Manuscript submitted for inclusion in Kimbrough Oller, D., U. Griebel and K. Plunkett (Eds.), The Evolution of Communication Systems: A Comparative Approach. The Vienna Series in Theoretical Biology. Cambridge MA: MIT Press,.

The Role of Learning and Development in Language Evolution: A Connectionist Perspective

Morten H. Christiansen, & Rick Dale

Introduction

Much ink has been spilled arguing over the idea that ontogeny recapitulates phylogeny. The discussions typically center on whether developmental stages reflect different points in the evolution of some specific trait, mechanism, or morphological structure. For example, the development trend from crawling to walking in human infants can be seen as recapitulating the evolutionary change from quadropedalism to bipedalism in the hominid lineage. Closer to the area of the evolution of communication, endocasts have been taken to indicate that the vocal tract of newborn human infants more closely resemble those of Australopithecines and extant primates than the adult human vocal tract — with the vocal tract of Neanderthals falling in between, roughly corresponding to that of a two-year-old human child (Lieberman, 1998). These data could suggest that the development of the vocal tract in human ontogeny is recapitulating the evolution of the vocal tract in hominid phylogeny. However, other researchers have strongly opposed such perspectives, arguing that evolution and development work along entirely different lines when it comes to language (Pinker & Bloom, 1990). In this chapter, we provide a different perspective on this discussion within the domain of linguistic communication, arguing that phylogeny to a large extent has been shaped by ontogeny.

A growing bulk of work on the evolution of language has focused on the role of learning – often in the guise of “cultural transmission” – in the evolution of linguistic communication (e.g., Batali, 1998; Christiansen, 1994; Deacon, 1997; Kirby & Hurford, 2002). Instead of concentrating on biological changes to accommodate language, this approach stresses the adaptation of linguistic structures to the biological substrate of the human brain. Languages are viewed as dynamical systems of communication, subject to selection pressures arising from limitations on human learning and processing. From this perspective language evolution can be construed as being shaped by language development, rather than vice versa.

Computational simulations have proved to be a useful tool to investigate the impact of learning on the evolution of language. Connectionist models (also sometimes referred to as “artificial neural networks” or “parallel distributed processing models”) provide a natural framework for exploring a learning-based perspective on language evolution because they have previously been applied extensively to model the development of language (see e.g., Bates & Elman, 1993; MacWhinney, in press; Plunkett 1995; Seidenberg & MacDonald, 2001; for reviews). In this chapter, we show how language phylogeny may have been shaped by ontogenetic constraints on language acquisition. First, we discuss connectionist models in which the explanations of particular aspects of language evolution and linguistic change depend crucially on the learning properties of specific networks – properties that have also been pressed into service to explain similar aspects of language acquisition. We then present two simulations that directly demonstrate how network learning biases over generations can shape the very language being learned. Finally, we conclude the chapter with a brief discussion of the possible theoretical advantages of approaching language evolution from a learning-based perspective.

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