Stephen Ferrigno, Ph.D.
Assistant Professor
Cognitive Origins Laboratory
Department of Psychology
University of Wisconsin-Madison
How do Children, Adults, and Monkeys Represent Hierarchical Artificial Grammars?
The ability to represent complex sequences is widely considered a critical feature of human cognition with implications for language, counting, social reasoning, music, and action planning. This line of research aims to explore the nature and development of sequence representation, examine the computational mechanisms that support it, and test how these representations influence early learning. I will present evidence that both young children and monkeys can represent and generate novel strings of a hierarchical center-embedded grammar. These results challenge prevailing theories of human uniqueness and suggest that this ability may be evolutionarily conserved and available early in development. In addition, I will discuss recent work into the potential memory architectures that could underlie these representations, including push-down stacks, queues, and content addressable memory. Finally, I will discuss how the cognitive demands of sequence processing intersect with early mathematical learning, particularly in relation to common errors observed in children’s counting and numerical reasoning.