title: Cross-Domain Statistical-Sequential Dependencies Are Difficult to Learn.
abstract: Recent studies have demonstrated participants' ability to learn cross-modal associations during statistical learning tasks. However, these studies are all similar in that the cross-modal associations to be learned occur simultaneously, rather than sequentially. In addition, the majority of these studies focused on learning across sensory modalities but not across perceptual categories. To test both cross-modal and cross-categorical learning of sequential dependencies, we used an artificial grammar learning task consisting of a serial stream of auditory and/or visual stimuli containing both within- and cross-domain dependencies. Experiment 1 examined within-modal and cross-modal learning across two sensory modalities (audition and vision). Experiment 2 investigated within-categorical and cross-categorical learning across two perceptual categories within the same sensory modality (e.g., shape and color; tones and non-words). Our results indicated that individuals demonstrated learning of the within-modal and within-categorical but not the cross-modal or cross-categorical dependencies. These results stand in contrast to the previous demonstrations of cross-modal statistical learning, and highlight the presence of modality constraints that limit the effectiveness of learning in a multimodal environment.
authors.affiliation: Neurocognitive Kinesiology Lab, Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana IL, USA.
authors.forename: Anne M
authors.initials: AM
authors.lastname: Walk
authors.affiliation: NeuroLearn Lab, Department of Psychology, Georgia State University, Atlanta GA, USA.
authors.forename: Christopher M
authors.initials: CM
authors.lastname: Conway
keywords: artificial grammar learning; cross-modal learning; implicit learning; modality constraints; multisensory integration; sequential learning; statistical learning