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Evolution of language: Lessons from the genome

Overview of attention for article published in Psychonomic Bulletin & Review, July 2016
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Title
Evolution of language: Lessons from the genome
Published in
Psychonomic Bulletin & Review, July 2016
DOI 10.3758/s13423-016-1112-8
Pubmed ID
Authors

Simon E. Fisher

Abstract

The post-genomic era is an exciting time for researchers interested in the biology of speech and language. Substantive advances in molecular methodologies have opened up entire vistas of investigation that were not previously possible, or in some cases even imagined. Speculations concerning the origins of human cognitive traits are being transformed into empirically addressable questions, generating specific hypotheses that can be explicitly tested using data collected from both the natural world and experimental settings. In this article, I discuss a number of promising lines of research in this area. For example, the field has begun to identify genes implicated in speech and language skills, including not just disorders but also the normal range of abilities. Such genes provide powerful entry points for gaining insights into neural bases and evolutionary origins, using sophisticated experimental tools from molecular neuroscience and developmental neurobiology. At the same time, sequencing of ancient hominin genomes is giving us an unprecedented view of the molecular genetic changes that have occurred during the evolution of our species. Synthesis of data from these complementary sources offers an opportunity to robustly evaluate alternative accounts of language evolution. Of course, this endeavour remains challenging on many fronts, as I also highlight in the article. Nonetheless, such an integrated approach holds great potential for untangling the complexities of the capacities that make us human.

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The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 <1%
Unknown 132 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 17%
Researcher 21 16%
Student > Bachelor 16 12%
Professor 12 9%
Student > Master 11 8%
Other 28 21%
Unknown 22 17%
Readers by discipline Count As %
Psychology 25 19%
Neuroscience 16 12%
Biochemistry, Genetics and Molecular Biology 13 10%
Linguistics 11 8%
Agricultural and Biological Sciences 10 8%
Other 30 23%
Unknown 28 21%