Imaging neuroscience (Cambridge, Mass.)最新文献

{"title":"Differential burst dynamics of slow and fast gamma rhythms in macaque primary visual cortex.","authors":"Vignesh Raju, Supratim Ray","doi":"10.1162/IMAG.a.1404","DOIUrl":"https://doi.org/10.1162/IMAG.a.1404","url":null,"abstract":"<p><p>Gamma oscillations have been ubiquitously observed across a wide spectrum of brain areas in multiple species. They tend to occur intermittently in the form of bursts, rather than being produced as sustained and continuous rhythmic activity. Recent studies have shown that large visual sinusoidal gratings elicit two distinct gamma rhythms, namely, slow (≈20-35 Hz) and fast gamma (≈40-65 Hz), in the primary visual cortex (V1) of non-human primates. However, their mechanisms of generation and potential functional role in cortical processing remain unclear. Details of their burst signatures could potentially provide crucial insights about how the two rhythms influence network dynamics. Therefore, we computed burst statistics (durations and latencies) of simultaneously induced slow and fast gamma rhythms in the local field potential (LFP) recorded from area V1 of two adult female bonnet monkeys using several burst estimation methods. We found that slow gamma rhythm exhibited significantly longer burst durations and longer latencies than fast gamma rhythm. Slow gamma also exhibited higher long-range synchrony than fast gamma, as estimated by coherence and weighted phase lag index (WPLI). Interestingly, longer burst length of slow gamma could be replicated in a recently developed noisy Wilson-Cowan network model by simply changing the firing-rate time constant of the corresponding inhibitory interneuronal population, which led to both slower and longer bursts. These results are consistent with the hypothesis that the two oscillations are generated by different inter-neuronal classes that operate over different temporal and spatial scales of integration.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13697248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149278096","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":"Interactions between age and sex in multiscale entropy and spectral power changes across the lifespan.","authors":"Jack P Solomon, Simon G J Dobri, Kelly Shen, Vasily A Vakorin, Sylvain Moreno, Anthony R McIntosh","doi":"10.1162/IMAG.a.1407","DOIUrl":"https://doi.org/10.1162/IMAG.a.1407","url":null,"abstract":"<p><p>Multiscale entropy (MSE) changes in relation to age, whereby ageing is associated with an increasing bias towards fine scale entropy. This change is thought to represent a shift towards localized information processing in the brain as we age. However, this relationship has not been tested in large sample sizes alongside other demographic factors and cognitive behaviours. This study aimed to replicate previously reported effects of ageing on MSE in an open access database (Cambridge Centre for Ageing and Neuroscience, N = 587) and expand the findings to include an investigation of the effects of sex and a variety of cognitive behaviours. MSE curves and power spectrum densities (PSD) were calculated for each region of interest from the magnetoencephalography data. Multivariate partial least squares analyses were used to assess the relationship between MSE or PSD and five behavioural/demographic factors including age, sex, fluid intelligence, visual short-term memory, and a generalized measure of cognitive function. Age was associated with increased fine scale and decreased coarse scale entropy, as well as complementary spectral changes, including slowing of peak alpha rhythms, increased beta-band activity, and reduced gamma-band activity, which replicates prior MSE and PSD findings. In both domains, these age-related patterns differentiated based on sex with advancing age. Importantly, the unique effects of sex diverged between MSE and PSD. This result indicates that entropy-based measures can isolate aspects of temporal organization that are not clearly summarized by spectral structure alone.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13697247/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149278117","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":"The electro-MICA toolbox for integrating electrophysiology within multimodal imaging and connectomics workflows.","authors":"Nicolás von Ellenrieder, Zhengchen Cai, Thaera Arafat, Laura Vavassori, Chifaou Abdallah, Jordan De Kraker, Raul Rodriguez-Cruces, Jessica Royer, Ella Sahlas, Paul Bautin, Raluca Pana, Olivier Aron, Birgit Frauscher, Boris C Bernhardt","doi":"10.1162/IMAG.a.1413","DOIUrl":"https://doi.org/10.1162/IMAG.a.1413","url":null,"abstract":"<p><p>The integration of electrophysiological recordings with multimodal neuroimaging data holds great promise for advancing our understanding of brain function and neurological disorders. To facilitate this endeavor, we present electro-MICA, an open-access Python toolbox designed to project electrophysiological features from scalp and intracranial electroencephalography (EEG) onto cortical and hippocampal surfaces generated by validated multimodal imaging ecosystems. The toolbox comprises two pipelines: one for intracranial EEG (iEEG) recorded with stereo-EEG depth electrodes and one for scalp EEG source localization. Both pipelines are grounded in numerical solutions to the electromagnetic equations governing electric activity in the brain, solved