Gaussian process models for geographic controls in phylogenetic trees.

Geographical confounding in phylogenetic inference models has long been an issue. Often models have great difficulty detecting whether congruences or similarities between languages in phylogenetic datasets stem from common genetic descent or geographical proximity effects such as language contact. In this study, we introduce a distance-based Gaussian process approach with latent phylogenetic distances that can detect potential geographic contact zones and subsequently account for geospatial biases in the resulting tree topologies. We find that this approach is able to determine potential high-contact areas, making it possible to calculate the strength of this influence on both the tree-level (clade support) and the language-level (pairwise distances).

Comparative exploration of the morphological plasticity of Trichodina centrostrigeata (Peritrichia: Mobilida), ectoparasite from the gills of two tilapia species (Oreochromis niloticus and O. mossambicus) in a global context.

Trichodina centrostrigeata Basson, Van As et Paperna, 1983 from Oreochromis mossambicus (Peters) and O. niloticus (Linnaeus) from different host populations from Argentina, Mexico and South Africa was reviewed. Although T. centrostrigeata has a distinct denticle structure that makes morphological taxonomic inferences uncomplicated, variation of the denticles within and among individuals and populations were still observed. While traditional taxonomy of mobilines is heavily reliant on morphometrics, and recently even more so on molecular analysis, this paper proposes the use of geometric morphometry, specifically elliptical Fourier analysis, to address morphological conflicts that arise when comparing different populations. By applying this technique, combined with traditional taxonomy, it was found that T. centrostrigeata in this study can be grouped into two separate morphotypes, the first (type a) from aquaculture farms in Argentina and Mexico and the second (type b) from a natural habitat in Glen Alpine Dam, South Africa. This study supports the validity of geometric morphometry as an additional technique to distinguish not only between species but also evolutionary plasticity of the same species from different localities and habitats.

Phylogenetic Typology.

In this article we propose a novel method to estimate the frequency distribution of linguistic variables while controlling for statistical non-independence due to shared ancestry. Unlike previous approaches, our technique uses all available data, from language families large and small as well as from isolates, while controlling for different degrees of relatedness on a continuous scale estimated from the data. Our approach involves three steps: First, distributions of phylogenies are inferred from lexical data. Second, these phylogenies are used as part of a statistical model to estimate transition rates between parameter states. Finally, the long-term equilibrium of the resulting Markov process is computed. As a case study, we investigate a series of potential word-order correlations across the languages of the world.

NorthEuraLex: a wide-coverage lexical database of Northern Eurasia.

This article describes the first release version of a new lexicostatistical database of Northern Eurasia, which includes Europe as the most well-researched linguistic area. Unlike in other areas of the world, where databases are restricted to covering a small number of concepts as far as possible based on often sparse documentation, good lexical resources providing wide coverage of the lexicon are available even for many smaller languages in our target area. This makes it possible to attain near-completeness for a substantial number of concepts. The resulting database provides a basis for rich benchmarks that can be used to test automated methods which aim to derive new knowledge about language history in underresearched areas.

Pragmatic processing: An investigation of the (anti-)presuppositions of determiners using mouse-tracking.

A presupposition is a condition that has to be met in order for a linguistic expression to be appropriate. The definite determiner (as in the banana) triggers the uniqueness-presupposition that there is a uniquely identifiable banana in the relevant discourse context. The indefinite determiner (as in a banana) is similarly associated with anti-uniqueness (that there are several bananas). Application of the Maximize Presupposition principle to the indefinite determiner suggests that this latter effect results indirectly as an anti-presupposition from considering the uniqueness-presupposition of the definite determiner, which is then negated. This results in increased processing difficulty. We utilized mouse-tracking to compare processing of definite and indefinite determiners when used felicitously and infelicitously in a particular context. First, processing of the indefinite determiner was associated with more processing difficulties compared with the definite determiner. Second, we also observed evidence for an initial temporary activation and evaluation of the uniqueness-presupposition, just as derived from anti-presupposition theory and the Maximize Presupposition principle.

Global-scale phylogenetic linguistic inference from lexical resources.

Automatic phylogenetic inference plays an increasingly important role in computational historical linguistics. Most pertinent work is currently based on expert cognate judgments. This limits the scope of this approach to a small number of well-studied language families. We used machine learning techniques to compile data suitable for phylogenetic inference from the ASJP database, a collection of almost 7,000 phonetically transcribed word lists over 40 concepts, covering two thirds of the extant world-wide linguistic diversity. First, we estimated Pointwise Mutual Information scores between sound classes using weighted sequence alignment and general-purpose optimization. From this we computed a dissimilarity matrix over all ASJP word lists. This matrix is suitable for distance-based phylogenetic inference. Second, we applied cognate clustering to the ASJP data, using supervised training of an SVM classifier on expert cognacy judgments. Third, we defined two types of binary characters, based on automatically inferred cognate classes and on sound-class occurrences. Several tests are reported demonstrating the suitability of these characters for character-based phylogenetic inference.

The evolution of language families is shaped by the environment beyond neutral drift.

There are more than 7,000 languages spoken in the world today1. It has been argued that the natural and social environment of languages drives this diversity2-13. However, a fundamental question is how strong are environmental pressures, and does neutral drift suffice as a mechanism to explain diversification? We estimate the phylogenetic signals of geographic dimensions, distance to water, climate and population size on more than 6,000 phylogenetic trees of 46 language families. Phylogenetic signals of environmental factors are generally stronger than expected under the null hypothesis of no relationship with the shape of family trees. Importantly, they are also-in most cases-not compatible with neutral drift models of constant-rate change across the family tree branches. Our results suggest that language diversification is driven by further adaptive and non-adaptive pressures. Language diversity cannot be understood without modelling the pressures that physical, ecological and social factors exert on language users in different environments across the globe.

