Crowd vocal learning induces vocal dialects in bats: Playback of conspecifics shapes fundamental frequency usage by pups

Generative vocal plasticity in chimpanzees

Modern theory posits that human-ape differences in voice command account for speech evolution. However, comparison has been indirect and conjectural based on vocal learning taxa far related from Hominids, instead of direct and quantitative based on great ape calls that, like all speech sounds, are local-specific and non-universal to the species. Moreover, the null hypothesis that the great ape voice command is purely reflexive has never been directly tested. Here, we show that in controlled, constant experimental settings, captive chimpanzees exhibit high-dimensional dexterity over voice activation and modulation in two atypical vowel-like calls. Subjects made unrestricted, multidimensional, and distinct voice changes within and between individuals, inducing parameter changes up to 10,000%, rejecting null hypothesis' predictions. Forecasting models indicated unmitigated voice novelty, altogether demonstrating emancipated and vast real-time voice control. Findings show that, contrary to traditional assumptions, speech and song evolution likely hinged on prolific voice command already available in ancestral ape-like ancestors.

Role of auditory feedback for vocal production learning in the Egyptian fruit bat

Some species have evolved the ability to use the sense of hearing to modify existing vocalizations, or even create new ones, which enlarges their repertoires and results in complex communication systems.1 This ability corresponds to various forms of vocal production learning that are all possessed by humans and independently displayed by distantly related vertebrates.1,2,3,4,5,6,7 Among mammals, a few species, including the Egyptian fruit bat,8,9,10 would possess such vocal production learning abilities.7 Yet the necessity of an intact auditory system for the development of the Egyptian fruit bat typical vocal repertoire has not been tested. Furthermore, a systematic causal examination of learned and innate aspects of the entire repertoire has never been performed in any vocal learner. Here we addressed these gaps by eliminating pups' sense of hearing at birth and assessing its effects on vocal production in adulthood. The deafening treatment enabled us to both causally test these bats' vocal learning ability and discern learned from innate aspects of their vocalizations. Leveraging wireless individual audio recordings from freely interacting adults, we show that a subset of the Egyptian fruit bat vocal repertoire necessitates auditory feedback. Intriguingly, these affected vocalizations belong to different acoustic groups in the vocal repertoire of males and females. These findings open the possibilities for targeted studies of the mammalian neural circuits that enable sexually dimorphic forms of vocal learning.

Endogenous Bornavirus-like Elements in Bats: Evolutionary Insights from the Conserved Riboviral L-Gene in Microbats and Its Antisense Transcription in Myotis daubentonii

Bats are ecologically diverse vertebrates characterized by their ability to host a wide range of viruses without apparent illness and the presence of numerous endogenous viral elements (EVEs). EVEs are well preserved, expressed, and may affect host biology and immunity, but their role in bat immune system evolution remains unclear. Among EVEs, endogenous bornavirus-like elements (EBLs) are bornavirus sequences integrated into animal genomes. Here, we identified a novel EBL in the microbat Myotis daubentonii, EBLL-Cultervirus.10-MyoDau (short name is CV.10-MyoDau) that shows protein-level conservation with the L-protein of a Cultervirus (Wuhan sharpbelly bornavirus). Surprisingly, we discovered a transcript on the antisense strand comprising three exons, which we named AMCR-MyoDau. The active transcription in Myotis daubentonii tissues of AMCR-MyoDau, confirmed by RNA-Seq analysis and RT-PCR, highlights its potential role during viral infections. Using comparative genomics comprising 63 bat genomes, we demonstrate nucleotide-level conservation of CV.10-MyoDau and AMCR-MyoDau across various bat species and its detection in 22 Yangochiropera and 12 Yinpterochiroptera species. To the best of our knowledge, this marks the first occurrence of a conserved EVE shared among diverse bat species, which is accompanied by a conserved antisense transcript. This highlights the need for future research to explore the role of EVEs in shaping the evolution of bat immunity.

Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements

Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

AI and the Doctor Dolittle challenge

Talking to animals is a fundamental human desire. The emergence of powerful AI algorithms, and specifically Large Language Models, has driven many to suggest that we are on the verge of fulfilling this wish. A few large scientific consortia have been formed around this topic and several commercial entities even offer such services. We frame the task of communicating with animals as 'The Doctor Dolittle challenge' and identify three main obstacles on the route to doing so. First, although generative AI models can create novel animal communication samples, it is very difficult to determine their context, and we will forever be biased by our human umwelt when doing so. Second, using AI to extract context in an unsupervised manner must be validated through controlled experiments aiming to measure the animals' response. This is difficult, and moreover, AI algorithms tend to cling on to any available information and are thus prone to finding spurious correlations. And third, animal communication focuses on a restricted set of contexts, such as alarm and courtship, highly limiting our ability to communicate regarding other contexts. Nevertheless, using the tremendous power of novel AI methods to decipher and mimic animal communication is both fascinating and important. We thus define the criteria for passing the Doctor Dolittle challenge and call upon scientists to take on the mission.

Bats possess the anatomical substrate for a laryngeal motor cortex

Cortical neurons that make direct connections to motor neurons in the brainstem and spinal cord are specialized for fine motor control and learning [1, 2]. Imitative vocal learning, the basis for human speech, requires the precise control of the larynx muscles [3]. While much knowledge on vocal learning systems has been gained from studying songbirds [4], an accessible laboratory model for mammalian vocal learning is highly desirable. Evidence indicative of complex vocal repertoires and dialects suggests that bats are vocal learners [5, 6], however the circuitry that underlies vocal control and learning in bats is largely unknown. A key feature of vocal learning animals is a direct cortical projection to the brainstem motor neurons that innervate the vocal organ [7]. A recent study [8] described a direct connection from the primary motor cortex to medullary nucleus ambiguus in the Egyptian fruit bat (Rousettus aegyptiacus). Here we show that a distantly related bat, Seba's short-tailed bat (Carollia perspicillata) also possesses a direct projection from the primary motor cortex to nucleus ambiguus. Our results, in combination with Wirthlin et al. [8], suggest that multiple bat lineages possess the anatomical substrate for cortical control of vocal output. We propose that bats would be an informative mammalian model for vocal learning studies to better understand the genetics and circuitry involved in human vocal communication.

Mutual mother-pup acoustic identification in Asian particolored bats

In many vertebrates, vocal communication is crucial in parent-offspring interactions, and parents are often able to discriminate between the calls of their own and others' offspring. There are many reports on the unidirectional recognition of isolation calls of pups by maternal bats, but few studies on the ability of bat pups to recognize maternal acoustic signals. In this study, we investigated whether the echolocation pulses of female Asian particolored bats (Vespertilio sinensis) and isolation calls of pups differ statistically among individuals. We used two-choice playback experiments to test whether the mothers and pups of V. sinensis can recognize each other by acoustic signals. Both the echolocation pulses of mother bats and the isolation calls of pups contained sufficient individual characteristics. Playback experiments showed that mothers were able to recognize isolation calls of pups, and most pups greater than 12 days old were able to distinguish echolocation pulses of their own mother from those of other mothers. This is the first use of two-choice acoustic signal playback experiments to confirm that pups can recognize their mothers by echolocation calls. The results provide behavioral evidence for bidirectional recognition of acoustic signals between mothers and infants in frequency-modulated type bats.

Geographic Variation in Social Vocalizations of the Great Himalayan Leaf-Nosed Bat, Hipposideros armiger: Acoustic Overflow Across Population Boundaries

Bat populations employ rich vocal repertoires for social communication in addition to emitting sound pulses for echolocation. Acoustic parameters of echolocation pulses can vary with the context in which they are emitted, and also with the individual and across populations as a whole. The acoustic parameters of social vocalizations, or “calls”, also vary with the individual and context, but not much is known about their variation across populations at different geographic locations. Here, we leveraged the detailed acoustic classification of social vocalizations available for the Great Himalayan leaf-nosed bat, Hipposideros armiger, to examine geographic variation in five commonly emitted simple syllable types. We hypothesized that individuals within geographically dispersed populations communicate using spectrographically similar constructs or “syllable types”. We also examined whether call syllables vary discordantly with the correlation pattern observed for echolocation pulses across those same geographic regions. Furthermore, we postulated that the acoustic boundaries of a syllable type are not uniquely constrained to its variation within a particular population of the same subspecies. To test our hypotheses, we obtained recordings of social calls of H. a. armiger from nine locations within the oriental region. These locations were consolidated into five geographic regions based on previously established region-specific differences in the peak frequency of echolocation pulses. A multivariate cluster analysis established that unlike echolocation pulses, syllable types exhibit a relatively large variance. Analysis of this variance showed significant differences in Least Squares Means estimates, establishing significant population-level differences in the multiparametric means of individual syllable types across geographic regions. Multivariate discriminant analysis confirmed the presence of region-specific centroids for different syllable constructs, but also showed a large overlap of their multiparametric boundaries across geographic regions. We propose that despite differences in the population-specific core construct of a syllable type, bats maximize acoustic variation across individuals within a population irrespective of its overflow and overlap with other populations.

