Vocal Non-learners Research Articles

Playback experiment shows no evidence for vocal learning in titipounamu nestlings (Acanthisitta chloris)

ABSTRACT A recent reshuffling in the avian phylogeny indicates that New Zealand wrens and songbirds share a close common ancestor with parrots – making New Zealand wrens an excellent group to test for vocal learning. The New Zealand wrens have previously been classified as vocal non-learners, but their vocal learning ability has never been experimentally tested. Here, we explore the potential presence of vocal learning in one species of New Zealand wren, the titipounamu (Acanthisitta chloris). We expose nestlings to synthetic playback stimuli that simulate adult feeding calls and determine whether the nestlings altered their calls after exposure to the playback stimuli. We found that experimental nestlings did not alter their calls towards the playback stimuli. While this indicates that no vocal imitation occurred during the nestling period, other developmental stages should be tested for vocal learning, particularly during the fledgling or first year adult phase.

FoxP2 protein decreases at a specific region in the chick midbrain after hatching

Forkhead-box subclass P member 2 (FOXP2/FoxP2) protein, a transcription factor, regulates the development of certain brain functions, including human speech and animal vocalization. Although rapid progress has been made in demonstrating a relationship between FoxP2 expression in the brain and vocalization of the zebra finch, a typical vocal learner, the relationship in avian vocal non-learners, including chickens remains elusive. Because the midbrain plays a key role in innate vocalization development, we analyzed the FoxP2 protein in the midbrain of chicks, which do not cheep before hatching but cheep and call after hatching. Western blot analyses showed a significant reduction in FoxP2 protein in the chick midbrain after hatching compared with the findings before hatching. Quantitative immunohistochemistry revealed that FoxP2-immunoreactive (ir) cells significantly decreased at the stratum gris fibrosum (SGFS) of the optic tectum in the chick midbrain after hatching compared with the findings before hatching. These findings support the notion that FoxP2-ir cell numbers decrease at a specific region in the midbrain after hatching may be involved in innate vocalization of avian vocal non-learners.

Syntax errors do not disrupt acoustic communication in the common cuckoo

When acoustic communication signals are distorted, receivers may misunderstand the signal, rendering it ineffective. Common cuckoos (Cuculus canorus) are popularly known for the males’ simple, two-note advertisement calls, the “cu-coo” used for declaring the male’s breeding territories. Cuckoos do not learn their calls (vocal non-learners), so they are expected to have a limited ability to produce different acoustic signals. Nevertheless, male cuckoos appear to make syntax errors (e.g., repeated, reversed, or fragmented elements) even in their simple advertisement calls. We conducted a playback experiment with male cuckoos, broadcasting ten call types, including seven modified calls with errors (e.g. “cu-cu”, and “coo-cu”) and three natural calls used for comparisons (“cu-coo”, “cu-cu-coo”, and interspecific control). Male cuckoos responded in a manner suggesting that the presence of the first (“cu”) note of the natural 2-note “cu-coo” call in any form or combination yield effective signals. However, through the elevated frequency (by about 200 Hz) and greater speed of the “cu” note, the natural 3-note version “cu-cu-coo” call appears to have gained a novel communicative function in signalling with female cuckoos. Thus, syntax errors in calls with the “cu” element are not responsible for changing the function of the male cuckoos’ “cu-coo” call.

Phylogenetic signal in the vocalizations of vocal learning and vocal non-learning birds.

Some animal vocalizations develop reliably in the absence of relevant experience, but an intriguing subset of animal vocalizations is learned: they require acoustic models during ontogeny in order to develop, and the learner's vocal output reflects those models. To what extent do such learned vocalizations reflect phylogeny? We compared the degree to which phylogenetic signal is present in vocal signals from a wide taxonomic range of birds, including both vocal learners (songbirds) and vocal non-learners. We used publically available molecular phylogenies and developed methods to analyse spectral and temporal features in a carefully curated collection of high-quality recordings of bird songs and bird calls, to yield acoustic distance measures. Our methods were initially developed using pairs of closely related North American and European bird species, and then applied to a non-overlapping random stratified sample of European birds. We found strong similarity in acoustic and genetic distances, which manifested itself as a significant phylogenetic signal, in both samples. In songbirds, both learned song and (mostly) unlearned calls allowed reconstruction of phylogenetic trees nearly isomorphic to the phylogenetic trees derived from genetic analysis. We conclude that phylogeny and inheritance constrain vocal structure to a surprising degree, even in learned birdsong.This article is part of the theme issue ‘Vocal learning in animals and humans’.

