Temperature induced syllable breaking unveils nonlinearly interacting timescales in birdsong motor pathway

Adaptive oscillators support Bayesian prediction in temporal processing

Humans excel at predictively synchronizing their behavior with external rhythms, as in dance or music performance. The neural processes underlying rhythmic inferences are debated: whether predictive perception relies on high-level generative models or whether it can readily be implemented locally by hard-coded intrinsic oscillators synchronizing to rhythmic input remains unclear and different underlying computational mechanisms have been proposed. Here we explore human perception for tone sequences with some temporal regularity at varying rates, but with considerable variability. Next, using a dynamical systems perspective, we successfully model the participants behavior using an adaptive frequency oscillator which adjusts its spontaneous frequency based on the rate of stimuli. This model better reflects human behavior than a canonical nonlinear oscillator and a predictive ramping model-both widely used for temporal estimation and prediction-and demonstrate that the classical distinction between absolute and relative computational mechanisms can be unified under this framework. In addition, we show that neural oscillators may constitute hard-coded physiological priors-in a Bayesian sense-that reduce temporal uncertainty and facilitate the predictive processing of noisy rhythms. Together, the results show that adaptive oscillators provide an elegant and biologically plausible means to subserve rhythmic inference, reconciling previously incompatible frameworks for temporal inferential processes.

Birdsong

Have your ever felt as happy as a lark, feathered your nest or taken someone under your wing? As we watch birds, we cannot help but be struck by their uncannily familiar behaviors - singing, nest building, caring for their young - to name just a few. Songbirds - the oscine suborder of perching birds that constitute roughly half (∼4,000) of all known avian species - are noted for the songs that males and sometimes both sexes in this group sing to court mates and defend territory from rivals. Birdsongs contain several to many acoustically distinct syllables, typically organized into a stereotyped phrase, and span the same audio bandwidth that we exploit for speech and music, making them easy for us to hear and appreciate. Consequently, eavesdropping humans long ago detected the most striking parallel between songbirds and humans: juvenile songbirds learn to sing in a manner similar to a child learning to speak.

Forebrain nuclei linked to woodpecker territorial drum displays mirror those that enable vocal learning in songbirds

Vocal learning is thought to have evolved in 3 orders of birds (songbirds, parrots, and hummingbirds), with each showing similar brain regions that have comparable gene expression specializations relative to the surrounding forebrain motor circuitry. Here, we searched for signatures of these same gene expression specializations in previously uncharacterized brains of 7 assumed vocal non-learning bird lineages across the early branches of the avian family tree. Our findings using a conserved marker for the song system found little evidence of specializations in these taxa, except for woodpeckers. Instead, woodpeckers possessed forebrain regions that were anatomically similar to the pallial song nuclei of vocal learning birds. Field studies of free-living downy woodpeckers revealed that these brain nuclei showed increased expression of immediate early genes (IEGs) when males produce their iconic drum displays, the elaborate bill-hammering behavior that individuals use to compete for territories, much like birdsong. However, these specialized areas did not show increased IEG expression with vocalization or flight. We further confirmed that other woodpecker species contain these brain nuclei, suggesting that these brain regions are a common feature of the woodpecker brain. We therefore hypothesize that ancient forebrain nuclei for refined motor control may have given rise to not only the song control systems of vocal learning birds, but also the drumming system of woodpeckers.

Vocal learning is thought to have evolved in three orders of birds (songbirds, parrots, and hummingbirds). This study shows that woodpeckers have evolved a set of brain nuclei to mediate their drum displays, and these regions closely mirror those that underlie song learning in songbirds.

Using focal cooling to link neural dynamics and behavior

Establishing a causal link between neural function and behavioral output has remained a challenging problem. Commonly used perturbation techniques enable unprecedented control over intrinsic activity patterns and can effectively identify crucial circuit elements important for specific behaviors. However, these approaches may severely disrupt activity, precluding an investigation into the behavioral relevance of moment-to-moment neural dynamics within a specified brain region. Here we discuss the application of mild focal cooling to slow down intrinsic neural circuit activity while preserving its overall structure. Using network modeling and examples from multiple species, we highlight the power and versatility of focal cooling for understanding how neural dynamics control behavior and argue for its wider adoption within the systems neuroscience community.

