On different attentional modes in the visual spatial regularities learning

Abstract

Humans possess the ability to unconsciously extract and learn patterns in structured spatial environments. However, the cognitive mechanisms responsible for enabling this capacity are to be discovered. Learning of spatial regularities falls under the purview of visual statistical learning. This form of learning occurs incidentally during the resolution of diverse tasks involving the processing of information from multiple objects. Consequently, visual spatial statistical learning is closely linked to the characteristics of attentional allocation. This paper is aimed to analyze recent empirical data concerning the relationship between learning and attentional distribution while resolving specific tasks. We describe principal experimental paradigms employed in investigations of spatial statistical learning. We also analyze data on the role of focused and distributed, global and local modes of attention in visual statistical learning. Additionally, the connection between statistical learning and the perception of ensemble perception, as well as statistical learning and global set perception, is explored. An exemplary situation in spatial statistical learning, namely the acquisition of contextual cues in a visual search task, is presented. Empirical data on the role of attentional modes in the context cueing paradigm is juxtaposed with findings from the original experimental approach in the field of spatial statistical learning. In conclusion, the paper discusses key challenges in spatial statistical learning and proposes potential avenues for further research in this domain.