NeuroImage最新文献

{"title":"Defining individualized theta frequency for memory modulation: A machine learning approach across brain states and regions","authors":"Tuba Aktürk ,&nbsp;Emine Elif Tülay ,&nbsp;Bahar Güntekin ,&nbsp;Alexander T. Sack","doi":"10.1016/j.neuroimage.2025.121482","DOIUrl":"10.1016/j.neuroimage.2025.121482","url":null,"abstract":"<div><div>Recent transcranial alternating current stimulation (tACS) studies suggest that theta-frequency stimulation can modulate memory performance, with evidence highlighting individual variability in optimal stimulation frequency. However, it remains unclear which brain state (\"when\") and cortical region (\"where\") are most predictive of memory-related theta frequencies. This study aimed to identify the most relevant individualized theta frequency (ITF) parameters for episodic memory modulation using a machine learning approach.</div><div>EEG data were collected from 46 healthy young-adults during rest and while performing visual (VM) and auditory (AM) memory tasks, followed by free-recall assessments. ITFs were extracted as peak theta frequencies from power spectra across 18 electrode sites and a global average (“where”), across three states: resting, task-encoding, and task-delay (\"when\"). Participants were clustered into high- and low-performing groups based on ITFs using K-means clustering, and candidate ITFs were further examined via correlation and Bayesian regression analyses to assess their predictive power.</div><div>All ITF candidates showed some clustering success, but global task-state ITFs best distinguished between performance groups, independent of task modality. Notably, resting-state left posterior parietal (LPP) ITF was negatively correlated with both VM and AM performance, suggesting a domain-general role in baseline memory capacity. Additionally, task-specific contributions were observed: encoding-related left temporoparietal and delay-related left central ITFs were significantly associated with AM performance, potentially reflecting auditory-specific processes.</div><div>These findings highlight the importance of “when” and “where” specificity in defining individualized stimulation protocols. Resting-state LPP ITF, in particular, may serve as a promising biomarker for tailoring tACS at sub-ITF frequencies to enhance memory performance.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121482"},"PeriodicalIF":4.5,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145150047","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":"Individual differences in policy precision: Links to suicidal risk and network dynamics","authors":"Dayoung Yoon ,&nbsp;Jaejoong Kim ,&nbsp;Do Hyun Kim ,&nbsp;Dong Woo Shin ,&nbsp;Su Hyun Bong ,&nbsp;Jaewon Kim ,&nbsp;Hae-Jeong Park ,&nbsp;Hong Jin Jeon ,&nbsp;Bumseok Jeong","doi":"10.1016/j.neuroimage.2025.121479","DOIUrl":"10.1016/j.neuroimage.2025.121479","url":null,"abstract":"<div><div>The Behavioural modelling of decision-making processes has advanced our understanding of impairments associated with various psychiatric conditions. While many studies have focused on models that best fit behavioural data, the extent to which such models reflect biologically plausible mechanisms remains underexplored. To bridge this gap, we developed a probabilistic two-armed bandit task model grounded in the active inference framework and evaluated its performance against established reinforcement learning (RL) models. Our model not only matched but outperformed conventional RL models in explaining individual variability in choice behaviour. A central feature of our model is the optimisation of policy precision based on previous outcomes. This process captures the dynamic balance between model-based predictions derived from the internal generative model and the influence of immediate past observations. Importantly, incorporating the temporal dynamics of policy precision significantly improved the model's capacity to explain large-scale brain network activity and inter-subject variability. We found that increases in policy precision were positively associated with default mode network dominance and negatively associated with states dominated by dorsal attention and frontoparietal networks. These opposing associations suggest functional coordination between these systems, as supported by the correlations between brain state transitions and behavioural parameters. Furthermore, prolonged dominance of another brain state, characterised by elevated ventral attention network activity and stronger inter-network connectivity, appeared to disrupt this coordination. Finally, we found that heightened sensitivity to negative outcomes in a loss-related context was associated with high suicidal risk among individuals with major depressive disorder.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121479"},"PeriodicalIF":4.5,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119561","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":"Linking dynamic connectivity states to cognitive decline and anatomical changes in Alzheimer’s disease","authors":"Jacopo Tessadori ,&nbsp;Ilaria Boscolo Galazzo ,&nbsp;Silvia F. Storti ,&nbsp;Lorenzo Pini ,&nbsp;Lorenza Brusini ,&nbsp;Federica Cruciani ,&nbsp;Diego Sona ,&nbsp;Gloria Menegaz ,&nbsp;Vittorio Murino","doi":"10.1016/j.neuroimage.2025.121448","DOIUrl":"10.1016/j.neuroimage.2025.121448","url":null,"abstract":"<div><div>Alterations in brain connectivity provide early indications of neurodegenerative diseases like Alzheimer’s disease (AD). Here, we present a novel framework that integrates a Hidden Markov Model (HMM) within the architecture of a convolutional neural network (CNN) to analyze dynamic functional connectivity (dFC) in resting-state functional magnetic resonance imaging (rs-fMRI). Our unsupervised approach captures recurring connectivity states in a large cohort of subjects spanning the Alzheimer’s disease continuum, including healthy controls, individuals with mild cognitive impairment (MCI), and patients with clinically diagnosed AD.