Iconicity and the Emergence of Combinatorial Structure in Language

In language, recombination of a discrete set of meaningless building blocks forms an unlimited set of possible utterances. How such combinatorial structure emerged in the evolution of human language is increasingly being studied. It has been shown that it can emerge when languages culturally evolve and adapt to human cognitive biases. How the emergence of combinatorial structure interacts with the existence of holistic iconic form‐meaning mappings in a language is still unknown. The experiment presented in this paper studies the role of iconicity and human cognitive learning biases in the emergence of combinatorial structure in artificial whistled languages. Participants learned and reproduced whistled words for novel objects with the use of a slide whistle. Their reproductions were used as input for the next participant, to create transmission chains and simulate cultural transmission. Two conditions were studied: one in which the persistence of iconic form‐meaning mappings was possible and one in which this was experimentally made impossible. In both conditions, cultural transmission caused the whistled languages to become more learnable and more structured, but this process was slightly delayed in the first condition. Our findings help to gain insight into when and how words may lose their iconic origins when they become part of an organized linguistic system.     

What bats have to say about speech and language

Understanding the biological foundations of language is vital to gaining insight into how the capacity for language may have evolved in humans. Animal models can be exploited to learn about the biological underpinnings of shared human traits, and although no other animals display speech or language, a range of behaviors found throughout the animal kingdom are relevant to speech and spoken language. To date, such investigations have been dominated by studies of our closest primate relatives searching for shared traits, or more distantly related species that are sophisticated vocal communicators, like songbirds. Herein I make the case for turning our attention to the Chiropterans, to shed new light on the biological encoding and evolution of human language-relevant traits. Bats employ complex vocalizations to facilitate navigation as well as social interactions, and are exquisitely tuned to acoustic information. Furthermore, bats display behaviors such as vocal learning and vocal turn-taking that are directly pertinent for human spoken language. Emerging technologies are now allowing the study of bat vocal communication, from the behavioral to the neurobiological and molecular level. Although it is clear that no single animal model can reflect the complexity of human language, by comparing such findings across diverse species we can identify the shared biological mechanisms likely to have influenced the evolution of human language.     

Using information theory to assess the diversity,complexity, and development of communicative repertoires

The application of quantitative and comparative measures from information theory on animal communication can provide novel insights into the ecological, environmental, social, and contextual properties that shape the structure, organization, and function of signal repertoires. Using 2 phylogenetically different mammalian species that share similar ecological and social constraints as examples, the authors quantitatively examined the internal structure and development of a subsystem of these species' vocal repertoires in comparison with that of human language and illustrated that these species exhibit convergent developmental processes. The authors also discussed how predictions on the structure and organization of animal communication systems can be made from this new application of information theoretic measures with respect to behavioral ecology.     

语言如何进化

人类语言具有复杂多变的递归结构,漫长的物种进化过程中唯独人类精通语言。语言的进化始于大约两百万年前的“更新世时期”,语言在当时作为一种认知适应对于人类应对自然界带给人类的挑战（如动物掠食与森林毁坏）有很大帮助。人类进化过程中学习与文化因素形成一种选择压力促使人际交流语法化,人际交流语法化引发大脑容量增加,然而,最初的语言进化与基因无关。学习与文化压力也使交流的媒介依次变为手语模式、表情模式与语言模式。交流媒介的逐渐变化最终导致了FOXP2基因突变,FOXP2基因突变让智人具有了自主的言语能力。与地球上其它的人科动物相比,人类的语言能力使人类在进化中具有明显的优势     

`Babbling' and social context in infant monkeys: parallels to human infants

Although only humans use spoken language, the vocal communication of many animals shares some features with language. Within the context of their family, normal children and young non-human primates develop proficiency in the nuances of their species-specific vocal communication system. Engaging in speech-like phonetic activity, or babbling, occurs in all normal children regardless of their native language. Similar periods of vocal development have not been described previously for non-human primates. However, in the pygmy marmoset, a South American monkey, we found that the primary vocal behavior of infants parallels many characteristics of human infant babbling. These analogous features include universality, repetition, use of a subset of the adult vocal repertoire, recognizably adult-like vocal structure and lack of a clear vocal referent. Also, like human infants, young marmosets develop in a closely knit family unit that includes both parents and often older siblings. In this context, the babbling-like behavior of the marmoset infant stimulates interaction with caregivers, thereby serving a key role in the infant's own development. These developmental and social processes indicate that the study of vocal development in non-human primate species can provide insights into the function of babbling in humans.     

