Determinants of visual ambiguity resolution

Abstract Visual inputs during natural perception are highly ambiguous: objects are frequently occluded, lighting conditions vary, and object identification depends significantly on prior experiences. However, why do certain images remain unidentifiable while others can be recognized immediately, and what visual features drive subjective clarification? To address these critical questions, we developed a unique dataset of 1,854 ambiguous images and collected more than 100,000 ratings (from a total of 947 participants) evaluating their identifiability before and after seeing undistorted versions of the images. Relating the representations of a brain-inspired neural network model in response to our images with human ratings, we show that subjective identification depends largely on the extent to which higher-level visual features from the original images are preserved in their ambiguous counterparts. In line with these results, an image-level regression analysis showed that the subjective identification of ambiguous images was best explained by high-level visual dimensions. Notably, the predominance of higher-level features over lower-level ones softens after participants disambiguate the images, suggesting that the visual system flexibly shifts between top-down guessing to bottom-up matching after disambiguation. Moreover, we found that the process of ambiguity resolution was accompanied by a notable decrease in semantic distance and a greater consistency in object naming among participants. However, the relationship between information gained after disambiguation and subjective identification was non-linear, indicating that acquiring more information does not necessarily enhance subjective clarity. Instead, we observed a U-shaped relationship, suggesting that subjective identification improves when the acquired information either strongly matches or mismatches prior predictions. Collectively, these findings advance our understanding on how we resolve ambiguity and extract meaning from incomplete visual information. Competing Interest Statement The authors have declared no competing interest. Footnotes This revised version of the manuscript includes clarifications, methodological refinements, and additional control analyses to improve transparency and interpretation while leaving the main conclusions unchanged. The theoretical framing has been refined to more clearly articulate the predicted shift between higher level and lower level visual features during ambiguity resolution. The Methods section has been expanded to improve reproducibility. We provide additional details on participant recruitment and exclusions, stimulus generation and preprocessing steps for semantic distance and semantic entropy. Statistical reporting has been improved throughout the manuscript. Effect sizes, confidence intervals, and exact statistical values are now reported consistently, and the description of the regression models and noise ceiling estimation has been clarified. We added control analyses testing whether image memorability or category frequency could account for the observed effects on subjective identification and semantic distance. These analyses indicate that neither factor explains the main results. Overall, these revisions improve the clarity and robustness of the manuscript without altering its findings.