Auditory Artificial Grammar Learning in Macaque and Marmoset Monkeys

Abstract

Artificial grammars (AG) are designed to emulate aspects of the structure of language, and AG learning (AGL) paradigms can be used to study the extent of nonhuman animals' structure-learning capabilities. However, different AG structures have been used with nonhuman animals and are difficult to compare across studies and species. We developed a simple quantitative parameter space, which we used to summarize previous nonhuman animal AGL results. This was used to highlight an under-studied AG with a forward-branching structure, designed to model certain aspects of the nondeterministic nature of word transitions in natural language and animal song. We tested whether two monkey species could learn aspects of this auditory AG. After habituating the monkeys to the AG, analysis of video recordings showed that common marmosets (New World monkeys) differentiated between well formed, correct testing sequences and those violating the AG structure based primarily on simple learning strategies. By comparison, Rhesus macaques (Old World monkeys) showed evidence for deeper levels of AGL. A novel eye-tracking approach confirmed this result in the macaques and demonstrated evidence for more complex AGL. This study provides evidence for a previously unknown level of AGL complexity in Old World monkeys that seems less evident in New World monkeys, which are more distant evolutionary relatives to humans. The findings allow for the development of both marmosets and macaques as neurobiological model systems to study different aspects of AGL at the neuronal level.

The Neural Representation of Sequences: From Transition Probabilities to Algebraic Patterns and Linguistic Trees

“…Undoubtedly, non-human primates can learn to detect structures within auditory sequences (Wilson et al, 2013) and may even represent certain abstract features of such sequences such as their number or algebraic pattern (Nieder, 2012;Nieder et al, 2006;Wang et al, 2015). However, those competences need not imply that nested rules are involved: specific experiments are needed to probe this representational level.…”

Conserved Sequence Processing in Primate Frontal Cortex

“…However, even with adjacent relationships ​, demands on learning and memory can increase as greater variability is introduced - for example, when the transitional probabilities between items in longer sequences become less predictable (as illustrated along the X-axis in Figure 1 4, 5, 8). Nonadjacent relationships generate a further increase in sequencing complexity (Figure 1B).…”

Representation of Numerical and Sequential Patterns in Macaque and Human Brains

“…Such evidence suggests that infants could detect and memorize at least some aspects of the regular pattern governing the stimuli (e.g., the initial repetition of two sounds, or the change in the last item). It has been claimed that monkeys and some birds may possess the rudiments of this ability [6][7][8], but current evidence remains inconclusive [9][10][11][12]. Although non-human primates can learn patterns based on number [13] or artificial grammars [8], we still do not know whether and how the neural networks underlying such abstract features differ in monkey and human brains.…”