Spencer R Loggia, Stuart J Duffield, Kurt Braunlich, Bevil R Conway
{"title":"Color and Spatial Frequency Provide Functional Signatures of Retinotopic Visual Areas.","authors":"Spencer R Loggia, Stuart J Duffield, Kurt Braunlich, Bevil R Conway","doi":"10.1523/JNEUROSCI.1673-23.2024","DOIUrl":null,"url":null,"abstract":"<p><p>Primate vision relies on retinotopically organized cortical parcels defined by representations of hemifield (upper versus lower visual field), eccentricity (fovea versus periphery), and area (V1, V2, V3, V4). Here we test for functional signatures of these organizing principles. We used fMRI to measure responses to gratings varying in spatial frequency, color, and saturation across retinotopically defined parcels in two macaque monkeys, and we developed a Sparse Supervised Embedding (SSE) analysis to identify stimulus features that best distinguish cortical parcels from each other. Constraining the SSE model to distinguish just eccentricity representations of the voxels revealed the expected variation of spatial frequency and S-cone modulation with eccentricity. Constraining the model according to the dorsal-ventral location and retinotopic area of each voxel provided unexpected functional signatures, which we investigated further with standard univariate analyses. Posterior parcels (V1) were distinguished from anterior parcels (V4) by differential responses to chromatic and luminance contrast, especially of low spatial frequency gratings. Meanwhile, ventral parcels were distinguished from dorsal parcels by differential responses to chromatic and luminance contrast, especially of colors that modulate all three cone types. The dorsal-ventral asymmetry not only resembled differences between candidate dorsal and ventral subdivisions of human V4, but also extended to include all retinotopic visual areas, starting in V1 and increasing from V1 to V4. The results provide insight into the functional roles of different retinotopic areas and demonstrate the utility of Sparse Supervised Embedding as a data-driven tool for generating hypotheses about cortical function and behavior.<b>Significance Statement</b> This study demonstrates a new analysis, Sparse Supervised Embedding (SSE), which promises to be useful for visualizing and understanding complex neuroimaging datasets. The paper uses SSE to explore the functional roles of retinotopic visual areas (V1, V2, V3, V4, V3a, MT). The results show that retinotopic areas parcellated by representations for eccentricity and upper/lower visual hemifield have functional signatures, which are defined by unique combinations of responses to color, spatial frequency, and contrast. The functional signatures provide hypotheses for the different roles that the parcels play in vision and help resolve apparent differences between human and macaque visual cortex organization.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1523/JNEUROSCI.1673-23.2024","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Primate vision relies on retinotopically organized cortical parcels defined by representations of hemifield (upper versus lower visual field), eccentricity (fovea versus periphery), and area (V1, V2, V3, V4). Here we test for functional signatures of these organizing principles. We used fMRI to measure responses to gratings varying in spatial frequency, color, and saturation across retinotopically defined parcels in two macaque monkeys, and we developed a Sparse Supervised Embedding (SSE) analysis to identify stimulus features that best distinguish cortical parcels from each other. Constraining the SSE model to distinguish just eccentricity representations of the voxels revealed the expected variation of spatial frequency and S-cone modulation with eccentricity. Constraining the model according to the dorsal-ventral location and retinotopic area of each voxel provided unexpected functional signatures, which we investigated further with standard univariate analyses. Posterior parcels (V1) were distinguished from anterior parcels (V4) by differential responses to chromatic and luminance contrast, especially of low spatial frequency gratings. Meanwhile, ventral parcels were distinguished from dorsal parcels by differential responses to chromatic and luminance contrast, especially of colors that modulate all three cone types. The dorsal-ventral asymmetry not only resembled differences between candidate dorsal and ventral subdivisions of human V4, but also extended to include all retinotopic visual areas, starting in V1 and increasing from V1 to V4. The results provide insight into the functional roles of different retinotopic areas and demonstrate the utility of Sparse Supervised Embedding as a data-driven tool for generating hypotheses about cortical function and behavior.Significance Statement This study demonstrates a new analysis, Sparse Supervised Embedding (SSE), which promises to be useful for visualizing and understanding complex neuroimaging datasets. The paper uses SSE to explore the functional roles of retinotopic visual areas (V1, V2, V3, V4, V3a, MT). The results show that retinotopic areas parcellated by representations for eccentricity and upper/lower visual hemifield have functional signatures, which are defined by unique combinations of responses to color, spatial frequency, and contrast. The functional signatures provide hypotheses for the different roles that the parcels play in vision and help resolve apparent differences between human and macaque visual cortex organization.
期刊介绍:
JNeurosci (ISSN 0270-6474) is an official journal of the Society for Neuroscience. It is published weekly by the Society, fifty weeks a year, one volume a year. JNeurosci publishes papers on a broad range of topics of general interest to those working on the nervous system. Authors now have an Open Choice option for their published articles