The language faculty that wasn't: a usage-based account of natural language recursion

Acquiring a language vs. inducing a grammar

Standard computational models of language acquisition treat acquiring a language as a process of inducing a set of string-generating rules from a collection of linguistic data assumed to be generated by these very rules. In this paper I give theoretical and empirical arguments that such a model is radically unlike what a human language learner must do to acquire their native language. Most centrally, I argue that such models presuppose that linguistic data is directly a product of a grammar, ignoring the myriad non-grammatical systems involved in the use of language. The significance of these non-target systems in shaping the linguistic data children are exposed to undermines any simple reverse inference from linguistic data to grammatical competence.

Large Language Models: A Historical and Sociocultural Perspective

This letter explores the intricate historical and contemporary links between large language models (LLMs) and cognitive science through the lens of information theory, statistical language models, and socioanthropological linguistic theories. The emergence of LLMs highlights the enduring significance of information-based and statistical learning theories in understanding human communication. These theories, initially proposed in the mid-20th century, offered a visionary framework for integrating computational science, social sciences, and humanities, which nonetheless was not fully fulfilled at that time. The subsequent development of sociolinguistics and linguistic anthropology, especially since the 1970s, provided critical perspectives and empirical methods that both challenged and enriched this framework. This letter proposes that two pivotal concepts derived from this development, metapragmatic function and indexicality, offer a fruitful theoretical perspective for integrating the semantic, textual, and pragmatic, contextual dimensions of communication, an amalgamation that contemporary LLMs have yet to fully achieve. The author believes that contemporary cognitive science is at a crucial crossroads, where fostering interdisciplinary dialogues among computational linguistics, social linguistics and linguistic anthropology, and cognitive and social psychology is in particular imperative. Such collaboration is vital to bridge the computational, cognitive, and sociocultural aspects of human communication and human-AI interaction, especially in the era of large language and multimodal models and human-centric Artificial Intelligence (AI).

Reduced syntactic recursion in spontaneous speech of Parkinson's disease patients

Although characterized as a movement disorder, Parkinson's disease (PD) affects more than just the motor system. Within the heterogenous non-motor symptoms, language impairment is frequent but poorly understood beyond semantic processing. This study investigates the impact of PD on syntactic subordination in spontaneous language production. Fifteen PD patients in ON levodopa status narrated a short story guided by a set of pictures. Thirteen PD patients were also assessed in OFF levodopa status. Narrations were digitally recorded, subsequently transcribed and annotated, making the produced speech accessible to systematical quantitative analysis. Compared to a healthy matched control group, PD patients showed a significant reduction of subordinating structures while the number of non-embedding sentences remained unaffected. No significant effect comparing ON versus OFF levodopa status emerged. Our results suggest a contribution of the basal ganglia to language processing, such as syntactic composition, which, however, does not seem to be dopamine dependent.

Lessons learned in animal acoustic cognition through comparisons with humans

Humans are an interesting subject of study in comparative cognition. While humans have a lot of anecdotal and subjective knowledge about their own minds and behaviors, researchers tend not to study humans the way they study other species. Instead, comparisons between humans and other animals tend to be based on either assumptions about human behavior and cognition, or very different testing methods. Here we emphasize the importance of using insider knowledge about humans to form interesting research questions about animal cognition while simultaneously stepping back and treating humans like just another species as if one were an alien researcher. This perspective is extremely helpful to identify what aspects of cognitive processes may be interesting and relevant across the animal kingdom. Here we outline some examples of how this objective human-centric approach has helped us to move forward knowledge in several areas of animal acoustic cognition (rhythm, harmonicity, and vocal units). We describe how this approach works, what kind of benefits we obtain, and how it can be applied to other areas of animal cognition. While an objective human-centric approach is not useful when studying traits that do not occur in humans (e.g., magnetic spatial navigation), it can be extremely helpful when studying traits that are relevant to humans (e.g., communication). Overall, we hope to entice more people working in animal cognition to use a similar approach to maximize the benefits of being part of the animal kingdom while maintaining a detached and scientific perspective on the human species.

Cartography: Innateness or Convergent Cultural Evolution?

Haspelmath argues that linguists who conduct comparative research and try to explain patterns that are general across languages can only consider two sources of these patterns: convergent cultural evolution of languages, which provides functional explanations of these phenomena, or innate building blocks for syntactic structure, specified in the human cognitive system. This paper claims that convergent cultural evolution and functional-adaptive explanations are not sufficient to explain the existence of certain crosslinguistic phenomena. The argument is based on comparative evidence of generalizations based on Rizzi and Cinque's theories of cartographic syntax, which imply the existence of finely ordered and complex innate categories. I argue that these patterns cannot be explained in functional-adaptive terms alone.

Voice modulatory cues to structure across languages and species

Voice modulatory cues such as variations in fundamental frequency, duration and pauses are key factors for structuring vocal signals in human speech and vocal communication in other tetrapods. Voice modulation physiology is highly similar in humans and other tetrapods due to shared ancestry and shared functional pressures for efficient communication. This has led to similarly structured vocalizations across humans and other tetrapods. Nonetheless, in their details, structural characteristics may vary across species and languages. Because data concerning voice modulation in non-human tetrapod vocal production and especially perception are relatively scarce compared to human vocal production and perception, this review focuses on voice modulatory cues used for speech segmentation across human languages, highlighting comparative data where available. Cues that are used similarly across many languages may help indicate which cues may result from physiological or basic cognitive constraints, and which cues may be employed more flexibly and are shaped by cultural evolution. This suggests promising candidates for future investigation of cues to structure in non-human tetrapod vocalizations. This article is part of the theme issue 'Voice modulation: from origin and mechanism to social impact (Part I)'.

Beyond input: Language learners produce novel relative clause types without exposure

Syntax famously consists of abstract hierarchical representations, essentially instructions for combining words into larger units like sentences. Less famously, most theories of syntax also assume a higher level of abstract representation. Representations at this level comprise instructions for creating the hierarchical representations used to create sentences. To date, however there is no experimental evidence for this additional level of abstraction. Here, we explain why the existence of such representations would imply that, under certain circumstances, speakers should be able to produce structures they have never been exposed to, and we test this prediction directly. We ask: Given the right type of input, can speakers learn a syntactic structure without direct exposure? In particular, different types of relative clauses have different surface word orders. These may be represented in two ways: with many individual representations or one general representation. If the latter, then learning one type of relative clause amounts to learning all types. We teach participants a novel grammar for only some relative clause types (e.g., just subject relative clauses) and test their knowledge of other types (e.g., object relative clauses). Across experiments, participants consistently produced untrained types, implicating the existence of this higher level of abstract syntactic knowledge.

Connecting primate gesture to the evolutionary roots of language: A systematic review

Comparative psychology provides important contributions to our understanding of the origins of human language. The presence of common features in human and nonhuman primate communication can be used to suggest the evolutionary trajectories of potential precursors to language. However, to do so effectively, our findings must be comparable across diverse species. This systematic review describes the current landscape of data available from studies of gestural communication in human and nonhuman primates that make an explicit connection to language evolution. We found a similar number of studies on human and nonhuman primates, but that very few studies included data from more than one species. As a result, evolutionary inferences remain restricted to comparison across studies. We identify areas of focus, bias, and apparent gaps within the field. Different domains have been studied in human and nonhuman primates, with relatively few nonhuman primate studies of ontogeny and relatively few human studies of gesture form. Diversity in focus, methods, and socio-ecological context fill important gaps and provide nuanced understanding, but only where the source of any difference between studies is transparent. Many studies provide some definition for their use of gesture; but definitions of gesture, and in particular, criteria for intentional use, are absent in the majority of human studies. We find systematic differences between human and nonhuman primate studies in the research scope, incorporation of other modalities, research setting, and study design. We highlight eight particular areas in a call to action through which we can strengthen our ability to investigate gestural communication's contribution within the evolutionary roots of human language.

