Production of Supra-regular Spatial Sequences by Macaque Monkeys
Open accessAbstract
Understanding and producing embedded sequences in language, music, or mathematics, is a central characteristic of our species. These domains are hypothesized to involve a human-specific competence for supra-regular grammars, which can generate embedded sequences that go beyond the regular sequences engendered by finite-state automata. However, is this capacity truly unique to humans? Using a production task, we show that macaque monkeys can be trained to produce time-symmetrical embedded spatial sequences whose formal description requires supra-regular grammars or, equivalently, a push-down stack automaton. Monkeys spontaneously generalized the learned grammar to novel sequences, including longer ones, and could generate hierarchical sequences formed by an embedding of two levels of abstract rules. Compared to monkeys, however, preschool children learned the grammars much faster using a chunking strategy. While supra-regular grammars are accessible to nonhuman primates through extensive training, human uniqueness may lie in the speed and learning strategy with which they are acquired.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Recursion is absent or very limited in other animals; they may acquire language-like symbolic abilities slowly and to a limited level.
“Such recursion is absent or very limited in other animals; although they may acquire some language-like symbolic abilities, they do so at a very slow pace and up to a limited level (Jiang et al., 2018; Yang, 2013).”
From Conscious Processing and the Global Neuronal Workspace Hypothesis (2020) · cites this paper as Jiang et al., 2018
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
ASPECTS OF THE THEORY OF SYNTAX
Chomsky, N. (1964) · doi:10.21236/ad0616323 · Cited by 13,587 · see citing works
The faculty of language: what is it, who has it, and how did it evolve?
Hauser, M. D., Chomsky, N., & Fitch, W. T. (2002) · Science · doi:10.1126/science.298.5598.1569 · Cited by 5,189 · see citing works
The symbolic species: the co-evolution of language and the brain
(1997) · Choice Reviews Online · doi:10.5860/choice.35-1500 · Cited by 2,443 · see citing works
Learning and Instinct in Animals
Kennedy, J. S., & Thorpe, W. H. (1964) · Journal of Animal Ecology · doi:10.2307/2644 · Cited by 1,598 · see citing works
A comparative approach to vocal learning: Song development in white-crowned sparrows.
Marler, P. (1970) · Journal of Comparative and Physiological Psychology · doi:10.1037/h0029144 · Cited by 963 · see citing works
The evolution of the arcuate fasciculus revealed with comparative DTI
Rilling, J. K., Glasser, M. F., Preuss, T. M., Ma, X., Zhao, T., Hu, X. P., & Behrens, T. E. J. (2008) · Nature Neuroscience · doi:10.1038/nn2072 · Cited by 866 · see citing works
Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies
Linzen, T., Emmanuel Dupoux, A., & Goldberg, Y. (2016) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00115 · Cited by 776 · see citing works
Friederici, A. D., Bahlmann, J., Heim, S., Schubotz, R. I., & Anwander, A. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0509389103 · Cited by 734 · see citing works
Ordering of the Numerosities 1 to 9 by Monkeys
Brannon, E. M., & Terrace, H. S. (1998) · Science · doi:10.1126/science.282.5389.746 · Cited by 702 · see citing works
Cortical representation of the constituent structure of sentences
Pallier, C., Devauchelle, A.-D., & Dehaene, S. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018711108 · Cited by 691 · see citing works
Self-citationLearning and instinct in animals
Brown, D. R. (1957) · Journal of the Franklin Institute · doi:10.1016/0016-0032(57)90298-3 · Cited by 685 · see citing works
Computational Constraints on Syntactic Processing in a Nonhuman Primate
Fitch, W. T., & HAUSER, M. D. (2004) · Science · doi:10.1126/science.1089401 · Cited by 664 · see citing works
Recursive syntactic pattern learning by songbirds
Gentner, T. Q., Fenn, K. M., Margoliash, D., & Nusbaum, H. C. (2006) · Nature · doi:10.1038/nature04675 · Cited by 659 · see citing works
The discovery of structural form
