Tag: network

Cultural and linguistic diversity: evolutionary approaches

Via HENRY:

There’s a special issue of Philosophical Transactions of the Royal Society out on the theme of Cultural and linguistic diversity: evolutionary approaches.

From the introduction:

Evolutionary approaches to cultural change are increasingly influential, and many scientists believe that a ‘grand synthesis’ is now in sight. The papers in this Theme Issue, which derives from a sym- posium held by the AHRC Centre for the Evolution of Cultural Diversity (University College London) in December 2008, focus on how the phylogenetic tree-building and network-based tech- niques used to estimate descent relationships in biology can be adapted to reconstruct cultural histories, where some degree of inter-societal diffusion will almost inevitably be superimposed on any deeper signal of a historical branching process.

Papers:

  • On the shape and fabric of human history – Russell D. Gray, David Bryant, and Simon J. Greenhill

    • Mapping Linguistic Phylogeny to Politics

    In a recent article covered in NatureNews in Societes Evolve in Steps, Tom Currie of UCL, and others, like Russell Gray of Auckland, use quantitative analysis of the Polynesian language group to plot socioanthropological movement and power hierarchies in Polynesia. This is based off of previous work, available here, which I saw presented at the Language as an Evolutionary Systemconference last July. The article claims that the means of change for political complexity can be determined using linguistic evidence in Polynesia, along with various migration theories and archaeological evidence.

    I have my doubts.

    Note: Most of the content in this post is refuted wonderfully in the comment section by one of the original authors of the paper. I highly recommend reading the comments, if you’re going to read this at all – that’s where the real meat lies. I’m keeping this post up, finally, because it’s good to make mistakes and learn from them. -Richard

    §§

    I had posted this already on the Edinburgh Language Society blog. I’ve edited it a bit for this blog. I should also state that this is my inaugural post on Replicated Typo; thanks to Wintz’ invitation, I’ll be posting here every now and again. It’s good to be here. Thanks for reading – and thanks for pointing out errors, problems, corrections, and commenting, if you do. Research blogging is relatively new to me, and I relish this unexpected chance to hone my skills and learn from my mistakes. (Who am I, anyway?) But without further ado:

    §

    In a recent article covered in NatureNews in Societes Evolve in Steps, Tom Currie of UCL, and others, like Russell Gray of Auckland, use quantitative analysis of the Polynesian language group to plot socioanthropological movement and power hierarchies in Polynesia. This is based off of previous work, available here, which I saw presented at the Language as an Evolutionary Systemconference last July. The article claims that the means of change for political complexity can be determined using linguistic evidence in Polynesia, along with various migration theories and archaeological evidence.

    I have my doubts. The talk that was given by Russell Gray suggested that there were still various theories about the migratory patterns of the Polynesians – in particular, where they started from. What his work did was to use massive supercomputers to narrow down all of the possibilities, by using lexicons and charting their similarities. The most probable were then recorded, and their statistical probability indicated what was probably the course of action. This, however, is where the ability for guessing ends. Remember, this is massive quantificational statistics. If one has a 70% probability chance of one language being the root of another, that isn’t to say that that language is the root, much less that the organisation of one determines the organisation of another. But statistics are normally unassailable – I only bring up this disclaimer because there isn’t always clear mapping between language usage and migration.

    Continue reading “Mapping Linguistic Phylogeny to Politics”

    Under the Influence: An overview of recent insights into the CNTNAP2 gene

    In my last post I outlined a number of experimental studies using the Zebra Finch that have highlighted an additional dimension to the FoxP2 gene – not only is it upregulated in the avian brain throughout song development, but it is also downregulated in important song nuclei of adult birds in singing contexts that seem to involve ‘listening to one’s own song’ and subsequent error correction.  Given that the pattern of expression of this gene is very similar in the developing brain of both humans and birds, one conclusion that has been drawn from this research is that FOXP2 downregulation may equivocally serve to facilitate online language processing function in the adult human brain.