A Gestalt Theory Approach to Structure in Language

The fact that human language is highly structured and that, moreover, the way it is structured shows striking similarities in the world’s languages has been addressed from two different perspectives. The first, and more traditional, generative hypothesis is that the similarities are due to an innate language faculty. There is an inborn ‘grammar’ with universal principles that manifest themselves in each language and cross-linguistic variation arises due to a different parameter setting of universal principles. A second perspective is that there is no inborn, innate language faculty, but that instead structure emerges from language usage. This paper purports to develop and illustrate a third perspective, according to which the structural similarities in human languages are the result of the way the cognitive system works in perception. The essential claim is that structural properties follow from the limitations of human cognition in focus.

How statistical learning interacts with the socioeconomic environment to shape children's language development

Language is acquired in part through statistical learning abilities that encode environmental regularities. Language development is also heavily influenced by social environmental factors such as socioeconomic status. However, it is unknown to what extent statistical learning interacts with SES to affect language outcomes. We measured event-related potentials in 26 children aged 8–12 while they performed a visual statistical learning task. Regression analyses indicated that children’s learning performance moderated the relationship between socioeconomic status and both syntactic and vocabulary language comprehension scores. For children demonstrating high learning, socioeconomic status had a weaker effect on language compared to children showing low learning. These results suggest that high statistical learning ability can provide a buffer against the disadvantages associated with being raised in a lower socioeconomic status household.

Cortical Tracking of Speech: Toward Collaboration between the Fields of Signal and Sentence Processing

In recent years, a growing number of studies have used cortical tracking methods to investigate auditory language processing. Although most studies that employ cortical tracking stem from the field of auditory signal processing, this approach should also be of interest to psycholinguistics-particularly the subfield of sentence processing-given its potential to provide insight into dynamic language comprehension processes. However, there has been limited collaboration between these fields, which we suggest is partly because of differences in theoretical background and methodological constraints, some mutually exclusive. In this paper, we first review the theories and methodological constraints that have historically been prioritized in each field and provide concrete examples of how some of these constraints may be reconciled. We then elaborate on how further collaboration between the two fields could be mutually beneficial. Specifically, we argue that the use of cortical tracking methods may help resolve long-standing debates in the field of sentence processing that commonly used behavioral and neural measures (e.g., ERPs) have failed to adjudicate. Similarly, signal processing researchers who use cortical tracking may be able to reduce noise in the neural data and broaden the impact of their results by controlling for linguistic features of their stimuli and by using simple comprehension tasks. Overall, we argue that a balance between the methodological constraints of the two fields will lead to an overall improved understanding of language processing as well as greater clarity on what mechanisms cortical tracking of speech reflects. Increased collaboration will help resolve debates in both fields and will lead to new and exciting avenues for research.

Nonhuman rationality: a predictive coding perspective

How can we rethink 'rationality' in the wake of animal and artificial intelligence studies? Can nonhuman systems be rational in any nontrivial sense? In this paper, we propose that all organisms, under certain circumstances, exhibit rationality to a diverse degree and aspect in the sense of the standard picture (SP): Their inferential processes conform to logic and probability rules. We first show that according to Calvo and Friston (J R Soc Interface 14(131):20170096, 2017) and Orlandi (2018), all biological systems must embody a top-down process (active inference) to minimize free energy. Next, based on Maddy's (Second philosophy, Oxford University Press, Oxford, 2007; The logical must: Wittgenstein on logic, Oxford University Press, Oxford, 2014) analysis, we argue that this inferential process conforms to logic and probability rules; thus, it satisfies the SP, which explains the rudimentary logic and arithmetic (e.g., categorizing and numbering) found among pigeons and mice. We also hold that the mammalian brain is only one among many ways of implementing rationality. Finally, we discuss data from microorganisms to support this view.

How Do Living Systems Create Meaning?

