Skip to main content
Log in

First Words Learning: A Cortical Model

  • Published:
Cognitive Computation Aims and scope Submit manuscript

Abstract

Humans come to recognize an infinite variety of natural and man-made objects in their lifetime and make use of sounds to identify and categorize them. How does this lifelong learning process begin? Many hypotheses have been proposed to explain the learning of first words with some emerging from the particular characteristics observed in child development. One is the peculiar trend in the speed with which words are learned, which have been referred to in the literature as “fast mapping”. We present a neural network model trained in stages that parallel developmental ones and that simulates cortical processes of self-organization during an early crucial stage of first word learning. This is done by taking into account strictly visual and acoustic perceptions only. The results obtained show evidence of the emergence in the artificial maps used in the model, of cortical functions similar to those found in the biological correlates in the brain. Evidence of non-catastrophic fast mapping based on the quantity of objects and labels gradually learned by the model is also found. We interpret these results as meaning that early stages of first word learning may be explained by strictly perceptual learning processes, coupled with cortical processes of self-organization and of fast mapping. Specialized word-learning mechanisms thus need not be invoked, at least not at an early word-learning stage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Bednar JA. Learning to see: genetic and environmental influences on visual development. Ph.D. thesis, University of Texas at Austin, tech Report AI-TR-02-294 2002.

  2. Belin P, Zatorre RJ, Ahad P. Human temporal-lobe response to vocal sounds. Cogn Brain Res. 2002;13:17–26.

    Article  Google Scholar 

  3. Biederman I. Recognition-by-components: a theory of human image understanding. Psychol Rev. 1987;94:115–47.

    Article  CAS  PubMed  Google Scholar 

  4. Black AW, Taylor PA. The festival speech synthesis system: System documentation. Tech Rep HCRC/TR-83, Human Communcation Research Centre, University of Edinburgh, Edinburgh 1997.

  5. Booth AE, Waxman SR. Word learning is smart: evidence that conceptual information affects preschoolers’ extension of novel words. Cognition. 2002;84:B11–B22.

    Article  PubMed  Google Scholar 

  6. Brewer AA, Liu J, Wade AR, Wandell BA. Visual field maps and stimulus selectivity in human ventral occipital cortex. Nat Neurosci. 2005;8:1102–9.

    Article  CAS  PubMed  Google Scholar 

  7. Carey S. The child as word learner. In: Halle M, Bresnan J, Miller G, editors. Linguistic theory and psychological reality. Cambridge: MIT Press;1978. pp. 264–93.

    Google Scholar 

  8. Carey S, Spelke E. Science and core knowledge. J Philos Sci. 1996;63:515–33.

    Article  Google Scholar 

  9. Dannemiller JL. A test of color constancy in 9-and 20-weeks-old human infants following simulated illuminant changes. Dev Psychol. 1989;25:171–84.

    Article  Google Scholar 

  10. Dickinson DK. First impressions: children’s knowledge of words gained from a single exposure. Appl Psycholinguist. 1984;5:359–73.

    Article  Google Scholar 

  11. Diesendruck G, Bloom P. How specific is the shape bias?. Child Dev. 2003;74:168–78.

    Article  PubMed  Google Scholar 

  12. Eimas PD, Quinn PC. Studies on the formation of perceptually based basic-level categories in young infants. Child Dev. 1994;3:903–17.

    Article  Google Scholar 

  13. Escabi MA, Read HL. Representation of spectrotemporal sound information in the ascending auditory pathway. Biol Cybern. 2003;89:350–62.

    Article  PubMed  Google Scholar 

  14. Ganger J, Brent MR. Reexamining the vocabulary spurt. Dev Psychol. 2004;40:621–32.

    Article  PubMed  Google Scholar 

  15. Gershkoff-Stowe L, Smith LB. Shape and the first hundred nouns. Child Dev. 2004;75:1098–114.

    Article  PubMed  Google Scholar 

  16. Gopnik A, Nazzi T. Words, kinds, and causal powers: a theory theory perspective on early naming and categorization. In: Rakison DH, editors. Early category and concept development. Oxford: Oxford University Press;2003. pp. 303–29.

