk of cognitive impairment. This study aimed to investigate the relationship among gradient connectivity, ventricle volumes, and transcriptional signatures in individuals experiencing cognitive deficits related to long-term SNHL. This study enrolled 81 patients with long-term SNHL and 78 healthy controls (HCs). All participants underwent audiological tests, neuropsychological assessment, and MRI scanning. Connectome gradient analysis and ventricular volume measurements were performed. Additionally, regional gene expression and neurotransmitter receptor data were integrated. Correlation analysis was conducted to examine associations between neuroimaging metrics and cognitive performance. Patients with SNHL had significantly higher hearing thresholds and worse cognitive performance than HCs. The principal gradient was compressed in the SNHL group, with significant differences in the default mode network and dorsal attention network. Enlarged volumes of the choroid plexus and lateral ventricles were also observed in the SNHL group. Correlation analysis revealed significant associations among ventricle volumes, gradient connectivity, and cognitive performance. Transcriptomic analysis revealed 496 genes associated with regions showing an increased principal gradient and 321 genes linked to regions with a decreased gradient. Enrichment analyses indicated these genes were implicated in synaptic plasticity, neurotransmitter regulation, energy metabolism, and neurodegenerative pathways. This study provides new insights into the multifaceted nature of SNHL-related cognitive impairments, suggesting that gradient connectivity, ventricle volumes, and transcriptional signatures are interconnected and may serve as potential biomarkers for monitoring cognitive decline in individuals with long-term SNHL. Future research should focus on elucidating the causal pathways and underlying biological mechanisms connecting these multimodal factors.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70521","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147580437","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":"Dynamic Alterations of Functional Systems in Alzheimer's Disease: A Co-Activation Pattern Analysis","authors":"Pan Wang,&nbsp;Mengfan Xue,&nbsp;Yingyin Mao,&nbsp;Chunyan Wang,&nbsp;Xing Yao,&nbsp;Bharat B. Biswal","doi":"10.1002/hbm.70509","DOIUrl":"10.1002/hbm.70509","url":null,"abstract":"<p>While resting-state brain dysfunctions have been extensively investigated in Alzheimer's disease (AD), the dynamic alterations of functional systems remain poorly understood. We employed co-activation pattern (CAP) analysis to characterize the functional-state alterations in 243 participants using resting-state fMRI data and applied graph theory analysis to estimate corresponding topological properties. The CAP analysis identified five distinct brain states across groups: State 1 (limbic network dominated), State 2 (dorsal attention network (DAN) and central executive network dominated), State 3 (default mode network and central executive network dominated), State 4 (somatomotor network and ventral attention network dominated), and State 5 (DAN, sensorimotor, and visual networks dominated). Compared to cognitively unimpaired individuals, State 3 demonstrated significantly reduced persistence and resilience in both mild cognitive impairment (MCI) and AD groups. Additionally, both clinical groups (MCI and AD) exhibited decreased transitions from State 2 to State 5 and reduced self-transitions within State 3. Graph theory analysis revealed that compared to cognitively unimpaired individuals, MCI and AD individuals had increased node degree centrality and node efficiency, alongside decreased node local efficiency in regions within the default mode network (DAN) and visual network, which corresponded well with CAP analysis results. Our findings provide a multiscale framework linking dynamic state instability to static network reorganization, advancing understanding of the dynamic functional alterations underlying cognitive decline in AD spectrum disorders.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70509","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147521080","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":"Watching Together, Yet Feeling Apart: Interpersonal Neural Synchronization as a Marker of Symptom Severity in Children With Autism Spectrum Disorder During Naturalistic Viewing","authors":"Jieqiong Liu,&nbsp;Yan Wu,&nbsp;Zijing Wang,&nbsp;Yujiao Deng,&nbsp;Zhijuan Jin,&nbsp;Xiaoning Sun,&nbsp;Yanrui Jiang,&nbsp;Guangshuai Wang,&nbsp;Mingming Zhang,&nbsp;Fan Jiang,&nbsp;Guanghai Wang","doi":"10.1002/hbm.70503","DOIUrl":"10.1002/hbm.70503","url":null,"abstract":"<p>Social interaction impairments in autism spectrum disorder (ASD) have been widely attributed to deficits in empathy, including both cognitive and affective components. However, the underlying neural mechanisms remain incompletely understood. In the current study, we used functional near-infrared spectroscopy (fNIRS) hyperscanning to simultaneously measure brain activities in children with ASD or typical development (TD) and their mothers while they co-viewed the animated film Partly Cloudy. Results revealed that compared to TD children, children with ASD exhibited significantly reduced interpersonal neural synchronization (INS), that is, desynchronization, in the frontopolar area and right dorsolateral prefrontal cortex (DLPFC) during scenes involving theory of mind (ToM) and pain-related events. Notably, TD children showed enhanced