Dynamical origin of spectrally rich vocalizations in birdsong

Note similarities affect syntactic stability in zebra finches

The acquisition of an acoustic template is a fundamental component of vocal imitation learning, which is used to refine innate vocalizations and develop a species-specific song. In the absence of a model, birds fail to develop species typical songs. In zebra finches (Taeniopygia guttata), tutored birds produce songs with a stereotyped sequence of distinct acoustic elements, or notes, which form the song motif. Songs of untutored individuals feature atypical acoustic and temporal structure. Here we studied songs and associated respiratory patterns of tutored and untutored male zebra finches to investigate whether similar acoustic notes influence the sequence of song elements. A subgroup of animals developed songs with multiple acoustically similar notes that are produced with alike respiratory motor gestures. These birds also showed increased syntactic variability in their adult motif. Sequence variability tended to occur near song elements which showed high similarity in acoustic structure and underlying respiratory motor gestures. The duration and depth of the inspirations preceding the syllables where syntactic variation occurred did not allow prediction of the following sequence of notes, suggesting that the varying duration and air requirement of the following expiratory pulse is not predictively encoded in the motor program. This study provides a novel method for calculation of motor/acoustic similarity, and the results of this study suggest that the note is a fundamental acoustic unit in the organization of the motif and could play a role in the neural code for song syntax.

Response of wild songbirds to songs synthesized with a low-dimensional model

In this work, we used a dynamical system derived from an avian vocal production model to generate synthetic songs that mimic the Zonotrichia capensis songs. We confirmed that these synthetic renditions elicited behavioral responses similar to those evoked by real songs in wild songbirds of the same species. Specifically, we observed an increase in the singing rate of individual birds when a playback device was introduced into their territories. The success of our approach instills confidence in the hypotheses underpinning the model and provides a valuable tool for investigating a wide range of biological questions.

Tonality over a broad frequency range is linked to vocal learning in birds

Many birds emit tonal song syllables even though the sound sources generate sound with rich upper harmonic energy content. This tonality is thought to arise in part from dynamically adjusted filtering of harmonic content. Here, we compare tonality of song syllables between vocal learners and non-learners to assess whether this characteristic is linked to the increased neural substrate that evolved with vocal learning. We hypothesize that vocal learning ability is correlated with enhanced ability for generating tonal sounds, because vocal production learners might also have an enhanced ability to articulate their vocal tracts and sound source for producing tonality. To test this hypothesis, we compared vocal learners and non-learners from two groups (186 passerines and 42 hummingbirds) by assessing tonality of song syllables. The data suggest that vocal learners in both clades have evolved to sing songs with higher tonality than the related, non-vocal learning clades, which is consistent with stronger roles for broadband dynamic filtering and adjustments to the sound source. In addition, oscine songs display higher tonality than those of hummingbirds. A complex interplay of vocal tract biomechanics, anatomical differences of the sound source as well as increased motor control through vocal learning facilitates generation of broad tonality.

Toward a Computational Neuroethology of Vocal Communication: From Bioacoustics to Neurophysiology, Emerging Tools and Future Directions

Recently developed methods in computational neuroethology have enabled increasingly detailed and comprehensive quantification of animal movements and behavioral kinematics. Vocal communication behavior is well poised for application of similar large-scale quantification methods in the service of physiological and ethological studies. This review describes emerging techniques that can be applied to acoustic and vocal communication signals with the goal of enabling study beyond a small number of model species. We review a range of modern computational methods for bioacoustics, signal processing, and brain-behavior mapping. Along with a discussion of recent advances and techniques, we include challenges and broader goals in establishing a framework for the computational neuroethology of vocal communication.

Neurally driven synthesis of learned, complex vocalizations

Brain machine interfaces (BMIs) hold promise to restore impaired motor function and serve as powerful tools to study learned motor skill. While limb-based motor prosthetic systems have leveraged nonhuman primates as an important animal model,^1-4 speech prostheses lack a similar animal model and are more limited in terms of neural interface technology, brain coverage, and behavioral study design.^5-7 Songbirds are an attractive model for learned complex vocal behavior. Birdsong shares a number of unique similarities with human speech,^8-10 and its study has yielded general insight into multiple mechanisms and circuits behind learning, execution, and maintenance of vocal motor skill.^11-18 In addition, the biomechanics of song production bear similarity to those of humans and some nonhuman primates.^19-23 Here, we demonstrate a vocal synthesizer for birdsong, realized by mapping neural population activity recorded from electrode arrays implanted in the premotor nucleus HVC onto low-dimensional compressed representations of song, using simple computational methods that are implementable in real time. Using a generative biomechanical model of the vocal organ (syrinx) as the low-dimensional target for these mappings allows for the synthesis of vocalizations that match the bird's own song. These results provide proof of concept that high-dimensional, complex natural behaviors can be directly synthesized from ongoing neural activity. This may inspire similar approaches to prosthetics in other species by exploiting knowledge of the peripheral systems and the temporal structure of their output.

