NeuroImage最新文献

{"title":"Parietal Structural and Functional Differentiation Associated with Visual Tracking Across Motor Participation Profiles.","authors":"Keying Zhang, Meng Qi, Ling Jiang, Qing Yan, Yuyan Wang, Shuang Bai, Chunmei Cao, Dong Zhang, Siyuan Ma","doi":"10.1016/j.neuroimage.2026.122302","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122302","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to examine whether structural and resting-state functional measures of parietal subregions differ across predefined motor participation groups with comparable physical activity levels, and whether these neural measures are associated with visual tracking performance.</p><p><strong>Methods: </strong>We adopted an a priori motor-cognitive grouping framework and recruited athletes accordingly, using two representative sports as operational exemplars for each profile: (1) externally driven spatial updating and action planning (ESU; basketball and taekwondo), (2) body-environment calibration and rhythmic sensorimotor integration (SCP; skating and running), and 3) internally guided control and sustained attentional precision (IPS; tai chi and shooting). A sedentary control group (CON) with low habitual physical activity was also recruited. In total, 80 college students participated. Physical activity (PA) was assessed using a standardized questionnaire. All participants underwent structural MRI and resting-state fMRI to derive gray matter volume (GMV), fractional amplitude of low-frequency fluctuations (fALFF), degree centrality (DC), regional homogeneity (ReHo), and functional connectivity (FC) within parietal subregions (S1, SPL, AG, and SMG). Supplementary SPL-based FC analyses further examined connectivity with regions of the broader visuospatial and sensorimotor network. Visual tracking was assessed using a multiple object tracking (MOT) task across three difficulty levels.</p><p><strong>Results: </strong>PA levels were significantly higher in all athlete groups than in sedentary controls, with no differences among athlete groups. Across structural and resting-state functional measures, the most consistent group differences were selectively concentrated in S1 and SPL, whereas effects involving other parietal regions were less consistent across measures. Specifically, the ESU group exhibited the highest bilateral S1 GMV, the SCP group showed the highest bilateral SPL GMV, and the IPS group demonstrated the highest fALFF in both S1 and SPL. The IPS group also showed the highest ReHo in bilateral SPL. FC differed significantly across several parietal connections, with distinct connectivity patterns across the three athlete groups. MOT accuracy differed significantly across groups at all difficulty levels, with the ESU and IPS groups outperforming the SCP and CON groups overall. Across all participants, multiple S1 and SPL metrics showed modest associations with MOT performance (r = 0.20-0.40). Within athlete subgroups, stronger and task-specific associations were observed, particularly in the SCP and IPS groups (r = 0.50-0.80).</p><p><strong>Conclusions: </strong>These findings identify distinct structural and functional patterns predominantly involving S1 and SPL across different motor participation profiles, despite comparable overall physical activity levels among the athlete groups. Such parietal diff","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122302"},"PeriodicalIF":5.3,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224556","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":"Multivariate Prediction of White Matter BOLD Activity and Its Relationship to Marginal Connectivity.","authors":"Muwei Li, Zhaohua Ding, John C Gore","doi":"10.1016/j.neuroimage.2026.122297","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122297","url":null,"abstract":"<p><p>Functional MRI studies have traditionally focused on gray matter, whereas white matter BOLD signals have often been treated as weak or artifactual. However, white matter BOLD fluctuations are robustly detectable and contain reproducible functional information, yet most gray-to-white matter analyses rely on only marginal functional connectivity, which cannot separate pairwise coupling from shared variance among distributed cortical systems. Here, we used a multivariate cortical prediction framework to test whether spontaneous white matter BOLD activity can be predicted from distributed cortical gray matter BOLD activity, and how this predictive structure relates to marginal connectivity. Resting-state fMRI data from 81 Human Connectome Project young adult participants were analyzed using a strict white matter mask with no overlap with cortical predictors. For each white matter voxel, time series from 400 cortical parcels were used to predict white matter BOLD signals with nested leave-one-run-out ridge regression. Cortical BOLD activity modestly but reliably predicted white matter BOLD dynamics, demonstrating consistent cross-validated prediction accuracy across a broad spatial extent of the white