Language Evolution and Computation Bibliography

Do the mechanisms underlying language in fact serve general-purpose functions that preexist this uniquely human capacity? To address this contentious and empirically challenging issue, we systematically tested the predictions of a well-studied neurocognitive theory of language motivated by evolutionary principles. Multiple metaanalyses were performed to examine predicted links between language and two general-purpose learning systems, declarative and procedural memory. The results tied lexical abilities to learning only in declarative memory, while grammar was linked to learning in both systems in both child first language and adult second language, in specific ways. In second language learners, grammar was associated with only declarative memory at lower language experience, but with only procedural memory at higher experience. The findings yielded large effect sizes and held consistently across languages, language families, linguistic structures, and tasks, underscoring their reliability and validity. The results, which met the predicted pattern, provide comprehensive evidence that language is tied to general-purpose systems both in children acquiring their native language and adults learning an additional language. Crucially, if language learning relies on these systems, then our extensive knowledge of the systems from animal and human studies may also apply to this domain, leading to predictions that might be unwarranted in the more circumscribed study of language. Thus, by demonstrating a role for these systems in language, the findings simultaneously lay a foundation for potentially important advances in the study of this critical domain.

Vocalizations are a pervasive feature of nonhuman primate social life, yet we know surprisingly little about their function. We review studies supporting the hypothesis that many primate vocalizations function to facilitate social interactions by reducing uncertainty about the signaler's intentions and likely behavior. Such interactions help to establish and maintain the social bonds that increase reproductive success. Compared with humans, songbirds, and a few other mammals, primates have small vocal repertoires that show little acoustic modification during development. However, their ability to modify call usage is extensive and tuned to variation in the social context, including the historical relationship between caller and listener and the caller's assessment of how a listener is likely to respond. We suggest parallels between the decision to vocalize and neurophysiological studies of other, nonvocal social decisions between interacting monkeys. The selective factors driving the early stages of language evolution may have come from the need to make decisions about when and how to call within the context of social challenges.

What happens when a new social convention replaces an old one? While the possible forces favoring norm change-such as institutions or committed activists-have been identified for a long time, little is known about how a population adopts a new convention, due to the difficulties of finding representative data. Here, we address this issue by looking at changes that occurred to 2,541 orthographic and lexical norms in English and Spanish through the analysis of a large corpora of books published between the years 1800 and 2008. We detect three markedly distinct patterns in the data, depending on whether the behavioral change results from the action of a formal institution, an informal authority, or a spontaneous process of unregulated evolution. We propose a simple evolutionary model able to capture all of the observed behaviors, and we show that it reproduces quantitatively the empirical data. This work identifies general mechanisms of norm change, and we anticipate that it will be of interest to researchers investigating the cultural evolution of language and, more broadly, human collective behavior.

In the past few decades, scholars from several disciplines have pursued the curious parallel noted by Darwin between the genetic evolution of species and the cultural evolution of beliefs, skills, knowledge, languages, institutions, and other forms of socially transmitted information. Here, I review current progress in the pursuit of an evolutionary science of culture that is grounded in both biological and evolutionary theory, but also treats culture as more than a proximate mechanism that is directly controlled by genes. Both genetic and cultural evolution can be described as systems of inherited variation that change over time in response to processes such as selection, migration, and drift. Appropriate differences between genetic and cultural change are taken seriously, such as the possibility in the latter of nonrandomly guided variation or transformation, blending inheritance, and one-to-many transmission. The foundation of cultural evolution was laid in the late 20th century with population-genetic style models of cultural microevolution, and the use of phylogenetic methods to reconstruct cultural macroevolution. Since then, there have been major efforts to understand the sociocognitive mechanisms underlying cumulative cultural evolution, the consequences of demography on cultural evolution, the empirical validity of assumed social learning biases, the relative role of transformative and selective processes, and the use of quantitative phylogenetic and multilevel selection models to understand past and present dynamics of society-level change. I conclude by highlighting the interdisciplinary challenges of studying cultural evolution, including its relation to the traditional social sciences and humanities.

It is widely recognized that language plays a key role in the transmission of human culture, but relatively little is known about the mechanisms by which language simultaneously encourages both cultural stability and cultural innovation. This paper examines this issue by focusing on the use of language to transmit categories, focusing on two universal devices: labels (e.g., shark, woman) and generics (e.g., "sharks attack swimmers"; "women are nurturing"). We propose that labels and generics each assume two key principles: norms and essentialism. The normative assumption permits transmission of category information with great fidelity, whereas essentialism invites innovation by means of an open-ended, placeholder structure. Additionally, we sketch out how labels and generics aid in conceptual alignment and the progressive "looping" between categories and cultural practices. In this way, human language is a technology that enhances and expands the categorization capacities that we share with other animals.

Focal colors, or best examples of color terms, have traditionally been viewed as either the underlying source of cross-language color-naming universals or derived from category boundaries that vary widely across languages. Existing data partially support and partially challenge each of these views. Here, we advance a position that synthesizes aspects of these two traditionally opposed positions and accounts for existing data. We do so by linking this debate to more general principles. We show that best examples of named color categories across 112 languages are well-predicted from category extensions by a statistical model of how representative a sample is of a distribution, independently shown to account for patterns of human inference. This model accounts for both universal tendencies and variation in focal colors across languages. We conclude that categorization in the contested semantic domain of color may be governed by principles that apply more broadly in cognition and that these principles clarify the interplay of universal and language-specific forces in color naming.

Language's expressive power is largely attributable to its compositionality: meaningful words are combined into larger/higher-order structures with derived meaning. Despite its importance, little is known regarding the evolutionary origins and emergence of this syntactic ability. Although previous research has shown a rudimentary capability to combine meaningful calls in primates, because of a scarcity of comparative data, it is unclear to what extent analog forms might also exist outside of primates. Here, we address this ambiguity and provide evidence for rudimentary compositionality in the discrete vocal system of a social passerine, the pied babbler (Turdoides bicolor). Natural observations and predator presentations revealed that babblers produce acoustically distinct alert calls in response to close, low-urgency threats and recruitment calls when recruiting group members during locomotion. On encountering terrestrial predators, both vocalizations are combined into a "mobbing sequence," potentially to recruit group members in a dangerous situation. To investigate whether babblers process the sequence in a compositional way, we conducted systematic experiments, playing back the individual calls in isolation as well as naturally occurring and artificial sequences. Babblers reacted most strongly to mobbing sequence playbacks, showing a greater attentiveness and a quicker approach to the loudspeaker, compared with individual calls or control sequences. We conclude that the sequence constitutes a compositional structure, communicating information on both the context and the requested action. Our work supports previous research suggesting combinatoriality as a viable mechanism to increase communicative output and indicates that the ability to combine and process meaningful vocal structures, a basic syntax, may be more widespread than previously thought.