Synthetic Birdsongs as a Tool to Induce, and Iisten to, Replay Activity in Sleeping Birds

Birdsong is a complex vocal behavior, which emerges out of the interaction between a nervous system and a highly nonlinear vocal device, the syrinx. In this work we discuss how low dimensional dynamical systems, interpretable in terms of the biomechanics involved, are capable of synthesizing realistic songs. We review the experimental and conceptual steps that lead to the formulation of low dimensional dynamical systems for the song system and describe the tests that quantify their success. In particular, we show how to evaluate computational models by comparing the responses of highly selective neurons to the bird's own song and to synthetic copies generated mathematically. Beyond testing the hypothesis behind the model's construction, these low dimensional models allow designing precise stimuli in order to explore the sensorimotor integration of acoustic signals.

Multifunctional bilateral muscle control of vocal output in the songbird syrinx

Songbirds produce complex vocalizations by coordinating neuromuscular control of syrinx, respiratory system, and upper vocal tract. The functional roles of syringeal muscles have been documented mainly with correlative data, which have suggested that synergistic activation plays a role in the fine control of vocal features. However, the specific involvement of individual muscles in achieving this fine control is still largely unknown. Here we investigate the contributions of the two main airflow controlling muscles, the dorsal and ventral tracheobronchial muscles in the zebra finch, through a new approach. Ablation of the muscle insertion on the cartilage framework reveals detailed insights into their respective roles in the fine control of song features. Unilateral ablation of a tracheobronchial muscle resulted in mostly subtle changes of the air sac pressure pattern and song features. Effects of ablation varied with the acoustic elements, thus indicating a context-dependent specific synergistic activation of muscles. High-frequency notes were most affected by the ablation, highlighting the importance of coordinated bilateral control. More pronounced effects on song features and air sac pressure were observed after bilateral ablation of the dorsal tracheobronchial muscles. The results illustrate that the gating muscles serve multiple functions in control of acoustic features and that each feature arises through context-dependent, synergistic activation patterns of syringeal muscles. Although many changes after the ablation are subtle, they fall within the perceptual range and thus may control behaviorally relevant features of sound. These data therefore provide important specific details about the underlying motor code for song production.NEW & NOTEWORTHY A new experimental approach was used to analyze the involvement of individual muscles in birdsong vocal control. Ablation of tracheobronchial muscles showed how these muscles contribute in manner specific to the acoustic structure of sound segments and how disruption of airflow regulation affects bilateral coordination. The results of this study illustrate that the gating muscles serve multiple functions in control of acoustic features and give further insight into the complex motor control of birdsong.

Song Feature Specific Analysis of Isolate Song Reveals Interspecific Variation in Learned Components

Studies of avian vocal development without exposure to conspecific song have been conducted in many passerine species, and the resultant isolate song is often interpreted to represent an expression of the genetic code for conspecific song. There is wide recognition that vocal learning exists in oscine songbirds, but vocal learning has only been thoroughly investigated in a few model species, resulting in a narrow view of birdsong learning. By extracting acoustic signals from published spectrograms, we have reexamined the findings of isolate studies with a universally applicable semi-automated quantitative analysis regimen. When song features were analyzed in light of three different production aspects (respiratory, syringeal, and central programming of sequence), all three show marked interspecific variability in how close isolate song features are to normal. This implies that song learning mechanisms are more variable than is commonly recognized. Our results suggest that the interspecific variation shows no readily observable pattern reflecting phylogeny, which has implications for understanding the mechanisms behind the evolution of avian vocal communication. We emphasize that song learning in passerines provides an excellent opportunity to investigate the evolution of a complex, plastic trait from a phylogenetic perspective.

Syringeal EMGs and synthetic stimuli reveal a switch-like activation of the songbird's vocal motor program

The coordination of complex vocal behaviors like human speech and oscine birdsong requires fine interactions between sensory and motor programs, the details of which are not completely understood. Here, we show that in sleeping male zebra finches (Taeniopygia guttata), the activity of the song system selectively evoked by playbacks of their own song can be detected in the syrinx. Electromyograms (EMGs) of a syringeal muscle show playback-evoked patterns strikingly similar to those recorded during song execution, with preferred activation instants within the song. Using this global and continuous readout, we studied the activation dynamics of the song system elicited by different auditory stimuli. We found that synthetic versions of the bird's song, rendered by a physical model of the avian phonation apparatus, evoked very similar responses, albeit with lower efficiency. Modifications of autogenous or synthetic songs reduce the response probability, but when present, the elicited activity patterns match execution patterns in shape and timing, indicating an all-or-nothing activation of the vocal motor program.

