C. Cate and K. Okanoya, Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning, Philos. Trans. R. Soc. Lond. B. Biol. Sci, vol.367, 1984.

W. T. Fitch, Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition, Phys. Life Rev, vol.11, pp.329-364, 2014.

B. Wilson, W. D. Marslen-wilson, and C. I. Petkov, Conserved Sequence Processing in Primate Frontal Cortex, Trends Neurosci, vol.40, pp.72-82, 2017.

W. T. Fitch, A. D. Friederici, and P. Hagoort, Pattern perception and computational complexity: introduction to the special issue, Philos. Trans. R. Soc. Lond. B Biol. Sci, vol.367, pp.1925-1932, 2012.

N. Chomsky, Three models for the description of language, IRE Trans Inf Theory IT, vol.2, pp.113-124, 1956.

P. Perruchet and A. Rey, Does the mastery of center-embedded linguistic structures distinguish humans from nonhuman primates?, Psychon. Bull. Rev, vol.12, pp.307-313, 2005.

G. Jäger and J. Rogers, Formal language theory: refining the Chomsky hierarchy, Philos. Trans. R. Soc. B Biol. Sci, vol.367, pp.1956-1970, 2012.

W. T. Fitch and M. D. Hauser, Computational Constraints on Syntactic Processing in a Nonhuman Primate, Science, vol.303, pp.377-380, 2004.

W. T. Fitch and A. D. Friederici, Artificial grammar learning meets formal language theory: an overview, Philos. Trans. R. Soc. Lond. B. Biol. Sci, vol.367, pp.1933-1955, 2012.

T. Q. Gentner, K. M. Fenn, D. Margoliash, and H. C. Nusbaum, Recursive syntactic pattern learning by songbirds, Nature, vol.440, pp.1204-1207, 2006.

C. A. Van-heijningen, J. Visser, . De, W. Zuidema, and C. Ten-cate, Simple rules can explain discrimination of putative recursive syntactic structures by a songbird species, Proc. Natl. Acad. Sci, vol.106, pp.20538-20543, 2009.

K. Abe and D. Watanabe, Songbirds possess the spontaneous ability to discriminate syntactic rules, Nat. Neurosci, vol.14, pp.1067-1074, 2011.

A. Rey, P. Perruchet, and J. Fagot, Centre-embedded structures are a by-product of associative learning and working memory constraints: evidence from baboons (Papio Papio), Cognition, vol.123, pp.180-184, 2012.
URL : https://hal.archives-ouvertes.fr/hal-01439711

N. Stobbe, G. Westphal-fitch, U. Aust, and W. T. Fitch, Visual artificial grammar learning: comparative research on humans, kea (Nestor notabilis) and pigeons (Columba livia), Philos. Trans. R. Soc. Lond. B. Biol. Sci, vol.367, 1995.

A. Ravignani, G. Westphal-fitch, U. Aust, M. M. Schlumpp, and W. T. Fitch, More than one way to see it: Individual heuristics in avian visual computation, Cognition, vol.143, pp.13-24, 2015.

X. Jiang, Production of Supra-regular Spatial Sequences by Macaque Monkeys, Curr. Biol, vol.28, pp.1851-1859, 2018.

G. J. Beckers, J. J. Bolhuis, K. Okanoya, and R. C. Berwick, Birdsong neurolinguistics: songbird context-free grammar claim is premature, Neuroreport, vol.23, pp.139-145, 2012.

G. J. Beckers, R. C. Berwick, K. Okanoya, and J. J. Bolhuis, What do animals learn in artificial grammar studies? Neurosci, Biobehav. Rev, 2016.

F. H. Poletiek, H. Fitz, and B. R. Bocanegra, What baboons can (not) tell us about natural language grammars, Cognition, vol.151, pp.108-112, 2016.

M. H. De-vries, P. Monaghan, S. Knecht, and P. Zwitserlood, Syntactic structure and artificial grammar learning: the learnability of embedded hierarchical structures, Cognition, vol.107, pp.763-774, 2008.

J. Hochmann, M. Azadpour, and J. Mehler, Do Humans Really Learn An Bn Artificial Grammars From Exemplars?, Cogn. Sci. Multidiscip. J, vol.32, pp.1021-1036, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01104125

V. C. Zimmerer, P. E. Cowell, and R. A. Varley, Individual behavior in learning of an artificial grammar, Mem. Cognit, vol.39, pp.491-501, 2011.

S. Ojima and K. Okanoya, The Non-Hierarchical Nature of the Chomsky Hierarchy-Driven Artificial-Grammar Learning, BIOLINGUISTICS, vol.8, pp.163-180, 2014.

M. F. Carr, S. P. Jadhav, and L. M. Frank, Hippocampal replay in the awake state: a potential substrate for memory consolidation and retrieval, Nat. Neurosci, vol.14, pp.147-153, 2011.

M. A. Long, D. Z. Jin, and M. S. Fee, Support for a synaptic chain model of neuronal sequence generation, Nature, vol.468, pp.394-399, 2010.

K. A. Katlowitz, M. A. Picardo, and M. A. Long, Stable Sequential Activity Underlying the Maintenance of a Precisely Executed Skilled Behavior, Neuron, vol.98, p.3, 2018.

S. M. Shieber, Evidence against the context-freeness of natural language, Linguist. Philos, vol.8, pp.333-343, 1985.

J. Bresnan, R. M. Kaplan, S. Peters, and A. Zaenen, Cross-Serial Dependencies in Dutch. Linguist. Inq, vol.13, pp.613-635, 1982.

C. Culy, The Complexity of the Vocabulary of Bambara, The Formal Complexity of Natural Language, pp.349-357, 1985.

E. P. Stabler, Varieties of crossing dependencies: structure dependence and mild context sensitivity, Cogn. Sci, vol.28, pp.699-720, 2004.