Kemp, C., & Tenenbaum, J. B. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0802631105 · Cited by 656 · see citing works
Dehaene, S., Meyniel, F., Wacongne, C., Wang, L., & Pallier, C. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.019 · Cited by 478 · see citing works
Self-citationSongs to syntax: the linguistics of birdsong
Berwick, R. C., Okanoya, K., Beckers, G. J. L., & Bolhuis, J. J. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.01.002 · Cited by 467 · see citing works
Broca's area and the language instinct
Musso, M., Moro, A., Glauche, V., Rijntjes, M., Reichenbach, J. R., Büchel, C., & Weiller, C. (2003) · Nature Neuroscience · doi:10.1038/nn1077 · Cited by 464 · see citing works
Working memory of numerals in chimpanzees
Inoue, S., & Matsuzawa, T. (2007) · Current Biology · doi:10.1016/j.cub.2007.10.027 · Cited by 418 · see citing works
Neubert, F.-X., Mars, R. B., Thomas, A. G., Sallet, J., & Rushworth, M. F. S. (2014) · Neuron · doi:10.1016/j.neuron.2013.11.012 · Cited by 416 · see citing works
The Price of Linguistic Productivity: How Children Learn to Break the Rules of Language
Yang, C. D. (2016) · Project Muse (Johns Hopkins University) · Cited by 296 · see citing works
Long Short-Term Memory Over Recursive Structures
Zhu, X., Sobihani, P., & Guo, H. (2015) · Cited by 292 · see citing works
Sequential learning in non-human primates
Conway, C. M., & Christiansen, M. H. (2001) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01800-3 · Cited by 263 · see citing works
Categorization of behavioural sequences in the prefrontal cortex
Shima, K., Isoda, M., Mushiake, H., & Tanji, J. (2006) · Nature · doi:10.1038/nature05470 · Cited by 259 · see citing works
Empirical approaches to the study of language evolution
Fitch, W. T. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-017-1236-5 · Cited by 259 · see citing works
TYLER, L. K., Marslen‐Wilson, W. D., Randall, B., Wright, P. K., Devereux, B. J., Zhuang, J., Papoutsi, M., & Stamatakis, E. A. (2011) · Brain · doi:10.1093/brain/awq369 · Cited by 258 · see citing works
The Oxford Handbook of Comparative Cognition
(2012) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780195392661.001.0001 · Cited by 232 · see citing works
Fitch, W. T. (2014) · Physics of Life Reviews · doi:10.1016/j.plrev.2014.04.005 · Cited by 221 · see citing works
van Heijningen, C. A. A., de Visser, J., Zuidema, W. H., & ten Cate, C. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908113106 · Cited by 215 · see citing works
Formal language theory: refining the Chomsky hierarchy
Jäger, G., & Rogers, J. (2012) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0077 · Cited by 210 · see citing works
Numerical memory span in a chimpanzee
Kawai, N., & Matsuzawa, T. (2000) · Nature · doi:10.1038/47405 · Cited by 209 · see citing works
Artificial grammar learning meets formal language theory: an overview
Fitch, W. T., & Friederici, A. D. (2012) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0103 · Cited by 201 · see citing works
Songbirds possess the spontaneous ability to discriminate syntactic rules
Abe, K., & Watanabe, D. (2011) · Nature Neuroscience · doi:10.1038/nn.2869 · Cited by 197 · see citing works
Amalric, M., Wang, L., Pica, P., Figueira, S. D., Sigman, M., & Dehaene, S. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005273 · Cited by 196 · see citing works
Self-citationRepresentation of Action Sequence Boundaries by Macaque Prefrontal Cortical Neurons
Fujii, N., & Graybiel, A. M. (2003) · Science · doi:10.1126/science.1086872 · Cited by 193 · see citing works
ten Cate, C., & Okanoya, K. (2012) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0055 · Cited by 181 · see citing works
Murphy, R. A., Mondragón, E., & Murphy, V. A. (2008) · Science · doi:10.1126/science.1151564 · Cited by 177 · see citing works
Representation of Numerical and Sequential Patterns in Macaque and Human Brains
Wang, L., Uhrig, L., Jarraya, B., & Dehaene, S. (2015) · Current Biology · doi:10.1016/j.cub.2015.06.035 · Cited by 166 · cited 1× · see citing works
“There is much evidence that nonhuman animals can learn sequences based on statistical transition probabilities [6], chunking [7], ordinal knowledge [8], or algebraic patterns [9, 10].”