Meaning has traditionally been regarded as a problem for philosophers and psychologists. Advances in cognitive science since the early 1960s, however, broadened discussions of meaning, or more technically, the semantics of perceptions, representations, and/or actions, into biology and computer science. Here, we review the notion of “meaning” as it applies to living systems, and argue that the question of how living systems create meaning unifies the biological and cognitive sciences across both organizational and temporal scales.

"This is a Titanic song": the effect of familiarity on children's learning affective meaning in music

Usage-based theories of language acquisition are thought to rely on domain-general learning mechanisms, such as mastering familiar routines by rote before generalizing to novel unfamiliar instances. If so, then the role of familiarity should extend to non-linguistic domains, like music. The purpose of the present study was to test the role of familiarity in children's learning of affective meaning of music. Music carries an affective meaning that is relayed through its elements, such as mode, rhythm, and tempo. The previous research has found differences between children and adults in their understanding of music's affective meaning, suggesting that this meaning is learned. We predicted that children would initially learn the affective meaning of familiar musical pieces before generalizing to unfamiliar pieces. Children between 3 and 5 years of age heard 16 musical segments, one for each emotion (i.e., anger, sadness, and happiness), and their accuracy in pairing music-emotion was measured. For younger children, their familiarity with the piece was positively associated with their accuracy. These results suggest that familiarity plays a role in learning affective meaning in music, providing support for the claim that this learning mechanism is domain-general.

Speed or Accuracy Instructions During Skill Learning do not Affect the Acquired Knowledge

A crucial question in skill learning research is how instruction affects the performance or the underlying representations. Little is known about the effects of instructions on one critical aspect of skill learning, namely, picking-up statistical regularities. More specifically, the present study tests how prelearning speed or accuracy instructions affect the acquisition of non-adjacent second-order dependencies. We trained 2 groups of participants on an implicit probabilistic sequence learning task: one group focused on being fast and the other on being accurate. As expected, we detected a strong instruction effect: accuracy instruction resulted in a nearly errorless performance, and speed instruction caused short reaction times (RTs). Despite the differences in the average RTs and accuracy scores, we found a similar level of statistical learning performance in the training phase. After the training phase, we tested the 2 groups under the same instruction (focusing on both speed and accuracy), and they showed comparable performance, suggesting a similar level of underlying statistical representations. Our findings support that skill learning can result in robust representations, and they highlight that this form of knowledge may appear with almost errorless performance. Moreover, multiple sessions with different instructions enabled the separation of competence from performance.

Emotional Voice Intonation: A Communication Code at the Origins of Speech Processing and Word-Meaning Associations?

The aim of the present work is to investigate the facilitating effect of vocal emotional intonation on the evolution of the following processes involved in language: (a) identifying and producing phonemes, (b) processing compositional rules underlying vocal utterances, and (c) associating vocal utterances with meanings. To this end, firstly, I examine research on the presence of these abilities in animals, and the biologically ancient nature of emotional vocalizations. Secondly, I review research attesting to the facilitating effect of emotional voice intonation on these abilities in humans. Thirdly, building on these studies in animals and humans, and through taking an evolutionary perspective, I provide insights for future empirical work on the facilitating effect of emotional intonation on these three processes in animals and preverbal humans. In this work, I highlight the importance of a comparative approach to investigate language evolution empirically. This review supports Darwin’s hypothesis, according to which the ability to express emotions through voice modulation was a key step in the evolution of spoken language.

How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning

Despite a growing body of research devoted to the study of how humans encode environmental patterns, there is still no clear consensus about the nature of the neurocognitive mechanisms underpinning statistical learning nor what factors constrain or promote its emergence across individuals, species, and learning situations. Based on a review of research examining the roles of input modality and domain, input structure and complexity, attention, neuroanatomical bases, ontogeny, and phylogeny, ten core principles are proposed. Specifically, there exist two sets of neurocognitive mechanisms underlying statistical learning. First, a "suite" of associative-based, automatic, modality-specific learning mechanisms are mediated by the general principle of cortical plasticity, which results in improved processing and perceptual facilitation of encountered stimuli. Second, an attention-dependent system, mediated by the prefrontal cortex and related attentional and working memory networks, can modulate or gate learning and is necessary in order to learn nonadjacent dependencies and to integrate global patterns across time. This theoretical framework helps clarify conflicting research findings and provides the basis for future empirical and theoretical endeavors.

