Linguistic tone is related to the population frequency of the adaptive haplogroups of two brain size genes,
            <i>ASPM</i>
            and
            <i>Microcephalin</i>

Dediu, Dan; Ladd, D. Robert

doi:10.1073/pnas.0610848104

Cited by 245 publications

(255 citation statements)

References 57 publications

(48 reference statements)

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“…The existence of causal correlations between inter-population genetic and linguistic diversities of the type suggested by Dediu and Ladd (2007) is potentially very important for a better understanding of the biological bases of language as well as the evolution of language and linguistic diversity (for a detailed discussion of these issues in the context of biolinguistics see Ladd et al, 2008). A very convincing support for the fact that learning biases can affect the outcome of trans-generational learning is provided, for example, by Feher et al (2008), which reared in social and acoustic isolation song-learning male zebra finches, resulting in highly abnormal songs.…”

Section: Discussionmentioning

confidence: 99%

“…For each run, there are two types of measures of interest: those reflecting the overall correlations between genetic diversity, linguistic diversity and geography, on one hand, and the specific correlations between the frequencies of the alleles and the frequencies of linguistic features across populations, on the other. For the first type of measures, Mantel correlations (Mantel, 1967) 7 involving the genetic distances (Nei, 1972; considering both G 1 and G 2 ), linguistic distances (Euclidean distances on the space of both features F 1 and F 2 ; Dediu and Ladd, 2007) and geographic distances (Euclidean distances between regions) between populations were computed: GenGeo (genetic and geographic 6 Given that the alleles are selectively neutral and independent, the only evolutionary process affecting their frequencies is random drift in large populations, so that these frequencies tend to remain constant during the simulations.…”

Section: The Modelmentioning

confidence: 99%

“…In their recent paper, Dediu and Ladd (2007) argued for the existence of a correlation between the population frequency of the derived haplogroups of two brain growth and development related genes, ASPM and Microcephalin, and the usage of linguistic tone in the language (s) spoken by that population. To this end, they used a world sample of 49 populations for which information was collected for 983 alleles and 26 linguistic features, while controlling for geographical distance and known historical linguistic relationships.…”

Section: Introductionmentioning

confidence: 99%

“…The exact nature of this genetic bias is not specified, but it is argued that it involves three components (Dediu and Ladd, 2007): i. from interindividual genetic differences to differences in brain structure and function,…”

Section: Introductionmentioning

confidence: 99%

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The role of genetic biases in shaping the correlations between languages and genes

Dediu

2008

Journal of Theoretical Biology

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It has recently been proposed (Dediu, D., Ladd, D.R., 2007. Linguistic tone is related to the population frequency of the adaptive haplogroups of two brain size genes, ASPM and Microcephalin. Proc Natl Acad Sci USA 104, 10944-10949) that genetically coded linguistic biases can influence the trajectory of language change. However, the nature of such biases and the conditions under which they can become manifest have remained vague. The present paper explores computationally two plausible types of linguistic acquisition biases in a population of agents implementing realistic genetic, linguistic and demographic processes. One type of bias represents an innate asymmetric initial state (Initial Expectation bias)while the other an innate asymmetric facility of acquisition (Rate of Learning bias). It was found that only the second type of bias produces detectable effects on language through cultural transmission across generations and that such effects are produced even by weak biases present at low frequencies in the population. This suggests that learning preference asymmetries, very small at the individual level and not very frequent at the population level, can bias the trajectory of language change through the process of cultural transmission.

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Section: Discussionmentioning

confidence: 99%

Section: The Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The role of genetic biases in shaping the correlations between languages and genes

Dediu

2008

Journal of Theoretical Biology

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“…It has been shown, for example, that the ability to identify incorrect tones in familiar melodies is a highly heritable trait, with genetic factors explaining up to 80% of variability in this ability (Drayna et al 2001). Moreover, there is evidence that the adoption of tone languages is associated with the frequency in the population of specific alleles of two genes related to brain growth, and this association is hard to explain by geographical or historical factors (Dediu and Ladd 2007). Studies comparing pitch-processing measures between different populations of listeners cannot disentangle the contribution of neural plasticity from the contribution of genetic factors to the differences measured.…”

Section: Subcortical Plasticity In the Auditory Systemmentioning

confidence: 99%

Subcortical Plasticity Following Perceptual Learning in a Pitch Discrimination Task

Carcagno

Plack

2010

JARO

134

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Practice can lead to dramatic improvements in the discrimination of auditory stimuli. In this study, we investigated changes of the frequency-following response (FFR), a subcortical component of the auditory evoked potentials, after a period of pitch discrimination training. Twenty-seven adult listeners were trained for 10 h on a pitch discrimination task using one of three different complex tone stimuli. One had a static pitch contour, one had a rising pitch contour, and one had a falling pitch contour. Behavioral measures of pitch discrimination and FFRs for all the stimuli were measured before and after the training phase for these participants, as well as for an untrained control group (n=12). Trained participants showed significant improvements in pitch discrimination compared to the control group for all three trained stimuli. These improvements were partly specific for stimuli with the same pitch modulation (dynamic vs. static) and with the same pitch trajectory (rising vs. falling) as the trained stimulus. Also, the robustness of FFR neural phase locking to the sound envelope increased significantly more in trained participants compared to the control group for the static and rising contour, but not for the falling contour. Changes in FFR strength were partly specific for stimuli with the same pitch modulation (dynamic vs. static) of the trained stimulus. Changes in FFR strength, however, were not specific for stimuli with the same pitch trajectory (rising vs. falling) as the trained stimulus. These findings indicate that even relatively low-level processes in the mature auditory system are subject to experience-related change.

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Cerebral Cortex Evolution and the ASPM Gene

Ali

2009

Encyclopedia of Life Sciences

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The cerebral cortex has diversified in many organisms despite having a similar basic plan. Neural cell division at one level and scaling laws at another level can explain interspecies differences in cerebral cortex sizes. Cerebral cortex components are also shaped by adaptive evolution, particularly by ecological and social factors. The genetic basis for brain development has only recently been probed. Guided initially by clinical studies of patients with reduced brain sizes (microcephaly), the gene ASPM has been identified as an important candidate involved in cerebral cortex development. Multiple lines of evidence from evolutionary genetics and functional studies have now implicated the gene in cerebral cortex size evolution across diverse organisms. Given the complexities associated with such a large organ, other genes and their expression patterns as well as noncoding DNA may also play a role in cerebral cortex evolution. Key concepts: Higher organisms such as mammals and birds show diversity in cerebral cortex size and organization. This diversity is explained partly by neural cell division and scaling laws that constrain the expansion of the cerebral cortex as a function of body size and development. Differences in cerebral cortex organization are also explained by adaptive evolution of animals in their unique niches. Mutations in the gene ASPM cause primary microcephaly or reduced brain size in humans. The gene ASPM controls cortical neurogenesis through cell cycle functions in the brain. There is evidence of accelerated evolution of ASPM in humans and other nonhuman primates with enlarged cerebral cortex sizes. In addition to ASPM , other genes particularly those underlying cellular energetics and regulation of gene expression may be involved in cerebral cortex evolution. The numerous single‐gene, genomic scan and expression studies have its limitations in explaining cerebral cortex evolution.

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

Cited by 245 publications

References 57 publications

The role of genetic biases in shaping the correlations between languages and genes

The role of genetic biases in shaping the correlations between languages and genes

Subcortical Plasticity Following Perceptual Learning in a Pitch Discrimination Task

Cerebral Cortex Evolution and the ASPM Gene

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