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  • Print publication year: 2018
  • Online publication date: November 2017

10 - Genetic Biases in Language: Computer Models and Experimental Approaches

from Part IV - Social and Language Evolution


Computer models of cultural evolution have shown language properties emerging on interacting agents with a brain that lacks dedicated, nativist language modules. Notably, models using Bayesian agents provide a precise specification of (extra-)liguististic factors (e.g., genetic) that shape language through iterated learning (biases on language), and demonstrate that weak biases get expressed more strongly over time (bias amplification). Other models attempt to lessen assumption on agents’ innate predispositions even more, and emphasize self-organization within agents, highlighting glossogenesis (the development of language from a nonlinguistic state). Ultimately however, one also has to recognize that biology and culture are strongly interacting, forming a coevolving system. As such, computer models show that agents might (biologically) evolve to a state predisposed to language adaptability, where (culturally) stable language features might get assimilated into the genome via Baldwinian niche construction. In summary, while many questions about language evolution remain unanswered, it is clear that it is not to be completely understood from a purely biological, cognitivist perspective. Language should be regarded as (partially) emerging on the social interactions between large populations of speakers. In this context, agent models provide a sound approach to investigate the complex dynamics of genetic biasing on language and speech.


Biasing Language

In this chapter, we argue not only that the best approach to understanding the origins and present-day diversity of language is rooted in evolutionary theory, but also that extra-linguistic factors, more specifically biological ones in our genes, may play an important role in shaping language. Likewise, these factors do not act in a void, but interact with multiple constraints and affordances on different scales in parallel. So-called cultural evolution of language (Section 10.1.2) must thus be seen in a rich context (partially) molded by the biological and cognitive entities that ultimately acquire, use, and transmit language – us. Important factors in this context are therefore represented not only by the brain – it has been recognized for a while now that the brain indeed shapes language (Christiansen & Chater 2008) – but also by the anatomy and physiology of the vocal tract and hearing organs.

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Language, Cognition, and Computational Models
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Baldwin, J. M. (1896), ‘A new factor in evolution’, American naturalist pp. 536–553.
Ball, P. (1999), The self-made tapestry: Pattern formation in nature, Oxford University Press.
Baronchelli, A., Chater, N., Christiansen, M. H. & Pastor-Satorras, R. (2013), ‘Evolution in a changing environment’, PloS one 8(1), e52742.
Baronchelli, A., Chater, N., Pastor-Satorras, R. & Christiansen, M. H. (2012), ‘The biological origin of linguistic diversity’, PloS one 7(10), e48029.
Bernardo, J. M. & Smith, A. F. (2009), Bayesian theory, Vol. 405, John Wiley & Sons.
Bouckaert, R., Lemey, P., Dunn, M., Greenhill, S. J., Alekseyenko, A. V., Drummond, A. J., Gray, R. D., Suchard, M. A. & Atkinson, Q. D. (2012), ‘Mapping the origins and expansion of the Indo-European language family’, Science 337(6097), 957– 960.
Burkett, D. and Griffiths, T. L. (2010), ‘Iterated learning of multiple languages from multiple teachers’, The evolution of language: Proceedings of Evolang pp. 58–65.
Butcher, A. (2006), Australian Aboriginal languages: Consonant-salient phonologies and the ‘place-of-articulation imperative’, New York and Hove: Psychology Press, pp. 187–210.
Calvin, W. H. (2002), A brain for all seasons: Human evolution and abrupt climate change, University of Chicago Press.
Campbell, L. & Poser, W. J. (2008), Language classification: History and method, Cambridge University Press.
Carroll, S. B. (2005), Endless forms most beautiful: The new science of evo devo and the making of the animal kingdom, number 54, W.W. Norton & Company.
Chater, N., Reali, F. & Christiansen, M. H. (2009), ‘Restrictions on biological adaptation in language evolution’, Proceedings of the National Academy of Sciences 106(4), 1015–1020.
Chomsky, N. (1965), Aspects of the theory of syntax, number 11, MIT press.
Chomsky, N. (1986), Knowledge of language: Its nature, origin, and use, Greenwood Publishing Group.