BackgroundSelf-citationThe psychology of communication
(1972) · Journal of Communication Disorders · doi:10.1016/0021-9924(72)90022-6 · Cited by 137 · see citing works
Spierings, M. J., & ten Cate, C. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1600483113 · Cited by 124 · see citing works
Auditory Artificial Grammar Learning in Macaque and Marmoset Monkeys
Wilson, B., Slater, H., Kikuchi, Y., Milne, A. E., Marslen‐Wilson, W. D., Smith, K., & Petkov, C. I. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.2414-13.2013 · Cited by 105 · see citing works
Conserved Sequence Processing in Primate Frontal Cortex
Wilson, B., Marslen‐Wilson, W. D., & Petkov, C. I. (2017) · Trends in Neurosciences · doi:10.1016/j.tins.2016.11.004 · Cited by 101 · see citing works
Rey, A., Perruchet, P., & Fagot, J. (2012) · Cognition · doi:10.1016/j.cognition.2011.12.005 · Cited by 78 · see citing works
Non-adjacent visual dependency learning in chimpanzees
Sonnweber, R. S., Ravignani, A., & Fitch, W. T. (2015) · Animal Cognition · doi:10.1007/s10071-015-0840-x · Cited by 78 · see citing works
Production and perception rules underlying visual patterns: effects of symmetry and hierarchy
Westphal‐Fitch, G., Huber, L., Gómez, J. C., & Fitch, W. T. (2012) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0098 · Cited by 58 · see citing works
Tree-structured composition in neural networks without tree-structured architecturesPreprint
Bowman, S. R., Manning, C. D., & Potts, C. E. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1506.04834 · Cited by 51 · see citing works
Assessing the uniqueness of language: Animal grammatical abilities take center stage
ten Cate, C. (2016) · Psychonomic Bulletin & Review · doi:10.3758/s13423-016-1091-9 · Cited by 45 · see citing works
What do animals learn in artificial grammar studies?
Beckers, G. J. L., Berwick, R. C., Okanoya, K., & Bolhuis, J. J. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.12.021 · Cited by 39 · see citing works
More than one way to see it: Individual heuristics in avian visual computation
Ravignani, A., Westphal‐Fitch, G., Aust, U., Schlumpp, M., & Fitch, W. T. (2015) · Cognition · doi:10.1016/j.cognition.2015.05.021 · Cited by 33 · see citing works
Evolution of the brain and social behavior in chimpanzees
Matsuzawa, T. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.01.012 · Cited by 32 · see citing works
The Organization of Sequential BehaviorConditioning, Memory, and Abstraction
Fountain, S. B., Rowan, J. D., Muller, M. D., Kundey, S. M. A., Pickens, L. R. G., & Doyle, K. E. (2012) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780195392661.013.0031 · Cited by 19 · see citing works
What baboons can (not) tell us about natural language grammars
Poletiek, F. H., Fitz, H., & Bocanegra, B. R. (2015) · Cognition · doi:10.1016/j.cognition.2015.04.016 · Cited by 15 · see citing works
The Comparative Psychology of Ordinal Knowledge
Terrace, H. S. (2012) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780195392661.013.0032 · Cited by 9 · see citing works
Flagged first, then by citations
1 of the 53 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- [36]Gentner D Analogy Robert FCK Wilson A The MIT Encyclopedia of the Cognitive Sciences Cambridge MIT Press 1999 17 20
Cited by
Sorted by citations
Conscious Processing and the Global Neuronal Workspace Hypothesis
Mashour, G. A., Roelfsema, P., Changeux, J.-P., & Dehaene, S. (2020) · Neuron · doi:10.1016/j.neuron.2020.01.026 · Cited by 1,164 · see citing works
“Such recursion is absent or very limited in other animals; although they may acquire some language-like symbolic abilities, they do so at a very slow pace and only up to a limited level (Jiang et al., 2018; Yang, 2013).”