    Google Scholar 

  17. Grill-Spector K, Kourtzi Z, Kanwisher N. The lateral occipital complex and its role in object recognition. Vision Res. 2001;41:1409–422.

    Article  CAS  PubMed  Google Scholar 

  18. Hebb DO. The organization of behavior. New York: Wiley;1949.

    Google Scholar 

  19. Kanwisher N. The ventral visual object pathway in humans: evidence from fMRI. In: Chalupa L, Werner J, editors. The visual neurosciences. Cambridge: MIT Press;2003.

    Google Scholar 

  20. Kemler Nelson DG, Frankenfield A, Morris C, Blair E. Young children’s use of functional information to categorize artifacts: three factors that matter. Cognition. 2000;77:133–68.

    Article  CAS  PubMed  Google Scholar 

  21. Kohonen T. Self-organizing formation of topologically correct feature maps. Biol Cybern. 1982;43:59–69.

    Article  Google Scholar 

  22. Kohonen T. Self-organizing maps. Berlin: Springer;1995.

    Google Scholar 

  23. Kripke SA. Naming and necessity. In: Davidson D, Harman GH, editors. Semantics of natural language. Dordrecht: Reidel Publishing Company;1972. pp. 253–355.

    Google Scholar 

  24. Landau B, Smith LB, Jones S. The importance of shape in early lexical learning. Cogn Dev. 1988;3:299–321.

    Article  Google Scholar 

  25. Malach R, Reppas JB, Benson RR, Kwong KK, Jiang H, Kennedy WA, Ledden PJ, Brady TJ, Rosen BR, Tootell RB. Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex. Procee Nat Acad Sci USA. 1995;92:8135–139.

    Google Scholar 

  26. Mandler JM. The foundations of mind. Oxford: Oxford University Press;2004.

    Google Scholar 

  27. Markson L, Bloom P. Evidence against a dedicated system for word learning in children. Nature. 1997;385:813–15.

    Article  CAS  PubMed  Google Scholar 

  28. Mazzone M, De la Cruz V, Plebe A. Una simulazione biologicamente orientata dell’apprendimento di aggettivi: tra categorizzazione e concettualizzazione. Sist Intelligenti. 2008;20:293–305.

    Google Scholar 

  29. Michotte A. La Perception de la causalité. Editions de l’Institut supérieur de Philosophie, Louvain, english translation by TR Miles, E Miles, Methuen, London 1963;1946.

  30. Murphy GL, Medin DL. The role of theories in conceptual coherence. Psychol Rev. 1985;92:289–316.

    Article  CAS  PubMed  Google Scholar 

  31. Nayar S, Murase H. Visual learning and recognition of 3-d object by appearance. Int J Comput Vis. 1995;14:5–24.

    Article  Google Scholar 

  32. Nazzi T, Bertoncini J. Before and after the vocabulary spurt: two modes of word acquisition?. Dev Sci. 2003;6:136–42.

    Article  Google Scholar 

  33. Plebe A. Learning visual invariance. In: Verleysen M, editors. ESANN 2006—14th European Symposium on Artificial Neural Networks. Evere: d-side Publications;2003. pp. 71–6.

  34. Plebe A. A model of angle selectivity development in visual area V2. Neurocomputing. 2007;70:2060–6.

    Article  Google Scholar 

  35. Plebe A. The ventral visual path: moving beyond V1 with computational models. In: Portocello TA, Velloti RB (eds) Visual cortex: new research. New York: Nova Science;2008. pp. 97–160.

    Google Scholar 

  36. Plebe A, Domenella RG. Early development of visual recognition. BioSystems. 2006;86:63–74.

    Article  PubMed  Google Scholar 

  37. Plebe A, Domenella RG. Object recognition by artificial cortical maps. Neural Netw. 2007;20:763–80.

    Article  PubMed  Google Scholar 

  38. Plebe A, De la Cruz V, Mazzone M. Synthetic learners of objects and names. In: Demiris Y, Scassellati B, Mareschal D, editors. Proceedings of the 6th International Conference on Development and Learning, IEEE;2007. pp. 300–5.