Christiansen, M. H. & Chater, N. (2008), ‘Language as shaped by the brain’, Behavioral and Brain Sciences 31(05), 489–509.
Croft, W. (2000), Explaining language change: An evolutionary approach, Pearson Education.
Dávid-Barrett, T. & Dunbar, R. (2013), ‘Processing power limits social group size: Computational evidence for the cognitive costs of sociality’, Proceedings of the Royal Society B: Biological Sciences 280(1765).
Dawkins, R. (1976), The selfish gene, Oxford University Press.
de Boer, B. (2000a), ‘Emergence of vowel systems through self-organisation’, AI Communications 13(1), 27–39.
de Boer, B. (2000b), ‘Self-organization in vowel systems’, Journal of Phonetics 28(4), 441–465.
de Boer, B. & Fitch, W. T. (2010), ‘Computer models of vocal tract evolution: An overview and critique’, Adaptive Behavior 18(1), 36–47.
de Boer, B. & Zuidema, W. (2010), ‘Multi-agent simulations of the evolution of combinatorial phonology’, Adaptive Behavior 18(2), 141–154.
Deacon, T. (1997), The symbolic species: The co–evolution of language and the brain, number 202, WW Norton & Company.
Dediu, D. (2008), ‘The role of genetic biases in shaping the correlations between languages and genes’, Journal of Theoretical Biology 254(2), 400–407.
Dediu, D. (2009), ‘Genetic biasing through cultural transmission: Do simple Bayesian models of language evolution generalise?’, Journal of Theoretical Biology 259(3), 552–561.
Dediu, D. (2011), ‘Are languages really independent from genes? If not, what would a genetic bias affecting language diversity look like?’, Human Biology 83(2), 279– 296.
Dediu, D. & Levinson, S. C. (2013), ‘On the antiquity of language: The reinterpretation of Neandertal linguistic capacities and its consequences’, Frontiers in Psychology 4.
Dunn, M., Greenhill, S. J., Levinson, S. C. & Gray, R. D. (2011), ‘Evolved structure of language shows lineage-specific trends in word-order universals’, Nature 473(7345), 79–82.
Everett, C., Blasi, D. E. & Roberts, S. G. (2015), ‘Climate, vocal folds, and tonal languages: Connecting the physiological and geographic dots’, Proceedings of the National Academy of Sciences 112(5), 1322–1327.
Farrell, S., Wagenmakers, E.-J. & Ratcliff, R. (2006), ‘1/f noise in human cognition: Is it ubiquitous, and what does it mean?’, Psychonomic Bulletin & Review 13(4), 737– 741.
Fehér, O., Wang, H., Saar, S., Mitra, P. P. and Tchernichovski, O. (2009), ‘De novo establishment of wild-type song culture in the zebra finch’, Nature 459(7246), 564– 568.
Ferdinand, V. and Zuidema,W. (2009), Thomas' theoremmeets Bayes' rule: A model of the iterated learning of language, in ‘Proceedings of the 31st Annual Conference of the Cognitive Science Society’, Cognitive Science Society Austin, TX, pp. 1786–1791.
Fisher, S. E. (2006), ‘Tangled webs: Tracing the connections between genes and cognition’, Cognition 101(2), 270–297.
Fodor, J. A. (1983), The modularity of mind: An essay on faculty psychology, MIT Press.
Gould, S. J. & Vrba, E. S. (1982), ‘Exaptation – a missing term in the science of form’, Paleobiology, pp. 4–15.
Gray, R. D. & Atkinson, Q. D. (2003), ‘Language-tree divergence times support the Anatolian theory of Indo-European origin’, Nature 426(6965), 435–439.
Griffiths, T. L. and Kalish, M. L. (2007), ‘Language evolution by iterated learning with bayesian agents’, Cognitive Science 31(3), 441–480.
Hamilton, W. D. (1963), ‘The evolution of altruistic behavior’, American Naturalist pp. 354–356.
Hanke, D. (2004), ‘Teleology: The explanation that bedevils biology’, Explanations: Styles of Explanation in Science, pp. 143–155.
Hebb, D. O. (1949), The organization of behavior: A neuropsychological approach, John Wiley & Sons.
