Exploring the Interplay of Mind Wandering and Implicit Learning: A Predictive Processing Perspective

In this thesis, we investigate the intricate relationship between mind-wandering and implicit statistical learning. Drawing upon the theoretical foundations of Predictive Processing framework, which views the brain as a prediction machine, our research aims to elucidate the role of spontaneous thinking in cognition by hypothesizing that MW is involved in the constant updating of internal models of the world which could manifest in strategy selection policy via presenting the near future and past encoded in memory. Given the presumed ubiquity of MW in human cognitive activity, it is likely to influence fundamental abilities like pattern detection, e.i. implicit statistical learning. Our experiment aims to explore the association between MW and ISL as well as the moderating effect of mediation and metacognitive monitoring. We found evidence that fluctuating mind episodes contribute to statistical learning, offering insights into the cognitive benefits of MW and enhancing our understanding of the mechanisms underlying spontaneous mental activity.