The Evolution of Speech and Language

Living reference work entry

Abstract

Human speech, language, and cognition derive from anatomy and neural mechanisms that have been shaped by the Darwinian process of natural selection acting on variation but that have roots present in other living species. Language did not suddenly arise 50,000–100,000 years ago through a mutation that yielded an innate “faculty of language ” nor does the human brain include an organ devoted to language and language alone. Broca’s area is not the center of language. Neural circuits linking local activity in different neural structures regulate complex behaviors. Neural circuits that were present in early mammal-like reptiles play a part in regulating laryngeal phonation, conveying both referential information and emotion. Speech plays a central role, enabling transmission of information at a rate that exceeds the auditory fusion frequency. The unique human tongue enhances the robustness of speech, but Neanderthals and other archaic hominins whose neck and skull proportions preclude their having an adult-like human tongue nevertheless could talk. Comparative studies of present-day apes suggest that hominin “protolanguage” lacking syntax never existed. The neural bases of human language are not domain-specific – in other words, they are not devoted to language alone. Mutations on the FOXP2 transcriptional gene shared by humans, Neanderthals, and at least one other archaic species enhanced synaptic plasticity in cortical–basal ganglia circuits that are implicated in motor behavior, cognitive flexibility, language, and associative learning. A selective sweep occurred about 200,000 years ago on a unique human version of this gene. Other transcriptional genes appear to be implicated in enhancing cortical–basal ganglia and other neural circuits.

Keywords

Basal Ganglion Neural Circuit Vocal Tract Hyoid Bone Human Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Brown UniversityProvidenceUSA
  2. 2.Department of Biological SciencesBenedictine UniversityLisleUSA

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