Henrich, J. & McElreath, R. (2003), ‘The evolution of cultural evolution’, Evolutionary Anthropology: Issues, News, and Reviews 12(3), 123–135.
Hinton, G. and Nowlan, S. (1987), ‘How learning can guide evolution’, Complex Systems 1(1), 495–502.
Hockett, C. (1960), ‘The origin of speech’, Scientific American 203, 88–96.
Johnson, K. (2005), Speaker normalization in speech perception, in The handbook of speech perception, John Wiley & Sons, pp. 363–389.
Kirby, S., Cornish, H. & Smith, K. (2008), ‘Cumulative cultural evolution in the laboratory: An experimental approach to the origins of structure in human language’, Proceedings of the National Academy of Sciences 105(31), 10681–10686.
Kirby, S., Dowman, M. and Griffiths, T. L. (2007), ‘Innateness and culture in the evolution of language’, Proceedings of the National Academy of Sciences 104(12), 5241–5245.
Kirby, S. & Hurford, J. R. (2002), The emergence of linguistic structure: An overview of the iterated learning model, in Simulating the evolution of language, Springer, pp. 121–147.
Kohonen, T. (1982), ‘Self-organized formation of topologically correct feature maps’, Biological Cybernetics 43(1), 59–69.
Kohonen, T. (2001), Self-organizing maps, Vol. 30, Springer.
Kröger, R. H. & Biehlmaier, O. (2009), ‘Space-saving advantage of an inverted retina’, Vision Research 49(18), 2318–2321.
Kruschke, J. K. (1992), ‘Alcove: An exemplar-based connectionist model of category learning.’, Psychological Review 99(1), 22.
Ladd, D. R., Dediu, D. & Kinsella, A. R. (2008), ‘Languages and genes: Reflections on biolinguistics and the nature-nurture question’, Biolinguistics 2(1), 114–126.
Ladefoged, P. (1984), Out of chaos comes order? Physical, biological, and structural patterns in phonetics in A., Cohen & M., van den Broecke, eds, Proceedings of the Tenth International Congress of Phonetic Sciences, Foris Publications: Dordrecht, Holland, pp. 83–95.
Ladefoged, P. & Maddieson, I. (1998), ‘The sounds of the world's languages’, Language 74(2), 374–376.
Laland, K. N., Odling-Smee, J. & Myles, S. (2010), ‘How culture shaped the human genome: Bringing genetics and the human sciences together’, Nature Reviews Genetics 11(2), 137–148.
Levinson, S. C. & Gray, R. D. (2012), ‘Tools from evolutionary biology shed new light on the diversification of languages’, Trends in Cognitive Sciences 16(3), 167– 173.
Lin, C. & Shu, F. H. (1964), ‘On the spiral structure of disk galaxies.’, The Astrophysical Journal 140, 646.
Maddieson, I. (1984), Patterns of sounds, Cambridge University Press.
Mameli, M. & Bateson, P. (2006), ‘Innateness and the sciences’, Biology and Philosophy 21(2), 155–188.
Mayley, G. (1996), The evolutionary cost of learning, in Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pp. 458–467.
Mesoudi, A. & Whiten, A. (2008), ‘The multiple roles of cultural transmission experiments in understanding human cultural evolution’, Philosophical Transactions of the Royal Society B: Biological Sciences 363(1509), 3489–3501.
Miller, G. (2001), ‘The mating mind: How sexual choice shaped the evolution of human nature’, Psycoloquy 12(8), 1–15.
Odling-Smee, F. J., Laland, K. N. & Feldman, M. W. (2003), Niche construction: The neglected process in evolution, number 37, Princeton University Press.
Okasha, S. (2006), Evolution and the Levels of Selection, Vol. 16, Clarendon Press Oxford.
Ostrom, J. H. (1976), ‘Archaeopteryx and the origin of birds’, Biological Journal of the Linnean Society 8(2), 91–182.
Oudeyer, P.-Y. (2005a), ‘The self-organization of combinatoriality and phonotactics in vocalization systems’, Connection Science 17(3-4), 325–341.
Oudeyer, P.-Y. (2005b), ‘The self-organization of speech sounds’, Journal of Theoretical Biology 233(3), 435–449.
