Rohan Banerjee, Merve Kaptan, Alexandra Tinnermann, Ali Khatibi, Alice Dabbagh, Christian Büchel, Christian W Kündig, Christine S W Law, Dario Pfyffer, David J Lythgoe, Dimitra Tsivaka, Dimitri Van De Ville, Falk Eippert, Fauziyya Muhammad, Gary H Glover, Gergely David, Grace Haynes, Jan Haaker, Jonathan C W Brooks, Jürgen Finsterbusch, Katherine T Martucci, Kimberly J Hemmerling, Mahdi Mobarak-Abadi, Mark A Hoggarth, Matthew A Howard, Molly G Bright, Nawal Kinany, Olivia S Kowalczyk, Patrick Freund, Robert L Barry, Sean Mackey, Shahabeddin Vahdat, Simon Schading, Stephen B McMahon, Todd Parish, Véronique Marchand-Pauvert, Yufen Chen, Zachary A Smith, Kenneth A Weber Ii, Benjamin De Leener, Julien Cohen-Adad
{"title":"EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data.","authors":"Rohan Banerjee, Merve Kaptan, Alexandra Tinnermann, Ali Khatibi, Alice Dabbagh, Christian Büchel, Christian W Kündig, Christine S W Law, Dario Pfyffer, David J Lythgoe, Dimitra Tsivaka, Dimitri Van De Ville, Falk Eippert, Fauziyya Muhammad, Gary H Glover, Gergely David, Grace Haynes, Jan Haaker, Jonathan C W Brooks, Jürgen Finsterbusch, Katherine T Martucci, Kimberly J Hemmerling, Mahdi Mobarak-Abadi, Mark A Hoggarth, Matthew A Howard, Molly G Bright, Nawal Kinany, Olivia S Kowalczyk, Patrick Freund, Robert L Barry, Sean Mackey, Shahabeddin Vahdat, Simon Schading, Stephen B McMahon, Todd Parish, Véronique Marchand-Pauvert, Yufen Chen, Zachary A Smith, Kenneth A Weber Ii, Benjamin De Leener, Julien Cohen-Adad","doi":"10.1162/IMAG.a.98","DOIUrl":"10.1162/IMAG.a.98","url":null,"abstract":"<p><p>Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.1 and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared with other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12421696/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145042348","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":"Detecting mild traumatic brain injury with MEG scan data: One-vs-K-sample tests.","authors":"Jian Zhang, Gary Green","doi":"10.1162/IMAG.a.137","DOIUrl":"10.1162/IMAG.a.137","url":null,"abstract":"<p><p>Magnetoencephalography (MEG) scanner has been shown to be more accurate than other medical devices in detecting mild traumatic brain injury (mTBI). However, MEG scan data in certain spectrum ranges can be skewed, multimodal, and heterogeneous which can mislead the conventional case-control analysis that requires the data to be homogeneous and normally distributed within the control group. To meet this challenge, we propose a flexible one-vs-K-sample testing procedure for detecting brain injury for a single-case versus heterogeneous controls. The new procedure begins with source magnitude imaging using MEG scan data in frequency domain, followed by region-wise contrast tests for abnormality between the case and controls. The critical values for these tests are automatically determined by cross-validation. We adjust the testing results for heterogeneity effects by similarity analysis. An asymptotic theory is established for the proposed test statistic. By simulated and real data analyses in the context of neurotrauma, we show that the proposed test outperforms commonly used nonparametric methods in terms of overall accuracy and ability in accommodating data non-normality and subject-heterogeneity.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12418114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145042283","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}
Malte R Güth, Andrew Reid, Yu Zhang, Sonja C Huntgeburth, Ravi D Mill, Alain Dagher, Kim Kerns, Clay B Holroyd, Michael Petrides, Michael W Cole, Travis E Baker
{"title":"Right posterior theta reflects human parahippocampal phase resetting by salient cues during goal-directed navigation.","authors":"Malte R Güth, Andrew Reid, Yu Zhang, Sonja C Huntgeburth, Ravi D Mill, Alain Dagher, Kim Kerns, Clay B Holroyd, Michael Petrides, Michael W Cole, Travis E Baker","doi":"10.1162/IMAG.a.105","DOIUrl":"10.1162/IMAG.a.105","url":null,"abstract":"<p><p>Animal and computational work indicate that phase resetting of theta oscillations (4-12 Hz) in the parahippocampal gyrus (PHG) by salient events (e.g., reward, landmarks) facilitates the encoding of goal-oriented information during navigation. Although well studied in animals, this mechanism has not been empirically substantiated in humans. In the present article, we present data from two studies (Study 1: asynchronous electroencephalography (EEG)-magnetoencephalography (MEG) | Study 2: simultaneous EEG-fMRI) to investigate theta phase resetting and its relationship with PHG blood oxygenation level dependent (BOLD) activation in healthy adults (aged 18-34 years old) navigating a virtual T-maze to find rewards. In the first experiment, both EEG and MEG data revealed a burst of theta power over right-posterior scalp locations following feedback onset (termed right-posterior theta, RPT), and RPT power and measures of phase resetting were sensitive to the subject's spatial trajectory. In Experiment 2, we used probabilistic tractography data from the human connectome project to segment the anterior and posterior PHG based on differential connectivity profiles to other brain regions. This analysis resulted in a PHG subdivision consisting of four distinct anterior and two posterior PHG clusters. Next, a