A neural circuit mechanism for regulating vocal variability during song learning in zebra finches

The central role of the individual in the history of brains

Every species' brain, body and behavior is shaped by the contingencies of their evolutionary history; these exert pressures that change their developmental trajectories. There is, however, another set of contingencies that shape us and other animals: those that occur during a lifetime. In this perspective piece, we show how these two histories are intertwined by focusing on the individual. We suggest that organisms--their brains and behaviors--are not solely the developmental products of genes and neural circuitry but individual centers of action unfolding in time. To unpack this idea, we first emphasize the importance of variation and the central role of the individual in biology. We then go over "errors in time" that we often make when comparing development across species. Next, we reveal how an individual's development is a process rather than a product by presenting a set of case studies. These show developmental trajectories as emerging in the contexts of the "the actual now" and "the presence of the past". Our consideration reveals that individuals are slippery-they are never static; they are a set of on-going, creative activities. In light of this, it seems that taking individual development seriously is essential if we aspire to make meaningful comparisons of neural circuits and behavior within and across species.

Unsupervised restoration of a complex learned behavior after large-scale neuronal perturbation

Reliable execution of precise behaviors requires that brain circuits are resilient to variations in neuronal dynamics. Genetic perturbation of the majority of excitatory neurons in HVC, a brain region involved in song production, in adult songbirds with stereotypical songs triggered severe degradation of the song. The song fully recovered within 2 weeks, and substantial improvement occurred even when animals were prevented from singing during the recovery period, indicating that offline mechanisms enable recovery in an unsupervised manner. Song restoration was accompanied by increased excitatory synaptic input to neighboring, unmanipulated neurons in the same brain region. A model inspired by the behavioral and electrophysiological findings suggests that unsupervised single-cell and population-level homeostatic plasticity rules can support the functional restoration after large-scale disruption of networks that implement sequential dynamics. These observations suggest the existence of cellular and systems-level restorative mechanisms that ensure behavioral resilience.

Generating variability from motor primitives during infant locomotor development

Motor variability is a fundamental feature of developing systems allowing motor exploration and learning. In human infants, leg movements involve a small number of basic coordination patterns called locomotor primitives, but whether and when motor variability could emerge from these primitives remains unknown. Here we longitudinally followed 18 infants on 2-3 time points between birth (~4 days old) and walking onset (~14 months old) and recorded the activity of their leg muscles during locomotor or rhythmic movements. Using unsupervised machine learning, we show that the structure of trial-to-trial variability changes during early development. In the neonatal period, infants own a minimal number of motor primitives but generate a maximal motor variability across trials thanks to variable activations of these primitives. A few months later, toddlers generate significantly less variability despite the existence of more primitives due to more regularity within their activation. These results suggest that human neonates initiate motor exploration as soon as birth by variably activating a few basic locomotor primitives that later fraction and become more consistently activated by the motor system.

Behavioral decomposition reveals rich encoding structure employed across neocortex in rats

The cortical population code is pervaded by activity patterns evoked by movement, but it remains largely unknown how such signals relate to natural behavior or how they might support processing in sensory cortices where they have been observed. To address this we compared high-density neural recordings across four cortical regions (visual, auditory, somatosensory, motor) in relation to sensory modulation, posture, movement, and ethograms of freely foraging male rats. Momentary actions, such as rearing or turning, were represented ubiquitously and could be decoded from all sampled structures. However, more elementary and continuous features, such as pose and movement, followed region-specific organization, with neurons in visual and auditory cortices preferentially encoding mutually distinct head-orienting features in world-referenced coordinates, and somatosensory and motor cortices principally encoding the trunk and head in egocentric coordinates. The tuning properties of synaptically coupled cells also exhibited connection patterns suggestive of area-specific uses of pose and movement signals, particularly in visual and auditory regions. Together, our results indicate that ongoing behavior is encoded at multiple levels throughout the dorsal cortex, and that low-level features are differentially utilized by different regions to serve locally relevant computations.

Neural circuit-wide analysis of changes to gene expression during deafening-induced birdsong destabilization

Sensory feedback is required for the stable execution of learned motor skills, and its loss can severely disrupt motor performance. The neural mechanisms that mediate sensorimotor stability have been extensively studied at systems and physiological levels, yet relatively little is known about how disruptions to sensory input alter the molecular properties of associated motor systems. Songbird courtship song, a model for skilled behavior, is a learned and highly structured vocalization that is destabilized following deafening. Here, we sought to determine how the loss of auditory feedback modifies gene expression and its coordination across the birdsong sensorimotor circuit. To facilitate this system-wide analysis of transcriptional responses, we developed a gene expression profiling approach that enables the construction of hundreds of spatially-defined RNA-sequencing libraries. Using this method, we found that deafening preferentially alters gene expression across birdsong neural circuitry relative to surrounding areas, particularly in premotor and striatal regions. Genes with altered expression are associated with synaptic transmission, neuronal spines, and neuromodulation and show a bias toward expression in glutamatergic neurons and Pvalb/Sst-class GABAergic interneurons. We also found that connected song regions exhibit correlations in gene expression that were reduced in deafened birds relative to hearing birds, suggesting that song destabilization alters the inter-region coordination of transcriptional states. Finally, lesioning LMAN, a forebrain afferent of RA required for deafening-induced song plasticity, had the largest effect on groups of genes that were also most affected by deafening. Combined, this integrated transcriptomics analysis demonstrates that the loss of peripheral sensory input drives a distributed gene expression response throughout associated sensorimotor neural circuitry and identifies specific candidate molecular and cellular mechanisms that support the stability and plasticity of learned motor skills.

