Imaging neuroscience (Cambridge, Mass.)最新文献

{"title":"Causal evidence for dorsal stream involvement in object shape recognition: A tractography-guided ccPAS Registered Report study.","authors":"Elena Bertacco, Francesca Saviola, Edoardo Paolini, Francesca Benedetta Pizzini, Nicolò Cardobi, Agnese Tamanti, Silvia Francesca Storti, Debora Brignani, Silvia Savazzi, Daniele Corbo, Chiara Mazzi, Chiara Bagattini","doi":"10.1162/IMAG.a.1345","DOIUrl":"10.1162/IMAG.a.1345","url":null,"abstract":"<p><p>Visual experience requires orchestration of intricate brain connections. One of the most influential models of human visual information processing posits two segregated streams and postulates that conscious object recognition relies exclusively on the ventral visual stream. However, recent evidence suggests that the dorsal stream is involved in encoding crucial attributes of visual object recognition, such as global shape. The specific role of the dorsal stream is controversial in this context. Through an individualized multimodal approach, we investigated the contribution of the dorsal pathway to object recognition. Combining MRI-based diffusion-weighted imaging tractography with cortico-cortical paired associative stimulation protocol (ccPAS), we causally manipulated V1-to-IPS dorsal stream connectivity by strengthening synaptic efficacy between targeted regions through Hebbian-like plasticity mechanisms. Thirty-two healthy participants underwent three tractography-guided ccPAS sessions targeting right V1-to-IPS connectivity with different interstimulus intervals (9 ms, 0 ms, 30 ms). Before and after each session, participants performed a two-alternative forced-choice task requiring discrimination of either global shape or local features. Results showed that the critical 9 ms V1-to-IPS ccPAS protocol improved global shape discrimination, as indexed by accuracy and d', relative to the 0 ms control condition, with no effect on reaction times or response bias. Although task specificity was not fully supported, exploratory analyses revealed no changes in local feature discrimination. These findings provide causal evidence that strengthening dorsal V1-to-IPS connectivity enhances global shape processing, supporting a direct contribution of the dorsal stream to object recognition and potentially guiding the development of targeted rehabilitative interventions after visual system damage.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13556797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148922058","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":"Development of a 24-channel 3T phased-array coil for fMRI in awake monkeys: Mitigating spatiotemporal artifacts in ferumoxytol-weighted functional connectivity estimation.","authors":"Joonas A Autio, Atsushi Yoshida, Yoshihiko Kawabata, Masahiro Ohno, Kantaro Nishigori, Takayuki Ose, Stephen M Smith, David C Van Essen, Matthew F Glasser, Takuya Hayashi","doi":"10.1162/IMAG.a.1354","DOIUrl":"10.1162/IMAG.a.1354","url":null,"abstract":"<p><p>Functional magnetic resonance imaging (fMRI) of awake macaque monkeys holds promise for advancing our understanding of primate brain organization, including humans. However, estimating functional connectivity in awake animals is challenging due to the limited duration of imaging sessions and the relatively low sensitivity to neural activity. To overcome these challenges, we developed a 24-channel 3T receive radiofrequency (RF) coil optimized for parallel imaging of awake macaques. This enabled the acquisition of cross-plane and in-plane accelerated ferumoxytol-weighted resting-state fMRI. The Human Connectome Project-style data processing pipelines were adapted to address the unique preprocessing demands of cerebral blood volume-weighted (CBVw) imaging, including motion correction, functional-to-structural image co-registration, and training a multi-run independent component analysis-based X-noiseifier (ICA-FIX) classifier for removal of structured artifacts. Our CBVw fMRI approach resulted in an elevated contrast-to-noise ratio compared with blood oxygenation level-dependent (BOLD) imaging in anesthetized macaques. However, structured imaging artifacts still contributed more variance to the functional timeseries than neural activity. By applying the ICA-FIX classifier, we achieved highly reproducible parcellated functional connectivity at the single-subject level, with test-retest matrix correlations and subject identification accuracy comparable with those observed in humans. At the group level, we identified dense functional networks with spatial features homologous to those observed in humans. The developed RF receive coil, image acquisition protocols, and data analysis pipelines are publicly available, providing the broader scientific community with tools to leverage these advances for further research.