Vocal learning and flexible rhythm pattern perception are linked: Evidence from songbirds

Rhythm perception is fundamental to speech and music. Humans readily recognize a rhythmic pattern, such as that of a familiar song, independently of the tempo at which it occurs. This shows that our perception of auditory rhythms is flexible, relying on global relational patterns more than on the absolute durations of specific time intervals. Given that auditory rhythm perception in humans engages a complex auditory-motor cortical network even in the absence of movement and that the evolution of vocal learning is accompanied by strengthening of forebrain auditory-motor pathways, we hypothesize that vocal learning species share our perceptual facility for relational rhythm processing. We test this by asking whether the best-studied animal model for vocal learning, the zebra finch, can recognize a fundamental rhythmic pattern-equal timing between event onsets (isochrony)-based on temporal relations between intervals rather than on absolute durations. Prior work suggests that vocal nonlearners (pigeons and rats) are quite limited in this regard and are biased to attend to absolute durations when listening to rhythmic sequences. In contrast, using naturalistic sounds at multiple stimulus rates, we show that male zebra finches robustly recognize isochrony independent of absolute time intervals, even at rates distant from those used in training. Our findings highlight the importance of comparative studies of rhythmic processing and suggest that vocal learning species are promising animal models for key aspects of human rhythm perception. Such models are needed to understand the neural mechanisms behind the positive effect of rhythm on certain speech and movement disorders.

Phylogenetic and kinematic constraints on avian flight signals.

Many birds vocalize in flight. Because wingbeat and respiratory cycles are often linked in flying vertebrates, birds in these cases must satisfy the respiratory demands of vocal production within the physiological limits imposed by flight. Using acoustic triangulation and high-speed video, we found that avian vocal production in flight exhibits a largely phasic and kinematic relationship with the power stroke. However, the sample of species showed considerable flexibility, especially those from lineages known for vocal plasticity (songbirds, parrots and hummingbirds), prompting a broader phylogenetic analysis. We thus collected data from 150 species across 12 avian orders and examined the links between wingbeat period, flight call duration and body mass. Overall, shorter wingbeat periods, controlling for ancestry and body mass, were correlated with shorter flight call durations. However, species from vocal learner lineages produced flight signals that, on average, exceeded multiple phases of their wingbeat cycle, while vocal non-learners had signal periods that were, on average, closer to the duration of their power stroke. These results raise an interesting question: is partial emancipation from respiratory constraints a necessary step in the evolution of vocal learning or an epiphenomenon? Our current study cannot provide the answer, but it does suggest several avenues for future research.

Predictive and tempo-flexible synchronization to a visual metronome in monkeys

Predictive and tempo-flexible synchronization to an auditory beat is a fundamental component of human music. To date, only certain vocal learning species show this behaviour spontaneously. Prior research training macaques (vocal non-learners) to tap to an auditory or visual metronome found their movements to be largely reactive, not predictive. Does this reflect the lack of capacity for predictive synchronization in monkeys, or lack of motivation to exhibit this behaviour? To discriminate these possibilities, we trained monkeys to make synchronized eye movements to a visual metronome. We found that monkeys could generate predictive saccades synchronized to periodic visual stimuli when an immediate reward was given for every predictive movement. This behaviour generalized to novel tempi, and the monkeys could maintain the tempo internally. Furthermore, monkeys could flexibly switch from predictive to reactive saccades when a reward was given for each reactive response. In contrast, when humans were asked to make a sequence of reactive saccades to a visual metronome, they often unintentionally generated predictive movements. These results suggest that even vocal non-learners may have the capacity for predictive and tempo-flexible synchronization to a beat, but that only certain vocal learning species are intrinsically motivated to do it.