Gating related activity in a syringeal muscle allows the reconstruction of zebra finches songs

Birdsong production involves the simultaneous and precise control of a set of muscles that change the configuration and dynamics of the vocal organ. Although it has been reported that each one of the different muscles is primarily involved in the control of one acoustic feature, recent advances have shown that they act synergistically to achieve the dynamical state necessary for phonation. In this work, we present a set of criteria that allow the extraction of gating-related information from the electromyographic activity of the syringealis ventralis muscle, a muscle that has been shown to be involved in frequency modulation. Using dynamical models of the muscle and syringeal dynamics, we obtain a full reconstruction of the zebra finch song using only the activity of this muscle.

Nonlinear dynamics in the study of birdsong

Birdsong, a rich and complex behavior, is a stellar model to understand a variety of biological problems, from motor control to learning. It also enables us to study how behavior emerges when a nervous system, a biomechanical device and the environment interact. In this review, I will show that many questions in the field can benefit from the approach of nonlinear dynamics, and how birdsong can inspire new directions for research in dynamics.

Evolution of Vocal Diversity through Morphological Adaptation without Vocal Learning or Complex Neural Control

The evolution of complex behavior is driven by the interplay of morphological specializations and neuromuscular control mechanisms [1-3], and it is often difficult to tease apart their respective contributions. Avian vocal learning and associated neural adaptations are thought to have played a major role in bird diversification [4-8], whereas functional significance of substantial morphological diversity of the vocal organ remains largely unexplored. Within the most species-rich order, Passeriformes, "tracheophones" are a suboscine group that, unlike their oscine sister taxon, does not exhibit vocal learning [9] and is thought to phonate with tracheal membranes [10, 11] instead of the two independent sources found in other passerines [12-14]. Here we show tracheophones possess three sound sources, two oscine-like labial pairs and the unique tracheal membranes, which collectively represent the largest described number of sound sources for a vocal organ. Birds with experimentally disabled tracheal membranes were still able to phonate. Instead of the main sound source, the tracheal membranes constitute a morphological specialization, which, through interaction with bronchial labia, contributes to different acoustic features such as spectral complexity, amplitude modulation, and enhanced sound amplitude. In contrast, these same features arise in oscines from neuromuscular control of two labial sources [15-17]. These findings are supported by a modeling approach and provide a clear example for how a morphological adaptation of the tracheophone vocal organ can generate specific, complex sound features. Morphological specialization therefore constitutes an alternative path in the evolution of acoustic diversity to that of oscine vocal learning and complex neural control.

Controllable biomimetic birdsong

Birdsong is the product of the controlled generation of sound embodied in a neuromotor system. From a biophysical perspective, a natural question is that of the difficulty of producing birdsong. To address this, we built a biomimetic syrinx consisting of a stretched simple rubber tube through which air is blown, subject to localized mechanical squeezing with a linear actuator. A large static tension on the tube and small dynamic variations in the localized squeezing allow us to control transitions between three states: a quiescent state, a periodic state and a solitary wave state. The static load brings the system close to threshold for spontaneous oscillations, while small dynamic loads allow for rapid transitions between the states. We use this to mimic a variety of birdsongs via the slow-fast modulated nonlinear dynamics of the physical substrate, the syrinx, regulated by a simple controller. Finally, a minimal mathematical model of the system inspired by our observations allows us to address the problem of song mimicry in an excitable oscillator for tonal songs.

Vocal development in a Waddington landscape

Vocal development is the adaptive coordination of the vocal apparatus, muscles, the nervous system, and social interaction. Here, we use a quantitative framework based on optimal control theory and Waddington’s landscape metaphor to provide an integrated view of this process. With a biomechanical model of the marmoset monkey vocal apparatus and behavioral developmental data, we show that only the combination of the developing vocal tract, vocal apparatus muscles and nervous system can fully account for the patterns of vocal development. Together, these elements influence the shape of the monkeys’ vocal developmental landscape, tilting, rotating or shifting it in different ways. We can thus use this framework to make quantitative predictions regarding how interfering factors or experimental perturbations can change the landscape within a species, or to explain comparative differences in vocal development across species

DOI:http://dx.doi.org/10.7554/eLife.20782.001

As infants develop they learn new behaviors and refine existing ones. For example, human infants progress from crying to babbling to producing speech-like sounds. A complex sequence of changes in muscles, the nervous system and in patterns of interactions with other individuals all contribute to these emerging behaviors.

Despite this complexity, most studies of vocal development have only considered single factors in isolation. A study of speech development, for example, might examine how changes in the brain enable infants to imitate sounds. However, that same study will probably ignore how changes in the structure of the vocal cords, or in the behavior of the parents, also promote imitation.