matter. Ridge β coefficients strongly recapitulated marginal functional connectivity fingerprints, indicating a shared functional backbone, but their first gradients differed reproducibly. The difference between these gradients defined a β-minus-FC G1 divergence axis that remained stable after broadly controlling for anatomical, signal-related, and spatial factors. At the low end of the axis, enriched in callosal and capsular structures, pairwise gray-to-white matter connectivity was relatively strong, but white matter BOLD fluctuations were predicted less well by distributed cortical BOLD activity than that connectivity would suggest. At the high end, enriched in posterior projection and association pathways, pairwise connectivity was relatively weak, but distributed cortical BOLD activity predicted white matter BOLD signals better than expected. These findings identify a reproducible, tract-organized contrast between marginal connectivity and its covariance-adjusted predictive representation.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122297"},"PeriodicalIF":5.3,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224282","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":"Circadian and Sleep-Wake Modulation of EEG Functional Connectivity Across Brain States and Its Associations With Cognition in Humans.","authors":"Alpar S Lazar, Zsolt I Lazar, Nayantara Santhi, June C Lo, John A Groeger, Derk-Jan Dijk","doi":"10.1016/j.neuroimage.2026.122301","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122301","url":null,"abstract":"<p><p>Sleep and circadian rhythms both influence human brain function, but their distinct contributions to large-scale network organization remain unclear. We quantified the effect of brain state (wake, NREM, REM), sleep-wake history, and circadian phase on functional connectivity using over 1,200 hours of artifact-free EEG recorded during a 10-day forced-desynchrony protocol. We derived principal components of functional connectivity and found that both sleep-wake history and circadian phase significantly modulated functional connectivity, with sleep-wake history exerting a broader influence. Complementary cosinor analyses further demonstrated circadian rhythmicity in several NREM and REM connectivity measures. Across sleep, global connectivity increased progressively during NREM sleep, particularly in the delta and sigma bands, but declined during REM sleep. During controlled resting wakefulness, increasing time awake was associated with higher global alpha-band connectivity, which was associated with poorer concurrent cognitive performance. Connectivity during NREM sleep was also associated with subsequent cognitive performance, with lower global theta and, to a lesser extent, higher sigma connectivity linked to better performance. REM connectivity was not associated with these cognitive measures. Together, these findings reveal opposing NREM and REM trajectories in large-scale EEG functional connectivity and show that these brain-state-specific network dynamics are shaped by both sleep-wake history and circadian phase and are associated with cognitive performance.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122301"},"PeriodicalIF":5.3,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224303","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":"A shape deformation-based framework for constructing individualized subcortical morphological networks.","authors":"Shutong Lu, Jiashun Zhang, Junle Li, Jinhui Wang","doi":"10.1016/j.neuroimage.2026.122305","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122305","url":null,"abstract":"<p><p>Individualized morphological brain networks have emerged as an important framework for imaging-based connectomics. However, existing methods have focused predominantly on the cerebral cortex, leaving subcortical structures largely unexplored despite their central roles in cognition and neuropsychiatric disorders. Here, we developed a novel framework for constructing individualized subcortical morphological networks from structural magnetic resonance imaging. Specifically, subcortical surfaces were reconstructed using a Point2Mesh-optimized multilayer perceptron architecture and vertex-wise shape deformation was quantified as the signed Euclidean distance between each vertex on an individual mesh and the corresponding vertex on the group-average template mesh. Interregional morphological connectivity in local shape deformation distributions was subsequently estimated using Jensen-Shannon Divergence. Applying this approach to the Human Connectome Project dataset, we found that subcortical morphological networks exhibited complex topological organization, including small-world architecture, modular organization, and highly connected hubs, which were consistently preserved at finer subregional scales. Analyses using an independent test-retest dataset further demonstrated fair-to-good reliability of these network properties. Importantly, these shape deformation-based networks showed significant coupling with subcortical functional networks estimated from resting-state functional magnetic resonance imaging. Leveraging large-scale multisite clinical datasets, we further demonstrated alterations of subcortical morphological networks in schizophrenia and major depressive disorder. Schizophrenia was characterized predominantly by right caudate-centered disruptions in morphological connectivity and nodal centrality, whereas major depressive disorder exhibited alterations only in nodal centrality of the right amygdala. Together, these findings establish a novel and reliable framework for investigating subcortical morphological network organization in the human brain across both healthy and psychiatric populations.