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.

Figure 1.

Comparing different AG structures and the current paradigm. A, Mapping of AGs previously used to test nonhuman animals, including the original AG designed by Reber (1967). These are plotted as the number of unique stimulus classes (filled circles) or structural elements (open circles) that contribute to the structure as a function of the linearity of the structure (see Materials and Methods). The black line subdividing the shaded regions denotes the maximum possible structural nonlinearity (i.e., random patterns devoid of structure). The checkmarks highlight regions of the parameter space for which there is evidence that the different animal species (labeled text in A) can learn that particular level of structural complexity. Crosses or question marks highlight uncertainty regarding whether the labeled species can learn those aspects, see text. Figure references: 1: Abe and Watanabe (2011), 2: Fitch and Hauser (2004), 3: Gentner et al., (2006), 4: Hauser and Glynn (2009), 5: Murphy et al. (2008), 6: Reber (1967), 7: Saffran et al. (2008), 8: van Heijningen et al. (2009), 9: Stobbe et al. (2012). B, The AG structure used here contains five unique elements and multiple forward branching relationships. Correct sequences (strings of nonsense words) are generated by following any path of arrows from START to END. Violation sequences do not follow the arrows. The AG was used to create 9 habituation sequences. All experiments began with a habituation phase following by a testing phase. The testing sequences that follow the AG (“Correct”) or do not follow the AG (“Violation”) are also shown.

Figure 2.

Video-coding experiment results in Rhesus macaques and common marmosets. (A, C) Mean proportion of trials (±SE across animals) on which the Rhesus macaques and common marmosets made unambiguous looking-responses as evaluated by a majority of 3 raters (see Materials and Methods). Subpanels indicate responses to correct and violation sequences, main panels display results to specific subsets of the correct or violation conditions. B, D, Mean response durations (±SE across animals) in macaques and marmosets in response to correct and violation sequences (subpanels) and to the four subcategories of stimuli. Both Bonferroni (β) and LSD (γ) post hoc tests are reported for all significant contrasts, *p < 0.05; **p < 0.01; ***p < 0.001.

Figure 3.

Eye-tracking measurement of preferential looking-responses to different testing sequences. A, Schematic of macaque eye-tracking experiment. B, Average eye trace from one monkey (±SE across trials). Positive values on the horizontal axis indicate eye movements toward the audio speaker (left or right) that presented a given test sequence. The dotted line denotes 3 SDs of the variance in eye position during fixation, which was used for analysis of significant looking-responses (shaded area is the individually defined response period; see Materials and Methods). C, Mean eye traces (±SE) to the correct and violation sequences for the same monkey. D, Group eye-tracking results including individual results by monkey: Top shows mean response duration (%) of looking-responses to the correct and violation conditions. Bottom shows results for the “familiar” and “novel” correct test sequences and violation sequences that (like the correct sequences) “begin with A” or those that “do not begin with A.” *p < 0.05, ***p < 0.001. a.u., Arbitrary units.

Figure 4.

Eye-tracking of looking-responses to individual elements. Group (and individual) mean difference plot of responses to “violation” minus “correct” sequences in response to each of the five stimulus elements (A, C, D, F, and G). Positive numbers reflect stronger looks to violation sequences than to correct sequences.

Figure 5.

Individual macaque eye-tracking sensitivity to violations at specific sequence positions (difference plots). A, Schematic plot of two of the violation sequences, identifying legal transitions (black arrows) and violations (red arrows). Violation sequence ii (green) contains one more violation than sequence i (purple) in the transition between the second and third elements in the sequence. B–D, Average difference in looking preferences toward sequence ii (positive numbers) or sequence i (negative numbers), across the repetitions of each sequence; respectively: 25, 25, and 26 for each animal. Vertical black lines denote stimulus onset (at 0 ms) and the onset of element 3, where the sequences diverge. Dashed lines indicate CI (based on bootstrapped differences, 1000 permutations, see Materials and Methods). Also shown are the areas >95% or <5% CI (bar plots, right) where each animal made statistically significant looks in favor of either sequence.

Figure 6.

Individual macaque eye traces in responses to specific violation sequences. Average eye position (degrees visual angle ± SE) in response to violation sequence (i) and (ii) for the three macaques. A–C, These sequences are identical for the first two elements but sequence ii then contains an additional violation before the start of element 3, relative to sequence i (Fig. 5A). Vertical black lines denote stimulus onset (at 0 ms) and the onset of element 3. Stronger responses to violation sequence (ii) can be seen in macaques 1 and 2 (A, B) after the onset of the third element (note the areas of separation between the colored areas of the SEs for the two sequences) but not for macaque 3 (C) who may only show a slight preference for sequence i during the period when both sequences are identical (element positions 1–2).