    General background on an intriguing new celebrity

    Naturally, the next step has been to try and identify the downstream genes regulated by FOXP2 in order to build up a more detailed picture of how interactions between complex genetic networks influence key language-related disorders in humans.   It is as a result of such efforts that another gene, although discovered almost a decade ago, has found its way into the spotlight: CNTNAP2.

    In the developing human brain, CNTNAP2 is enriched in functionally specialised regions such as the frontal cortex, the stratium, and the dorsal thalamus (circuits within these regions are referred to as cortico-striato-thalmic circuits) central to executive function, planning and executing complex sequential movements, and thus potentially, language.  This presents a striking contrast to the more uniform expression of Cntnap2 observed in the developing rodent brain where there is no evidence for enrichment in specific regions, suggesting a functional difference in the human version that could be related to vocal learning and modification.

    Continue reading “Under the Influence: An overview of recent insights into the CNTNAP2 gene”

    Some Links #17: The Return of Whorf

    The famous Klingon linguist, Whorf, has returned with his theories on linguistic relativity (I know, terrible joke).

    The Largest Whorfian Study Ever. The Lousy Linguist looks at the paper Ways to go: Methodological considerations in Whorfian studies on motion events. As you can probably guess, the paper deals with the methodological issues surrounding linguistic relativity. It’s all interesting stuff, bringing to light important questions about how the brain handles language. I’m fairly lay when it comes to this topic, so for more background on the current events, see similar posts over at Language Log: Never Mind the Conclusions, What’s the Evidence? and SLA Blog: Linguistic Relativity, Whorf, Linguistic Relativity.

    But Science Doesn’t Work That Way: Miller & Chomsky (1963). Many of you who read this blog will be familiar with the position taken by Melody’s post over at Child’s Play: against a strong nativist position in language acquisition. It’s the first part in a series of posts so I’ll reserve judgement on her conclusions until she’s finished. But much of her post is drawn from a brilliant paper by Scholz and Pullum (2005): Irrational Nativist Exuberance. Key paragraph:

    Do we really want to say that phonemes are ‘innate’?

    I haven’t yet addressed how we know — with all but certainty — that the model Miller and Chomsky used had to be a poor approximation of human learning capabilities.  It has to do with phonemes.

    Experiments have shown that people are remarkably sensitive to the transitional probabilities between phonemes in their native languages, both when speaking and when listening to speech.  If Miller and Chomsky’s assessment of probabilistic learning is correct, then the problem of “parameter estimation” should apply not only to learning the probabilities between words, but also to learning the probabilities between phonemes.  Given that people do learn to predict phonemes, Miller and Chomsky’s logic would force us to conclude that not only must ‘grammar’ be innate, but the particular distribution of phonemes in English (and every other language) must be innate as well.

    We only get to this absurdist conclusion because Miller & Chomsky’s argument mistakes philosophical logic for science (which is, of course, exactly what intelligent design does).  So what’s the difference between philosophical logic and science? Here’s the answer, in Einstein’s words, “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”

    PLoS Blogs. Yet another blogging network. This time it’s with the Public Library of Science. The most notable move, for me at least, is Neuroanthropology. That move hasn’t seemed to impact upon their ability to produce good articles, the latest of which being in regards to Uner Tan Syndrome (I’m sure there was a documentary about this on BBC…).

    Hap Map 3: more people ~ more genetic variation. Razib has a cool read on the new HapMap dataset. The current paper (Integrating common and rare genetic variation in diverse human populations) looked for variants across the genome in 11 populations, consisting of 1184 samples. It’s been especially useful with less common variants. As with previous versions, you can also explore the data. Here’s the conclusion from the paper:

    With improvements in sequencing technology, low-frequency variation is becoming increasingly accessible. This greater resolution will no doubt expand our ability to identify genes and variants associated with disease and other human traits. This study integrates CNPs and lower-frequency SNPs with common SNPs in a more diverse set of human populations than was previously available. The results underscore the need to characterize population-genetic parameters in each population, and for each stratum of allele frequency, as it is not possible to extrapolate from past experience with common alleles. As expected, lower-frequency variation is less shared across populations, even closely related ones, highlighting the importance of sampling widely to achieve a comprehensive understanding of human variation.