Communicative and other cognitive characteristics of bottlenose dolphins

Scientists have tried to capture the rich cognitive life of dolphins through field and laboratory studies of their brain anatomy, social lives, communication and perceptual abilities. Encopheliration quotient data sugest a level of intelligence or cognitive processing in the large-brained dolphin that is closer to the human range than are our nearest primate relatives. Field studies indicate a fission-fusion type of social structure, showing social complexity rivaling that found in chimpanzee societies. Notably, cetaceans are the only mammals other than humans that clearly demonstrate vocal learning and parallels in stages of vocal learning have been reported for humans, birds and dolphins. The dolphin's vocal plasticity from infancy through adulthood, in what is probably an 'open' communication system, is likely to be related to their fission-fusion social structure and, specifically, to the fluidity of their short-term associations. However, conflicting evidence exists on the composition and organization of the dolphins whistle repertoire. In general, the level of dolphin performance on complex auditory learning and memory tasks has been compared with that of primates on similar visual tasks; however, dolphins have also demonstrated sophistrcated visual processing abilities. Laboratory studies have also provided suggestive, evidence of minor self-recognition in the dolphin, an ability previously thought to be exclusive to humans humans and apes.     

Culture-gene coevolution, norm-psychology and the emergence of human prosociality

Diverse lines of theoretical and empirical research are converging on the notion that human evolution has been substantially influenced by the interaction of our cultural and genetic inheritance systems. The application of this culture-gene coevolutionary approach to understanding human social psychology has generated novel insights into the cognitive and affective foundations of large-scale cooperation, social norms and ethnicity. This approach hypothesizes a norm-psychology: a suite of psychological adaptations for inferring, encoding in memory, adhering to, enforcing and redressing violations of the shared behavioral standards of one's community. After reviewing the substantial body of formal theory underpinning these predictions, we outline how this account organizes diverse empirical findings in the cognitive sciences and related disciplines. Norm-psychology offers explanatory traction on the evolved psychological mechanisms that underlie cultural evolution, cross-cultural differences and the emergence of norms.     

THE CUMULATIVE QUALITY OF CULTURE EXPLAINS HUMAN UNIQUENESS

What explains the unique features of human culture? Culture is not uniquely human, but human culture is uniquely cumulative. Cumulative culture is a product of our collective intelligence and is supported by cognitive processes and learning strategies that enable people to acquire, transform, and transmit information and technologies within and across generations. Technological and social innovations are currently driving unprecedented changes in cultural complexity and diversity. Innovation is a cognitively and socially complex, multistep process that typically requires (cumulative) cultural learning to achieve. I argue that the technological solutions that characterize twenty-first-century innovation can only be explained by understanding both the capacity to learn from and build upon the insights of others and the transmission systems that store the knowledge and technologies of previous generations. Human uniqueness is a product of cumulative cultural learning, transmission, and innovation.     

The cognitive bases of human tool use

This article has two goals. The first is to assess, in the face of accruing reports on the ingenuity of great ape tool use, whether and in what sense human tool use still evidences unique, higher cognitive ability. To that effect, I offer a systematic comparison between humans and nonhuman primates with respect to nine cognitive capacities deemed crucial to tool use: enhanced hand-eye coordination, body schema plasticity, causal reasoning, function representation, executive control, social learning, teaching, social intelligence, and language. Since striking differences between humans and great apes stand firm in eight out of nine of these domains, I conclude that human tool use still marks a major cognitive discontinuity between us and our closest relatives. As a second goal of the paper, I address the evolution of human technologies. In particular, I show how the cognitive traits reviewed help to explain why technological accumulation evolved so markedly in humans, and so modestly in apes.     

What's social about social learning?