Genomewide Analysis and Biological Characterization of Cathelicidins with Potent Antimicrobial Activity and Low Cytotoxicity from Three Bat Species

Cathelicidins are potent antimicrobial peptides with broad spectrum antimicrobial activity in many vertebrates and an important component of the innate immune system. However, our understanding of the genetic variations and biological characteristics of bat cathelicidins is limited. In this study, we performed genome-level analysis of the antimicrobial peptide cathelicidins from seven bat species in the six families, listed 19 cathelicidin-like sequences, and showed that the number of functional cathelicidin genes differed among bat species. Based on the identified biochemical characteristics of bat cathelicidins, three cathelicidins, HA-CATH (from Hipposideros armiger), ML-CATH (from Myotis lucifugus), and PD-CATH (from Phyllostomus discolor), with clear antimicrobial signatures were chemically synthesized and evaluated antimicrobial activity. HA-CATH showed narrow-spectrum antibacterial activity against a panel of 12 reference bacteria, comprising 6 Gram-negative and 6 Gram-positive strains. However, ML-CATH and PD-CATH showed potent antibacterial activity against a broad spectrum of Gram-negative and Gram-positive bacteria with minimum inhibitory concentration (MIC) of 1 and 3 μg/mL, respectively, against Staphylococcus aureus. ML-CATH and PD-CATH also showed antifungal activities against Candida albicans and Cryptococcus cuniculi with MIC of 5 to 40 μg/mL, respectively, and 80% inhibition of the metabolism of Mucor hiemalis hyphae at 80 μg/mL, while displaying minimal cytotoxicity to HaCaT cells. Taken together, although the spectrum and efficacy of bat cathelicidins were species-dependent, the antimicrobial activity of ML-CATH and PD-CATH was comparable to that of other highly active cathelicidins in vertebrates while having negligible cytotoxicity to mammalian cells. ML-CATH and PD-CATH can be exploited as promising candidates for the development of antimicrobial therapeutics.

Unravelling the Stability of Nightingale Song Over Time and Space Using Open, Citizen Science and Shared Data

Open science approaches enable and facilitate the investigation of many scientific questions in bioacoustics, such as studies on the temporal and spatial evolution of song, as in vocal dialects. In contrast to previous dialect studies, which mostly focused on songbird species with a small repertoire, here we studied the common nightingale (Luscinia megarhynchos), a bird species with a complex and large repertoire. To study dialects on the population level in this species, we used recordings from four datasets: an open museum archive, a citizen science platform, a citizen science project, and shared recordings from academic researchers. We conducted to the date largest temporal and geographic dialect study of birdsong including recordings from 1930 to 2019 and from 13 European countries, with a geographical coverage of 2,652 km of linear distance. To examine temporal stability and spatial dialects, a catalog of 1,868 song types of common nightingales was created. Instead of dialects, we found a high degree of stability over time and space in both, the sub-categories of song and in the occurrence of song types. For example, the second most common song type in our datasets occurred over nine decades and across Europe. In our case study, open and citizen science data proved to be equivalent, and in some cases even better, than data shared by an academic research group. Based on our results, we conclude that the combination of diverse and open datasets was particularly useful to study the evolution of song in a bird species with a large repertoire.

Identification, Analysis and Characterization of Base Units of Bird Vocal Communication: The White Spectacled Bulbul (Pycnonotus xanthopygos) as a Case Study

