NeuroImage最新文献

{"title":"Imagined movement modulates cardiac-cortico-cortical and cardiac-cortico-cerebellar oscillatory networks","authors":"Diego Candia-Rivera,&nbsp;Mario Chavez,&nbsp;Fabrizio De Vico Fallani,&nbsp;Marie-Constance Corsi","doi":"10.1016/j.neuroimage.2026.121804","DOIUrl":"10.1016/j.neuroimage.2026.121804","url":null,"abstract":"<div><div>Understanding the mechanisms of motor imagery, the mental simulation of movement without execution, is key for the development of neurotechnologies, including understanding inter-individual variability in motor imagery performance. For instance, for detecting covert motor intent in noncommunicative patients or refining motor commands through brain-computer interfaces. While motor imagery engages motor-related brain regions, its precise mechanisms remain unclear, particularly in relation to cardiac dynamics. Evidence suggests heart-rate variability features have potential to enhance tasks’ classifications, yet the brain-heart relationship is not well understood. In this study, we examined motor imagery learning using a task involving right-hand grasping imagery. We found that motor imagery is correlated with a task-dependent modulation of cardiac sympathetic activity and its relation with directed functional connectivity from the supplementary motor area to premotor and primary motor cortices. Additionally, cerebellar-supplementary motor area segregation, in relation to cardiac parasympathetic activity, indexed longitudinal motor learning. These results suggest that dynamic reconfiguration of brain-heart interactions contributes to sensorimotor function and learning-related physiology during motor imagery, supporting the brain-heart axis as a functional component of motor imagery rather than a passive correlate.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121804"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146197795","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":"DeepMultiConnectome: Deep multi-task prediction of structural connectomes directly from diffusion MRI tractography","authors":"Marcus J. Vroemen ,&nbsp;Yuqian Chen ,&nbsp;Yui Lo ,&nbsp;Tengfei Xue ,&nbsp;Weidong Cai ,&nbsp;Fan Zhang ,&nbsp;Josien P.W. Pluim ,&nbsp;Lauren J. O'Donnell","doi":"10.1016/j.neuroimage.2026.121765","DOIUrl":"10.1016/j.neuroimage.2026.121765","url":null,"abstract":"<div><div>Diffusion MRI (dMRI) tractography enables in vivo mapping of brain structural connections, but traditional connectome generation is time-consuming and requires gray matter parcellation, posing challenges for large-scale studies. We introduce DeepMultiConnectome, a deep-learning model that predicts structural connectomes directly from tractography, bypassing the need for gray matter parcellation while supporting multiple parcellation schemes. Using a point-cloud-based neural network with multi-task learning, the model classifies streamlines according to their connected regions across two parcellation schemes, sharing a learned representation. By classifying individual streamlines, our method’s output serves as a flexible prerequisite for constructing a wide range of differently weighted connectomes. We train and validate DeepMultiConnectome on tractography from the Human Connectome Project Young Adult dataset (<em>N</em> = 1000), labeled with an 84 and 164 region gray matter parcellation scheme. DeepMultiConnectome predicts multiple structural connectomes from a 3-million-streamline tractogram in ∼40 seconds. DeepMultiConnectome is evaluated by comparing predicted connectomes with traditional connectomes generated using the conventional method of labeling streamlines using a gray matter parcellation. The predicted connectomes show high agreement with traditionally generated connectomes across two parcellation schemes and multiple weighting strategies, and largely preserve network properties. Pearson correlations were <em>r</em> = 0.992 and 0.986 for streamline-count-weighted connectomes, <em>r</em> = 0.995 and 0.992 for SIFT2-weighted connectomes, and <em>r</em> = 0.775 and 0.727 for mean-FA-weighted connectomes. Test-retest analysis and downstream predictions of age and cognitive function demonstrate performance and reproducibility comparable to traditionally generated connectomes. Overall, DeepMultiConnectome provides a fast and scalable model for generating subject-specific connectomes across multiple parcellation and weighting schemes.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121765"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146097191","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 scoping review of variations in cerebral Doppler venous waveforms in infants","authors":"Siv Steinsmo Ødegård ,&nbsp;Anders Hagen Jarmund ,&nbsp;Sindre Andre Pedersen ,&nbsp;Paul Govaert ,&nbsp;Jeroen Dudink ,&nbsp;Siri Ann Nyrnes","doi":"10.1016/j.neuroimage.2026.121766","DOIUrl":"10.1016/j.neuroimage.2026.121766","url":null,"abstract":"<div><div>Advances in ultrasound technology have positioned cerebral venous Doppler as a valuable method for evaluating cerebral hemodynamics, complementing arterial velocity assessments. This scoping review provides an overview of normal and abnormal venous waveforms that can guide management. A systematic search in three bibliographic databases identified 5320 unique records, of which 37 studies met inclusion criteria, reporting 205 cerebral venous Doppler waveforms from at least three infants under one year old. These studies describe both physiological variation and changes associated with lesions and medical interventions, most commonly reported using velocity-based parameters. Six studies employed a total of three different scoring systems to characterize velocity fluctuations. An atlas of cerebral venous Doppler waveforms was compiled. It highlights differences between the superficial and deep venous systems and identifies characteristic pathological changes. These include velocity fluctuation in the internal cerebral vein associated with germinal matrix and intraventricular hemorrhage; ventilatory- and extracorporeal membrane oxygenation (ECMO) pump-synchronous flow in the superior sagittal sinus; and perioperative velocity monitoring in the superior sagittal sinus in cases of Vein of Galen malformation. The review also discusses the impact of head position and external compression on venous drainage. Future studies should deepen understanding of cerebral venous hemodynamics in conditions causing systemic compromise. Investigations into the influence of head position during the transitional period in preterm neonates may help guide clinical management during this critical phase. Longitudinal studies on velocity fluctuation in relation to disease progression and medical interventions may enhance care of preterm and critically ill term infants.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121766"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146106399","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 neurophenomenology of a self-induced transcendental visionary state: A case study","authors":"Gabriel Della Bella ,&nbsp;Agustina Velez Picatto ,&nbsp;Dante Sebastián Galván Rial ,&nbsp;Sebastián Cukier ,&nbsp;Gustavo Foa Torres ,&nbsp;Magaly Catanzariti ,&nbsp;Diego Mateos ,&nbsp;Pedro Lamberti ,&nbsp;Etzel Cardeña ,&nbsp;Pablo Barttfeld","doi":"10.1016/j.neuroimage.2026.121784","DOIUrl":"10.1016/j.neuroimage.2026.121784","url":null,"abstract":"<div><div>Non-ordinary states of consciousness (NOC) offer a way to examine how large-scale brain dynamics reorganize as experience changes. We studied a participant able to reliably enter a self-induced NOC state characterized by vivid imagery, altered bodily perception, and a sense of unity. Across 20 fMRI sessions, we measured functional connectivity in four conditions (Baseline, Transition, NOC, and Residual) and compared the results with a matched control group. During the Transition phase, connectivity became more variable, indicating a temporary destabilization of network organization. In the NOC state, inter-network connectivity decreased broadly, with visual cortex showing reduced coupling to auditory, sensorimotor, orbitofrontal, thalamic, and cerebellar regions, and the somatomotor-dorsal network disengaging from auditory and language cortices, paralleling the reported visual phenomena and changes in bodily experience. In contrast, frontoparietal and salience networks showed increased coupling with precuneus/posterior cingulate, multimodal temporal cortex, and cerebellar hubs, in agreement with subjective reports of sustained inward-directed attention and stable absorption. Entropy and complexity analyses revealed systematic shifts that tracked the experiential sequence and returned to baseline in the Residual condition. This single-case study brings together something uncommon: controlled experimentation, voluntary induction of NOC states, and rich phenomenological data. Taken together, these elements offer a strong foundation for neurophenomenological research and illustrate why pairing structured paradigms with lived experience is useful for understanding non-ordinary states of consciousness.