Research on social learning in animals has revealed a rich variety of cases where animals--from caddis fly larvae to chimpanzees--acquire biologically important information by observing the actions of others. A great deal is known about the adaptive functions of social learning, but very little about the cognitive mechanisms that make it possible. Even in the case of imitation, a type of social learning studied in both comparative psychology and cognitive science, there has been minimal contact between the two disciplines. Social learning has been isolated from cognitive science by two longstanding assumptions: that it depends on a set of special-purpose modules--cognitive adaptations for social living; and that these learning mechanisms are largely distinct from the processes mediating human social cognition. Recent research challenges these assumptions by showing that social learning covaries with asocial learning; occurs in solitary animals; and exhibits the same features in diverse species, including humans. Drawing on this evidence, I argue that social and asocial learning depend on the same basic learning mechanisms; these are adapted for the detection of predictive relationships in all natural domains; and they are associative mechanisms--processes that encode information for long-term storage by forging excitatory and inhibitory links between event representations. Thus, human and nonhuman social learning are continuous, and social learning is adaptively specialized--it becomes distinctively "social"--only when input mechanisms (perceptual, attentional, and motivational processes) are phylogenetically or ontogenetically tuned to other agents.     

Building human-like communicative intelligence: A grounded perspective

Modern Artificial Intelligence (AI) systems excel at diverse tasks, from image classification to strategy games, even outperforming humans in many of these domains. After making astounding progress in language learning in the recent decade, AI systems, however, seem to approach the ceiling that does not reflect important aspects of human communicative capacities. Unlike human learners, communicative AI systems often fail to systematically generalize to new data, suffer from sample inefficiency, fail to capture common-sense semantic knowledge, and do not translate to real-world communicative situations. Cognitive Science offers several insights on how AI could move forward from this point. This paper aims to: (1) suggest that the dominant cognitively-inspired AI directions, based on nativist and symbolic paradigms, lack necessary substantiation and concreteness to guide progress in modern AI, and (2) articulate an alternative, “grounded”, perspective on AI advancement, inspired by Embodied, Embedded, Extended, and Enactive Cognition (4E) research. I review results on 4E research lines in Cognitive Science to distinguish the main aspects of naturalistic learning conditions that play causal roles for human language development. I then use this analysis to propose a list of concrete, implementable components for building “grounded” linguistic intelligence. These components include embodying machines in a perception–action cycle, equipping agents with active exploration mechanisms so they can build their own curriculum, allowing agents to gradually develop motor abilities to promote piecemeal language development, and endowing the agents with adaptive feedback from their physical and social environment. I hope that these ideas can direct AI research towards building machines that develop human-like language abilities through their experiences with the world.     

Precursors to language: Social cognition and pragmatic inference in primates

Despite their differences, human language and the vocal communication of nonhuman primates share many features. Both constitute forms of coordinated activity, rely on many shared neural mechanisms, and involve discrete, combinatorial cognition that includes rich pragmatic inference. These common features suggest that during evolution the ancestors of all modern primates faced similar social problems and responded with similar systems of communication and cognition. When language later evolved from this common foundation, many of its distinctive features were already present.     

Whom do children copy? Model-based biases in social learning

This review investigates the presence of young children’s model-based cultural transmission biases in social learning, arguing that such biases are adaptive and flexible. Section 1 offers five propositions regarding the presence and direction of model-based transmission biases in young children’s copying of a model. Section 2 discusses the cognitive abilities required for differing model-based biases and tracks their development in early childhood. Section 3 suggests future areas of research including considering the social aspect of model-based biases and understanding their use within a comparative perspective.     

Comparative cognitive development

This paper aims to compare cognitive development in humans and chimpanzees to illuminate the evolutionary origins of human cognition. Comparison of morphological data and life history strongly highlights the common features of all primate species, including humans. The human mother-infant relationship is characterized by the physical separation of mother and infant, and the stable supine posture of infants, that enables vocal exchange, face-to-face communication, and manual gestures. The cognitive development of chimpanzees was studied using the participation observation method. It revealed that humans and chimpanzees show similar development until 3 months of age. However, chimpanzees have a unique type of social learning that lacks the social reference observed in human children. Moreover, chimpanzees have unique immediate short-term memory capabilities. Taken together, this paper presents a plausible evolutionary scenario for the uniquely human characteristics of cognition.     