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122305"},"PeriodicalIF":5.3,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224676","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":"Amplitude-Conditioned Brain Dynamics Reveal Widespread Negative Modulation and Targeted Positive Modulation of Functional Networks.","authors":"Mohammad Reza Salehi, Ali BashirGonbadi, Hamid Soltanian-Zadeh","doi":"10.1016/j.neuroimage.2026.122304","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122304","url":null,"abstract":"<p><p>Functional connectivity is traditionally characterized through pairwise interactions between brain regions. However, growing evidence suggests that neural communication is also shaped by higher-order interactions in which the activity of a third region modulates the coupling between others. Here, we introduce a whole-brain framework for mapping resting-state nonlinear conditional connectivity from functional MRI. For each cortical region, we quantified how spontaneous amplitude fluctuations modulate the functional connectivity of all other region pairs. This procedure generated a modulation spectrum for every connection, describing connectivity changes across multiple amplitude states of the modulator. From these spectra, we derived four interpretable features capturing modulatory strength, polarity, volatility, and nonlinear complexity. The framework was applied to resting-state data from the Human Connectome Project and evaluated using stationary surrogate models, spatial topography analyses, test-retest reliability assessments, and behavioral prediction. Surrogate analyses demonstrated that the observed modulation spectra could not be explained by static covariance structure or spectral properties alone, indicating genuine state-dependent dynamic interactions. Topographic mapping reveals a profound functional asymmetry: the macroscopic connectome is dominated by widespread negative modulatory influences, with positive modulation restricted to sparse assortative pathways. Furthermore, by evaluating the effect of temporal integration, we show that spatial and temporal aggregation robustly stabilizes these dynamic fluctuations into reliable, individual-specific traits. Finally, employing regularized predictive modeling, we demonstrate that these dynamic modulatory features can provide complementary predictive value beyond conventional static FC, particularly for capturing state-dependent affective traits such as internalizing behavior. Together, this framework unveils a structured, asymmetric, and behaviorally relevant higher-order modulatory architecture.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122304"},"PeriodicalIF":5.3,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224647","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":"Subjective emotional ratings dissociate brain activation and network patterns during counterfactual outcome processing.","authors":"Tingting Zhang, Denghui Bai, Xiaotong Wei, Lei Zhuo, Qiuzhu Zhang, Junjun Zhang, Zhenlan Jin, Ling Li","doi":"10.1016/j.neuroimage.2026.122303","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122303","url":null,"abstract":"<p><p>Human decision-making integrates outcome evaluation, counterfactual comparison, and individual traits. We investigated the neural processing of outcome-related emotions during economic decision-making by classifying feedback according to participants' subjective emotional ratings rather than objective gain-loss categories. Participants completed a Wheel of Fortune gambling task during fMRI scanning and provided emotional ratings for feedback outcomes, enabling identification of regret, relief, disappointment, and elation. We also assessed individual differences in regret proneness, maximization tendencies, alternative search, high standards, and decision difficulty. Behaviorally, emotional ratings increased with larger obtained outcomes and decreased as reference outcomes increased, indicating robust modulation of outcome evaluation by counterfactual information Whole-brain analyses revealed greater activation for low-rating than high-rating outcomes, indicating stronger neural responses to negative than positive emotions across feedback types. Complete feedback also elicited greater activation than partial feedback within the same emotional