Imaging neuroscience (Cambridge, Mass.)最新文献

{"title":"Fine-scale individualized gyral folding-based cortical similarity networks reveal distinct organizational patterns in Alzheimer's disease and Lewy body dementia.","authors":"Minheng Chen, Chao Cao, Tong Chen, Dunia Alhamad, Tianming Liu, Li Su, Dajiang Zhu","doi":"10.1162/IMAG.a.1322","DOIUrl":"10.1162/IMAG.a.1322","url":null,"abstract":"<p><p>Alzheimer's disease (AD) and Lewy body dementia (LBD) are common neurodegenerative dementias with overlapping clinical presentations, making differential diagnosis challenging. While structural magnetic resonance imaging (MRI) has revealed characteristic regional atrophy patterns, regional morphometric measures alone may not fully capture distributed cortical alterations. Morphometric similarity networks (MSNs) offer a systems-level framework to characterize coordinated structural organization, but existing approaches typically rely on atlas-based parcellations that may obscure individual-specific cortical folding geometry. Here, we propose a fine-scale, folding-informed cortical similarity network framework based on automatically detected three-hinge gyral (3HG) landmarks. Using a thickness-constrained arealization strategy in native surface space, we define individualized cortical regions and construct subject-specific MSNs without cross-subject registration. We then investigate how network topology relates to landmark-defined node count and how these properties differ between AD and LBD. We find that several graph theoretical metrics, particularly global efficiency and characteristic path length, exhibit clear associations with the number of detected landmarks, indicating that topology in individualized networks is partly shaped by node availability. When accounting for landmark count, several apparent group differences in global topology are attenuated, whereas multiple heterogeneity-related metrics remain significant, indicating that node-count scaling substantially influences the interpretation of individualized network topology. Nevertheless, multivariate topological patterns remain informative for AD/LBD classification after residualizing for node count, and landmark count itself provides modest diagnostic information. These findings highlight node-count scaling as a key methodological consideration in individualized structural networks and suggest that folding-based MSNs capture disease-related variation in cortical network organization between AD and LBD.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13449931/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148698504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spontaneous activation of cortical somatosensory networks depresses their excitability in preterm human neonates.","authors":"Kimberley Whitehead, Maria Pureza Laudiano-Dray, Judith Meek, Sofia Olhede, Lorenzo Fabrizi","doi":"10.1162/IMAG.a.1324","DOIUrl":"10.1162/IMAG.a.1324","url":null,"abstract":"<p><p>The cortical activity of preterm human infants is highly discontinuous, comprising transient high-amplitude bursts separated by periods of relative quiescence. While the functional significance of these bursts is well established, the underlying mechanism remains unclear. This burst-quiescence pattern could arise from a transient refractoriness within excitatory recurrent cortical networks following spontaneous activation. To assess this possibility, we tested whether such activation is followed by a transient reduction in excitability by evaluating whether externally evoked tactile responses are attenuated when somatosensory circuits have recently been active. We recorded electroencephalographic (EEG) responses to tactile stimulation of hands and feet in 35 preterm infants (40% female), with a median postmenstrual age of 32 weeks. This stimulation elicited wideband increases in EEG power, showing two distinct peaks: one in the delta range (1 Hz) and another in the alpha-beta range (~13 Hz). Low-frequency activity showed a single, broadly distributed peak across the scalp, whereas faster high beta-gamma responses were more confined to somatotopically specific regions, suggesting engagement of both widespread (tangential) and localized (columnar) cortical circuits. Importantly, the magnitude of the evoked response was significantly reduced when the activity immediately preceding stimulation resembled the spectro-spatial pattern of the somatosensory evoked response, indicating prior spontaneous activation of the somatosensory network. Stimulus-evoked EEG power changes decreased by 3.2 and 2.5 dB following hand and foot stimulation, respectively, for every 1.0-degree increase in the similarity between pre-stimulus activity and the spectro-spatial pattern of the somatosensory evoked response (scale 0-5). This effect was the strongest and most temporally sustained at slower frequencies. These results suggest that when somatosensory networks are spontaneously active, they become temporarily less responsive to stimulation-a form of refractoriness-preventing immediate reactivation. The extent of this refractory-like modulation is not uniform but depends on the spatial scale of the underlying networks, as indexed by their dominant frequency of activation. This mechanism may explain the cyclical pattern of bursting and quiescence neural activity observed in the preterm brain.