Animal vocal communication is a broad and multi-disciplinary field of research. Studying various aspects of communication can provide key elements for understanding animal behavior, evolution, and cognition. Given the large amount of acoustic data accumulated from automated recorders, for which manual annotation and analysis is impractical, there is a growing need to develop algorithms and automatic methods for analyzing and identifying animal sounds. In this study we developed an automatic detection and analysis system based on audio signal processing algorithms and deep learning that is capable of processing and analyzing large volumes of data without human bias. We selected the White Spectacled Bulbul (Pycnonotus xanthopygos) as our bird model because it has a complex vocal communication system with a large repertoire which is used by both sexes, year-round. It is a common, widespread passerine in Israel, which is relatively easy to locate and record in a broad range of habitats. Like many passerines, the Bulbul’s vocal communication consists of two primary hierarchies of utterances, syllables and words. To extract each of these units’ characteristics, the fundamental frequency contour was modeled using a low degree Legendre polynomial, enabling it to capture the different patterns of variation from different vocalizations, so that each pattern could be effectively expressed using very few coefficients. In addition, a mel-spectrogram was computed for each unit, and several features were extracted both in the time-domain (e.g., zero-crossing rate and energy) and frequency-domain (e.g., spectral centroid and spectral flatness). We applied both linear and non-linear dimensionality reduction algorithms on feature vectors and validated the findings that were obtained manually, namely by listening and examining the spectrograms visually. Using these algorithms, we show that the Bulbul has a complex vocabulary of more than 30 words, that there are multiple syllables that are combined in different words, and that a particular syllable can appear in several words. Using our system, researchers will be able to analyze hundreds of hours of audio recordings, to obtain objective evaluation of repertoires, and to identify different vocal units and distinguish between them, thus gaining a broad perspective on bird vocal communication.

A unifying mechanism governing inter-brain neural relationship during social interactions

A key goal of social neuroscience is to understand the inter-brain neural relationship-the relationship between the neural activity of socially interacting individuals. Decades of research investigating this relationship have focused on the similarity in neural activity across brains. Here, we instead asked how neural activity differs between brains, and how that difference evolves alongside activity patterns shared between brains. Applying this framework to bats engaged in spontaneous social interactions revealed two complementary phenomena characterizing the inter-brain neural relationship: fast fluctuations of activity difference across brains unfolding in parallel with slow activity covariation across brains. A model reproduced these observations and generated multiple predictions that we confirmed using experimental data involving pairs of bats and a larger social group of bats. The model suggests that a simple computational mechanism involving positive and negative feedback could explain diverse experimental observations regarding the inter-brain neural relationship.

Hearing, echolocation, and beam steering from day 0 in tongue-clicking bats

Little is known about the ontogeny of lingual echolocation. We examined the echolocation development of Rousettus aegyptiacus, the Egyptian fruit bat, which uses rapid tongue movements to produce hyper-short clicks and steer the beam's direction. We recorded from day 0 to day 35 postbirth and assessed hearing and beam-steering abilities. On day 0, R. aegyptiacus pups emit isolation calls and hyper-short clicks in response to acoustic stimuli, demonstrating hearing. Auditory brainstem response recordings show that pups are sensitive to pure tones of the main hearing range of adult Rousettus and to brief clicks. Newborn pups produced clicks in the adult paired pattern and were able to use their tongues to steer the sonar beam. As they aged, pups produced click pairs faster, converging with adult intervals by age of first flights (7-8 weeks). In contrast with laryngeal bats, Rousettus echolocation frequency and duration are stable through to day 35, but shift by the time pups begin to fly, possibly owing to tongue-diet maturation effects. Furthermore, frequency and duration shift in the opposite direction of mammalian laryngeal vocalizations. Rousettus lingual echolocation thus appears to be a highly functional sensory system from birth and follows a different ontogeny from that of laryngeal bats.

Vocal production learning in mammals revisited

Vocal production learning, the ability to modify the structure of vocalizations as a result of hearing those of others, has been studied extensively in birds but less attention has been given to its occurrence in mammals. We summarize the available evidence for vocal learning in mammals from the last 25 years, updating earlier reviews on the subject. The clearest evidence comes from cetaceans, pinnipeds, elephants and bats where species have been found to copy artificial or human language sounds, or match acoustic models of different sound types. Vocal convergence, in which parameter adjustments within one sound type result in similarities between individuals, occurs in a wider range of mammalian orders with additional evidence from primates, mole-rats, goats and mice. Currently, the underlying mechanisms for convergence are unclear with vocal production learning but also usage learning or matching physiological states being possible explanations. For experimental studies, we highlight the importance of quantitative comparisons of seemingly learned sounds with vocal repertoires before learning started or with species repertoires to confirm novelty. Further studies on the mammalian orders presented here as well as others are needed to explore learning skills and limitations in greater detail. This article is part of the theme issue 'Vocal learning in animals and humans'.

