All or nothing: No half-Merge and the evolution of syntax.

In their Essay on the evolution of human language, Martins and Boeckx seek to refute what they call the "half-Merge fallacy"-the conclusion that the most elementary computational operation for human language syntax, binary set formation, or "Merge," evolved in a single step. We show that their argument collapses. It is based on a serious misunderstanding of binary set formation as well as formal language theory. Furthermore, their specific evolutionary scenario counterproposal for a "two-step" evolution of Merge does not work. Although we agree with their Essay on several points, including that there must have been many steps in the evolution of human language and the importance of understanding how language and language syntax are implemented in the brain, we disagree that there is any justification, empirical or conceptual, for the decomposition of binary set formation into separate steps.

The slings and arrows of comparative linguistics.

In this Formal Comment the authors respond to objections to their previous Essay, reiterating that comparative linguistics is not an easy undertaking.

Meaningful syntactic structure in songbird vocalizations?

The faculty of language is thought to be uniquely human. Recently, it has been claimed that songbirds are able to associate meaning with sound, comparable to the way that humans do. In human language, the meaning of expressions (semantics) is dependent on a mind-internal hierarchical structure (syntax). Meaning is associated with structure through the principle of compositionality, whereby the meaning of a complex expression is a function of the meaning of its constituent parts and the mode of composition. We argue that while recent experimental findings on songbird call sequences offer exciting novel insights into animal communication, despite claims to the contrary, they are quite unlike what we find in human language. There are indeed remarkable behavioral and neural parallels in auditory-vocal imitation learning between songbirds and human infants that are absent in our closest evolutionary relatives, the great apes. But so far, there is no convincing evidence of syntax-determined meaning in nonhuman animals.

The growth of language: Universal Grammar, experience, and principles of computation.

Human infants develop language remarkably rapidly and without overt instruction. We argue that the distinctive ontogenesis of child language arises from the interplay of three factors: domain-specific principles of language (Universal Grammar), external experience, and properties of non-linguistic domains of cognition including general learning mechanisms and principles of efficient computation. We review developmental evidence that children make use of hierarchically composed structures ('Merge') from the earliest stages and at all levels of linguistic organization. At the same time, longitudinal trajectories of development show sensitivity to the quantity of specific patterns in the input, which suggests the use of probabilistic processes as well as inductive learning mechanisms that are suitable for the psychological constraints on language acquisition. By considering the place of language in human biology and evolution, we propose an approach that integrates principles from Universal Grammar and constraints from other domains of cognition. We outline some initial results of this approach as well as challenges for future research.

Language, mind and brain.

Language serves as a cornerstone of human cognition. However, our knowledge about its neural basis is still a matter of debate, partly because 'language' is often ill-defined. Rather than equating language with 'speech' or 'communication', we propose that language is best described as a biologically determined computational cognitive mechanism that yields an unbounded array of hierarchically structured expressions. The results of recent brain imaging studies are consistent with this view of language as an autonomous cognitive mechanism, leading to a view of its neural organization, whereby language involves dynamic interactions of syntactic and semantic aspects represented in neural networks that connect the inferior frontal and superior temporal cortices functionally and structurally.

What do animals learn in artificial grammar studies?

Artificial grammar learning is a popular paradigm to study syntactic ability in nonhuman animals. Subjects are first trained to recognize strings of tokens that are sequenced according to grammatical rules. Next, to test if recognition depends on grammaticality, subjects are presented with grammar-consistent and grammar-violating test strings, which they should discriminate between. However, simpler cues may underlie discrimination if they are available. Here, we review stimulus design in a sample of studies that use particular sounds as tokens, and that claim or suggest their results demonstrate a form of sequence rule learning. To assess the extent of acoustic similarity between training and test strings, we use four simple measures corresponding to cues that are likely salient. All stimulus sets contain biases in similarity measures such that grammatical test stimuli resemble training stimuli acoustically more than do non-grammatical test stimuli. These biases may contribute to response behaviour, reducing the strength of grammatical explanations. We conclude that acoustic confounds are a blind spot in artificial grammar learning studies in nonhuman animals.

Structures, Not Strings: Linguistics as Part of the Cognitive Sciences.

