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Perceiving object size in pictures involves high-level processing

2025/05/01 by Ecem Altan, Hüseyin Boyacı, Steven C. Dakin +1 · 1 voice · 3 citations
Neuroscience · Psychology · #Artificial intelligence #Biology #Cognitive psychology #Communication #Computer science #Computer vision #Depth perception #Face Recognition and Perception #Illusion #Inversion (geology) #Neural dynamics and brain function #Neuroscience #Optical illusion #Perception #Psychology #Visual cortex #Visual perception #Visual perception and processing mechanisms #Visual processing

paper · doi:10.1098/rspb.2024.2967

published in Proceedings of the Royal Society B Biological Sciences 292(2046), 20242967 (Royal Society)

openalex publication_date 2025/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Spatial context is critical for telling how big a visual object is, although it may also cause the perceived size to diverge dramatically from the true dimensions. Interestingly, responses in the primary visual cortex (V1) mirror such illusory perception; however, the stage of processing that leads to such neural correlates remains unknown. Here, we tested the involvement of higher level processing in a Ponzo-like illusion, by quantifying the effect of manipulating depth cues and inversion of the whole scene. We report a stronger illusion for realistic compared with simpler backgrounds, and for upright compared with inverted scenes (except for scenes where the target objects appeared on the ceiling or in the sky). Next, using functional MRI, we tested the effect of inversion on V1 responses. Inverted scenes elicited a smaller extent of activation in V1 compared with upright scenes, consistent with their perceived sizes. Taken together, since the inversion should disrupt the high-level processing while keeping the low-level features intact, our findings demonstrate that Ponzo-like illusions involve high-level processes that integrate contextual depth cues and visual experience, thereby modulating the object's neural representation in V1.

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