Imaging neuroscience (Cambridge, Mass.)最新文献

{"title":"The multidimensional relationship between alpha oscillations and cognition.","authors":"Agatha Lenartowicz, Sebastian C Coleman, Nicolas Zink, Karen J Mullinger","doi":"10.1162/IMAG.a.96","DOIUrl":"10.1162/IMAG.a.96","url":null,"abstract":"<p><p>Alpha oscillations are a robust neurophysiological phenomenon associated with cortical suppression and synaptic input gating, functionally interpreted as a mechanism of selective attention. Here, we highlight known dissociations between alpha oscillations and selective attention that question the specificity of this interpretation. We postulate that the inconsistencies are accounted for when we consider alpha oscillations as a neurophysiological mechanism that tracks cortical excitability, but one that can be modulated by a multitude of factors that include but are not limited to selective attention and include bottom-up and top-down interactions, internal processes, and regulatory system influences on cortical excitability. Thus, reverse inference regarding the cognitive role of alpha modulations may depend on experimental context. Importantly, this perspective reiterates that there exists a significant need for research that disentangles the mechanistic bases of alpha oscillations across different cognitive phenomena.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330858/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839170","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":"Local response function estimation in spherical deconvolution for comprehensive tissue representation using diffusion MRI.","authors":"Siebe Leysen, Ahmed Radwan, Frederik Maes, Stefan Sunaert, Daan Christiaens","doi":"10.1162/IMAG.a.95","DOIUrl":"10.1162/IMAG.a.95","url":null,"abstract":"<p><p>Diffusion MRI (dMRI) plays a crucial role in studying tissue microstructure and fibre orientation. Due to the intricate nature of the dMRI signal, end users require representations that provide a straightforward interpretation. Currently, these representations rely on tissue-average estimations or simplified tissue models and are hence limited in their applicability to pathology. In this study, we propose a novel approach called LoRE-SD-a local response function estimation in spherical deconvolution. LoRE-SD minimises assumptions about tissue microstructure to improve the reconstruction of dMRI data in the presence of pathology. This is achieved by introducing a general signal representation that spans the most common multi-compartment microstructure models used in neuroimaging. Leveraging spherical deconvolution, LoRE-SD provides accurate estimations of the local fibre orientations, allowing tractography in the healthy and pathological brain. We evaluate this approach using simulations and in vivo data from a healthy volunteer and from patients with glioma. Comparing the results quantitatively with the state-of-the-art, we find that LoRE-SD accurately reconstructs fibre orientations across the brain while also significantly improving glioma reconstruction and fibre bundle estimation. Additionally, the tissue representation in LoRE-SD facilitates the generation of various image contrasts, including response function anisotropy and contrasts accentuating intra-axonal, extra-axonal, and free water spaces, which enables a more flexible approach for tractography. In conclusion, LoRE-SD introduces a framework for estimating a data-driven, local representation of tissue microstructure with minimal prior assumptions. This approach provides a new way to represent the human brain, pathology, and other organs using dMRI and opens avenues for defining novel image contrasts, which may benefit tractography.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839052","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":"Imaging the developing brain with near-infrared spectroscopy in cochlear implanted children.","authors":"Gaia Lucarini, Caroline Nallet, Davide Brotto, Valeria Del Vecchio, Alessandro Martini, Patrizia Trevisi, Anna Rita Fetoni, Judit Gervain","doi":"10.1162/IMAG.a.90","DOIUrl":"10.1162/IMAG.a.90","url":null,"abstract":"<p><p>Cochlear implants (CIs) have revolutionized how we treat hearing impairment. Despite major technological and clinical advances, some CI children's language abilities remain below those of their age-matched peers, and there is still considerable individual variability in final outcomes. One important factor underlying this may be individual differences in brain plasticity before and after implantation. However, the neural changes induced in the developing brain by deafness, language deprivation, and the restoration of hearing due to implantation are little understood, in part because the methodological options available are limited. Recently, functional near-infrared spectroscopy (fNIRS) has emerged as a fully CI-compatible, infant-friendly, non-invasive, and inexpensive technique that holds the promise of shedding light on the neural mechanisms accompanying deafness and CI use. Here, we review the existing fNIRS studies with developmental populations. We then discuss the methodological challenges that using fNIRS with CI children raise. Finally, we describe open questions that fNIRS has the potential to answer. We conclude that fNIRS is a powerful tool to investigate the neural mechanisms and changes brought about by deafness and the subsequent restoration of hearing with CI.