valence. Network-level analyses revealed partially dissociable neural profiles for positive and negative emotions. Positive emotions, including elation and relief, predominantly recruited the somatomotor network, whereas negative emotions, including disappointment and regret, engaged broader distributions across the default mode, dorsal attention, and other large-scale networks. Regret elicited the largest activation extent, whereas elation elicited the smallest. Region-of-interest analyses showed that bilateral orbitofrontal cortex (OFC) responses were significantly greater for negative than positive emotions and for complete than partial feedback conditions. Across all four emotions, right OFC activation was negatively associated with maximization. For elation, relief, and disappointment, right OFC activation was also negatively associated with alternative search and decision difficulty, whereas these associations were absent for regret. Together, these findings demonstrate that subjective emotional evaluation, counterfactual context, and decision-related traits jointly shape the neural processing of decision outcomes, while suggesting relatively trait-independent neural processing of regret.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122303"},"PeriodicalIF":5.3,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149224581","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":"Precise modeling of task-related sensorimotor activation based on simultaneous surface electromyography.","authors":"Monika Jasenská, Pavel Hok, Martin Kojan, Ondřej Burkot, Barbora Kolářová, Aleš Holobar, Petr Hluštík","doi":"10.1016/j.neuroimage.2026.122300","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122300","url":null,"abstract":"<p><p>The aim of this study was to evaluate the relationship between motor control of ankle movements and actual motor performance using simultaneous functional magnetic resonance imaging (fMRI) and surface electromyography (EMG) in healthy individuals. Twenty participants performed dorsi-/plantarflexion of the ankle (Ankle) and gait imagery in a block design during fMRI. First-level models consisting of task regressors included either orthogonalized accelerometry (Acc) from the foot, EMG from the tibialis anterior, EMG with Acc, EMG split across conditions, or none. Each model was additionally evaluated either by default with or without a temporal derivative (TD) of the ankle movement task regressor. Voxel-wise and post-hoc region-of-interest (ROI) analyses revealed that both Acc and EMG explained fMRI signal in the primary sensorimotor cortices, while EMG was additionally associated with activation in the cerebellar vermis and the secondary somatosensory cortex. The two latter findings were, however, neither reproduced when separating the signal fluctuations during rest and gait imagery nor reflected in pairwise comparisons. Leaving out the TD reduced each model's performance by increasing unexplained variance, but resulted in more signal being explained by the EMG or Acc in the cerebellum, reflecting that it preferentially exhibited brief signal changes during transitions between conditions. Taken together, both EMG and Acc enabled capturing specific brain activity related to the movement variability; however, including the TD may significantly affect the ability to detect EMG- or Acc-related signal in regions with transient fMRI responses sensitive to changes in movement context, such as the cerebellum.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122300"},"PeriodicalIF":5.3,"publicationDate":"2026-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149216511","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":"Interplay of action-based prediction and top-down attention: EEG evidence for joint modulation of late perceptual processing.","authors":"Thomas Holstein, Jean-Christophe Sarrazin, Bruno Berberian, Andrea Desantis","doi":"10.1016/j.neuroimage.2026.122293","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122293","url":null,"abstract":"<p><p>Voluntary action shapes our perception through sensory predictions of its consequences. These predictions are thought to inhibit perceptual processing of predicted outcomes, leading to sensory attenuation. However, some studies have reported findings that contrast with this effect, suggesting that the influence of predictions may reflect, or interact with, attentional processes. Here, we investigated the interplay of action-based prediction and top-down attention on early and late perceptual processing, with prediction and attention referring to the likelihood of a sensory event and its behavioral relevance, respectively. Electroencephalography (EEG) was recorded while participants viewed two sequential gratings. The orientation of the first was either predicted and self-generated or unpredicted and externally generated. Participants judged the tilt direction of the second grating relative to the first but responded only when the grating appeared in a task-relevant color. EEG analyses revealed no modulation