How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides indirect access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here, we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries to translate words to and from languages carefully selected to be representative of worldwide diversity. These translations reveal cases where a particular language uses a single "polysemous" word to express multiple concepts that another language represents using distinct words. We use the frequency of such polysemies linking two concepts as a measure of their semantic proximity and represent the pattern of these linkages by a weighted network. This network is highly structured: Certain concepts are far more prone to polysemy than others, and naturally interpretable clusters of closely related concepts emerge. Statistical analysis of the polysemies observed in a subset of the basic vocabulary shows that these structural properties are consistent across different language groups, and largely independent of geography, environment, and the presence or absence of a literary tradition. The methods developed here can be applied to any semantic domain to reveal the extent to which its conceptual structure is, similarly, a universal attribute of human cognition and language use.

The ability to abstract a regularity that underlies strings of sounds is a core mechanism of the language faculty but might not be specific to language learning or even to humans. It is unclear whether and to what extent nonhuman animals possess the ability to abstract regularities defining the relation among arbitrary auditory items in a string and to generalize this abstraction to strings of acoustically novel items. In this study we tested these abilities in a songbird (zebra finch) and a parrot species (budgerigar). Subjects were trained in a go/no-go design to discriminate between two sets of sound strings arranged in an XYX or an XXY structure. After this discrimination was acquired, each subject was tested with test strings that were structurally identical to the training strings but consisted of either new combinations of known elements or of novel elements belonging to other element categories. Both species learned to discriminate between the two stimulus sets. However, their responses to the test strings were strikingly different. Zebra finches categorized test stimuli with previously heard elements by the ordinal position that these elements occupied in the training strings, independent of string structure. In contrast, the budgerigars categorized both novel combinations of familiar elements as well as strings consisting of novel element types by their underlying structure. They thus abstracted the relation among items in the XYX and XXY structures, an ability similar to that shown by human infants and indicating a level of abstraction comparable to analogical reasoning.

The naming of colors has long been a topic of interest in the study of human culture and cognition. Color term research has asked diverse questions about thought and communication, but no previous research has used an evolutionary framework. We show that there is broad support for the most influential theory of color term development (that most strongly represented by Berlin and Kay [Berlin B, Kay P (1969) (Univ of California Press, Berkeley, CA)]); however, we find extensive evidence for the loss (as well as gain) of color terms. We find alternative trajectories of color term evolution beyond those considered in the standard theories. These results not only refine our knowledge of how humans lexicalize the color space and how the systems change over time; they illustrate the promise of phylogenetic methods within the domain of cognitive science, and they show how language change interacts with human perception.

Identifying universal principles underpinning diverse natural systems is a key goal of the life sciences. A powerful approach in addressing this goal has been to test whether patterns consistent with linguistic laws are found in nonhuman animals. Menzerath's law is a linguistic law that states that, the larger the construct, the smaller the size of its constituents. Here, to our knowledge, we present the first evidence that Menzerath's law holds in the vocal communication of a nonhuman species. We show that, in vocal sequences of wild male geladas (Theropithecus gelada), construct size (sequence size in number of calls) is negatively correlated with constituent size (duration of calls). Call duration does not vary significantly with position in the sequence, but call sequence composition does change with sequence size and most call types are abbreviated in larger sequences. We also find that intercall intervals follow the same relationship with sequence size as do calls. Finally, we provide formal mathematical support for the idea that Menzerath's law reflects compression-the principle of minimizing the expected length of a code. Our findings suggest that a common principle underpins human and gelada vocal communication, highlighting the value of exploring the applicability of linguistic laws in vocal systems outside the realm of language.

Explaining the variation between human languages and the constraints on that variation is a core goal of linguistics. In the last 20 y, it has been claimed that many striking universals of cross-linguistic variation follow from a hypothetical principle that dependency length--the distance between syntactically related words in a sentence--is minimized. Various models of human sentence production and comprehension predict that long dependencies are difficult or inefficient to process; minimizing dependency length thus enables effective communication without incurring processing difficulty. However, despite widespread application of this idea in theoretical, empirical, and practical work, there is not yet large-scale evidence that dependency length is actually minimized in real utterances across many languages; previous work has focused either on a small number of languages or on limited kinds of data about each language. Here, using parsed corpora of 37 diverse languages, we show that overall dependency lengths for all languages are shorter than conservative random baselines. The results strongly suggest that dependency length minimization is a universal quantitative property of human languages and support explanations of linguistic variation in terms of general properties of human information processing.

We summarize a number of findings in laryngology demonstrating that perturbations of phonation, including increased jitter and shimmer, are associated with desiccated ambient air. We predict that, given the relative imprecision of vocal fold vibration in desiccated versus humid contexts, arid and cold ecologies should be less amenable, when contrasted to warm and humid ecologies, to the development of languages with phonemic tone, especially complex tone. This prediction is supported by data from two large independently coded databases representing 3,700+ languages. Languages with complex tonality have generally not developed in very cold or otherwise desiccated climates, in accordance with the physiologically based predictions. The predicted global geographic-linguistic association is shown to operate within continents, within major language families, and across language isolates. Our results offer evidence that human sound systems are influenced by environmental factors.

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.

The effect of population size on patterns and rates of language evolution is controversial. Do languages with larger speaker populations change faster due to a greater capacity for innovation, or do smaller populations change faster due to more efficient diffusion of innovations? Do smaller populations suffer greater loss of language elements through founder effects or drift, or do languages with more speakers lose features due to a process of simplification? Revealing the influence of population size on the tempo and mode of language evolution not only will clarify underlying mechanisms of language change but also has practical implications for the way that language data are used to reconstruct the history of human cultures. Here, we provide, to our knowledge, the first empirical, statistically robust test of the influence of population size on rates of language evolution, controlling for the evolutionary history of the populations and formally comparing the fit of different models of language evolution. We compare rates of gain and loss of cognate words for basic vocabulary in Polynesian languages, an ideal test case with a well-defined history. We demonstrate that larger populations have higher rates of gain of new words whereas smaller populations have higher rates of word loss. These results show that demographic factors can influence rates of language evolution and that rates of gain and loss are affected differently. These findings are strikingly consistent with general predictions of evolutionary models.