Young marmoset monkeys, like human infants, gradually develop from producing immature cries to adult-like calls. Teramoto, Takahashi et al. built a computational model of this process and compared the model to data from real animals. The first version of the model focused solely on how the marmosets’ vocal cords grow, and did not fully reproduce how adult-like calls emerge in real marmosets. Teramoto, Takahashi et al. therefore added factors to the model that simulate improvements in muscle control, learning in the nervous system and in the behavior of other animals. These findings show that, to reflect how adult-like calls emerge in real marmosets, the model needs to include all of these factors.

The model developed by Teramoto, Takahashi et al. may also provide insights into why vocal learning and some other behaviors emerge in some species and not others. It may also be used to predict the consequences of disrupting individual processes in young animals at particular points in time and how such disruptions shape the way an animal develops on its way to adulthood.

DOI:http://dx.doi.org/10.7554/eLife.20782.002

Contributions of rapid neuromuscular transmission to the fine control of acoustic parameters of birdsong

Neural control of complex vocal behaviors, such as birdsong and speech, requires integration of biomechanical nonlinearities through muscular output. Although control of airflow and tension of vibrating tissues are known functions of vocal muscles, it remains unclear how specific muscle characteristics contribute to specific acoustic parameters. To address this gap, we removed heparan sulfate chains using heparitinases to perturb neuromuscular transmission subtly in the syrinx of adult male zebra finches (Taeniopygia guttata). Infusion of heparitinases into ventral syringeal muscles altered their excitation threshold and reduced neuromuscular transmission changing their ability to modulate airflow. The changes in muscle activation dynamics caused a reduction in frequency modulation rates and elimination of many high-frequency syllables but did not alter the fundamental frequency of syllables. Sound amplitude was reduced and sound onset pressure was increased, suggesting a role of muscles in the induction of self-sustained oscillations under low-airflow conditions, thus enhancing vocal efficiency. These changes were reversed to preinfusion levels by 7 days after infusion. These results illustrate complex interactions between the control of airflow and tension and further define the importance of syringeal muscle in the control of a variety of acoustic song characteristics. In summary, the findings reported here show that altering neuromuscular transmission can lead to reversible changes to the acoustic structure of song. Understanding the full extent of muscle involvement in song production is critical in decoding the motor program for the production of complex vocal behavior, including our search for parallels between birdsong and human speech motor control.

NEW & NOTEWORTHY

It is largely unknown how fine motor control of acoustic parameters is achieved in vocal organs. Subtle manipulation of syringeal muscle function was used to test how active motor control influences acoustic parameters. Slowed activation kinetics of muscles reduced frequency modulation and, unexpectedly, caused a distinct decrease in sound amplitude and increase in phonation onset pressure. These results show that active control enhances the efficiency of energy conversion in the syrinx.

Difference between the vocalizations of two sister species of pigeons explained in dynamical terms

Vocal communication is an unique example, where the nonlinear nature of the periphery can give rise to complex sounds even when driven by simple neural instructions. In this work we studied the case of two close-related bird species, Patagioenas maculosa and Patagioenas picazuro, whose vocalizations differ only in the timbre. The temporal modulation of the fundamental frequency is similar in both cases, differing only in the existence of sidebands around the fundamental frequency in the P. maculosa. We tested the hypothesis that the qualitative difference between these vocalizations lies in the nonlinear nature of the syrinx. In particular, we propose that the roughness of maculosa's vocalizations is due to an asymmetry between the right and left vibratory membranes, whose nonlinear dynamics generate the sound. To test the hypothesis, we generated a biomechanical model for vocal production with an asymmetric parameter Q with which we can control the level of asymmetry between these membranes. Using this model we generated synthetic vocalizations with the principal acoustic features of both species. In addition, we confirmed the anatomical predictions by making post mortem inspection of the syrinxes, showing that the species with tonal song (picazuro) has a more symmetrical pair of membranes compared to maculosa.

The vocal repertoire of the domesticated zebra finch: a data-driven approach to decipher the information-bearing acoustic features of communication signals

Although a universal code for the acoustic features of animal vocal communication calls may not exist, the thorough analysis of the distinctive acoustical features of vocalization categories is important not only to decipher the acoustical code for a specific species but also to understand the evolution of communication signals and the mechanisms used to produce and understand them. Here, we recorded more than 8000 examples of almost all the vocalizations of the domesticated zebra finch, Taeniopygia guttata: vocalizations produced to establish contact, to form and maintain pair bonds, to sound an alarm, to communicate distress or to advertise hunger or aggressive intents. We characterized each vocalization type using complete representations that avoided any a priori assumptions on the acoustic code, as well as classical bioacoustics measures that could provide more intuitive interpretations. We then used these acoustical features to rigorously determine the potential information-bearing acoustical features for each vocalization type using both a novel regularized classifier and an unsupervised clustering algorithm. Vocalization categories are discriminated by the shape of their frequency spectrum and by their pitch saliency (noisy to tonal vocalizations) but not particularly by their fundamental frequency. Notably, the spectral shape of zebra finch vocalizations contains peaks or formants that vary systematically across categories and that would be generated by active control of both the vocal organ (source) and the upper vocal tract (filter).