The Role of Simple Semantics in the Process of Artificial Grammar Learning.

This study investigated the effect of semantic information on artificial grammar learning (AGL). Recursive grammars of different complexity levels (regular language, mirror language, copy language) were investigated in a series of AGL experiments. In the with-semantics condition, participants acquired semantic information prior to the AGL experiment; in the without-semantics control condition, participants did not receive semantic information. It was hypothesized that semantics would generally facilitate grammar acquisition and that the learning benefit in the with-semantics conditions would increase with increasing grammar complexity. Experiment 1 showed learning effects for all grammars but no performance difference between conditions. Experiment 2 replicated the absence of a semantic benefit for all grammars even though semantic information was more prominent during grammar acquisition as compared to Experiment 1. Thus, we did not find evidence for the idea that semantics facilitates grammar acquisition, which seems to support the view of an independent syntactic processing component.

Tracking modern human population history from linguistic and cranial phenotype.

Languages and genes arguably follow parallel evolutionary trajectories, descending from a common source and subsequently differentiating. However, although common ancestry is established within language families, it remains controversial whether language preserves a deep historical signal. To address this question, we evaluate the association between linguistic and geographic distances across 265 language families, as well as between linguistic, geographic, and cranial distances among eleven populations from Africa, Asia, and Australia. We take advantage of differential population history signals reflected by human cranial anatomy, where temporal bone shape reliably tracks deep population history and neutral genetic changes, while facial shape is more strongly associated with recent environmental effects. We show that linguistic distances are strongly geographically patterned, even within widely dispersed groups. However, they are correlated predominantly with facial, rather than temporal bone, morphology, suggesting that variation in vocabulary likely tracks relatively recent events and possibly population contact.

Support for linguistic macrofamilies from weighted sequence alignment.

Computational phylogenetics is in the process of revolutionizing historical linguistics. Recent applications have shed new light on controversial issues, such as the location and time depth of language families and the dynamics of their spread. So far, these approaches have been limited to single-language families because they rely on a large body of expert cognacy judgments or grammatical classifications, which is currently unavailable for most language families. The present study pursues a different approach. Starting from raw phonetic transcription of core vocabulary items from very diverse languages, it applies weighted string alignment to track both phonetic and lexical change. Applied to a collection of ∼1,000 Eurasian languages and dialects, this method, combined with phylogenetic inference, leads to a classification in excellent agreement with established findings of historical linguistics. Furthermore, it provides strong statistical support for several putative macrofamilies contested in current historical linguistics. In particular, there is a solid signal for the Nostratic/Eurasiatic macrofamily.

Does formal complexity reflect cognitive complexity? Investigating aspects of the Chomsky Hierarchy in an artificial language learning study.

This study investigated whether formal complexity, as described by the Chomsky Hierarchy, corresponds to cognitive complexity during language learning. According to the Chomsky Hierarchy, nested dependencies (context-free) are less complex than cross-serial dependencies (mildly context-sensitive). In two artificial grammar learning (AGL) experiments participants were presented with a language containing either nested or cross-serial dependencies. A learning effect for both types of dependencies could be observed, but no difference between dependency types emerged. These behavioral findings do not seem to reflect complexity differences as described in the Chomsky Hierarchy. This study extends previous findings in demonstrating learning effects for nested and cross-serial dependencies with more natural stimulus materials in a classical AGL paradigm after only one hour of exposure. The current findings can be taken as a starting point for further exploring the degree to which the Chomsky Hierarchy reflects cognitive processes.

Formal language theory: refining the Chomsky hierarchy.

The first part of this article gives a brief overview of the four levels of the Chomsky hierarchy, with a special emphasis on context-free and regular languages. It then recapitulates the arguments why neither regular nor context-free grammar is sufficiently expressive to capture all phenomena in the natural language syntax. In the second part, two refinements of the Chomsky hierarchy are reviewed, which are both relevant to the extant research in cognitive science: the mildly context-sensitive languages (which are located between context-free and context-sensitive languages), and the sub-regular hierarchy (which distinguishes several levels of complexity within the class of regular languages).

Studying language change using price equation and Pólya-urn dynamics.

Language change takes place primarily via diffusion of linguistic variants in a population of individuals. Identifying selective pressures on this process is important not only to construe and predict changes, but also to inform theories of evolutionary dynamics of socio-cultural factors. In this paper, we advocate the Price equation from evolutionary biology and the Pólya-urn dynamics from contagion studies as efficient ways to discover selective pressures. Using the Price equation to process the simulation results of a computer model that follows the Pólya-urn dynamics, we analyze theoretically a variety of factors that could affect language change, including variant prestige, transmission error, individual influence and preference, and social structure. Among these factors, variant prestige is identified as the sole selective pressure, whereas others help modulate the degree of diffusion only if variant prestige is involved. This multidisciplinary study discerns the primary and complementary roles of linguistic, individual learning, and socio-cultural factors in language change, and offers insight into empirical studies of language change.

Evolutionary stability conditions for signaling games with costly signals.

The paper investigates the class of signaling games with the following properties: (a) the interests of sender and receiver coincide, (b) different signals incur differential costs, and (c) different events (meanings/types) have different probabilities. Necessary and sufficient conditions are presented for a profile to be evolutionarily stable and neutrally stable, and for a set of profiles to be an evolutionarily stable set. The main finding is that a profile belongs to some evolutionarily stable set if and only if a maximal number of events can be reliably communicated. Furthermore, it is shown that under the replicator dynamics, a set of states with a positive measure is attracted to "sub-optimal" equilibria that do not belong to any asymptotically stable set.