Active adjustment of the cervical spine during pitch production compensates for shape: The ArtiVarK study

The anterior lordosis of the cervical spine is thought to contribute to pitch (fo) production by influencing cricoid rotation as a function of larynx height. This study examines the matter of inter-individual variation in cervical spine shape and whether this has an influence on how fo is produced along increasing or decreasing scales, using the ArtiVarK dataset, which contains real-time MRI pitch production data. We find that the cervical spine actively participates in fo production, but the amount of displacement depends on individual shape. In general, anterior spine motion (tending toward cervical lordosis) occurs for low fo, while posterior movement (tending towards cervical kyphosis) occurs for high fo

Causal correlations between genes and linguistic features: The mechanism of gradual language evolution

The causal correlations between human genetic variants and linguistic (typological) features could represent the mechanism required for gradual, accretionary models of language evolution. The causal link is mediated by the process of cultural transmission of language across generations in a population of genetically biased individuals. The particular case of Tone, ASPM and Microcephalin is discussed as an illustration. It is proposed that this type of genetically-influenced linguistic bias, coupled with a fundamental role for genetic and linguistic diversities, provides a better explanation for the evolution of language and linguistic universals

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

Language is a hallmark of our species and understanding linguistic diversity is an area of major interest. Genetic factors influencing the cultural transmission of language provide a powerful and elegant explanation for aspects of the present day linguistic diversity and a window into the emergence and evolution of language. In particular, it has recently been proposed that linguistic tone—the usage of voice pitch to convey lexical and grammatical meaning—is biased by two genes involved in brain growth and development, ASPM and Microcephalin. This hypothesis predicts that tone is a stable characteristic of language because of its ‘genetic anchoring’. The present paper tests this prediction using a Bayesian phylogenetic framework applied to a large set of linguistic features and language families, using multiple software implementations, data codings, stability estimations, linguistic classifications and outgroup choices. The results of these different methods and datasets show a large agreement, suggesting that this approach produces reliable estimates of the stability of linguistic data. Moreover, linguistic tone is found to be stable across methods and datasets, providing suggestive support for the hypothesis of genetic influences on its distribution

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

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

Genetic biasing through cultural transmission: Do simple Bayesian models of language evolution generalize?

The recent Bayesian approaches to language evolution and change seem to suggest that genetic biases can impact on the characteristics of language, but, at the same time, that its cultural transmission can partially free it from these same genetic constraints. One of the current debates centres on the striking differences between sampling and a posteriori maximising Bayesian learners, with the first converging on the prior bias while the latter allows a certain freedom to language evolution. The present paper shows that this difference disappears if populations more complex than a single teacher and a single learner are considered, with the resulting behaviours more similar to the sampler. This suggests that generalisations based on the language produced by Bayesian agents in such homogeneous single agent chains are not warranted. It is not clear which of the assumptions in such models are responsible, but these findings seem to support the rising concerns on the validity of the “acquisitionist” assumption, whereby the locus of language change and evolution is taken to be the first language acquirers (children) as opposed to the competent language users (the adults)

Anatomical biasing of click learning and production: An MRI and 3d palate imaging study

The current paper presents results for data on click learning obtained from a larger imaging study (using MRI and 3D intraoral scanning) designed to quantify and characterize intra- and inter-population variation of vocal tract structures and the relation of this to speech production. The aim of the click study was to ascertain whether and to what extent vocal tract morphology influences (1) the ability to learn to produce clicks and (2) the productions of those that successfully learn to produce these sounds. The results indicate that the presence of an alveolar ridge certainly does not prevent an individual from learning to produce click sounds (1). However, the subtle details of how clicks are produced may indeed be driven by palate shape (2)

Language evolution: Constraints and opportunities from modern genetics

Our understanding of language, its origins and subsequent evolution (including language change) is shaped not only by data and theories from the language sciences, but also fundamentally by the biological sciences. Recent developments in genetics and evolutionary theory offer both very strong constraints on what scenarios of language evolution are possible and probable but also offer exciting opportunities for understanding otherwise puzzling phenomena. Due to the intrinsic breathtaking rate of advancement in these fields, the complexity, subtlety and sometimes apparent non-intuitiveness of the phenomena discovered, some of these recent developments have either being completely missed by language scientists, or misperceived and misrepresented. In this short paper, we offer an update on some of these findings and theoretical developments through a selection of illustrative examples and discussions that cast new light on current debates in the language sciences. The main message of our paper is that life is much more complex and nuanced than anybody could have predicted even a few decades ago, and that we need to be flexible in our theorizing instead of embracing a priori dogmas and trying to patch paradigms that are no longer satisfactory

Defining and counting phonological classes in cross-linguistic segment databases

Recently, there has been an explosion in the availability of large, good-quality cross-linguistic databases such as WALS (Dryer & Haspelmath, 2013), Glottolog (Hammarstrom et al., 2015) and Phoible (Moran & McCloy, 2014). Databases such as Phoible contain the actual segments used by various languages as they are given in the primary language descriptions. However, this segment-level representation cannot be used directly for analyses that require generalizations over classes of segments that share theoretically interesting features. Here we present a method and the associated R (R Core Team, 2014) code that allows the exible denition of such meaningful classes and that can identify the sets of segments falling into such a class for any language inventory. The method and its results are important for those interested in exploring cross-linguistic patterns of phonetic and phonological diversity and their relationship to extra-linguistic factors and processes such as climate, economics, history or human genetics