BackgroundSelf-citationGeometry of sequence working memory in macaque prefrontal cortex
Xie, Y., Hu, P., Li, J., Chen, J., Song, W., Wang, X., Yang, T., Dehaene, S., Tang, S., Min, B., et al. (2022) · Science · doi:10.1126/science.abm0204 · Cited by 215 · see citing works
Self-citationSymbols and mental programs: a hypothesis about human singularity
Dehaene, S., Roumi, F. A., Lakretz, Y., Planton, S., & Sablé-Meyer, M. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.06.010 · Cited by 195 · see citing works
Self-citationA theory of memory for binary sequences: Evidence for a mental compression algorithm in humans
Planton, S., van Kerkoerle, T., Abbih, L., Maheu, M., Meyniel, F., Sigman, M., Wang, L., Figueira, S. D., Romano, S., & Dehaene, S. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008598 · Cited by 84 · see citing works
Self-citationOld and New Approaches to Animal Cognition: There Is Not “One Cognition”
Bräuer, J., Hanus, D., Pika, S., Gray, R. D., & Uomini, N. (2020) · Journal of Intelligence · doi:10.3390/jintelligence8030028 · Cited by 89 · see citing works
Parallels in the sequential organization of birdsong and human speech
Sainburg, T., Theilman, B. H., Thielk, M., & Gentner, T. Q. (2019) · Nature Communications · doi:10.1038/s41467-019-11605-y · Cited by 85 · see citing works
Recursive sequence generation in monkeys, children, U.S. adults, and native Amazonians
Ferrigno, S., Cheyette, S., Piantadosi, S. T., & Cantlon, J. F. (2020) · Science Advances · doi:10.1126/sciadv.aaz1002 · Cited by 77 · see citing works
Roumi, F. A., Marti, S., Wang, L., Amalric, M., & Dehaene, S. (2021) · Neuron · doi:10.1016/j.neuron.2021.06.009 · Cited by 58 · see citing works
Self-citationThe measurement, evolution, and neural representation of action grammars of human behavior
Stout, D., Chaminade, T., Apel, J., Shafti, A., & Faisal, A. A. (2021) · Scientific Reports · doi:10.1038/s41598-021-92992-5 · Cited by 55 · see citing works
Becker, Y., Loh, K., Coulon, O., & Meguerditchian, A. (2021) · Neuroscience and Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.12.013 · Cited by 44 · see citing works
One model for the learning of language
Yang, Y., & Piantadosi, S. T. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2021865119 · Cited by 50 · see citing works
Low-frequency neural activity reflects rule-based chunking during speech listening
Jin, P., Lu, Y., & Ding, N. (2020) · eLife · doi:10.7554/elife.55613 · Cited by 42 · see citing works
Chen, L., Goucha, T., Männel, C., Friederici, A. D., & Zaccarella, E. (2021) · Human Brain Mapping · doi:10.1002/hbm.25432 · Cited by 39 · see citing works
Sainburg, T., & Gentner, T. Q. (2021) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2021.811737 · Cited by 43 · see citing works
Mental programming of spatial sequences in working memory in the macaque frontal cortex
Tian, Z., Chen, J., Zhang, C., Min, B., Xu, B., & Wang, L. (2024) · Science · doi:10.1126/science.adp6091 · Cited by 43 · see citing works
Self-citationNonadjacent dependency processing in monkeys, apes, and humans
Watson, S. K., Burkart, J. M., Schapiro, S. J., Lambeth, S. P., Mueller, J. L., & Townsend, S. W. (2020) · Science Advances · doi:10.1126/sciadv.abb0725 · Cited by 42 · see citing works
Recursive sequence generation in crows
Liao, D. A., Brecht, K. F., Johnston, M., & Nieder, A. (2022) · Science Advances · doi:10.1126/sciadv.abq3356 · Cited by 42 · see citing works
Uddén, J., Martins, M. J. D., Zuidema, W. H., & Fitch, W. T. (2019) · Topics in Cognitive Science · doi:10.1111/tops.12442 · Cited by 38 · see citing works
Flexible control of sequence working memory in the macaque frontal cortex
Chen, J., Zhang, C., Hu, P., Min, B., & Wang, L. (2024) · Neuron · doi:10.1016/j.neuron.2024.07.024 · Cited by 37 · see citing works
Self-citationStructured Sequence Learning: Animal Abilities, Cognitive Operations, and Language Evolution
