Uncovering the cognitive mechanisms underlying the gaze cueing effect

Abstract

The gaze cueing effect is the tendency for people to respond faster to targets appearing at locations gazed at by others compared to locations gazed away from by others. The effect is robust, widely studied, and is an influential finding within social cognition. Formal evidence accumulation models provide the dominant theoretical account of the cognitive processes underlying speeded decision making, but they have rarely been applied to social cognition research. In this study, using a combination of individual-level and hierarchical computational modelling techniques, we applied evidence accumulation models to gaze cueing data (three data sets total, N = 171, 139,001 trials) for the first time to assess the relative capacity that an attentional orienting mechanism and information processing mechanisms have for explaining the gaze cueing effect. We found that most participants were best described by the attentional orienting mechanism, such that response times were slower at gazed away from locations because they had to re-orient to the target before they could process the cue. However, we found evidence for individual differences, whereby the models suggested that some gaze cueing effects were driven by a short allocation of information processing resources to the gazed at location, allowing for a brief period where orienting and processing could occur in parallel. There was exceptionally little evidence to suggest any sustained reallocation of information processing resources neither at the group nor individual level. We discuss how this individual variability might represent credible individual differences in the cognitive mechanisms that subserve behaviourally observed gaze-cueing effects.

Enhancing ecological validity of gaze-cueing stimuli is associated with increased gaze following for older but not younger adults.

“…Our recent meta-analysis (McKay et al, 2021) and a recent review (Dalmaso et al, 2020) identified several variables that moderate the magnitude of gaze-cued orienting at the task, cue, and context level; almost all of which have not been assessed as but could potentially be moderators of age effects in gaze following (e.g., eye contact, interpersonal trust, etc.). Furthermore, in a large sample, mathematical modeling (as in Alister et al, 2023) could be used to determine whether there are group-level differences in the mechanisms that subserve gaze following between younger and older adults.…”

“…Each target can therefore be categorized as being either gaze-cued (appearing at the location the gaze cue looked toward) or gaze-miscued (appearing at the location the gaze cue looked away from). Gaze following-an attention shift via the gaze cue stimulus-is considered to have occurred when response times to gaze-cued targets are faster than response times to gaze-miscued targets (Alister et al, 2023).…”

ParAcT-DDM: A diffusion-based framework for modelling systematic, time-varying cognitive processes

“…Nonetheless, despite requiring a substantial number of trials for reliable fitting (Lerche et al, 2017), these models offer only a single estimate of a given construct for the entire duration of an experiment, failing to account for potential changes in these constructs over time. For example, a researcher might have a hypothesis that a particular manipulation will decrease task efficiency, so they compare the model's single estimate of efficiency in that condition, with the model's single estimate of efficiency in the control condition (e.g., Alister et al, 2023;Lerche et al, 2020;Ratcliff et al, 2004;van Ravenzwaaij et al, 2012).…”

“…Probability according to BIC (AIC) that Exponential drift rate (v) and threshold (a) modelswere the best fit to data generated from each model respectively, collapsed across participants.As expected based on previous research (e.g.,Alister et al, 2023;Lerche & Voss, 2016;Lerche et al, 2017), all of the parameters for the standard diffusion model showed good measurement properties, with generating and estimating parameters having correlations of at least r = .96 (see Supplementary Material 3A…”

Enhancing Ecological Validity of Gaze-Cueing Stimuli is Associated with Increased Gaze Following for Older but not Younger Adults

“…Each target can therefore be categorized as being either gaze-cued (appearing at the location the gaze cue looked towards) or gaze-miscued (appearing at the location the gaze cue looked away from). Gaze followingan attention shift via the gaze cue stimulusis considered to have occurred when response times to gaze-cued targets are faster than response times to gaze-miscued targets (Alister et al, 2023).…”