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839097","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":"An fMRI study of initiation and inhibition of manual and spoken responses in people who stutter.","authors":"Charlotte E E Wiltshire, Jennifer Chesters, Saloni Krishnan, Gabriel J Cler, Máiréad P Healy, Kate E Watkins","doi":"10.1162/IMAG.a.89","DOIUrl":"10.1162/IMAG.a.89","url":null,"abstract":"<p><p>Stuttering is characterised by difficulties initiating speech and frequent interruptions to the flow of speech. Neuroimaging studies of speech production in people who stutter consistently reveal greater activity of the right inferior frontal cortex, an area robustly implicated in stopping manual and spoken responses. This has been linked to an \"overactive response suppression mechanism\" in people who stutter. Here, we used fMRI to investigate neural differences related to response initiation and inhibition in people who stutter and matched controls (aged 19-45) during performance of the stop-signal task in both the manual and speech domains. We hypothesised there would be increased activity in an inhibitory network centred on the right inferior frontal cortex. Out-of-scanner behavioural testing revealed that people who stutter were slower than controls to respond to 'go' stimuli in both the manual and the speech domains, but the groups did not differ in their stop-signal reaction times in either domain. During the fMRI task, both groups activated the expected networks for the manual and speech tasks. Contrary to our hypothesis, we did not observe differences in task-evoked activity between people who stutter and controls during either 'go' or 'stop' trials. Targeted region-of-interest analyses in the inferior frontal cortex, the supplementary motor area, and the putamen bilaterally confirmed that there were no group differences in activity. These results focus on tasks involving button presses and production of single nonwords, and therefore do not preclude inhibitory involvement related specifically to stuttering events. Our findings indicate that people who stutter do not show behavioural or neural differences in response inhibition, when making simple manual responses and producing fluent speech, contrary to predictions from the global inhibition hypothesis.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330837/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839012","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":"Multi-echo versus single-echo EPI sequences for task-fMRI: A comparative study.","authors":"Alice Giubergia, Giulio Ferrazzi, Marco Castellaro, Sara Mascheretti, Valentina Lampis, Florian Montano, Alessandra Bertoldo, Denis Peruzzo","doi":"10.1162/IMAG.a.94","DOIUrl":"10.1162/IMAG.a.94","url":null,"abstract":"<p><p>Functional magnetic resonance imaging (fMRI) studies in cognitive and clinical neuroscience rely on blood oxygenation level-dependent (BOLD) contrast, measured with single-shot gradient-echo-planar imaging. However, conventional schemes encompass the acquisition of single-echo fMRI, which samples a single echo at a single-echo time (TE), facing limitations in disentangling neural signals from artifacts. Multi-echo (ME) fMRI captures images at multiple echo times within a single repetition time (TR) period and enables the separation of BOLD and non-BOLD signal components. Previous studies have highlighted the benefits of ME-fMRI but often relied on comparisons with suboptimal single-echo data derived from ME acquisitions, limiting the validity of these evaluations. This study performs a more rigorous comparison between three datasets: the data acquired with an optimized single-echo (OSE) fMRI sequence at the highest possible temporal resolution, those acquired with an ME-fMRI sequence, and, as previously reported in the literature, the echo-2 time-series extracted from the ME-fMRI data itself. ME-fMRI <i>vs.</i> echo-2 comparison confirmed previous findings, which advantage the ME approach. However, the acquisition of multi-echo fMRI did not clearly outperform an optimized single-echo scheme. While OSE-fMRI exhibits benefits in terms of higher statistical power, ME-fMRI demonstrates superior performance at the single-subject level in terms of reliability (p < 0.05). Additional investigation and optimization could clarify the conditions under which one sequence may be preferred over the other.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330833/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839116","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":"An embodied perspective: Angular gyrus and precuneus decode selfhood in memories of naturalistic events.","authors":"Heather M Iriye, Peggy L St Jacques","doi":"10.1162/IMAG.a.93","DOIUrl":"10.1162/IMAG.a.93","url":null,"abstract":"<p><p>While we often assume that memory encoding occurs from an in-body (first-person) perspective, out-of-body experiences demonstrate that we can form memories from a third-person perspective. This phenomenon provides a distinctive opportunity to examine the interaction between embodiment and visual perspective during encoding, and how this interplay shapes the recall of past events. Participants formed memories for naturalistic events following a manipulation of their sense of