A Cautionary Note on Evidence-Accumulation Models of Response Inhibition in the Stop-Signal Paradigm

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Abstract

The stop-signal paradigm is a popular procedure to investigate response inhibition—the ability to stop ongoing responses. It consists of a choice response time (RT) task that is occasionally interrupted by a stop stimulus signaling participants to withhold their response. Performance in the stop-signal paradigm is often formalized as race between a set of go runners triggered by the choice stimulus and a stop runner triggered by the stop signal. We investigated whether evidence-accumulation processes, which have been widely used in choice RT analysis, can serve as the runners in the stop-signal race model and support the estimation of psychologically meaningful parameters. We examined two types of the evidence-accumulation architectures: the racing Wald model (Logan et al. 2014) and a novel proposal based on the lognormal race (Heathcote and Love 2012). Using a series of simulation studies and fits to empirical data, we found that these models are not measurement models in the sense that the data-generating parameters cannot be recovered in realistic experimental designs.

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Matzke, D., Logan, G. D., & Heathcote, A. (2020). A Cautionary Note on Evidence-Accumulation Models of Response Inhibition in the Stop-Signal Paradigm. Computational Brain and Behavior, 3(3), 269–288. https://doi.org/10.1007/s42113-020-00075-x

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