Distinct neural networks for detecting violations of adjacent versus nonadjacent sequential dependencies: An fMRI study

The ability to learn and process sequential dependencies is essential for language acquisition and other cognitive domains. Recent studies suggest that the learning of adjacent (e.g., "A-B") versus nonadjacent (e.g., "A-X-B") dependencies have different cognitive demands, but the neural correlates accompanying such processing are currently underspecified. We developed a sequential learning task in which sequences of printed nonsense syllables containing both adjacent and nonadjacent dependencies were presented. After incidentally learning these grammatical sequences, twenty-one healthy adults (age M = 22.1, 12 females) made familiarity judgments about novel grammatical sequences and ungrammatical sequences containing violations of the adjacent or nonadjacent structure while in a 3T MRI scanner. Violations of adjacent dependencies were associated with increased BOLD activation in both posterior (lateral occipital and angular gyrus) as well as frontal regions (e.g., medial frontal gyrus, inferior frontal gyrus). Initial results indicated no regions showing significant BOLD activations for the violations of nonadjacent dependencies. However, when using a less stringent cluster threshold, exploratory analyses revealed that violations of nonadjacent dependencies were associated with increased activation in subcallosal cortex, paracingulate cortex, and anterior cingulate cortex (ACC). Finally, when directly comparing the adjacent condition to the nonadjacent condition, we found significantly greater levels of activation for the right superior lateral occipital cortex (BA 19) for the adjacent relative to nonadjacent condition. In sum, the detection of violations of adjacent and nonadjacent dependencies appear to involve distinct neural networks, with perceptual brain regions mediating the processing of adjacent but not nonadjacent dependencies. These results are consistent with recent proposals that statistical-sequential learning is not a unified construct but depends on the interaction of multiple neurocognitive mechanisms acting together.

Human Linguisticality and the Building Blocks of Languages

This paper discusses the widely held idea that the building blocks of languages (features, categories, and architectures) are part of an innate blueprint for Human Language, and notes that if one allows for convergent cultural evolution of grammatical structures, then much of the motivation for it disappears. I start by observing that human linguisticality (=the biological capacity for language) is uncontroversial, and that confusing terminology ("language faculty," "universal grammar") has often clouded the substantive issues in the past. I argue that like musicality and other biological capacities, linguisticality is best studied in a broadly comparative perspective. Comparing languages like other aspects of culture means that the comparisons are of the Greenbergian type, but many linguists have presupposed that the comparisons should be done as in chemistry, with the presupposition that the innate building blocks are also the material that individual grammars are made of. In actual fact, the structural uniqueness of languages (in lexicon, phonology, and morphosyntax) leads us to prefer a Greenbergian approach to comparison, which is also more in line with the Minimalist idea that there are very few domain-specific elements of the biological capacity for language.

Constructing a Consensus on Language Evolution? Convergences and Differences Between Biolinguistic and Usage-Based Approaches

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 closer together. For example, theoretical advancements such as evo-devo and complex adaptive system 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: (1) modularity and domain specificity; (2) innateness and development; (3) cultural and biological evolution; and (4) 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 lead to an increased amount of common ground between minimalist biolinguistics and usage-based approaches.

