Neuroimage-Clinical最新文献

{"title":"Distinct neurologic state in patients with traumatic brain injury and hemorrhagic stroke during the stage of acute disorders of consciousness and the correlation with the neurological prognosis: A multi-modal PET/rs-fMRI study","authors":"Danjing Yu ,&nbsp;Kemeng Gao ,&nbsp;Xiefeng Wang ,&nbsp;Lin Zhao ,&nbsp;Yi Sun ,&nbsp;Zhiyan Shen ,&nbsp;Yu Wang ,&nbsp;Ying Wang ,&nbsp;Wei Ding ,&nbsp;Lin Yang ,&nbsp;Ying Duan ,&nbsp;Daniel Cui ,&nbsp;Zekai Qiang ,&nbsp;Federico Capelli ,&nbsp;Yuxi Gong ,&nbsp;Ailiang Zeng ,&nbsp;Xi Wang ,&nbsp;Wei Yan","doi":"10.1016/j.nicl.2026.103990","DOIUrl":"10.1016/j.nicl.2026.103990","url":null,"abstract":"<div><h3>Purpose</h3><div>The exact mechanisms underlying the distinct neurological outcomes between Traumatic Brain Injury (TBI) and Hemorrhagic Stroke (HS) remain unclear. Our objective is to assess distinct features of neurologic state between comatose patients with TBI and HS during the stage of acute disorder of consciousness (aDoC) and to identify the correlation of neurologic features with prognosis.</div></div><div><h3>Methods</h3><div>Data were analyzed from TBI and HS patients examined by positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI) simultaneously. Primary clinical outcomes consisted of the state of consciousness and neurological prognosis. The regional neural activity was assessed by the amplitude of fractional low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) on rs-fMRI scans. The standardized uptake value (SUV) on PET scans quantified neural metabolism. Functional connectivity (FC) and graph theoretic approach (GTA) were employed to compare the FC patterns between TBI and HS. Correlations of PET/rs-fMRI indicators with the prognosis of HS and TBI were identified.</div></div><div><h3>Results</h3><div>Muti-modal PET/rs-fMRI analysis showed more active local neurological state in TBI patients than HS patients, specifically in the right precentral gyrus (PreCG.R), right postcentral gyrus (PoCG.R), right superior temporal gyrus (STG.R) and right middle temporal gyrus (MTG.R). TBI patients demonstrated significantly higher clustering coefficient and nodal efficiency of the sensorimotor network (SMN) along with lower connectivity and network efficiency in the default network (DMN) compared to HS patients. PET/rs-fMRI indicators significantly correlated with the neurological prognosis of TBI and HS.</div></div><div><h3>Conclusions</h3><div>This study elucidated the underlying mechanisms contributing to the distinct neurologic prognosis between comatose TBI and HS patients, and may contribute to the development of early targeted intervention strategies for specific diseases.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"50 ","pages":"Article 103990"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147657615","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":"Condition-dependent disruption of low-frequency EEG–fMRI coupling reveals delayed hemodynamic timing and motor-network reorganization in chronic stroke","authors":"Parikshat Sirpal ,&nbsp;Nishaal Parmar ,&nbsp;Beni Mulyana ,&nbsp;Hazem H. Refai ,&nbsp;Yuan Yang","doi":"10.1016/j.nicl.2026.103989","DOIUrl":"10.1016/j.nicl.2026.103989","url":null,"abstract":"<div><div>Neurovascular coupling (NVC) is frequently disrupted after stroke, yet its temporal alignment and motor-network organization during sensorimotor engagement remain incompletely characterized. We tested whether chronic hemiparetic stroke alters the temporal alignment between EEG low-frequency oscillations (LFOs; 0.1–1.5 Hz) and the fMRI BOLD response during peripheral finger stimulation, and whether these alterations map onto motor-network anatomy and motor impairment. Simultaneous EEG–fMRI was acquired in 13 participants (7 chronic stroke; 6 healthy controls), during block-design peripheral transcutaneous index finger stimulation. EEG was decomposed using empirical mode decomposition to isolate physiologically grounded LFO components and Hilbert amplitude envelopes were incorporated into voxel-wise EEG-informed fMRI models. To evaluate robustness to hemodynamic assumptions, we implemented canonical HRF modeling, a derivative-augmented basis set, and subject-specific HRF estimation. Spatial inference was anchored to the Human