A Functionally and Anatomically Bipartite Vocal Pattern Generator in the Rat Brain Stem

The mammalian vocal pattern generator is situated in the brainstem but its exact structure is debated. We mapped these circuits in rats by cooling and microstimulation. Local cooling disrupted call production above an anterior and a posterior brainstem position. Anterior cooling affected predominantly high-frequency calls, whereas posterior cooling affected low-frequency calls. Electrical microstimulation of the anterior part led to modulated high-frequency calls, whereas microstimulation of the posterior part led to flat, low-frequency calls. At intermediate positions cooling did not affect calls and stimulation did not elicit calls. The anterior region corresponds to a subsection of the parvicellular reticular formation that we term the vocalization parvicellular reticular formation (VoPaRt). The posterior vocalization sites coincide with the nucleus retroambiguus (NRA). VoPaRt and NRA neurons were very small and the VoPaRt was highly myelinated, suggestive of high-speed processing. Our data suggest an anatomically and functionally bipartite vocal pattern generator.

The neurobiology of innate and learned vocalizations in rodents and songbirds

Vocalizations are an important medium for sexual and social signaling in mammals and birds. In most mammals other than humans, vocalizations are specified by innate mechanisms and develop normally in the absence of auditory experience. By contrast, juvenile songbirds memorize and copy the songs of adult tutors, a process with many parallels to human speech learning. Despite the centrality of vocal learning to human speech, vocal production in humans as well as in songbirds exploits ancestral circuitry for innate vocalizations, and effective vocal communication depends on the fluent blending of innate and learned elements. This review covers recent advances in our understanding of central mechanisms for learned and innate vocalizations in birds and mice, including brainstem mechanisms that help to 'gate' vocalizations on or off, cortical involvement in learned and innate vocalizations, and the delineation of circuits that evaluate and reinforce song performance to facilitate vocal learning.

Manipulations of inhibition in cortical circuitry differentially affect spectral and temporal features of Bengalese finch song

The interplay between inhibition and excitation can regulate behavioral expression and control, including the expression of communicative behaviors like birdsong. Computational models postulate varying degrees to which inhibition within vocal motor circuitry influences birdsong, but few studies have tested these models by manipulating inhibition. Here we enhanced and attenuated inhibition in the cortical nucleus HVC (used as proper name) of Bengalese finches (Lonchura striata var. domestica). Enhancement of inhibition (with muscimol) in HVC dose-dependently reduced the amount of song produced. Infusions of higher concentrations of muscimol caused some birds to produce spectrally degraded songs, whereas infusions of lower doses of muscimol led to the production of relatively normal (nondegraded) songs. However, the spectral and temporal structures of these nondegraded songs were significantly different from songs produced under control conditions. In particular, muscimol infusions decreased the frequency and amplitude of syllables, increased various measures of acoustic entropy, and increased the variability of syllable structure. Muscimol also increased sequence durations and the variability of syllable timing and syllable sequencing. Attenuation of inhibition (with bicuculline) in HVC led to changes to song distinct from and often opposite to enhancing inhibition. For example, in contrast to muscimol, bicuculline infusions increased syllable amplitude, frequency, and duration and decreased the variability of acoustic features. However, like muscimol, bicuculline increased the variability of syllable sequencing. These data highlight the importance of inhibition to the production of stereotyped vocalizations and demonstrate that changes to neural dynamics within cortical circuitry can differentially affect spectral and temporal features of song.NEW & NOTEWORTHY We reveal that manipulations of inhibition in the cortical nucleus HVC affect the structure, timing, and sequencing of syllables in Bengalese finch song. Enhancing and blocking inhibition led to opposite changes to the acoustic structure and timing of vocalizations, but both caused similar changes to vocal sequencing. These data provide support for computational models of song control but also motivate refinement of existing models to account for differential effects on syllable structure, timing, and sequencing.

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?'