There are many questions one can ask about human language: its distinctive properties, neural representation, characteristic uses including use in communicative contexts, variation, growth in the individual, and origin. Every such inquiry is guided by some concept of what 'language' is. Sharpening the core question--what is language?--and paying close attention to the basic property of the language faculty and its biological foundations makes it clear how linguistics is firmly positioned within the cognitive sciences. Here we will show how recent developments in generative grammar, taking language as a computational cognitive mechanism seriously, allow us to address issues left unexplained in the increasingly popular surface-oriented approaches to language.

Language: UG or not to be, that is the question.

Language is not the same as speech or communication; rather, it is a computational cognitive system. It has appeared very recently, consistent with a minimalist view of language's hierarchical syntactic structure.

Comparative analyses of speech and language converge on birds.

Unlike nonhuman primates, thousands of bird species have articulatory capabilities that equal or surpass those of humans, and they develop their vocalizations through vocal imitation in a way that is very similar to how human infants learn to speak. An understanding of how speech mechanisms have evolved is therefore unlikely to yield key insights into how the human brain is special.

How could language have evolved?

The evolution of the faculty of language largely remains an enigma. In this essay, we ask why. Language's evolutionary analysis is complicated because it has no equivalent in any nonhuman species. There is also no consensus regarding the essential nature of the language "phenotype." According to the "Strong Minimalist Thesis," the key distinguishing feature of language (and what evolutionary theory must explain) is hierarchical syntactic structure. The faculty of language is likely to have emerged quite recently in evolutionary terms, some 70,000-100,000 years ago, and does not seem to have undergone modification since then, though individual languages do of course change over time, operating within this basic framework. The recent emergence of language and its stability are both consistent with the Strong Minimalist Thesis, which has at its core a single repeatable operation that takes exactly two syntactic elements a and b and assembles them to form the set {a, b}.

The integration hypothesis of human language evolution and the nature of contemporary languages.

How human language arose is a mystery in the evolution of Homo sapiens. Miyagawa et al. (2013) put forward a proposal, which we will call the Integration Hypothesis of human language evolution, that holds that human language is composed of two components, E for expressive, and L for lexical. Each component has an antecedent in nature: E as found, for example, in birdsong, and L in, for example, the alarm calls of monkeys. E and L integrated uniquely in humans to give rise to language. A challenge to the Integration Hypothesis is that while these non-human systems are finite-state in nature, human language is known to require characterization by a non-finite state grammar. Our claim is that E and L, taken separately, are in fact finite-state; when a grammatical process crosses the boundary between E and L, it gives rise to the non-finite state character of human language. We provide empirical evidence for the Integration Hypothesis by showing that certain processes found in contemporary languages that have been characterized as non-finite state in nature can in fact be shown to be finite-state. We also speculate on how human language actually arose in evolution through the lens of the Integration Hypothesis.

The mystery of language evolution.

Understanding the evolution of language requires evidence regarding origins and processes that led to change. In the last 40 years, there has been an explosion of research on this problem as well as a sense that considerable progress has been made. We argue instead that the richness of ideas is accompanied by a poverty of evidence, with essentially no explanation of how and why our linguistic computations and representations evolved. We show that, to date, (1) studies of nonhuman animals provide virtually no relevant parallels to human linguistic communication, and none to the underlying biological capacity; (2) the fossil and archaeological evidence does not inform our understanding of the computations and representations of our earliest ancestors, leaving details of origins and selective pressure unresolved; (3) our understanding of the genetics of language is so impoverished that there is little hope of connecting genes to linguistic processes any time soon; (4) all modeling attempts have made unfounded assumptions, and have provided no empirical tests, thus leaving any insights into language's origins unverifiable. Based on the current state of evidence, we submit that the most fundamental questions about the origins and evolution of our linguistic capacity remain as mysterious as ever, with considerable uncertainty about the discovery of either relevant or conclusive evidence that can adjudicate among the many open hypotheses. We conclude by presenting some suggestions about possible paths forward.

The emergence of hierarchical structure in human language.