The biology and evolution of music: a comparative perspective

Studies of the biology of music (as of language) are highly interdisciplinary and demand the integration of diverse strands of evidence. In this paper, I present a comparative perspective on the biology and evolution of music, stressing the value of comparisons both with human language, and with those animal communication systems traditionally termed "song". A comparison of the "design features" of music with those of language reveals substantial overlap, along with some important differences. Most of these differences appear to stem from semantic, rather than structural, factors, suggesting a shared formal core of music and language. I next review various animal communication systems that appear related to human music, either by analogy (bird and whale "song") or potential homology (great ape bimanual drumming). A crucial comparative distinction is between learned, complex signals (like language, music and birdsong) and unlearned signals (like laughter, ape calls, or bird calls). While human vocalizations clearly build upon an acoustic and emotional foundation shared with other primates and mammals, vocal learning has evolved independently in our species since our divergence with chimpanzees. The convergent evolution of vocal learning in other species offers a powerful window into psychological and neural constraints influencing the evolution of complex signaling systems (including both song and speech), while ape drumming presents a fascinating potential homology with human instrumental music. I next discuss the archeological data relevant to music evolution, concluding on the basis of prehistoric bone flutes that instrumental music is at least 40,000 years old, and perhaps much older. I end with a brief review of adaptive functions proposed for music, concluding that no one selective force (e.g., sexual selection) is adequate to explaining all aspects of human music. I suggest that questions about the past function of music are unlikely to be answered definitively and are thus a poor choice as a research focus for biomusicology. In contrast, a comparative approach to music promises rich dividends for our future understanding of the biology and evolution of music.     

RELIGIOUS BELIEF AS ACQUIRED SECOND NATURE

Multiple authors in cognitive science of religion (CSR) argue that there is something about the human mind that disposes it to form religious beliefs. The dispositions would result from the internal architecture of the mind. In this article, I will argue that this disposition can be explained by various forms of (cultural) learning and not by the internal architecture of the mind. For my argument, I draw on new developments in predictive processing. I argue that CSR theories argue for the naturalness of religious belief in at least three ways; religious beliefs are adaptive; religious beliefs are the product of cognitive biases; and religious beliefs are the product of content biases. I argue that all three ideas can be integrated in a predictive coding framework where religious belief is learned and hence not caused by the internal architecture of the mind. I argue that the framework makes it doubtful that there are modular cognitive mechanisms for religious beliefs and that the human mind has a fixed proneness for religious belief. I also argue that a predictive coding framework can incorporate a larger role for cultural processes and allows for more flexibility.     

Toward the Language-Ready Brain: Biological Evolution and Primate Comparisons

The approach to language evolution suggested here focuses on three questions: How did the human brain evolve so that humans can develop, use, and acquire languages? How can the evolutionary quest be informed by studying brain, behavior, and social interaction in monkeys, apes, and humans? How can computational modeling advance these studies? I hypothesize that the brain is language ready in that the earliest humans had protolanguages but not languages (i.e., communication systems endowed with rich and open-ended lexicons and grammars supporting a compositional semantics), and that it took cultural evolution to yield societies (a cultural constructed niche) in which language-ready brains could become language-using brains. The mirror system hypothesis is a well-developed example of this approach, but I offer it here not as a closed theory but as an evolving framework for the development and analysis of conflicting subhypotheses in the hope of their eventual integration. I also stress that computational modeling helps us understand the evolving role of mirror neurons, not in and of themselves, but only in their interaction with systems “beyond the mirror.” Because a theory of evolution needs a clear characterization of what it is that evolved, I also outline ideas for research in neurolinguistics to complement studies of the evolution of the language-ready brain. A clear challenge is to go beyond models of speech comprehension to include sign language and models of production, and to link language to visuomotor interaction with the physical and social world.     

Thinking outside the cortex: social motivation in the evolution and development of language

Alteration of the organization of social and motivational neuroanatomical circuitry must have been an essential step in the evolution of human language. Development of vocal communication across species, particularly birdsong, and new research on the neural organization and evolution of social and motivational circuitry, together suggest that human language is the result of an obligatory link of a powerful cortico-striatal learning system, and subcortical socio-motivational circuitry.     

Iterated learning: Intergenerational knowledge transmission reveals inductive biases

Cultural transmission of information plays a central role in shaping human knowledge. Some of the most complex knowledge that people acquire, such as languages or cultural norms, can only be learned from other people, who themselves learned from previous generations. The prevalence of this process of “iterated learning” as a mode of cultural transmission raises the question of how it affects the information being transmitted. Analyses of iterated learning utilizing the assumption that the learners are Bayesian agents predict that this process should converge to an equilibrium that reflects the inductive biases of the learners. An experiment in iterated function learning with human participants confirmed this prediction, providing insight into the consequences of intergenerational knowledge transmission and a method for discovering the inductive biases that guide human inferences.