Using eye-tracking to parse object recognition: Priming activates primarily a parts-based but also a late-emerging features-based representation

Autor: Sarah Olsen, Peter Gerhardstein
Rok vydání: 2020
Předmět:
Zdroj: Attention, perceptionpsychophysics. 82(6)
ISSN: 1943-393X
Popis: Biederman and Cooper (Cognitive Psychology, 23, 393-419, 1991), using parts-deleted and features-deleted stimuli, presented evidence that object priming occurs at the level of the objects’ parts, but not features. A control condition confirmed that some priming was accrued by the (non-visual) object concept that the stimulus represented, but all visual-level priming appeared to be at the more global level of the parts of objects, rather than the local level of the individual features (edges, vertices). This outcome has long been viewed as an important piece of supporting evidence for the existence of structural descriptions (e.g., Biederman, Psychological Review, 94, 115, 1987). The original report used a naming response task, and concluded that stimuli presenting half of the parts of an object primed only those parts, whereas half-features-deleted stimuli primed both themselves and the “complementary” half, containing the features deleted from the first image, equally. The current study adapts an eye-tracking approach to enable examination of the time course of priming across an exposure to both the primed image and unprimed competitors. Parts-deleted images primed themselves quickly and exclusively, replicating the finding of Biederman and Cooper (1991). Features-deleted images showed a deviation across time, however; initially a features-deleted prime attracted looking to itself and to its complement equally, but later on, looking to the target deviated upward, demonstrating an ability to distinguish between the two versions. The outcome of the present tests provide support for the primacy of a structural parts description, while also demonstrating the existence of multiple types of representations, both global and local.
Databáze: OpenAIRE