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)

People are remarkably smart: They use language, possess complex motor skills, make nontrivial inferences, develop and use scientific theories, make laws, and adapt to complex dynamic environments. Much of this knowledge requires concepts and this study focuses on how people acquire concepts. It is argued that conceptual development progresses from simple perceptual grouping to highly abstract scientific concepts. This proposal of conceptual development has four parts. First, it is argued that categories in the world have different structure. Second, there might (...) be different learning systems that evolved to learn categories of differing structures. Third, these systems exhibit differential maturational course, which affects how categories of different structures are learned in the course of development. And finally, an interaction of these components may result in the developmental transition from perceptual groupings to more abstract concepts. This study reviews a large body of empirical evidence supporting this proposal. (shrink)

In this third and last article on the evolution of religious capacity, the authors focus on compassion, one of religious expression's common companions. They explore the various meanings of compassion, using Biblical and early related documents, and derive general cognitive components before an evolutionary analysis of compassion using their model. Then, in taking on neural reuse theory, they adapt a model from linguistics theory to understand how neural reuse could have operated to fix religious capacity in the human genome. They (...) present a teaching tool on “Religious Capacity in Action,” and develop an example of compassionate decision making in very early Homo sapiens in North Africa. They round out their analysis of compassion by exploring theory in neuroscience on a standard decision-making model, and investigate what goes on in the human brain when a values-based decision is made. (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.

This article addresses gender differences in laughter and smiling from an evolutionary perspective. Laughter and smiling can be responses to successful display behavior or signals of affiliation amongst conversational partners—differing social and evolutionary agendas mean there are different motivations when interpreting these signals. Two experiments assess perceptions of genuine and simulated male and female laughter and amusement social signals. Results show male simulation can always be distinguished. Female simulation is more complicated as males seem to distinguish cues of simulation yet (...) judge simulated signals to be genuine. Females judge other female’s genuine signals to have higher levels of simulation. Results highlight the importance of laughter and smiling in human interactions, use of dynamic stimuli, and using multiple methodologies to assess perception. (shrink)

How linguistic structures evolve so as to become easier to process is addressed by Isbilen and Christiansen for the Now‐or‐Never bottleneck. The authors suggest that this fundamental challenge in language processing is coped with by rapid compression of the transient linguistic input into chunks then to be passed on. As linguistic structures that can be chunked more easily tend to stabilize and proliferate, language evolves to fit learners’ cognitive capabilities.

Children learn their native language by exposure to their linguistic and communicative environment, but apparently without requiring that their mistakes be corrected. Such learning from “positive evidence” has been viewed as raising “logical” problems for language acquisition. In particular, without correction, how is the child to recover from conjecturing an over-general grammar, which will be consistent with any sentence that the child hears? There have been many proposals concerning how this “logical problem” can be dissolved. In this study, we review (...) recent formal results showing that the learner has sufficient data to learn successfully from positive evidence, if it favors the simplest encoding of the linguistic input. Results include the learnability of linguistic prediction, grammaticality judgments, language production, and form-meaning mappings. The simplicity approach can also be “scaled down” to analyze the learnability of specific linguistic constructions, and it is amenable to empirical testing as a framework for describing human language acquisition. (shrink)

Evolutionary linguistics is methodologically inspired by evolutionary psychology and the neo-Darwinian, selectionist approach. Language is claimed to have evolved by means of natural selection. The focus therefore lies not on how language evolved, but on finding out why language evolved. This latter question is answered by identifying the functional benefits and adaptive status that language provides, from which in turn selective pressures are deduced. This article analyses five of the most commonly given pressures or reasons why presumably language evolved. I (...) demonstrate that these reasons depend on functional definitions of what language is. To undo this bias, I suggest that scholars move away from the ?why? and ?what for? questions of language evolution, and focus on how language actually evolved. The latter project inquires into the distinct evolutionary mechanisms enabling the evolution of the anatomical and sociocultural traits underlying linguistic behaviour. (shrink)

The contributions to this special issue on cognitive development collectively propose ways in which learning involves developing constraints that shape subsequent learning. A learning system must be constrained to learn efficiently, but some of these constraints are themselves learnable. To know how something will behave, a learner must know what kind of thing it is. Although this has led previous researchers to argue for domain-specific constraints that are tied to different kinds/domains, an exciting possibility is that kinds/domains themselves can be (...) learned. General cognitive constraints, when combined with rich inputs, can establish domains, rather than these domains necessarily preexisting prior to learning. Knowledge is structured and richly differentiated, but its “skeleton” must not always be preestablished. Instead, the skeleton may be adapted to fit patterns of co-occurrence, task requirements, and goals. Finally, we argue that for models of development to demonstrate genuine cognitive novelty, it will be helpful for them to move beyond highly preprocessed and symbolic encodings that limit flexibility. We consider two physical models that learn to make tone discriminations. They are mechanistic models that preserve rich spatial, perceptual, dynamic, and concrete information, allowing them to form surprising new classes of hypotheses and encodings. (shrink)

