Abstract

In a signal detection theory (SDT) approach to associative learning, one assumes that, when a subject is exposed to a flow of stimuli, an association is created between the internal representations of a cue and of an outcome, allowing the representation of the cue to activate the representation of the outcome. The outcome activation is a random variable drawn from a Gaussian distribution with mean m (sensitivity to the contingency) and standard deviation d (variability in outcome activation). Depending on whether the outcome activation is above or below various decision thresholds, the participant perceives either a negative, a null, or a positive contingency between the cue and the outcome. This study presents a detailed SDT analysis of the performance of four participants on whom data in a contingency assessment task were collected almost daily during several months. Parameters from the SDT model proved relatively stable over time, except if feedback was provided to the subject. In that case, for some participants but not all, the sensitivity increased. The decision criteria were also affected. Some of these changes endured despite the discontinuation of feedback. The variability in outcome activation was not affected by the feedback.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call