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121784"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146132775","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":"Toward a better measure of functional laterality: Comparing and refining laterality indices in resting-state functional connectivity","authors":"Taeyoung Lee ,&nbsp;Kyung Hwan Kim ,&nbsp;Seo Yeong Ha ,&nbsp;Hang Joon Jo","doi":"10.1016/j.neuroimage.2026.121782","DOIUrl":"10.1016/j.neuroimage.2026.121782","url":null,"abstract":"<div><div>Systematic investigations into the lateralized human brain have revealed a bivariate functional architecture that underpins distinct cognitive processes. This architecture manifests through inter- and intra-hemispheric lateralization, captured respectively by neural integration and segregation. In this study, we conducted a comprehensive evaluation of multiple quantitative laterality metrics in resting-state fMRI connectivity, using conceptual models to illustrate how inter- and intra-hemispheric correlations shape functional lateralization. We further highlight the critical influence of factors such as correlation sign, correlation coefficient distribution, and statistical thresholding methodology on the interpretation of functional connectivity-based laterality indices. Our findings show that, in our dataset, laterality metrics based on positive-only functional connectivity with a lenient connection-level threshold most consistently capture established relationships between functional brain lateralization and performance in language and visuospatial domains.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121782"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146132703","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":"Attention decoding at the cocktail party: Preserved in hearing aid users, reduced in cochlear implant users","authors":"Constantin Jehn ,&nbsp;Jasmin Riegel ,&nbsp;Tobias Reichenbach ,&nbsp;Anja Hahne ,&nbsp;Niki Katerina Vavatzanidis","doi":"10.1016/j.neuroimage.2026.121771","DOIUrl":"10.1016/j.neuroimage.2026.121771","url":null,"abstract":"<div><div>Users of hearing aids (HAs) and cochlear implants (CIs) experience significant difficulty understanding a target speaker in multi-talker environments or when other background noise is present. Segregation of a particular voice from background noise occurs partly through enhanced cortical tracking of amplitude fluctuations in the target signal. Measuring a person’s cortical tracking allows decoding their focus of attention and may be used for neurofeedback in hearing devices, potentially aiding their users with speech-in-noise comprehension. Most studies on cortical speech tracking have employed typical hearing (TH) individuals, whereas studies in people with hearing impairment whose cortical tracking may differ are still scarce. The objective of this study was to compare cortical speech tracking of HA (n=29) and CI users (n=24) to that of age-matched TH individuals (n=29). We recorded EEG data while the participants attended one of two competing talkers (one with a female and one with a male voice), in a free-field acoustic environment. Importantly, HA users as well as CI users used their personal, clinically-fitted devices. Cortical speech tracking was assessed through linear backward and forward models that related the EEG data to the speech envelope. For the CI users, electrical artifacts stemming from the implant were addressed through a bespoke method for artifact rejection. We found that the HA group exhibited cortical tracking and attentional modulation that were largely comparable to those of the TH group. CI users also showed successful cortical tracking. However, they displayed a profound deficit in attentional modulation, seen in the significantly poorer neural segregation of the attended vs. the ignored speech streams. These results shed light on a neurobiological mechanism for speech-in-noise comprehension and have implications for neurofeedback in hearing devices.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121771"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137775","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":"VSSI2p-Net: Physics-guided deep unfolding with L2p-norm and variation sparsity for EEG source imaging","authors":"Luhua Wang ,&nbsp;Jun Zhang ,&nbsp;Zhenghui Gu ,&nbsp;Ke Liu ,&nbsp;Wei Wu ,&nbsp;Tianyou Yu ,&nbsp;Zhuliang Yu ,&nbsp;Yuanqing Li","doi":"10.1016/j.neuroimage.2026.121793","DOIUrl":"10.1016/j.neuroimage.2026.121793","url":null,"abstract":"<div><div>Electroencephalogram (EEG) source imaging (ESI) is highly underdetermined, which poses a long-standing challenge in neuroimaging. Traditional methods typically rely on predefined priors to constrain the solution space; however, the need for manual parameter adjustments often makes it difficult to achieve optimal integration of prior information. Although recent deep learning methods can automatically