Pagel, M., Atkinson, Q. D. & Meade, A. (2007), ‘Frequency of word-use predicts rates of lexical evolution throughout Indo-European history’, Nature 449(7163), 717–720.
Perfors, A. (2012), ‘Bayesian models of cognition: What's built in after all?’, Philosophy Compass 7(2), 127–138.
Perfors, A. & Navarro, D. J. (2011), Language evolution is shaped by the structure of the world, in Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Cognitive Science Society.
Perfors, A. and Navarro, D. J. (2014), ‘Language evolution can be shaped by the structure of the world’, Cognitive Science 38(4), 775–793.
Pigliucci, M. (2007), ‘Do we need an extended evolutionary synthesis?’, Evolution 61(12), 2743–2749.
Pinker, S. & Bloom, P. (1990), ‘Natural language and natural selection’, Behavioral and Brain Sciences 13(4), 707–727.
Richerson, P. J. & Boyd, R. (2008), Not by genes alone: How culture transformed human evolution, University of Chicago Press.
Richerson, P. J., Boyd, R. & Henrich, J. (2010), ‘Gene-culture coevolution in the age of genomics’, Proceedings of the National Academy of Sciences 107(Supplement 2), 8985–8992.
Richerson, P. J. & Christiansen, M. H. (2013), Cultural evolution: Society, technology, language, and religion, MIT Press.
Schwartz, J.-L., Boë, L.-J., Vallée, N. & Abry, C. (1997), ‘Major trends in vowel system inventories’, Journal of Phonetics 25(3), 233–253.
Shannon, C. E. (1948), The mathematical theory of communication, University of Illinois Press.
Smith, K. (2001), The evolution of learning mechanisms supporting symbolic communication, in CogSci2001, the 23rd Annual Conference of the Cognitive Science Society, Citeseer.
Smith, K. (2009), Iterated learning in populations of bayesian agents, in Proceedings of the 31st annual conference of the cognitive science society, Austin, TX: Cognitive Science Society, pp. 697–702.
Smith, K. and Kirby, S. (2008), ‘Cultural evolution: Implications for understanding the human language faculty and its evolution’, Philosophical Transactions of the Royal Society B: Biological Sciences 363(1509), 3591–3603.
Smith, K., Tamariz, M. & Kirby, S. (2013), Linguistic structure is an evolutionary tradeoff between simplicity and expressivity, in Proceedings of Cogsci 2013, pp. 1348– 1353.
Turney, P. (1996),Myths and legends of the Baldwin Effect, in Proceedings of the Workshop on Evolutionary Computing and Machine Learning at the 13th International Conference on Machine Learning, pp. 135–142.
Verhoef, T. & de Boer, B. (2011), Cultural emergence of feature economy in an artificial whistled language, in Proceedings of the 17th international congress of phonetic sciences. Hong Kong: City University of Hong Kong, pp. 2066–2069.
Verhoef, T., de Boer, B. & Kirby, S. (2012), Holistic or synthetic protolanguage: Evidence from iterated learning of whistled signals, in The evolution of language: Proceedings of the 9th international conference (EVOLANG9), World Scientific, pp. 368–375.
Waddington, C. H. (1942), ‘Canalization of development and the inheritance of acquired characters’, Nature 150(3811), 563–565.
Williams, G. C. (1966), Adaptation and natural selection: A critique of some current evolutionary thought, Princeton University Press.
Wilson, D. S. & Wilson, E. O. (2008), ‘Evolution “for the good of the group”’, American Scientist 96(5), 380–389.
Wynne-Edwards, V. C. (1962), Animal dispersion in relation to social behaviour, Hafner Pub. Co.
Wynne-Edwards, V. C. (1986), Evolution through group selection, Blackwell Scientific.
Zipf, G. K. (1949), Human behavior and the principle of least effort, Addison-Wesley.
Zuidema, W. & de Boer, B. (2009), ‘The evolution of combinatorial phonology’, Journal of Phonetics 37(2), 125–144.
Zwicker, E. (1961), ‘Subdivision of the audible frequency range into critical bands (Frequenzgruppen)’, The Journal of the Acoustical Society of America 33(2), 248–248.