Petkov, C. I., & ten Cate, C. (2019) · Topics in Cognitive Science · doi:10.1111/tops.12444 · Cited by 37 · see citing works
Zhang, H., Zhen, Y., Yu, S., Long, T., Zhang, B., Jiang, X., Li, J., Fang, W., Sigman, M., Dehaene, S., et al. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0603-21.2021 · Cited by 35 · see citing works
Self-citationLanguage and action in Broca’s area: Computational differentiation and cortical segregation
Zaccarella, E., Papitto, G., & Friederici, A. D. (2020) · Brain and Cognition · doi:10.1016/j.bandc.2020.105651 · Cited by 32 · see citing works
Brain-imaging evidence for compression of binary sound sequences in human memory
Planton, S., Roumi, F. A., Wang, L., & Dehaene, S. (2023) · eLife · doi:10.7554/elife.84376 · Cited by 30 · see citing works
Self-citationEvolutionary neuroanatomical expansion of Broca’s region serving a human-specific function
Friederici, A. D. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.07.004 · Cited by 26 · see citing works
Recursive self-embedded vocal motifs in wild orangutans
Lameira, A. R., Hardus, M. E., Ravignani, A., Raimondi, T., & Gamba, M. (2024) · eLife · doi:10.7554/elife.88348.3 · Cited by 26 · see citing works
Recursive self-embedded vocal motifs in wild orangutans
Lameira, A. R., Hardus, M. E., Ravignani, A., Raimondi, T., & Gamba, M. (2023) · eLife · doi:10.7554/elife.88348 · Cited by 42 · see citing works
Cognitive Linguistics and Language Evolution
Pleyer, M., & Hartmann, S. (2024) · Cambridge University Press eBooks · doi:10.1017/9781009385022 · Cited by 22 · see citing works
What enables human language? A biocultural framework
Arnon, I., Carmel, L., Claidière, N., Fitch, W. T., Susan Goldin-meadow, A., Kirby, S., Okanoya, K., Raviv, L., Wolters, L., & Fisher, S. E. (2025) · Science · doi:10.1126/science.adq8303 · Cited by 21 · see citing works
Iaboni, C., & Abichandani, P. (2024) · IEEE Access · doi:10.1109/access.2024.3479968 · Cited by 21 · see citing works
Brain Inspired Sequences Production by Spiking Neural Networks With Reward-Modulated STDP
Fang, H., Zeng, Y., & Zhao, F. (2021) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2021.612041 · Cited by 19 · see citing works
Language design and communicative competence: The minimalist perspective
Murphy, E. (2020) · Glossa a journal of general linguistics · doi:10.5334/gjgl.1081 · Cited by 19 · see citing works
Baboons (Papio papio) Process a Context-Free but Not a Context-Sensitive Grammar
Malassis, R., Dehaene, S., & Fagot, J. (2020) · Scientific Reports · doi:10.1038/s41598-020-64244-5 · Cited by 19 · see citing works
Self-citationBio-Linguistics: Monkeys Break Through the Syntax Barrier
Fitch, W. T. (2018) · Current Biology · doi:10.1016/j.cub.2018.04.087 · Cited by 18 · see citing works
Nonhuman and Nonhuman-Human Communication: Some Issues and Questions
Pepperberg, I. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.647841 · Cited by 17 · see citing works
Calmus, R., Wilson, B., Kikuchi, Y., & Petkov, C. I. (2019) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0304 · Cited by 15 · see citing works
Common functional localizers to enhance NHP & cross-species neuroscience imaging research
Russ, B. E., Petkov, C. I., Kwok, S. C., Zhu, Q., Belin, P., Vanduffel, W., & Hamed, S. B. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118203 · Cited by 16 · see citing works
Filippi, P. (2020) · Journal of Nonverbal Behavior · doi:10.1007/s10919-020-00337-z · Cited by 15 · see citing works
Neural representation of action symbols in primate frontal cortex
Tian, L. Y., Gupta, K. G., Hanuska, D. J., Rouse, A. G., Eldridge, M. A. G., Schieber, M. H., Wang, X., Tenenbaum, J. B., & Freiwald, W. A. (2026) · Nature · doi:10.1038/s41586-026-10297-x · Cited by 14 · see citing works
Lessons learned in animal acoustic cognition through comparisons with humans