Motor cortex analogue neurons in songbirds utilize Kv3 channels to generate ultranarrow spikes

Complex motor skills in vertebrates require specialized upper motor neurons with precise action potential (AP) firing. To examine how diverse populations of upper motor neurons subserve distinct functions and the specific repertoire of ion channels involved, we conducted a thorough study of the excitability of upper motor neurons controlling somatic motor function in the zebra finch. We found that robustus arcopallialis projection neurons (RAPNs), key command neurons for song production, exhibit ultranarrow spikes and higher firing rates compared to neurons controlling non-vocal somatic motor functions (dorsal intermediate arcopallium [AId] neurons). Pharmacological and molecular data indicate that this striking difference is associated with the higher expression in RAPNs of high threshold, fast-activating voltage-gated Kv3 channels, that likely contain Kv3.1 (KCNC1) subunits. The spike waveform and Kv3.1 expression in RAPNs mirror properties of Betz cells, specialized upper motor neurons involved in fine digit control in humans and other primates but absent in rodents. Our study thus provides evidence that songbirds and primates have convergently evolved the use of Kv3.1 to ensure precise, rapid AP firing in upper motor neurons controlling fast and complex motor skills.

Vagus nerve stimulation drives selective circuit modulation through cholinergic reinforcement

Vagus nerve stimulation (VNS) is a neuromodulation therapy for a broad and expanding set of neurologic conditions. However, the mechanism through which VNS influences central nervous system circuitry is not well described, limiting therapeutic optimization. VNS leads to widespread brain activation, but the effects on behavior are remarkably specific, indicating plasticity unique to behaviorally engaged neural circuits. To understand how VNS can lead to specific circuit modulation, we leveraged genetic tools including optogenetics and in vivo calcium imaging in mice learning a skilled reach task. We find that VNS enhances skilled motor learning in healthy animals via a cholinergic reinforcement mechanism, producing a rapid consolidation of an expert reach trajectory. In primary motor cortex (M1), VNS drives precise temporal modulation of neurons that respond to behavioral outcome. This suggests that VNS may accelerate motor refinement in M1 via cholinergic signaling, opening new avenues for optimizing VNS to target specific disease-relevant circuitry.

Responses to Song Playback Differ in Sleeping versus Anesthetized Songbirds

Vocal learning in songbirds is mediated by a highly localized system of interconnected forebrain regions, including recurrent loops that traverse the cortex, basal ganglia, and thalamus. This brain-behavior system provides a powerful model for elucidating mechanisms of vocal learning, with implications for learning speech in human infants, as well as for advancing our understanding of skill learning in general. A long history of experiments in this area has tested neural responses to playback of different song stimuli in anesthetized birds at different stages of vocal development. These studies have demonstrated selectivity for different song types that provide neural signatures of learning. In contrast to the ease of obtaining responses to song playback in anesthetized birds, song-evoked responses in awake birds are greatly reduced or absent, indicating that behavioral state is an important determinant of neural responsivity. Song-evoked responses can be elicited during sleep as well as anesthesia, and the selectivity of responses to song playback in adult birds is highly similar between anesthetized and sleeping states, encouraging the idea that anesthesia and sleep are similar. In contrast to that idea, we report evidence that cortical responses to song playback in juvenile zebra finches (Taeniopygia guttata) differ greatly between sleep and urethane anesthesia. This finding indicates that behavioral states differ in sleep versus anesthesia and raises questions about relationships between developmental changes in sleep activity, selectivity for different song types, and the neural substrate for vocal learning.

Modelling learning in C. elegans chemosensory and locomotive circuitry for T-maze navigation

Recently, a new type of Caenorhabditis elegans associative learning was reported, where nematodes learn to reach a target arm in an empty T‐maze, after they have successfully located reward (food) in the same side arm of a similar, baited, training maze. Here, we present a simplified mathematical model of C. elegans chemosensory and locomotive circuitry that replicates C. elegans navigation in a T‐maze and predicts the underlying mechanisms generating maze learning. Based on known neural circuitry, the model circuit responds to food‐released chemical cues by modulating motor neuron activity that drives simulated locomotion. We show that, through modulation of interneuron activity, such a circuit can mediate maze learning by acquiring a turning bias, even after a single training session. Simulated nematode maze navigation during training conditions in food‐baited mazes and during testing conditions in empty mazes is validated by comparing simulated behaviour with new experimental video data, extracted through the implementation of a custom‐made maze tracking algorithm. Our work provides a mathematical framework for investigating the neural mechanisms underlying this novel learning behaviour in C. elegans. Model results predict neuronal components involved in maze and spatial learning and identify target neurons and potential neural mechanisms for future experimental investigations into this learning behaviour.