A method for testing synchronization to a musical beat in domestic horses (Equus ferus caballus)

According to the “vocal learning and rhythmic synchronization hypothesis” (Patel, 2006), only species capable of complex vocal learning, such as humans and parrots, have the capacity to synchronize their movements to a musical beat. While empirical research to date on a few species (e.g., parrots and monkeys) has supported this hypothesis, many species remain to be examined. Domestic horses are particularly important to study, as they are vocal non-learners who are occasionally reported to move in synchrony with a musical beat, based on informal observations. If these reports are substantiated by scientific experiments, this would refute the vocal learning hypothesis and provide a new species for the comparative study of musical rhythm. Here we present a new method for testing whether horses can synchronize their trotting to a musical beat, including an illustration of data analysis based on data collected from one horse.

Convergent Differential Regulation of Parvalbumin in the Brains of Vocal Learners

Spoken language and learned song are complex communication behaviors found in only a few species, including humans and three groups of distantly related birds – songbirds, parrots, and hummingbirds. Despite their large phylogenetic distances, these vocal learners show convergent behaviors and associated brain pathways for vocal communication. However, it is not clear whether this behavioral and anatomical convergence is associated with molecular convergence. Here we used oligo microarrays to screen for genes differentially regulated in brain nuclei necessary for producing learned vocalizations relative to adjacent brain areas that control other behaviors in avian vocal learners versus vocal non-learners. A top candidate gene in our screen was a calcium-binding protein, parvalbumin (PV). In situ hybridization verification revealed that PV was expressed significantly higher throughout the song motor pathway, including brainstem vocal motor neurons relative to the surrounding brain regions of all distantly related avian vocal learners. This differential expression was specific to PV and vocal learners, as it was not found in avian vocal non-learners nor for control genes in learners and non-learners. Similar to the vocal learning birds, higher PV up-regulation was found in the brainstem tongue motor neurons used for speech production in humans relative to a non-human primate, macaques. These results suggest repeated convergent evolution of differential PV up-regulation in the brains of vocal learners separated by more than 65–300 million years from a common ancestor and that the specialized behaviors of learned song and speech may require extra calcium buffering and signaling.

Birds, primates, and spoken language origins: behavioral phenotypes and neurobiological substrates.

Vocal learners such as humans and songbirds can learn to produce elaborate patterns of structurally organized vocalizations, whereas many other vertebrates such as non-human primates and most other bird groups either cannot or do so to a very limited degree. To explain the similarities among humans and vocal-learning birds and the differences with other species, various theories have been proposed. One set of theories are motor theories, which underscore the role of the motor system as an evolutionary substrate for vocal production learning. For instance, the motor theory of speech and song perception proposes enhanced auditory perceptual learning of speech in humans and song in birds, which suggests a considerable level of neurobiological specialization. Another, a motor theory of vocal learning origin, proposes that the brain pathways that control the learning and production of song and speech were derived from adjacent motor brain pathways. Another set of theories are cognitive theories, which address the interface between cognition and the auditory-vocal domains to support language learning in humans. Here we critically review the behavioral and neurobiological evidence for parallels and differences between the so-called vocal learners and vocal non-learners in the context of motor and cognitive theories. In doing so, we note that behaviorally vocal-production learning abilities are more distributed than categorical, as are the auditory-learning abilities of animals. We propose testable hypotheses on the extent of the specializations and cross-species correspondences suggested by motor and cognitive theories. We believe that determining how spoken language evolved is likely to become clearer with concerted efforts in testing comparative data from many non-human animal species.

Dynamics of crowing development in the domestic Japanese quail (Coturnix coturnix japonica).

