Effects of Statistical Learning on Target Detection Speed Can Reflect Prediction

In a recent study in Cognitive Science, Sheinenson, Kleiman, and Siegelman found that statistical learning of visual pairs produces response time facilitation during target detection that is driven exclusively by the predictive value of the preceding shape rather than by the predictability of the target itself. These intriguing results suggest that facilitation effects in the target detection task may reflect attentional modulation by statistical structure, whereby greater attention is allocated to temporal segments of greater certainty rather than the prediction of specific upcoming items. Here, we highlight an important divergent finding that suggests that Sheinenson and colleagues' framework may not generalize across all statistical learning studies using the target detection task. Using a speech-based statistical learning paradigm with a conceptually similar design, we recently showed that facilitation during target detection depends entirely on whether the target itself is specifically predicted by the preceding syllable and not on whether the preceding syllable is predictive, as suggested by Sheinenson and colleagues. We suggest that the relative stability of the statistical environment and the domain of statistical learning may be important factors that critically shape whether prediction is invoked during target detection. The target detection task can index learning of specific regularities, at least in the speech domain when violations of learned structure are rare. Identifying the precise boundary conditions under which prediction does and does not operate in statistical learning will be an important goal of future research.