Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex
5 affiliations
- 1Department of Psychology, Justus Liebig University Giessen, Germany
- 2Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- 3Center for Mind, Brain and Behavior (CMBB), Universities of Marburg, Giessen, and Darmstadt, Germany
- 4Department of Medicine, Justus Liebig University Giessen, Germany
- 5Department of Mathematics and Computer Science, Physics, Geography, Justus Liebig University Giessen, Germany
Abstract
Two prominent accounts describe the functional organization of human high-level visual cortex. A categorical view emphasizes category-selective areas, while a dimensional view highlights continuous feature maps spanning these areas. Here, we asked whether these two views reflect complementary expressions of the same underlying organization. Using a data-driven decomposition of fMRI responses from human participants (female and male) in face-, body-, and scene-selective areas, we identified spatially overlapping activity patterns that were shared across individuals. Each area encoded multiple interpretable dimensions capturing both finer within-category and coarser between-category distinctions, even in the most category-selective voxels. These dimensions formed distinct clusters within category-selective areas but extended as distributed maps across visual cortex. Together, these findings reveal an underlying organization that links category-selective areas to continuous feature maps, thereby reconciling categorical and dimensional accounts of high-level visual cortex.
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BibTeX
@article{dyck2026multidimensional,
title = {{Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex}},
author = {Leonard Elia van Dyck and Martin N. Hebart and Katharina Dobs},
journal = {Journal of Neuroscience},
year = {2026},
month = jun,
doi = {10.1523/jneurosci.0038-26.2026},
url = {https://doi.org/10.1523/jneurosci.0038-26.2026},
note = {CC BY},
}
RIS
TY - JOUR
TI - Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex
AU - Leonard Elia van Dyck
AU - Martin N. Hebart
AU - Katharina Dobs
PY - 2026
DA - 2026/06/17
JO - Journal of Neuroscience
DO - 10.1523/jneurosci.0038-26.2026
UR - https://doi.org/10.1523/jneurosci.0038-26.2026
AB - Two prominent accounts describe the functional organization of human high-level visual cortex. A categorical view emphasizes category-selective areas, while a dimensional view highlights continuous feature maps spanning these areas. Here, we asked whether these two views reflect complementary expressions of the same underlying organization. Using a data-driven decomposition of fMRI responses from human participants (female and male) in face-, body-, and scene-selective areas, we identified spatially overlapping activity patterns that were shared across individuals. Each area encoded multiple interpretable dimensions capturing both finer within-category and coarser between-category distinctions, even in the most category-selective voxels. These dimensions formed distinct clusters within category-selective areas but extended as distributed maps across visual cortex. Together, these findings reveal an underlying organization that links category-selective areas to continuous feature maps, thereby reconciling categorical and dimensional accounts of high-level visual cortex.
SN - 0270-6474
SN - 1529-2401
ER -