using the Boundary Element Method. A key methodological contribution is the use of a current density double layer model for neural generators, which avoids the mathematical singularities introduced by conventional dipole-based models when electrodes are near the cortical surface, a situation that can arise in iEEG. Electrode contacts are additionally modeled with non-zero length, improving physical realism. Scalp EEG source localization is performed using eLORETA on a subject-specific three-layer head model derived from the anatomical input. Validation against empirical gamma-band iEEG data from 32 subjects demonstrates that the distributed generator model outperforms both distance-based and dipole-based alternatives. An illustrative clinical example demonstrates the toolbox's capacity to reveal associations between intracranial spike rates, cortical thickness, and anatomical connectivity in an epilepsy patient. Electro-MICA requires no parameter selection from the user, facilitating straightforward multimodal analyses. The toolbox is available at http://github.com/MICA-MNI/electromica with extensive online documentation at http://electromica.readthedocs.io.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13697246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149278067","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":"Beta-band dynamics during a naturalistic motor task: An OPM-MEG study.","authors":"Joseph Gibson, Jessikah Fildes, Alan Kirby, Niall Holmes, Lukas Rier, Karen J Mullinger, Matias Ison, Peter G Morris, Elena Boto, Ryan M Hill, Matthew J Brookes","doi":"10.1162/IMAG.a.1405","DOIUrl":"https://doi.org/10.1162/IMAG.a.1405","url":null,"abstract":"<p><p>Beta oscillations are a fundamental feature of brain activity, linked to long-range connectivity within canonical networks, inhibition of sensorimotor cortices, and the maintenance of a stable sensorimotor state in situations where the external world is predictable. The importance of beta oscillations in brain function is underscored by observations of their perturbation in neurological and psychiatric disorders. However, the precise role played by beta activity, particularly in mediating complex or skilful movements, remains incompletely understood. Here, we used a newly developed wearable optically pumped magnetometer-based magnetoencephalography (OPM-MEG) system to measure beta dynamics as participants learned to play a musical instrument. Twenty-two novice players took part in a study in which OPM-MEG data were recorded during two scanning sessions, while participants attempted to play a tune on a violin. Between the two sessions, participants received a violin lesson from an expert teacher. Results showed that robust data could be acquired during this naturalistic task, with beta oscillations decreasing in amplitude during movement and increasing upon movement cessation, as expected. Moreover, beta power while playing, in the motor and pre-motor areas, was significantly elevated after the lesson compared to before, and the movement-related modulation of beta amplitude was more pronounced after the lesson. These findings align with predictive coding models which suggest that beta amplitude should increase when individuals have greater certainty over the movements they carry out. Our study adds to an expanding literature on the role of beta oscillations and provides further evidence for the utility of OPM-MEG in naturalistic neuroscience.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13697249/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149278059","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":"Assessing the reliability of hippocampal single-voxel proton magnetic resonance spectroscopy through intra-class effect decomposition.","authors":"Martin Nilsson, Jonathan Berrebi, Sahar Nikkhou-Aski, Bárbara Avelar-Pereira, Per Thorsell, Vlad Legendi, Marc Guitart-Masip, Goran Papenberg","doi":"10.1162/IMAG.a.1401","DOIUrl":"https://doi.org/10.1162/IMAG.a.1401","url":null,"abstract":"<p><p>The hippocampus is crucial for learning, memory, and stress regulation, but is vulnerable to influences that compromise its structural and metabolic integrity. Proton magnetic resonance spectroscopy (MRS) enables in vivo quantification of hippocampal neurochemistry, yet the absolute and relative reliability of these measures has rarely been systematically evaluated. We assessed hippocampal metabolite estimates acquired with single-voxel MRS using a semi-adiabatic localization by adiabatic selective refocusing (semi-LASER) sequence at 3 T. Nineteen healthy adults (8 male; mean age = 40.9 ± 16.9 years) underwent four measurements across 2 consecutive days, with one session including an extended acquisition. Absolute reliability was quantified using within-subject coefficients of variation (CVs), and relative reliability was estimated with the Intra-Class Effect Decomposition (ICED) framework, which partitions variance into true-score, day-specific, session-specific, and residual components. Despite good spectral quality and high absolute reliability for several metabolites, relative reliability ranged from poor to good. Good relative reliability was observed only for water-referenced myo-inositol, total choline, and total creatine; no creatine-referenced metabolite reached this threshold. Increasing the number of transients increased signal-to-noise ratio but did not improve relative reliability; only creatine-referenced total N-acetylaspartate showed significant session-specific variance. Thus, high absolute reliability did not necessarily imply high relative reliability. Hippocampal MRS at 3 T may, therefore, be suitable for group-level or mean-level metabolite estimates, but appears less suitable for correlational, biomarker, or other individual-difference applications that require stable between-person differences. Methodological refinement, including improved voxel placement, motion correction, shimming, and quantification pipelines, may improve the relative reliability of hippocampal MRS.