Lateral Inhibition Provides a Better Explanation of Double Responding Than Feed-Forward Inhibition or Inhibition-Free Mechanisms

Evidence accumulation models (EAMs) have dominated theoretical accounts of speeded decision-making for decades, with a proliferation of different variants that each provide different theoretical accounts of how the decision-making process operates. However, these variants often show strong mimicry in their predictions about empirical data, hindering the ability to contrast these accounts and make further theoretical progress. Evans et al. (2020a) proposed double responding (DR) - where participants make a second response after their initial response - as an additional constraint to help distinguish between theoretical accounts, and found that models with lateral inhibition provided a superior account of the data to models with feed-forward inhibition or no inhibition. However, the study of Evans et al. (2020a) had two key limitations: (1) the focus on "implicit'' double responding behaviour, where participants were not told that they could change their response, and (2) the inability of any model to explain the positively skewed DR response time (DRRT) distributions. Here, we provide a conceptual replication of Evans et al. (2020a), where we explicitly instructed participants that they could change their mind, and included a leaky integrating threshold (LIT) framework to attempt to explain the positively skewed DRRT distributions. As in Evans et al. (2020a), models with lateral inhibition consistently provided a superior account of the data relative to models with feed-forward inhibition and without inhibition, mostly in terms of predictions about DR proportions. However, in contrast to Evans et al. (2020a), we found that the models - even without the LIT framework - were able to predict positively skewed DRRT distributions, with these contrasting findings likely influenced by the shorter DR deadline in Evans et al. (2020a). Our findings provide further evidence that lateral inhibition is crucial to explaining changes of mind in decision-making, and that DRs can serve as an important extra constraint in distinguishing between competing decision-making models.