Hoeschele, M., Wagner, B., & Mann, D. C. (2022) · Animal Cognition · doi:10.1007/s10071-022-01735-0 · Cited by 11 · see citing works
Yang, L., Gao, C., Wang, P., Friederici, A. D., Zaccarella, E., & Chen, L. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1151518 · Cited by 11 · see citing works
Sequence and hierarchy in vocal rhythms and phonology
Fitch, W. T. (2019) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.14215 · Cited by 11 · see citing works
Positional encoding in cotton-top tamarins (Saguinus oedipus)
Versace, E., Rogge, J. R., Shelton, N., & Ravignani, A. (2019) · Animal Cognition · doi:10.1007/s10071-019-01277-y · Cited by 10 · see citing works
Cognitive Mechanisms Underlying Recursive Pattern Processing in Human Adults
Dedhe, A. M., Piantadosi, S. T., & Cantlon, J. F. (2023) · Cognitive Science · doi:10.1111/cogs.13273 · Cited by 9 · see citing works
Long-range sequential dependencies precede complex syntactic production in language acquisition
Sainburg, T., Mai, A., & Gentner, T. Q. (2022) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2021.2657 · Cited by 9 · see citing works
Caught in the ACTS: Defining Abstract Cognitive Task Sequences as an Independent Process
Desrochers, T. M., Ahuja, A., Maechler, M. R., Shires, J., Rodriguez, N. Y., & Berryhill, M. E. (2022) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01850 · Cited by 9 · see citing works
Origins of Hierarchical Logical Reasoning
Dedhe, A. M., Clatterbuck, H., Piantadosi, S. T., & Cantlon, J. F. (2023) · Cognitive Science · doi:10.1111/cogs.13250 · Cited by 8 · see citing works
Fang, W., Jiang, X., Chen, J., Zhang, C., & Wang, L. (2025) · Current Biology · doi:10.1016/j.cub.2025.02.031 · Cited by 7 · see citing works
Self-citationDynamic hierarchical cognition: Music and language demand further types of abstracta
Popescu, T., & Fitch, W. T. (2020) · Behavioral and Brain Sciences · doi:10.1017/s0140525x1900308x · Cited by 6 · see citing works
Formal language hierarchy reflects different levels of cognitive complexity.
Silva, S., Inácio, F., Sousa, D. R. E., Gaspar, N., Folia, V., & Petersson, K. M. (2022) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0001182 · Cited by 5 · see citing works
McCoy, R. T., Culbertson, J., Smolensky, P., & Géraldine Legendre, A. (2021) · doi:10.31234/osf.io/r8ct2 · Cited by 5 · see citing works
Englund, M. D., Whitham, W., Conway, C. M., Beran, M. J., & Washburn, D. A. (2021) · Learning & Behavior · doi:10.3758/s13420-021-00485-2 · Cited by 4 · see citing works
Learning boosts the decoding of sound sequences in rat auditory cortex
Luo, D., Li, K., An, H., Schnupp, J. W. H., & Auksztulewicz, R. (2021) · Current Research in Neurobiology · doi:10.1016/j.crneur.2021.100019 · Cited by 4 · see citing works
Recursive self-embedded vocal motifs in wild orangutansPreprint
Lameira, A. R., Hardus, M. E., Ravignani, A., Raimondi, T., & Gamba, M. (2023) · eLife · doi:10.7554/elife.88348.2 · Cited by 4 · see citing works
Malassis, R., & Seed, A. M. (2023) · Consciousness and Cognition · doi:10.1016/j.concog.2023.103557 · Cited by 4 · see citing works
Recognizing structure in novel tunes: differences between human and rats
Crespo-Bojorque, P., Cauvet, É., Pallier, C., & Toro, J. M. (2024) · Animal Cognition · doi:10.1007/s10071-024-01848-8 · Cited by 3 · see citing works
Abstract rule learning and generalization in human and nonhuman primates
Antoun, A., Murugan, R., & Wilson, B. (2025) · Scientific Reports · doi:10.1038/s41598-025-24523-5 · Cited by 3 · see citing works
Neural representation of action grammar structure in primate frontal cortexPreprint
Tian, L. Y., Hanuska, D. J., Gupta, K. G., Liu, Y., Wang, X.-J., Tenenbaum, J. B., & Freiwald, W. A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.18.700235 · Cited by 3 · see citing works
Addressing the theory crisis in statistical learning research
