NeuroImage最新文献

{"title":"Probabilistic Cognitive State Modeling (PCSM): Decoding dynamic brain states to derive emergent cognitive processing properties from task fMRI","authors":"Drew E. Winters","doi":"10.1016/j.neuroimage.2026.121807","DOIUrl":"10.1016/j.neuroimage.2026.121807","url":null,"abstract":"<div><div>Studying flexible, adaptive transitions between cognitive tasks and serial–parallel processing under changing task demands has been central to understanding human cognition. Advances in neuroimaging analysis have improved the ability to link cognition with brain function, motivating methods that characterize dynamic brain activity to quantify emergent cognitive properties during task-based fMRI.</div><div>Probabilistic Cognitive State Modeling (PCSM) combines Finite Impulse Response modeling of BOLD activity with a Gaussian Mixture Model–Hidden Markov Model to infer recurring multivariate patterns of task-evoked BOLD responses across spatially distributed regions over time (“brain states”). From the resulting posterior structure, PCSM deterministically derives interpretable processing metrics, including serial–parallel deviation, cognitive demand, and serial bottleneck.</div><div>Data-informed generative simulations evaluated PCSM across systematically varied noise levels and transition regimes. Results show that PCSM reliably recovers latent structure (∼98 % state-alignment accuracy under known generative conditions) and produces stable parameter estimates across simulation regimes. Threshold analyses identify reliable boundaries between parallel, mixed, and serial processing modes and recover expected relationships among demand, and bottleneck.</div><div>Together, these results demonstrate that PCSM provides a principled framework for characterizing dynamic task-evoked processing architectures and estimating individual-level cognitive dynamics from task-based fMRI, supporting future investigation of cognitive processing constraints across tasks and populations.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121807"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146201708","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":"Cerebro-cerebellar structure-function coupling’s role in motor recovery after infarction","authors":"Jing Liu ,&nbsp;Yi Shan ,&nbsp;Bi-Xiao Cui ,&nbsp;Zhen-Ming Wang ,&nbsp;Shao-Zhen Yan ,&nbsp;Jie Xu ,&nbsp;Lin-Lin Ye ,&nbsp;Lei Cao ,&nbsp;Miao Zhang ,&nbsp;Jie Lu","doi":"10.1016/j.neuroimage.2026.121810","DOIUrl":"10.1016/j.neuroimage.2026.121810","url":null,"abstract":"<div><h3>Objective</h3><div>To investigate the pathway-specific structure-function coupling induced by focal subcortical infarction and its influence on clinical symptoms.</div></div><div><h3>Methods</h3><div>In this prospective study, 50 patients with unilateral subcortical infarction and motor impairment and 50 matched controls underwent resting state fMRI, DTI, and Fugl-Meyer-Assessment lower-extremity (FMA-LE) at 7–14- and 30-days post-infarction. To analyze the pathway-specific structure-function coupling, we evaluated the association between structural integrity of the corticospinal tract (CST), dentate thalamocortical tract (DTCT), cortico-pontocerebellar tract (CPCT), and dorsal spinocerebellar tract (DSCT) and functional connectivity (FC) of corresponding subregions. Moderation analysis assesses whether the structure-function coupling pathway moderates FMA-LE.</div></div><div><h3>Results</h3><div>At baseline, patients exhibited significantly lower structural integrity of DTCT, DSCT, and CST than controls. We found structure-function couplings in the three motor pathways of the cerebro-cerebellar circuit: (1) contralesional thalamus to ipsilesional cerebellum-crus_2 with dentate thalamocortical tract (DTCT), (2) contralesional thalamus to cerebellum vermis_10 with dorsal spinocerebellar tract (DSCT), (3) ipsilesional precentral gyrus to frontal medial gyrus with CST. The baseline DSCT structural integrity specificity modulates the relationship between FC and FMA-LE over 30 days.</div></div><div><h3>Conclusions</h3><div>We observed that cerebro-cerebellar circuit structure-function coupling after infarction, based on its anatomy and mapped to motor function (with DSCT as the key pathway mediating/moderating prognosis), serves as a potent biomarker for lower limb prognosis and a basis for precise rehabilitation.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121810"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146207408","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":"Morphometric dissimilarity in association cortices linked to autism subtype with more severe symptoms","authors":"Hongxiu Jiang ,&nbsp;Raul Rodriguez-Cruces ,&nbsp;Ke Xie ,&nbsp;Valeria Kebets ,&nbsp;Yezhou Wang ,&nbsp;Clara F. Weber ,&nbsp;Ying He ,&nbsp;Jonah Kember ,&nbsp;Hilary Sweatman ,&nbsp;Zeus Gracia Tabuenca ,&nbsp;Jean-Baptiste Poline ,&nbsp;Danilo Bzdok ,&nbsp;Seok-Jun Hong ,&nbsp;Boris Bernhardt ,&nbsp;Xiaoqian Chai","doi":"10.1016/j.neuroimage.2026.121775","DOIUrl":"10.1016/j.neuroimage.2026.121775","url":null,"abstract":"<div><div>Autism spectrum disorder (ASD) is a prevalent and heterogeneous neurodevelopmental condition marked by atypical brain connectivity. Understanding ASD neural subtypes at the network level is critical for clarifying its neuroanatomical heterogeneity. Morphometric similarity networks (MSNs), derived from region-to-region similarity across multiple anatomical features, offer a powerful approach for capturing individual-level neural architecture. In this study, MSNs were estimated from seven anatomical features in 348 individuals with ASD and 452 typically developing (TD) controls. Across all ASD participants, the first principal component of MSN values was negatively correlated with social and communication severity. Three ASD subtypes with distinct MSN patterns were identified. Subtype-1, characterized by weaker morphometric similarity values in frontotemporal association regions compared to TD individuals, exhibited the most severe symptoms in social, communication and repetitive behaviors, and displayed hyperconnectivity