Automatic reconstruction of physiological gestures used in a model of birdsong production

Highly coordinated learned behaviors are key to understanding neural processes integrating the body and the environment. Birdsong production is a widely studied example of such behavior in which numerous thoracic muscles control respiratory inspiration and expiration: the muscles of the syrinx control syringeal membrane tension, while upper vocal tract morphology controls resonances that modulate the vocal system output. All these muscles have to be coordinated in precise sequences to generate the elaborate vocalizations that characterize an individual's song. Previously we used a low-dimensional description of the biomechanics of birdsong production to investigate the associated neural codes, an approach that complements traditional spectrographic analysis. The prior study used algorithmic yet manual procedures to model singing behavior. In the present work, we present an automatic procedure to extract low-dimensional motor gestures that could predict vocal behavior. We recorded zebra finch songs and generated synthetic copies automatically, using a biomechanical model for the vocal apparatus and vocal tract. This dynamical model described song as a sequence of physiological parameters the birds control during singing. To validate this procedure, we recorded electrophysiological activity of the telencephalic nucleus HVC. HVC neurons were highly selective to the auditory presentation of the bird's own song (BOS) and gave similar selective responses to the automatically generated synthetic model of song (AUTO). Our results demonstrate meaningful dimensionality reduction in terms of physiological parameters that individual birds could actually control. Furthermore, this methodology can be extended to other vocal systems to study fine motor control.

A versatile class of prototype dynamical systems for complex bifurcation cascades of limit cycles

A general class of prototype dynamical systems is introduced, which allows to study the generation of complex bifurcation cascades of limit cycles, including bifurcations breaking spontaneously a symmetry of the system, period doubling and homoclinic bifurcations, and transitions to chaos induced by sequences of limit cycle bifurcations. The prototype systems are adaptive, with friction forces f(V(x)) being functionally dependent exclusively on the mechanical potential V(x), characterized in turn by a finite number of local minima. We discuss several low-dimensional systems, with friction forces f(V) which are linear, quadratic or cubic polynomials in the potential V. We point out that the zeros of f(V) regulate both the relative importance of energy uptake and dissipation respectively, serving at the same time as bifurcation parameters, hence allowing for an intuitive interpretation of the overall dynamical behavior. Starting from simple Hopf- and homoclinic bifurcations, complex sequences of limit cycle bifurcations are observed when the energy uptake gains progressively in importance.

Modeling vocalization with ECoG cortical activity recorded during vocal production in the macaque monkey

Vocal production is an example of controlled motor behavior with high temporal precision. Previous studies have decoded auditory evoked cortical activity while monkeys listened to vocalization sounds. On the other hand, there have been few attempts at decoding motor cortical activity during vocal production. Here we recorded cortical activity during vocal production in the macaque with a chronically implanted electrocorticographic (ECoG) electrode array. The array detected robust activity in motor cortex during vocal production. We used a nonlinear dynamical model of the vocal organ to reduce the dimensionality of `Coo' calls produced by the monkey. We then used linear regression to evaluate the information in motor cortical activity for this reduced representation of calls. This simple linear model accounted for circa 65% of the variance in the reduced sound representations, supporting the feasibility of using the dynamical model of the vocal organ for decoding motor cortical activity during vocal production.

Motor control of sound frequency in birdsong involves the interaction between air sac pressure and labial tension

Frequency modulation is a salient acoustic feature of birdsong. Its control is usually attributed to the activity of syringeal muscles, which affect the tension of the labia responsible for sound production. We use experimental and theoretical tools to test the hypothesis that for birds producing tonal sounds such as domestic canaries (Serinus canaria), frequency modulation is determined by both the syringeal tension and the air sac pressure. For different models, we describe the structure of the isofrequency curves, which are sets of parameters leading to sounds presenting the same fundamental frequencies. We show how their shapes determine the relative roles of syringeal tension and air sac pressure in frequency modulation. Finally, we report experiments that allow us to unveil the features of the isofrequency curves.

