October 2020
Volume 20, Issue 11
Open Access
Vision Sciences Society Annual Meeting Abstract  |   October 2020
White matter anatomy and cortical microstructure predict reading-related responses in ventral temporal cortex
Author Affiliations & Notes
  • Mareike Grotheer
    Psychology Department, Stanford University
  • Jason Yeatman*
    Graduate School of Education, Stanford University
    Division of Developmental and Behavioral Pediatrics, Stanford University, *Authors contributed equally
  • Kalanit Grill-Spector*
    Psychology Department, Stanford University
  • Footnotes
    Acknowledgements  This research was supported by the National Institute of Health (NIH; R01EY023915, R01MH121868 and R01HD09586101)
Journal of Vision October 2020, Vol.20, 201. doi:https://doi.org/10.1167/jov.20.11.201
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      Mareike Grotheer, Jason Yeatman*, Kalanit Grill-Spector*; White matter anatomy and cortical microstructure predict reading-related responses in ventral temporal cortex. Journal of Vision 2020;20(11):201. https://doi.org/10.1167/jov.20.11.201.

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

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Abstract

Reading-related responses in the ventral temporal cortex (VTC) show a consistent spatial layout across individuals, which is puzzling, since reading skills are typically acquired during childhood. Moreover, while peak responses generally fall within the occipito-temporal sulcus (OTS), the precise location within this sulcus can vary. Here, we tested the hypothesis that specific white matter fascicles and microstructural properties of the gray matter constrain where reading-related responses emerge in VTC in a given individual. Thus, we obtained functional (fMRI), diffusion (dMRI), and quantitative (qMRI) magnetic resonance imaging data in 30 adults. fMRI was used to map reading-related responses by contrasting responses in a reading task with those in an adding and a color task performed on the same visual stimuli (Grotheer et al., 2018, 2019); qMRI was used to measure proton relaxation time (T1), which is dependent on tissue microstructure; dMRI was used to automatically identify the 6 fascicles that connect to VTC and to map their endpoints density (ED) on the cortical surface. Within VTC, ED and T1 were then used to predict reading-related responses. First, linear regression with leave-one-subject-out cross-validation in a subset of participants (N=10), showed that ED of the arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), and vertical occipital fasciculus (VOF) significantly predict reading-related responses. Adding gray-matter T1 to a model that combines AF, ILF and VOF endpoints significantly improved the model. Finally, evaluation of the full structural model in the remaining participants with leave-one-subject-out cross-validation showed that this model i) significantly predicts the topology of reading-related responses across VTC and ii) predicts the location of reading-related regions of interest known as the visual word form areas. Overall, our data-driven approach reveals that the AF, ILF, VOF and T1 predict responses in VTC, suggesting that these structural features of the brain constrain the location of reading-related responses.

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