Mixed-complexity artificial grammar learning in humans and macaque monkeys: evaluating learning strategies.

ABSTRACT: Artificial grammars (AG) can be used to generate rule-based sequences of stimuli. Some of these can be used to investigate sequence-processing computations in non-human animals that might be related to, but not unique to, human language. Previous AG learning studies in non-human animals have used different AGs to separately test for specific sequence-processing abilities. However, given that natural language and certain animal communication systems (in particular, song) have multiple levels of complexity, mixed-complexity AGs are needed to simultaneously evaluate sensitivity to the different features of the AG. Here, we tested humans and Rhesus macaques using a mixed-complexity auditory AG, containing both adjacent (local) and non-adjacent (longer-distance) relationships. Following exposur

SUBMITTER: Wilson B 

PROVIDER: S-EPMC4493314 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature