Language Evolution and Computation Bibliography

The evolution of language and the evolution of the brain are tightly interlinked. Language evolution represents a special kind of adaptation, in part because language is a complex behavior (as opposed to a physical feature) but also because changes are adaptive only to the extent that they increase either one's understanding of others, or one's understanding to others. Evolutionary changes in the human brain that are thought to be relevant to language are reviewed. The extent to which these changes are a cause or consequence of language evolution is a good question, but it is argued that the process may best be viewed as a complex adaptive system, in which cultural learning interacts with biology iteratively over time to produce language.

The evolutionary process works by modifying pre-existing mechanisms, which makes continuity likely. A review of the evidence available to date suggests that there are many aspects of language that show evolutionary continuity, though the direct evidence for syntax and grammar is less clear. However, the universal features of grammar in modern human languages appear to be essentially descriptions of aspects of our basic conceptual universe. It is argued that the most parsimonious model of language evolution involves an increase in conceptual/semantic complexity, which in turn drove the acquisition of syntax and grammar. In this model, universal features of grammar are actually simply reflections of our internal conceptual universe, which are manifested culturally in a variety of ways that are consistent with our pre-linguistic cognitive abilities. This explains both why grammatical rules vary so much across languages, as well as the fact that the commonalities appear to be inherently semantic in nature. An understanding of the way in which concepts are instantiated in the brain, combined with a comparative perspective on brain structure/function relationships, suggest a tight relationship between increasing brain size during hominid evolution and increasing conceptual complexity. A simulation using populations of interacting artificial neural-net agents illustrating this hypothesis is described. The association of brain size and conceptual complexity suggests that language has a deep ancestry.