Is there a prediction network? Meta-analytic evidence for a cortical-subcortical network likely subserving prediction

Predictive coding is an increasingly influential and ambitious concept in neuroscience viewing the brain as a 'hypothesis testing machine' that constantly strives to minimize prediction error, the gap between its predictions and the actual sensory input. Despite the invaluable contribution of this framework to the formulation of brain function, its neuroanatomical foundations have not been fully defined. To address this gap, we conducted activation likelihood estimation (ALE) meta-analysis of 39 neuroimaging studies of three functional domains (action perception, language and music) inherently involving prediction. The ALE analysis revealed a widely distributed brain network encompassing regions within the inferior and middle frontal gyri, anterior insula, premotor cortex, pre-supplementary motor area, temporoparietal junction, striatum, thalamus/subthalamus and the cerebellum. This network is proposed to subserve domain-general prediction and its relevance to motor control, attention, implicit learning and social cognition is discussed in light of the predictive coding scheme. Better understanding of the presented network may help advance treatments of neuropsychiatric conditions related to aberrant prediction processing and promote cognitive enhancement in healthy individuals.

Infinite Generation of Language Unreachable From a Stepwise Approach

Language is commonly thought of as a culturally evolved system of communication rather than a computational system for generating linguistic objects that express thought. Furthermore, language is commonly argued to have gradually evolved from finite proto-language which eventually developed into infinite language of modern humans. Both ideas are typically integrated in accounts that attempt to explain gradual evolution of more complex language from the increasingly strong pressures of communicative needs. Recently some arguments have been presented that the probability of the emergence of infinitely productive languages is increased by communicative pressures. These arguments fail. The question whether decidable languages evolve into infinite language is vacuous since infinite generation is the null hypothesis for a generative procedure. The argument that increasing cardinality leads to infinite language is incoherent since it essentially conflates concepts of performance with notions of competence. Recursive characterization of infinite language is perfectly consistent with finite output. Further, the discussion completely ignores a basic insight that language is not about decidability of weakly generated strings but rather about properties of strongly generated structures. Finally, the plausibility proof that infinite productivity evolves from finite language is false because it confuses (infinite) cardinal numbers with (natural) ordinal numbers. Infinite generation cannot be reached with a stepwise approach.

Under What Conditions Can Recursion Be Learned? Effects of Starting Small in Artificial Grammar Learning of Center-Embedded Structure

It has been suggested that external and/or internal limitations paradoxically may lead to superior learning, that is, the concepts of starting small and less is more (Elman, 1993; Newport, 1990). In this paper, we explore the type of incremental ordering during training that might help learning, and what mechanism explains this facilitation. We report four artificial grammar learning experiments with human participants. In Experiments 1a and 1b we found a beneficial effect of starting small using two types of simple recursive grammars: right‐branching and center‐embedding, with recursive embedded clauses in fixed positions and fixed length. This effect was replicated in Experiment 2 (N = 100). In Experiment 3 and 4, we used a more complex center‐embedded grammar with recursive loops in variable positions, producing strings of variable length. When participants were presented an incremental ordering of training stimuli, as in natural language, they were better able to generalize their knowledge of simple units to more complex units when the training input “grew” according to structural complexity, compared to when it “grew” according to string length. Overall, the results suggest that starting small confers an advantage for learning complex center‐embedded structures when the input is organized according to structural complexity.

Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension

Recent decades have ushered in tremendous progress in understanding the neural basis of language. Most of our current knowledge on language and the brain, however, is derived from lab-based experiments that are far removed from everyday language use, and that are inspired by questions originating in linguistic and psycholinguistic contexts. In this paper we argue that in order to make progress, the field needs to shift its focus to understanding the neurobiology of naturalistic language comprehension. We present here a new conceptual framework for understanding the neurobiological organization of language comprehension. This framework is non-language-centered in the computational/neurobiological constructs it identifies, and focuses strongly on context. Our core arguments address three general issues: (i) the difficulty in extending language-centric explanations to discourse; (ii) the necessity of taking context as a serious topic of study, modeling it formally and acknowledging the limitations on external validity when studying language comprehension outside context; and (iii) the tenuous status of the language network as an explanatory construct. We argue that adopting this framework means that neurobiological studies of language will be less focused on identifying correlations between brain activity patterns and mechanisms postulated by psycholinguistic theories. Instead, they will be less self-referential and increasingly more inclined towards integration of language with other cognitive systems, ultimately doing more justice to the neurobiological organization of language and how it supports language as it is used in everyday life.