Conway, C. M., Jenkins, H., Milne, A. E., Singh, S., & Wilson, B. (2025) · npj Science of Learning · doi:10.1038/s41539-025-00359-6 · Cited by 2 · see citing works
Flexible Use of Limited Resources for Sequence Working Memory in Macaque Prefrontal Cortex
Li, S., Chen, J., Zhang, C., Tang, S., Xie, Y., & Wang, L. (2025) · Nature Communications · doi:10.1038/s41467-025-65380-0 · Cited by 2 · see citing works
Self-citationNeural Correlates of Analogical Reasoning on Syntactic Patterns
Zhong-shan, L., Zhou, Z., Wang, X., Wu, J., & Chen, L. (2024) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02115 · Cited by 2 · see citing works
Xiao, F., Liang, K., Sun, T., & He, F. (2024) · PsyCh Journal · doi:10.1002/pchj.749 · Cited by 2 · see citing works
Recursive self-embedded vocal motifs in wild orangutansPreprint
Lameira, A. R., Hardus, M. E., Ravignani, A., Raimondi, T., & Gamba, M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.14.536836 · Cited by 2 · see citing works
Decomposing dynamical subprocesses for compositional generalizationPreprint
Luettgau, L., Erdmann, T., Veselič, S., Stachenfeld, K., Moran, R., Kurth-Nelson, Z. L., & Dolan, R. J. (2023) · doi:10.31234/osf.io/sxn4a · Cited by 2 · see citing works
Decomposing dynamical subprocesses for compositional generalizationPreprint
Luettgau, L., Erdmann, T., Veselič, S., Stachenfeld, K., Moran, R., Kurth-Nelson, Z. L., & Dolan, R. J. (2023) · Research Square · doi:10.21203/rs.3.rs-3358736/v1 · Cited by 2 · see citing works
Insights from Animals to Build Better Artificial Language Learners
Toro, J. M. (2024) · Comparative Cognition & Behavior Reviews · doi:10.3819/ccbr.2024.190008 · Cited by 1 · see citing works
Do Humans Use Push‐Down Stacks When Learning or Producing Center‐Embedded Sequences?
Ferrigno, S., Cheyette, S., & Carey, S. E. (2025) · Cognitive Science · doi:10.1111/cogs.70112 · Cited by 1 · see citing works
Extending research on language foundations and evolution
Gong, T., Shuai, L., & Wu, Y. (2018) · Physics of Life Reviews · doi:10.1016/j.plrev.2018.09.001 · Cited by 1 · see citing works
ten Cate, C., Gervain, J., Levelt, C. C., Petkov, C. I., & Zuidema, W. H. (2020) · Topics in Cognitive Science · doi:10.1111/tops.12493 · Cited by 1 · see citing works
A simulation on coevolution between language and multiple cognitive abilities
Gong, T., Shuai, L., & Yang, X. (2022) · Journal of Language Evolution · doi:10.1093/jole/lzab006 · Cited by 1 · see citing works
Recursive self-embedded vocal motifs in wild orangutansPreprint
Lameira, A. R., Hardus, M. E., Ravignani, A., Raimondi, T., & Gamba, M. (2023) · eLife · doi:10.7554/elife.88348.1 · Cited by 1 · see citing works
Linguistic evolution minimizes the amount of syntactic hierarchy in grammarPreprint
Meloni, C. Y., Cathcart, C., Ivani, J. K., Zakharko, T., Ringen, E. J., & Bickel, B. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.19.665693 · Cited by 1 · see citing works
Neural Latching Switch Circuits for implementing Finite-State AutomataPreprint
Dubreuil, A. M., Leblois, A., & Monasson, R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.27.696649 · Cited by 1 · see citing works
Evolutionary continuity and origin explanation of syntax
Rong, Y. I. N., & Zhao, J. (2021) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2021.01264
Action Grammars of Human Behavior – Measurement, Evolution, and Neural RepresentationPreprint
Stout, D., Chaminade, T., Apel, J., & Faisal, A. A. (2021) · Research Square · doi:10.21203/rs.3.rs-289382/v1
Passingham, R. E. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198844570.003.0011
Psychologie cognitive expérimentale
Dehaene, S. (2020) · L’annuaire du Collège de France · doi:10.4000/annuaire-cdf.15303
Self-citationWilson, B. R., & Jenkins, H. E. (2022) · doi:10.1093/oso/9780197501573.003.0012
Is core knowledge a natural subdivision of infant cognition?