embodiment from in-body and out-of-body perspectives and recalled them during functional scanning. Region of interest multivariate analyses examined how the angular gyrus, precuneus, and hippocampus reflected visual perspective, embodiment, and their interaction during remembering. Patterns of activity during retrieval in the left angular gyrus and bilateral precuneus predicted embodiment on its own separated from visual perspective. In contrast, we observed only inconclusive evidence that these posterior parietal regions predicted visual perspective independent of embodiment. While the left angular gyrus distinguished between in-body and out-of-body perspectives during the retrieval of events associated with both strong and weak embodiment, decoding accuracy predicting visual perspective was only above chance for events encoded with strong embodiment in the precuneus bilaterally. Our results suggest that the contribution of posterior parietal regions in establishing visual perspectives within memories is tightly interconnected with embodiment. Encoding events from an embodied in-body perspective compared with embodied out-of-body perspective led to higher memory accuracy following repeated retrieval. These results elucidate how fundamental feelings of being located in and experiencing the world from our own body's perspective are integrated within memory.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330842/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839009","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":"Functional MRI reveals regional changes of brain activity in rats following longitudinal focal high-density theta burst stimulation (hdTBS).","authors":"Charlotte Qiong Li, Samantha Hoffman, Hieu Nguyen, Antonia Vrana, Aidan Carney, Ying Duan, Zilu Ma, Nanyin Zhang, Yihong Yang, Hanbing Lu","doi":"10.1162/IMAG.a.92","DOIUrl":"10.1162/IMAG.a.92","url":null,"abstract":"<p><p>The therapeutic benefits of transcranial magnetic stimulation (TMS) are believed to stem from neuroplasticity induced by repeated sessions. While animal models have contributed to our understanding of TMS-induced plasticity, there is a need for a rodent model that closely replicates the prolonged conditions experienced by humans. This study aimed to develop a rat model that reflects the spatial and temporal dynamics of human TMS protocols and to evaluate the carryover effects of TMS on the brain at a systems level. Experiments were carried out on two groups of rats (N = 33). In the first cohort, rats were implanted with microwire electrodes to record motor-evoked potential (MEP) signals and received daily sessions of high-density theta burst stimulation (hdTBS) for 5 days. Cortical excitability was assessed through input-output (I-O) curves before and after hdTBS (Day 0 and Day 6). To identify brain regions affected by the longitudinal TMS, the second cohort underwent identical TMS protocol and received fMRI scans on Days 0 and 6 to measure basal cerebral blood volume (CBV). Results reveal that daily hdTBS significantly shifted I-O curves upward in the TMS group (N = 9) compared to the sham group (N = 7), reflecting enhanced cortical excitability. Additionally, fMRI data showed elevated basal CBV in both the stimulation sites and in the connected networks (N = 8 for active TMS and N = 9 for sham), suggesting increased basal metabolism. This study opens a novel platform for further exploring the mechanisms underlying TMS-induced plasticity.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330834/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839018","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":"High-resolution quantitative T₂ mapping of the human brain at 7 T using a multi-echo spin-echo sequence and dictionary-based modeling.","authors":"Jochen Schmidt, Dvir Radunsky, Patrick Scheibe, Carsten Jäger, Noam Ben-Eliezer, Robert Trampel, Nikolaus Weiskopf","doi":"10.1162/IMAG.a.81","DOIUrl":"10.1162/IMAG.a.81","url":null,"abstract":"<p><p>Quantitative <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> mapping offers a unique contrast for detailed brain imaging. At ultra-high field strengths (7 T), the higher signal-to-noise ratio (SNR) enables higher spatial resolution and the delineation of smaller structures. The translation of multi-echo spin-echo-based acquisitions to higher field strength, however, is complicated by inhomogeneities in the radio frequency (RF) transmit field resulting in stronger stimulated echoes and multi-echo refocusing pathways. The <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> decay will thus depend on the specific sequence details and other experimental properties. The signal can be modeled by Bloch equation simulations to create a dictionary of possible signal patterns to fit the experimental data and estimate <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> . Particularly at smaller voxel sizes and shorter <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> times, noise will affect the dictionary matching of the data by the introduction of a bias in the acquired signal magnitude dependent on the SNR. This study aims to develop a robust, accurate, and fast <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> mapping approach at 7 T, addressing RF inhomogeneity and noise bias. We employed a 2D multi-echo spin-echo sequence combined with a