The scene and the unseen: Manipulating photographs for experiments on change blindness and scene memory

Abstract

The change blindness paradigm, in which participants often fail to notice substantial changes in a scene, is a popular tool for studying scene perception, visual memory, and the link between awareness and attention. Some of the most striking and popular examples of change blindness have been demonstrated with digital photographs of natural scenes; in most studies, however, much simpler displays, such as abstract stimuli or "free-floating" objects, are typically used. Although simple displays have undeniable advantages, natural scenes remain a very useful and attractive stimulus for change blindness research. To assist researchers interested in using natural-scene stimuli in change blindness experiments, we provide here a step-by-step tutorial on how to produce changes in natural-scene images with a freely available image-processing tool (GIMP). We explain how changes in a scene can be made by deleting objects or relocating them within the scene or by changing the color of an object, in just a few simple steps. We also explain how the physical properties of such changes can be analyzed using GIMP and MATLAB (a high-level scientific programming tool). Finally, we present an experiment confirming that scenes manipulated according to our guidelines are effective in inducing change blindness and demonstrating the relationship between change blindness and the physical properties of the change and inter-individual differences in performance measures. We expect that this tutorial will be useful for researchers interested in studying the mechanisms of change blindness, attention, or visual memory using natural scenes.

Phasic and sustained interactions of multisensory interplay and temporal expectation

“…traffic, when suprathreshold stimuli can be easily missed (as shown by e.g. change blindness experiments 3 – 5 ). To summarize, while physical effectiveness can determine MSF in simple paradigms, internal and physical effectiveness might determine MSF in more complex paradigms.…”

“…To test which factors optimally predict the label of MSF for each participant (hypotheses 4–5), we conducted a modelling analysis. To this end, we modelled our data on the basis of a generalized linear regression using the glmfit function in Matlab 3 . Analyses were run separately for dʹ and RT scores.…”

Food-pics: an image database for experimental research on eating and appetite

“…However, effects of such image features on visual perception and stimulus-evoked neuronal responses are well known. Consequently, it is recommended to carefully control the physical properties of visual stimulus material (Knebel et al, 2008; Willenbockel et al, 2010; Kovalenko et al, 2012; Ball et al, 2013). For example, the role of image complexity and spatial frequencies for neural responses are heavily debated in the field of face processing (Vuilleumier et al, 2003; Thierry et al, 2007; Rossion and Jacques, 2008) and are increasingly considered during affective picture viewing (Bradley et al, 2007; Delplanque et al, 2007; Wiens et al, 2011).…”

Change detection on a hunch: Pre-attentive vision allows “sensing” of unique feature changes

“…However, this intuition has been challenged by results obtained with the "change blindness" paradigm (see Rensink, 2002;Simons & Rensink, 2005, for reviews). This line of research has demonstrated that observers are surprisingly poor at detecting substantial changes in a scene if the change occurs simultaneously with a brief visual disruption, be it a saccade (McConkie & Currie, 1996;Hayhoe et al, 1998), an eye blink (O'Regan et al, 2000), a flicker (Ball et al, 2013;Rensink et al, 1997), or a distracting stimulus (O'Regan et al, 1999). Under these conditions, change detection cannot be based on detecting a motion or contrast transient, but depends on encoding, preserving, and comparing object representations of pre-change and post-change objects.…”