series of linear mixed effects models based on simultaneous EEG-fMRI data revealed that single-trial RPT peak power significantly predicted single-trial hemodynamic responses in two clusters within the posterior PHG and one in the anterior PHG. This coupling between RPT power and PHG BOLD was exclusive to trials performed during maze navigation, and not during a similar task devoid of the spatial context of the maze. These findings highlight a role of PHG theta phase resetting for the purpose of encoding salient information during goal-directed spatial navigation. Taken together, RPT during virtual navigation integrates experimental, computational, and theoretical research of PHG function in animals with human cognitive electrophysiology studies and clinical research on memory-related disorders such as Alzheimer's disease.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12418113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145042413","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}
Jiaxin Cindy Tu, Jung-Hoon Kim, Chenyan Lu, Patrick H Luckett, Babatunde Adeyemo, Joshua S Shimony, Jed T Elison, Adam T Eggebrecht, Muriah D Wheelock
{"title":"Deep learning-based embedding of functional connectivity profiles for precision functional mapping.","authors":"Jiaxin Cindy Tu, Jung-Hoon Kim, Chenyan Lu, Patrick H Luckett, Babatunde Adeyemo, Joshua S Shimony, Jed T Elison, Adam T Eggebrecht, Muriah D Wheelock","doi":"10.1162/IMAG.a.129","DOIUrl":"10.1162/IMAG.a.129","url":null,"abstract":"<p><p>Spatial similarity of functional connectivity profiles across matching anatomical locations in individuals is often calculated to delineate individual differences in functional networks. Likewise, spatial similarity is assessed across average functional connectivity profiles of groups to evaluate the maturity of functional networks during development. Despite its widespread use, spatial similarity is limited to comparing two samples at a time. In this study, we employed a variational autoencoder to embed functional connectivity profiles from various anatomical locations, individuals, and group averages for simultaneous comparison. We demonstrate that our variational autoencoder, with pre-trained weights, can project new functional connectivity profiles from the vertex space to a latent space with as few as two dimensions, yet still retain meaningful global and local structures in the data. Functional connectivity profiles from various functional networks occupy distinct compartments of the latent space. Moreover, the variability of functional connectivity profiles from the same anatomical location is readily captured in the latent space. We believe that this approach could be useful for visualization and exploratory analyses in precision functional mapping.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12409741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145016794","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 representations of visual statistical learning based on temporal duration.","authors":"Sachio Otsuka, Jun Saiki","doi":"10.1162/IMAG.a.135","DOIUrl":"10.1162/IMAG.a.135","url":null,"abstract":"<p><p>Time perception is an essential aspect of daily life, and transitional probabilities can be learned based on temporal durations that are independent of individual objects. Previous studies on temporal and spatial visual statistical learning (VSL) have shown that the hippocampus and lateral occipital cortex are engaged in learning visual regularities. However, it remains unclear whether VSL on temporal duration unlinked to object identity is represented in brain regions involved in VSL and object recognition or in those involved in time perception without sensory cortex involvement. We examined this question by adapting a VSL paradigm to time perception using functional magnetic resonance imaging. Thirty-four students participated in the VSL experiment, comprising a familiarization scan and a subsequent familiarity-decision test. The region-of-interest (ROI)-based classification showed chance-level performance across all ROIs, but only the left medial frontal gyrus, which is involved in subsecond time perception, showed a moderate effect size with 95% confidence intervals not crossing the chance level of 50%. Moreover, searchlight analysis showed that the right orbitofrontal cortex successfully decoded brain responses related to the processing of structured timing sequences. Meanwhile, representational similarity analysis suggested that the neural signal patterns could not be divided between the structured timing and pseudo-random sequences in the lateral occipital cortex. Our findings serve as a pilot study suggesting that the medial frontal and orbitofrontal regions are involved in VSL based on temporal duration, independent of visual object processing, which is a key and common timing mechanism for predicting sequential events.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12409740/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145016742","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}
Patrick Bedard, Kristine M Knutson, Patrick M McGurrin, Felipe Vial, Traian Popa, Silvina G Horovitz, Mark Hallett, Avindra Nath, Brian Walitt
