Journal article
Mixed-complexity artificial grammar learning in humans and macaque monkeys: evaluating learning strategies
The European journal of neuroscience, Vol.41(5), pp.568-578
03/01/2015
DOI: 10.1111/ejn.12834
PMCID: PMC4493314
PMID: 25728176
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 exposure to exemplary sequences generated by the AG, humans and macaques were individually tested with sequences that were either consistent with the AG or violated specific adjacent or non-adjacent relationships. We observed a considerable level of cross-species correspondence in the sensitivity of both humans and macaques to the adjacent AG relationships and to the statistical properties of the sequences. We found no significant sensitivity to the non-adjacent AG relationships in the macaques. A subset of humans was sensitive to this non-adjacent relationship, revealing interesting between- and within-species differences in AG learning strategies. The results suggest that humans and macaques are largely comparably sensitive to the adjacent AG relationships and their statistical properties. However, in the presence of multiple cues to grammaticality, the non-adjacent relationships are less salient to the macaques and many of the humans.
Details
- Title: Subtitle
- Mixed-complexity artificial grammar learning in humans and macaque monkeys: evaluating learning strategies
- Creators
- Benjamin Wilson - Newcastle UniversityKenny Smith - University of EdinburghChristopher I. Petkov - Newcastle University
- Resource Type
- Journal article
- Publication Details
- The European journal of neuroscience, Vol.41(5), pp.568-578
- DOI
- 10.1111/ejn.12834
- PMID
- 25728176
- PMCID
- PMC4493314
- NLM abbreviation
- Eur J Neurosci
- ISSN
- 0953-816X
- eISSN
- 1460-9568
- Publisher
- Wiley
- Number of pages
- 11
- Grant note
- WT092606/Z/10/Z; WT102961MA / Wellcome Trust; European Commission BB/J009849/1 / BBSRC; UK Research & Innovation (UKRI); Biotechnology and Biological Sciences Research Council (BBSRC)
- Language
- English
- Date published
- 03/01/2015
- Academic Unit
- Iowa Neuroscience Institute; Neurosurgery; Otolaryngology
- Record Identifier
- 9984360131502771
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