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ScienceDirect Editorial overview: Communication and language: Animal communication and human language Michael S Brainard and W Tecumseh Fitch Current Opinion in Neurobiology 2014, 28:v–viii For a complete overview see the Issue Available online 2nd September 2014 http://dx.doi.org/10.1016/j.conb.2014.07.015 0959-4388/# 2014 Elsevier Ltd. All right reserved.
Michael S Brainard UCSF MC 0444, 675 Nelson Rising Lane, Room 514E, San Francisco, CA 94158, USA e-mail: [email protected] Michael S Brainard is Professor of Physiology and Psychiatry at UC San Francisco and an Investigator of the Howard Hughes Medical Institute. His research focuses on behavioral, neural, and genetic mechanisms of sensorymotor learning, using vocal learning in the songbird as a model.
W Tecumseh Fitch Faculty of Life Sciences, University of Vienna, 14 Althanstrasse, A-1090 Vienna, Austria W Tecumseh Fitch is a biologist and cognitive scientist at the University of Vienna, where he heads the Department of Cognitive Biology. His core interests are in the evolution of cognition and communication in vertebrates, including humans. He has worked both on the physics and physiology of sound production (bioacoustics) and, using a broad comparative method, on the perceptual and cognitive bases for complex pattern perception.
www.sciencedirect.com
Introduction Scholars have been comparing and contrasting human language and animal communication since ancient times. For example, around 350 BC Aristotle wondered why dolphins, though clearly intelligent, are unable to speak. He concluded that the dolphin’s ‘tongue is not loose, nor has it lips, so as to give utterance to an articulate sound (or a sound of vowel and consonant in combination)’ (Book IV, part 9 ‘Voice’ [1]). Since these early times, scholars have remained consistently interested in comparing language and animal calls, whether they emphasized the similarities or differences (e.g., [2–5]). But this interest has accelerated in the last few decades, leading to impressive gains in our scientific understanding of animal communication at many levels. These advances range from the basic physics of vocal production to the neural mechanisms controlling vocalizations and their perception, and even the genetic and developmental mechanisms underlying those neural mechanisms. Our goal as editors of this special issue was to provide a concise and up-to-date review of this scientific progress, emphasizing how comparisons among multiple species can help clarify commonalities, and sharpen key distinctions, that are relevant to human spoken language. The articles mainly focus on acoustic communication in animals and spoken language in humans. Although we are well aware that human language can be expressed via multiple modalities (e.g. writing or signed language), speech is the biological default modality for linguistic communication, and vocal communication provides many of the clearest examples illustrating the value of a broad comparative approach. For example we review in detail the capacity for complex vocal learning (the ability to reproduce sounds heard in the environment that are not part of an inborn species repertoire). The capacity for vocal learning is a fundamental prerequisite for our ability to acquire a large and flexible vocabulary shared among a speech community, and although highly developed in humans, appears to be absent or extremely limited in nonhuman primates. Nonetheless this capacity has evolved convergently in many other vertebrates including a number of mammalian clades along with songbirds (where it is best understood from a neuroscientific viewpoint). Research on songbirds has also provided important insights into the molecular, genetic, and developmental basis for the neural circuitry underlying vocal learning (Matsunaga and Okanoya; Tchernichovski and Marcus; Wohlgemuth et al.). Here we offer what is to our knowledge the first review under one cover of all known vocal-learning mammals including elephants (Stoeger and Manger), bats (Kno¨rnschild), pinnipeds (Reichmuth and Casey) and cetaceans (Janik), as well as an exploration of the possible adaptive benefits of vocal learning (Nowicki). Current Opinion in Neurobiology 2014, 28:v–viii
vi Communication and language