Rethinking foundations of language from a multidisciplinary perspective

The issue of language foundations has been of great controversy ever since it was first raised in Lenneberg's (1967) monograph Biological Foundations of Language. Based on a survey of recent findings relevant to the study of language acquisition and evolution, we propose that: (i) the biological predispositions for language are largely domain-general, not necessarily language-specific or human-unique; (ii) the socio-cultural environment of language serves as another important foundation of language, which helps shape language components, induce and drive language shift; and (iii) language must have coevolved with the cognitive mechanisms associated with it through intertwined biological and cultural evolution. In addition to theoretical issues, this paper also evaluates the primary approaches recently joining the endeavor of studying language foundations and evolution, including human experiments and computer simulations. Most of the evidence surveyed in this paper comes from a variety of disciplines, and methodology therein complements each other to form a global picture of language foundations. These reflect the complexity of the issue of language foundations and the necessity of taking a multidisciplinary perspective to address it.

Child first language and adult second language are both tied to general-purpose learning systems

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.

The Molecular Basis of Human Brain Evolution

Humans are a remarkable species, especially because of the remarkable properties of their brain. Since the split from the chimpanzee lineage, the human brain has increased three-fold in size and has acquired abilities for vocal learning, language and intense cooperation. To better understand the molecular basis of these changes is of great biological and biomedical interest. However, all the about 16 million fixed genetic changes that occurred during human evolution are fully correlated with all molecular, cellular, anatomical and behavioral changes that occurred during this time. Hence, as humans and chimpanzees cannot be crossed or genetically manipulated, no direct evidence for linking particular genetic and molecular changes to human brain evolution can be obtained. Here, I sketch a framework how indirect evidence can be obtained and review findings related to the molecular basis of human cognition, vocal learning and brain size. In particular, I discuss how a comprehensive comparative approach, leveraging cellular systems and genomic technologies, could inform the evolution of our brain in the future.

Assessing the uniqueness of language: Animal grammatical abilities take center stage

Questions related to the uniqueness of language can only be addressed properly by referring to sound knowledge of the relevant cognitive abilities of nonhuman animals. A key question concerns the nature and extent of animal rule-learning abilities. I discuss two approaches used to assess these abilities. One is comparing the structures of animal vocalizations to linguistic ones, and another is addressing the grammatical rule- and pattern-learning abilities of animals through experiments using artificial grammars. Neither of these approaches has so far provided unambiguous evidence of advanced animal abilities. However, when we consider how animal vocalizations are analyzed, the types of stimuli and tasks that are used in artificial grammar learning experiments, the limited number of species examined, and the groups to which these belong, I argue that the currently available evidence is insufficient to arrive at firm conclusions concerning the limitations of animal grammatical abilities. As a consequence, the gap between human linguistic rule-learning abilities and those of nonhuman animals may be smaller and less clear than is currently assumed. This means that it is still an open question whether a difference in the rule-learning and rule abstraction abilities between animals and humans played the key role in the evolution of language.

Sequential learning in individuals with agrammatic aphasia: evidence from artificial grammar learning

We examined sequential learning in individuals with agrammatic aphasia (n = 12) and healthy age-matched participants (n = 12) using an artificial grammar. Artificial grammar acquisition, 24-hour retention, and the potential benefits of additional training were examined by administering an artificial grammar judgment test (1) immediately following auditory exposure-based training, (2) one day after training, and (3) after a second training session on the second day. An untrained control group (n = 12 healthy age-matched participants) completed the tests on the same time schedule. The trained healthy and aphasic groups showed greater sensitivity to the detection of grammatical items than the control group. No significant correlations between sequential learning and language abilities were observed among the aphasic participants. The results suggest that individuals with agrammatic aphasia show sequential learning, but the underlying processes involved in this learning may be different than for healthy adults.