The coupling between auditory and motor cortices is rate-restricted: Evidence for an intrinsic speech-motor rhythm

The relation between perception and action remains a fundamental question for neuroscience. In the context of speech, existing data suggest an interaction between auditory and speech-motor cortices, but the underlying mechanisms remain incompletely characterized. We fill a basic gap in our understanding of the sensorimotor processing of speech by examining the synchronization between auditory and speech-motor regions over different speech rates, a fundamental parameter delimiting successful perception. First, using magnetoencephalography, we measure synchronization between auditory and speech-motor regions while participants listen to syllables at various rates. We show, surprisingly, that auditory-motor synchrony is significant only over a restricted range and is enhanced at ~4.5 Hz, a value compatible with the mean syllable rate across languages. Second, neural modeling reveals that this modulated coupling plausibly emerges as a consequence of the underlying neural architecture. The findings suggest that the temporal patterns of speech emerge as a consequence of the intrinsic rhythms of cortical areas.

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.

Temperature manipulation of neuronal dynamics in a forebrain motor control nucleus

Different neuronal types within brain motor areas contribute to the generation of complex motor behaviors. A widely studied songbird forebrain nucleus (HVC) has been recognized as fundamental in shaping the precise timing characteristics of birdsong. This is based, among other evidence, on the stretching and the “breaking” of song structure when HVC is cooled. However, little is known about the temperature effects that take place in its neurons. To address this, we investigated the dynamics of HVC both experimentally and computationally. We developed a technique where simultaneous electrophysiological recordings were performed during temperature manipulation of HVC. We recorded spontaneous activity and found three effects: widening of the spike shape, decrease of the firing rate and change in the interspike interval distribution. All these effects could be explained with a detailed conductance based model of all the neurons present in HVC. Temperature dependence of the ionic channel time constants explained the first effect, while the second was based in the changes of the maximal conductance using single synaptic excitatory inputs. The last phenomenon, only emerged after introducing a more realistic synaptic input to the inhibitory interneurons. Two timescales were present in the interspike distributions. The behavior of one timescale was reproduced with different input balances received form the excitatory neurons, whereas the other, which disappears with cooling, could not be found assuming poissonian synaptic inputs. Furthermore, the computational model shows that the bursting of the excitatory neurons arises naturally at normal brain temperature and that they have an intrinsic delay at low temperatures. The same effect occurs at single synapses, which may explain song stretching. These findings shed light on the temperature dependence of neuronal dynamics and present a comprehensive framework to study neuronal connectivity. This study, which is based on intrinsic neuronal characteristics, may help to understand emergent behavioral changes.

The study of the neuronal mechanisms that give rise to the complex behavior of singing in birds has been hotly debated lately. Many models have been tested and novel tools have been developed to try to understand the role of a key brain nucleus in the song pathway: HVC. It is believed that it is highly responsible for generating the precise timing of songs, and this has been tested by manipulating it with temperature. Results showed that cooling can stretch, but that it can also restructure or “break” the song syllables. However, single neuronal mechanisms are not yet described. To better understand this, we cooled HVC in canaries and measured spontaneous activity electrophysiologically. We found three effects: spike shape widening, spike rate reduction and changes in inter-spike-interval (ISI) distributions. To explain them, we built a computational model with a detailed description of ion channel conductances and temperature dependency. We could explain the first effect with a single neuron model. The second, could be explained adding single synapses. Finally, we showed similar ISI modifications of one of the timescales present by means of multiple stochastic inputs. In addition, we found that excitatory neurons show natural bursting behavior at normal brain temperatures and that synaptic delays are the main candidates to explain song stretching at low temperatures.

Breathtaking Songs: Coordinating the Neural Circuits for Breathing and Singing

The vocal behavior of birds is remarkable for its diversity, and songs can feature elaborate characteristics such as long duration, rapid temporal pattern, and broad frequency range. The respiratory system plays a central role in generating the complex song patterns that must be integrated with its life-sustaining functions. Here, we explore how precise coordination between the neural circuits for breathing and singing is fundamental to production of these remarkable behaviors.