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13543443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898637","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":"Model-based cardiac field artefact correction for OP-MEG.","authors":"Sascha P Woelk, Nicholas A Alexander, George C O'Neill, Sarah N Garfinkel, Gareth R Barnes","doi":"10.1162/IMAG.a.1353","DOIUrl":"10.1162/IMAG.a.1353","url":null,"abstract":"<p><p>Each heartbeat creates an electro-magnetic field that propagates throughout the body and is superimposed on measured brain activity in electroencephalography (EEG) and magnetoencephalography (MEG) recordings. Being several orders of magnitude larger than a typical evoked response in the brain, the Cardiac Field Artefact (CFA) is especially problematic in studies where cortical activity time locked to the cardiac cycle is of interest, such as in interoception research. In this work, we develop a model-based CFA correction method, which exploits the fact that the magnetic field propagates relatively evenly through the mostly diamagnetic tissue of the human body, and that in studies using wearable optically pumped magnetometers (OP-MEG), participants are free to rotate their head. Free head rotation decouples the heart's magnetic field from that of the brain, allowing for the creation of a cardiac dipole moment (CDM) estimate, that is, an estimate of the electrical current flow in the heart, which is minimally confounded by concurrent neuronal activity in the brain. We show in simulations that, given information about the relative position and orientation of head and chest, this CDM estimate can be used to predict and correct the sensor-level CFA by dynamically accounting for the spatial relationship between heart, brain, and sensors. We further provide an empirical proof-of-principle demonstration of the pipeline in a single participant using recordings with intermittent head movement, tracked by optical motion capture, as well as an established auditory response paradigm with well-characterized response pattern.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13543444/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898611","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":"Rapid cortical mapping with cross-participant encoding models.","authors":"Jerry Tang, Alexander G Huth","doi":"10.1162/IMAG.a.1349","DOIUrl":"10.1162/IMAG.a.1349","url":null,"abstract":"<p><p>Voxelwise encoding models trained on functional MRI data can produce detailed maps of cortical organization. However, voxelwise encoding models must be trained on many hours of brain responses from each participant, limiting clinical applications. In this study, we introduce a cross-participant modeling framework for rapid cortical mapping. In this framework, voxelwise encoding models are trained on many hours of brain responses from previously scanned reference participants, and then transferred to a new participant by aligning brain responses using a small set of stimuli. We evaluated cross-participant encoding models on linguistic semantic mapping, non-linguistic semantic mapping, and auditory mapping. In each case, we found that cross-participant encoding models had more accurate selectivity estimates and prediction performance than within-participant encoding models trained on the same amount of data from the new participant. We also found that cross-participant encoding models improved with the amount of data from each reference participant and the number of reference participants. These results demonstrate that cross-participant modeling can substantially reduce the amount of data required for detailed cortical mapping, which may facilitate new clinical applications of functional neuroimaging.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13543446/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148898605","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":"Hyperpolarized ¹³C-bicarbonate production correlates with excitatory neuron distribution in the human brain.","authors":"Biranavan Uthayakumar, Dylan A Dingwell, Nicole I C Cappelletto, Nadia D Bragagnolo, Albert P Chen, Nathan Ma, Ruby Endre, Jesse Gillis, Hany Soliman, Charles H Cunningham","doi":"10.1162/IMAG.a.1342","DOIUrl":"10.1162/IMAG.a.1342","url":null,"abstract":"<p><p>Whole-brain metabolic topography measured with hyperpolarized ¹³C-pyruvate MRI in 40 healthy individuals was correlated with microarray transcriptomic data from the Allen Human Brain Atlas. Spatial autocorrelation was addressed using both model-based and non-model-based methods, and two parcellation atlases with different numbers of regions were employed to reduce the likelihood of false positives. Brain regions with higher expression of transcripts characteristic of excitatory neurons showed an elevated bicarbonate-to-pyruvate ratio, indicating a higher flux through pyruvate dehydrogenase. Specifically, the Ex2 and Ex4 excitatory neuron subtypes showed the strongest enrichment among all cell-type gene sets. Collectively, these findings connect regional variations in metabolic neuroimaging profiles to underlying patterns of cellular gene expression, offering a framework for understanding the molecular basis of tissue-level metabolic organization.