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13681051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149240697","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":"Bridging language phenotypes, neural dynamics and gene regulation in autism.","authors":"Mariette Vinurel, Xiaoyue Wang, Djeser Kordon, Delphine Jochaut, Mario Speranza, Cedric Boeckx, Anne-Lise Giraud","doi":"10.1162/IMAG.a.1396","DOIUrl":"https://doi.org/10.1162/IMAG.a.1396","url":null,"abstract":"<p><p>Autism Spectrum Disorders (ASDs) affect approximately 1% of the global population, with prevalence rising over recent decades. Although ASDs are heritable (~70%), translating genetic findings into effective therapeutics remains challenging due to the vast number of implicated risk genes (>700) and the limited influence of individual genes on disease expression. Their collective impact and convergent expression patterns of small-effect genes provide insights into ASD-related neurobiological mechanisms. Current interventions remain symptom-focused and do not address underlying neurodevelopmental mechanisms. Emerging approaches in functional genomics offer new insights into ASD pathogenesis by exploring gene expression diversity, yet clinical applications remain distant. Language deficits are among the most frequent and disabling features of ASD, profoundly affecting individuals' and families' quality of life. Recent evidence from neuroimaging and electrophysiology studies suggests disrupted neural oscillatory dynamics are linked to language deficits in ASD. Several ASD-associated genes have been implicated in biological pathways involved in the regulation of brain oscillatory dynamics, suggesting a potential mechanistic link between genetic variation, altered brain rhythms, and language impairment. We propose a neurophysiological imaging genetics framework that leverages neural oscillatory profiles as endophenotypes for targeted investigation and as functional readouts of gene expression. Within this framework, neuromodulation is proposed as an experimental approach to investigate and potentially modulate altered oscillatory dynamics associated with speech communication deficits in ASD, while integrating oscillation-related ASD candidate genes into a symptom-oriented model of functional genomics. This approach shows how integrating genetic variation, non-invasive neuroimaging, and behavioral phenotypes can advance our understanding of ASD and inform targeted, mechanism-based interventions.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13681050/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149240625","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":"Insulin resistance and brain sulcal morphology in non-diabetic adults.","authors":"Daisuke Yoshimaru, Ami Yuzawa, Masakazu Ozawa, Motoki Hirabayashi, Yutaka Matsushita, Tomokazu Tsurugizawa, Hirotaka James Okano","doi":"10.1162/IMAG.a.1402","DOIUrl":"https://doi.org/10.1162/IMAG.a.1402","url":null,"abstract":"<p><p>Insulin resistance exerts direct effects on brain structure, yet most neuroimaging evidence comes from populations with established diabetes, and conventional gray matter volumetry may lack sensitivity to detect early structural changes. Here, we examined associations between insulin resistance and sulcal morphology, a measure that integrates cortical thinning, subcortical atrophy, and white matter degeneration into a single outcome, in 728 non-diabetic adults (518 men, 210 women; mean age 61.4 ± 11.6 years). Brain volumes were quantified using OpenMAP-T1, an automated deep learning-based parcellation tool, and associations between HOMA-IR and 30 cerebrospinal fluid-related regional volumes were examined using multiple linear regression adjusted for age, sex, and estimated total intracranial volume, with FDR correction for multiple comparisons. Higher HOMA-IR was significantly associated with greater frontal sulcal volumes (left: β = 596 mm³, right: β = 344 mm³; both FDR-corrected p < 0.001), with a dose-response relationship across insulin resistance categories. This association was observed only in men (sex × HOMA-IR interaction p = 0.019) and was strongest in participants younger than 70 years. Mediation analysis revealed that the relationship between BMI and frontal sulcal enlargement was largely accounted for by the indirect pathway through insulin resistance, with no significant direct effect of BMI. These findings suggest that sulcal morphology can detect metabolic effects on brain structure at a pre-diabetic stage, changes that were not apparent through frontal gray matter volumetry in the same sample, and identify insulin resistance as a potential modifiable target for preserving brain health.