Reciprocal semantic predictions drive categorization of scene contexts and objects even when they are separate

Abstract

AbstractVisual categorization improves when object-context associations in scenes are semantically consistent, thus predictable from schemas stored in long-term memory. However, it is unclear whether this is due to differences in early perceptual processing, in matching of memory representations or in later stages of response selection. We tested these three concurrent explanations across five experiments. At each trial, participants had to categorize a scene context and an object briefly presented within the same image (Experiment 1), or separately in simultaneous images (Experiments 2–5). We analyzed unilateral (Experiments 1, 3) and bilateral presentations (Experiments 2, 4, 5), and presentations on the screen’s horizontal midline (Experiments 1–2) and in the upper and lower visual fields (Experiments 3, 4). In all the experiments, we found a semantic consistency advantage for both context categorization and object categorization. This shows that the memory for object-context semantic associations is activated regardless of whether these two scene components are integrated in the same percept. Our study suggests that the facilitation effect of semantic consistency on categorization occurs at the stage of matching the percept with previous knowledge, supporting the object selection account and extending this framework to an object-context reciprocal influence on matching processes (object-context selection account).