General principles of human cognition can help to explain why languages are more likely to have certain characteristics than others: structures that are difficult to process or produce will tend to be lost over time. One aspect of cognition that is implicated in language use is working memory—the component of short‐term memory used for temporary storage and manipulation of information. In this study, we consider the relationship between working memory and regularization of linguistic variation. Regularization is a well‐documented process whereby (...) languages become less variable (on some dimension) over time. This process has been argued to be driven by the behavior of individual language users, but the specific mechanism is not agreed upon. Here, we use an artificial language learning experiment to investigate whether limitations in working memory during either language learning or language production drive regularization behavior. We find that taxing working memory during production results in the loss of all types of variation, but the process by which random variation becomes more predictable is better explained by learning biases. A computational model offers a potential explanation for the production effect using a simple self‐priming mechanism. (shrink)

Research in anthropology has shown that kin terminologies have a complex combinatorial structure and vary systematically across cultures. This article argues that universals and variation in kin terminology result from the interaction of (1) an innate conceptual structure of kinship, homologous with conceptual structure in other domains, and (2) principles of optimal, “grammatical” communication active in language in general. Kin terms from two languages, English and Seneca, show how terminologies that look very different on the surface may result from variation (...) in the rankings of a universal set of constraints. Constraints on kin terms form a system: some are concerned with absolute features of kin (sex), others with the position (distance and direction) of kin in “kinship space,” others with groups and group boundaries (matrilines, patrilines, generations, etc.). Also, kin terms sometimes extend indefinitely via recursion, and recursion in kin terminology has parallels with recursion in other areas of language. Thus the study of kinship sheds light on two areas of cognition, and their phylogeny. The conceptual structure of kinship seems to borrow its organization from the conceptual structure of space, while being specialized for representing genealogy. And the grammar of kinship looks like the product of an evolved grammar faculty, opportunistically active across traditional domains of semantics, syntax, and phonology. Grammar is best understood as an offshoot of a uniquely human capacity for playing coordination games. (shrink)

This paper compares two explanations of the process by which human communication systems evolve: iterated learning and social collaboration. It then reports an experiment testing the social collaboration account. Participants engaged in a graphical communication task either as a member of a community, where they interacted with seven different partners drawn from the same pool, or as a member of an isolated pair, where they interacted with the same partner across the same number of games. Participants’ horizontal, pair‐wise interactions led (...) “bottom up” to the creation of an effective and efficient shared sign system in the community condition. Furthermore, the community‐evolved sign systems were as effective and efficient as the local sign systems developed by isolated pairs. Finally, and as predicted by a social collaboration account, and not by an iterated learning account, interaction was critical to the creation of shared sign systems, with different isolated pairs establishing different local sign systems and different communities establishing different global sign systems. (shrink)

The computational metaphor for mind is still the central guiding idea in cognitive science despite many insightful and well-founded rejections of it. There is good reason for its staying power: when we are at our cognitive best, we reason about our world with our concepts. But the challengers are right, I argue, in insisting that no reductive account of that capacity is forthcoming. Here I describe an externalist account that grounds representations in organism-level engagement with its environment, not in its (...) neural activity. (shrink)

Converging findings from English, Mandarin, and other languages suggest that observed “universals” may be algorithmic. First, computational principles behind recently developed algorithms that acquire productive constructions from raw texts or transcribed child-directed speech impose family resemblance on learnable languages. Second, child-directed speech is particularly rich in statistical (and social) cues that facilitate learning of certain types of structures.

Is the ability to speak a language an acquired skill? Leading proponents of the generative approach to human language—notably Chomsky (2000) and Pinker (2003)—have argued that the thesis that language capacities are skills is hopelessly confused and at odds with a range of empirical evidence, which suggests that human language capacities are grounded in a biologically inherited set of language instincts or a Universal Grammar (UG). In this paper, we argue that resistance to the claim that human language capacities are (...) skills has been fostered by naïve and implausible conceptions of the nature of skilled action. Correcting these misconceptions about the nature of skilled action breathes new life into the old idea that human language competences are particular kinds of skills and does so in a way that is fully consistent with appeals to the central importance of UG, broadly construed. More generally, we argue that by taking human language capacities to be skills, we capture what is right about the generative program while at the same time avoiding its most serious pitfalls. (shrink)

Distributional models of lexical semantics are capable of acquiring sophisticated representations of word meanings. The main theoretical insight provided by these models is that they demonstrate the systematic connection between the knowledge that people acquire and the experience that they have with the natural language environment. However, linguistic experience is inherently variable and differs radically across people due to demographic and cultural variables. Recently, distributional models have been used to examine how word meanings vary across languages and it was found (...) that there is considerable variability in the meanings of words across languages for most semantic categories. The goal of this article is to examine how variable word meanings are across individual language users within a single language. This was accomplished by assembling 500 individual user corpora attained from the online forum Reddit. Each user corpus ranged between 3.8 and 32.3 million words each, and a count‐based distributional framework was used to extract word meanings for each user. These representations were then used to estimate the semantic alignment of word meanings across individual language users. It was found that there are significant levels of relativity in word meanings across individuals, and these differences are partially explained by other psycholinguistic factors, such as concreteness, semantic diversity, and social aspects of language usage. These results point to word meanings being fundamentally relative and contextually fluid, with this relativeness being related to the individualized nature of linguistic experience. (shrink)

Change and variation, while inherent to language, might be seen as running counter to human communicative needs. However, variation also gives language the power to convey reliable indexical information about the speaker. This has been argued to play a significant role in allowing the establishment of large communities based on cooperative exchange , although there has been little experimental investigation of the hypothesis. Here I present a preliminary study intended to help fill this gap. Participants played an online team game (...) in which they negotiated anonymously for resources using an artificial language. Players succeeded in using linguistic cues to distinguish between their teammates and their opponents, and displayed between-team variation in the use of the language. (shrink)

The sound system of a language must be able to support a perceptual contrast between different words in order to signal communicatively relevant meaning distinctions. In this paper, we use a simple agent-based exemplar model in which the evolution of sound-category systems is understood as a co-evolutionary process, where the range of variation within sound categories is constrained by functional pressure to keep different words perceptually distinct. We show that this model can reproduce several observed effects on the range of (...) sound variation. We argue that phonological systems can be seen as finding a relative optimum of variation: Efficient communication is sustained while at the same time, hidden category variation provides pathways for future evolution. (shrink)

Behavioral genetics and cultural evolution have both revolutionized our understanding of human behavior – largely independent of each other. Here, we reconcile these two fields under a dual inheritance framework, offering a more nuanced understanding of the interaction between genes and culture. Going beyond typical analyses of gene–environment interactions, we describe the cultural dynamics that shape these interactions by shaping the environment and population structure. A cultural evolutionary approach can explain, for example, how factors such as rates of innovation and (...) diffusion, density of cultural subgroups, and tolerance for behavioral diversity impact heritability estimates, thus yielding predictions for different social contexts. Moreover, when cumulative culture functionally overlaps with genes, genetic effects become masked, unmasked, or even reversed, and the causal effects of an identified gene become confounded with features of the cultural environment. The manner of confounding is specific to a particular society at a particular time, but a WEIRD (western, educated, industrialized, rich, and democratic) sampling problem obscures this boundedness. Cultural evolutionary dynamics are typically missing from models of gene-to-phenotype causality, hindering generalizability of genetic effects across societies and across time. We lay out a reconciled framework and use it to predict the ways in which heritability should differ between societies, between socioeconomic levels, and other groupings within some societies but not others, and over the life course. An integrated cultural evolutionary behavioral genetic approach cuts through the nature–nurture debate and helps resolve controversies in topics such as IQ. (shrink)

The 29 commentaries amplified our key arguments; offered extensions, implications, and applications of the framework; and pushed back and clarified. To help forge the path forward for cultural evolutionary behavioral genetics, we (1) focus on conceptual disagreements and misconceptions about the concepts of heritability and culture; (2) further discuss points raised about the intertwined relationship between culture and genes; and (3) address extensions to the proposed framework, particularly as it relates to cultural clusters, development, and power. These commentaries, and the (...) deep engagement they represent, reinforce the importance of integrating cultural evolution and behavioral genetics. (shrink)

Cognitive Science, Volume 46, Issue 3, March 2022.