Kaicher, C. M., Conti, J., Dedhe, A. M., Aulet, L. S., & Cantlon, J. F. (2024) · Behavioral and Brain Sciences · doi:10.1017/s0140525x23003229
From generative hierarchicality to parallel-dialogic syntax: modeling typological protolanguage
Zhong, Y. (2024) · SN Social Sciences · doi:10.1007/s43545-024-00931-8
Methods of examining the processing and production of rule-based sequences in animals
Berthet, M., Leroux, M., Townsend, S. W., & Watson, S. K. (2025) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780192886491.013.26
The evolution of auditory cortex in primates including humans
Rauschecker, J. P., & Orpella, J. (2025) · Evolution of Nervous Systems · doi:10.1016/b978-0-443-27380-3.00040-3
Study of Sequence Encoding in the Prefrontal Cortex of Non-Human Primates
Schmidt, M. D. (2024) · theses.fr (ABES) · doi:10.70675/6c17db3bz5de8z4550z8deezf289d8bb4468
Assembling Neural Latching Switch Circuits for temporally structured behaviorPreprint
Dubreuil, A. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.15.718666
Humans compress order-based structure into short mental programsPreprint
Tabbane, E., Figueira, S. D., Benjamin, L., Dehaene, S., & Roumi, F. A. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.14.725160
Self-citationRhesus macaques show metacognitive sensitivity to artificial grammars
Murugan, R., Antoun, A., Bostick, K. J., Correa, T. S., & Wilson, B. (2026) · Current Biology · doi:10.1016/j.cub.2026.05.018
Processing negation may demonstrate compositionality in rhesus macaques
Antoun, A., Murugan, R., Bostick, K. J., & Wilson, B. (2026) · Cognition · doi:10.1016/j.cognition.2026.106638
Flexibility of hierarchical reasoning across age and species
Dedhe, A. M., Ferrigno, S., Liao, D. A., Nieder, A., Piantadosi, S. T., & Cantlon, J. F. (2026) · Cognition · doi:10.1016/j.cognition.2026.106732
Chunking: What working memory gains and loses
Xie, Y., Zhang, H., & Wang, L. (2026) · Current Biology · doi:10.1016/j.cub.2026.09.028
Self-citation
- Authors
- Jiang, X., Long, T., Cao, W., Li, J., Dehaene, S., & Wang, L.
- Affiliations
- Chinese Academy of Sciences (CN)
- Université Paris-Sud (FR)
- Corresponding author
- Wang, Liping
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 28
- Issue
- 12
- Pages
- 1851-1859.e4
- ISSN
- 0960-9822 (ISSN-L)
- PMC
- PMC6606444
- OpenAlex
- W2805791143
- Cited by
- 89
- References
- 53
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 12 · 2023: 12 · 2022: 11 · 2021: 16 · 2020: 12 · 2019: 6 · 2018: 2
- FWCI
- 12.21
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Current Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- CAS Pioneer Hundreds of Talents Program
- Key Research Program of Frontier Sciences, CAS (QYZDY-SSW-SMC001)
- Shanghai Key Basic Research Project (16JC14202001)
- Collège de France
- Fondation Bettencourt-Schueller (ERC, NeuroSyntax)
- Topics
- Social Sciences › Psychology › Social Psychology › Primate Behavior and Ecology
- Social Sciences › Cultural Studies › Language and cultural evolution
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Keywords
- sequence generation, macaque, nonhuman primate cognition, chunking strategies, human uniqueness, sequence learning, spatial sequence, preschool children
- MeSH terms
- Animals, Child, Child, Preschool, China, Female, Humans, Learning, Linguistics, Macaca mulatta, Male, Memory
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review