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13449929/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148698515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atypical low-frequency and high-frequency neural entrainment to rhythmic audiovisual speech in adults with dyslexia.","authors":"Mahmoud Keshavarzi, Brian C J Moore, Usha Goswami","doi":"10.1162/IMAG.a.1329","DOIUrl":"10.1162/IMAG.a.1329","url":null,"abstract":"<p><p>Developmental dyslexia has been linked to atypical neural processing of the temporal dynamics of speech, but there has been disagreement concerning whether faster or slower dynamics are impaired. According to the temporal sampling (TS) theory, dyslexia arises from impaired entrainment of low-frequency neural oscillations-particularly in the delta (1-4 Hz) and theta (4-8 Hz) bands-to the rhythmic modulations of speech. This hypothesis was tested for adults with and without dyslexia using electroencephalography (EEG) and employing a rhythmic audiovisual speech paradigm previously used with dyslexic children. Participants viewed a \"talking head\" repeating the syllable \"ba\" at a 2-Hz rate. Measures were neural phase entrainment and band power in the delta, theta, beta (15-25 Hz), and low gamma (25-40 Hz) bands. Phase-amplitude coupling (PAC) and phase-phase coupling (PPC) were also assessed for delta-theta, delta-beta, theta-beta, delta-gamma, and theta-gamma interactions. Both groups exhibited significant delta- and theta-band phase entrainment; however, the two groups differed significantly in the preferred phase for the theta band. While the control group showed consistent beta- and low gamma-band phase entrainment, this was not observed for the dyslexic group. There was significantly greater delta-band power for the dyslexic group across the whole brain and in the right temporal region. These findings indicate that temporal sampling deficits appear to persist into adulthood and show a multi-timescale pattern, with altered low-frequency processing and atypical higher-frequency entrainment. The data also generate developmental hypotheses about possible compensation or reorganisation mechanisms that could be examined in future longitudinal research.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13449930/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148698456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding everyday levels of musical training from subcortical white-matter architecture.","authors":"Massimo Lumaca, Marcus T Pearce, Peter E Keller, Peter Vuust, Elvira Brattico, Giosuè Baggio, Katarzyna Hat, Ole A Heggli, Kristian Sandberg","doi":"10.1162/IMAG.a.1325","DOIUrl":"10.1162/IMAG.a.1325","url":null,"abstract":"<p><p>Most people engage with music informally or through the standard school curriculum rather than through extensive professional practice, resulting in graded levels of accumulated musical training. In this study, we used cross-validated machine learning on whole-brain structural connectomes to investigate whether individual differences in brain wiring predict variation in musical training across 225 adults with none-to-moderate training levels. Connectomes were weighted by fiber bundle capacity (FBC), a quantitative diffusion MRI metric of structural connectivity. Musical training was quantified using the Gold-MSI Musical Training subscale (F3), a self-reported measure encompassing both formal and informal musical practice. Subcortical white-matter pathways linking thalamus, putamen, and pallidum with sensorimotor cortex carried the strongest predictive signal (r = 0.261; R² = 0.068; p_perm = 0.003). Furthermore, this connectivity predicted the association between musical training and auditory perception skill, which was present in individuals with stronger subcortical-sensorimotor connectivity (+1 SD: β = 0.192, p = 0.004), but absent in those with weaker connectivity (-1 SD: β = -0.066, p = 0.488). Subcortical-sensorimotor connectivity is, therefore, the strongest structural correlate of graded musical training in non-specialists within the general population, identifying the structural neural substrate on which the training-skill association depends. This work warrants renewed targeted focus on subcortical circuits in models of musical expertise.