What can evidence accumulation modelling tell us about human social cognition?

Abstract

Evidence accumulation models are a series of computational models that provide an accountfor speeded decision making. These models have been used extensively within the cognitive psychology literature to great success, allowing inferences to be drawn about the psychological processes that underlie cognition that are sometimes not available in a traditional analysis of accuracy or reaction time. Despite this, there have been few applications of these models within the domain of social cognition. In this paper we explore several ways in which the study of human social information processing would benefit from application of evidence accumulation modelling. We begin first with a brief overview of the evidence accumulation modelling framework and their past success within the domain of cognitive psychology. We then highlight five ways in which social cognitive research would benefit from an evidence accumulation approach. This includes 1) greater specification of assumptions; 2) unambiguous comparisons across blocked task conditions; 3) quantifying and comparing the magnitude of effects in standardised measures; 4) a novel approach for studying individual differences; and 5) improved reproducibility and accessibility. These points are illustrated using examples from the domain of social attention. Finally, we outline several methodological and practical considerations, which should help researchers use evidence accumulation models productively. Ultimately it will be seen that evidence accumulation modelling offers a well-developed, accessible and commonly understood framework that can reveal inferences about cognition that may otherwise be out of reach in a traditional analysis of accuracy and RT. This approach, therefore, has the potential to substantially revise our understanding of social cognition.

The computational substrates of holistic face processing in cognitive control

“…Moreover, the distance between decision threshold (a) for the gaze task is significantly greater for the arrow task. Parker & Ramsey (2022) reveals that response caution is 1.5 times higher when attention was directed with an arrow cue than when attention was directed with a gaze cue. Consistent with this finding, it appears plausible that the gaze judgment task in this study would exhibit a more cautious response, thus leading to irrelevant arrow interfering more with gaze task than vice versa.…”

Uncovering the cognitive mechanisms underlying the gaze cueing effect

“…Despite this, relatively little research has sought to understand the cognitive processes underlying its emergence. Evidence accumulation models represent the dominant framework through which the cognitive processes underlying speeded decisions can be inferred ( Donkin & Brown, 2018 ; Evans & Wagenmakers, 2019 ; Forstmann et al, 2016 ; Ratcliff et al, 2016 ) and have recently been identified as an important (but underused) tool for studying social cognition ( Parker & Ramsey, 2022b ). Here, we focused on three particular cognitive mechanisms described by evidence accumulation models: non-decision time, starting point, and drift rate.…”

“…Evidence accumulation models are a class of computational models that jointly address response time and accuracy data to infer several cognitive mechanisms underlying a decision, and have become the dominant theoretical framework for describing speeded decisions (see Evans & Wagenmakers, 2019 ; Ratcliff et al, 2016 for reviews). However, although the gaze cueing effect arises from data derived from a speeded decision task, it is still unclear how evidence accumulation mechanisms contribute to the emergence of the gaze cueing effect, despite recent calls for their wider use in social cognition research ( Parker & Ramsey, 2022b ). Indeed, there has only been one other study that has attempted to model the gaze cueing effect using an evidence accumulation framework, and that study only tested one potential underlying mechanism ( Parker & Ramsey, 2022a ).…”