September 2024
Volume 24, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2024
Towards a detailed functional neuroanatomy of the ventral visual cortex
Author Affiliations & Notes
  • Josefine A. Zerbe
    Vision and Computational Cognition Group, Max Planck Institute of Human Cognitive and Brain Sciences
    equal contribution
  • Maggie Mae Mell
    Vision and Computational Cognition Group, Max Planck Institute of Human Cognitive and Brain Sciences
    equal contribution
  • Juliane Damm
    Department of Neurophysics, Max Planck Institute of Human Cognitive and Brain Sciences
  • Marianna Schmidt
    Department of Neurophysics, Max Planck Institute of Human Cognitive and Brain Sciences
  • Nikolaus Weiskopf
    Department of Neurophysics, Max Planck Institute of Human Cognitive and Brain Sciences
    Felix Bloch Institute for Solid State Physics, Leipzig University
  • Evgeniya Kirilina
    Department of Neurophysics, Max Planck Institute of Human Cognitive and Brain Sciences
  • Tomas Knapen
    Spinoza Centre for Neuroimaging
    Netherlands Institute for Neuroscience
    Experimental and Applied Psychology, Vrije Universiteit Amsterdam
    equal contribution
  • Martin N. Hebart
    Vision and Computational Cognition Group, Max Planck Institute of Human Cognitive and Brain Sciences
    Department of Medicine, Justus Liebig University Giessen
    equal contribution
  • Footnotes
    Acknowledgements  This work was supported by a Max Planck Research Group Grant and the ERC Starting Grant COREDIM awarded to MNH.
Journal of Vision September 2024, Vol.24, 931. doi:https://doi.org/10.1167/jov.24.10.931
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      Josefine A. Zerbe, Maggie Mae Mell, Juliane Damm, Marianna Schmidt, Nikolaus Weiskopf, Evgeniya Kirilina, Tomas Knapen, Martin N. Hebart; Towards a detailed functional neuroanatomy of the ventral visual cortex. Journal of Vision 2024;24(10):931. https://doi.org/10.1167/jov.24.10.931.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Previous research of human visual cortex has revealed functionally distinct and hierarchically organized processing pathways, each consisting of sequences of retinotopic maps. However, beyond early visual cortex the extent and even presence of these maps is not generally agreed upon. Specifically, it is unclear if variability in retinotopic structure reflects true idiosyncratic effects or noise in the retinotopic mapping data. Moreover, beyond the functional organization, the fine-grained structural connectome underlying human visual cortex is largely unknown and until recently had to be inferred indirectly from post-mortem studies. This has made it challenging to relate the macroscale structural organization of visual cortex to its functional topographic organization. To address these challenges, here we provide a densely-sampled dataset of 7 individuals, combining ultrahigh-resolution functional, structural, and diffusion data across 12 scanning sessions. We rigorously preselected individuals based on the reliability of an initial retinotopic mapping scan. Across 7 sessions of 7T MRI, we collected 192 minutes of retinotopy, as well as extensive object and motion-specific localizer and resting state data supplemented by multi-parameter mapping anatomy. Across three retinotopic mapping tasks, we (1) used moving bar apertures of varying width, (2) focused on the foveal representation (central 4 dva), and (3) focused on the periphery by moving the fixation cross to each corner of the screen. Across 5 additional sessions of 3T Connectom MRI, we further collected structural and diffusion data at 0.8mm isotropic resolution, allowing for a detailed mapping of short association fibers between adjacent brain regions. Data quality analyses of the functional data revealed minimal head motion and high noise ceilings, offering detailed, individually specific retinotopic maps. Paired with the densely sampled ultrahigh-resolution diffusion data, this dataset promises a highly detailed understanding of the functional neuroanatomy of the human visual system.

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