A researcher's guide to the comparative assessment of vocal production learning

Vocal production learning (VPL) is the capacity to learn to produce new vocalizations, which is a rare ability in the animal kingdom and thus far has only been identified in a handful of mammalian taxa and three groups of birds. Over the last few decades, approaches to the demonstration of VPL have varied among taxa, sound production systems and functions. These discrepancies strongly impede direct comparisons between studies. In the light of the growing number of experimental studies reporting VPL, the need for comparability is becoming more and more pressing. The comparative evaluation of VPL across studies would be facilitated by unified and generalized reporting standards, which would allow a better positioning of species on any proposed VPL continuum. In this paper, we specifically highlight five factors influencing the comparability of VPL assessments: (i) comparison to an acoustic baseline, (ii) comprehensive reporting of acoustic parameters, (iii) extended reporting of training conditions and durations, (iv) investigating VPL function via behavioural, perception-based experiments and (v) validation of findings on a neuronal level. These guidelines emphasize the importance of comparability between studies in order to unify the field of vocal learning. This article is part of the theme issue 'Vocal learning in animals and humans'.

Fruit bats adjust their foraging strategies to urban environments to diversify their diet

Background

Urbanization is one of the most influential processes on our globe, putting a great number of species under threat. Some species learn to cope with urbanization, and a few even benefit from it, but we are only starting to understand how they do so. In this study, we GPS tracked Egyptian fruit bats from urban and rural populations to compare their movement and foraging in urban and rural environments. Because fruit trees are distributed differently in these two environments, with a higher diversity in urban environments, we hypothesized that foraging strategies will differ too.

Results

When foraging in urban environments, bats were much more exploratory than when foraging in rural environments, visiting more sites per hour and switching foraging sites more often on consecutive nights. By doing so, bats foraging in settlements diversified their diet in comparison to rural bats, as was also evident from their choice to often switch fruit species. Interestingly, the location of the roost did not dictate the foraging grounds, and we found that many bats choose to roost in the countryside but nightly commute to and forage in urban environments.

Conclusions

Bats are unique among small mammals in their ability to move far rapidly. Our study is an excellent example of how animals adjust to environmental changes, and it shows how such mobile mammals might exploit the new urban fragmented environment that is taking over our landscape.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01060-x.

The Cognitive Philosophy of Communication

Numerous species use different forms of communication in order to successfully interact in their respective environment. This article seeks to elucidate limitations of the classical conduit metaphor by investigating communication from the perspectives of biology and artificial neural networks. First, communication is a biological natural phenomenon, found to be fruitfully grounded in an organism’s embodied structures and memory system, where specific abilities are tied to procedural, semantic, and episodic long-term memory as well as to working memory. Second, the account explicates differences between non-verbal and verbal communication and shows how artificial neural networks can communicate by means of ontologically non-committal modelling. This approach enables new perspectives of communication to emerge regarding both sender and receiver. It is further shown that communication features gradient properties that are plausibly divided into a reflexive and a reflective form, parallel to knowledge and reflection.

Do Bats Have the Necessary Prerequisites for Symbolic Communication?

Training animals such as apes, gray parrots, or dolphins that communicate via arbitrary symbols with humans has revealed astonishing mental capacities that may have otherwise gone unnoticed. Albeit bats have not yet been trained to communicate via symbols with humans, we are convinced that some species, especially captive Pteropodid bats ("flying foxes"), show the potential to master this cognitive task. Here, we briefly review what is known about bats' cognitive skills that constitute relevant prerequisites for symbolic communication with humans. We focus on social learning in general, trainability by humans, associative learning from humans, imitation, vocal production learning and usage learning, and social knowledge. Moreover, we highlight potential training paradigms that could be used to elicit simple "symbolic" bat-human communication, i.e., training bats to select arbitrary symbols on a touchscreen to elicit a desired behavior of the human caregiver. Touchscreen-proficient bats could participate in cognition research, e.g., to study their numerical competence or categorical perception, to further elucidate how nonhuman animals learn and perceive the world.

A Hierarchy of Autonomous Systems for Vocal Production

Vocal production is hierarchical in the time domain. These hierarchies build upon biomechanical and neural dynamics across various timescales. We review studies in marmoset monkeys, songbirds, and other vertebrates. To organize these data in an accessible and across-species framework, we interpret the different timescales of vocal production as belonging to different levels of an autonomous systems hierarchy. The first level accounts for vocal acoustics produced on short timescales; subsequent levels account for longer timescales of vocal output. The hierarchy of autonomous systems that we put forth accounts for vocal patterning, sequence generation, dyadic interactions, and context dependence by sequentially incorporating central pattern generators, intrinsic drives, and sensory signals from the environment. We then show the framework's utility by providing an integrative explanation of infant vocal production learning in which social feedback modulates infant vocal acoustics through the tuning of a drive signal.