Rhythmic Continuous-Time Coding in the Songbird Analog of Vocal Motor Cortex

Songbirds learn and produce complex sequences of vocal gestures. Adult birdsong requires premotor nucleus HVC, in which projection neurons (PNs) burst sparsely at stereotyped times in the song. It has been hypothesized that PN bursts, as a population, form a continuous sequence, while a different model of HVC function proposes that both HVC PN and interneuron activity is tightly organized around motor gestures. Using a large dataset of PNs and interneurons recorded in singing birds, we test several predictions of these models. We find that PN bursts in adult birds are continuously and nearly uniformly distributed throughout song. However, we also find that PN and interneuron firing rates exhibit significant 10-Hz rhythmicity locked to song syllables, peaking prior to syllable onsets and suppressed prior to offsets-a pattern that predominates PN and interneuron activity in HVC during early stages of vocal learning.

From perception to action in songbird production: dynamics of a whole loop

Birdsong emerges when a set of highly interconnected brain areas manage to generate a complex output. This consists of precise respiratory rhythms as well as motor instructions to control the vocal organ configuration. In this way, during birdsong production, dedicated cortical areas interact with life-supporting ones in the brainstem, such as the respiratory nuclei. We discuss an integrative view of this interaction together with a widely accepted "top-down" representation of the song system. We also show that a description of this neural network in terms of dynamical systems allows to explore songbird production and processing by generating testable predictions.

Rhythmic syllable-related activity in a songbird motor thalamic nucleus necessary for learned vocalizations

Birdsong is a complex behavior that exhibits hierarchical organization. While the representation of singing behavior and its hierarchical organization has been studied in some detail in avian cortical premotor circuits, our understanding of the role of the thalamus in adult birdsong is incomplete. Using a combination of behavioral and electrophysiological studies, we seek to expand on earlier work showing that the thalamic nucleus Uvaeformis (Uva) is necessary for the production of stereotyped, adult song in zebra finch (Taeniopygia guttata). We confirm that complete bilateral lesions of Uva abolish singing in the ‘directed’ social context, but find that in the ‘undirected’ social context, such lesions result in highly variable vocalizations similar to early babbling song in juvenile birds. Recordings of neural activity in Uva reveal strong syllable-related modulation, maximally active prior to syllable onsets and minimally active prior to syllable offsets. Furthermore, both song and Uva activity exhibit a pronounced coherent modulation at 10Hz—a pattern observed in downstream premotor areas in adult and, even more prominently, in juvenile birds. These findings are broadly consistent with the idea that Uva is critical in the sequential activation of behavioral modules in HVC.

EM connectomics reveals axonal target variation in a sequence-generating network

The sequential activation of neurons has been observed in various areas of the brain, but in no case is the underlying network structure well understood. Here we examined the circuit anatomy of zebra finch HVC, a cortical region that generates sequences underlying the temporal progression of the song. We combined serial block-face electron microscopy with light microscopy to determine the cell types targeted by HVC(RA) neurons, which control song timing. Close to their soma, axons almost exclusively targeted inhibitory interneurons, consistent with what had been found with electrical recordings from pairs of cells. Conversely, far from the soma the targets were mostly other excitatory neurons, about half of these being other HVC(RA) cells. Both observations are consistent with the notion that the neural sequences that pace the song are generated by global synaptic chains in HVC embedded within local inhibitory networks.

Neural mechanisms of vocal imitation: The role of sleep replay in shaping mirror neurons

Learning by imitation involves not only perceiving another individual's action to copy it, but also the formation of a memory trace in order to gradually establish a correspondence between the sensory and motor codes, which represent this action through sensorimotor experience. Memory and sensorimotor processes are closely intertwined. Mirror neurons, which fire both when the same action is performed or perceived, have received considerable attention in the context of imitation. An influential view of memory processes considers that the consolidation of newly acquired information or skills involves an active offline reprocessing of memories during sleep within the neuronal networks that were initially used for encoding. Here, we review the recent advances in the field of mirror neurons and offline processes in the songbird. We further propose a theoretical framework that could establish the neurobiological foundations of sensorimotor learning by imitation. We propose that the reactivation of neuronal assemblies during offline periods contributes to the integration of sensory feedback information and the establishment of sensorimotor mirroring activity at the neuronal level.