We also explore the area of animal pattern learning in multiple species, which has seen an explosion of recent interest. This topic is especially relevant in birds (reviewed in ten Cate as well as Gentner), where the neural basis of both production and perception of complex learned patterns can be explored in detail. Beyond these two general foci, we have taken a very broad comparative approach, including reviews of vocal communication in species that are not thought to exhibit imitative vocal learning, such as fish (Ladich, Fernald), frogs (Ryan and Guerra, Sweeney and Kelley) and mice (Portfors and Perkel). These examples enable exploration of the degree to which the neural basis for vocal control in all vertebrates, including fish and frogs, follows a shared ‘Bauplan’, upon which neural mechanisms for learning are elaborated (Bass). A similar question is asked concerning broad similarities in the neural underpinnings of social behavior and communication among vertebrates (Hoffman; Fernald). All of these reviews suggest that basic and important aspects of human social behavior and communication have very deep evolutionary roots indeed, and may have evolved in the early jawed fish that was the common ancestor of all terrestrial vertebrates and most living fish. We have not, of course, neglected our closest relatives, the primates. Comparisons of nonhuman primate vocal communication with spoken language from both neural (Rilling; Ghazanfar and Eliades) and behavioral (Seyfarth and Cheney, Zuberbuhler) perspectives illustrate a complex mix of similarities and differences. Such comparisons exemplify the need to separate vocal production (where the differences are quite evident) from vocal perception, and the interpretation of complex sequences of vocalization, where deep similarities with human abilities are clear. Regarding language, several of the reviews in this issue provide brief authoritative overviews of the current state of the art in neurolinguistics and the neural basis of human linguistic competence. Although many issues in this discipline remain controversial, it is now widely agreed that the ‘classical’ model of human language processing as confined to Broca’s and Wernicke’s areas in the left hemisphere is seriously incomplete, with many other brain regions in both hemispheres playing important roles (Poeppel, Hagoort). An important new development has used noninvasive brain-imaging techniques to investigate connectivity between different brain regions (e.g. diffusion tensor imaging and related approaches), which again reveals a complex mixture of similarities and differences in connectivity when comparing humans with other primates (Rilling; Simonyan; Catani). Although our understanding of the differences is clearest with regard to speech production (see below), it is also becoming clear that at least some aspects of more challenging components of human language, including syntax and semantics, can be tentatively linked to changes in brain structure (e.g. the Current Opinion in Neurobiology 2014, 28:v–viii
six-fold expansion of Broca’s area, and its greatly increased connection to posterior brain regions, in humans relative to chimpanzees, cf. Rilling).
The value of a broad comparative approach A key area of agreement among most of the authors in this special issue is the central value of a broad comparative approach, which seeks appropriate species for approaching a particular problem that go beyond the typical list of ‘worm, fly, mouse, monkey, . . .’ or so-called ‘model’ organisms. The essential idea here has been dubbed the ‘August Krogh Principle’ [6,7]: that for many biological problems there is some organism particularly suitable for its study. While originally introduced in the context of physiology, it is equally true for neuroscience or ethology. Often, comparisons of a pair of related species that contrast on some particular trait can be most revealing. For example, the contrast between vocal-learning and non-learning birds has helped to reveal the neural bases of vocal learning. This can be true in investigating phylogenetic and evolutionary issues as well: As reviewed in Ryan (in this issue) the comparison of related frogs that either do or do not possess a low-frequency ‘chuck’ element in their calls helped to reveal both the mechanistic basis of that component and the evolutionary forces that drove the evolution of this trait (in this case sexual selection: the mating preferences of female frogs). Other well-known illustrations of this point include comparisons between monogamous and polygynous rodent species [8–10] or comparisons of domesticated and wild-type members of the same species [11–14]. Such paired comparisons, based on a specific contrast of interest, provide a rich source of knowledge. But any comparison of just two species (or two clades representing a single evolutionary event) suffers from a statistical power issue, and it is here that the virtues of a broad comparative approach become most evident. Convergently evolved traits, by definition, represent independent evolutionary events and thus are valid data for a statistical comparison, where independent samples are required. Although more than 4000 songbird species (‘songbird’ denotes the oscine passerines) have a capacity for vocal learning, this capability appears to be shared by the entire clade, suggesting that this ability evolved once, in the common ancestor of all songbirds, and therefore reflects a single evolutionary event. The input N in this case is one (and using N = 4000 would constitute massive data inflation). Fortunately in this case, vocal learning has evolved repeatedly in many clades including other birds (parrots, hummingbirds) and many mammals (humans, cetaceans, elephants, and some bats and pinnipeds), providing an appropriate sample for larger scale investigations of both mechanism and adaptive function [15]. A good example of this power is provided by investigations of the mechanistic underpinnings of complex vocal learning. Despite a long fascination with the idea www.sciencedirect.com
Editorial overview: Communication and language: Animal communication and human language Brainard and Fitch vii
that deficits in the vocal apparatus itself may underpin the inability of many species to produce complex sounds (e.g. the Aristotle quote above), considerable data suggest that this factor is less important than neural factors (cf. [16]). For example, x-ray investigations show that, when producing species-typical vocalizations, many mammals exhibit considerable dynamic flexibility in their vocal apparatus. Similarly, species with drastically different vocal production mechanisms can learn to produce the same complex vocalizations: Despite using a syrinx and lipless beak to produce sounds, many bird species can produce convincing imitations of human speech (reviewed in Elemans, in this issue, cf. [17,18]), and an Asian elephant learned to imitate Korean words by inserting its trunk in its mouth and moving it (cf. Stoeger and Manger). These and other data suggest that the significance of the vocal periphery has been overestimated. In contrast, comparative research provides a well-supported neural difference between those species that can and cannot learn novel vocalizations: the so-called Kuypers/Ju¨rgens or ‘direct connections’ hypothesis [19,20]. This hypothesis is based on the observation that in humans, but not in other primates, cortical neurons in primary motor regions synapse directly onto the motor neurons controlling the laryngeal musculature, whose cell bodies are located in the nucleus ambiguus of the medulla [20–23]. In nonhuman primates, in contrast, cortical neurons make only indirect, multi-synaptic connections to the brainstem motor neurons, via brainstem interneurons (cf. [24]). Because humans alone among primates have a well-developed capacity for vocal imitation, this suggests that direct cortico-ambigual connections are a prerequisite for complex vocal learning (cf. Simonyan, in this issue). While this hypothesis is certainly plausible, the human/primate comparison is based on a single evolutionary event that evidently occurred specifically in humans, and thus by itself provides an inadequate database to justify any strong conclusions. This is where the frequent convergent evolution of vocal learning in other clades provides a crucial source of additional data. If direct connections are indeed necessary for vocal learning, we would expect them to also be present in other clades capable of vocal learning and absent in those species incapable of vocal learning. While this mechanistic prediction is in principle testable via comparisons between any vocal learning species and some related non-vocal learner, clear data are currently only available from parrots and songbirds, where the prediction is clearly met: Direct connections appear to be present from telencephalic motor neurons directly onto syringeal motor neurons in vocal learning birds (cf. Elemans, in this issue), but not other species [25]. This example shows why a broad comparative approach is necessary, examining convergently evolved ‘analogies’ in addition to homologous traits is important in evaluating www.sciencedirect.com
hypotheses concerning species differences, and has led to a wide acceptance of the importance of direct connections in vocal control and vocal learning (e.g., [23,26–30]).
Answering Tinbergen’s four questions A second perspective that the current issue embodies is the importance of addressing a particular biological question at many levels of analysis, from the mechanistic to the evolutionary. The great ethologist Niko Tinbergen helpfully summarized four important levels at which any biological question about ‘why’ can be answered: mechanism, ontogeny, phylogeny, and function. Each of these classes of questions are important, and our understanding of any particular phenomenon will only be complete when we can answer all of them. For example, there are many valid answers to the question of why a blackbird sings. Mechanistic answers would concern the neural, hormonal, and cognitive basis of song, and ultimately the genetic underpinnings of the system. Ontogenetic answers would include the developmental history of that particular blackbird and the adults’ songs that he heard as a fledgling. Functional (or adaptive) answers would include the usefulness of learned song, and vocal learning more generally, in territory defense or female courtship in ancestral populations of blackbirds. Finally, phylogenetic answers might use the current distribution of traits like the syrinx (a production mechanism found in all birds, and no living non-birds) or vocal learning (which, as described above, is found in some but not all bird species) to derive inferences about how these traits evolved. In this issue, the authors address all of these issues. Most of the papers address mechanism in one way or another, but several also address function (e.g. Nowicki or Janik on the adaptive function of vocal learning) and phylogeny (e.g. Ryan on the phylogeny of the ‘chuck’ element in some frog calls, or Bass on the phylogenetic depth of basic vocal control circuitry). Ontogeny is also addressed, whether at the level of behavior (Tchernichovski and Marcus) or the development of neural circuits (Matsunaga and Okanoya, French and Fisher, Wohlgemuth et al.). Tinbergen never intended his four questions to be exhaustive, and a further level of explanation provides a fifth class of answer: historical changes observed in a learned system. In any system that is passed from one generation to the next via learning (e.g. a particular human language, or a local dialect of birdsong), we expect slight deviations from the original model to accumulate over time, leading to a level of ‘cultural’ change interspersed between the individual ontogenetic level and the population phylogenetic level. For human language, such change is sometimes termed ‘glossogeny’ [31,32]. Such cumulative change is seen in other systems as well, including humpbacked whale song [33–35] and birdsong [36], and constitutes an additional explanatory factor to consider in understanding any system of learned transmitted behaviors. The explosion of interest Current Opinion in Neurobiology 2014, 28:v–viii
viii Communication and language
in this factor is reviewed in the article by Kirby et al. (in this issue), who explore communicative systems acquired via ‘iterated learning’ from mathematical, computational, and experimental perspectives.
Conclusion In conclusion, in this series of short but authoritative reviews we have tried to provide an overview of current understanding of vertebrate communication, including human language, and focused on vocal communication. These reviews reveal an ever broader basis of shared traits that include both homologies (e.g. the many aspects of human behavior and communication that are shared with other primates, mammals or even among all vertebrates), along with an increasingly abundant set of convergentlyevolved or ‘analogous’ behaviors (e.g. the repeated evolution of vocal learning in independent clades). Although human language, seen as a whole, is unique to our species, many of the individual components underlying human language (whether genetic, developmental, neural, or behavioral) are shared with other animals. This both provides a rich source for detailed biological investigations, and allows us to sharpen and refine our understanding of those components that are not shared.
Conflict of interest statement Nothing declared.
Acknowledgements
12. Trut LN, Oskina I, Kharlamova A: Animal evolution during domestication: the domesticated fox as a model. Bioessays 2009, 31:349-360. 13. Wayne RK, vonHoldt BM: Evolutionary genomics of dog domestication. Mammalian Genome 2012, 23:3-18. 14. Wilkins AS, Wrangham RW, Fitch WT: The ‘domestication syndrome’ in mammals: A unified explanation based on neural crest cell behavior and genetics. Genetics 2014. (in press). 15. Fitch WT, Jarvis ED: Language, music, and the brain: a mysterious relationship. In Language, Music, and the Bra. Edited by Arbib MA. Cambridge, MA: MIT Press; 2013:499-539. 16. Fitch WT: The Evolution of Language. Cambridge: Cambridge University Press; 2010, . 17. Nottebohm F: Vocal tract and brain: A search for evolutionary bottlenecks. Ann New York Acad Sci 1976, 280:643-649. 18. Pepperberg IM: Functional vocalizations by an African grey parrot. Z Tierpsychol 1981, 55:139-160. 19. Ju¨rgens U, Kirzinger A, von Cramon DY: The effects of deepreaching lesions in the cortical face area on phonation: a combined case report and experimental monkey study. Cortex 1982, 18:125-139. 20. Kuypers HGJM: Corticobulbar connections to the pons and lower brainstem in man: an anatomical study. Brain 1958, 81:364-388. 21. Iwatsubo T, Kuzuhara S, Kanemitsu A, Shimada H, Toyokura Y: Corticofugal projections to the motor nuclei of the brainstem and spinal cord in humans. Neurology 1990, 40:309-312. 22. Kuypers HGJM: Some projections from the pericentral cortex to the pons and lower brain stem in monkey and chimpanzee. J Comp Neurol 1958, 110:221-255. 23. Myers RE: Comparative neurology of vocalization and speech: proof of a dichotomy. Ann N Y Acad Sci 1976, 280:745-757. 24. Ju¨rgens U: Neural pathways underlying vocal control. Neurosci Biobehav Rev 2002, 26:235-258.
WTF thanks ERC Advanced Grant SOMACCA (#230604) and FWF Grant ‘Cognition and Communication’ (W1234-G17) for financial support. MSB thanks NIH (R01 DC006636) and the Howard Hughes Medical Institute for financial support.
25. Wild JM: The avian nucleus retroambigualis: a nucleus for breathing, singing and calling. Brain Res 1993, 606:119-124.
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31. Hurford J: Nativist and functional explanations in language acquisition. In Logical Issues in Language Acquisition. Edited by Roca IM. Dordrecht: Foris Publications; 1990:85-136.
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32. Fitch WT: Glossogeny and phylogeny: Cultural evolution meets genetic evolution. Trends Genetics 2008, 24:373-374.
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10. Insel TR, Winslow JT, Wang ZX, Young L, Hulihan TJ: Oxytocin and the molecular basis of monogamy. Adv Exp Med Biol 1995, 395:227-234. 11. Albert FW, Carlborg O¨, Plyusnina I, Besnier F, Hedwig D, Lautenschla¨ger S et al.: Genetic architecture of tameness in a rat model of animal domestication. Genetics 2009, 182:541-554. Current Opinion in Neurobiology 2014, 28:v–viii
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34. Noad MJ, Cato DH, Bryden MM, Jenner MN, Jenner KCS: Cultural revolution in whale songs. Nature 2000, 408:537. 35. Payne RS, McVay S: Songs of humpback whales. Science 1971, 173:583-597. 36. Fehe´r O, Wang H, Saar S, Mitra PP, Tchernichovski O: De novo establishment of wild-type song culture in the zebra finch. Nature 2009, 459:564-568. www.sciencedirect.com
ScienceDirect Editorial overview: Communication and language: Animal communication and human language Michael S Brainard and W Tecumseh Fitch Current Opinion in Neurobiology 2014, 28:v–viii For a complete overview see the Issue Available online 2nd September 2014 http://dx.doi.org/10.1016/j.conb.2014.07.015 0959-4388/# 2014 Elsevier Ltd. All right reserved.
Michael S Brainard UCSF MC 0444, 675 Nelson Rising Lane, Room 514E, San Francisco, CA 94158, USA e-mail: [email protected] Michael S Brainard is Professor of Physiology and Psychiatry at UC San Francisco and an Investigator of the Howard Hughes Medical Institute. His research focuses on behavioral, neural, and genetic mechanisms of sensorymotor learning, using vocal learning in the songbird as a model.
W Tecumseh Fitch Faculty of Life Sciences, University of Vienna, 14 Althanstrasse, A-1090 Vienna, Austria W Tecumseh Fitch is a biologist and cognitive scientist at the University of Vienna, where he heads the Department of Cognitive Biology. His core interests are in the evolution of cognition and communication in vertebrates, including humans. He has worked both on the physics and physiology of sound production (bioacoustics) and, using a broad comparative method, on the perceptual and cognitive bases for complex pattern perception.