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13440155/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148681228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Slow running benefits: Boosts in mood and facilitation of prefrontal cortex function even at very light intensity.","authors":"Chorphaka Damrongthai, Ryuta Kuwamizu, Yudai Yamazaki, Naoki Aoike, Dongmin Lee, Kyeongho Byun, Ferenc Torma, Kazuki Hyodo, Worachat Churdchomjan, Michael A Yassa, Kazutaka Adachi, Hideaki Soya","doi":"10.1162/IMAG.a.1297","DOIUrl":"10.1162/IMAG.a.1297","url":null,"abstract":"<p><p>Although running upright has been reported to have positive effects on both physical and mental health, the minimum running intensity/speed that would benefit mood and prefrontal cognition is not yet clear. Here, we tested the hypothesis that a brief bout of very slow running, which is classified as a very light intensity exercise, would enhance positive mood and executive function and increase activation in executive-function-related prefrontal subregions. Twenty-four healthy participants completed a 10-minute very slow running session on a treadmill at 35% <i>V̇</i>o_2peak and a resting control session in randomized order. Executive function was measured using the Stroop task and mood state was measured using the Two-Dimensional Mood Scale (TDMS) before and after both sessions. Cortical hemodynamic changes while performing the task were monitored using functional near-infrared spectroscopy (fNIRS). The results show that 10 minutes of very slow running significantly enhanced mood, reduced Stroop interference time (i.e., enhanced executive function), and elicited left lateral PFC activation. Moreover, head acceleration, the magnitude of up-and-down oscillations, was measured during running, and a significant positive correlation with pleasant mood was found. Head acceleration is a remarkable characteristic of running and may be one of the factors related to a pleasant mood induced by very slow running. In conclusion, the current study reveals that a single bout of running, even at very slow speed, elicits a pleasant mood and improved executive function with enhancing activation in prefrontal subregions. This sheds light on the slow running benefits to brain health.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13439976/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148681251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RAVEN: Robust, generalizable, multi-resolution structural MRI upsampling using autoencoders.","authors":"Walter Adame-Gonzalez, Roqaie Moqadam, Yashar Zeighami, Mahsa Dadar","doi":"10.1162/IMAG.a.1326","DOIUrl":"10.1162/IMAG.a.1326","url":null,"abstract":"<p><p>Due to their high inter-tissue contrast, Magnetic resonance images (MRIs) can reflect neuroanatomical changes related to healthy aging and pathological processes. However, standard brain MRI acquisition resolutions hinder the ability to measure the more subtle changes that occur in early disease stages. Increasing the resolution during acquisition poses multiple challenges, including increased noise, higher acquisition times and cost, and discomfort of the scanned individual. In this work, we propose a robust, generalizable single-image super-resolution network for brain MRIs named Resolution Augmentation with Variational auto-Encoder Networks (RAVEN) with generative adversarial networks (GANs). We show RAVEN is capable of upsampling in-vivo and ex-vivo MRIs of diverse modalities (e.g. T1-weighted, T2-weighted, and T2*) and varying field strengths (3T to 7T) to target voxel sizes as small as 0.5 mm isotropic using arbitrary upsampling factors. RAVEN achieved state-of-the-art performance against deep learning and non-deep learning methods, best preserving true anatomical information. We have also made RAVEN open access, with the source code as well as training and evaluation scripts available and ready to use at: https://github.com/waadgo/raven.