Temperature Manipulation in Songbird Brain Implicates the Premotor Nucleus HVC in Birdsong Syntax

Variable motor sequences of animals are often structured and can be described by probabilistic transition rules between action elements. Examples include the songs of many songbird species such as the Bengalese finch, which consist of stereotypical syllables sequenced according to probabilistic rules (song syntax). The neural mechanisms behind such rules are poorly understood. Here, we investigate where the song syntax is encoded in the brain of the Bengalese finch by rapidly and reversibly manipulating the temperature in the song production pathway. Cooling the premotor nucleus HVC (proper name) slows down the song tempo, consistent with the idea that HVC controls moment-to-moment timings of acoustic features in the syllables. More importantly, cooling HVC alters the transition probabilities between syllables. Cooling HVC reduces the number of repetitions of long-repeated syllables and increases the randomness of syllable sequences. In contrast, cooling the downstream motor area RA (robust nucleus of the acropallium), which is critical for singing, does not affect the song syntax. Unilateral cooling of HVC shows that control of syllables is mostly lateralized to the left HVC, whereas transition probabilities between the syllables can be affected by cooling HVC in either hemisphere to varying degrees. These results show that HVC is a key site for encoding song syntax in the Bengalese finch. HVC is thus involved both in encoding timings within syllables and in sequencing probabilistic transitions between syllables. Our finding suggests that probabilistic selections and fine-grained timings of action elements can be integrated within the same neural circuits.SIGNIFICANCE STATEMENT Many animal behaviors such as birdsong consist of variable sequences of discrete actions. Where and how the probabilistic rules of such sequences are encoded in the brain is poorly understood. We locally and reversibly cooled brain areas in songbirds during singing. Mild cooling of area HVC in the Bengalese finch brain-a premotor area homologous to the mammalian premotor cortex-alters the statistics of the syllable sequences, suggesting that HVC is critical for birdsong sequences. HVC is also known for controlling moment-to-moment timings within syllables. Our results show that timing and probabilistic sequencing of actions can share the same neural circuits in local brain areas.

An integrated model for motor control of song in Serinus canaria

Birdsong is a learned motor behavior controlled by an interconnected structure of neural nuclei. This pathway is bilaterally organized, with anatomically indistinguishable structures in each brain hemisphere. In this work, we present a computational model whose variables are the average activities of different neural nuclei of the song system of oscine birds. Two of the variables are linked to the air sac pressure and the tension of the labia during canary song production. We show that these time dependent gestures are capable of driving a model of the vocal organ to synthesize realistic canary like songs.

A Distributed Recurrent Network Contributes to Temporally Precise Vocalizations

How do forebrain and brainstem circuits interact to produce temporally precise and reproducible behaviors? Birdsong is an elaborate, temporally precise, and stereotyped vocal behavior controlled by a network of forebrain and brainstem nuclei. An influential idea is that song premotor neurons in a forebrain nucleus (HVC) form a synaptic chain that dictates song timing in a top-down manner. Here we combine physiological, dynamical, and computational methods to show that song timing is not generated solely by a mechanism localized to HVC but instead is the product of a distributed and recurrent synaptic network spanning the forebrain and brainstem, of which HVC is a component.

"Bird Song Metronomics": Isochronous Organization of Zebra Finch Song Rhythm

The human capacity for speech and vocal music depends on vocal imitation. Songbirds, in contrast to non-human primates, share this vocal production learning with humans. The process through which birds and humans learn many of their vocalizations as well as the underlying neural system exhibit a number of striking parallels and have been widely researched. In contrast, rhythm, a key feature of language, and music, has received surprisingly little attention in songbirds. Investigating temporal periodicity in bird song has the potential to inform the relationship between neural mechanisms and behavioral output and can also provide insight into the biology and evolution of musicality. Here we present a method to analyze birdsong for an underlying rhythmic regularity. Using the intervals from one note onset to the next as input, we found for each bird an isochronous sequence of time stamps, a “signal-derived pulse,” or pulse^S, of which a subset aligned with all note onsets of the bird's song. Fourier analysis corroborated these results. To determine whether this finding was just a byproduct of the duration of notes and intervals typical for zebra finches but not dependent on the individual duration of elements and the sequence in which they are sung, we compared natural songs to models of artificial songs. Note onsets of natural song deviated from the pulse^S significantly less than those of artificial songs with randomized note and gap durations. Thus, male zebra finch song has the regularity required for a listener to extract a perceived pulse (pulse^P), as yet untested. Strikingly, in our study, pulses^S that best fit note onsets often also coincided with the transitions between sub-note elements within complex notes, corresponding to neuromuscular gestures. Gesture durations often equaled one or more pulse^S periods. This suggests that gesture duration constitutes the basic element of the temporal hierarchy of zebra finch song rhythm, an interesting parallel to the hierarchically structured components of regular rhythms in human music.

