A revised diffusion model for conflict tasks

Abstract

The recently developed diffusion model for conflict tasks (DMC) Ulrich et al. (Cognitive Psychology, 78, 148–174, 2015) provides a good account of data from all standard conflict tasks (e.g., Stroop, Simon, and flanker tasks) within a common evidence accumulation framework. A central feature of DMC’s processing dynamics is that there is an initial phase of rapid accumulation of distractor evidence that is then selectively withdrawn from the decision mechanism as processing continues. We argue that this assumption is potentially troubling because it could be viewed as implying qualitative changes in the representation of distractor information over the time course of processing. These changes suggest more than simple inhibition or suppression of distractor information, as they involve evidence produced by distractor processing “changing sign” over time. In this article, we (a) develop a revised DMC (RDMC) whose dynamics operate strictly within the limits of inhibition/suppression (i.e., evidence strength can change monotonically, but cannot change sign); (b) demonstrate that RDMC can predict the full range of delta plots observed in the literature (i.e., both positive-going and negative-going); and (c) show that the model provides excellent fits to Simon and flanker data used to benchmark the original DMC at both the individual and group level. Our model provides a novel account of processing differences across Simon and flanker tasks. Specifically, that they differ in how distractor information is processed on congruent trials, rather than incongruent trials: congruent trials in the Simon task show relatively slow attention shifting away from distractor information (i.e., location) while complete and rapid attention shifting occurs in the flanker task. Our new model highlights the importance of considering dynamic interactions between top-down goals and bottom-up stimulus effects in conflict processing.

Perceptual target discriminability modulates the Simon effect beyond the fading of distractor-based activation: Insights from delta plots and diffusion model analyses.

“…While these exploratory fitting results seem generally plausible and further highlight how a perceptual manipulation influences conflict processing beyond what can be explained by the predictions of pure fading activations in the Simon task, it seems worthwhile to also consider the present findings with other conflict task models built on different theoretical assumptions (Heuer et al, 2023; Lee & Sewell, 2024; López & Pomi, 2023; Miller & Schwarz, 2021; Weichart et al, 2020). For example, distractor-based activation might also change as a function of target-based activation rather than time (Weichart et al, 2020), which in turn could also result in observing an earlier modulation of distractor-based activation with easier (more activation) than hard targets.…”

How do linguistic illusions arise? Rational inference and good-enough processing as competing latent processes within individuals

“…Finding such negative correlations would strengthen the case for shared cognitive mechanisms across different illusions, and crucially also yield insights into whether and how these mechanisms compete within individuals. 3 Finding such trade-offs would lend support to the notion that good-enough processing and rational inference serve conflicting goals, and suggest that both mechanisms draw on a shared pool of resources, as has been suggested in other models of conflict tasks (e.g., Lee and Sewell, 2024).…”

Uncovering the cognitive mechanisms underlying the gaze cueing effect

“…While the DDM did a reasonable job accounting for the data, it was limited in its ability to describe some trends, such as the tendency for cueing effects to reverse at later stages of the response time distributions. One logical next step for future research would be to assess whether models of conflict tasks, such as the conflict diffusion models ( Evans & Servant, 2020 ; Hübner et al, 2010 ; Lee & Sewell, 2023 ; Ulrich et al, 2015 ; White et al, 2011 ) are better able to capture the patterns of data in the gaze cueing task. Conflict evidence accumulation models hold many of the same assumptions as standard evidence accumulation models, but have been designed to assess the influence of task-irrelevant information, such as the type of distractors found in Stroop or Flanker tasks.…”

“…These models would therefore be able to assess the degree to which people are trying to suppress gaze cues and disregard them as task-irrelevant information. Conflict models have also been found to be able to account for the ordering of response times between conditions to overlap or reverse later in the response time distribution ( Lee & Sewell, 2023 ; Ulrich et al, 2015 ), which suggests they could be useful for further understanding the gaze cueing effect in future investigations. We would like to emphasise, however, that although assessing other models in gaze cueing task is a useful future direction, we believe that the DDM was an appropriate first model to use.…”