between the salience and visual networks, and between language and visual networks. Subtype-2 showed greater values of morphometric similarities than TD and less severe social symptoms compared to subtype-1, along with hyperconnectivity between default and salience networks relative to TD. Subtype-3 displayed morphometric similarity values largely comparable to TD and the least severe symptoms out of the three subtypes. Transcriptomic analysis revealed that GABAergic parvalbumin and glutamatergic intratelencephalic-projecting neurons were key cell types differentiating subtypes. These findings suggest the existence of distinct ASD neuroanatomical subtypes defined by regional morphometric similarity, each linked to unique behavioral, functional, and transcriptomic profiles. Morphometric dissimilarity in association regions may serve as a neural signature for ASD subtypes characterized by more severe clinical manifestations.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121775"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146132793","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":"Recognizing EEG responses to active TMS vs. sham stimulations in different TMS-EEG datasets: A machine learning approach","authors":"Ahmadreza Keihani ,&nbsp;Francesco L. Donati ,&nbsp;Simone Russo ,&nbsp;Sara Parmigiani ,&nbsp;Michela Solbiati ,&nbsp;Adenauer G. Casali ,&nbsp;Matteo Fecchio ,&nbsp;Omeed Chaichian ,&nbsp;John Rothwell ,&nbsp;Marcello Massimini ,&nbsp;Lorenzo Rocchi ,&nbsp;Mario Rosanova ,&nbsp;Fabio Ferrarelli","doi":"10.1016/j.neuroimage.2026.121802","DOIUrl":"10.1016/j.neuroimage.2026.121802","url":null,"abstract":"<div><div>Transcranial Magnetic Stimulation with simultaneous Electroencephalogram (TMS-EEG) allows for the assessment of neurophysiological properties of cortical neurons. However, TMS-evoked EEG potentials (TEPs) can be affected by components unrelated to TMS direct neuronal activation. Accurate, automatic tools are therefore needed to establish the quality of TEPs. We defined innovative comparisons, including effects of both baseline and post-TMS responses, while employing a sequence-to-sequence machine learning model to objectively ascertain active TMS vs. sham stimulation responses.</div><div>Two independent TMS-EEG datasets including TMS and several sham stimulation conditions were obtained from the left motor area of 33 healthy individuals (total: 27,590 trials across datasets). A Bi-directional Long Short-Term Memory (BiLSTM) machine learning network was used to label each time point of the EEG signals as pertaining to TMS or sham conditions.</div><div>For TMS conditions, post-stimulus vs. baseline/pre-stimulus EEG comparisons yielded moderate (60 %-75 %) single-trial accuracy and high-accuracy (&gt;75 %) for 20 trials across datasets. For sham conditions, post- vs. baseline/pre-stimulus EEG comparisons yielded lower accuracy rates than for TMS conditions, except for unmasked auditory stimulation. Baseline/pre-stimulus TMS vs. baseline/pre-stimulus sham EEG comparisons showed chance-level accuracy. Conversely, post-stimulus TMS vs. post-stimulus sham EEG comparisons had moderate (single trial) to high (20 trial) accuracy, except for TMS with and without the click noise masking.</div><div>Consistently across datasets, TEPs after active TMS are discernible from various sham stimulations after few trials and at the single-subject level using a BiLSTM ML model. This approach offers objective criteria to support TEP authenticity, which may help address ongoing discussions about TEP characteristics in TMS-EEG studies.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121802"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146195139","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":"Cognitive and neural mechanisms of improving informal reasoning in human-GenAI interactive learning contexts: An fNIRS study","authors":"Liangliang Xia ,&nbsp;Yan Dong ,&nbsp;Wei-Peng Teo","doi":"10.1016/j.neuroimage.2026.121796","DOIUrl":"10.1016/j.neuroimage.2026.121796","url":null,"abstract":"<div><div>While generative artificial intelligence (GenAI) has advanced personalized interactive learning, the cognitive and neural mechanisms underlying learners’ informal reasoning improvement remain underexplored. Thus, we conducted sliding-window correlation and k-means clustering to capture learners’ dynamic functional connectivity (dFC) states, time-varying correlations among brain regions, and examined their correlations with the informal reasoning improvement. 78 participants completed a learning task under either a traditional search engine-supported interactive learning mode (TSE group) or a human-GenAI interactive learning mode (GenAI group). Functional near-infrared spectroscopy (fNIRS) was employed to measure cortical hemodynamic responses from the medial and dorsolateral prefrontal cortex and the right temporo-parietal regions. The results showed that the two groups demonstrated no significant difference in informal reasoning improvement. Moreover, both groups presented a series of dynamic dFC states throughout the learning process, and the properties of these dFC states were similar across groups. Nevertheless, the neural correlates underlying informal reasoning improvement differed across groups. In the GenAI group, State 1, associated with goal-directed sense-making processes, showed a significant positive correlation with informal reasoning improvement. In contrast, in the TSE group, State 3, associated with the retrieval and extraction of task-relevant information, was significantly positively correlated with informal reasoning improvement. These findings deepen our understanding of brain dynamics in learning and uncover shared and distinct neural mechanisms that characterize the GenAI-supported and traditional search engine-supported interactive learning modes.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"328 ","pages":"Article 121796"},"PeriodicalIF":4.5,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146195133","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":"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}