Bloch equation simulation-aided dictionary matching technique. The method incorporated a pre-measured <math> <mrow><msubsup><mtext>B</mtext> <mn>1</mn> <mo>+</mo></msubsup> </mrow> </math> map for regularization of the dictionary fit and applied a patch-based PCA denoising algorithm with magnitude bias correction to mitigate noise-induced errors. The method was tested in simulations, phantom validations, and in five human participants. In vivo, <math> <mrow> <msup> <mrow><mrow><mo>(</mo> <mrow><mn>0.7</mn> <mo> </mo> <mi>m</mi> <mi>m</mi></mrow> <mo>)</mo></mrow> </mrow> <mn>3</mn></msup> </mrow> </math> isotropic high-resolution <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> maps showed detailed contrast within cortical and subcortical areas. Notably, regions with high iron content, such as the substantia nigra or nucleus ruber, were distinctly visible. The proposed method provided consistent <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> values across different brain regions that aligned well with the literature where available. Simulations and experiments demonstrated the importance of the noise correction to achieve high-quality maps. The proposed method can significantly contribute to studies on brain microstructure and pathology, since it produces reliable <math> <mrow><msub><mtext>T</mtext> <mn>2</mn></msub> </mrow> </math> maps at high resolution.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330843/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839073","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":"Linking microscopy to diffusion MRI with degenerate biophysical models: An application of the Bayesian EstimatioN of CHange (BENCH) framework.","authors":"Daniel Z L Kor, Hossein Rafipoor, Istvan N Huszar, Adele Smart, Greg Daubney, Saad Jbabdi, Michiel Cottaar, Karla L Miller, Amy F D Howard","doi":"10.1162/IMAG.a.85","DOIUrl":"10.1162/IMAG.a.85","url":null,"abstract":"<p><p>Biophysical modelling of diffusion MRI (dMRI) is used to non-invasively estimate microstructural features of tissue, particularly in the brain. However, meaningful description of tissue requires many unknown parameters, resulting in a model that is often ill-posed. The Bayesian EstimatioN of CHange (BENCH) framework was specifically designed to circumvent parameter fitting for ill-conditioned models when one is simply interested in interpreting signal changes related to some variable of interest. To understand the biological underpinning of some observed change in MR signal between different conditions, BENCH predicts which model parameter, or combination of parameters, best explains the observed change, without having to invert the model. BENCH has been previously used to identify which biophysical parameters could explain group-wise dMRI signal differences (e.g., patients vs. controls); here, we adapt BENCH to interpret dMRI signal changes related to continuous variables. We investigate how parameters from the dMRI standard model of white matter, with an additional sphere compartment to represent glial cell bodies, relate to tissue microstructure quantified from histology. We validate BENCH using synthetic dMRI data from numerical simulations. We then apply it to ex-vivo macaque brain data with dMRI and microscopy metrics of glial density, axonal density, and axonal dispersion in the same brain. We found that (i) increases in myelin density are primarily associated with an increased intra-axonal volume fraction and (ii) changes in the orientation dispersion derived from myelin microscopy are linked to variations in the orientation dispersion index. Finally, we found that the dMRI signal is sensitive to changes in glial cell load in the brain white matter, though no single parameter in the extended standard model was able to explain this observed signal change.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330835/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839031","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":"Increasing spectral DCM flexibility and speed by leveraging Julia's ModelingToolkit and automated differentiation.","authors":"David Hofmann, Anthony G Chesebro, Chris Rackauckas, Lilianne R Mujica-Parodi, Karl J Friston, Alan Edelman, Helmut H Strey","doi":"10.1162/IMAG.a.88","DOIUrl":"10.1162/IMAG.a.88","url":null,"abstract":"<p><p>Using neuroimaging and electrophysiological data to infer neural parameter estimations from theoretical circuits requires solving the inverse problem. Here, we provide a new Julia language package designed to i) compose complex dynamical models in a simple and modular way with ModelingToolkit.jl, ii) implement parameter fitting based on spectral dynamic causal modeling (sDCM) using the Laplace approximation, analogous to MATLAB implementation in SPM, and iii) leverage Julia's unique strengths to increase accuracy and speed by employing Automatic Differentiation during the fitting procedure. To illustrate the utility of our flexible modular approach, we provide a method to improve correction for fMRI scanner field strengths (1.5T, 3T, 7T) when fitting models to real data.</p>","PeriodicalId":73341,"journal":{"name":"Imaging neuroscience (Cambridge, Mass.)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12330849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144839099","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}