Resurgent Na+ currents promote ultrafast spiking in projection neurons that drive fine motor control

The underlying mechanisms that promote precise spiking in upper motor neurons controlling fine motor skills are not well understood. Here we report that projection neurons in the adult zebra finch song nucleus RA display robust high-frequency firing, ultra-narrow spike waveforms, superfast Na⁺ current inactivation kinetics, and large resurgent Na⁺ currents (I_NaR). These properties of songbird pallial motor neurons closely resemble those of specialized large pyramidal neurons in mammalian primary motor cortex. They emerge during the early phases of song development in males, but not females, coinciding with a complete switch of Na+ channel subunit expression from Navβ3 to Navβ4. Dynamic clamping and dialysis of Navβ4's C-terminal peptide into juvenile RA neurons provide evidence that Navβ4, and its associated I_NaR, promote neuronal excitability. We thus propose that I_NaR modulates the excitability of upper motor neurons that are required for the execution of fine motor skills.

Computational benefits of structural plasticity, illustrated in songbirds

The plasticity of nervous systems allows animals to quickly adapt to a changing environment. In particular, the structural plasticity of brain networks is often critical to the development of the central nervous system and the acquisition of complex behaviors. As an example, structural plasticity is central to the development of song-related brain circuits and may be critical for song acquisition in juvenile songbirds. Here, we review current evidences for structural plasticity and their significance from a computational point of view. We start by reviewing evidence for structural plasticity across species and categorizing them along the spatial axes as well as the along the time course during development. We introduce the vocal learning circuitry in zebra finches, as a useful example of structural plasticity, and use this specific case to explore the possible contributions of structural plasticity to computational models. Finally, we discuss current modeling studies incorporating structural plasticity and unexplored questions which are raised by such models.

Disengagement of Motor Cortex during Long-Term Learning Tracks the Performance Level of Learned Movements

Not all movements require the motor cortex for execution. Intriguingly, dependence on motor cortex of a given movement is not fixed, but instead can dynamically change over the course of long-term learning. For instance, rodent forelimb movements that initially require motor cortex can become independent of the motor cortex after an extended period of training. However, it remains unclear whether long-term neural changes rendering the motor cortex dispensable are a simple function of the training length. To address this issue, we trained mice (both male and female) to perform two distinct forelimb movements, forward versus downward reaches with a joystick, concomitantly over several weeks, and then compared the involvement of the motor cortex between the two movements. Most mice achieved different levels of motor performance between the two movements after long-term training. Of the two movements, the one that achieved higher trial-to-trial consistency (i.e., consistent-direction movement) was significantly less affected by inactivation of motor cortex than the other (i.e., variable-direction movement). Two-photon calcium imaging of motor cortical neurons revealed that the consistent-direction movement activates fewer neurons, producing weaker and less consistent population activity than the variable-direction movement. Together, the motor cortex was less engaged and less necessary for learned movements that achieved higher levels of consistency. Thus, the long-term reorganization of neural circuits that frees the motor cortex from the learned movement is not a mere function of training length. Rather, this reorganization tracks the level of motor performance that the animal achieves during training.SIGNIFICANCE STATEMENT Long-term training of a movement reshapes motor circuits, disengaging motor cortex potentially for automatized execution of the learned movement. Acquiring new motor skills often involves learning of multiple movements (e.g., forehand and backhand strokes when learning tennis), but different movements do not always improve at the same time nor reach the same level of proficiency. Here we showed that the involvement of motor cortex after long-term training differs between similar yet distinct movements that reached different levels of expertise. Motor cortex was less engaged and less necessary for the more proficient movement. Thus, disengagement of motor cortex is not a simple function of training time, but instead tracks the level of expertise of a learned movement.

Actor-critic reinforcement learning in the songbird

It feels rewarding to ace your opponent on match point. Here, we propose common mechanisms underlie reward and performance learning. First, when a singing bird unexpectedly hits the right note, its dopamine (DA) neurons are activated as when a thirsty monkey receives an unexpected juice reward. Second, these DA signals reinforce vocal variations much as they reinforce stimulus-response associations. Third, limbic inputs to DA neurons signal the predicted quality of song syllables much like they signal the predicted reward value of a place or a stimulus during foraging. Finally, songbirds may solve difficult problems in reinforcement learning - such as credit assignment and catastrophic forgetting - with node perturbation and consolidation of reinforced vocal patterns in motor cortical circuits. Consolidation occurs downstream of a canonical 'actor-critic' circuit motif that learns to maximize performance quality in essentially the same way it learns to maximize reward: by computing and learning from prediction errors.