Some of the psychological abilities that underlie human speech are shared with other species. One hallmark of speech is that linguistic context affects both how speech sounds are categorized into phonemes, and how different versions of phonemes are produced. We here confirm earlier findings that swamp sparrows categorically perceive the notes that constitute their learned songs and then investigate how categorical boundaries differ according to context. We clustered notes according to their acoustic structure, and found statistical evidence for clustering into 10 population-wide note types. Examining how three related types were perceived, we found, in both discrimination and labeling tests, that an "intermediate" note type is categorized with a "short" type when it occurs at the beginning of a song syllable, but with a "long" type at the end of a syllable. In sum, three produced note-type clusters appear to be underlain by two perceived categories. Thus, in birdsong, as in human speech, categorical perception is context-dependent, and as is the case for human phonology, there is a complex relationship between underlying categorical representations and surface forms. Our results therefore suggest that complex phonology can evolve even in the absence of rich linguistic components, like syntax and semantics.

Although it is widely agreed that learning the syntax of natural languages involves acquiring structure-dependent rules, recent work on acquisition has nevertheless attempted to characterize the outcome of learning primarily in terms of statistical generalizations about surface distributional information. In this paper we investigate whether surface statistical knowledge or structural knowledge of English is used to infer properties of a novel language under conditions of impoverished input. We expose learners to artificial-language patterns that are equally consistent with two possible underlying grammars--one more similar to English in terms of the linear ordering of words, the other more similar on abstract structural grounds. We show that learners' grammatical inferences overwhelmingly favor structural similarity over preservation of superficial order. Importantly, the relevant shared structure can be characterized in terms of a universal preference for isomorphism in the mapping from meanings to utterances. Whereas previous empirical support for this universal has been based entirely on data from cross-linguistic language samples, our results suggest it may reflect a deep property of the human cognitive system--a property that, together with other structure-sensitive principles, constrains the acquisition of linguistic knowledge.

The word for “sky” in the indigenous Saaroa language of Taiwan is la?ica. Across the South China Sea in the Philippines, the speakers of Ilonggo use la?it, whereas, on the far-flung islands of the Pacific, Hawaiians say lani and Rarotongans and New Zealand Maori ra?i (1). Systematic sound correspondences between many such words tell us that these languages have evolved from a common ancestor to form part of the Austronesian language family. By meticulously comparing the sounds of words across many languages, linguists can learn about the genealogical relationships between languages and the people who speak them, how sounds change through time and even how long-extinct ancestral languages would have sounded. In PNAS, Bouchard-Côté et al. (2) automate this process by using probabilistic models of sound change to trace the evolution of thousands of words across more than 600 Austronesian languages.

We report on the emergence of functional flexibility in vocalizations of human infants. This vastly underappreciated capability becomes apparent when prelinguistic vocalizations express a full range of emotional content--positive, neutral, and negative. The data show that at least three types of infant vocalizations (squeals, vowel-like sounds, and growls) occur with this full range of expression by 3-4 mo of age. In contrast, infant cry and laughter, which are species-specific signals apparently homologous to vocal calls in other primates, show functional stability, with cry overwhelmingly expressing negative and laughter positive emotional states. Functional flexibility is a sine qua non in spoken language, because all words or sentences can be produced as expressions of varying emotional states and because learning conventional "meanings" requires the ability to produce sounds that are free of any predetermined function. Functional flexibility is a defining characteristic of language, and empirically it appears before syntax, word learning, and even earlier-developing features presumed to be critical to language (e.g., joint attention, syllable imitation, and canonical babbling). The appearance of functional flexibility early in the first year of human life is a critical step in the development of vocal language and may have been a critical step in the evolution of human language, preceding protosyntax and even primitive single words. Such flexible affect expression of vocalizations has not yet been reported for any nonhuman primate but if found to occur would suggest deep roots for functional flexibility of vocalization in our primate heritage.

One of the oldest problems in linguistics is reconstructing the words that appeared in the protolanguages from which modern languages evolved. Identifying the forms of these ancient languages makes it possible to evaluate proposals about the nature of language change and to draw inferences about human history. Protolanguages are typically reconstructed using a painstaking manual process known as the comparative method. We present a family of probabilistic models of sound change as well as algorithms for performing inference in these models. The resulting system automatically and accurately reconstructs protolanguages from modern languages. We apply this system to 637 Austronesian languages, providing an accurate, large-scale automatic reconstruction of a set of protolanguages. Over 85% of the system’s reconstructions are within one character of the manual reconstruction provided by a linguist specializing in Austronesian languages. Being able to automatically reconstruct large numbers of languages provides a useful way to quantitatively explore hypotheses about the factors determining which sounds in a language are likely to change over time. We demonstrate this by showing that the reconstructed Austronesian protolanguages provide compelling support for a hypothesis about the relationship between the function of a sound and its probability of changing that was first proposed in 1955.

The search for ever deeper relationships among the World’s languages is bedeviled by the fact that most words evolve too rapidly to preserve evidence of their ancestry beyond 5,000 to 9,000 y. On the other hand, quantitative modeling indicates that some “ultraconserved” words exist that might be used to find evidence for deep linguistic relationships beyond that time barrier. Here we use a statistical model, which takes into account the frequency with which words are used in common everyday speech, to predict the existence of a set of such highly conserved words among seven language families of Eurasia postulated to form a linguistic superfamily that evolved from a common ancestor around 15,000 y ago. We derive a dated phylogenetic tree of this proposed superfamily with a time-depth of ?14,450 y, implying that some frequently used words have been retained in related forms since the end of the last ice age. Words used more than once per 1,000 in everyday speech were 7- to 10-times more likely to show deep ancestry on this tree. Our results suggest a remarkable fidelity in the transmission of some words and give theoretical justification to the search for features of language that might be preserved across wide spans of time and geography.

It is generally difficult to define reasonable parameters and interpret their values in mathematical models of social phenomena. Rather than directly fitting abstract parameters against empirical data, we should define some concrete parameters to denote the sociocultural factors relevant for particular phenomena, and compute the values of these parameters based upon the corresponding empirical data. Taking the example of modeling studies of language competition, we propose a language diffusion principle and two language inheritance principles to compute two critical parameters, namely the impacts and inheritance rates of competing languages, in our language competition model derived from the Lotka–Volterra competition model in evolutionary biology. These principles assign explicit sociolinguistic meanings to those parameters and calculate their values from the relevant data of population censuses and language surveys. Using four examples of language competition, we illustrate that our language competition model with thus-estimated parameter values can reliably replicate and predict the dynamics of language competition, and it is especially useful in cases lacking direct competition data.

Languages of the world display many structural similarities. We test the hypothesis that some of these structural properties may arise from biases operating during language acquisition that shape languages over time. Specifically, we investigate whether language learners are biased toward linguistic systems that strike an efficient balance between robust information transfer, on the one hand, and effort or resource demands, on the other hand, thereby increasing the communicative utility of the acquired language. In two experiments, we expose learners to miniature artificial languages designed in such a way that they do not use their formal devices (case marking) efficiently to facilitate robust information transfer. We find that learners restructure such languages in ways that facilitate efficient information transfer compared with the input language. These systematic changes introduced by the learners follow typologically frequent patterns, supporting the hypothesis that some of the structural similarities found in natural languages are shaped by biases toward communicatively efficient linguistic systems.

We demonstrate a substantial improvement on one of the most celebrated empirical laws in the study of language, Zipf's 75-y-old theory that word length is primarily determined by frequency of use. In accord with rational theories of communication, we show across 10 languages that average information content is a much better predictor of word length than frequency. This indicates that human lexicons are efficiently structured for communication by taking into account interword statistical dependencies. Lexical systems result from an optimization of communicative pressures, coding meanings efficiently given the complex statistics of natural language use.

If you think about the classes you expect to take when studying linguistics in graduate school, probability theory is unlikely to be on the list. However, recent work in linguistics and cognitive science has begun to show that probability theory, combined with the methods of computer science and statistics, is surprisingly effective in explaining aspects of how people produce and interpret sentences (13), how language might be learned (46), and how words change over time (7, 8). The paper by Piantadosi et al. (9) that appears in PNAS adds to this literature, using probabilistic models estimated from large databases to update a classic result about the length of words.

Verbal communication is a joint activity; however, speech production and comprehension have primarily been analyzed as independent processes within the boundaries of individual brains. Here, we applied fMRI to record brain activity from both speakers and listeners during natural verbal communication. We used the speaker's spatiotemporal brain activity to model listeners' brain activity and found that the speaker's activity is spatially and temporally coupled with the listener's activity. This coupling vanishes when participants fail to communicate. Moreover, though on average the listener's brain activity mirrors the speaker's activity with a delay, we also find areas that exhibit predictive anticipatory responses. We connected the extent of neural coupling to a quantitative measure of story comprehension and find that the greater the anticipatory speaker-listener coupling, the greater the understanding. We argue that the observed alignment of production- and comprehension-based processes serves as a mechanism by which brains convey information.

The empirical evidence that human color categorization exhibits some universal patterns beyond superficial discrepancies across different cultures is a major breakthrough in cognitive science. As observed in the World Color Survey (WCS), indeed, any two groups of individuals develop quite different categorization patterns, but some universal properties can be identified by a statistical analysis over a large number of populations. Here, we reproduce the WCS in a numerical model in which different populations develop independently their own categorization systems by playing elementary language games. We find that a simple perceptual constraint shared by all humans, namely the human Just Noticeable Difference (JND), is sufficient to trigger the emergence of universal patterns that unconstrained cultural interaction fails to produce. We test the results of our experiment against real data by performing the same statistical analysis proposed to quantify the universal tendencies shown in the WCS [Kay P & Regier T. (2003) Proc. Natl. Acad. Sci. USA 100: 9085-9089], and obtain an excellent quantitative agreement. This work confirms that synthetic modeling has nowadays reached the maturity to contribute significantly to the ongoing debate in cognitive science.

Language acquisition and processing are governed by genetic constraints. A crucial unresolved question is how far these genetic constraints have coevolved with language, perhaps resulting in a highly specialized and species-specific language 'module,' and how much language acquisition and processing redeploy preexisting cognitive machinery. In the present work, we explored the circumstances under which genes encoding language-specific properties could have coevolved with language itself. We present a theoretical model, implemented in computer simulations, of key aspects of the interaction of genes and language. Our results show that genes for language could have coevolved only with highly stable aspects of the linguistic environment; a rapidly changing linguistic environment does not provide a stable target for natural selection. Thus, a biological endowment could not coevolve with properties of language that began as learned cultural conventions, because cultural conventions change much more rapidly than genes. We argue that this rules out the possibility that arbitrary properties of language, including abstract syntactic principles governing phrase structure, case marking, and agreement, have been built into a 'language module' by natural selection. The genetic basis of human language acquisition and processing did not coevolve with language, but primarily predates the emergence of language. As suggested by Darwin, the fit between language and its underlying mechanisms arose because language has evolved to fit the human brain, rather than the reverse.

Language acquisition maps linguistic experience, primary linguistic data (PLD), onto linguistic knowledge, a grammar. Classically, computational models of language acquisition assume a single target grammar and one PLD source, the central question being whether the target grammar can be acquired from the PLD. However, real-world learners confront populations with variation, i.e., multiple target grammars and PLDs. Removing this idealization has inspired a new class of population-based language acquisition models. This paper contrasts 2 such models. In the first, iterated learning (IL), each learner receives PLD from one target grammar but different learners can have different targets. In the second, social learning (SL), each learner receives PLD from possibly multiple targets, e. g., from 2 parents. We demonstrate that these 2 models have radically different evolutionary consequences. The IL model is dynamically deficient in 2 key respects. First, the IL model admits only linear dynamics and so cannot describe phase transitions, attested rapid changes in languages over time. Second, the IL model cannot properly describe the stability of languages over time. In contrast, the SL model leads to nonlinear dynamics, bifurcations, and possibly multiple equilibria and so suffices to model both the case of stable language populations, mixtures of more than 1 language, as well as rapid language change. The 2 models also make distinct, empirically testable predictions about language change. Using historical data, we show that the SL model more faithfully replicates the dynamics of the evolution of Middle English.

The enormous increase of popularity and use of the worldwide web has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with keywords known as ``tags.'' Understanding the rich emergent structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks (RWs), and complex networks theory, can effectively contribute to the mathematical modeling of social annotation systems. Here, we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of RWs. This modeling framework reproduces several aspects, thus far unexplained, of social annotation, among which are the peculiar growth of the size of the vocabulary used by the community and its complex network structure that represents an externalization of semantic structures grounded in cognition and that are typically hard to access.

Abstract According to a controversial hypothesis, a characteristic unique to human language is recursion. Contradicting this hypothesis, it has been claimed that the starling, one of the two animal species tested for this ability to date, is able to distinguish acoustic stimuli ...

Symbolic gestures, such as pantomimes that signify actions (e.g., threading a needle) or emblems that facilitate social transactions (e.g., finger to lips indicating 'be quiet'), play an important role in human communication. They are autonomous, can fully take the place of words, and function as complete utterances in their own right. The relationship between these gestures and spoken language remains unclear. We used functional MRI to investigate whether these two forms of communication are processed by the same system in the human brain. Responses to symbolic gestures, to their spoken glosses (expressing the gestures' meaning in English), and to visually and acoustically matched control stimuli were compared in a randomized block design. General Linear Models (GLM) contrasts identified shared and unique activations and functional connectivity analyses delineated regional interactions associated with each condition. Results support a model in which bilateral modality-specific areas in superior and inferior temporal cortices extract salient features from vocal-auditory and gestural-visual stimuli respectively. However, both classes of stimuli activate a common, left-lateralized network of inferior frontal and posterior temporal regions in which symbolic gestures and spoken words may be mapped onto common, corresponding conceptual representations. We suggest that these anterior and posterior perisylvian areas, identified since the mid-19th century as the core of the brain's language system, are not in fact committed to language processing, but may function as a modality-independent semiotic system that plays a broader role in human communication, linking meaning with symbols whether these are words, gestures, images, sounds, or objects.

Primate vocal behavior is often considered irrelevant in modeling human language evolution, mainly because of the caller's limited vocal control and apparent lack of intentional signaling. Here, we present the results of a long-term study on Campbell's monkeys, which has revealed an unrivaled degree of vocal complexity. Adult males produced six different loud call types, which they combined into various sequences in highly context-specific ways. We found stereotyped sequences that were strongly associated with cohesion and travel, falling trees, neighboring groups, nonpredatory animals, unspecific predatory threat, and specific predator classes. Within the responses to predators, we found that crowned eagles triggered four and leopards three different sequences, depending on how the caller learned about their presence. Callers followed a number of principles when concatenating sequences, such as nonrandom transition probabilities of call types, addition of specific calls into an existing sequence to form a different one, or recombination of two sequences to form a third one. We conclude that these primates have overcome some of the constraints of limited vocal control by combinatorial organization. As the different sequences were so tightly linked to specific external events, the Campbell's monkey call system may be the most complex example of 'proto-syntax' in animal communication known to date.

When people speak, they often insinuate their intent indirectly rather than stating it as a bald proposition. Examples include sexual come-ons, veiled threats, polite requests, and concealed bribes. We propose a three-part theory of indirect speech, based on the idea that human communication involves a mixture of cooperation and conflict. First, indirect requests allow for plausible deniability, in which a cooperative listener can accept the request, but an uncooperative one cannot react adversarially to it. This intuition is supported by a game-theoretic model that predicts the costs and benefits to a speaker of direct and indirect requests. Second, language has two functions: to convey information and to negotiate the type of relationship holding between speaker and hearer (in particular, dominance, communality, or reciprocity). The emotional costs of a mismatch in the assumed relationship type can create a need for plausible deniability and, thereby, select for indirectness even when there are no tangible costs. Third, people perceive language as a digital medium, which allows a sentence to generate common knowledge, to propagate a message with high fidelity, and to serve as a reference point in coordination games. This feature makes an indirect request qualitatively different from a direct one even when the speaker and listener can infer each other's intentions with high confidence.

Over the last 30 years, the idea that the processes producing cultural stability and change are analogous in important respects to those of biological evolution has become increasingly popular. Biological evolution is characterized by changing frequencies of genes in populations through time as a result of such processes as natural selection; likewise, cultural evolution refers to the changing distributions of cultural attributes in populations, which are affected by processes such as natural selection but also by others that have no analogue in genetic evolution. The fundamental, mathematically based theory that justified and spelled out the necessary modifications to standard population genetics theory to make it relevant to culture was laid out by Cavalli-Sforza and Feldman (1) and Boyd and Richerson (2) in the 1980s, on the basis of earlier papers, and Richard Dawkins (3) had already introduced the idea to the popular imagination with his concept of the meme as analogous to the gene. In the intervening period, the development of what has come to be called dual inheritance theory or gene ``culture coevolution theory has continued, and it has been accompanied by a slowly growing number of empirical case studies that apply these ideas to understanding patterned variation in cultural data. The article by Rogers and Ehrlich (4) in this issue of PNAS makes a significant contribution to this growing field by showing how different cultural evolutionary processes can be identified and distinguished from one another and how they differentially affect different kinds of cultural traits; it will certainly become a widely cited classic case study, and the dataset of descriptive traits of canoes from different Polynesian groups is likely to become a test bed for future cultural evolutionary studies.

It has been claimed that a meaningful theory of cultural evolution is not possible because human beliefs and behaviors do not follow predictable patterns. However, theoretical models of cultural transmission and observations of the development of societies suggest that patterns in cultural evolution do occur. Here, we analyze whether two sets of related cultural traits, one tested against the environment and the other not, evolve at different rates in the same populations. Using functional and symbolic design features for Polynesian canoes, we show that natural selection apparently slows the evolution of functional structures, whereas symbolic designs differentiate more rapidly. This finding indicates that cultural change, like genetic evolution, can follow theoretically derived patterns.

Categories provide a coarse-grained description of the world. A fundamental question is whether categories simply mirror an underlying structure of nature or instead come from the complex interactions of human beings among themselves and with the environment. Here, we address this question by modeling a population of individuals who co-evolve their own system of symbols and meanings by playing elementary language games. The central result is the emergence of a hierarchical category structure made of two distinct levels: a basic layer, responsible for fine discrimination of the environment, and a shared linguistic layer that groups together perceptions to guarantee communicative success. Remarkably, the number of linguistic categories turns out to be finite and small, as observed in natural languages.

We introduce an experimental paradigm for studying the cumulative cultural evolution of language. In doing so we provide the first experimental validation for the idea that cultural transmission can lead to the appearance of design without a designer. Our experiments involve the iterated learning of artificial languages by human participants. We show that languages transmitted culturally evolve in such a way as to maximize their own transmissibility: over time, the languages in our experiments become easier to learn and increasingly structured. Furthermore, this structure emerges purely as a consequence of the transmission of language over generations, without any intentional design on the part of individual language learners. Previous computational and mathematical models suggest that iterated learning provides an explanation for the structure of human language and link particular aspects of linguistic structure with particular constraints acting on language during its transmission. The experimental work presented here shows that the predictions of these models, and models of cultural evolution more generally, can be tested in the laboratory.

Collaborative tagging has been quickly gaining ground because of its ability to recruit the activity of web users into effectively organizing and sharing vast amounts of information. Here we collect data from a popular system and investigate the statistical properties of tag cooccurrence. We introduce a stochastic model of user behavior embodying two main aspects of collaborative tagging: (i) a frequency-bias mechanism related to the idea that users are exposed to each other's tagging activity; (ii) a notion of memory, or aging of resources, in the form of a heavy-tailed access to the past state of the system. Remarkably, our simple modeling is able to account quantitatively for the observed experimental features with a surprisingly high accuracy. This points in the direction of a universal behavior of users who, despite the complexity of their own cognitive processes and the uncoordinated and selfish nature of their tagging activity, appear to follow simple activity patterns.

