A Bayesian approach for estimating the probability of trigger failures in the stop-signal paradigm.

ABSTRACT: Response inhibition is frequently investigated using the stop-signal paradigm, where participants perform a two-choice response time task that is occasionally interrupted by a stop signal instructing them to withhold their response. Stop-signal performance is formalized as a race between a go and a stop process. If the go process wins, the response is executed; if the stop process wins, the response is inhibited. Successful inhibition requires fast stop responses and a high probability of triggering the stop process. Existing methods allow for the estimation of the latency of the stop response, but are unable to identify deficiencies in triggering the stop process. We introduce a Bayesian model that addresses this limitation and enables researchers to simultaneously estimate the probabilit

SUBMITTER: Matzke D 

PROVIDER: S-EPMC5352806 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature