Spatial Structure Is Learned through Temporal Coherence in Visual Statistical Learning

Using a novel visual statistical learning paradigm, in which spatial structure unfolds over time, we found that participants' implicit learning of noisy spatial regularities depends critically on temporal coherence. The current findings lay the foundation for a deeper understanding of how the acquisition of spatial and temporal regularities are intertwined.