www.sciencedirect.com
Introduction Scholars have been comparing and contrasting human language and animal communication since ancient times. For example, around 350 BC Aristotle wondered why dolphins, though clearly intelligent, are unable to speak. He concluded that the dolphin’s ‘tongue is not loose, nor has it lips, so as to give utterance to an articulate sound (or a sound of vowel and consonant in combination)’ (Book IV, part 9 ‘Voice’ [1]). Since these early times, scholars have remained consistently interested in comparing language and animal calls, whether they emphasized the similarities or differences (e.g., [2–5]). But this interest has accelerated in the last few decades, leading to impressive gains in our scientific understanding of animal communication at many levels. These advances range from the basic physics of vocal production to the neural mechanisms controlling vocalizations and their perception, and even the genetic and developmental mechanisms underlying those neural mechanisms. Our goal as editors of this special issue was to provide a concise and up-to-date review of this scientific progress, emphasizing how comparisons among multiple species can help clarify commonalities, and sharpen key distinctions, that are relevant to human spoken language. The articles mainly focus on acoustic communication in animals and spoken language in humans. Although we are well aware that human language can be expressed via multiple modalities (e.g. writing or signed language), speech is the biological default modality for linguistic communication, and vocal communication provides many of the clearest examples illustrating the value of a broad comparative approach. For example we review in detail the capacity for complex vocal learning (the ability to reproduce sounds heard in the environment that are not part of an inborn species repertoire). The capacity for vocal learning is a fundamental prerequisite for our ability to acquire a large and flexible vocabulary shared among a speech community, and although highly developed in humans, appears to be absent or extremely limited in nonhuman primates. Nonetheless this capacity has evolved convergently in many other vertebrates including a number of mammalian clades along with songbirds (where it is best understood from a neuroscientific viewpoint). Research on songbirds has also provided important insights into the molecular, genetic, and developmental basis for the neural circuitry underlying vocal learning (Matsunaga and Okanoya; Tchernichovski and Marcus; Wohlgemuth et al.). Here we offer what is to our knowledge the first review under one cover of all known vocal-learning mammals including elephants (Stoeger and Manger), bats (Kno¨rnschild), pinnipeds (Reichmuth and Casey) and cetaceans (Janik), as well as an exploration of the possible adaptive benefits of vocal learning (Nowicki). Current Opinion in Neurobiology 2014, 28:v–viii
vi Communication and language
We also explore the area of animal pattern learning in multiple species, which has seen an explosion of recent interest. This topic is especially relevant in birds (reviewed in ten Cate as well as Gentner), where the neural basis of both production and perception of complex learned patterns can be explored in detail. Beyond these two general foci, we have taken a very broad comparative approach, including reviews of vocal communication in species that are not thought to exhibit imitative vocal learning, such as fish (Ladich, Fernald), frogs (Ryan and Guerra, Sweeney and Kelley) and mice (Portfors and Perkel). These examples enable exploration of the degree to which the neural basis for vocal control in all vertebrates, including fish and frogs, follows a shared ‘Bauplan’, upon which neural mechanisms for learning are elaborated (Bass). A similar question is asked concerning broad similarities in the neural underpinnings of social behavior and communication among vertebrates (Hoffman; Fernald). All of these reviews suggest that basic and important aspects of human social behavior and communication have very deep evolutionary roots indeed, and may have evolved in the early jawed fish that was the common ancestor of all terrestrial vertebrates and most living fish. We have not, of course, neglected our closest relatives, the primates. Comparisons of nonhuman primate vocal communication with spoken language from both neural (Rilling; Ghazanfar and Eliades) and behavioral (Seyfarth and Cheney, Zuberbuhler) perspectives illustrate a complex mix of similarities and differences. Such comparisons exemplify the need to separate vocal production (where the differences are quite evident) from vocal perception, and the interpretation of complex sequences of vocalization, where deep similarities with human abilities are clear. Regarding language, several of the reviews in this issue provide brief authoritative overviews of the current state of the art in neurolinguistics and the neural basis of human linguistic competence. Although many issues in this discipline remain controversial, it is now widely agreed that the ‘classical’ model of human language processing as confined to Broca’s and Wernicke’s areas in the left hemisphere is seriously incomplete, with many other brain regions in both hemispheres playing important roles (Poeppel, Hagoort). An important new development has used noninvasive brain-imaging techniques to investigate connectivity between different brain regions (e.g. diffusion tensor imaging and related approaches), which again reveals a complex mixture of similarities and differences in connectivity when comparing humans with other primates (Rilling; Simonyan; Catani). Although our understanding of the differences is clearest with regard to speech production (see below), it is also becoming clear that at least some aspects of more challenging components of human language, including syntax and semantics, can be tentatively linked to changes in brain structure (e.g. the Current Opinion in Neurobiology 2014, 28:v–viii
six-fold expansion of Broca’s area, and its greatly increased connection to posterior brain regions, in humans relative to chimpanzees, cf. Rilling).
