Population receptive field size does not correspond to spatial frequency processing in scene-selective cortex
Humans are experts at scene perception, for example, for recognizing familiar places or navigating new spaces. Scene representations in the brain are often thought of as global or large-scale, suggesting that scenes are represented by coarse-grained or holistic features. Recent work has shown that high spatial frequency or fine-grained visual information is also represented within scene-selective areas, which challenges the idea of strictly low-frequency, gist-like representations in those regions. Here, we explore whether these contrasting views can be explained by the size of the population receptive fields (pRFs) within two scene-selective areas: the parahippocampal place area (PPA) and occipital place area (OPA). Our results show that both the PPA and the OPA contain voxels with a variety of receptive field sizes, which follow a gradient from large to small along the anterior-posterior axis. This organization would predict scene representations in anterior PPA/OPA to be dominated by low spatial frequencies and scene representations in posterior PPA/OPA by high spatial frequencies. We find the opposite pattern when decoding scene categories of spatial frequency-filtered images. Our results indicate that preferred scene feature representations are transformed along the visual hierarchy, adhering closely to the expected correspondence between spatial frequency preferences and pRF size in early visual areas, but demonstrably less so in high-level visual brain regions.
Authors
- Claudia Damiano (ORCID: https://orcid.org/0000-0003-0574-3068)
- Charlotte Leferink
- Dirk Walther (ORCID: https://orcid.org/0000-0002-5509-8899)
Institutions
- Dartmouth College (US)
- University of Toronto (CA)
Publication Details
- Journal
- Imaging Neuroscience
- Published
- 2026-01-01
- DOI
- https://doi.org/10.1162/imag.a.1111
- Primary Topic
- Face Recognition and Perception
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- McDonnell Center for Systems Neuroscience