A mechanism for frequency modulation in songbirds shared with humans

In most animals that vocalize, control of fundamental frequency is a key element for effective communication. In humans, subglottal pressure controls vocal intensity but also influences fundamental frequency during phonation. Given the underlying similarities in the biomechanical mechanisms of vocalization in humans and songbirds, songbirds offer an attractive opportunity to study frequency modulation by pressure. Here, we present a novel technique for dynamic control of subsyringeal pressure in zebra finches. By regulating the opening of a custom-built fast valve connected to the air sac system, we achieved partial or total silencing of specific syllables, and could modify syllabic acoustics through more complex manipulations of air sac pressure. We also observed that more nuanced pressure variations over a limited interval during production of a syllable concomitantly affected the frequency of that syllable segment. These results can be explained in terms of a mathematical model for phonation that incorporates a nonlinear description for the vocal source capable of generating the observed frequency modulations induced by pressure variations. We conclude that the observed interaction between pressure and frequency was a feature of the source, not a result of feedback control. Our results indicate that, beyond regulating phonation or its absence, regulation of pressure is important for control of fundamental frequencies of vocalizations. Thus, although there are separate brainstem pathways for syringeal and respiratory control of song production, both can affect airflow and frequency. We hypothesize that the control of pressure and frequency is combined holistically at higher levels of the vocalization pathways.

Elemental gesture dynamics are encoded by song premotor cortical neurons

Quantitative biomechanical models can identify control parameters used during movements, and movement parameters encoded by premotor neurons. We fit a mathematical dynamical systems model including subsyringeal pressure, syringeal biomechanics, and upper vocal tract filtering to the songs of zebra finches. This reduced the dimensionality of singing dynamics, described as trajectories in pressure-tension space (motor “gestures”). We assessed model performance by characterizing the auditory response "replay" of song premotor HVC neurons to presentation of song variants in sleeping birds, and by examining HVC activity in singing birds. HVC projection neurons were excited and interneurons were suppressed with near-zero time lag, at times of gesture trajectory extrema. Thus, HVC precisely encodes vocal motor output via the timing of extreme points of movement trajectories. We propose that the sequential activity of HVC neurons represents the sequence of gestures in song as a “forward” model making predictions on expected behavior to evaluate feedback.

Integrative physiology of fundamental frequency control in birds

One major feature of the remarkable vocal repertoires of birds is the range of fundamental frequencies across species, but also within individual species. This review discusses four variables that determine the oscillation frequency of the vibrating structures within a bird's syrinx. These are (1) viscoelastic properties of the oscillating tissue, (2) air sac pressure, (3) neuromuscular control of movements and (4) source-filter interactions. Our current understanding of morphology, biomechanics and neural control suggests that a complex interplay of these parameters can lead to multiple combinations for generating a particular fundamental frequency. An increase in the complexity of syringeal morphology from non-passeriform birds to oscines also led to a different interplay for regulating oscillation frequency by enabling control of tension that is partially independent of regulation of airflow. In addition to reviewing the available data for all different contributing variables, we point out open questions and possible approaches.

A species-specific view of song representation in a sensorimotor nucleus

Songbirds constitute a powerful model system for the investigation of how complex vocal communication sounds are represented and generated, offering a neural system in which the brain areas involved in auditory, motor and auditory-motor integration are well known. One brain area of considerable interest is the nucleus HVC. Neurons in the HVC respond vigorously to the presentation of the bird's own song and display song-related motor activity. In the present paper, we present a synthesis of neurophysiological studies performed in the HVC of one songbird species, the canary (Serinus canaria). These studies, by taking advantage of the singing behavior and song characteristics of the canary, have examined the neuronal representation of the bird's own song in the HVC. They suggest that breeding cues influence the degree of auditory selectivity of HVC neurons for the bird's own song over its time-reversed version, without affecting the contribution of spike timing to the information carried by these two song stimuli. Also, while HVC neurons are collectively more responsive to forward playback of the bird's own song than to its temporally or spectrally modified versions, some are more broadly tuned, with an auditory responsiveness that extends beyond the bird's own song. Lastly, because the HVC is also involved in song production, we discuss the peripheral control of song production, and suggest that interspecific variations in song production mechanisms could be exploited to improve our understanding of the functional role of the HVC in respiratory-vocal coordination.

Prosthetic avian vocal organ controlled by a freely behaving bird based on a low dimensional model of the biomechanical periphery

Because of the parallels found with human language production and acquisition, birdsong is an ideal animal model to study general mechanisms underlying complex, learned motor behavior. The rich and diverse vocalizations of songbirds emerge as a result of the interaction between a pattern generator in the brain and a highly nontrivial nonlinear periphery. Much of the complexity of this vocal behavior has been understood by studying the physics of the avian vocal organ, particularly the syrinx. A mathematical model describing the complex periphery as a nonlinear dynamical system leads to the conclusion that nontrivial behavior emerges even when the organ is commanded by simple motor instructions: smooth paths in a low dimensional parameter space. An analysis of the model provides insight into which parameters are responsible for generating a rich variety of diverse vocalizations, and what the physiological meaning of these parameters is. By recording the physiological motor instructions elicited by a spontaneously singing muted bird and computing the model on a Digital Signal Processor in real-time, we produce realistic synthetic vocalizations that replace the bird's own auditory feedback. In this way, we build a bio-prosthetic avian vocal organ driven by a freely behaving bird via its physiologically coded motor commands. Since it is based on a low-dimensional nonlinear mathematical model of the peripheral effector, the emulation of the motor behavior requires light computation, in such a way that our bio-prosthetic device can be implemented on a portable platform.

