You won’t believe what this guy is doing with the potato: The ObjAct stimulus-set depicting human actions on congruent and incongruent objects

Abstract

Perception famously involves both bottom-up and top-down processes. The latter are influenced by our previous knowledge and expectations about the world. In recent years, many studies have focused on the role of expectations in perception in general, and in object processing in particular. Yet studying this question is not an easy feat, requiring—among other things—the creation and validation of appropriate stimuli. Here, we introduce the ObjAct stimulus-set of free-to-use, highly controlled real-life scenes, on which critical objects are pasted. All scenes depict human agents performing an action with an object that is either congruent or incongruent with the action. The focus on human actions yields highly constraining contexts, strengthening congruency effects. The stimuli were analyzed for low-level properties, using the SHINE toolbox to control for luminance and contrast, and using a deep convolutional neural network to mimic V1 processing and potentially discover other low-level factors that might differ between congruent and incongruent scenes. Two online validation studies (N = 500) were also conducted to assess the congruency manipulation and collect additional ratings of our images (e.g., arousal, likeability, visual complexity). We also provide full descriptions of the online sources from which all images were taken, as well as verbal descriptions of their content. Taken together, this extensive validation and characterization procedure makes the ObjAct stimulus-set highly informative and easy to use for future researchers in multiple fields, from object and scene processing, through top-down contextual effects, to the study of actions.

How much can we differentiate at a brief glance: revealing the truer limit in conscious contents through the massive report paradigm (MRP)

“…In Experiment 1, all 15 participants viewed the same 82 pairs of congruent and incongruent images. In Experiment 2, we used 139 pairs of images developed by Shir et al [17]. To calculate the viewing size of images for each participant, we used the data from the calibration.…”

“…In this paper, we use a set of natural images, which are modified in terms of an object in the scene [ 17 ]. In half of the trials, a critical object is congruent with the global scene semantic (or gist) while in the rest of the trials, it is replaced with another object that is incongruent with the gist.…”

Perception of semantic relations in scenes: a registered report study of attention hold

“…Two sets of stimuli were used. First one is a subset of 50 pairs of scenes from the set developed by Mudrik et al (2010) and recently validated by Shir et al (2021). In each pair a congruent version of a scene presents a person performing an action with an object that is highly probable in a given context (e.g., a man playing a violin), whereas in the incongruent version the key object has a very low probability of occurring in a given context (e.g., a man "playing" a broomstick).…”

“…To provide conclusive evidence, either in favour or against the automatic attention capture by incongruent objects, the study was designed in the following way. First, we employed a set of congruent and incongruent scene images, which had been validated in several previous studies (Mudrik et al 2010(Mudrik et al , 2011(Mudrik et al , 2014Mack et al, 2017;Biderman and Mudrik 2018;Moors et al, 2018;Faivre et al 2019;Shir et al, 2021). Second, we employed a well-established methodology, based on the dot-probe task and the N2pc ERP component analysis, which had been used to investigate attention capture by threatening real-world scenes (Kappenman et al, 2014(Kappenman et al, , 2015.…”

“…First, we used the stimuli developed by Mudrik et al (2010), which allowed comparing results of the present study to previous work of our and other groups using the same stimuli set (e.g. Mudrik et al 2011Mudrik et al , 2014Mack et al, 2017;Biderman and Mudrik 2018;Moors et al, 2018;Faivre et al 2019;Bola et al, 2021;Shir et al, 2021). Second, we employed a procedure developed specifically to investigate automatic hold of spatial attention by real-world scene images (van Hooff et al, 2013(van Hooff et al, , 2014.…”