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13440154/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148681257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformed idiographic symptom networks to identify neurobiological predictors of affective-state transitions in bipolar disorder.","authors":"Siraj J Lyons, John Foley, Olivia Cook, Brendan E Depue","doi":"10.1162/IMAG.a.1327","DOIUrl":"10.1162/IMAG.a.1327","url":null,"abstract":"<p><p>Bipolar disorder remains an understudied psychiatric condition. Research has been focused on neurobiological mechanisms with the hope of identifying unique markers distinguishing bipolar disorder from similar conditions (i.e., major depressive disorder and schizophrenia), in addition to neurocognitive mechanisms driving affective state transitions. While these investigations continue to gain popularity, the current literature does not present a strong account for a neurobiological cause of affective state transitions and document significant heterogeneity between individuals. We argue that current difficulties with identifying neurobiological associations of affective state transitions can be targeted by incorporating idiographic symptom network analyses, a statistical and methodological tool more commonly used within the behavioral psychopathology literature, into the neurobiological study of bipolar disorder. Idiographic symptom networks allow the modeling of temporal relationships between symptoms and behavior at a finer temporal resolution compared to standard longitudinal analyses. As such, collecting many within-subject neurological measures samples alongside ecological momentary assessments indexing transient mood and cognitive functioning can provide an opportunity to identify potential neurobiological drivers of bipolar disorder symptoms and affective state transitions. The perspective explores current methodological designs, their associated strengths and limitations, in addition to the clinical utility with adopting idiographic network analyses within clinical neuroscience research.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13435685/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148674463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Navigator readouts with optimized processing improve spinal cord and gray matter segmentability in multi-echo gradient-echo imaging.","authors":"Silvan Büeler, Laura Beghini, Christian W Kündig, Martina D Liechti, S Johanna Vannesjo, Gergely David","doi":"10.1162/IMAG.a.1320","DOIUrl":"10.1162/IMAG.a.1320","url":null,"abstract":"<p><p>Multi-echo gradient-echo (ME-GRE) acquisitions of the spinal cord (SC) are highly susceptible to breathing-induced magnetic field fluctuations arising from the proximity of the lungs, often resulting in ghosting artifacts and signal loss. A navigator readout can be employed to monitor and correct for these field variations; however, conventional navigator processing methods frequently fail in the SC due to its small size and distinct anatomy. Here, we evaluate the impact of a recently introduced, SC-specific navigator processing approach on SC and gray matter (GM) segmentability. ME-GRE images were acquired at 3T during free breathing in ten healthy volunteers, covering the cervical, thoracic, and lumbosacral spinal cord. Data were collected both with and without a centerline navigator readout. Acquisitions without navigators included five imaging echoes, whereas those with navigators comprised four imaging echoes followed by an additional readout of the k-space centerline (the \"navigator echo\"). The navigator readout was processed using a recently introduced method optimized for the SC. The effect of the optimized navigator correction was evaluated by contrast-to-noise ratio (CNR), qualitative ratings of SC and GM segmentability, and the performance of automatic segmentation algorithms. Compared with acquisitions without navigators, optimized navigator correction significantly improved quantitative image quality metrics, particularly GM-white matter CNR at the C7-T1 and T7-T8 vertebral levels and across the lumbosacral cord. Regarding SC and GM segmentability, raters preferred images with navigators over uncorrected images at nearly all spinal cord levels, with the strongest effect observed for GM segmentability in the lumbosacral cord. Although overall automatic segmentation performance was comparable between acquisition types, automatic GM segmentation failed at the lumbosacral cord in the presence of severe artifacts in acquisitions without navigators, while remaining robust in the corresponding navigator-corrected images. In conclusion, navigator processing optimized for SC imaging improves image quality and segmentability in ME-GRE acquisitions, making this technique attractive for both clinical and research applications.