The Visual Integration of Semantic and Spatial Information of Objects in Naturalistic Scenes (VISIONS) database: attentional, conceptual, and perceptual norms.

Abstract

The complex interplay between low- and high-level mechanisms governing our visual system can only be fully understood within ecologically valid naturalistic contexts. For this reason, in recent years, substantial efforts have been devoted to equipping the scientific community with datasets of realistic images normed on semantic or spatial features. Here, we introduce VISIONS, an extensive database of 1136 naturalistic scenes normed on a wide range of perceptual and conceptual norms by 185 English speakers across three levels of granularity: isolated object, whole scene, and object-in-scene. Each naturalistic scene contains a critical object systematically manipulated and normed regarding its semantic consistency (e.g., a toothbrush vs. a flashlight in a bathroom) and spatial position (i.e., left, right). Normative data are also available for low- (i.e., clarity, visual complexity) and high-level (i.e., name agreement, confidence, familiarity, prototypicality, manipulability) features of the critical object and its embedding scene context. Eye-tracking data during a free-viewing task further confirms the experimental validity of our manipulations while theoretically demonstrating that object semantics is acquired in extra-foveal vision and used to guide early overt attention. To our knowledge, VISIONS is the first database exhaustively covering norms about integrating objects in scenes and providing several perceptual and conceptual norms of the two as independently taken. We expect VISIONS to become an invaluable image dataset to examine and answer timely questions above and beyond vision science, where a diversity of perceptual, attentive, mnemonic, or linguistic processes could be explored as they develop, age, or become neuropathological.