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.

Highlights

  • Understanding which brain processes are evolutionarily conserved in humans and other animals, and which have undergone unique specialisation in humans requires cross-species comparisons

  • We support the principles on reporting animal research stated in the consortium on Animal Research Reporting of In Vivo Experiments (ARRIVE)

  • We overview the key features of the Artificial grammar (AG) and the experimental design, which are important for understanding the results obtained

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Summary

Introduction

Understanding which brain processes are evolutionarily conserved in humans and other animals, and which have undergone unique specialisation in humans requires cross-species comparisons. Artificial grammar (AG) learning paradigms have shown that human and non-human animals can process certain relationships between elements in a sequence (Fitch & Hauser, 2004; Gentner et al, 2006; Saffran et al, 2008; Wilson et al, 2013) The complexity of these relationships can be controlled experimentally, related to features of human language or animal song, and quantitatively compared with other sequence-processing paradigms (Petkov & Wilson, 2012; Wilson et al, 2013), such as auditory oddball or rhythm perception paradigms (Ulanovsky et al, 2003; Selezneva et al, 2013). We directly compare the sensitivity of Received 16 September 2014, revised 03 December 2014, accepted 15 December 2014 macaques and humans with various features of a mixed-complexity AG to inform neurobiological research

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