Motor Area Template (HMAT). Stroke participants exhibited delayed and attenuated stimulation-evoked BOLD responses relative to controls. Cross-modal timing analyses revealed a distributional shift of peak EEG–BOLD alignment lags in stroke toward smaller and more frequently negative values, consistent with altered temporal alignment in the context of delayed hemodynamics, as opposed to causal inversion. The relative ordering of timing and coupling effects was preserved across HRF modeling strategies. HMAT-constrained analyses demonstrated reduced ipsilesional M1/PMd coupling during paretic stimulation with increased contralesional premotor and SMA recruitment. Importantly, ipsilesional motor-region coupling scaled with upper-extremity Fugl–Meyer scores. Together, these findings demonstrate convergent temporal and spatial reorganization of EEG–BOLD coupling after stroke and support LFO-informed EEG–fMRI as a physiologically interpretable framework for quantifying motor-network neurovascular timing.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"50 ","pages":"Article 103989"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147595881","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":"Subregional thalamic atrophy in Progressive Supranuclear Palsy: A machine learning study","authors":"Camilla Calomino ,&nbsp;Maria Giovanna Bianco ,&nbsp;Chiara Camastra ,&nbsp;Jolanda Buonocore ,&nbsp;Pier Paolo Arcuri ,&nbsp;Aldo Quattrone ,&nbsp;Andrea Quattrone","doi":"10.1016/j.nicl.2026.103992","DOIUrl":"10.1016/j.nicl.2026.103992","url":null,"abstract":"<div><h3>Background</h3><div>Several MRI studies have documented thalamic atrophy in Progressive Supranuclear Palsy (PSP), but investigations to date have considered the whole thalami, without evaluating their subcomponents. This study aimed to assess atrophy of thalamic substructures in PSP and investigate their potential to support PSP differential diagnosis.</div></div><div><h3>Methods</h3><div>A total of 398 subjects were enrolled in the study, including 164 PSP patients, 180 Parkinson’s disease (PD) patients and 64 healthy controls (HC), from two cohorts. An automatic probabilistic segmentation of thalamic nuclei was employed on T1-weighted MRI images using FreeSurfer 7.4 to investigate thalamic subregional atrophy. Subsequently, machine learning analysis (XGBoost) was employed to differentiate 97 PSP from 98 PD patients, and the results were validated in an independent international cohort (67 PSP, 82 PD patients).</div></div><div><h3>Results</h3><div>PSP patients showed widespread thalamic atrophy, most prominent in the lateral, paraventricular, and pulvinar nuclei in comparison with HC. Conversely, no significant differences were observed between PD patients and HC. The machine learning model based on the thalamic nuclei volumes achieved excellent performance in distinguishing PSP from PD, and the results were validated in the independent international cohort (AUC: 0.96 in both cohorts), outperforming the volume of the whole thalamus (De Long test, p &lt; 0.05).</div></div><div><h3>Conclusion</h3><div>This study investigated subregional thalamic atrophy in PSP patients and demonstrated that a machine learning based on thalamic nuclei volumes was able to accurately distinguish PSP from PD in two independent cohorts, highlighting the potential of subregional thalamic atrophy as diagnostic biomarker for PSP.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"50 ","pages":"Article 103992"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147655522","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":"Resting-state EEG activity in depression: a systematic review and meta-analysis","authors":"Henrik Heitmann ,&nbsp;Jean-François Siani ,&nbsp;Paul Theo Zebhauser ,&nbsp;Peter Henningsen ,&nbsp;Stefan Leucht ,&nbsp;Josef Priller ,&nbsp;Markus Ploner","doi":"10.1016/j.nicl.2026.103997","DOIUrl":"10.1016/j.nicl.2026.103997","url":null,"abstract":"<div><div>Depression is a highly prevalent and disabling disorder affecting approximately 5% of the adult population worldwide. Despite its impact, the underlying pathophysiology remains insufficiently understood, and current treatments are only partially effective. Understanding electrophysiological correlates of depression offers promise for a better grasp of the underlying brain mechanisms and might even guide novel treatment approaches, including neuromodulation. EEG is particularly attractive for this purpose due to its wide availability, cost-effectiveness, and potential for direct neuromodulatory targeting.</div><div>We conducted a PROSPERO-registered systematic review in accordance with PRISMA guidelines to assess resting-state EEG activity in adult patients with depression, diagnosed according to DSM-IV/V or ICD-10/11. Included studies reported cross-sectional or correlational data on well-established quantitative EEG measures such as power, cordance, peak frequency, and alpha asymmetry. Semiquantitative analyses using modified albatross plots and <em>meta</em>-analyses were performed. Study quality was assessed with a modified Newcastle-Ottawa Scale.</div><div>Fifty-two studies met the inclusion criteria. Semiquantitative findings showed a trend for increased low-frequency (delta and theta) and high-frequency (beta and gamma) power, as well as left frontal alpha asymmetry, in depressed patients compared to healthy controls. However, <em>meta</em>-analysis only confirmed a significant increase in beta power. Results regarding disease severity correlations and data on peak alpha frequency and cordance were insufficient for interpretation. Risk of bias across studies was high.</div><div>Our results support a potential role for increased beta oscillations in depression. These oscillations may reflect disrupted corticolimbic control and reward processing and partially overlap with mechanisms implicated in chronic pain and fatigue. Further investigation is warranted into their potential as a diagnostic tool or even a biomarker, as well as their potential use as a neuromodulatory treatment target.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"50 ","pages":"Article 103997"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147802494","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":"Additive value of early-phase β-Amyloid-PET for the differential diagnosis of non-Alzheimer’s disease dementia","authors":"Sebastian Eckenweber ,&nbsp;Friederike Völter ,&nbsp;Nicolai Franzmeier ,&nbsp;Carla Palleis ,&nbsp;Olivia Wagemann ,&nbsp;Endy Weidinger ,&nbsp;Sabrina Katzdobler ,&nbsp;Elisabeth Wlasich ,&nbsp;Katja Sandkühler ,&nbsp;Guido Böning ,&nbsp;Johannes Gnörich ,&nbsp;Maximilian Scheifele ,&nbsp;Florian Eckenweber ,&nbsp;Daniel Janowitz ,&nbsp;Carolin Kurz ,&nbsp;Robert Perneczky ,&nbsp;Katharina Bürger ,&nbsp;Adrian Danek ,&nbsp;Günter Höglinger ,&nbsp;Johannes Levin ,&nbsp;Sonja Schönecker","doi":"10.1016/j.nicl.2026.103963","DOIUrl":"10.1016/j.nicl.2026.103963","url":null,"abstract":"<div><h3>Purpose</h3><div>Recent studies demonstrated strong agreement between early-phase β-amyloid-PET perfusion imaging and glucose hypometabolism assessed by [¹⁸F]FDG-PET, indicating the potential of early-phase β-amyloid-PET as a surrogate biomarker of neuronal injury. We therefore aimed to investigate the additive value of early-phase β-amyloid-PET for the differential diagnosis of non-Alzheimer’s disease dementia syndromes in clinical routine.</div></div><div><h3>Materials and methods</h3><div>[¹⁸F]florbetaben- and [¹⁸F]flutemetamol-PET scans (n = 379) performed between July 2013 and July 2021 were analyzed for their amyloid status and the presence of a neurodegenerative hypoperfusion pattern using visual assessment and z-score maps. In patients visually rated as amyloid-negative/neurodegeneration-positive (A-N+), the most likely diagnosis based on perfusion patterns was compared to the final clinical diagnosis, i.e. frontotemporal dementia or psychiatric disorders, suspected 4R-tauopathy, and suspected non-Alzheimer pathophysiology. Logistic regression models based on a data-driven selection of cerebral regions of hypoperfusion by principal component analysis were used to predict neurodegenerative disease and clinical diagnoses. Diagnostic accuracy was compared between visual assessment and the regression models.</div></div><div><h3>Results</h3><div>Neurodegeneration status was correctly identified in 78.8% (119/151) of amyloid-negative patients through visual rating, compared to 67.5% (102/151) using logistic regression. Visual assessment assigned 75.3% (67/89) of A-N+ patients to the correct diagnostic category. In contrast, the regression model classified 69.7% (62/89) of patients.