Non‐adjacent Dependency Learning in Humans and Other Animals. (8th September 2018)

• Record Type: Journal Article
• Authors: Wilson, Benjamin; Spierings, Michelle; Ravignani, Andrea; Mueller, Jutta L.; Mintz, Toben H.; Wijnen, Frank; van der Kant, Anne; Smith, Kenny; Rey, Arnaud
• Is Part Of: Topics in cognitive science. Volume 12:Number 3(2020)
• Page Start: 843
• Page End: 858
• Publication Date: 2018-09-08
• Subjects: Non‐adjacent dependency -- Artificial grammar -- Structured sequence processing -- Human -- Infant -- Nonhuman animal -- Primate; Cognitive science -- Periodicals; Cognitive Science -- Periodicals; 153.05
• DOI: 10.1111/tops.12381
• Languages: English
• ISSNs: 1756-8757

Abstract

Abstract: Learning and processing natural language requires the ability to track syntactic relationships between words and phrases in a sentence, which are often separated by intervening material. These nonadjacent dependencies can be studied using artificial grammar learning paradigms and structured sequence processing tasks. These approaches have been used to demonstrate that human adults, infants and some nonhuman animals are able to detect and learn dependencies between nonadjacent elements within a sequence. However, learning nonadjacent dependencies appears to be more cognitively demanding than detecting dependencies between adjacent elements, and only occurs in certain circumstances. In this review, we discuss different types of nonadjacent dependencies in language and in artificial grammar learning experiments, and how these differences might impact learning. We summarize different types of perceptual cues that facilitate learning, by highlighting the relationship between dependent elements bringing them closer together either physically, attentionally, or perceptually. Finally, we review artificial grammar learning experiments in human adults, infants, and nonhuman animals, and discuss how similarities and differences observed across these groups can provide insights into how language is learned across development and how these language‐related abilities might have evolved. Abstract : Wilson et al. focus on one class of AGL tasks: the cognitively demanding task of detecting non‐adjacent dependencies (NADs) among items. They provide a typology of the different types of NADs in natural languages and in AGL tasks. A range of cues affect NAD learning, ranging from the variability and number of intervening elements to the presence of shared prosodic cues between the dependent items. These cues, important for humans to discover non‐adjacent dependencies, are also found to facilitate NAD learning in several nonhuman animal species.