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13681054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149240726","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":"Correction to: Oxygen extraction fraction mapping between normal cognition and mild cognitive impairment in older adults using quantitative BOLD.","authors":"Linh N N Le, Gregory J Wheeler, Nicholas P Blockley, Evan Fletcher, Youngkyoo Jung, Sarah E T Farias, Brandon Gavett, Charles DeCarli, Audrey P Fan","doi":"10.1162/IMAG.x.1423","DOIUrl":"https://doi.org/10.1162/IMAG.x.1423","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1162/IMAG.a.1378.].</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13681049/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149240784","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":"Inter-subject correlations and their behavioral associations vary across movies: Implications for generalizability.","authors":"Simon Leipold, Rajat Ravi Rao, Jan-Mathijs Schoffelen, Sara Bögels, Ivan Toni","doi":"10.1162/IMAG.a.1400","DOIUrl":"10.1162/IMAG.a.1400","url":null,"abstract":"<p><p>Movie-watching functional magnetic resonance imaging (fMRI) has become increasingly popular in neuroscience. Movie-fMRI data are commonly analyzed using inter-subject correlation (ISC), which quantifies the similarity of neural time series across individuals. Differences in ISC during movie viewing have been associated with psychological traits and clinical diagnoses. However, most studies investigating group differences in ISC or ISC-behavior associations have drawn conclusions from a single movie. Because ISC is inherently stimulus driven, effects observed for one movie may not generalize to another. Yet, the extent to which ISC patterns and ISC-behavior associations depend on the specific movie being viewed has received limited systematic attention. Here, we analyzed three independent datasets comprising 318 subjects and 36 movies in total to quantify between-movie variability in ISC and assess its consequences for ISC-behavior associations. Across datasets, ISC varied between movies throughout the cortex. This variability was spatially heterogeneous: regions with stronger ISC showed greater between-movie variability. Movie-specific inter-subject representational similarity analysis revealed distinct spatial distributions of ISC-behavior associations, with little overlap between movies. This pattern was observed for two distinct behavioral constructs. These findings suggest that ISC-behavior associations can be strongly movie specific.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13681052/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149240800","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":"Mentalizing from self and friend perspectives: Relations between inter-brain neural similarity, affective similarity and social anxiety symptoms.","authors":"Alicia Vallorani, Kathryn A McNaughton, Marisa N Lytle, Michael N Hallquist, Elizabeth Redcay, Koraly Pérez-Edgar","doi":"10.1162/IMAG.a.1403","DOIUrl":"10.1162/IMAG.a.1403","url":null,"abstract":"<p><p>Social interactions are dynamic and complex, relying on tracking variation in your own and your partner's affective and mental states. Being \"in-sync\" neurally and building a shared consensus can mark successful social interactions. In addition, social anxiety can impact social experiences. We used a novel, naturalistic paradigm to investigate relations between inter-brain neural similarity within mentalizing regions, affective similarity, and social anxiety symptoms. Undergraduate student friend pairs (N = 34, 85% White, 65% Women) engaged in a social interaction while videos captured from their individual perspectives were recorded. Participants watched clips of the social interaction from both their own perspective (their personal view of the social interaction) and their friend's perspective (their friend's personal view of the social interaction) while fMRI data were collected. They rated their affect after each clip. Inter-brain neural similarity was computed across three conditions: 1) Same-Stimuli: both participants viewed identical visual stimuli as in a traditional neural similarity paradigm, 2) Self-Perspective: both participants viewed the clip from their own perspective like the originally experienced social interaction, and 3) Friend-Perspective: both participants viewed the clip from their friend's perspective, a novel perspective. Participants self-reported their social anxiety symptoms, and affective similarity captured affect rating concordance within dyads. In contrast to the Same-Stimuli condition, when participants viewed the clips like they originally experienced the social interaction (Self-Perspective), greater affective similarity was associated with greater inter-brain neural similarity. When participants viewed the clips from a novel perspective (Friend-Perspective), participants lower in social anxiety symptoms exhibited greater inter-brain neural similarity with greater affective similarity; whereas participants higher in social anxiety symptoms exhibited greater inter-brain neural similarity with less affective similarity. The results suggest stimuli from socially relevant perspectives, rather than identical stimuli, may reveal more nuanced brain-behavior dynamics, allowing for a better understanding of individual differences in socioemotional experience.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13681053/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149240816","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}