</div><div>We propose a deep neural model with embedded HMM dynamics to identify stable recurring brain states from resting-state fMRI. These states exhibit distinct connectivity patterns and are differentially expressed across the Alzheimer’s disease continuum. Our analysis shows that the fraction of time each state is active varies systematically with disease severity, highlighting dynamic network alterations that track neurodegeneration.</div><div>Our findings suggest that the disruption of dynamic connectivity patterns in AD may follow a two-stage trajectory, where early shifts toward integrative network states give way to reduced connectivity organization as the disease progresses. This framework offers a promising tool for early diagnosis and monitoring of AD, and may have broader applications in the study of other neurodegenerative conditions.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121448"},"PeriodicalIF":4.5,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145138013","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":"White matter tracts underlying rhythm perception in adolescence","authors":"Peiyang Guo ,&nbsp;Zonglei Zhen ,&nbsp;Shiting Yang ,&nbsp;Huijuan Chen ,&nbsp;Yi-Chen Zhang ,&nbsp;Qi Dong ,&nbsp;Kunru Song ,&nbsp;Jin-tao Zhang ,&nbsp;Yun Nan","doi":"10.1016/j.neuroimage.2025.121478","DOIUrl":"10.1016/j.neuroimage.2025.121478","url":null,"abstract":"<div><div>Adolescence is a critical developmental stage marked by significant neuropsychological changes coinciding with the maturation of white matter microstructure. Recent studies suggest that musical rhythm processing may serve both as a sensitive marker and a cognitive foundation for intervention strategies in adolescent neuropsychological development. However, our understanding of the white matter networks supporting rhythm processing in this age group remains limited. In this study, we investigated the extent to which the microstructure of white matter fiber tracts correlated with beat-based (detection of regular pulses) and sequence-based (discrimination of rhythmic patterns) rhythm perception in 65 typically developing adolescents. Our findings indicate that shared white matter networks, including the fornix, cerebellar tracts, and the body and tapetum of the corpus callosum, are critical for both beat-based and sequence-based rhythm perception. These pathways are involved in temporal sequence processing, duration-based timing, and interhemispheric communication. Additionally, specific sensorimotor pathways, including the bilateral superior longitudinal fasciculi I (SLF_I) and the middle cerebellar peduncle, were linked to beat-based perception, supporting the integration of auditory inputs with motor planning and execution. In contrast, the bilateral cingulum bundles, which are involved in memory processes, were specifically associated with sequence-based rhythm perception. Notably, the relationship between beat-based rhythm perception and both the left SLF_I and fornix became non-significant after adjusting for rapid automatized naming skill, suggesting shared neural resources between these processes. These findings suggest that the white matter pathways associated with rhythm perception in adolescents integrate sensorimotor and memory systems, with potential applications for rhythm-based interventions in developmental disorders.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121478"},"PeriodicalIF":4.5,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119558","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":"Tuning into the brain: Readiness potentials as instigators of intention reports","authors":"Ceci Verbaarschot ,&nbsp;Jason Farquhar ,&nbsp;Pim Haselager","doi":"10.1016/j.neuroimage.2025.121481","DOIUrl":"10.1016/j.neuroimage.2025.121481","url":null,"abstract":"<div><div>Multiple neuroscientific studies have claimed that neural signals such as the readiness potential (RP) are predictive of action performance well before a person reports to experience an intention to act. Much literature has focused on assessing the consequences of this priority for agency, responsibility and free will. Rather than being the cause of an intention experience or action, we believe that the RP may function as an ingredient and, in some experimental contexts, even as a trigger of intention reports. In this paper, we argue for this by focusing on the informational role of the brain in the generation of intention reports. To do so, we conduct a multi-study analysis of five of our previously published experiments on the neural preparation and subjective experience of intended movement across various experimental contexts. Based on these novel results, we argue that signals like the RP are among the latest stages of brain processing before movement onset, making them a useful source of information to (co-) inform and/or initiate an intention report.