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13537045/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148882787","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 role of high-amplitude bursts of high-gamma activity in naturalistic speech and music listening.","authors":"Matteo Neri, Claudio Runfola, Pierre Guilleminot, Noemie Te Rietmolen, Pierpaolo Sorrentino, Daniele Schon, Benjamin Morillon, Giovanni Rabuffo","doi":"10.1162/IMAG.a.1348","DOIUrl":"10.1162/IMAG.a.1348","url":null,"abstract":"<p><p>A central challenge in systems neuroscience is to understand how distributed brain networks organize activity during naturalistic cognition. Here, we investigate whether transient, high-amplitude bursts of high-gamma activity, referred to as neuronal avalanches, provide a compact and functionally informative description of large-scale neural dynamics during auditory processing. Using intracranial stereotactic intracranial electroencephalography (sEEG) recordings from epileptic patients, we analyzed brain activity during speech listening, music listening, and rest. We show that high-amplitude bursts, defined as the top 1% of high-gamma activations, are strongly stimulus-driven: they synchronize across participants exposed to the same auditory input, exhibit condition-specific spatial topographies, and display distinct propagation patterns across cortical networks. Notably, although these events represent only a small fraction of the signal, they preserve substantial stimulus-related information. Temporal response function analyses reveal that avalanche activity reliably encodes both speech and music stimuli, even under extreme data sparsification. Together, these findings demonstrate that neuronal avalanches capture stimulus-relevant, large-scale neural dynamics and provide a computationally efficient framework for studying cognition in naturalistic settings.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522956/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148852122","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":"Improving respiratory and heart rate variation estimation from resting-state BOLD fMRI across the lifespan using a functionally informed, tissue-aware deep learning framework.","authors":"Abdoljalil Addeh, Karen Ardila, Pattarawut Charatpangoon, Ethan Church, Rebecca J Williams, G Bruce Pike, M Ethan MacDonald","doi":"10.1162/IMAG.a.1346","DOIUrl":"10.1162/IMAG.a.1346","url":null,"abstract":"<p><p>Accurate measurement of physiological signals such as respiration and cardiac activity is essential for modeling physiological confounds in BOLD-fMRI data. However, external monitoring devices such as respiratory belts and photoplethysmographs often suffer from signal loss, noise, or incomplete recordings, and many fMRI datasets lack physiological measurements altogether due to practical constraints. In this work, we propose a data-driven framework to reconstruct respiratory variation (RV) and heart rate variation (HRV) directly from resting-state fMRI data using a hybrid machine learning architecture that combines one-dimensional convolutional neural networks (1D-CNN) with gated recurrent units (GRUs). The model processes BOLD signals from 630 regions of interest (ROIs), spanning cortical and subcortical gray matter, white matter, and cerebrospinal fluid. For RV estimation, six head motion parameters were included as additional inputs to capture motion-related physiological information. The proposed method was trained and evaluated on three cohorts across the lifespan from the Human Connectome Project (HCP), including HCP in Development (HCP-D, ages 5-21 years), HCP in Young Adults (HCP-YA, ages 22-35 years), and HCP in Aging (HCP-A, ages 36-100 years). Age-specific architectural tuning was applied to accommodate developmental, neurovascular, and physiological variability across these populations. When compared against established CNN- and RNN-based baselines under matched preprocessing and native temporal resolution, the proposed architecture achieved consistent performance gains across all evaluation metrics. The largest relative improvements were observed for error-based and temporal alignment metrics, with MAE, MSE, and DTW reduced by approximately 7-10%, indicating lower absolute reconstruction error and improved temporal fidelity, while correlation-based improvements were more modest (approximately 5-7%). These results demonstrate the feasibility and effectiveness of reconstructing RV and HRV directly from fMRI time series using spatially and temporally enriched neural architectures. Building on earlier efforts in this domain, the proposed framework extends prior work through evaluation across multiple cohorts, broader anatomical coverage, and enhanced modeling capacity, offering a robust alternative for physiological modeling in the absence of external recordings.