update parameters in a data-driven manner, their black-box characteristics lead to a lack of interpretability and the need for extensive training sets. To integrate the advantages of these two types of methods, we propose a novel neural network model based on deep unfolding, called variation sparse source imaging network (VSSI<span><math><msub><mrow></mrow><mrow><mn>2</mn><mi>p</mi></mrow></msub></math></span>-Net). Specifically, we introduce variation sparsity and <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>2</mn><mo>,</mo><mi>p</mi></mrow></msub></math></span> norm (<span><math><mrow><mn>0</mn><mo>&lt;</mo><mi>p</mi><mo>&lt;</mo><mn>1</mn></mrow></math></span>) regularization into the model of the ESI problem and utilize the Alternating Direction Method of Multipliers (ADMM) to iteratively solve this model. Furthermore, by mapping the iterative process into a neural network structure, the proposed VSSI<span><math><msub><mrow></mrow><mrow><mn>2</mn><mi>p</mi></mrow></msub></math></span>-Net can optimize all parameters, including the critical <span><math><mi>p</mi></math></span> in <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>2</mn><mo>,</mo><mi>p</mi></mrow></msub></math></span>-norm and the variation sparsity operator, in an end-to-end manner with a reasonably sized training set. In this way, VSSI<span><math><msub><mrow></mrow><mrow><mn>2</mn><mi>p</mi></mrow></msub></math></span>-Net achieves more flexible prior information integration while retaining the interpretability of traditional methods, so that a more accurate and efficient solution for ESI can be obtained. We compared the performance of VSSI<span><math><msub><mrow></mrow><mrow><mn>2</mn><mi>p</mi></mrow></msub></math></span>-Net with several traditional baseline methods and state-of-the-art deep learning methods on synthetic and real datasets. The results show that VSSI<span><math><msub><mrow></mrow><mrow><mn>2</mn><mi>p</mi></mrow></msub></math></span>-Net significantly outperforms existing methods in source localization accuracy, spatial range estimation, and imaging speed across various source configurations.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121793"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143011","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":"Stress-induced takotsubo syndrome: dynamic changes in regional cerebral metabolism revealed by quantitative PET imaging","authors":"Alejandro Ariza-Carrasco ,&nbsp;Thulaciga Yoganathan ,&nbsp;María Alonso de Leciñana ,&nbsp;Thomas Viel ,&nbsp;Nidaa Mikail ,&nbsp;Joaquin L. Herraiz ,&nbsp;Jose M. Udias ,&nbsp;Paula Ibáñez ,&nbsp;Bertrand Tavitian ,&nbsp;Mailyn Pérez-Liva","doi":"10.1016/j.neuroimage.2026.121797","DOIUrl":"10.1016/j.neuroimage.2026.121797","url":null,"abstract":"<div><div>Stress significantly contributes to cardiovascular diseases such as Takotsubo syndrome (TTS), which mimics an acute coronary syndrome without coronary obstruction. TTS is triggered by surgery, trauma, and emergency treatments in patients, and is reproduced in animal models by a catecholamine surge that impacts cardiac sympathetic innervation. The action of catecholamines on energy metabolism is well documented in the heart, less so in the brain. We investigated the effects of acute catecholaminergic stress on regional cerebral glucose metabolism and interregional metabolic organization in a TTS rat model using FDG-PET and quantitative two-tissue compartment modeling. Adult female rats received a single intraperitoneal injection of isoprenaline (ISO) (50 mg/kg). Dynamic FDG-PET imaging was performed at baseline, 2 hours (acute phase), and 7 days (recovery phase) post-injection. Kinetic parameters, namely glucose inflow (K1) and glucose phosphorylation (k3), were quantified in 58 brain regions. Interregional metabolic coordination, defined as statistically significant linear correlations between regional kinetic parameters, was assessed across functional brain areas. During the acute phase, the catecholaminergic surge induced widespread reductions in glucose inflow and regional decreases in phosphorylation, particularly in the limbic and sensorimotor areas. During the recovery phase, most regions remained below baseline. Metabolic coordination increased for glucose inflow in both phases but declined for phosphorylation, especially during recovery, indicating a disruption of metabolic synchronization. Persistent changes in brain metabolism imply that mid-to-long-term changes in regional cerebral metabolism may contribute to long-term TTS consequences.