Species-specific behaviours gradually emerge, via incomplete patterns, to the final complete adult form. A classical example is birdsong, a learned behaviour ideally suited for studying the neural and molecular substrates of vocal learning. Young songbirds gradually transform primitive unstructured vocalizations (subsong, akin to human babbling) into complex, stereotyped sequences of syllables that constitute adult song. In comparison with birdsong, territorial and mating calls of vocal non-learner species are thought to exhibit little change during development. We revisited this issue using the crowing behaviour of domestic Japanese quail (Coturnix coturnix japonica). Crowing activity was continuously recorded in young males maintained in social isolation from the age of three weeks to four months. We observed developmental changes in crow structure, both the temporal and the spectral levels. Speed and trajectories of these developmental changes exhibited an unexpected high inter-individual variability. Mechanisms used by quails to transform sounds during ontogeny resemble those described in oscines during the sensorimotor phase of song learning. Studies on vocal non-learners could shed light on the specificity and evolution of vocal learning.

Molecular Mapping of Movement-Associated Areas in the Avian Brain: A Motor Theory for Vocal Learning Origin

Vocal learning is a critical behavioral substrate for spoken human language. It is a rare trait found in three distantly related groups of birds-songbirds, hummingbirds, and parrots. These avian groups have remarkably similar systems of cerebral vocal nuclei for the control of learned vocalizations that are not found in their more closely related vocal non-learning relatives. These findings led to the hypothesis that brain pathways for vocal learning in different groups evolved independently from a common ancestor but under pre-existing constraints. Here, we suggest one constraint, a pre-existing system for movement control. Using behavioral molecular mapping, we discovered that in songbirds, parrots, and hummingbirds, all cerebral vocal learning nuclei are adjacent to discrete brain areas active during limb and body movements. Similar to the relationships between vocal nuclei activation and singing, activation in the adjacent areas correlated with the amount of movement performed and was independent of auditory and visual input. These same movement-associated brain areas were also present in female songbirds that do not learn vocalizations and have atrophied cerebral vocal nuclei, and in ring doves that are vocal non-learners and do not have cerebral vocal nuclei. A compilation of previous neural tracing experiments in songbirds suggests that the movement-associated areas are connected in a network that is in parallel with the adjacent vocal learning system. This study is the first global mapping that we are aware for movement-associated areas of the avian cerebrum and it indicates that brain systems that control vocal learning in distantly related birds are directly adjacent to brain systems involved in movement control. Based upon these findings, we propose a motor theory for the origin of vocal learning, this being that the brain areas specialized for vocal learning in vocal learners evolved as a specialization of a pre-existing motor pathway that controls movement.

Differential expression of glutamate receptors in avian neural pathways for learned vocalization

Learned vocalization, the substrate for human language, is a rare trait. It is found in three distantly related groups of birds-parrots, hummingbirds, and songbirds. These three groups contain cerebral vocal nuclei for learned vocalization not found in their more closely related vocal nonlearning relatives. Here, we cloned 21 receptor subunits/subtypes of all four glutamate receptor families (AMPA, kainate, NMDA, and metabotropic) and examined their expression in vocal nuclei of songbirds. We also examined expression of a subset of these receptors in vocal nuclei of hummingbirds and parrots, as well as in the brains of dove species as examples of close vocal nonlearning relatives. Among the 21 subunits/subtypes, 19 showed higher and/or lower prominent differential expression in songbird vocal nuclei relative to the surrounding brain subdivisions in which the vocal nuclei are located. This included relatively lower levels of all four AMPA subunits in lMAN, strikingly higher levels of the kainite subunit GluR5 in the robust nucleus of the arcopallium (RA), higher and lower levels respectively of the NMDA subunits NR2A and NR2B in most vocal nuclei and lower levels of the metabotropic group I subtypes (mGluR1 and -5) in most vocal nuclei and the group II subtype (mGluR2), showing a unique expression pattern of very low levels in RA and very high levels in HVC. The splice variants of AMPA subunits showed further differential expression in vocal nuclei. Some of the receptor subunits/subtypes also showed differential expression in hummingbird and parrot vocal nuclei. The magnitude of differential expression in vocal nuclei of all three vocal learners was unique compared with the smaller magnitude of differences found for nonvocal areas of vocal learners and vocal nonlearners. Our results suggest that evolution of vocal learning was accompanied by differential expression of a conserved gene family for synaptic transmission and plasticity in vocal nuclei. They also suggest that neural activity and signal transduction in vocal nuclei of vocal learners will be different relative to the surrounding brain areas.