of early visual potentials (N1a), but modulations at later processing stages. Specifically, the P3b exhibited reduced amplitude for predicted compared to unpredicted stimuli, but only when they were task-relevant, whereas task-relevance enhanced the P3b only for unpredicted stimuli. Interestingly, multivariate pattern analysis showed significant temporal clusters for decoding the grating's orientation exclusively for predicted and task-relevant stimuli, although decoding performance did not significantly differ between conditions. Furthermore, predicted and task-relevant stimuli elicited faster behavioral responses, with prediction-related P3b latency differences correlating with reaction-time differences. Overall, converging findings from the P3b, multivariate, time-frequency and behavioral analyses provide suggestive evidence that top-down attention and action-based prediction may jointly facilitate late perceptual and decision-related processing.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122293"},"PeriodicalIF":5.3,"publicationDate":"2026-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149216525","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":"Neural dynamics of auditory attention: Interactions between top-down and bottom-up processes.","authors":"S Graceffo, M Elhilali","doi":"10.1016/j.neuroimage.2026.122285","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122285","url":null,"abstract":"<p><p>Auditory attention allows listeners to navigate complex acoustic environments by prioritizing behaviorally-relevant sounds while limiting interference from competing input. This process is guided by a dynamic interplay between top-down attention, driven by behavioral goals and expectations, and bottom-up attention, triggered by stimulus-driven salience. Although this distinction remains useful at a conceptual level, growing evidence suggests that auditory attention emerges from continuous interactions between goal-directed and stimulus-driven processes that recruit partially overlapping neural systems and vary with task demands, stimulus properties, and prior experience. This review focuses on the neural mechanisms underlying attentional control and interactions between top-down and bottom-up auditory attention. It synthesizesevidence from neurophysiological, behavioral, and neuroimaging studies and explores how top-down control modulates the neural processing and attentional impact of salient input, how bottom-up signals override attentional focus, and how these interactions are shaped by task demands and individual cognitive capacity. The findings synthesized here support a view of auditory attention as a flexible and adaptive system, whose operation emerges from context-dependent interactions, with important implications for models of attention and real-world listening behaviors.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122285"},"PeriodicalIF":5.3,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207407","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":"Decoding Spatial Attention in the Cocktail Party Problem Using Whole-head High-Density fNIRS.","authors":"Sudan Duwadi, De'Ja Rogers, Alex D Boyd, Laura B Carlton, Yiwen Zhang, Anna Kawai Gaona, Aneesa Diya Pathiyaparambath, Ravin Chaudhury, Grace Magee, Bernhard B Zimmermann, Walker J O'Brien, Alexander von Lühmann, David A Boas, Meryem A Yücel, Kamal Sen","doi":"10.1016/j.neuroimage.2026.122292","DOIUrl":"https://doi.org/10.1016/j.neuroimage.2026.122292","url":null,"abstract":"<p><p>Spatial attention is critical for solving the cocktail party problem, a longstanding problem in neuroscience and artificial speech recognition. The ability to decode where humans are attending in a cocktail party like scene would empower applications in brain computer interfaces and assistive devices such as hearing aids. Here we demonstrate that, in an overt attention task, the attended spatial location can be decoded robustly from single trial hemodynamic responses, using a whole head high density fNIRS system. We also identify critical brain regions that make the highest contribution to decoding accuracy. Specifically, we find that decoding based on a small fraction of channels located within the left and right inferior parietal lobule (IPL) achieves maximal decoding accuracy comparable to all channels. Decoding fell close to chance in a covert auditory condition in which participants held central fixation while attending to the same talkers, indicating that auditory attention alone without orientation is not sufficient for decoding. Finally, control experiments suggest that overt-condition decoding is influenced by sustained eye position/gaze direction, not eye movement. These results support the development of fNIRS-integrated BCIs and assistive devices controlled by overt spatial attention.</p>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":" ","pages":"122292"},"PeriodicalIF":5.3,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207278","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}