A circular model for song motor control in Serinus canaria

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.

Independent premotor encoding of the sequence and structure of birdsong in avian cortex

How the brain coordinates rapid sequences of learned behavior, such as human speech, remains a fundamental problem in neuroscience. Birdsong is a model of such behavior, which is learned and controlled by a neural circuit that spans avian cortex, basal ganglia, and thalamus. The songs of adult male zebra finches (Taeniopygia guttata), produced as rapid sequences of vocal gestures (syllables), are encoded by the cortical premotor region HVC (proper name). While the motor encoding of song within HVC has traditionally been viewed as unitary and distributed, we used an ablation technique to ask whether the sequence and structure of song are processed independently within HVC. Results revealed a functional topography across the medial-lateral axis of HVC. Bilateral ablation of medial HVC induced a positive disruption of song (increase in atypical syllable sequences), whereas bilateral ablation of lateral HVC induced a negative disruption (omission of individual syllables). Bilateral ablation of central HVC either had no effect on song or induced syllable omission, similar to lateral HVC ablation. We then investigated HVC connectivity and found parallel afferent and efferent pathways that transit medial and lateral HVC and converge at vocal motor cortex. In light of recent evidence that syntactic and lexical components of human speech are processed independently by neighboring regions of cortex (Menenti et al., 2012), our demonstration of anatomically distinct pathways that differentially process the sequence and structure of birdsong in parallel suggests that the vertebrate brain relies on a common approach to encode rapid sequences of vocal gestures.

Parameter estimation, nonlinearity, and Occam's razor

Nonlinear systems are capable of displaying complex behavior even if this is the result of a small number of interacting time scales. A widely studied case is when complex dynamics emerges out of a nonlinear system being forced by a simple harmonic function. In order to identify if a recorded time series is the result of a nonlinear system responding to a simpler forcing, we develop a discrete nonlinear transformation for time series based on synchronization techniques. This allows a parameter estimation procedure which simultaneously searches for a good fit of the recorded data, and small complexity of a fluctuating driving parameter. We illustrate this procedure using data from respiratory patterns during birdsong production.

The singer and the song: the neuromechanics of avian sound production

Song is crucial to songbirds for establishing territories and signaling genetic quality and an important driver in speciation. Songbirds also have become a widely used experimental model system to study the neural basis of vocal learning, a form of imitation learning with strong parallels to human speech learning. While there is a strong focus on central processing of song production, we still have limited insights into the functional output of the motor neural circuits. This review focuses on recent developments in motor control, biomechanics and feedback mechanisms of sound production in songbirds.

Two neural streams, one voice: pathways for theme and variation in the songbird brain

Birdsong offers a unique model system to understand how a developing brain - once given a set of purely acoustic targets - teaches itself the vocal-tract gestures necessary to imitate those sounds. Like human infants, to juvenile male zebra finches (Taeniopygia guttata) falls the burden of initiating the vocal-motor learning of adult sounds. In both species, adult caregivers provide only a set of sounds to be imitated, with little or no information about the vocal-tract gestures used to produce the sounds. Here, we focus on the central control of birdsong and review the recent discovery that zebra finch song is under dual premotor control. Distinct forebrain pathways for structured (theme) and unstructured (variation) singing not only raise new questions about mechanisms of sensory-motor integration, but also provide a fascinating new research opportunity. A cortical locus for a motor memory of the learned song is now firmly established, meaning that anatomical, physiological, and computational approaches are poised to reveal the neural mechanisms used by the brain to compose the songs of birds.