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121797"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146181428","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":"Unveiling clouded consciousness: Broad-band EEG slowing tracks recovery from post-traumatic confusional state","authors":"Michele Angelo Colombo ,&nbsp;Chiara-Camilla Derchi ,&nbsp;Tiziana Atzori ,&nbsp;Elisabetta Litterio ,&nbsp;Pietro Arcuri ,&nbsp;Chiara Valota ,&nbsp;Arturo Chieregato ,&nbsp;Jorge Navarro ,&nbsp;Marcello Massimini ,&nbsp;Angela Comanducci","doi":"10.1016/j.neuroimage.2026.121783","DOIUrl":"10.1016/j.neuroimage.2026.121783","url":null,"abstract":"<div><h3>Background</h3><div>Post-traumatic confusional state (PTCS) frequently occurs during the recovery from disorders of consciousness (DoC) following severe traumatic brain injury (TBI). Confusional symptoms span multiple domains influencing consciousness, including impairments in the access and integration of mental contents, distortions in perceptual and emotional experiences, vigilance fluctuations, and deficits in memory, orientation, and executive control. While the clinical presentation can be systematically characterized using the Confusion Assessment Protocol (CAP), the underlying neurophysiological mechanisms remain poorly understood. Specifically, slowing of both periodic and aperiodic EEG activity is a consistent finding across multiple alterations of consciousness.</div></div><div><h3>Objective</h3><div>We assessed whether recovery from PTCS involves a renormalization of EEG slowing.</div></div><div><h3>Methods</h3><div>We recorded resting-state EEG from subacute severe TBI patients at admission (T0), comparing patients with PTCS (N=22) to TBI Controls who had already emerged (N = 19). Patients with PTCS were longitudinally monitored using CAP, and a follow-up EEG (T1) was acquired after rehabilitation either upon recovery (N=19) or at discharge (N=3).</div></div><div><h3>Results</h3><div>Recovery from PTCS was marked by partial normalization of the spectral profile—as indexed by the spectral exponent, and peak frequency—converging toward the profile of TBI Controls. However, marginal persistent elevations in power, indexed by spectral offset and delta power, indicated residual abnormalities. Spectral features, particularly spectral exponent and offset, correlated with CAP and robustly discriminated the presence of PTCS (bivariate model ROC AUC = 0.894).</div></div><div><h3>Conclusion</h3><div>Results show that PTCS is marked by broadband EEG slowing affecting both periodic and aperiodic activity. Spectral reorganization over time provides insight into the mechanisms of recovery from PTCS and may inform rehabilitation pathways.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121783"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146132734","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":"Temporal dynamics of flexible cognitive control","authors":"Chengyuan Wu ,&nbsp;Carol A. Seger ,&nbsp;Yixuan Ku ,&nbsp;Canhuang Luo ,&nbsp;Ying Zhou ,&nbsp;Jiefeng Jiang ,&nbsp;Qi Chen","doi":"10.1016/j.neuroimage.2026.121787","DOIUrl":"10.1016/j.neuroimage.2026.121787","url":null,"abstract":"<div><div>In dynamic environments, flexible cognitive control adaptively adjusts processing through proactive mechanisms deployed in advance and reactive mechanisms engaged upon conflict. Previous studies have primarily focused on identifying neural networks supporting specific control components, while less is known about how multiple components interact over time to support adaptive control. To characterize these temporal dynamics, we combined electroencephalography (EEG) recordings with a face-word Stroop paradigm under changing conflict environment. A hierarchical Bayesian model was used to estimate trial-wise learning rate, predicted conflict level, and prediction error, providing computational indices of cognitive control flexibility. Neural correlation analysis indicated that these variables correlated with Theta, Alpha, and Beta oscillations in distinct brain regions. Granger causality analyses revealed connectivity patterns among these regions that varied across different task phase. Furthermore, connections reflecting updates to predicted conflict level prior to stimulus onset indexed individual strength in proactive control, while connections reflecting learning rate updates after stimulus onset indexed reactive control. These findings highlight how oscillatory dynamics coordinate multiple control components and provide new insight into how proactive and reactive control emerge as distinct modes within this interconnected neural architecture of flexible cognitive control.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121787"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137738","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}