INS in the right DLPFC, with significant group differences. Moreover, the right DLPFC INS negatively correlated with ASD symptom severity and mediated the relationship between group and symptom severity. Inter-brain functional connectivity analysis revealed that, during empathy-related events, children's frontopolar area/right DLPFC and maternal brain regions were reduced in ASD but enhanced in TD dyads, with significant group-level contrasts. Finally, using support vector machine (SVM) classification, we found that INS features in the right DLPFC during empathy scenes could accurately distinguish between ASD and TD children. This study offers novel insights into the neural basis of empathy deficits in ASD by examining mother–child INS in a naturalistic setting. These findings provide preliminary insights into the neural mechanisms of INS in ASD and may inform future research on parent–child neural synchrony and its potential relevance for intervention strategies.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70503","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147521134","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":"Introducing Structural Reliance: A New Method to Assess Structure–Function Coupling in the Brain","authors":"Derek Madden,&nbsp;Paul J. Laurienti,&nbsp;Heather M. Shappell,&nbsp;Mohsen Bahrami","doi":"10.1002/hbm.70499","DOIUrl":"10.1002/hbm.70499","url":null,"abstract":"<p>The relationship between the structural connectome and functional activity in the brain is highly complex, and understanding of the connection between the two is limited. Previous work has shown a marginal reliance of functional brain activity on underlying structural connections, indicating significant flexibility of neural communication. Here, we introduce a new method to quantify structure–function coupling and compare it with a standard coupling technique by evaluating the structure–function relationship across numerous fMRI task paradigms. Through this comparison, we investigate how structure–function relationships change during different cognitive demands and we evaluate how they relate to behavior. The new method introduced here, structural reliance, exhibits different structure–function correspondence patterns throughout the brain, and it generally outperforms the standard coupling measure in coupling-based behavioral measure predictions.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70499","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147511822","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":"Effects of Age on Resting-State Cortical Networks","authors":"Chetan Gohil,&nbsp;Oliver Kohl,&nbsp;Jemma Pitt,&nbsp;Mats W. J. van Es,&nbsp;Andrew J. Quinn,&nbsp;Diego Vidaurre,&nbsp;Martin R. Turner,&nbsp;Anna C. Nobre,&nbsp;Mark W. Woolrich","doi":"10.1002/hbm.70516","DOIUrl":"10.1002/hbm.70516","url":null,"abstract":"&lt;p&gt;Understanding how ageing affects brain function remains a central challenge in neuroscience. Electrophysiological brain imaging techniques provide a near-direct measure of neuronal activity, which is useful for characterising neurophysiological health. They offer us the ability to track large-scale networks of functional activity with high temporal precision. The effects of healthy ageing on these networks remain poorly understood, in part due to small sample sizes and limited control for confounding factors in previous studies. Here, we analysed resting-state source-reconstructed magnetoencephalography (MEG) data from a large cross-sectional cohort of healthy adults (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;N&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ N $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; = 612, 18–88 years old) to characterise the effect of age using not only time-averaged (static), but also transient (dynamic) network activity. We examined time-averaged power and coherence across canonical frequency bands (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;δ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ delta $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;θ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ theta $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;α&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ alpha $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;β&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ beta $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;γ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ gamma $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;), as well as transient network dynamics identified using Hidden Markov Modelling. We included many confounding variables known to be affected by age, such as brain volume, as well as head size and position, which have previously been overlooked. Ageing was associated with frequency-specific changes in oscillatory power, with decreases in low-frequency (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;δ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ delta $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;θ&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ theta $$&lt;/annotation&gt;\u0000 &lt;","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70516","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147521159","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":"Efficacy of Optically Pumped Magnetometers in Detecting Activity From the Cerebellar Cortex","authors":"Santtu Roos,&nbsp;Matti Hämäläinen,&nbsp;Joonas