Future Portrait of the Athletic Brain: Mechanistic Understanding of Human Sport Performance Via Animal Neurophysiology of Motor Behavior

Sport performances are often showcases of skilled motor control. Efforts to understand the neural processes subserving such movements may teach us about general principles of behavior, similarly to how studies on neurological patients have guided early work in cognitive neuroscience. While investigations on non-human animal models offer valuable information on the neural dynamics of skilled motor control that is still difficult to obtain from humans, sport sciences have paid relatively little attention to these mechanisms. Similarly, knowledge emerging from the study of sport performance could inspire innovative experiments in animal neurophysiology, but the latter has been only partially applied. Here, we advocate that fostering interactions between these two seemingly distant fields, i.e., animal neurophysiology and sport sciences, may lead to mutual benefits. For instance, recording and manipulating the activity from neurons of behaving animals offer a unique viewpoint on the computations for motor control, with potentially untapped relevance for motor skills development in athletes. To stimulate such transdisciplinary dialog, in the present article, we also discuss steps for the reverse translation of sport sciences findings to animal models and the evaluation of comparability between animal models of a given sport and athletes. In the final section of the article, we envision that some approaches developed for animal neurophysiology could translate to sport sciences anytime soon (e.g., advanced tracking methods) or in the future (e.g., novel brain stimulation techniques) and could be used to monitor and manipulate motor skills, with implications for human performance extending well beyond sport.

Synaptic mechanisms for motor variability in a feedforward network

Behavioral variability often arises from variable activity in the behavior-generating neural network. The synaptic mechanisms underlying this variability are poorly understood. We show that synaptic noise, in conjunction with weak feedforward excitation, generates variable motor output in the Aplysia feeding system. A command-like neuron (CBI-10) triggers rhythmic motor programs more variable than programs triggered by CBI-2. CBI-10 weakly excites a pivotal pattern-generating interneuron (B34) strongly activated by CBI-2. The activation properties of B34 substantially account for the degree of program variability. CBI-10- and CBI-2-induced EPSPs in B34 vary in amplitude across trials, suggesting that there is synaptic noise. Computational studies show that synaptic noise is required for program variability. Further, at network state transition points when synaptic conductance is low, maximum program variability is promoted by moderate noise levels. Thus, synaptic strength and noise act together in a nonlinear manner to determine the degree of variability within a feedforward network.

Acetylcholine acts on songbird premotor circuitry to invigorate vocal output

Acetylcholine is well-understood to enhance cortical sensory responses and perceptual sensitivity in aroused or attentive states. Yet little is known about cholinergic influences on motor cortical regions. Here we use the quantifiable nature of birdsong to investigate how acetylcholine modulates the cortical (pallial) premotor nucleus HVC and shapes vocal output. We found that dialyzing the cholinergic agonist carbachol into HVC increased the pitch, amplitude, tempo and stereotypy of song, similar to the natural invigoration of song that occurs when males direct their songs to females. These carbachol-induced effects were associated with increased neural activity in HVC and occurred independently of basal ganglia circuitry. Moreover, we discovered that the normal invigoration of female-directed song was also accompanied by increased HVC activity and was attenuated by blocking muscarinic acetylcholine receptors. These results indicate that, analogous to its influence on sensory systems, acetylcholine can act directly on cortical premotor circuitry to adaptively shape behavior.

Adaptive Regulation of Motor Variability

Trial-to-trial movement variability can both drive motor learning and interfere with expert performance, suggesting benefits of regulating it in context-specific ways. Here we address whether and how the brain regulates motor variability as a function of performance by training rats to execute ballistic forelimb movements for reward. Behavioral datasets comprising millions of trials revealed that motor variability is regulated by two distinct processes. A fast process modulates variability as a function of recent trial outcomes, increasing it when performance is poor and vice versa. A slower process tunes the gain of the fast process based on the uncertainty in the task's reward landscape. Simulations demonstrated that this regulation strategy optimizes reward accumulation over a wide range of time horizons, while also promoting learning. Our results uncover a sophisticated algorithm implemented by the brain to adaptively regulate motor variability to improve task performance. VIDEO ABSTRACT.

Failure to attune to language predicts autism in high risk infants

Young humans are typically sensitive to evolutionarily important aspects of information in the surrounding environment in a way that makes us thrive. Seeking to probe the putative disruptions of this process in infancy, I examined the statistical character of head movements in 52 9-10 mo-old infants, half at high familial risk (HR) for Autism Spectrum Disorders (ASD), who underwent an fMRI scan while listening to words spoken with alternating stress patterns on syllables. Relative to low risk (LR) infants, HR infants, in particular those showing the least rapid receptive language progress, had significantly lower noise-to-signal levels and increased symmetry. A comparison of patterns during a native language and a sleep scan revealed the most atypical ordering of signatures on the 3 tasks in a subset of HR infants, suggesting that the biological mechanism of language development is least acquisitive in those HR infants who go on to develop ASD in toddlerhood.