Brain Machine Interfaces (BMIs) decode motor instructions from neuro-physiological recordings and feed them to bio-mimetic effectors. Many applications achieve high accuracy on a limited number of tasks by applying statistical methods to these data to extract features corresponding to certain motor instructions. We built a bio-prosthetic avian vocal organ. The device is based on a low-dimensional mathematical model that accounts for the dynamics of the bird's vocal organ and robustly relates smooth paths in a physiologically meaningful parameter space to complex sequences of vocalizations. The two physiological motor gestures (sub-syringeal pressure and ventral syringeal muscular activity), are reconstructed from the bird's song, and the model is implemented on a portable Digital Signal Processor to produce synthetic birdsong when driven by a freely behaving bird via the sub-syringeal pressure gesture. This exemplifies the plausibility of a type of synthetic interfacing between the brain and a complex behavior. In this type of devices, the understanding of the bio-mechanics of the periphery is key to identifying a low dimensional physiological signal coding the motor instructions, therefore enabling real-time implementation at a low computational cost.

The anatomy of onomatopoeia

Virtually every human faculty engage with imitation. One of the most natural and unexplored objects for the study of the mimetic elements in language is the onomatopoeia, as it implies an imitative-driven transformation of a sound of nature into a word. Notably, simple sounds are transformed into complex strings of vowels and consonants, making difficult to identify what is acoustically preserved in this operation. In this work we propose a definition for vocal imitation by which sounds are transformed into the speech elements that minimize their spectral difference within the constraints of the vocal system. In order to test this definition, we use a computational model that allows recovering anatomical features of the vocal system from experimental sound data. We explore the vocal configurations that best reproduce non-speech sounds, like striking blows on a door or the sharp sounds generated by pressing on light switches or computer mouse buttons. From the anatomical point of view, the configurations obtained are readily associated with co-articulated consonants, and we show perceptual evidence that these consonants are positively associated with the original sounds. Moreover, the pairs vowel-consonant that compose these co-articulations correspond to the most stable syllables found in the knock and click onomatopoeias across languages, suggesting a mechanism by which vocal imitation naturally embeds single sounds into more complex speech structures. Other mimetic forces received extensive attention by the scientific community, such as cross-modal associations between speech and visual categories. The present approach helps building a global view of the mimetic forces acting on language and opens a new venue for a quantitative study of word formation in terms of vocal imitation.

Reconstruction of physiological instructions from Zebra finch song

We reconstruct the physiological parameters that control an avian vocal organ during birdsong production using recorded song. The procedure involves fitting the time dependent parameters of an avian vocal organ model. Computationally, the model is implemented as a dynamical system ruling the behavior of the oscillating labia that modulate the air flow during sound production, together with the equations describing the dynamics of pressure fluctuations in the vocal tract. We tested our procedure for Zebra finch song with, simultaneously recorded physiological parameters: air sac pressure and the electromyographic activity of the left and right ventral syringeal muscles. A comparison of the reconstructed instructions with measured physiological parameters during song shows a high degree of correlation. Integrating the model with reconstructed parameters leads to the synthesis of highly realistic songs.

A lumped mucosal wave model of the vocal folds revisited: recent extensions and oscillation hysteresis

This paper examines an updated version of a lumped mucosal wave model of the vocal fold oscillation during phonation. Threshold values of the subglottal pressure and the mean (DC) glottal airflow for the oscillation onset are determined. Depending on the nonlinear characteristics of the model, an oscillation hysteresis phenomenon may occur, with different values for the oscillation onset and offset threshold. The threshold values depend on the oscillation frequency, but the occurrence of the hysteresis is independent of it. The results are tested against pressure data collected from a mechanical replica of the vocal folds, and oral airflow data collected from speakers producing intervocalic /h/. In the human speech data, observed differences between voice onset and offset may be attributed to variations in voice pitch, with a very small or inexistent hysteresis phenomenon.