Biological evolution and cultural evolution are distinct evolutionary processes; they are apparent also in human language, where both processes contributed in shaping its evolution. However, the nature of the interaction between these two processes is still debated today. It is often claimed that the emergence of modern language was preceded by the evolution of a language-ready brain: the latter is usually intended as a product of biological evolution, while the former is believed to be the consequence of cultural processes. I (...) label this account separationist, and I argue that current evidence coming from the archaeological and fossil record suggests that cultural evolution has played a pivotal role in shaping not only modern language but also the language-ready brain. I label the latter the integrative perspective. I analyze the two accounts from two different conceptual frameworks, the Standard Evolutionary Theory and the Extended Evolutionary Synthesis, and I discuss the limits of the sharp proximate–ultimate distinction in this specific case study arguing in favor of a causal feedback model. I extend the argument to the debate on gradual and punctuational evolutionary rates, suggesting that the debate on patterns in language evolution should leave room for discussion of the nature of the processes involved in producing those patterns, providing reasons in favor of the eco-evolutionary feedback dynamics underlying the integrative perspective. (shrink)

Language evolution, intended as an open problem in the evolutionary research programme, will be here analyzed from the theoretical perspective advanced by the supporters of the Extended Evolutionary Synthesis. Four factors and two associated concepts will be matched with a selection of critical examples concerning genus Homo evolution, relevant for the evolution of language, such as the evolution of hominin life-history traits, the enlargement of the social group, increased cooperation among individuals, behavioral change and innovations, heterochronic modifications leading to increased (...) synaptic plasticity. A particular form of niche construction will be considered in a multilevel framework. It will be argued that the four points mentioned above prove to be fundamental explanatory tools to understand how language might have emerged as a result of a gene-culture coevolutionary dynamics. (shrink)

The underlying structures that are common to the world's languages bear an intriguing connection with early emerging forms of “core knowledge” (Spelke & Kinzler, 2007), which are frequently studied by infant researchers. In particular, grammatical systems often incorporate distinctions (e.g., the mass/count distinction) that reflect those made in core knowledge (e.g., the non-verbal distinction between an object and a substance). Here, I argue that this connection occurs because non-verbal core knowledge systematically biases processes of language evolution. This account potentially explains (...) a wide range of cross-linguistic grammatical phenomena that currently lack an adequate explanation. Second, I suggest that developmental researchers and cognitive scientists interested in (non-verbal) knowledge representation can exploit this connection to language by using observations about cross-linguistic grammatical tendencies to inspire hypotheses about core knowledge. (shrink)

It is a reasonable assumption that universal properties of natural languages are not accidental. They occur either because they are underwritten by genetic code, because they assist in language processing or language learning, or due to some combination of the two. In this paper we investigate one such language universal: the suffixing preference across the world’s languages, whereby inflections tend to be added to the end of words. A corpus analysis of child‐directed speech in English found that suffixes were more (...) accurate at cuing the grammatical category of the root word than were prefixes. An artificial language experiment found that there was a learning advantage for suffixes over prefixes in terms of grammatical categorization within an artificial language. The results are consistent with an account of language universals that originate in general purpose learning mechanisms. (shrink)

Rule-like behaviour is found throughout human language, provoking a number of apparently conflicting explanations. This paper frames the topic in terms of Tinbergen’s four questions and works within the context of rule-like behaviour seen both in nature and the non-linguistic domain in humans. I argue for a minimal account of linguistic rules which relies on powerful domain-general cognition, has a communicative function allowing for multiple engineering solutions, and evolves mainly culturally, while leaving the door open for some genetic adaptation in (...) the form of learning biases. (shrink)

Smith gives an excellent overview on research in language evolution, in which he discusses several recent models of how linguistic systems and the cognitive capacities involved in language learning may have co‐evolved. He illustrates how combined pressures on language learning and communication/use produce compositionally structured languages. Once in place, a (culturally transmitted) communication system creates new selection pressures on the capacity for acquiring these systems.

Two complementary approaches to a naturalistic theory of culture are, on the one hand, mainstream cultural evolution research, and, on the other, work done under the banners of cultural attraction and the epidemiology of representations. There is much agreement between these two schools of thought, including in particular a commitment to population thinking. Both schools also acknowledge that the propagation of culture is not simply a matter of replication, but rather one of reconstruction. However, the two schools of thought differ (...) on the relative importance of this point. The cultural attraction school believes it to be fundamental to genuinely causal explanations of culture. In contrast, most mainstream cultural evolution thinking abstracts away from it. In this paper I make flesh a simple thought experiment that directly contrasts the effects that replication and reconstruction have on cultural items. Results demonstrate, in a simple and graphic way, that normal cultural propagation is not replicative, but reconstructive, and that these two different modes of propagation afford two qualitatively different explanations of stability. If propagation is replicative, as it is in biology, then stability arises from the fidelity of that replication, and hence an explanation of stability comes from an explanation of how and why this high-fidelity is achieved. If, on the other hand, propagation is reconstructive, then stability arises from the fact that a subclass of cultural types are easily re-producible, while others are not, and hence an explanation of stability comes from a description of what types are easily re-producible, and an explanation of why they are. I discuss two implications of this result for research at the intersection of evolution, cognition, and culture. (shrink)

In this article, we consider infants’ acquisition of foundational aspects of language and emotion through the lens of statistical learning. By taking a comparative developmental approach, we highlight ways in which the learning problems presented by input from these two rich communicative domains are both similar and different. Our goal is to encourage other scholars to consider multiple domains of human experience when developing theories in developmental cognitive science.

This paper outlines a first attempt to model the special constraints that arise in language processing in conversation, and to explore the implications such functional considerations may have on language typology and language change. In particular, we focus on processing pressures imposed by conversational turn-taking and their consequences for the cultural evolution of the structural properties of language. We present an agent-based model of cultural evolution where agents take turns at talk in conversation. When the start of planning for the (...) next turn is constrained by the position of the verb, the stable distribution of dominant word orders across languages evolves to match the actual distribution reasonably well. We suggest that the interface of cognition and interaction should be a more central part of the story of language evolution. (shrink)

It is widely assumed that language in some form or other originated by piggybacking on pre-existing learning mechanism not dedicated to language. Using evolutionary connectionist simulations, we explore the implications of such assumptions by determining the effect of constraints derived from an earlier evolved mechanism for sequential learning on the interaction between biological and linguistic adaptation across generations of language learners. Artificial neural networks were initially allowed to evolve “biologically” to improve their sequential learning abilities, after which language was introduced (...) into the population. We compared the relative contribution of biological and linguistic adaptation by allowing both networks and language to change over time. The simulation results support two main conclusions: First, over generations, a consistent head-ordering emerged due to linguistic adaptation. This is consistent with previous studies suggesting that some apparently arbitrary aspects of linguistic structure may arise from cognitive constraints on sequential learning. Second, when networks were selected to maintain a good level of performance on the sequential learning task, language learnability is significantly improved by linguistic adaptation but not by biological adaptation. Indeed, the pressure toward maintaining a high level of sequential learning performance prevented biological assimilation of linguistic-specific knowledge from occurring. (shrink)

The general principles of perceptuo-motor processing and memory give rise to theNow-or-Never bottleneckconstraint imposed on the organization of the language processing system. In particular, the Now-or-Never bottleneck demands an appropriate structure of linguistic input and rapid incorporation of both linguistic and multisensory contextual information in a progressive, integrative manner. I argue that the emerging predictive processing framework is well suited for the task of providing a comprehensive account of language processing under the Now-or-Never constraint. Moreover, this framework presents a stronger (...) alternative to theChunk-and-Passaccount proposed by Christiansen and Chater (2016), as it better accommodates the available evidence concerning the role of context (in both the narrow and wider senses) in language comprehension at various levels of linguistic representation. Furthermore, the predictive processing approach allows for treating language as a special case of domain-general processing strategies, suggesting deep parallels with other cognitive processes such as vision. (shrink)

Two of the main theoretical approaches to the evolution of language are biolinguistics and usage-based approaches. Both are often conceptualized as belonging to seemingly irreconcilable ‘camps.’ Biolinguistic approaches assume that the ability to acquire language is based on a language-specific genetic foundation. Usage-based approaches, on the other hand, stress the importance of domain-general cognitive capacities, social cognition, and interaction. However, there have been a number of recent developments in both paradigms which suggest that biolinguistic and usage-based approaches are actually moving (...) closing together. For example, theoretical advancements such as evo-devo and complex adaptive systems theory have gained traction in the language sciences, leading to changed conceptions of issues like the relative influence of “nature” and “nurture.” In this paper, we outline points of convergence between current minimalist biolinguistic and usage-based approaches regarding four contentious issues: a) modularity and domain-specificity, b) innateness and development, c) cultural and biological evolution, d) knowledge of language and its description. We show that across both paradigms, researchers have come to increasingly embrace more complex views of these issues. They also have come to appreciate the view that biological and cultural evolution are closely intertwined, which leads to an increased amount of common ground between minimalist biolinguistics and usage-based approaches. (shrink)