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121481"},"PeriodicalIF":4.5,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119569","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":"High-definition MEG source estimation using the reciprocal boundary element fast multipole method","authors":"Guillermo Núñez Ponasso ,&nbsp;Derek A. Drumm ,&nbsp;Abbie Wang ,&nbsp;Gregory M. Noetscher ,&nbsp;Matti Hämäläinen ,&nbsp;Thomas R. Knösche ,&nbsp;Burkhard Maess ,&nbsp;Jens Haueisen ,&nbsp;Sergey N. Makaroff ,&nbsp;Tommi Raij","doi":"10.1016/j.neuroimage.2025.121452","DOIUrl":"10.1016/j.neuroimage.2025.121452","url":null,"abstract":"<div><div><em>Magnetoencephalographic</em> (MEG) source estimation relies on the computation of the gain (lead-field) matrix, which embodies the linear relationship between the amplitudes of the sources and the recorded signals. However, with a realistic forward model, the calculation of the gain matrix in a “direct” fashion is a computationally expensive task, forcing the number of dipolar sources in standard MEG pipelines to be typically limited to 10,000. We propose a fast computational approach to calculate the gain matrix, which is based on the reciprocal relationship between MEG and transcranial magnetic stimulation (TMS), and which we couple with the charge-based boundary element fast multipole method (BEM-FMM). Our method allows us to efficiently generate gain matrices for high-resolution multi-layer non-nested meshes involving source spaces of up to 1 million dipoles. We employed the gain matrices generated with our approach to perform minimum norm estimate (MNE) source localization against simulated data (at varying noise levels) and experimental MEG data of evoked somatosensory fields elicited by right-hand median nerve stimulation on 5 healthy participants. Additionally, we compare our experimental source estimates against the standard 1- and 3-layer BEM models of the MNE-Python source estimation pipeline, and against a 3-layer isotropic FEM model.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121452"},"PeriodicalIF":4.5,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145119559","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":"Reduced integrity of white matter fiber tracts connecting frontal and posterior sites are associated with a higher propensity to experience meaningful coincidences","authors":"Christian Rominger ,&nbsp;Karl Koschutnig ,&nbsp;Andreas Fink ,&nbsp;Corinna M. Perchtold-Stefan","doi":"10.1016/j.neuroimage.2025.121480","DOIUrl":"10.1016/j.neuroimage.2025.121480","url":null,"abstract":"<div><div>The propensity to experience meaningful patterns in random arrangements and unrelated events is a personality trait with relationships to perceptual alterations and decreased working memory capacity. This study investigated the relationship between the propensity to experience meaningful coincidences and white matter fiber tracts (voxel-based), especially those connecting frontal and (temporal) posterior cortical areas. We studied this in a comparatively large sample of <em>n</em> = 101 participants and found a reduced integrity of white matter (i.e., lower quantitative anisotropy [QA]) in people experiencing more meaningful coincidences (FDR corrected <em>p</em> &lt; 0.001). The associative fiber tracts connecting the frontal and posterior areas (that is, inferior fronto-occipital fasciculus), as well as the commissural fiber tracts connecting the regions of the left and right brain, showed the strongest negative associations. These structural characteristics of the coincidence perceiver’s brain are in line with the hypothesis that reduced inhibitory control (over sensory processes) and working memory deficits are the main reason why some people perceive more meaningful coincidences than others.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121480"},"PeriodicalIF":4.5,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145125198","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":"Measuring the potential risk of re-identification of imaging research participants from open-source automated face recognition software","authors":"Carl M. Prakaashana ,&nbsp;Marios Savvides ,&nbsp;Jeffrey L. Gunter ,&nbsp;Matthew L. Senjem ,&nbsp;Prashanthi Vemuri ,&nbsp;Kejal Kantarci ,&nbsp;Johnanthan Graff-Radford ,&nbsp;Ronald C. Petersen ,&nbsp;Clifford R. Jack Jr ,&nbsp;Christopher G. Schwarz","doi":"10.1016/j.neuroimage.2025.121476","DOIUrl":"10.1016/j.neuroimage.2025.121476","url":null,"abstract":"<div><div>In recent years facial recognition software has gone from an area of research to widespread adoption and broad public availability. Open-source face recognition packages are freely available on the internet for anyone to download, and several public websites allow users to run facial recognition on photos without needing any technical knowledge or equipment beyond internet access, making facial recognition accessible for anyone to use for any purpose. Previous research has demonstrated the ability of commercial software to identify a person based on facial content in brain imaging. In this study we tested two commercial facial recognition programs and a variety of popular open-source computer vision and facial recognition software packages to measure how accurately they could be used for reidentification of research participants in brain imaging studies. We tested a “population to sample” threat model, measuring the rates of success for which face recognition software selected the correct MRI-based face reconstruction from a set of 182 participants as its top-scoring match for input facial photographs. We found that the freely available open-source software packages we tested can reidentify a research participant with up to 59 % accuracy. This was less than the commercial packages, which were able to achieve much higher accuracies in the ranges of 92 % and 98 % in identical testing scenarios, but it demonstrates the feasibility of re-identifying faces in research MRI even by individuals with access to only freely available software. As the trust and confidence of potential participants is essential to brain imaging research, especially with widespread and mandated data-sharing of brain scans, this further supports the need to replace identifiable face imagery in brain images to protect the privacy of research participants.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121476"},"PeriodicalIF":4.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145113978","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":"Synthetizing SWI from 3T to 7T by generative diffusion network for deep medullary veins visualization","authors":"Sui Li ,&nbsp;Xingguang Deng ,&nbsp;Qiwei Li ,&nbsp;Zhiming Zhen ,&nbsp;Luyi Han ,&nbsp;Kang Chen ,&nbsp;Chaoyang Zhou ,&nbsp;Fengxi Chen ,&nbsp;Peiyu Huang ,&nbsp;Ruiting Zhang ,&nbsp;Hao Chen ,&nbsp;Tianyu Zhang ,&nbsp;Wei Chen ,&nbsp;Tao Tan ,&nbsp;Chen Liu","doi":"10.1016/j.neuroimage.2025.121475","DOIUrl":"10.1016/j.neuroimage.2025.121475","url":null,"abstract":"<div><div>Ultrahigh-field susceptibility-weighted imaging (SWI) provides excellent tissue contrast and anatomical details of brain. However, ultrahigh-field magnetic resonance (MR) scanner often expensive and provides uncomfortable noise experience for patient. Therefore, some deep learning approaches have been proposed to synthesis high-field MR images from low-filed MR images, most existing methods rely on generative adversarial network (GAN) and achieve acceptable results. While the dilemma in train process of GAN, generally recognized, limits the synthesis performance in SWI images for its microvascular structure. Diffusion models, as a promising alternative, indirectly characterize the gaussian noise to the target image with a slow sampling through a considerable number of steps. To address this limitation, we presented a generative diffusion-based deep learning imaging model, named conditional denoising diffusion probabilistic model (CDDPM), for synthesizing high-field (7 Tesla) SWI images form low-field (3 Tesla) SWI images and assess clinical applicability. Crucially, the experiment results demonstrate that the diffusion-based model that synthesizes 7T SWI from 3T SWI images is potentially to providing an alternative way to achieve the advantages of ultra-high field 7T MR images for deep medullary veins visualization.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121475"},"PeriodicalIF":4.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145113983","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":"Cortical aperiodic dynamics in hearing impairments predicts neural tracking of speech","authors":"Hangze Mao ,&nbsp;Yuhan Lu ,&nbsp;Zhuang Jiang ,&nbsp;Difei Hu ,&nbsp;Shuihong Zhou ,&nbsp;Xing Tian ,&nbsp;Yan Han ,&nbsp;Yongtao Xiao ,&nbsp;Zhili Zhang","doi":"10.1016/j.neuroimage.2025.121477","DOIUrl":"10.1016/j.neuroimage.2025.121477","url":null,"abstract":"<div><div>Excitation–inhibition balance is a fundamental property of cortical circuits, reflecting homeostatic plasticity that stabilizes neural activity in the face of functional disruption. This framework has been widely implicated in sensory deprivation and psychiatric disorders. In the auditory domain, it remains unclear how long-term bilateral and unilateral hearing loss reorganizes cortical E-I balance and how such reorganization affects speech processing. Here, we recorded resting-state EEG and measured spectral exponents as a noninvasive proxy for cortical E-I balance in individuals with bilateral hearing loss, single-sided deafness, and normal hearing. We found that spectral exponents differed systematically across hearing loss types. Participants with bilateral hearing loss exhibited reduced exponents, primarily in central-parietal regions, relative to normal-hearing controls, with a gradual increase with prolonged hearing-loss duration. In contrast, left- and right-sided deafness showed distinct patterns of hemispheric lateralization in spectral exponents. Participants also performed a naturalistic speech listening task, allowing quantification of neural tracking of speech. It showed stronger envelope tracking response for bilateral hearing loss group than normal control. Importantly, resting-state exponents across all hearing-impaired groups robustly predicted the strength of speech envelope tracking in noisy environments. These findings reveal dissociable patterns of aperiodic cortical dynamics following bilateral and unilateral auditory deprivation and highlight the homeostatic plasticity in supporting speech perception under challenging listening conditions.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"320 ","pages":"Article 121477"},"PeriodicalIF":4.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145107826","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}