Real-world object size is a fundamental dimension of visual cognition, supporting effective interaction with the environment and object manipulation. However, neural mechanisms underlying size representation have largely been inferred from extreme size comparisons, leaving the neural representation of subtle size differences within a manipulable, “hand-scale” range poorly understood. Here, we applied a three-dimensional deep neural network (3D DNN) to decode real-world size from whole-brain fMRI data (N = 50) using objects that all fell within a graspable range.
The 3D DNN successfully decoded subtle size differences, achieving predictive accuracies comparable to those obtained with multivariate pattern analysis. Importantly, Guided Gradient-weighted Class Activation Mapping (Guided Grad-CAM) revealed that voxel patterns contributing to the classifier’s small- versus large-object predictions were not confined to the ventral occipito-temporal cortex but extended to distributed regions. Notably, these regions spatially overlapped with the specific brain areas previously implicated in size-perception distortions following brain damage.
Our findings suggest that the subtle variations in object size may be represented through a non-linear, distributed network that extends beyond the traditional visual hierarchy. Specifically, this system may support the integration of visual properties with semantic scaling and the multimodal convergence of vision, space, and memory. We would like to thank Ms.
Maoko Yamanaka for her administrative assistance. This study was supported by KAKENHI from Japan Society for the Promotion of Science (20H00521, 21K18267 and 26K03285 to M.T.), Adaptable and Seamless Technology Transfer Program through Target-driven R&D (A-STEP) from Japan Science and Technology Agency (JST) Grant Number JPMJTR25UE to M.T., a grant from Takeda Science Foundation to M.T., and a grant from Uehara Memorial Foundation to M.T. Graduate School of Engineering, Kochi University of Technology, Kami, Kochi, 782-8502, Japan Narrative Nights, Inc, Yokohama, Kanagawa, 236-0011, Japan Research Center for Brain Communication, Kochi University of Technology, Kami, Kochi, 782-8502, Japan The authors declare no competing interests.
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