Visual statistical learning is related to natural language ability in adults: An ERP study

Statistical learning (SL) is believed to enable language acquisition by allowing individuals to learn regularities within linguistic input. However, neural evidence supporting a direct relationship between SL and language ability is scarce. We investigated whether there are associations between event-related potential (ERP) correlates of SL and language abilities while controlling for the general level of selective attention. Seventeen adults completed tests of visual SL, receptive vocabulary, grammatical ability, and sentence completion. Response times and ERPs showed that SL is related to receptive vocabulary and grammatical ability. ERPs indicated that the relationship between SL and grammatical ability was independent of attention while the association between SL and receptive vocabulary depended on attention. The implications of these dissociative relationships in terms of underlying mechanisms of SL and language are discussed. These results further elucidate the cognitive nature of the links between SL mechanisms and language abilities.

Influence of Perceptual Saliency Hierarchy on Learning of Language Structures: An Artificial Language Learning Experiment

Psychological experiments have revealed that in normal visual perception of humans, color cues are more salient than shape cues, which are more salient than textural patterns. We carried out an artificial language learning experiment to study whether such perceptual saliency hierarchy (color > shape > texture) influences the learning of orders regulating adjectives of involved visual features in a manner either congruent (expressing a salient feature in a salient part of the form) or incongruent (expressing a salient feature in a less salient part of the form) with that hierarchy. Results showed that within a few rounds of learning participants could learn the compositional segments encoding the visual features and the order between them, generalize the learned knowledge to unseen instances with the same or different orders, and show learning biases for orders that are congruent with the perceptual saliency hierarchy. Although the learning performances for both the biased and unbiased orders became similar given more learning trials, our study confirms that this type of individual perceptual constraint could contribute to the structural configuration of language, and points out that such constraint, as well as other factors, could collectively affect the structural diversity in languages.

Fronto-Parietal Contributions to Phonological Processes in Successful Artificial Grammar Learning

Sensitivity to regularities plays a crucial role in the acquisition of various linguistic features from spoken language input. Artificial grammar learning paradigms explore pattern recognition abilities in a set of structured sequences (i.e., of syllables or letters). In the present study, we investigated the functional underpinnings of learning phonological regularities in auditorily presented syllable sequences. While previous neuroimaging studies either focused on functional differences between the processing of correct vs. incorrect sequences or between different levels of sequence complexity, here the focus is on the neural foundation of the actual learning success. During functional magnetic resonance imaging (fMRI), participants were exposed to a set of syllable sequences with an underlying phonological rule system, known to ensure performance differences between participants. We expected that successful learning and rule application would require phonological segmentation and phoneme comparison. As an outcome of four alternating learning and test fMRI sessions, participants split into successful learners and non-learners. Relative to non-learners, successful learners showed increased task-related activity in a fronto-parietal network of brain areas encompassing the left lateral premotor cortex as well as bilateral superior and inferior parietal cortices during both learning and rule application. These areas were previously associated with phonological segmentation, phoneme comparison, and verbal working memory. Based on these activity patterns and the phonological strategies for rule acquisition and application, we argue that successful learning and processing of complex phonological rules in our paradigm is mediated via a fronto-parietal network for phonological processes.

Squeezing through the Now-or-Never bottleneck: Reconnecting language processing, acquisition, change, and structure

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.

Linguistic explanation and domain specialization: a case study in bound variable anaphora

The core question behind this Frontiers research topic is whether explaining linguistic phenomena requires appeal to properties of human cognition that are specialized to language. We argue here that investigating this issue requires taking linguistic research results seriously, and evaluating these for domain-specificity. We present a particular empirical phenomenon, bound variable interpretations of pronouns dependent on a quantifier phrase, and argue for a particular theory of this empirical domain that is couched at a level of theoretical depth which allows its principles to be evaluated for domain-specialization. We argue that the relevant principles are specialized when they apply in the domain of language, even if analogs of them are plausibly at work elsewhere in cognition or the natural world more generally. So certain principles may be specialized to language, though not, ultimately, unique to it. Such specialization is underpinned by ultimately biological factors, hence part of UG.