Interactions between motor exploration and reinforcement learning

Motor exploration, a trial-and-error process in search for better motor outcomes, is known to serve a critical role in motor learning. This is particularly relevant during reinforcement learning, where actions leading to a successful outcome are reinforced while unsuccessful actions are avoided. Although early on motor exploration is beneficial to finding the correct solution, maintaining high levels of exploration later in the learning process might be deleterious. Whether and how the level of exploration changes over the course of reinforcement learning, however, remains poorly understood. Here we evaluated temporal changes in motor exploration while healthy participants learned a reinforcement-based motor task. We defined exploration as the magnitude of trial-to-trial change in movements as a function of whether the preceding trial resulted in success or failure. Participants were required to find the optimal finger-pointing direction using binary feedback of success or failure. We found that the magnitude of exploration gradually increased over time when participants were learning the task. Conversely, exploration remained low in participants who were unable to correctly adjust their pointing direction. Interestingly, exploration remained elevated when participants underwent a second training session, which was associated with faster relearning. These results indicate that the motor system may flexibly upregulate the extent of exploration during reinforcement learning as if acquiring a specific strategy to facilitate subsequent learning. Also, our findings showed that exploration affects reinforcement learning and vice versa, indicating an interactive relationship between them. Reinforcement-based tasks could be used as primers to increase exploratory behavior leading to more efficient subsequent learning.NEW & NOTEWORTHY Motor exploration, the ability to search for the correct actions, is critical to learning motor skills. Despite this, whether and how the level of exploration changes over the course of training remains poorly understood. We showed that exploration increased and remained high throughout training of a reinforcement-based motor task. Interestingly, elevated exploration persisted and facilitated subsequent learning. These results suggest that the motor system upregulates exploration as if learning a strategy to facilitate subsequent learning.

Co-opting evo-devo concepts for new insights into mechanisms of behavioural diversity

We propose that insights from the field of evolutionary developmental biology (or 'evo-devo') provide a framework for an integrated understanding of the origins of behavioural diversity and its underlying mechanisms. Towards that goal, in this Commentary, we frame key questions in behavioural evolution in terms of molecular, cellular and network-level properties with a focus on the nervous system. In this way, we highlight how mechanistic properties central to evo-devo analyses - such as weak linkage, versatility, exploratory mechanisms, criticality, degeneracy, redundancy and modularity - affect neural circuit function and hence the range of behavioural variation that can be filtered by selection. We outline why comparative studies of molecular and neural systems throughout ontogeny will provide novel insights into diversity in neural circuits and behaviour.

Differential developmental changes in cortical representations of auditory-vocal stimuli in songbirds

Procedural skill learning requires iterative comparisons between feedback of self-generated motor output and a goal sensorimotor pattern. In juvenile songbirds, neural representations of both self-generated behaviors (each bird's own immature song) and the goal motor pattern (each bird's adult tutor song) are essential for vocal learning, yet little is known about how these behaviorally relevant stimuli are encoded. We made extracellular recordings during song playback in anesthetized juvenile and adult zebra finches ( Taeniopygia guttata) in adjacent cortical regions RA (robust nucleus of the arcopallium), AId (dorsal intermediate arcopallium), and RA cup, each of which is well situated to integrate auditory-vocal information: RA is a motor cortical region that drives vocal output, AId is an adjoining cortical region whose projections converge with basal ganglia loops for song learning in the dorsal thalamus, and RA cup surrounds RA and receives inputs from primary and secondary auditory cortex. We found strong developmental differences in neural selectivity within RA, but not in AId or RA cup. Juvenile RA neurons were broadly responsive to multiple songs but preferred juvenile over adult vocal sounds; in addition, spiking responses lacked consistent temporal patterning. By adulthood, RA neurons responded most strongly to each bird's own song with precisely timed spiking activity. In contrast, we observed a complete lack of song responsivity in both juvenile and adult AId, even though this region receives song-responsive inputs. A surprisingly large proportion of sites in RA cup of both juveniles and adults did not respond to song playback, and responsive sites showed little evidence of song selectivity. NEW & NOTEWORTHY Motor skill learning entails changes in selectivity for behaviorally relevant stimuli across cortical regions, yet the neural representation of these stimuli remains understudied. We investigated how information important for vocal learning in zebra finches is represented in regions analogous to infragranular layers of motor and auditory cortices during vs. after the developmentally regulated learning period. The results provide insight into how neurons in higher level stages of cortical processing represent stimuli important for motor skill learning.