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13522955/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148852074","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":"Brain cannabinoid CB1 receptor signaling modulates reward responses and inhibitory control in humans.","authors":"Lihua Sun, Tatu Kantonen, Laura Pekkarinen, Pirjo Nuutila, Lauri Nummenmaa","doi":"10.1162/IMAG.a.1344","DOIUrl":"10.1162/IMAG.a.1344","url":null,"abstract":"<p><p>The central endocannabinoid system, particularly the <i>in vivo</i> cannabinoid type 1 (CB1) receptor signaling, presents a promising target for treating eating disorders. However, its precise role in appetite control remains unclear. This study aimed to determine how CB1 receptor signaling contributes to key aspects of appetite regulation, specifically anticipatory food reward responses and inhibitory control. Forty-one healthy male participants underwent [¹⁸F]FMPEP-d2 positron emission tomography (PET) to quantify CB1 receptor availability. Functional magnetic resonance imaging (fMRI) was used to assess anticipatory neural responses to food cues, while inhibitory control was measured using a go/nogo task. Data show that individuals with higher CB1 receptor availability exhibited stronger anticipatory reward-related neural responses and reduced activation during inhibitory control. Therefore, CB1 receptor signaling plays a distinct role in modulating reward and inhibitory processes related to feeding behavior. The findings suggest that the CB1 receptor may serve as a therapeutic target for regulating appetite.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519986/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148842186","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":"Neural and behavioural correlates of theory of mind reasoning in five-year-old children born preterm.","authors":"Selina Abel, Melissa Thye, Katie Mckinnon, Rebekah Smikle, Jean Skelton, Lorena Jiménez-Sánchez, Ray Amir, Gayle Barclay, Charlotte Jardine, Donna Mcintyre, Iona Hamilton, Yu Wei Chua, Aditi Hosangadi, Alan Quigley, G David Batty, Michael J Thrippleton, Heather C Whalley, James P Boardman, Hilary Richardson","doi":"10.1162/IMAG.a.1347","DOIUrl":"10.1162/IMAG.a.1347","url":null,"abstract":"<p><p>Behavioural studies suggest atypical or delayed development of \"theory of mind\" (ToM; our ability to reason about others' mental states) following preterm birth. Using pre-registered analyses of behavioural and movie-viewing functional magnetic resonance imaging (fMRI) metrics of ToM, we tested for a domain-specific impact of preterm birth (24-32 weeks' gestational age) on theory of mind development at age 5 years. Preterm-born children (<i>n</i> = 52) scored lower than term-born comparators (<i>n</i> = 58) on a linguistic behavioural ToM task, but this difference was primarily driven by differences in receptive language. Neurally, preterm-born children (<i>n</i> = 30) had qualitatively similar responses in brain regions that support ToM reasoning to a short movie to term-born comparators (<i>n</i> = 46), as characterised by four neural metrics; responses to one scene differed as a function of gestational age. Using intersubject correlation analyses, we found that preterm-born children's ToM network responses were more heterogenous than term-born children's responses; however, individual preterm-born children's responses most resembled those observed in same-age term-born children, relative to younger children or other preterm-born children. Taken together, preterm birth does not appear to preclude broadly similar functional development in ToM brain regions by age 5 years.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519987/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148842178","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: N-back task revisited: Comparing the neural correlates of updating and interference control.","authors":"Esmeralda Hidalgo-Lopez, Isabel Noachtar, Belinda Angela Pletzer","doi":"10.1162/IMAG.x.1339","DOIUrl":"https://doi.org/10.1162/IMAG.x.1339","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1162/IMAG.a.1025.].</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13507899/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148835387","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}