  39. Plebe A, De la Cruz V, Mazzone M. Modeling language emergence by way of working memory. In: Smith ADM, Smith K, Ferrer i Cancho R, editors. The Evolution of Language: Proceedings of the 7th International Conference (EVOLANG7). Singapore: World Scientific Press;1976. pp. 480–1.

  40. Pruden SM, Hirsh-Pasek K, Golinkoff RM, Hennon EA. The birth of words: ten-month-olds learn words through perceptual salience. Child Dev. 2006;77:266–80.

    Article  PubMed  Google Scholar 

  41. Putnam H. The meaning of “meaning”. In: Putnam H, editors. Mind, language and reality, vol 2. Cambridge: MIT Press;1975.

    Chapter  Google Scholar 

  42. Regier T. The emergence of words: attentional learning in form and meaning. Cogn Sci. 2005;29:819–65.

    Article  Google Scholar 

  43. Rogers TT, McClelland JL. Semantic Cognition—a parallel distributed processing approach. Cambridge;MIT Press;2006.

    Google Scholar 

  44. Scholl BJ, Tremoulet PD. Perceptual causality and animacy. Trends Cogn Sci. 2000;4:299–309.

    Article  PubMed  Google Scholar 

  45. Searle JR. Intentionality: an essay in the philosophy of mind. Cambridge: Cambridge University Press;1983.

    Google Scholar 

  46. Sengpiel F, Kind PC. The role of activity in development of the visual system. Current Biol. 2002;12:818–26.

    Article  Google Scholar 

  47. Sirosh J, Miikkulainen R. Topographic receptive fields and patterned lateral interaction in a self-organizing model of the primary visual cortex. Neural Comput. 1997;9:577–94.

    Article  CAS  PubMed  Google Scholar 

  48. Smith LB. How domain-general processes may create domain-specific biases. In: Bowerman M, Levinson S, editors. Language acquisition and conceptual development. Cambridge: Cambridge University Press;2001.

    Google Scholar 

  49. Smith LB. Shape: A developmental product. In: Carlson L, VanderZee E, editors. Functional features in language and space. Oxford: Oxford University Press;2005.

    Google Scholar 

  50. Tomasello M. The cultural origins of human cognition. Cambridge: Harvard University Press;1999.

    Google Scholar 

  51. Tomasello M. Constructing a language: a usage-based theory of language acquisition. Cambridge: Harvard University Press;2003.

    Google Scholar 

  52. Turrigiano GG, Nelson SB. Homeostatic plasticity in the developing nervous system. Nat Rev Neurosci. 2004;391:892–6.

    Google Scholar 

  53. Vanduffel W, Tootell RB, Schoups AA, Orban GA. The organization of orientation selectivity throughout the macaque visual cortex. Cereb Cortex. 2002;12:647–62.

    Article  PubMed  Google Scholar 

  54. Verkindt C, Bertrand O, Echallier F, Pernier J. Tonotopic organization of the human auditory cortex: N100 topography and multiple dipole model analysis. Electroencephalogr Clin Neurophysiol. 1995;96:143–56.

    Article  CAS  PubMed  Google Scholar 

  55. von der Malsburg C. Self-organization of orientation sensitive cells in the striate cortex. Kibernetic. 1973;14:85–100.

    Article  Google Scholar 

  56. Wallis G, Rolls E. Invariant face and object recognition in the visual system. Prog Neurobiol. 1997;51:167–94.

    Article  CAS  PubMed  Google Scholar 

  57. Willshaw DJ, von der Malsburg C. How patterned neural connections can be set up by self-organization. Procee Royal Soci London. 1976;B194:431–45.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alessio Plebe.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Plebe, A., Mazzone, M. & De la Cruz, V. First Words Learning: A Cortical Model. Cogn Comput 2, 217–229 (2010). https://doi.org/10.1007/s12559-010-9044-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12559-010-9044-5

Keywords

Navigation