{"title":"Multimodal neuroimaging of fatigability development.","authors":"Patrick Bedard, Kristine M Knutson, Patrick M McGurrin, Felipe Vial, Traian Popa, Silvina G Horovitz, Mark Hallett, Avindra Nath, Brian Walitt","doi":"10.1162/IMAG.a.132","DOIUrl":"10.1162/IMAG.a.132","url":null,"abstract":"<p><p>Fatigability refers to the inability of the neuromuscular system to generate enough force to produce movements to meet task challenges. Fatigability has a central and a peripheral component linked via the neuromuscular system, but how these two components interact as fatigue develops lacks a complete understanding. The effects of fatigability are experienced in healthy humans but also accompany various disorders, often exacerbating their symptoms. We studied how fatigability develops in the neuromuscular system using multimodal neuroimaging. We recruited healthy participants to perform a fatiguing grip force task, while recording force, electromyography of forearm muscles (EMG), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI) in 30-second blocks of grip task alternating with 30 seconds of rest. The task entailed maintaining 50% of the maximum force. We combined EMG and EEG to compute corticomuscular coherence and combined EEG and fMRI to compute EEG-informed fMRI. We selected eight task blocks specific to each participant to represent how the neuromuscular system adapted from pre-fatigability to actual fatigability. Those included five blocks for pre-fatigability in which participants could generate enough force to match the required 50% of maximum force and three blocks when the force fell below that limit. Across blocks of the grip force task, we observed changes in the neuromuscular system that preceded grip force changes. We found that electromyography of arm muscles shifted from high to low frequency, EEG in the channel covering the contralateral sensorimotor area increased steadily up to the fifth block and then plateaued, and fMRI signal also increased in the cerebellum. Corticomuscular coherence increased within each of the 30-second blocks of the grip task. EEG-informed fMRI revealed areas of the brain that the traditional regression did not, including the bilateral sensorimotor cortex, temporal-parietal junction, and supplementary motor area. Thus, as fatigability developed, the neuromuscular system experienced changes earlier than the actual behavior. While we found evidence for fatigability of central and peripheral origins, peripheral fatigue seems to occur first.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12406056/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145002161","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":"More similarity than difference: Comparison of within- and between-sex variance in early adolescent brain structure.","authors":"Carinna Torgerson, Katherine Bottenhorn, Hedyeh Ahmadi, Jeiran Choupan, Megan M Herting","doi":"10.1162/IMAG.a.127","DOIUrl":"10.1162/IMAG.a.127","url":null,"abstract":"<p><p>Adolescent neuroimaging studies of sex differences in the human brain predominantly examine average differences between males and females. This focus on mean differences without probing relative distributions and similarities may contribute to both conflation and overestimation of sex differences and sexual dimorphism in the developing human brain. We aimed to characterize the variance in brain macro- and micro-structure in early adolescence as it pertains to sex at birth using a large sample of 9-11-year-olds from the Adolescent Brain Cognitive Development (ABCD) Study (N = 7,723). For global and regional estimates of gray and white matter volume, cortical thickness, and white matter microstructure (i.e., fractional anisotropy and mean diffusivity), we examined: within- and between-sex variance, overlap between male and female distributions, inhomogeneity of variance, effect size, and CLES. We examined these sex differences using both unadjusted (raw) brain estimates and residualized brain estimates from mixed-effects modeling (adjusted) to account for variance better attributed to age, pubertal development, socioeconomic status, race, ethnicity, MRI scanner manufacturer, and total brain volume, where applicable. Contrary to the popular view of the brain as sexually dimorphic, we found high similarity and low difference between sexes in all regional measurements of brain structure examined after accounting for other sources of variance. However, the sex difference for adjusted total brain volume (TBV) had a medium effect size and a 71.9% probability that a randomly chosen male adolescent would have a larger brain than a randomly chosen female adolescent. All cortical and subcortical volumes showed significant inhomogeneity of variance between sexes, whereas a minority of brain regions showed significant sex differences in variance for cortical thickness, white matter volume, fractional anisotropy, and mean diffusivity. Previously reported sex differences in early adolescent regional human brain volume may, therefore, be driven by disparities in variance, rather than binary, sex-based phenotypes. This study builds upon previous findings illustrating the importance of considering variance when examining sex differences in brain structure.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12406053/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145002176","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}