Peripheral mechanisms for vocal production in birds - differences and similarities to human speech and singing

Song production in songbirds is a model system for studying learned vocal behavior. As in humans, bird phonation involves three main motor systems (respiration, vocal organ and vocal tract). The avian respiratory mechanism uses pressure regulation in air sacs to ventilate a rigid lung. In songbirds sound is generated with two independently controlled sound sources, which reside in a uniquely avian vocal organ, the syrinx. However, the physical sound generation mechanism in the syrinx shows strong analogies to that in the human larynx, such that both can be characterized as myoelastic-aerodynamic sound sources. Similarities include active adduction and abduction, oscillating tissue masses which modulate flow rate through the organ and a layered structure of the oscillating tissue masses giving rise to complex viscoelastic properties. Differences in the functional morphology of the sound producing system between birds and humans require specific motor control patterns. The songbird vocal apparatus is adapted for high speed, suggesting that temporal patterns and fast modulation of sound features are important in acoustic communication. Rapid respiratory patterns determine the coarse temporal structure of song and maintain gas exchange even during very long songs. The respiratory system also contributes to the fine control of airflow. Muscular control of the vocal organ regulates airflow and acoustic features. The upper vocal tract of birds filters the sounds generated in the syrinx, and filter properties are actively adjusted. Nonlinear source-filter interactions may also play a role. The unique morphology and biomechanical system for sound production in birds presents an interesting model for exploring parallels in control mechanisms that give rise to highly convergent physical patterns of sound generation. More comparative work should provide a rich source for our understanding of the evolution of complex sound producing systems.

Physiologically driven avian vocal synthesizer

In this work, we build an electronic syrinx, i.e., a programmable electronic device capable of integrating biomechanical model equations for the avian vocal organ in order to synthesize song. This vocal prosthesis is controlled by the bird's neural instructions to respiratory and the syringeal motor systems, thus opening great potential for studying motor control and its modification by sensory feedback mechanisms. Furthermore, a well-functioning subject-controlled vocal prosthesis can lay the foundation for similar devices in humans and thus provide directly health-related data and procedures.

Biomechanical modeling of the three-dimensional aspects of human vocal fold dynamics

Human voice originates from the three-dimensional (3D) oscillations of the vocal folds. In previous studies, biomechanical properties of vocal fold tissues have been predicted by optimizing the parameters of simple two-mass-models to fit its dynamics to the high-speed imaging data from the clinic. However, only lateral and longitudinal displacements of the vocal folds were considered. To extend previous studies, a 3D mass-spring, cover-model is developed, which predicts the 3D vibrations of the entire medial surface of the vocal fold. The model consists of five mass planes arranged in vertical direction. Each plane contains five longitudinal, mass-spring, coupled oscillators. Feasibility of the model is assessed using a large body of dynamical data previously obtained from excised human larynx experiments, in vivo canine larynx experiments, physical models, and numerical models. Typical model output was found to be similar to existing findings. The resulting model enables visualization of the 3D dynamics of the human vocal folds during phonation for both symmetric and asymmetric vibrations.

Functional morphology of the sound-generating labia in the syrinx of two songbird species

In songbirds, two sound sources inside the syrinx are used to produce the primary sound. Laterally positioned labia are passively set into vibration, thus interrupting a passing air stream. Together with subsyringeal pressure, the size and tension of the labia determine the spectral characteristics of the primary sound. Very little is known about how the histological composition and morphology of the labia affect their function as sound generators. Here we related the size and microstructure of the labia to their acoustic function in two songbird species with different acoustic characteristics, the white-crowned sparrow and zebra finch. Histological serial sections of the syrinx and different staining techniques were used to identify collagen, elastin and hyaluronan as extracellular matrix components. The distribution and orientation of elastic fibers indicated that the labia in white-crowned sparrows are multi-layered structures, whereas they are more uniformly structured in the zebra finch. Collagen and hyaluronan were evenly distributed in both species. A multi-layered composition could give rise to complex viscoelastic properties of each sound source. We also measured labia size. Variability was found along the dorso-ventral axis in both species. Lateral asymmetry was identified in some individuals but not consistently at the species level. Different size between the left and right sound sources could provide a morphological basis for the acoustic specialization of each sound generator, but only in some individuals. The inconsistency of its presence requires the investigation of alternative explanations, e.g. differences in viscoelastic properties of the labia of the left and right syrinx. Furthermore, we identified attachments of syringeal muscles to the labia as well as to bronchial half rings and suggest a mechanism for their biomechanical function.

New perspectives on the physics of birdsong

In this work, we revisit the path that has been travelled during the last few years towards the modelling of the avian vocal organ, the syrinx, using numerical and theoretical techniques from bifurcation theory as analysing tools and present experimental support for the models. This fruitful perspective allowed the retracing of many acoustic features of syllables to intrinsic properties of the syrinx, thereby relocating the bird phonatory organ from the role of a mere vocal instrument of the nervous system to a central source of complex acoustical behaviour.

Beyond harmonic sounds in a simple model for birdsong production

In this work we present an analysis of the dynamics displayed by a simple bidimensional model of labial oscillations during birdsong production. We show that the same model capable of generating tonal sounds can present, for a wide range of parameters, solutions which are spectrally rich. The role of physiologically sensible parameters is discussed in each oscillatory regime, allowing us to interpret previously reported data.