Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T
IntroductionA full understanding of how we see our world remains a fundamental research question in vision neuroscience. While topographic profiling has allowed us to identify different visual areas, the exact functional characteristics and organization of areas up in the visual hierarchy (beyond V1...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2025.1537026/full |
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| author | Elisa Zamboni Elisa Zamboni Isaac Watson Isaac Watson Rüdiger Stirnberg Laurentius Huber Elia Formisano Rainer Goebel Aneurin J. Kennerley Antony B. Morland Antony B. Morland Antony B. Morland |
| author_facet | Elisa Zamboni Elisa Zamboni Isaac Watson Isaac Watson Rüdiger Stirnberg Laurentius Huber Elia Formisano Rainer Goebel Aneurin J. Kennerley Antony B. Morland Antony B. Morland Antony B. Morland |
| author_sort | Elisa Zamboni |
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| description | IntroductionA full understanding of how we see our world remains a fundamental research question in vision neuroscience. While topographic profiling has allowed us to identify different visual areas, the exact functional characteristics and organization of areas up in the visual hierarchy (beyond V1 & V2) is still debated. It is hypothesized that visual area V4 represents a vital intermediate stage of processing spatial and curvature information preceding object recognition. Advancements in magnetic resonance imaging hardware and acquisition techniques (e.g., non-BOLD functional MRI) now permits the capture of cortical layer-specific functional properties and organization of the human brain (including the visual system) at high precision.MethodsHere, we use functional cerebral blood volume measures to study the modularity in how responses to contours (curvature) are organized within area V4 of the human brain. To achieve this at 3 Tesla (a clinically relevant field strength) we utilize optimized high-resolution 3D-Echo Planar Imaging (EPI) Vascular Space Occupancy (VASO) measurements.ResultsData here provide the first evidence of curvature domains in human V4 that are consistent with previous findings from non-human primates. We show that VASO and BOLD tSNR maps for functional imaging align with high field equivalents, with robust time series of changes to visual stimuli measured across the visual cortex. V4 curvature preference maps for VASO show strong modular organization compared to BOLD imaging contrast. It is noted that BOLD has a much lower sensitivity (due to known venous vasculature weightings) and specificity to stimulus contrast. We show evidence that curvature domains persist across the cortical depth. The work advances our understanding of the role of mid-level area V4 in human processing of curvature and shape features.ImpactKnowledge of how the functional architecture and hierarchical integration of local contours (curvature) contribute to formation of shapes can inform computational models of object recognition. Techniques described here allow for quantification of individual differences in functional architecture of mid-level visual areas to help drive a better understanding of how changes in functional brain organization relate to difference in visual perception. |
| format | Article |
| id | doaj-art-96bf0d39d64d41f99cfe041d5677e9fb |
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| publishDate | 2025-02-01 |
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| spelling | doaj-art-96bf0d39d64d41f99cfe041d5677e9fb2025-08-20T02:03:36ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2025-02-011910.3389/fnins.2025.15370261537026Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3TElisa Zamboni0Elisa Zamboni1Isaac Watson2Isaac Watson3Rüdiger Stirnberg4Laurentius Huber5Elia Formisano6Rainer Goebel7Aneurin J. Kennerley8Antony B. Morland9Antony B. Morland10Antony B. Morland11School of Psychology, University of Nottingham, Nottingham, United KingdomYork Neuroimaging Centre, University of York, York, United KingdomYork Neuroimaging Centre, University of York, York, United KingdomBiomedical Imaging Science Department, Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United KingdomGerman Centre for Neurodegenerative Diseases, Bonn, GermanyNational Institutes of Health, Bethesda, MD, United StatesDepartment of Cognitive Neuroscience, Maastricht University, Maastricht, NetherlandsDepartment of Cognitive Neuroscience, Maastricht University, Maastricht, NetherlandsInstitute of Sport, Department of Sports and Exercise Sciences, Manchester Metropolitan University, Manchester, United KingdomYork Neuroimaging Centre, University of York, York, United KingdomDepartment of Psychology, University of York, York, United KingdomYork Biomedical Research Institute, University of York, York, United KingdomIntroductionA full understanding of how we see our world remains a fundamental research question in vision neuroscience. While topographic profiling has allowed us to identify different visual areas, the exact functional characteristics and organization of areas up in the visual hierarchy (beyond V1 & V2) is still debated. It is hypothesized that visual area V4 represents a vital intermediate stage of processing spatial and curvature information preceding object recognition. Advancements in magnetic resonance imaging hardware and acquisition techniques (e.g., non-BOLD functional MRI) now permits the capture of cortical layer-specific functional properties and organization of the human brain (including the visual system) at high precision.MethodsHere, we use functional cerebral blood volume measures to study the modularity in how responses to contours (curvature) are organized within area V4 of the human brain. To achieve this at 3 Tesla (a clinically relevant field strength) we utilize optimized high-resolution 3D-Echo Planar Imaging (EPI) Vascular Space Occupancy (VASO) measurements.ResultsData here provide the first evidence of curvature domains in human V4 that are consistent with previous findings from non-human primates. We show that VASO and BOLD tSNR maps for functional imaging align with high field equivalents, with robust time series of changes to visual stimuli measured across the visual cortex. V4 curvature preference maps for VASO show strong modular organization compared to BOLD imaging contrast. It is noted that BOLD has a much lower sensitivity (due to known venous vasculature weightings) and specificity to stimulus contrast. We show evidence that curvature domains persist across the cortical depth. The work advances our understanding of the role of mid-level area V4 in human processing of curvature and shape features.ImpactKnowledge of how the functional architecture and hierarchical integration of local contours (curvature) contribute to formation of shapes can inform computational models of object recognition. Techniques described here allow for quantification of individual differences in functional architecture of mid-level visual areas to help drive a better understanding of how changes in functional brain organization relate to difference in visual perception.https://www.frontiersin.org/articles/10.3389/fnins.2025.1537026/fullfMRIlaminarlayersVASOvisual featurescurvature |
| spellingShingle | Elisa Zamboni Elisa Zamboni Isaac Watson Isaac Watson Rüdiger Stirnberg Laurentius Huber Elia Formisano Rainer Goebel Aneurin J. Kennerley Antony B. Morland Antony B. Morland Antony B. Morland Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T Frontiers in Neuroscience fMRI laminar layers VASO visual features curvature |
| title | Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T |
| title_full | Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T |
| title_fullStr | Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T |
| title_full_unstemmed | Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T |
| title_short | Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T |
| title_sort | mapping curvature domains in human v4 using cbv sensitive layer fmri at 3t |
| topic | fMRI laminar layers VASO visual features curvature |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2025.1537026/full |
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