Serriere, L. | Search bioRxiv

bioRxiv2026

Grasping at the organization of object knowledge: testing different object-related dimensions as organizational principles of ventral temporal cortex.

In our daily lives we encounter a myriad of things with which we might need to interact as we navigate our environment. Mental representations of these things must be computed and stored in our brains to be manipulated to support cognition. How are such representations organized in the brain? Several proposals have been put forth on what the principles of organization of object information in the brain might be: within ventral temporal cortex - regions thought to support object recognition - possible dimensions include the animacy status of target stimuli, their real size, their texture and material properties, and potentially their graspable status, amongst others. Here we used functional magnetic resonance imaging (fMRI) and multivariate approaches to discriminate patterns of activation for different categories of objects to test the role of these dimensions as organizing principles of object information in the brain. We show that pattern discriminability between different categories of objects does not seem to follow differences in their animacy status in any continuous way. Moreover, graspability of the target stimuli and their haptic texture properties are better predictors of representational content within ventral temporal cortex than animacy and real size. These results are in line with recent studies demonstrating the importance of computational contingencies superimposed by bi-directional functional coupling between parietal regions dedicated to the processing of object manipulation and grasping and ventral temporal regions responsible for object recognition, potentially involving material and texture processing.

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bioRxiv2025

Human and generative AI integrate visual cues differently in a shape completion task

In amodal completion observers perceive complete objects despite partial occlusion. When two object parts are divided by an occluder, completion can result in perceiving one or two objects. This phenomenon involves both lower-level cues (e.g., symmetry, contour continuity) and higher-level cues (e.g., prior knowledge). Experiment 1 investigates how occluder size, familiarity, and symmetry affect human completions using a drawing task. Narrow occluders and asymmetry promote single-shape completions, while familiarity and (global) symmetry promote two-shape interpretations. Good continuation emerges as the strongest cue, with symmetry and familiarity playing increasingly important roles as occluder width increases. Experiment 2 compares human performance with three state-of-the-art generative AI models. Models often generated creative but non-compliant outputs, altering even unoccluded regions. We restricted analysis to instruction-following generations, identified through ratings by naive observers. Among compliant outputs, models showed some human-like biases (e.g., more two-shape completions for wide occluders), but failed with higher-level cues. They did not use symmetry to guide completions and showed reversed familiarity effects. Our findings highlight differences between human and AI completions. Humans integrate low- and high-level cues, whereas compliant outputs from the AI models rely primarily on low-level pattern continuation. Current AI models lack the flexible integration of multiple representational levels that characterize human perception. This work establishes an analytical framework for evaluating whether next-generation models achieve more human-like visual reasoning. HighlightsO_LIHumans see one or two objects behind occluders using geometric and semantic cues. C_LIO_LIHuman drawings and generative AI completions show how different cues modulate perception C_LIO_LIGood continuation dominates human and AI shape completions C_LIO_LISymmetry and familiarity guide humans, but not instruction-following AI outputs C_LIO_LIHumans integrate multiple levels; instruction-following AI engages lower-level-processing. C_LI

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