Visualising mental representations: A primer on noise-based reverse correlation in social psychology

Abstract

With the introduction of the psychophysical method of reverse correlation, a holy grail of social psychology appears to be within reach -visualising mental representations. Reverse correlation is a data-driven method that yields visual proxies of mental representations, based on judgements of randomly varying stimuli. This review is a primer to an influential reverse correlation approach in which stimuli vary by applying random noise to the pixels of images. Our review suggests that the technique is an invaluable tool in the investigation of social perception (e.g., in the perception of race, gender and personality traits), with ample potential applications. However, it is unclear how these visual proxies are best interpreted. Building on advances in cognitive neuroscience, we suggest that these proxies are visual reflections of the internal representations that determine how social stimuli are perceived. In addition, we provide a tutorial on how to perform reverse correlation experiments using R.

Dominance and competence face to face: Dissociations obtained with a reverse correlation approach

“…Reverse correlation methods have proven their usefulness in social perception research as a data-driven tool to probe a perceiver's a priori expectations (or internal representations) about their social world (for a review see Brinkman, Todorov, & Dotsch, 2017;Jack & Schyns, 2017). These methods allow the identification of face configurations that are diagnostic of specific social judgments.…”

Facial Features Underlying the Decoding of Pain Expressions

“…as displaying an expression of pain). Thus, following a minimum of 300 trials [6] in which patches of noise are created randomly and added to a base face, it is possible to infer what visual properties of the noise fit with the mental representation of a stimulus category (e.g. a facial expression of pain).…”

Simply insane? Attributing terrorism to mental illness (versus ideology) affects mental representations of race Word

“…1 Classification images were created by averaging the noise of the faces chosen by all participants within the different conditions and applying it to the base image using the rcicr script (Dotsch, 2016). This procedure has been validated within various domains of face perception (see, e.g., Brinkman et al, 2017;Dotsch & Todorov, 2012;Imhoff, Woelki, Hanke, & Dotsch, 2013;Kunst, Kteily, & Thomsen, 2018;Todorov et al, 2011). The resulting classification images represent approximations of the average mental representation that participants had of the terrorist in the different conditions.…”