    Mathematics: From the Birth of Numbers. Someone gave this in to the charity store I work at: it’s a brilliant book by Jan Gullberg on (surprise, surprise) the history of mathematics. The first chapter was on mathematics and language, so I had to pick it up, and not just for that chapter alone, as there are plenty of gaps in my mathematical knowledge I’m sure this will clear up.

    Guardian Science Blogs

    Some smart moves by the Guardian. They’ve created their own mini science blog network, containing some top names and proven bloggers. There are currently five blogs: Punctuated Equilibrium, Political Science, The Lay Scientist, Life and Physics. The fifth blog, in case you were concerned about my ability to count, is going to rotate between various bloggers, the first of which being the brilliant Mo Costandi of Neurophilosophy. I would normally subscribe to each of these blogs individually, so it’s nice to see them all under one digital roof of science-blogging goodness.

    Btw, here’s the RSS feed for all the blogs: http://www.guardian.co.uk/science/scienceblogs/roundup/rss.

    Theory of Mind and Language Evolution; What can psychopathology tell us?

    Theory of Mind is the ability to infer other persons’ mental states and emotions. It is thought to have evolved as part of the human’s social brain and probably emerged as an adaptive response to increasingly complex primate social interaction.

    Brüne and Brüne-Cohrs (2006) explore the ‘evolutionary cost’ of language evolution:

    This sophisticated ‘metacognitive’ ability comes at an evolutionary cost, reflected in a broad spectrum of psychopathological conditions. Extensive research into autistic spectrum disorders has revealed that theory of mind may be selectively impaired, leaving other cognitive faculties intact. Recent studies have shown that observed deficits in theory of mind task performance are part of a broad range of symptoms in schizophrenia, bipolar affective disorder, some forms of dementia, ‘psychopathy’ and in other psychiatric disorders.

    Now it’s fairly uncontroversial to assert that without the ability of theory of mind humans would have never evolved language (Sperber and Wilson, 2002). This is due to the fact that if one can’t attribute another to have a ‘mind’ like ones own, or assume that other minds hold different information to ones own then one would see little point in trying to share information. (I’m sorry for the amount of ‘ones’ in that sentence).

    Sooo, it does not seem presumptuous to assume that people interested in the evolution of language should be interested in theory of mind, in fact for many years evolutionary linguists, psychologists and biologists have been looking into this, but mostly through observing the behaviour of animals, and especially primates to see if they display theory of mind capabilities. A good summary of this work can be found here, and a lot of relevant studies can be found on this blog in the What makes humans unique? posts by Michael. I’m not going to look at the animal data in this post, but instead what the deficiencies in some human conditions can tell us about the evolution of theory of mind. That is, what can autism, schizophrenia, bipolar affective disorder, dementia, ‘psychopathy’ and other psychiatric disorders tell us?

    Continue reading “Theory of Mind and Language Evolution; What can psychopathology tell us?”

    Evolution of Colour Terms: 5 Cultural Constraints

    Continuing my series on the Evolution of Colour terms, this post reviews studies of cultural constraints on colour naming. For the full dissertation and for references, go here.

    Continue reading “Evolution of Colour Terms: 5 Cultural Constraints”

    Language Evolution and Language Acquisition

    The way children learn language sets the adaptive landscape on which languages evolve.  This is acknowledged by many, but there are few connections between models of language acquisition and models of language Evolution (some exceptions include Yang (2002), Yu & Smith (2007) and Chater & Christiansen (2009)).

    However, the chasm between the two fields may be getting smaller, as theories are defined as models which are both more interpretable to the more technically-minded Language Evolutionists and extendible into populations and generations.

    Also, strangely, models of word learning have been getting simpler over time.  This may reflect a move from attributing language acquisition to specific mechanisms towards a more general cognitive explanation.  I review some older models here, and a recent publication by Fazly et al.