Human language arises from biological evolution, individual learning, and cultural transmission, but the interaction of these three processes has not been widely studied. We set out a formal framework for analyzing cultural transmission, which allows us to investigate how innate learning biases are related to universal properties of language. We show that cultural transmission can magnify weak biases into strong linguistic universals, undermining one of the arguments for strong innate constraints on language learning. As a consequence, the strength of innate biases can be shielded from natural selection, allowing these genes to drift. Furthermore, even when there is no natural selection, cultural transmission can produce apparent adaptations. Cultural transmission thus provides an alternative to traditional nativist and adaptationist explanations for the properties of human languages.

We investigate in a series of laboratory experiments how costs and benefits of linguistic communication affect the emergence of simple languages in a coordination task when no common language is available in the beginning. The experiment involved pairwise computerized communication between 152 subjects involved in at least 60 rounds. The subjects had to develop a common code referring to items in varying lists of geometrical figures distinguished by up to three features. A code had to be made of a limited repertoire of letters. Using letters had a cost. We are interested in the question of whether a common code is developed, and what enhances its emergence. Furthermore, we explore the emergence of compositional, protogrammatical structure in such codes. We compare environments that differ in terms of available linguistic resources (number of letters available) and in terms of stability of the task environment (variability in the set of figures). Our experiments show that a too small repertoire of letters causes coordination failures. Cost efficiency and role asymmetry are important factors enhancing communicative success. In stable environments, grammars do not seem to matter much, and instead efficient arbitrary codes often do better. However, in an environment with novelty, compositional grammars offer considerable coordination advantages and therefore are more likely to arise.

The natural communication of apes may hold clues about language origins, especially because apes frequently gesture with limbs and hands, a mode of communication thought to have been the starting point of human language evolution. The present study aimed to contrast brachiomanual gestures with orofacial movements and vocalizations in the natural communication of our closest primate relatives, bonobos (Pan paniscus) and chimpanzees (Pan troglodytes). We tested whether gesture is the more flexible form of communication by measuring the strength of association between signals and specific behavioral contexts, comparing groups of both the same and different ape species. Subjects were two captive bonobo groups, a total of 13 individuals, and two captive chimpanzee groups, a total of 34 individuals. The study distinguished 31 manual gestures and 18 facial/vocal signals. It was found that homologous facial/vocal displays were used very similarly by both ape species, yet the same did not apply to gestures. Both within and between species gesture usage varied enormously. Moreover, bonobos showed greater flexibility in this regard than chimpanzees and were also the only species in which multimodal communication (i.e., combinations of gestures and facial/vocal signals) added to behavioral impact on the recipient.

All human languages perform the same function, and the set of distinctions that they use to do so is probably highly constrained. The constraints come from the universal architecture of the human mind, which influences language form through the way it hears, articulates, remembers, and learns. However, within these constraints, there is latitude for variation from language to language. For example, the major categories of subject, verb, and object vary in their typical order, and some languages signal grammatical distinctions primary by syntax, or the combinatorics of words, whereas others achieve this mainly through morphology, or the internal mutation of words. What determines the historical evolution of any particular language across the possibility space formed by these different options? In this issue of PNAS, Dediu and Ladd (1) present evidence suggestive of an answer that has seldom been considered before, which is that interpopulation genetic differences may play a role.

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.

Numerous studies indicate strong associations between languages and genes among human populations at the global scale, but all broader scale genetic and linguistic patterns must arise from processes originating at the community level. We examine linguistic and genetic variation in a contact zone on the eastern Indonesian island of Sumba, where Neolithic Austronesian farming communities settled and began interacting with aboriginal foraging societies approximately 3,500 years ago. Phylogenetic reconstruction based on a 200-word Swadesh list sampled from 29 localities supports the hypothesis that Sumbanese languages derive from a single ancestral Austronesian language. However, the proportion of cognates (words with a common origin) traceable to Proto-Austronesian (PAn) varies among language subgroups distributed across the island. Interestingly, a positive correlation was found between the percentage of Y chromosome lineages that derive from Austronesian (as opposed to aboriginal) ancestors and the retention of PAn cognates. We also find a striking correlation between the percentage of PAn cognates and geographic distance from the site where many Sumbanese believe their ancestors arrived on the island. These language-gene-geography correlations, unprecedented at such a fine scale, imply that historical patterns of social interaction between expanding farmers and resident hunter-gatherers largely explain community-level language evolution on Sumba. We propose a model to explain linguistic and demographic coevolution at fine spatial and temporal scales.

This report contains a linguistic description of a language created spontaneously without any apparent external influence in a stable existing community. We describe the syntactic structure of Al-Sayyid Bedouin Sign Language, a language that has arisen in the last 70 years in an isolated endogamous community with a high incidence of nonsyndromic, genetically recessive, profound prelingual neurosensory deafness. In the space of one generation from its inception, systematic grammatical structure has emerged in the language. Going beyond a conventionalized list of words for actions, objects, people, characteristics, and so on, a systematic way of marking the grammatical relations among those elements has appeared in the form of highly regular word order. These systematic structures cannot be attributed to influence from other languages, because the particular word orders that appear in Al-Sayyid Bedouin Sign Language differ from those found both in the ambient spoken languages in the community and in the other sign language found predominantly in the surrounding area. Therefore, the emerging grammatical structures should be regarded as an independent development within the language.

Cultural and linguistic groups are often expected to represent genetic populations. In this article, we tested the hypothesis that the hierarchical classification of languages proposed by J. Greenberg [(1987) Language in the Americas (Stanford Univ. Press, Stanford, CA)] also represents the genetic structure of Native North American populations. The genetic data are mtDNA sequences for 17 populations gleaned from literature sources and public databases. The hypothesis was rejected. Further analysis showed that departure of the genetic structure from the linguistic classification was pervasive and not due to an outlier population or a problematic language group. Therefore, Greenberg's language groups are at best an imperfect approximation to the genetic structure of these populations. Moreover, we show that the genetic structure among these Native North American populations departs significantly from the best-fitting hierarchical models. Analysis of median joining networks for mtDNA haplotypes provides strong evidence for gene flow across linguistic boundaries. In principle, the language of a population can be replaced more rapidly than its genes because language can be transmitted both vertically from parents to children and horizontally between unrelated people. However, languages are part of a cultural complex, and there may be strong pressure to maintain a language in place whereas genes are free to flow.