Vocal practice regulates singing activity-dependent genes underlying age-independent vocal learning in songbirds

The development of highly complex vocal skill, like human language and bird songs, is underlain by learning. Vocal learning, even when occurring in adulthood, is thought to largely depend on a sensitive/critical period during postnatal development, and learned vocal patterns emerge gradually as the long-term consequence of vocal practice during this critical period. In this scenario, it is presumed that the effect of vocal practice is thus mainly limited by the intrinsic timing of age-dependent maturation factors that close the critical period and reduce neural plasticity. However, an alternative, as-yet untested hypothesis is that vocal practice itself, independently of age, regulates vocal learning plasticity. Here, we explicitly discriminate between the influences of age and vocal practice using a songbird model system. We prevented zebra finches from singing during the critical period of sensorimotor learning by reversible postural manipulation. This enabled to us to separate lifelong vocal experience from the effects of age. The singing-prevented birds produced juvenile-like immature song and retained sufficient ability to acquire a tutored song even at adulthood when allowed to sing freely. Genome-wide gene expression network analysis revealed that this adult vocal plasticity was accompanied by an intense induction of singing activity-dependent genes, similar to that observed in juvenile birds, rather than of age-dependent genes. The transcriptional changes of activity-dependent genes occurred in the vocal motor robust nucleus of the arcopallium (RA) projection neurons that play a critical role in the production of song phonology. These gene expression changes were accompanied by neuroanatomical changes: dendritic spine pruning in RA projection neurons. These results show that self-motivated practice itself changes the expression dynamics of activity-dependent genes associated with vocal learning plasticity and that this process is not tightly linked to age-dependent maturational factors.

How is plasticity associated with vocal learning regulated during a critical period? Although there are abundant studies on the critical period in sensory systems, which are passively regulated by the external environment, few studies have manipulated the sensorimotor experience through the entire critical period. Thus, it is a commonly held belief that age or intrinsic maturation is a crucial factor for the closure of the critical period of vocal learning. Contrary to this idea, our study using songbirds provides a new insight that self-motivated vocal practice, not age, regulates vocal learning plasticity during the critical period. To examine the effects of vocal practice on vocal learning, we prevented juvenile zebra finches from singing during the critical period by postural manipulation, which separated the contribution of lifelong vocal experience from that of age. When these birds were allowed to freely sing as adults, they generated highly plastic songs and maintained the ability to mimic tutored songs, as normal juveniles did. Genome-wide transcriptome analysis revealed that both juveniles and singing-prevented adults, but not normally reared adults, expressed a similar set of singing-dependent genes in a song nucleus in the brain that regulates syllable acoustics. However, age-dependent genes were still similarly expressed in both singing-prevented and normally reared adult birds. These results exhibit that vocal learning plasticity is actively controlled by self-motivated vocal practice.

Vocal learning in songbirds requires cholinergic signaling in a motor cortex-like nucleus

Cholinergic inputs to cortex modulate plasticity and sensory processing, yet little is known about their role in motor control. Here, we show that cholinergic signaling in a songbird vocal motor cortical area, the robust nucleus of the arcopallium (RA), is required for song learning. Reverse microdialysis of nicotinic and muscarinic receptor antagonists into RA in juvenile birds did not significantly affect syllable timing or acoustic structure during vocal babbling. However, chronic blockade over weeks reduced singing quantity and impaired learning, resulting in an impoverished song with excess variability, abnormal acoustic features, and reduced similarity to tutor song. The demonstration that cholinergic signaling in a motor cortical area is required for song learning motivates the songbird as a tractable model system to identify roles of the basal forebrain cholinergic system in motor control. NEW & NOTEWORTHY Cholinergic inputs to cortex are evolutionarily conserved and implicated in sensory processing and synaptic plasticity. However, functions of cholinergic signals in motor areas are understudied and poorly understood. Here, we show that cholinergic signaling in a songbird vocal motor cortical area is not required for normal vocal variability during babbling but is essential for developmental song learning. Cholinergic modulation of motor cortex is thus required for learning but not for the ability to sing.

Singing activity-driven Arc expression associated with vocal acoustic plasticity in juvenile songbird

Learned vocalization, including birdsong and human speech, is acquired through self‐motivated vocal practice during the sensitive period of vocal learning. The zebra finch (Taeniopygia guttata) develops a song characterized by vocal variability and crystallizes a defined song pattern as adulthood. However, it remains unknown how vocal variability is regulated with diurnal singing during the sensorimotor learning period. Here, we investigated the expression of activity‐dependent neuroplasticity‐related gene Arc during the early plastic song phase to examine its potential association with vocal plasticity. We first confirmed that multiple acoustic features of syllables in the plastic song were dramatically and simultaneously modulated during the first 3 hr of singing in a day and the altered features were maintained until sleep. In a concurrent manner, Arc was intensely induced during morning singing and a subsequent attenuation during afternoon singing in the robust nucleus of the arcopallium (RA) and the interfacial nucleus of the nidopallium (NIf). The singing‐driven Arc expression was not altered by circadian rhythm, but rather reduced during the day as juveniles produced more songs. Song stabilization accelerated by testosterone administration in juveniles was accompanied with attenuation of Arc induction in RA and NIf. In contrast, although early‐deafened birds produced highly unstable song even at adulthood, singing‐driven Arc expression was not different between intact and early‐deafened adults. These results suggest a potential functional link between Arc expression in RA and NIf and vocal plasticity during the sensorimotor phase of song learning. Nonetheless, Arc expression did not reflect the quality of bird's own song or auditory feedback.