The neurobiology of innate, volitional and learned vocalizations in mammals and birds

Vocalization is an ancient vertebrate trait essential to many forms of communication, ranging from courtship calls to free verse. Vocalizations may be entirely innate and evoked by sexual cues or emotional state, as with many types of calls made in primates, rodents and birds; volitional, as with innate calls that, following extensive training, can be evoked by arbitrary sensory cues in non-human primates and corvid songbirds; or learned, acoustically flexible and complex, as with human speech and the courtship songs of oscine songbirds. This review compares and contrasts the neural mechanisms underlying innate, volitional and learned vocalizations, with an emphasis on functional studies in primates, rodents and songbirds. This comparison reveals both highly conserved and convergent mechanisms of vocal production in these different groups, despite their often vast phylogenetic separation. This similarity of central mechanisms for different forms of vocal production presents experimentalists with useful avenues for gaining detailed mechanistic insight into how vocalizations are employed for social and sexual signalling, and how they can be modified through experience to yield new vocal repertoires customized to the individual's social group. This article is part of the theme issue 'What can animal communication teach us about human language?'

Comparing context-dependent call sequences employing machine learning methods: an indication of syntactic structure of greater horseshoe bats

For analysis of vocal syntax, accurate classification of call sequence structures in different behavioural contexts is essential. However, an effective, intelligent program for classifying call sequences from numerous recorded sound files is still lacking. Here, we employed three machine learning algorithms (logistic regression, support vector machine and decision trees) to classify call sequences of social vocalizations of greater horseshoe bats (Rhinolophus ferrumequinum) in aggressive and distress contexts. The three machine learning algorithms obtained highly accurate classification rates (logistic regression 98%, support vector machine 97% and decision trees 96%). The algorithms also extracted three of the most important features for the classification: the transition between two adjacent syllables, the probability of occurrences of syllables in each position of a sequence, and the characteristics of a sequence. The results of statistical analysis also supported the classification of the algorithms. The study provides the first efficient method for data mining of call sequences and the possibility of linguistic parameters in animal communication. It suggests the presence of song-like syntax in the social vocalizations emitted within a non-breeding context in a bat species.

Behaviour, biology and evolution of vocal learning in bats

The comparative approach can provide insight into the evolution of human speech, language and social communication by studying relevant traits in animal systems. Bats are emerging as a model system with great potential to shed light on these processes given their learned vocalizations, close social interactions, and mammalian brains and physiology. A recent framework outlined the multiple levels of investigation needed to understand vocal learning across a broad range of non-human species, including cetaceans, pinnipeds, elephants, birds and bats. Here, we apply this framework to the current state-of-the-art in bat research. This encompasses our understanding of the abilities bats have displayed for vocal learning, what is known about the timing and social structure needed for such learning, and current knowledge about the prevalence of the trait across the order. It also addresses the biology (vocal tract morphology, neurobiology and genetics) and evolution of this trait. We conclude by highlighting some key questions that should be answered to advance our understanding of the biological encoding and evolution of speech and spoken communication. This article is part of the theme issue 'What can animal communication teach us about human language?'

A taxonomy for vocal learning

Humans and songbirds learn to sing or speak by listening to acoustic models, forming auditory templates, and then learning to produce vocalizations that match the templates. These taxa have evolved specialized telencephalic pathways to accomplish this complex form of vocal learning, which has been reported for very few other taxa. By contrast, the acoustic structure of most animal vocalizations is produced by species-specific vocal motor programmes in the brainstem that do not require auditory feedback. However, many mammals and birds can learn to fine-tune the acoustic features of inherited vocal motor patterns based upon listening to conspecifics or noise. These limited forms of vocal learning range from rapid alteration based on real-time auditory feedback to long-term changes of vocal repertoire and they may involve different mechanisms than complex vocal learning. Limited vocal learning can involve the brainstem, mid-brain and/or telencephalic networks. Understanding complex vocal learning, which underpins human speech, requires careful analysis of which species are capable of which forms of vocal learning. Selecting multiple animal models for comparing the neural pathways that generate these different forms of learning will provide a richer view of the evolution of complex vocal learning and the neural mechanisms that make it possible.

This article is part of the theme issue ‘What can animal communication teach us about human language?’

Are dialects socially learned in marmoset monkeys? Evidence from translocation experiments

The acoustic properties of vocalizations in common marmosets differ between populations. These differences may be the result of social vocal learning, but they can also result from environmental or genetic differences between populations. We performed translocation experiments to separately quantify the influence of a change in the physical environment (experiment 1), and a change in the social environment (experiment 2) on the acoustic properties of calls from individual captive common marmosets. If population differences were due to genetic differences, we expected no change in the vocalizations of the translocated marmosets. If differences were due to environmental factors, we expected vocalizations to permanently change contingent with environmental changes. If social learning was involved, we expected that the vocalizations of animals translocated to a new population with a different dialect would become more similar to the new population. In experiment 1, we translocated marmosets to a different physical environment without changing the social composition of the groups or their neighbours. Immediately after the translocation to the new facility, one out of three call types showed a significant change in call structure, but 5-6 weeks later, the calls were no longer different from before the translocation. Thus, the novel physical environment did not induce long lasting changes in the vocalizations of the marmosets. In experiment 2, we translocated marmosets to a new population with a different dialect. Importantly, our previous work had shown that these two populations differed significantly in vocalization structure. The translocated marmosets were still housed in their original social group, but after translocation they were surrounded by the vocalizations from neighbouring groups of the new population. The vocal distance between the translocated individuals and the new population decreased for two out of three call types over 16 weeks. Thus, even without direct social contact or interaction, the vocalizations of the translocated animals converged towards the new population, indicating that common marmosets can modify their calls due to acoustic input from conspecifics alone, via crowd vocal learning. To our knowledge, this is the first study able to distinguish between different explanations for vocal dialects as well as to show crowd vocal learning in a primate species.

A Modular Approach to Vocal Learning: Disentangling the Diversity of a Complex Behavioral Trait

Vocal learning is a behavioral trait in which the social and acoustic environment shapes the vocal repertoire of individuals. Over the past century, the study of vocal learning has progressed at the intersection of ecology, physiology, neuroscience, molecular biology, genomics, and evolution. Yet, despite the complexity of this trait, vocal learning is frequently described as a binary trait, with species being classified as either vocal learners or vocal non-learners. As a result, studies have largely focused on a handful of species for which strong evidence for vocal learning exists. Recent studies, however, suggest a continuum in vocal learning capacity across taxa. Here, we further suggest that vocal learning is a multi-component behavioral phenotype comprised of distinct yet interconnected modules. Discretizing the vocal learning phenotype into its constituent modules would facilitate integration of findings across a wider diversity of species, taking advantage of the ways in which each excels in a particular module, or in a specific combination of features. Such comparative studies can improve understanding of the mechanisms and evolutionary origins of vocal learning. We propose an initial set of vocal learning modules supported by behavioral and neurobiological data and highlight the need for diversifying the field in order to disentangle the complexity of the vocal learning phenotype.

A comprehensive annotation and differential expression analysis of short and long non-coding RNAs in 16 bat genomes

Although bats are increasingly becoming the focus of scientific studies due to their unique properties, these exceptional animals are still among the least studied mammals. Assembly quality and completeness of bat genomes vary a lot and especially non-coding RNA (ncRNA) annotations are incomplete or simply missing. Accordingly, standard bioinformatics pipelines for gene expression analysis often ignore ncRNAs such as microRNAs or long antisense RNAs. The main cause of this problem is the use of incomplete genome annotations. We present a complete screening for ncRNAs within 16 bat genomes. NcRNAs affect a remarkable variety of vital biological functions, including gene expression regulation, RNA processing, RNA interference and, as recently described, regulatory processes in viral infections. Within all investigated bat assemblies, we annotated 667 ncRNA families including 162 snoRNAs and 193 miRNAs as well as rRNAs, tRNAs, several snRNAs and lncRNAs, and other structural ncRNA elements. We validated our ncRNA candidates by six RNA-Seq data sets and show significant expression patterns that have never been described before in a bat species on such a large scale. Our annotations will be usable as a resource (rna.uni-jena.de/supplements/bats) for deeper studying of bat evolution, ncRNAs repertoire, gene expression and regulation, ecology and important host–virus interactions.