Human languages vary in many ways but also show striking cross-linguistic universals. Why do these universals exist? Recent theoretical results demonstrate that Bayesian learners transmitting language to each other through iterated learning will converge on a distribution of languages that depends only on their prior biases about language and the quantity of data transmitted at each point; the structure of the world being communicated about plays no role (Griffiths & Kalish, , ). We revisit these findings and show that when (...) certain assumptions about the relationship between language and the world are abandoned, learners will converge to languages that depend on the structure of the world as well as their prior biases. These theoretical results are supported with a series of experiments showing that when human learners acquire language through iterated learning, the ultimate structure of those languages is shaped by the structure of the meanings to be communicated. (shrink)

In our opinion, the discontinuity between extant human and nonhuman minds is much broader and deeper than most researchers admit. We are happy to report that Evans & Levinson's (E&L's) target article strongly corroborates our unpopular hypothesis, and that the comparative evidence, in turn, bolsters E&L's provocative argument. Both a Universal Grammar and the “mental continuity” between human and nonhuman minds turn out to be modern myths.

In our opinion, the discontinuity between extant human and nonhuman minds is much broader and deeper than most researchers admit. We are happy to report that Evans & Levinson's (E&L's) target article strongly corroborates our unpopular hypothesis, and that the comparative evidence, in turn, bolsters E&L's provocative argument. Both a Universal Grammar and the “mental continuity” between human and nonhuman minds turn out to be modern myths.

Studies of language evolution in the lab have used the iterated learning paradigm to show how linguistic structure emerges through cultural transmission—repeated cycles of learning and use across generations of speakers. However, agent-based simulations suggest that prior biases crucially impact the outcome of cultural transmission. Here, we explored this notion through an iterated learning study of English-French bilingual adults (mostly sequential bilinguals dominant in English). Each participant learned two unstructured artificial languages in a counterbalanced fashion, one resembling English, another resembling (...) French at the phono-orthographic level. The output of each participant was passed down to the next participant, forming diffusion chains of 10 generations per language. We hypothesized that artificial languages would become easier to learn and exhibit greater structure when they were aligned with participants’ bilingual experience (i.e., English languages being easier to learn overall), or as a function of practice (i.e., languages learned second being easier to learn overall). Instead, we found that English-like languages became more structured over generations, but only when they were learned first. In contrast, French-like languages became more structured regardless of the order of learning, suggesting the presence of an asymmetric switch cost during artificial language learning. Moreover, individual differences in language usage modulated the amount of structure produced by the participants. Overall, these data suggest that bilingual experience impacts how novel languages are learned at an individual level, which can then scale up to cultural transmission of novel language at a group level. (shrink)

This article introduces the Special Issue and its focus on research in language evolution with emphasis on theory as well as computational and robotic modeling. A key theme is based on the growth of evolutionary developmental biology or evo-devo. The Special Issue consists of 13 articles organized in two sections: A) Theoretical foundations and B) Modeling and simulation studies. All the papers are interdisciplinary in nature, encompassing work in biological and linguistic foundations for the study of language evolution as well (...) as a variety of computational and robotic modeling efforts shedding light on how language may be developed and may have evolved. (shrink)

Recent research suggests that language evolution is a process of cultural change, in which linguistic structures are shaped through repeated cycles of learning and use by domain-general mechanisms. This paper draws out the implications of this viewpoint for understanding the problem of language acquisition, which is cast in a new, and much more tractable, form. In essence, the child faces a problem of induction, where the objective is to coordinate with others (C-induction), rather than to model the structure of the (...) natural world (N-induction). We argue that, of the two, C-induction is dramatically easier. More broadly, we argue that understanding the acquisition of any cultural form, whether linguistic or otherwise, during development, requires considering the corresponding question of how that cultural form arose through processes of cultural evolution. This perspective helps resolve the “logical” problem of language acquisition and has far-reaching implications for evolutionary psychology. (shrink)

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS, an implementation of the Configural Cue Model in a Maximum Entropy phonotactic-learning framework with a single free parameter, against the alternative hypothesis that learners (...) seek featurally simple algebraic rules. We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins (), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. (shrink)