Double responding: A new constraint for models of speeded decision making

Abstract

Evidence accumulation models (EAMs) have become the dominant models of speeded decision making, which are able to decompose choices and response times into cognitive parameters that drive the decision process. Several models within the EAM framework contain fundamentally different ideas of how the decision making process operates, though previous assessments have found that these models display a high level of mimicry, which has hindered the ability of researchers to contrast these different theoretical viewpoints. Our study introduces a neglected phenomenon that we term "double responding", which can help to further constrain these models. We show that double responding produces several interesting benchmarks, and that the predictions of different EAMs can be distinguished in standard experiment paradigms when they are constrained to account for the choice response time distributions and double responding behaviour in unison. Our findings suggest that lateral inhibition (e.g., the leaky-competing accumulator) provides models with a universal ability to make accurate predictions for these data. Furthermore, only models containing feed-forward inhibition (e.g., the diffusion model) performed poorly under both of our proposed extensions of the standard EAM framework to double responding, suggesting a general inability of feed-forward inhibition to accurately predict these data. We believe that our study provides an important step forward in further constraining models of speeded decision making, though additional research on double responding is required before broad conclusions are made about which models provide the best explanation of the underlying decision-making process.

Keywords: Double responding; Evidence accumulation models; Model mimicry; Response time models.