Literature DB >> 17537923

Linguistic tone is related to the population frequency of the adaptive haplogroups of two brain size genes, ASPM and Microcephalin.

Dan Dediu1, D Robert Ladd.   

Abstract

The correlations between interpopulation genetic and linguistic diversities are mostly noncausal (spurious), being due to historical processes and geographical factors that shape them in similar ways. Studies of such correlations usually consider allele frequencies and linguistic groupings (dialects, languages, linguistic families or phyla), sometimes controlling for geographic, topographic, or ecological factors. Here, we consider the relation between allele frequencies and linguistic typological features. Specifically, we focus on the derived haplogroups of the brain growth and development-related genes ASPM and Microcephalin, which show signs of natural selection and a marked geographic structure, and on linguistic tone, the use of voice pitch to convey lexical or grammatical distinctions. We hypothesize that there is a relationship between the population frequency of these two alleles and the presence of linguistic tone and test this hypothesis relative to a large database (983 alleles and 26 linguistic features in 49 populations), showing that it is not due to the usual explanatory factors represented by geography and history. The relationship between genetic and linguistic diversity in this case may be causal: certain alleles can bias language acquisition or processing and thereby influence the trajectory of language change through iterated cultural transmission.

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Year:  2007        PMID: 17537923      PMCID: PMC1904158          DOI: 10.1073/pnas.0610848104

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  45 in total

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2.  Neural characteristics of successful and less successful speech and word learning in adults.

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Journal:  Hum Brain Mapp       Date:  2007-10       Impact factor: 5.038

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Review 4.  Genetic links between brain development and brain evolution.

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5.  The detection of disease clustering and a generalized regression approach.

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6.  A forkhead-domain gene is mutated in a severe speech and language disorder.

Authors:  C S Lai; S E Fisher; J A Hurst; F Vargha-Khadem; A P Monaco
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Review 7.  Generalist genes and learning disabilities.

Authors:  Robert Plomin; Yulia Kovas
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8.  Innateness and culture in the evolution of language.

Authors:  Simon Kirby; Mike Dowman; Thomas L Griffiths
Journal:  Proc Natl Acad Sci U S A       Date:  2007-03-12       Impact factor: 11.205

9.  A novel domain suggests a ciliary function for ASPM, a brain size determining gene.

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Journal:  Bioinformatics       Date:  2006-01-27       Impact factor: 6.937

Review 10.  Human microcephaly.

Authors:  C Geoffrey Woods
Journal:  Curr Opin Neurobiol       Date:  2004-02       Impact factor: 6.627

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  53 in total

1.  Human inferior colliculus activity relates to individual differences in spoken language learning.

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Journal:  J Neurophysiol       Date:  2011-11-30       Impact factor: 2.714

2.  A Bayesian phylogenetic approach to estimating the stability of linguistic features and the genetic biasing of tone.

Authors:  Dan Dediu
Journal:  Proc Biol Sci       Date:  2010-09-01       Impact factor: 5.349

3.  Ethnicity effects in relative pitch.

Authors:  Michael J Hove; Mary Elizabeth Sutherland; Carol L Krumhansl
Journal:  Psychon Bull Rev       Date:  2010-06

4.  Subcortical plasticity following perceptual learning in a pitch discrimination task.

Authors:  Samuele Carcagno; Christopher J Plack
Journal:  J Assoc Res Otolaryngol       Date:  2010-09-28

Review 5.  Language and genes: a new perspective on the origins of human cultural diversity.

Authors:  Daniel Nettle
Journal:  Proc Natl Acad Sci U S A       Date:  2007-06-20       Impact factor: 11.205

Review 6.  How culture shaped the human genome: bringing genetics and the human sciences together.

Authors:  Kevin N Laland; John Odling-Smee; Sean Myles
Journal:  Nat Rev Genet       Date:  2010-02       Impact factor: 53.242

7.  Learning a novel phonological contrast depends on interactions between individual differences and training paradigm design.

Authors:  Tyler K Perrachione; Jiyeon Lee; Louisa Y Y Ha; Patrick C M Wong
Journal:  J Acoust Soc Am       Date:  2011-07       Impact factor: 1.840

Review 8.  Genes, cognition, and communication: insights from neurodevelopmental disorders.

Authors:  D V M Bishop
Journal:  Ann N Y Acad Sci       Date:  2009-03       Impact factor: 5.691

9.  A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis.

Authors:  Carlos Riveros; Drew Mellor; Kaushal S Gandhi; Fiona C McKay; Mathew B Cox; Regina Berretta; S Yahya Vaezpour; Mario Inostroza-Ponta; Simon A Broadley; Robert N Heard; Stephen Vucic; Graeme J Stewart; David W Williams; Rodney J Scott; Jeanette Lechner-Scott; David R Booth; Pablo Moscato
Journal:  PLoS One       Date:  2010-12-01       Impact factor: 3.240

10.  Real-time correlates of phonological quantity reveal unity of tonal and non-tonal languages.

Authors:  Juhani Järvikivi; Martti Vainio; Daniel Aalto
Journal:  PLoS One       Date:  2010-09-08       Impact factor: 3.240

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