Unraveling Temporal Dynamics of Multidimensional Statistical Learning in Implicit and Explicit Systems: An X-Way Hypothesis

Statistical learning enables humans to involuntarily process and utilize different kinds of patterns from the environment. However, the cognitive mechanisms underlying the simultaneous acquisition of multiple regularities from different perceptual modalities remain unclear. A novel multidimensional serial reaction time task was developed to test 40 participants’ ability to learn simple first-order and complex second-order relations between uni-modal visual and cross-modal audio-visual stimuli. Using the difference in reaction times between sequenced and random stimuli as the index of domain-general statistical learning, a significant difference and dissociation of learning occurred between the initial and final learning phases. Furthermore, we used a negative and positive occurrence-frequency-and-reaction-time correlation to indicate implicit and explicit learning, respectively, and found that learning simple uni-modal patterns involved an implicit-to-explicit segue, while acquiring complex cross-modal patterns required an explicit-to-implicit segue, resulting in a X-shape crossing of regularity learning. Thus, we propose an X-way hypothesis to elucidate the dynamic interplay between the implicit and explicit systems at two distinct stages when acquiring various regularities in a multidimensional probability space.