Flexibility in motor timing constrains the topology and dynamics of pattern generator circuits

Temporally precise movement patterns underlie many motor skills and innate actions, yet the flexibility with which the timing of such stereotyped behaviors can be modified is poorly understood. To probe this, we induce adaptive changes to the temporal structure of birdsong. We find that the duration of specific song segments can be modified without affecting the timing in other parts of the song. We derive formal prescriptions for how neural networks can implement such flexible motor timing. We find that randomly connected recurrent networks, a common approximation for how neocortex is wired, do not generally conform to these, though certain implementations can approximate them. We show that feedforward networks, by virtue of their one-to-one mapping between network activity and time, are better suited. Our study provides general prescriptions for pattern generator networks that implement flexible motor timing, an important aspect of many motor skills, including birdsong and human speech.

Human speech and bird song requires the generation of precisely timed motor patterns. The authors show that zebra finches can learn to independently modify the duration of individual song segments and find that synfire chain networks are ideally suited to implement such flexible motor timing.

Remodeling of Dendritic Spines in the Avian Vocal Motor Cortex Following Deafening Depends on the Basal Ganglia Circuit

Deafening elicits a deterioration of learned vocalization, in both humans and songbirds. In songbirds, learned vocal plasticity has been shown to depend on the basal ganglia-cortical circuit, but the underlying cellular basis remains to be clarified. Using confocal imaging and electron microscopy, we examined the effect of deafening on dendritic spines in avian vocal motor cortex, the robust nucleus of the arcopallium (RA), and investigated the role of the basal ganglia circuit in motor cortex plasticity. We found rapid structural changes to RA dendritic spines in response to hearing loss, accompanied by learned song degradation. In particular, the morphological characters of RA spine synaptic contacts between 2 major pathways were altered differently. However, experimental disruption of the basal ganglia circuit, through lesions in song-specialized basal ganglia nucleus Area X, largely prevented both the observed changes to RA dendritic spines and the song deterioration after hearing loss. Our results provide cellular evidence to highlight a key role of the basal ganglia circuit in the motor cortical plasticity that underlies learned vocal plasticity.

Neural activity in cortico-basal ganglia circuits of juvenile songbirds encodes performance during goal-directed learning

Cortico-basal ganglia circuits are thought to mediate goal-directed learning by a process of outcome evaluation to gradually select appropriate motor actions. We investigated spiking activity in core and shell subregions of the cortical nucleus LMAN during development as juvenile zebra finches are actively engaged in evaluating feedback of self-generated behavior in relation to their memorized tutor song (the goal). Spiking patterns of single neurons in both core and shell subregions during singing correlated with acoustic similarity to tutor syllables, suggesting a process of outcome evaluation. Both core and shell neurons encoded tutor similarity via either increases or decreases in firing rate, although only shell neurons showed a significant association at the population level. Tutor similarity predicted firing rates most strongly during early stages of learning, and shell but not core neurons showed decreases in response variability across development, suggesting that the activity of shell neurons reflects the progression of learning.

Building a state space for song learning

The songbird system has shed light on how the brain produces precisely timed behavioral sequences, and how the brain implements reinforcement learning (RL). RL is a powerful strategy for learning what action to produce in each state, but requires a unique representation of the states involved in the task. Songbird RL circuitry is thought to operate using a representation of each moment within song syllables, consistent with the sparse sequential bursting of neurons in premotor cortical nucleus HVC. However, such sparse sequences are not present in very young birds, which sing highly variable syllables of random lengths. Here, we review and expand upon a model for how the songbird brain could construct latent sequences to support RL, in light of new data elucidating connections between HVC and auditory cortical areas. We hypothesize that learning occurs via four distinct plasticity processes: 1) formation of 'tutor memory' sequences in auditory areas; 2) formation of appropriately-timed latent HVC sequences, seeded by inputs from auditory areas spontaneously replaying the tutor song; 3) strengthening, during spontaneous replay, of connections from HVC to auditory neurons of corresponding timing in the 'tutor memory' sequence, aligning auditory and motor representations for subsequent song evaluation; and 4) strengthening of connections from premotor neurons to motor output neurons that produce the desired sounds, via well-described song RL circuitry.