</div></div><div><h3>Conclusions</h3><div>The current study demonstrates an additive value of early-phase β-amyloid-PET for the differential diagnosis of dementia syndromes. While visual assessment of early-phase β-amyloid-PET already provides substantial diagnostic accuracy, a data-driven analysis approach could aid in cases of uncertainty.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"49 ","pages":"Article 103963"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188175","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":"Functional network organization is locally atypical in children, adolescents, and young adults with congenital heart disease","authors":"Joy Roy ,&nbsp;William Reynolds ,&nbsp;Julia Wallace ,&nbsp;Daryaneh Badaly ,&nbsp;Rafael Ceschin","doi":"10.1016/j.nicl.2026.103965","DOIUrl":"10.1016/j.nicl.2026.103965","url":null,"abstract":"<div><div>Children, adolescents, and young adults with congenital heart disease (CHD) frequently experience disruptions in neurodevelopment affecting their executive functioning and other cognitive abilities, which in turn can impact academic performance, psychosocial adjustment, and overall quality of life. This exploratory study aims to investigate the impact of CHD on functional brain network connectivity and cognitive function, with a particular focus on executive functioning. Rather than relying on a single network construction method or arbitrary thresholds, our study methodically employed both weighted networks and binarized networks generated using absolute and proportional thresholding. This cross-method approach enables us to identify functional connectivity features that persist across heuristically and arbitrarily defined parameters, and to evaluate their association with neurocognition. Using resting-state fMRI data, we examined several network metrics across brain regions using three network construction types: weighted networks, absolute-threshold binarized networks, and proportional-threshold binarized networks. Regression models were then fit to neuropsychological test scores using metrics obtained from each network construction approach. Our results identified differences in network connectivity with a predilection for temporal, occipital, and subcortical regions, across both weighted and binarized networks. Furthermore, we identified distinct correlations between network metrics and cognitive performance, suggesting potential compensatory mechanisms within specific brain regions. These results provide an initial, methodologically transparent characterization of altered network organization in CHD and offer directions for future hypothesis-driven investigations.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"49 ","pages":"Article 103965"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146222015","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":"Longitudinal MRI-based changes in intracranial volume and skull thickness observed in both metachromatic leukodystrophy and multiple sclerosis","authors":"Guus H.J. Vorst ,&nbsp;Nicole I. Wolf ,&nbsp;David R. van Nederpelt ,&nbsp;Frederik Barkhof ,&nbsp;Marjo S. van der Knaap ,&nbsp;Menno M. Schoonheim ,&nbsp;Eva M.M. Strijbis ,&nbsp;Petra J.W. Pouwels","doi":"10.1016/j.nicl.2026.103968","DOIUrl":"10.1016/j.nicl.2026.103968","url":null,"abstract":"<div><div>Intracranial volume (ICV) is often used as normalization factor in volumetrics and considered to be stable in young adults. We noticed thick skulls on MRI scans of leukodystrophy patients, suggesting potentially changing skull morphology. In this study we aimed to quantify skull thickness and ICV in metachromatic leukodystrophy (MLD) patients and people with multiple sclerosis (pwMS). We retrospectively analyzed single-center cross-sectional and longitudinal MRI scans. Skull thickness and ICV were determined using automated segmentation techniques. Participants included MLD (n = 32, 11 male, scans = 136, median age first scan = 14.1 [IQR 7.9–25.7] years), MS (n = 232, 78 male, median age first scan = 47.3 [IQR 39.6–55.4] years, scans = 431), and controls (n = 139, 67 male, median age first scan = 30.7 [IQR 10.7–48.9] years, scans = 283). Both ICV and skull thickness