The value of a broad comparative approach A key area of agreement among most of the authors in this special issue is the central value of a broad comparative approach, which seeks appropriate species for approaching a particular problem that go beyond the typical list of ‘worm, fly, mouse, monkey, . . .’ or so-called ‘model’ organisms. The essential idea here has been dubbed the ‘August Krogh Principle’ [6,7]: that for many biological problems there is some organism particularly suitable for its study. While originally introduced in the context of physiology, it is equally true for neuroscience or ethology. Often, comparisons of a pair of related species that contrast on some particular trait can be most revealing. For example, the contrast between vocal-learning and non-learning birds has helped to reveal the neural bases of vocal learning. This can be true in investigating phylogenetic and evolutionary issues as well: As reviewed in Ryan (in this issue) the comparison of related frogs that either do or do not possess a low-frequency ‘chuck’ element in their calls helped to reveal both the mechanistic basis of that component and the evolutionary forces that drove the evolution of this trait (in this case sexual selection: the mating preferences of female frogs). Other well-known illustrations of this point include comparisons between monogamous and polygynous rodent species [8–10] or comparisons of domesticated and wild-type members of the same species [11–14]. Such paired comparisons, based on a specific contrast of interest, provide a rich source of knowledge. But any comparison of just two species (or two clades representing a single evolutionary event) suffers from a statistical power issue, and it is here that the virtues of a broad comparative approach become most evident. Convergently evolved traits, by definition, represent independent evolutionary events and thus are valid data for a statistical comparison, where independent samples are required. Although more than 4000 songbird species (‘songbird’ denotes the oscine passerines) have a capacity for vocal learning, this capability appears to be shared by the entire clade, suggesting that this ability evolved once, in the common ancestor of all songbirds, and therefore reflects a single evolutionary event. The input N in this case is one (and using N = 4000 would constitute massive data inflation). Fortunately in this case, vocal learning has evolved repeatedly in many clades including other birds (parrots, hummingbirds) and many mammals (humans, cetaceans, elephants, and some bats and pinnipeds), providing an appropriate sample for larger scale investigations of both mechanism and adaptive function [15]. A good example of this power is provided by investigations of the mechanistic underpinnings of complex vocal learning. Despite a long fascination with the idea www.sciencedirect.com
Editorial overview: Communication and language: Animal communication and human language Brainard and Fitch vii
that deficits in the vocal apparatus itself may underpin the inability of many species to produce complex sounds (e.g. the Aristotle quote above), considerable data suggest that this factor is less important than neural factors (cf. [16]). For example, x-ray investigations show that, when producing species-typical vocalizations, many mammals exhibit considerable dynamic flexibility in their vocal apparatus. Similarly, species with drastically different vocal production mechanisms can learn to produce the same complex vocalizations: Despite using a syrinx and lipless beak to produce sounds, many bird species can produce convincing imitations of human speech (reviewed in Elemans, in this issue, cf. [17,18]), and an Asian elephant learned to imitate Korean words by inserting its trunk in its mouth and moving it (cf. Stoeger and Manger). These and other data suggest that the significance of the vocal periphery has been overestimated. In contrast, comparative research provides a well-supported neural difference between those species that can and cannot learn novel vocalizations: the so-called Kuypers/Ju¨rgens or ‘direct connections’ hypothesis [19,20]. This hypothesis is based on the observation that in humans, but not in other primates, cortical neurons in primary motor regions synapse directly onto the motor neurons controlling the laryngeal musculature, whose cell bodies are located in the nucleus ambiguus of the medulla [20–23]. In nonhuman primates, in contrast, cortical neurons make only indirect, multi-synaptic connections to the brainstem motor neurons, via brainstem interneurons (cf. [24]). Because humans alone among primates have a well-developed capacity for vocal imitation, this suggests that direct cortico-ambigual connections are a prerequisite for complex vocal learning (cf. Simonyan, in this issue). While this hypothesis is certainly plausible, the human/primate comparison is based on a single evolutionary event that evidently occurred specifically in humans, and thus by itself provides an inadequate database to justify any strong conclusions. This is where the frequent convergent evolution of vocal learning in other clades provides a crucial source of additional data. If direct connections are indeed necessary for vocal learning, we would expect them to also be present in other clades capable of vocal learning and absent in those species incapable of vocal learning. While this mechanistic prediction is in principle testable via comparisons between any vocal learning species and some related non-vocal learner, clear data are currently only available from parrots and songbirds, where the prediction is clearly met: Direct connections appear to be present from telencephalic motor neurons directly onto syringeal motor neurons in vocal learning birds (cf. Elemans, in this issue), but not other species [25]. This example shows why a broad comparative approach is necessary, examining convergently evolved ‘analogies’ in addition to homologous traits is important in evaluating www.sciencedirect.com
hypotheses concerning species differences, and has led to a wide acceptance of the importance of direct connections in vocal control and vocal learning (e.g., [23,26–30]).
