Statistical learning allows us to implicitly create memory traces of recurring sequential patterns appearing in our environment. Here, we study the dynamics of how these sequential memory traces develop in a species of nonhuman primates (i.e., Guinea baboons, "Papio papio") that, unlike humans, cannot use language and verbal recoding…

Recursive hierarchical embedding allows humans to generate multiple hierarchical levels using simple rules. We can acquire recursion from exposure to linguistic and visual examples, but only develop the ability to understand "multiple-level" structures like "[[second] red] ball]" after mastering "same-level"…

In this article, we explore the extraction of recursive nested structure in the processing of binary sequences. Our aim was to determine whether humans learn the higher-order regularities of a highly simplified input where only sequential-order information marks the hierarchical structure. To this end, we implemented a sequence generated by the…

There are two main approaches to how statistical patterns are extracted from sequences: The transitional probability approach proposes that statistical learning occurs through the computation of probabilities between items in a sequence. The chunking approach, including models such as PARSER and TRACX, proposes that units are extracted as chunks.…

Complex sequences are ubiquitous in human mental life, structuring representations within many different cognitive domains--natural language, music, mathematics, and logic, to name a few. However, the representational and computational machinery used to learn abstract grammars and process complex sequences is unknown. Here, we used an artificial…

Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences--and the relations between the elements they comprise--are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the…

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about…