Severi Santavirta, Yuhang Wu, Lauri Suominen, Lauri Nummenmaa
{"title":"GPT-4V shows human-like social perceptual capabilities at phenomenological and neural levels.","authors":"Severi Santavirta, Yuhang Wu, Lauri Suominen, Lauri Nummenmaa","doi":"10.1162/IMAG.a.134","DOIUrl":"10.1162/IMAG.a.134","url":null,"abstract":"<p><p>Humans navigate the social world by rapidly perceiving social features from other people and their interaction. Recently, large-language models (LLMs) have achieved high-level visual capabilities for detailed object and scene content recognition and description. This raises the question whether LLMs can infer complex social information from images and videos, and whether the high-dimensional structure of the feature annotations aligns with that of humans. We collected evaluations for 138 social features from GPT-4V for images (N = 468) and videos (N = 234) that are derived from social movie scenes. These evaluations were compared with human evaluations (N = 2,254). The comparisons established that GPT-4V can achieve human-like capabilities at annotating individual social features. The GPT-4V social feature annotations also express similar structural representation compared to the human social perceptual structure (i.e., similar correlation matrix over all social feature annotations). Finally, we modeled hemodynamic responses (N = 97) to viewing socioemotional movie clips with feature annotations by human observers and GPT-4V. These results demonstrated that GPT-4V based stimulus models can also reveal the social perceptual network in the human brain highly similar to the stimulus models based on human annotations. These human-like annotation capabilities of LLMs could have a wide range of real-life applications ranging from health care to business and would open exciting new avenues for psychological and neuroscientific research.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12410153/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145016722","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":"Searchlight-based trial-wise fMRI decoding in the presence of trial-by-trial correlations.","authors":"Joram Soch","doi":"10.1162/IMAG.a.131","DOIUrl":"10.1162/IMAG.a.131","url":null,"abstract":"<p><p>In multivariate pattern analysis (MVPA) for functional magnetic resonance imaging (fMRI) signals, trial-wise response amplitudes are sometimes estimated using a general linear model (GLM) with one onset regressor for each trial. When using rapid event-related designs with trials closely spaced in time, those estimates can be highly correlated due to the temporally smoothed shape of the hemodynamic response function. In previous work (Soch et al., 2020), we have proposed inverse transformed encoding modeling (ITEM), a principled approach for trial-wise decoding from fMRI signals in the presence of trial-by-trial correlations. Here, we (i) perform simulation studies addressing its performance for multivariate signals and (ii) present searchlight-based ITEM analysis-which allows to predict a variable of interest from the vicinity of each voxel in the brain. We empirically validate the approach by confirming <i>a priori</i> plausible hypotheses about the well-understood visual system.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12406051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145002116","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}
Pierre-Antoine Comby, Alexandre Vignaud, Philippe Ciuciu
{"title":"SNAKE: A modular realistic fMRI data simulator from the space-time domain to k-space and back.","authors":"Pierre-Antoine Comby, Alexandre Vignaud, Philippe Ciuciu","doi":"10.1162/IMAG.a.121","DOIUrl":"10.1162/IMAG.a.121","url":null,"abstract":"<p><p>We propose a new, modular, open-source, Python-based 3D+time realistic functional magnetic resonance imaging (fMRI) data simulation software. SNAKE or <i>S</i>imulator from <i>N</i>eurovascular coupling to <i>A</i>cquisition of <i>K</i>-space data for <i>E</i>xploration of fMRI acquisition techniques. It is the first simulator to simulate the entire chain of fMRI data acquisition, from the spatio-temporal design of evoked brain responses to various 3D sampling strategies of k-space data with multiple coils. We now have the possibility to extend the forward acquisition model to different noise and artifact sources while remaining memory-efficient. Using this in-silico setup, we can provide a realistic and reproducible ground truth for fMRI reconstruction methods in 3D accelerated acquisition settings and explore the influence of critical parameters. This includes the acceleration factor and signal-to-noise ratio (SNR), on downstream tasks of image reconstruction and statistical analysis of evoked brain activity. In this paper, we present three scenarios of increasing complexity to showcase the flexibility, versatility, and fidelity of SNAKE: From a temporally fixed full 3D Cartesian to various 3D non-Cartesian sampling patterns, we can compare-with reproducibility guarantees-how experimental paradigms, acquisition strategies, and reconstruction methods contribute and interact together, affecting the downstream statistical analysis.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12406052/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145002153","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}