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mitecs_logo  The Cognitive Neurosciences IV : Table of Contents: The Biology and Evolution of Language: “Deep Homology” and the Evolution of Innovation : Abstract
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The Biology and Evolution of Language: “Deep Homology” and the Evolution of Innovation

Abstract

<span style="font-variant: small-caps">abstract</span>

The last decade has seen rapid and impressive progress in understanding the biology and evolution of complex “innovative” traits (e.g., insect wings or vertebrate eyes), and the fruits of this understanding are beginning to have an impact on our understanding of that most innovative of human traits: language. Although language, as a whole, is unique to Homo sapiens, many of the neural and cognitive mechanisms supporting language are shared with other species. An empirically based, mechanistic understanding of the evolution of language therefore requires research on both unique aspects of language (such as complex syntax) and broadly shared features. Evolutionary developmental biology (“evo-devo”) has added a new twist to this distinction, with the discovery that traits shared due to convergent evolution (such as vocal learning in humans and birds) may nonetheless be based on homologous genes and developmental pathways. Such “deep homologies” may involve convergence at the phenotypic level and homology at the genotypic level, and illustrate the need to rethink traditional ideas about homology. Studies of eyes, limbs, and body plans have revealed deep homologies in all these systems. Here, I suggest that language is also likely to have its share of deep homologies, and that this possibility provides a powerful rationale for investigations of convergently evolved traits in widely separated species. I illustrate the potential of this new approach with an exploration of the neural and genetic basis of vocal learning in humans and birds. I conclude that neuroethological investigations of diverse vertebrate species, from fish to birds to mice, will powerfully augment more traditional work on primates in the search for the neural mechanisms underlying language.

 
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