Iivanainen","doi":"10.1002/hbm.70514","DOIUrl":"10.1002/hbm.70514","url":null,"abstract":"<p>The cerebral cortex has been extensively studied using magnetoencephalography (MEG), but the cerebellum has received less attention, partly due to technical limitations. Recent advances in high-resolution anatomical modeling enable surface-based analysis of cerebellar activity. At the same time, MEG technology has evolved, with on-scalp systems employing optically pumped magnetometers (OPMs) emerging as an alternative for conventional superconducting quantum interference device (SQUID)-based systems. In contrast to rigid one-size-fits-all SQUID sensor helmets, OPMs allow flexible positioning of the sensors on the participant's scalp to provide improved coverage of the cerebellum. To assess the benefits provided by OPMs in detecting cerebellar activity, we conducted simulations using a high-resolution model of the human cerebellum, where we compared OPM arrays consisting either of single-axis or triaxial sensors to commercial SQUID sensor arrays. We show that both OPM types measure stronger net signals from across the cerebellum compared to the SQUID-based systems. OPMs also reduce signal correlations between the cerebral and cerebellar cortices, improving source separability. Increasing the number of OPM sensors leads to larger gains in total information capacity compared to SQUIDs. In all metrics, triaxial OPMs outperformed single-axis configurations. These results suggest that already a 102-sensor, triaxial OPM-based on-scalp MEG system could substantially improve noninvasive electrophysiological studies of the human cerebellum.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70514","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147521119","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":"Precision Imaging for Intraindividual Investigation of the Reward Response","authors":"Matthew Mattoni,&nbsp;Shenghan Wang,&nbsp;Cooper J. Sharp,&nbsp;Thomas M. Olino,&nbsp;David V. Smith","doi":"10.1002/hbm.70512","DOIUrl":"10.1002/hbm.70512","url":null,"abstract":"<p>The reliance of fMRI research on between-person comparisons is limited by low test–retest reliability and an inability to explain within-person processes. Intraindividual studies are needed to understand how changes in brain functioning relate to changes in behavior. Here, we present open data and analysis of a novel intensively sampled fMRI study. This precision imaging dataset includes 44 sessions acquired across four participants at a twice-weekly rate. In each session, participants completed multiple reward-related tasks, mood and alertness ratings, and a behavioral mood manipulation. We examined how the reward response reflects between-person or within-person variance. Trial-level models suggested dramatically more trials than typically collected are needed to maximize reliability within runs and individuals. Test-retest reliability of the reward response was very low and not explained by measurement error, suggesting low power for between-person comparisons without large amounts of data. At an intraindividual level, mood and alertness explained up to 37% of the intraindividual variance of the anticipatory reward response. Finally, we found that while reliability or brain-behavior associations were not improved by multi-echo denoising, a multivariate reward signature had stronger intraindividual behavioral associations than a univariate anatomical mask. Together, results suggest that the BOLD reward response is not a stable trait-like marker, but moderated by state-like factors. More broadly, BOLD activation to reward tasks—and likely other fMRI tasks—presents substantial opportunity for within-person study to complement the traditional focus on between-person study. We conclude with a discussion of considerations for intensive longitudinal neuroimaging designs.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70512","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147511834","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":"Distinct Resting-State Connectomes for Face and Scene Perception Predict Individual Task Performance","authors":"Orhan Soyuhos,&nbsp;Aurelia Scarpa,&nbsp;Daniel Baldauf","doi":"10.1002/hbm.70498","DOIUrl":"10.1002/hbm.70498","url":null,"abstract":"<p>Face and scene perception rely on distinct neural networks centered on the Fusiform Face Area (FFA) and Parahippocampal Place Area (PPA). However, how these regions interact with broader brain networks remains unclear. Using resting-state fMRI and MEG data, we mapped the spatial and frequency-specific functional connectivity of the FFA and PPA. We found that the FFA showed predominant fMRI connectivity with lateral occipitotemporal, inferior temporal, and temporoparietal regions, while the PPA connected more strongly with ventral medial visual, posterior cingulate, and entorhinal-perirhinal areas. MEG analyses further revealed this network segregation was reflected in beta and gamma bands. Importantly, connectome-based predictive modeling showed that the strength of these intrinsic fMRI connectivity patterns predicted individual reaction times on corresponding face and scene perception tasks. Our findings demonstrate that the FFA and PPA anchor distinct intrinsic networks with unique spatio-temporal profiles that provide a functional architecture supporting their specialized roles in face and scene perception.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70498","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147498728","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}