We propose a novel account for the emergence of human language syntax. Like many evolutionary innovations, language arose from the adventitious combination of two pre-existing, simpler systems that had been evolved for other functional tasks. The first system, Type E(xpression), is found in birdsong, where the same song marks territory, mating availability, and similar "expressive" functions. The second system, Type L(exical), has been suggestively found in non-human primate calls and in honeybee waggle dances, where it demarcates predicates with one or more "arguments," such as combinations of calls in monkeys or compass headings set to sun position in honeybees. We show that human language syntax is composed of two layers that parallel these two independently evolved systems: an "E" layer resembling the Type E system of birdsong and an "L" layer providing words. The existence of the "E" and "L" layers can be confirmed using standard linguistic methodology. Each layer, E and L, when considered separately, is characterizable as a finite state system, as observed in several non-human species. When the two systems are put together they interact, yielding the unbounded, non-finite state, hierarchical structure that serves as the hallmark of full-fledged human language syntax. In this way, we account for the appearance of a novel function, language, within a conventional Darwinian framework, along with its apparently unique emergence in a single species.

Evolution, brain, and the nature of language.

Language serves as a cornerstone for human cognition, yet much about its evolution remains puzzling. Recent research on this question parallels Darwin's attempt to explain both the unity of all species and their diversity. What has emerged from this research is that the unified nature of human language arises from a shared, species-specific computational ability. This ability has identifiable correlates in the brain and has remained fixed since the origin of language approximately 100 thousand years ago. Although songbirds share with humans a vocal imitation learning ability, with a similar underlying neural organization, language is uniquely human.

A Bird's Eye View of Human Language Evolution.

COMPARATIVE STUDIES OF LINGUISTIC FACULTIES IN ANIMALS POSE AN EVOLUTIONARY PARADOX: language involves certain perceptual and motor abilities, but it is not clear that this serves as more than an input-output channel for the externalization of language proper. Strikingly, the capability for auditory-vocal learning is not shared with our closest relatives, the apes, but is present in such remotely related groups as songbirds and marine mammals. There is increasing evidence for behavioral, neural, and genetic similarities between speech acquisition and birdsong learning. At the same time, researchers have applied formal linguistic analysis to the vocalizations of both primates and songbirds. What have all these studies taught us about the evolution of language? Is the comparative study of an apparently species-specific trait like language feasible? We argue that comparative analysis remains an important method for the evolutionary reconstruction and causal analysis of the mechanisms underlying language. On the one hand, common descent has been important in the evolution of the brain, such that avian and mammalian brains may be largely homologous, particularly in the case of brain regions involved in auditory perception, vocalization, and auditory memory. On the other hand, there has been convergent evolution of the capacity for auditory-vocal learning, and possibly for structuring of external vocalizations, such that apes lack the abilities that are shared between songbirds and humans. However, significant limitations to this comparative analysis remain. While all birdsong may be classified in terms of a particularly simple kind of concatenation system, the regular languages, there is no compelling evidence to date that birdsong matches the characteristic syntactic complexity of human language, arising from the composition of smaller forms like words and phrases into larger ones.

Birdsong neurolinguistics: songbird context-free grammar claim is premature.

There are remarkable behavioral, neural, and genetic similarities between song learning in songbirds and speech acquisition in human infants. Previously, we have argued that this parallel cannot be extended to the level of sentence syntax. Although birdsong can indeed have a complex structure, it lacks the combinatorial complexity of human language syntax. Recently, this conclusion has been challenged by a report purporting to show that songbirds can learn so-called context-free syntactic rules and then use them to discriminate particular syllable patterns. Here, we demonstrate that the design of this study is inadequate to draw such a conclusion, and offer alternative explanations for the experimental results that do not require the acquisition and use of context-free grammar rules or a grammar of any kind, only the simpler hypothesis of acoustic similarity matching. We conclude that the evolution of vocal learning involves both neural homologies and behavioral convergence, and that human language reflects a unique cognitive capacity.

Poverty of the stimulus revisited.

A central goal of modern generative grammar has been to discover invariant properties of human languages that reflect "the innate schematism of mind that is applied to the data of experience" and that "might reasonably be attributed to the organism itself as its contribution to the task of the acquisition of knowledge" (Chomsky, 1971). Candidates for such invariances include the structure dependence of grammatical rules, and in particular, certain constraints on question formation. Various "poverty of stimulus" (POS) arguments suggest that these invariances reflect an innate human endowment, as opposed to common experience: Such experience warrants selection of the grammars acquired only if humans assume, a priori, that selectable grammars respect substantive constraints. Recently, several researchers have tried to rebut these POS arguments. In response, we illustrate why POS arguments remain an important source of support for appeal to a priori structure-dependent constraints on the grammars that humans naturally acquire.