We address the problem, fundamental to linguistics, bioinformatics, and certain other disciplines, of using corpora of raw symbolic sequential data to infer underlying rules that govern their production. Given a corpus of strings (such as text, transcribed speech, chromosome or protein sequence data, sheet music, etc.), our unsupervised algorithm recursively distills from it hierarchically structured patterns. The ADIOS (automatic distillation of structure) algorithm relies on a statistical method for pattern extraction and on structured generalization, two processes that have been implicated in language acquisition. It has been evaluated on artificial context-free grammars with thousands of rules, on natural languages as diverse as English and Chinese, and on protein data correlating sequence with function. This unsupervised algorithm is capable of learning complex syntax, generating grammatical novel sentences, and proving useful in other fields that call for structure discovery from raw data, such as bioinformatics.

Traditional language learning theory explores an idealized interaction between a teacher and a learner. The teacher provides sentences from a language, while the learner has to infer the underlying grammar. Here, we study a new approach by considering a population of individuals that learn from each other. There is no designated teacher. We are inspired by the observation that children grow up to speak the language of their peers, not of their parents. Our goal is to characterize learning strategies that generate ``linguistic coherence,'' which means that most individuals use the same language. We model the resulting learning dynamics as a random walk of a population on a graph. Each vertex represents a candidate language. We find that a simple strategy using a certain aspiration level with the principle of win-stay, lose-shift does extremely well: stay with your current language, if at least three others use that language; otherwise, shift to an adjacent language on the graph. This strategy guarantees linguistic coherence on all nearly regular graphs, in the relevant limit where the number of candidate languages is much greater than the population size. Moreover, for many graphs, it is sufficient to have an aspiration level demanding only two other individuals to use the same language.

The emergence of a complex language is one of the fundamental events of human evolution, and several remarkable features suggest the presence of fundamental principles of organization. These principles seem to be common to all languages. The best known is the so-called Zipf's law, which states that the frequency of a word decays as a (universal) power law of its rank. The possible origins of this law have been controversial, and its meaningfulness is still an open question. In this article, the early hypothesis of Zipf of a principle of least effort for explaining the law is shown to be sound. Simultaneous minimization in the effort of both hearer and speaker is formalized with a simple optimization process operating on a binary matrix of signal-object associations. Zipf's law is found in the transition between referentially useless systems and indexical reference systems. Our finding strongly suggests that Zipf's law is a hallmark of symbolic reference and not a meaningless feature. The implications for the evolution of language are discussed. We explain how language evolution can take advantage of a communicative phase transition.

Indo-European is the largest and best-documented language family in the world, yet the reconstruction of the Indo-European tree, first proposed in 1863, has remained controversial. Complications may include ascertainment bias when choosing the linguistic data, and disregard for the wave model of 1872 when attempting to reconstruct the tree. Essentially analogous problems were solved in evolutionary genetics by DNA sequencing and phylogenetic network methods, respectively. We now adapt these tools to linguistics, and analyze Indo-European language data, focusing on Celtic and in particular on the ancient Celtic language of Gaul (modern France), by using bilingual Gaulish-Latin inscriptions. Our phylogenetic network reveals an early split of Celtic within Indo-European. Interestingly, the next branching event separates Gaulish (Continental Celtic) from the British (Insular Celtic) languages, with Insular Celtic subsequently splitting into Brythonic (Welsh, Breton) and Goidelic (Irish and Scottish Gaelic). Taken together, the network thus suggests that the Celtic language arrived in the British Isles as a single wave (and then differentiated locally), rather than in the traditional two-wave scenario ('P-Celtic' to Britain and 'Q-Celtic' to Ireland). The phylogenetic network furthermore permits the estimation of time in analogy to genetics, and we obtain tentative dates for Indo-European at 8100 BC ± 1,900 years, and for the arrival of Celtic in Britain at 3200 BC ± 1,500 years. The phylogenetic method is easily executed by hand and promises to be an informative approach for many problems in historical linguistics.

The lexicon consists of a set of word meanings and their semantic relationships. A systematic representation of the English lexicon based in psycholinguistic considerations has been put together in the database Wordnet in a long-term collaborative effort. We present here a quantitative study of the graph structure of Wordnet to understand the global organization of the lexicon. Semantic links follow power-law, scale-invariant behaviors typical of self-organizing networks. Polysemy (the ambiguity of an individual word) is one of the links in the semantic network, relating the different meanings of a common word. Polysemous links have a profound impact in the organization of the semantic graph, conforming it as a small world network, with clusters of high traffic (hubs) representing abstract concepts such as line, head, or circle. Our results show that: (i) Wordnet has global properties common to many self-organized systems, and (ii) polysemy organizes the semantic graph in a compact and categorical representation, in a way that may explain the ubiquity of polysemy across languages.

The costly signaling hypothesis proposes that animal signals are kept honest by appropriate signal costs. We show that to the contrary, signal cost is unnecessary for honest signaling even when interests conflict. We illustrate this principle by constructing examples of cost-free signaling equilibria for the two paradigmatic signaling games of Grafen (1990) and Godfray (1991). Our findings may explain why some animal signals use cost to ensure honesty whereas others do not and suggest that empirical tests of the signaling hypothesis should focus not on equilibrium cost but, rather, on the cost of deviation from equilibrium. We use these results to apply costly signaling theory to the low-cost signals that make up human language. Recent game theoretic models have shown that several key features of language could plausibly arise and be maintained by natural selection when individuals have coincident interests. In real societies, however, individuals do not have fully coincident interests. We show that coincident interests are not a prerequisite for linguistic communication, and find that many of the results derived previously can be expected also under more realistic models of society.

The Americas harbor a very great diversity of indigenous language stocks, many more than are found in any other continent. J. Nichols [(1990) Language 66, 475-521] has argued that this diversity indicates a great time depth of in situ evolution. She thus infers that the colonization of the Americas must have begun around 35,000 years ago. This estimate is much earlier than the date for which there is strong archaeological support, which does not much exceed 12,000 years. Nichols' assumption is that the diversity of linguistic stocks increases linearly with time. This paper compares the major continents of the world to show that this assumption is not correct. In fact, stock diversity is highest in the Americas, which are by consensus the youngest continents, intermediate in Australia and New Guinea, and lowest in Africa and Eurasia where the time depth is greatest. If anything, then, after an initial radiation, stock diversity decreases with time. A simple model is outlined that predicts these dynamics. It assumes that early in the peopling of continents, there are many unfilled niches for communities to live in, and so fissioning into new lineages is frequent. As the habitat is filled up, the rate of fissioning declines and lineage extinction becomes the dominant evolutionary force.

