Abstract
Previous research has uncovered a large-scale organization of object categories in occipitotemporal cortex by the dimensions of animacy and real-world size (Konkle & Caramazza, 2013). The tripartite division of cortical zones with a preference for large objects, all animals, and small objects has been robustly replicated and appears to be driven by the mid-level visual feature curvature, i.e. large objects tend to be boxier, and small objects and animals curvier (Long et al., 2017). However, given the factorial design in the original studies, it has remained open to what degree these findings generalize to larger stimulus sets. To address this question, we used THINGS-fMRI, a large-scale dataset comprising fMRI responses to 8,740 naturalistic images of 720 animate and inanimate object categories (Contier et al., 2021). We then collected and applied a rich behavioral dataset of perceived animacy, real-world size, and image-wise curvature ratings (Stoinski et al., 2022). Our results replicate many facets of the characteristic animacy-size organization, such as alternating patterns of animate-to-inanimate and large-to-small gradients, respectively. However, beyond these previous findings, we found additional, bilateral clusters in-between FFA and PPA that responded preferentially to small objects. In addition, our results showed pronounced size gradients within animate selective regions of the right hemisphere. These results were replicated across all three subjects and could not be explained by the broader size range and diversity of our categories. Instead, other factors, such as naturalistic image background or object eccentricity, may contribute to the stronger alternation of large-small preferences. Finally, contrary to the view that high-level animacy and size distinctions are driven strongly by curvature information, curvature explained only limited portions of observed animacy and size selectivity while the overall pattern of results remained the same. Together, our results add important facets to the understanding of the large-scale functional organization of occipitotemporal cortex.