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13435687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148674484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pooling quantitative MRI data: A multi-protocol study of healthy subcortical aging.","authors":"Mikhail Zubkov, Kerrin J Pine, Pierre-Louis Bazin, Niklas Kuegler, Puneet Talwar, Nasrin Mortazavi, Solène Dauby, Chloé Geron, Elise Beckers, Laurent Lamalle, Christophe Phillips, Fabienne Collette, Pierre Maquet, Emilie Lommers, Anneke Alkemade, Nikolaus Weiskopf, Gilles Vandewalle, Evgeniya Kirilina","doi":"10.1162/IMAG.a.1315","DOIUrl":"10.1162/IMAG.a.1315","url":null,"abstract":"<p><p>Quantitative MRI (qMRI) measures relaxation rates, exchange rates, and proton densities that reflect biophysical properties of tissue and are ideally free from protocol- and scanner-dependence. In practice, qMRI has not yet achieved this level of independence from sequence and hardware choice, and quantitative estimates often differ across sites and acquisition schemes. At the same time, pooling data across different sources can be beneficial to statistical power of longitudinal, cross-sectional, or case-control studies. Here, we investigate how protocol and hardware differences can affect pooling data from different sources in large ultra high field (UHF) qMRI studies in the context of healthy aging. We combine the openly available aging UHF qMRI MP2RAGEME-based dataset with two different multiparameter mapping (MPM)-based sets of qMRI data. We evaluate how pooling affects age dependence of qMRI parameters and investigate protocol-related biases, with a particular focus on subcortical structures. We focus the analysis, first, on replication and expansion of the previously published qMRI dataset on normative aging, second, the examination of the protocol influence on the estimated qMRI values, and third, on detecting the protocol effect on the age dependence inferred from the data. We find that the age-related changes in the pooled dataset for R1 measure around 4-17% of the lifespan mean in different structures. Similarly, age-related R2* variation in different structures constitutes around 6-30% of the lifespan mean in the pooled dataset. Subcortical structure volume change is on the order of 5-26%. We further observe larger relative difference between protocols for R1 and volume, while R2* remains more consistent for most regions. We show how pooling the UHF qMRI data from different sites and collected with different quantitative protocols can be both detrimental and beneficial for the analysis outcomes.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13439991/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148681239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phase similarity between similar objects indicates representational merging across retrieval training but not sleep.","authors":"Hayley Bree Caldwell, Alex Chatburn, Kurt Lushington, Simon Hanslmayr, Sebastian Michelmann","doi":"10.1162/IMAG.a.1321","DOIUrl":"10.1162/IMAG.a.1321","url":null,"abstract":"<p><p>Retrieval training (i.e., cued recall) is theorised to induce rapid memory consolidation, similarly to sleep. Across consolidation, related neural representations become increasingly similar; yet, representational change has never been directly compared between sleep and retrieval training to test similarities in their underlying mechanisms. In this study, 30 subjects (27F, 18-34, <i>M</i> = 22.17) completed 4 separate sessions in which they (1) learnt object-word pairs, followed by (2) immediate recognition testing, (3) one of four 120-min interventions (retrieval training, restudy, sleep, or wake), and (4) delayed recognition testing. We compared EEG phase similarity between similar and different objects to assess the time, frequency, and anatomical distribution of representational similarity across encoding (learning to immediate recognition), and each intervention (immediate to delayed recognition). We hypothesised that EEG phase patterns for similar objects would become more similar (i.e., representational merging) across retrieval training and sleep interventions, and predict a greater endorsement of similar-object lures. We found increased representational similarity between similar objects across encoding in the theta-band and occipital sources. Crucially, additional representational merging was only observed across the retrieval training intervention, in the alpha-band and parieto-occipital sources. Despite retrieval training leading to reduced performance in discriminating similar-objects lures, greater representational merging across retrieval training predicted greater discrimination of similar-object lures. Together, these findings suggest that sleep and retrieval training induce different memory transformations across equivalent timescales. Retrieval training may generally provoke rapid gist extraction, with greater neocortical integration supporting episodic discrimination. Conversely, sleep may selectively maintain short-term task-relevant episodic and semantic details.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13430988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148671498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}