Animals Have No Language, and Humans Are Animals Too

Language is a cornerstone of human culture, yet the evolution of this cognitive-demanding ability is shrouded in mystery. Studying how different species demonstrate this trait can provide clues for its evolutionary route. Indeed, recent decades saw ample scientific attempts to compare human speech, the prominent behavioral manifestation of language, with other animals' vocalizations. Diligent studies have found only elementary parallels to speech in other animals, fortifying the belief that language is uniquely human. But have we really tested this uniqueness claim? Surprisingly, a true impartial comparison between human speech and other animals' vocalizations has hardly ever been conducted. Here, I illustrate how treating humans as an equal species in vocal-communication research is expected to provide us with no evidence for human superiority in this realm. Thus, novel balanced and unbiased comparative studies are vital for identifying any unique component of human speech and language.

Long-term and persistent vocal plasticity in adult bats

Bats exhibit a diverse and complex vocabulary of social communication calls some of which are believed to be learned during development. This ability to produce learned, species-specific vocalizations – a rare trait in the animal kingdom – requires a high-degree of vocal plasticity. Bats live extremely long lives in highly complex and dynamic social environments, which suggests that they might also retain a high degree of vocal plasticity in adulthood, much as humans do. Here, we report persistent vocal plasticity in adult bats (Rousettus aegyptiacus) following exposure to broad-band, acoustic perturbation. Our results show that adult bats can not only modify distinct parameters of their vocalizations, but that these changes persist even after noise cessation – in some cases lasting several weeks or months. Combined, these findings underscore the potential importance of bats as a model organism for studies of vocal plasticity, including in adulthood.

Bats are long-lived animals that can produce a complex vocabulary of social communication calls. Here, the authors show that even in adulthood, bats retain the ability to adaptively introduce long-term modifications to their vocalizations, showing persistent vocal plasticity.

Correlated Neural Activity across the Brains of Socially Interacting Bats

Social interactions occur between multiple individuals, but what is the detailed relationship between the neural dynamics across their brains? To address this question across timescales and levels of neural activity, we used wireless electrophysiology to simultaneously record from pairs of bats engaged in a wide range of natural social interactions. We found that neural activity was remarkably correlated between their brains over timescales from seconds to hours. The correlation depended on a shared social environment and was most prominent in high frequency local field potentials (>30 Hz), followed by local spiking activity. Furthermore, the degree of neural correlation covaried with the extent of social interactions, and an increase in correlation preceded their initiation. These results show that inter-brain correlation is an inherent feature of natural social interactions, reveal the domain of neural activity where it is most prominent, and provide a foundation for studying its functional role in social behaviors.

The rise and fall of dialects in northern elephant seals

Vocal dialects are fundamental to our understanding of the transmission of social behaviours between individuals and populations, however few accounts trace this phenomenon among mammals over time. Northern elephant seals (Mirounga angustirostris) provide a rare opportunity to examine the trajectory of dialects in a long-lived mammalian species. Dialects were first documented in the temporal patterns of the stereotyped vocal displays produced by breeding males at four sites in the North Pacific in 1968 and 1969, as the population recovered from extreme exploitation. We evaluated the longevity of these geographical differences by comparing these early recordings to calls recently recorded at these same locations. While the presence of vocal dialects in the original recordings was re-confirmed, geographical differences in vocal behaviour were not found at these breeding rookeries nearly 50 years later. Moreover, the calls of contemporary males displayed more structural complexity after approximately four generations, with substantial between-individual variation and call features not present in the historical data. In the absence of measurable genetic variation in this species-owing to an extreme population bottleneck-a combination of migration patterns and cultural mutation are proposed as factors influencing the fall of dialects and the dramatic increase in call diversity.

Cultural transmission in an ever-changing world: trial-and-error copying may be more robust than precise imitation

Cultural transmission facilitates the spread of behaviours within social groups and may lead to the establishment of stable traditions in both human and non-human animals. The fidelity of transmission is frequently emphasized as a core component of cultural evolution and as a prerequisite for cumulative culture. Fidelity is often considered a synonym of precise copying of observed behaviours. However, while precise copying guarantees reliable transmission in an ideal static world, it may be vulnerable to realistic variability in the actual environment. Here, we argue that fidelity may be more naturally achieved when the social learning mechanisms incorporate trial-and-error; and that the robustness of social transmission is thereby increased. We employed a simple model to demonstrate how culture that is produced through exact copying is fragile in an (even slightly) noisy world. When incorporating a certain degree of trial-and-error, however, cultures are more readily formed in a stochastic environment and are less vulnerable to rare ecological changes. We suggest that considering trial-and-error learning as a stabilizing component of social transmission may provide insights into cultural evolution in a realistic, variable, world.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'.