Vocal learning promotes patterned inhibitory connectivity

Skill learning is instantiated by changes to functional connectivity within premotor circuits, but whether the specificity of learning depends on structured changes to inhibitory circuitry remains unclear. We used slice electrophysiology to measure connectivity changes associated with song learning in the avian analog of primary motor cortex (robust nucleus of the arcopallium, RA) in Bengalese Finches. Before song learning, fast-spiking interneurons (FSIs) densely innervated glutamatergic projection neurons (PNs) with apparently random connectivity. After learning, there was a profound reduction in the overall strength and number of inhibitory connections, but this was accompanied by a more than two-fold enrichment in reciprocal FSI–PN connections. Moreover, in singing birds, we found that pharmacological manipulations of RA's inhibitory circuitry drove large shifts in learned vocal features, such as pitch and amplitude, without grossly disrupting the song. Our results indicate that skill learning establishes nonrandom inhibitory connectivity, and implicates this patterning in encoding specific features of learned movements.

Complex motor behaviors such as birdsong are learned through practice and are thought to depend on specific excitatory connectivity in premotor circuits. Here the authors show that song learning in Bengalese Finches is associated with enrichment of inhibitory network connectivity that can affect specific song features.

Population-Level Representation of a Temporal Sequence Underlying Song Production in the Zebra Finch

The zebra finch brain features a set of clearly defined and hierarchically arranged motor nuclei that are selectively responsible for producing singing behavior. One of these regions, a critical forebrain structure called HVC, contains premotor neurons that are active at precise time points during song production. However, the neural representation of this behavior at a population level remains elusive. We used two-photon microscopy to monitor ensemble activity during singing, integrating across multiple trials by adopting a Bayesian inference approach to more precisely estimate burst timing. Additionally, we examined spiking and motor-related synaptic inputs using intracellular recordings during singing. With both experimental approaches, we find that premotor events do not occur preferentially at the onsets or offsets of song syllables or at specific subsyllabic motor landmarks. These results strongly support the notion that HVC projection neurons collectively exhibit a temporal sequence during singing that is uncoupled from ongoing movements.

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.

The Role of Variability in Motor Learning

Trial-to-trial variability in the execution of movements and motor skills is ubiquitous and widely considered to be the unwanted consequence of a noisy nervous system. However, recent studies have suggested that motor variability may also be a feature of how sensorimotor systems operate and learn. This view, rooted in reinforcement learning theory, equates motor variability with purposeful exploration of motor space that, when coupled with reinforcement, can drive motor learning. Here we review studies that explore the relationship between motor variability and motor learning in both humans and animal models. We discuss neural circuit mechanisms that underlie the generation and regulation of motor variability and consider the implications that this work has for our understanding of motor learning.

A canonical neural mechanism for behavioral variability

The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5-6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these 'universal' statistics.

Rules and mechanisms for efficient two-stage learning in neural circuits

Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in 'tutor' circuits (e.g., LMAN) should match plasticity mechanisms in 'student' circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.

Growth and splitting of neural sequences in songbird vocal development

Neural sequences are a fundamental feature of brain dynamics underlying diverse behaviors, but the mechanisms by which they develop during learning remain unknown. Songbirds learn vocalizations composed of syllables; in adult birds, each syllable is produced by a different sequence of action potential bursts in the premotor cortical area HVC. Here we carried out recordings of large populations of HVC neurons in singing juvenile birds throughout learning to examine the emergence of neural sequences. Early in vocal development, HVC neurons begin producing rhythmic bursts, temporally locked to a ‘prototype’ syllable. Different neurons are active at different latencies relative to syllable onset to form a continuous sequence. Through development, as new syllables emerge from the prototype syllable, initially highly overlapping burst sequences become increasingly distinct. We propose a mechanistic model in which multiple neural sequences can emerge from the growth and splitting of a common precursor sequence.

Phylogenetic and individual variation in gastropod central pattern generators

Gastropod molluscs provide a unique opportunity to explore the neural basis of rhythmic behaviors because of the accessibility of their nervous systems and the number of species that have been examined. Detailed comparisons of the central pattern generators (CPGs) underlying rhythmic feeding and swimming behaviors highlight the presence and effects of variation in neural circuits both across and within species. The feeding motor pattern of the snail, Lymnaea, is stereotyped, whereas the feeding motor pattern in the sea hare, Aplysia, is variable. However, the Aplysia motor pattern is regularized with operant conditioning or by mimicking learning using the dynamic clamp to change properties of CPG neurons. Swimming evolved repeatedly in marine gastropods. Distinct neural mechanisms underlie dissimilar forms of swimming, with homologous neurons playing different roles. However, even similar swimming behaviors in different species can be produced by distinct neural mechanisms, resulting from different synaptic connectivity of homologous neurons. Within a species, there can be variation in the strength and even valence of synapses, which does not have functional relevance under normal conditions, but can cause some individuals to be more susceptible to lesion of the circuit. This inter- and intra-species variation provides novel insights into CPG function and plasticity.