J. Bahlmann, R. I. Schubotz, and A. D. Friederici, Hierarchical artificial grammar processing engages Broca's area, NeuroImage, vol.42, pp.525-534, 2008.

J. Lai and F. H. Poletiek, The impact of adjacent-dependencies and staged-input on the learnability of center-embedded hierarchical structures, Cognition, vol.118, pp.265-273, 2011.

J. Bahlmann, R. I. Schubotz, J. L. Mueller, D. Koester, and A. D. Friederici, Neural circuits of hierarchical visuo-spatial sequence processing, Brain Res, vol.1298, pp.161-170, 2009.

G. Westphal-fitch, B. Giustolisi, C. Cecchetto, J. S. Martin, and W. T. Fitch, Artificial Grammar Learning Capabilities in an Abstract Visual Task Match Requirements for Linguistic Syntax, Front. Psychol, vol.9, 2018.

J. Fagot and C. De-lillo, A comparative study of working memory: Immediate serial spatial recall in baboons (Papio papio) and humans, Neuropsychologia, vol.49, pp.3870-3880, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01440414

S. Inoue and T. Matsuzawa, Working memory of numerals in chimpanzees, Curr. Biol, vol.17, pp.1004-1005, 2007.

P. Marler, A comparative approach to vocal learning: Song development in white-crowned sparrows, J. Comp. Physiol. Psychol, vol.71, pp.1-25, 1970.

M. J. Nissen and P. Bullemer, Attentional requirements of learning: Evidence from performance measures, Cognit. Psychol, vol.19, pp.1-32, 1987.

A. Cleeremans and J. L. Mcclelland, Learning the structure of event sequences, J. Exp. Psychol. Gen, vol.120, pp.235-253, 1991.

R. H. Hunt and R. N. Aslin, Statistical learning in a serial reaction time task: Access to separable statistical cues by individual learners, J. Exp. Psychol. Gen, vol.130, pp.658-680, 2001.

J. B. Misyak, M. H. Christiansen, and J. Bruce-tomblin, Sequential Expectations: The Role of Prediction-Based Learning in Language, Top. Cogn. Sci, vol.2, pp.138-153, 2010.

A. A. Wright, J. J. Rivera, J. S. Katz, and J. Bachevalier, Abstract-concept learning and list-memory processing by capuchin and rhesus monkeys, J. Exp. Psychol. Anim. Behav. Process, vol.29, pp.184-198, 2003.

C. Pliatsikas, Working memory in older adults declines with age, but is modulated by sex and education, Q. J. Exp. Psychol, 2018.

K. Beigneux, T. Plaie, and M. Isingrini, Aging Effect on Visual and Spatial Components of Working Memory, Int. J. Aging Hum. Dev, vol.65, pp.301-314, 2007.

A. Orsini, Effects of Age, Education and Sex on Two Tests of Immediate Memory: A Study of Normal Subjects from 20 to 99 Years of Age, Percept. Mot. Skills, vol.63, pp.727-732, 1986.

S. T. Piantadosi, J. B. Tenenbaum, and N. D. Goodman, Bootstrapping in a language of thought: a formal model of numerical concept learning, Cognition, vol.123, pp.199-217, 2012.

S. T. Piantadosi, J. B. Tenenbaum, and N. D. Goodman, The logical primitives of thought: Empirical foundations for compositional cognitive models, Psychol. Rev, vol.123, pp.392-424, 2016.

M. Amalric, The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers, PLOS Comput. Biol, vol.13, p.1005273, 2017.
URL : https://hal.archives-ouvertes.fr/halshs-01495585

X. Zhu, P. Sobhani, and H. Guo, Long short-term memory over recursive structures, Proceedings of the 32nd International Conference on International Conference on Machine Learning, vol.37, pp.1604-1612, 2015.

W. T. Fitch, Bio-Linguistics: Monkeys Break Through the Syntax Barrier, Curr. Biol, vol.28, pp.695-697, 2018.

R. L. Raaum, K. N. Sterner, C. M. Noviello, C. Stewart, and T. R. Disotell, Catarrhine primate divergence dates estimated from complete mitochondrial genomes: concordance with fossil and nuclear DNA evidence, J. Hum. Evol, vol.48, pp.237-257, 2005.

M. E. Steiper and N. M. Young, Primate molecular divergence dates, Mol. Phylogenet. Evol, vol.41, pp.384-394, 2006.

I. S. Zalmout, New Oligocene primate from Saudi Arabia and the divergence of apes and Old World monkeys, Nature, vol.466, pp.360-364, 2010.

N. J. Stevens, Palaeontological evidence for an Oligocene divergence between Old World monkeys and apes, Nature, vol.497, pp.611-614, 2013.

C. I. Petkov and B. Wilson, On the pursuit of the brain network for proto-syntactic learning in non-human primates: conceptual issues and neurobiological hypotheses, Philos. Trans. R. Soc. B Biol. Sci, vol.367, pp.2077-2088, 2012.

D. C. Penn, K. J. Holyoak, and D. J. Povinelli, Darwin's mistake: explaining the discontinuity between human and nonhuman minds, Behav. Brain Sci, vol.31, pp.130-178, 2008.

J. Fagot and E. Bonté, Automated testing of cognitive performance in monkeys: use of a battery of computerized test systems by a troop of semi-free-ranging baboons (Papio papio), Behav. Res. Methods, vol.42, pp.507-516, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01440461

J. Fagot and D. Paleressompoulle, Automatic testing of cognitive performance in baboons maintained in social groups, Behav. Res. Methods, vol.41, pp.396-404, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01440557