Our response takes advantage of the wide-ranging commentary to clarify some aspects of our original proposal and augment others. We argue against the generative critics of our coevolutionary program for the language sciences, defend the use of close-to-surface models as minimizing cross-linguistic data distortion, and stress the growing role of stochastic simulations in making generalized historical accounts testable. These methods lead the search for general principles away from idealized representations and towards selective processes. Putting cultural evolution central in understanding language (...) diversity makes learning fundamental in the cognition of language: increasingly powerful models of general learning, paired with channelled caregiver input, seem set to manage language acquisition without recourse to any innate “universal grammar.” Understanding why human language has no clear parallels in the animal world requires a cross-species perspective: crucial ingredients are vocal learning (for which there are clear non-primate parallels) and an intention-attributing cognitive infrastructure that provides a universal base for language evolution. We conclude by situating linguistic diversity within a broader trend towards understanding human cognition through the study of variation in, for example, human genetics, neurocognition, and psycholinguistic processing. (shrink)

Talk of linguistic universals has given cognitive scientists the impression that languages are all built to a common pattern. In fact, there are vanishingly few universals of language in the direct sense that all languages exhibit them. Instead, diversity can be found at almost every level of linguistic organization. This fundamentally changes the object of enquiry from a cognitive science perspective. This target article summarizes decades of cross-linguistic work by typologists and descriptive linguists, showing just how few and unprofound the (...) universal characteristics of language are, once we honestly confront the diversity offered to us by the world's 6,000 to 8,000 languages. After surveying the various uses of “universal,” we illustrate the ways languages vary radically in sound, meaning, and syntactic organization, and then we examine in more detail the core grammatical machinery of recursion, constituency, and grammatical relations. Although there are significant recurrent patterns in organization, these are better explained as stable engineering solutions satisfying multiple design constraints, reflecting both cultural-historical factors and the constraints of human cognition.Linguistic diversity then becomes the crucial datum for cognitive science: we are the only species with a communication system that is fundamentally variable at all levels. Recognizing the true extent of structural diversity in human language opens up exciting new research directions for cognitive scientists, offering thousands of different natural experiments given by different languages, with new opportunities for dialogue with biological paradigms concerned with change and diversity, and confronting us with the extraordinary plasticity of the highest human skills. (shrink)

If human language must be squeezed through a narrow cognitive bottleneck, what are the implications for language processing, acquisition, change, and structure? In our target article, we suggested that the implications are far-reaching and form the basis of an integrated account of many apparently unconnected aspects of language and language processing, as well as suggesting revision of many existing theoretical accounts. With some exceptions, commentators were generally supportive both of the existence of the bottleneck and its potential implications. Many commentators (...) suggested additional theoretical and linguistic nuances and extensions, links with prior work, and relevant computational and neuroscientific considerations; some argued for related but distinct viewpoints; a few, though, felt traditional perspectives were being abandoned too readily. Our response attempts to build on the many suggestions raised by the commentators and to engage constructively with challenges to our approach. (shrink)

Homo deceptus is a book that brings together new ideas on language, consciousness and physics into a comprehensive theory that unifies science and philosophy in a different kind of Theory of Everything. The subject of how we are to make sense of the world is addressed in a structured and ordered manner, which starts with a recognition that scientific truths are constructed within a linguistic framework. The author argues that an epistemic foundation of natural language must be understood before laying (...) claim to any notion of reality. This foundation begins with Ludwig Wittgenstein’s Tractatus Logico-Philosophicus and the relationship of language to formal logic. Ultimately, we arrive at an answer to the question of why people believe the things they do. This is effectively a modification of Alfred Tarski’s semantic theory of truth. The second major issue addressed is the ‘dreaded’ Hard Problem of Consciousness as first stated by David Chalmers in 1995. The solution is found in the unification of consciousness, information theory and notions of physicalism. The physical world is shown to be an isomorphic representation of the phenomenological conscious experience. New concepts in understanding how language operates help to explain why this relationship has been so difficult to appreciate. The inclusion of concepts from information theory shows how a digital mechanics resolves heretofore conflicting theories in physics, cognitive science and linguistics. Scientific orthodoxy is supported, but viewed in a different light. Mainstream science is not challenged, but findings are interpreted in a manner that unifies consciousness without contradiction. Digital mechanics and formal systems of logic play central roles in combining language, consciousness and the physical world into a unified theory where all can be understood within a single consistent framework. (shrink)