showed natural growth in young controls. In young MLD participants, ICV decreased (−18.8 ± 22.4 mL/year, <em>p</em> &lt; 0.001). Above age 20, ICV and skull thickness remained stable in controls. In comparison to controls, we observed ICV loss in MLD participants (−4.01 ± 8.29 mL/year, <em>p</em> &lt; 0.001) and in pwMS (−2.99 ± 2.69 mL/year, <em>p</em> &lt; 0.001), as well as skull thickening (MLD: 0.16 ± 0.14 mm/year, <em>p</em> &lt; 0.001, pwMS: 0.04 ± 0.09 mm/year, <em>p</em> = 0.009). In adult patient groups, negative correlations were found between ICV and skull thickness (MLD: −19.24 mL/mm, <em>p</em> &lt; 0.001, pwMS: −11.56 mL/mm, <em>p</em> &lt; 0.001), but not in controls (<em>p =</em> 0.11). Despite limitations due to scanner variations, segmentation reliability and absence of validation against ground truth, these findings demonstrate a reduction in ICV in pathologies, already in young adulthood. Although the observed changes are small, they may lead to underestimations of atrophy when using ICV as a normalization factor.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"49 ","pages":"Article 103968"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146259955","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":"Advanced neuroimaging assessment of neurodegenerative dementia syndromes: A framework for comprehensive multimodal FDG-PET, MR-perfusion, and MR-diffusion analysis","authors":"Joachim Strobel ,&nbsp;Jan Kassubek ,&nbsp;Wolfgang Thaiss ,&nbsp;Sarah Straub-Anderl ,&nbsp;Zeljko Uzelac ,&nbsp;Sarah Jesse ,&nbsp;Laura Michelberger ,&nbsp;Christoph Solbach ,&nbsp;Ambros J. Beer ,&nbsp;Meinrad Beer ,&nbsp;Georg Grön ,&nbsp;Hans-Peter Müller ,&nbsp;Nico Sollmann","doi":"10.1016/j.nicl.2026.103964","DOIUrl":"10.1016/j.nicl.2026.103964","url":null,"abstract":"<div><h3>Background</h3><div>The reference for imaging in neurodegenerative dementia syndromes (NDS) is [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography (PET). Advanced multimodal magnetic resonance imaging (MRI) may complement PET-derived measures for differential diagnostics.</div></div><div><h3>Objectives</h3><div>The aim of the present study was to evaluate a new methodological approach integrating metabolic, perfusion, and microstructural parameters from simultaneous FDG-PET/MRI to reveal different imaging signatures for different NDS subtypes.</div></div><div><h3>Materials and Methods</h3><div>66 patients with NDS (Alzheimer’s disease: 28; behavioral frontotemporal dementia: 10; semantic variant primary progressive aphasia (PPA): 8; non-fluent variant PPA: 11; logopenic variant PPA: 9) and 10 subjects with subjective cognitive deficits (SCD) underwent combined FDG-PET/MRI with pseudo-continuous arterial spin labeling (pCASL) and diffusion tensor imaging (DTI). Standardized uptake values (SUV), cerebral blood flow (CBF), and fractional anisotropy (FA) were used to separate a respective NDS subgroup from all other NDS subgroups and from SCD based on a support vector machine (SVM) applied on region of interest (ROI)-based parameters.</div></div><div><h3>Results</h3><div>White matter alterations directly adjacent to the regions of alterations in SUV and CBF were identified. The SVM analysis on ROI-based parameters reached accuracies between 81% and 94% for separating an NDS subgroup from all other NDS subgroups and from SCD.</div></div><div><h3>Conclusions</h3><div>Multimodal neuroimaging by combination of FDG-PET and MRI shows potential to further advance the diagnostic spectrum in NDS. Since particularly early diagnosis of NDS remains key for effective treatment and management of patients with NDS, the present framework appears promising to be developed further until it aligns and integrates with clinical routine.