    Continue reading “Language Evolution and Language Acquisition”

    Genetic Components and Cultural Differences: The social sensitivity hypothesis

    ResearchBlogging.orgCultural differences are often attributed to events far removed from genetics. The basis for this belief is often based on the assertion that if you take an individual, at birth, from one society and implant them in another, then they will generally grow up to become well-adjusted to their adopted culture. Whilst this is more than likely true, even if there may be certain cultural features that may disagree with someone of a different ethnic background (e.g. degrees of alcohol tolerance), the situation is not as clear cut as certain political factions may have you believe.  Yet, largely due to studies on gene-culture coevolution, we are now starting to understand the complex dynamics through which genes and culture interact.

    First, a particular culture may exert selection pressures on genes that provide an advantageous benefit to the adoption of a particular cultural trait. This is evident in the strong selection of the lactose-tolerance allele due to the spread of dairy farming. Second, pre-existing gene distributions provide pressures through which culture adapts. Off the top of my head, one proposed example of this is a paper by Dediu and Ladd (2007), which looked at how the distribution of the derived haplotypes of ASPM and Microcephalin may have subtly influenced the development of tonal languages. The paper in question, however, is looking more broadly at culture. Specifically, the authors, Baldwin May and Matthew Lieberman, examine recent genetic association studies and how within-variation of genes involved in central neurotransmitter systems are associated with differences in social sensitivity. In particular, they highlight a correlation between the relative frequencies of certain gene-variants and the relative degree of individualism or collectivism within certain populations.

    Continue reading “Genetic Components and Cultural Differences: The social sensitivity hypothesis”

    Population Size and Rates of Language Change

    In previous posts, I’ve looked at the relationship between cultural evolution and demography (see here, here and here). As such, it makes sense to see if such methods are applicable in language which is, after all, a cultural product. So, having spent the last few days looking over the literature on language and demography, I found the following paper on population size and language change (free download). In it, the authors, Søren Wichmann and Eric Holman, use lexical data from WALS to test for an effect of the number of speakers on the rate of language change. Their general findings argue against a strong influence of  population size, with them instead opting for a model where the type of network influences change at a local level, through different degrees of connectivity between individuals. Here is the abstract:

    Previous empirical studies of population size and language change have  produced  equivocal  results. We  therefore  address  the  question  with  a new set of lexical data from nearly one-half of the world’s languages. We first show that relative population sizes of modern languages can be extrapolated to ancestral languages, albeit with diminishing accuracy, up to several thousand years into the past. We then test for an effect of population against the null hypothesis that the ultrametric inequality is satisified by lexical distances among triples of related languages. The test shows mainly negligible effects of population, the exception being an apparently faster rate of change in the larger of two closely related variants. A possible explanation for the exception may be the influence on emerging standard (or cross-regional) variants from speakers who shift from different dialects to the standard. Our results strongly indicate that the sizes of speaker populations do not in and of themselves determine rates of language change. Comparison of this empirical  finding with previously published computer simulations suggests that the most plausible model  for  language  change  is  one  in  which  changes  propagate  on  a  local level in a type of network in which the individuals have different degrees of connectivity.

    As I’m in the middle of several other things at the moment I don’t really have time to provide a thorough review of this paper. Having said that, I agree with their claim of population size being unlikely to account for rates of language change. I reckon their results would be stronger if they factored in population density. So those that are dense and large will change faster than those which are large and distributed. The main point being that population size and population density influence the degree of social interconnectivity. Nettle (1999), for instance, argues that “spreading an innovation over a tribe of 500 people is much easier and takes much less time than spreading one over five million people.” This is fairly reasonable if we are looking at the generation of a single innovation within each of these populations. However, if those 500 people are spread across a large distance, then their transmission chain is going to be stretched: effectively lowering the rate of transmission. The same applies for a population of five million individuals who are packed into a small area: Arguably, given the right conditions, we can arrive at a situation where a population of five million show greater levels of interconnectivity than 500. I think it’s this aspect, the level of social interconnectivity, which may be more relevant to the rate of language change (other things to test for, include: writing systems/literacy and inter-language contact).