Answering Tinbergen’s four questions A second perspective that the current issue embodies is the importance of addressing a particular biological question at many levels of analysis, from the mechanistic to the evolutionary. The great ethologist Niko Tinbergen helpfully summarized four important levels at which any biological question about ‘why’ can be answered: mechanism, ontogeny, phylogeny, and function. Each of these classes of questions are important, and our understanding of any particular phenomenon will only be complete when we can answer all of them. For example, there are many valid answers to the question of why a blackbird sings. Mechanistic answers would concern the neural, hormonal, and cognitive basis of song, and ultimately the genetic underpinnings of the system. Ontogenetic answers would include the developmental history of that particular blackbird and the adults’ songs that he heard as a fledgling. Functional (or adaptive) answers would include the usefulness of learned song, and vocal learning more generally, in territory defense or female courtship in ancestral populations of blackbirds. Finally, phylogenetic answers might use the current distribution of traits like the syrinx (a production mechanism found in all birds, and no living non-birds) or vocal learning (which, as described above, is found in some but not all bird species) to derive inferences about how these traits evolved. In this issue, the authors address all of these issues. Most of the papers address mechanism in one way or another, but several also address function (e.g. Nowicki or Janik on the adaptive function of vocal learning) and phylogeny (e.g. Ryan on the phylogeny of the ‘chuck’ element in some frog calls, or Bass on the phylogenetic depth of basic vocal control circuitry). Ontogeny is also addressed, whether at the level of behavior (Tchernichovski and Marcus) or the development of neural circuits (Matsunaga and Okanoya, French and Fisher, Wohlgemuth et al.). Tinbergen never intended his four questions to be exhaustive, and a further level of explanation provides a fifth class of answer: historical changes observed in a learned system. In any system that is passed from one generation to the next via learning (e.g. a particular human language, or a local dialect of birdsong), we expect slight deviations from the original model to accumulate over time, leading to a level of ‘cultural’ change interspersed between the individual ontogenetic level and the population phylogenetic level. For human language, such change is sometimes termed ‘glossogeny’ [31,32]. Such cumulative change is seen in other systems as well, including humpbacked whale song [33–35] and birdsong [36], and constitutes an additional explanatory factor to consider in understanding any system of learned transmitted behaviors. The explosion of interest Current Opinion in Neurobiology 2014, 28:v–viii
viii Communication and language
in this factor is reviewed in the article by Kirby et al. (in this issue), who explore communicative systems acquired via ‘iterated learning’ from mathematical, computational, and experimental perspectives.
Conclusion In conclusion, in this series of short but authoritative reviews we have tried to provide an overview of current understanding of vertebrate communication, including human language, and focused on vocal communication. These reviews reveal an ever broader basis of shared traits that include both homologies (e.g. the many aspects of human behavior and communication that are shared with other primates, mammals or even among all vertebrates), along with an increasingly abundant set of convergentlyevolved or ‘analogous’ behaviors (e.g. the repeated evolution of vocal learning in independent clades). Although human language, seen as a whole, is unique to our species, many of the individual components underlying human language (whether genetic, developmental, neural, or behavioral) are shared with other animals. This both provides a rich source for detailed biological investigations, and allows us to sharpen and refine our understanding of those components that are not shared.
Conflict of interest statement Nothing declared.
Acknowledgements
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WTF thanks ERC Advanced Grant SOMACCA (#230604) and FWF Grant ‘Cognition and Communication’ (W1234-G17) for financial support. MSB thanks NIH (R01 DC006636) and the Howard Hughes Medical Institute for financial support.
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