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"49 ","pages":"Article 103964"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147272998","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":"Resting state functional connectivity patterns associate with alcohol use disorder characteristics: Insights from the triple network model","authors":"Daniel Guerrero ,&nbsp;Mario Dzemidzic ,&nbsp;Mahdi Moghaddam ,&nbsp;Mintao Liu ,&nbsp;Andrea Avena-Koenigsberger ,&nbsp;Jaroslaw Harezlak ,&nbsp;David A. Kareken ,&nbsp;Martin H. Plawecki ,&nbsp;Melissa A. Cyders ,&nbsp;Joaquín Goñi","doi":"10.1016/j.nicl.2025.103939","DOIUrl":"10.1016/j.nicl.2025.103939","url":null,"abstract":"<div><div>Prolonged alcohol use results in neuroadaptations that mark more severe and treatment-resistant alcohol use. The goal of this study was to identify functional connectivity brain patterns underlying Alcohol Use Disorder (AUD)-related characteristics in fifty-five adults (31 female) who endorsed heavy alcohol use. We hypothesized that resting-state functional connectivity (rsFC) of the Salience (SN), Frontoparietal (FPN), and Default Mode (DMN) networks would reflect self-reported recent and lifetime alcohol use, laboratory-based alcohol seeking, urgency, and sociodemographic characteristics related to AUD. To test our hypothesis, we combined the triple network model (TNM) of psychopathology with a multivariate data-driven approach, regularized partial least squares (rPLS), to unfold concurrent functional connectivity (FC) patterns and their association with AUD-related characteristics. We observed three concurrent associations of interest: i) drinking and age-related cross communication between the SN and both the FPN and DMN; ii) family history density of AUD and urgency anticorrelations between the SN and FPN; and iii) alcohol seeking and sex-associated SN and DMN interactions. These findings provide an integrative interpretation for many individual findings reported in the literature relating functional connectivity signatures and AUD factors. Moreover, we identified a set of neural mechanisms and brain regions concomitant with AUD-related characteristics that can serve as potential treatment targets across clinical and preclinical models.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"49 ","pages":"Article 103939"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145913918","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":"Fetal functional connectivity prospectively associates with autistic traits in toddlerhood","authors":"Bosi Chen ,&nbsp;Iris Menu ,&nbsp;Lanxin Ji ,&nbsp;Christopher J. Trentacosta ,&nbsp;Moriah E. Thomason","doi":"10.1016/j.nicl.2025.103938","DOIUrl":"10.1016/j.nicl.2025.103938","url":null,"abstract":"<div><div>Accumulating evidence from neuroimaging studies has implicated widespread disruptions in brain connectivity in autism spectrum disorder (ASD), with altered connectivity patterns reported as early as infancy. However, it remains unexplored whether functional connectivity differences are evident prior to birth in the brain of fetuses who will later exhibit autistic traits in early childhood. In this study, we leveraged a longitudinal sample of 62 children with both quality-assured fetal brain resting-state MRI data and a parent-report measure of autistic traits at age 3 years. Enrichment analysis was employed to identify network pairs significantly correlated with autistic traits. Specificity analysis was conducted by additionally controlling for other childhood psychopathology. Our results demonstrated significant correlations between autistic traits and functional connectivity in the cingulate-left temporal and right prefrontal-left operculum network pairs in both the primary and specificity analyses. Visual network connectivity with prefrontal and opercular regions was also implicated. These network pairs demonstrated positive associations with autistic traits, indicating that stronger connectivity between these network pairs was associated with higher autistic traits. In contrast, weaker cerebellum-right operculum connectivity was associated with higher autistic traits, uniquely in the specificity analysis. This study provides the first <em>in vivo</em> evidence prospectively linking variation in functional network connectivity in the fetal brain to autistic traits in toddlerhood. These findings extend the current understanding of the prenatal brain origins of ASD and highlight the potential of fetal rs-fMRI as a tool to identify neural signatures related to social-emotional development and ASD likelihood.</div></div>","PeriodicalId":54359,"journal":{"name":"Neuroimage-Clinical","volume":"49 ","pages":"Article 103938"},"PeriodicalIF":3.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145913913","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}