The emergence of language was a defining moment in the evolution of modern humans. It was an innovation that changed radically the character of human society. Here, we provide an approach to language evolution based on evolutionary game theory. We explore the ways in which protolanguages can evolve in a nonlinguistic society and how specific signals can become associated with specific objects. We assume that early in the evolution of language, errors in signaling and perception would be common. We model the probability of misunderstanding a signal and show that this limits the number of objects that can be described by a protolanguage. This 'error limit' is not overcome by employing more sounds but by combining a small set of more easily distinguishable sounds into words. The process of 'word formation' enables a language to encode an essentially unlimited number of objects. Next, we analyze how words can be combined into sentences and specify the conditions for the evolution of very simple grammatical rules. We argue that grammar originated as a simplified rule system that evolved by natural selection to reduce mistakes in communication. Our theory provides a systematic approach for thinking about the origin and evolution of human language.

The mammalian hypoglossal canal transmits the nerve that supplies the muscles of the tongue. This canal is absolutely and relatively larger in modern humans than it is in the African apes (Pan and Gorilla). We hypothesize that the human tongue is supplied more richly with motor nerves than are those of living apes and propose that canal size in fossil hominids may provide an indication about the motor coordination of the tongue and reflect the evolution of speech and language. Canals of gracile Australopithecus, and possibly Homo habilis, fall within the range of extant Pan and are significantly smaller than those of modern Homo. The canals of Neanderthals and an early ``modern'' Homo sapiens (Skhul 5), as well as of African and European middle Pleistocene Homo (Kabwe and Swanscombe), fall within the range of extant Homo and are significantly larger than those of Pan troglodytes. These anatomical findings suggest that the vocal capabilities of Neanderthals were the same as those of humans today. Furthermore, the vocal abilities of Australopithecus were not advanced significantly over those of chimpanzees whereas those of Homo may have been essentially modern by at least 400,000 years ago. Thus, human vocal abilities may have appeared much earlier in time than the first archaeological evidence for symbolic behavior

Linguistic evidence indicates that the Yeniseian family of languages, spoken in central Siberia, is most closely related to the Na-Dene family of languages spoken, for the most part, in northwestern North America. This hypothesis locates the source of one of the three migrations responsible for the peopling of the Americas.

The inference of the evolutionary history of a set of languages is a complex problem. Although some languages are known to be related through descent from common ancestral languages, for other languages determining whether such a relationship holds is itself a difficult problem. In this paper we report on new methods, developed by linguists Johanna Nichols (University of California, Berkeley), Donald Ringe and Ann Taylor (University of Pennsylvania, Philadelphia), and me, for answering some of the most difficult questions in this domain. These methods and the results of the analyses based on these methods were presented in November 1995 at the Symposium on the Frontiers of Science held by the National Academy of Sciences.

The genetic history of a group of populations is usually analyzed by reconstructing a tree of their origins. Reliability of the reconstruction depends on the validity of the hypothesis that genetic differentiation of the populations is mostly due to population fissions followed by independent evolution. If necessary, adjustment for major population admixtures can be made. Dating the fissions requires comparisons with paleoanthropological and paleontological dates, which are few and uncertain. A method of absolute genetic dating recently introduced uses mutation rates as molecular clocks; it was applied to human evolution using microsatellites, which have a sufficiently high mutation rate. Results are comparable with those of other methods and agree with a recent expansion of modern humans from Africa. An alternative method of analysis, useful when there is adequate geographic coverage of regions, is the geographic study of frequencies of alleles or haplotypes. As in the case of trees, it is necessary to summarize data from many loci for conclusions to be acceptable. Results must be independent from the loci used. Multivariate analyses like principal components or multidimensional scaling reveal a number of hidden patterns and evaluate their relative importance. Most patterns found in the analysis of human living populations are likely to be consequences of demographic expansions, determined by technological developments affecting food availability, transportation, or military power. During such expansions, both genes and languages are spread to potentially vast areas. In principle, this tends to create a correlation between the respective evolutionary trees. The correlation is usually positive and often remarkably high. It can be decreased or hidden by phenomena of language replacement and also of gene replacement, usually partial, due to gene flow.

In an earlier paper it was shown that linguistic families of languages spoken by a set of 38 populations associate rather strongly with an evolutionary tree of the same populations derived from genetic data. While the correlation was clearly high, there was no evaluation of statistical significance; no such test was available at the time. This gap has now been filled by adapting to this aim a procedure based on the consistency index, and the level of significance is found to be much stronger than 10(-3). Possible reasons for coevolution of strictly genetic characters and the strictly cultural linguistic system are discussed briefly. Results of this global analysis are compared with those obtained in independent local analysis.

The genetic information for this work came from a very large collection of gene frequencies for 'classical' (non-DNA) polymorphisms of the world aborigines. The data were grouped in 42 populations studied for 120 alleles. The reconstruction of human evolutionary history thus generated was checked with statistical techniques such as 'boot-strapping'. It changes some earlier conclusions and is in agreement with more recent ones, including published and unpublished DNA-marker results. The first split in the phylogenetic tree separates Africans from non-Africans, and the second separates two major clusters, one corresponding to Caucasoids, East Asians, Arctic populations, and American natives, and the other to Southeast Asians (mainland and insular), Pacific islanders, and New Guineans and Australians. Average genetic distances between the most important clusters are proportional to archaeological separation times. Linguistic families correspond to groups of populations with very few, easily understood overlaps, and their origin can be given a time frame. Linguistic superfamilies show remarkable correspondence with the two major clusters, indicating considerable parallelism between genetic and linguistic evolution. The latest step in language development may have been an important factor determining the rapid expansion that followed the appearance of modern humans and the demise of Neanderthals.

Communication between individuals of a species is likely to increase the capacity to acquire skills useful for survival and propagation and thus may confer important selective advantages. Since interaction occurs between two or more individuals, the selective process is frequency dependent, and the analysis shows that communication cannot initially increase at a reasonable rate when it is limited to random unrelated individuals, so that it is likely to abort for stochastic reasons. However, this bottleneck is removed if the communication process takes place in the nuclear family or among close relatives or if aggregation of communicators occurs because of assortative mating or meeting. Use of the individual conditional fitnesses we have introduced earlier permits an exact analysis. We show that, in general, the initial rate of increase can be geometric if and only if, in the class of selective models considered, the conditional probability of a communicator interacting with another contains a positive constant term. In our discussion of communication, cost factors for the act of communication have been omitted. However, the model has been generalized to include cooperativeness, and also altruism, or competition, by introducing costs. There is a close relationship among these situations, and the same considerations about the initial bottleneck and its resolution also extend to them. The models given here are for haploids but they extend to diploids and the conclusions are similar.