Many parameter sets in a multicompartment model oscillator are robust to temperature perturbations

Neurons in cold-blooded animals remarkably maintain their function over a wide range of temperatures, even though the rates of many cellular processes increase twofold, threefold, or many-fold for each 10°C increase in temperature. Moreover, the kinetics of ion channels, maximal conductances, and Ca(2+) buffering each have independent temperature sensitivities, suggesting that the balance of biological parameters can be disturbed by even modest temperature changes. In stomatogastric ganglia of the crab Cancer borealis, the duty cycle of the bursting pacemaker kernel is highly robust between 7 and 23°C (Rinberg et al., 2013). We examined how this might be achieved in a detailed conductance-based model in which exponential temperature sensitivities were given by Q10 parameters. We assessed the temperature robustness of this model across 125,000 random sets of Q10 parameters. To examine how robustness might be achieved across a variable population of animals, we repeated this analysis across six sets of maximal conductance parameters that produced similar activity at 11°C. Many permissible combinations of maximal conductance and Q10 parameters were found over broad regions of parameter space and relatively few correlations among Q10s were observed across successful parameter sets. A significant portion of Q10 sets worked for at least 3 of the 6 maximal conductance sets (∼11.1%). Nonetheless, no Q10 set produced robust function across all six maximal conductance sets, suggesting that maximal conductance parameters critically contribute to temperature robustness. Overall, these results provide insight into principles of temperature robustness in neuronal oscillators.

Models of vocal learning in the songbird: Historical frameworks and the stabilizing critic

Birdsong is a form of sensorimotor learning that involves a mirror-like system that activates with both song hearing and production. Early models of song learning, based on behavioral measures, identified key features of vocal plasticity, such as the requirements for memorization of a tutor song and auditory feedback during song practice. The concept of a comparator, which compares the memory of the tutor song to auditory feedback, featured prominently. Later models focused on linking anatomically-defined neural modules to behavioral concepts, such as the comparator. Exploiting the anatomical modularity of the songbird brain, localized lesions illuminated mechanisms of the neural song system. More recent models have integrated neuronal mechanisms identified in other systems with observations in songbirds. While these models explain multiple aspects of song learning, they must incorporate computational elements based on unknown biological mechanisms to bridge the motor-to-sensory delay and/or transform motor signals into the sensory domain. Here, I introduce the stabilizing critic hypothesis, which enables sensorimotor learning by (1) placing a purely sensory comparator afferent of the song system and (2) endowing song system disinhibitory interneuron networks with the capacity both to bridge the motor-sensory delay through prolonged bursting and to stabilize song segments selectively based on the comparator signal. These proposed networks stabilize an otherwise variable signal generated by both putative mirror neurons and a cortical-basal ganglia-thalamic loop. This stabilized signal then temporally converges with a matched premotor signal in the efferent song motor cortex, promoting spike-timing-dependent plasticity in the premotor circuitry and behavioral song learning.

The respiratory-vocal system of songbirds: anatomy, physiology, and neural control

This wide-ranging review presents an overview of the respiratory-vocal system in songbirds, which are the only other vertebrate group known to display a degree of respiratory control during song rivalling that of humans during speech; this despite the fact that the peripheral components of both the respiratory and vocal systems differ substantially in the two groups. We first provide a brief description of these peripheral components in songbirds (lungs, air sacs and respiratory muscles, vocal organ (syrinx), upper vocal tract) and then proceed to a review of the organization of central respiratory-related neurons in the spinal cord and brainstem, the latter having an organization fundamentally similar to that of the ventral respiratory group of mammals. The second half of the review describes the nature of the motor commands generated in a specialized "cortical" song control circuit and how these might engage brainstem respiratory networks to shape the temporal structure of song. We also discuss a bilaterally projecting "respiratory-thalamic" pathway that links the respiratory system to "cortical" song control nuclei. This necessary pathway for song originates in the brainstem's primary inspiratory center and is hypothesized to play a vital role in synchronizing song motor commands both within and across hemispheres.

Evidence and control of bifurcations in a respiratory system

We studied the pressure patterns used by domestic canaries in the production of birdsong. Acoustically different sound elements ("syllables") were generated by qualitatively different pressure gestures. We found that some ubiquitous transitions between syllables can be interpreted as bifurcations of a low dimensional dynamical system. We interpreted these results as evidence supporting a model in which different timescales interact nonlinearly.