Mechanisms and time course of vocal learning and consolidation in the adult songbird

Female calls promote song learning in male juvenile zebra finches

Social interactions promote vocal learning, but the impact of social feedback on this process and its neural circuitry is not well understood. We studied song imitation in juvenile male zebra finches raised either in the presence or absence of adult females. Juveniles learned songs more accurately with a female present, suggesting her presence improves imitation. When female calls correlated with practice, tutees' songs better resembled the tutor's, hinting toward the possibility that females provide practice-specific vocalizations. Intracellular recordings of HVC projection neurons revealed that a subset of these neurons in both juveniles and adults is sensitive to female calls during listening, suggesting a consistent neural mechanism for processing important vocalizations, regardless of age. However, call-related neural responses during singing were observed only in juveniles. These findings highlight how vocalizations, beyond those of the tutor, influence the neural circuits for vocal learning and production.

Synaptic weight dynamics underlying memory consolidation: Implications for learning rules, circuit organization, and circuit function

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We provide two biologically plausible implementations for this reset that propose functional roles in stabilizing consolidation for core elements of the cerebellar circuit.

Recall tempo of Hebbian sequences depends on the interplay of Hebbian kernel with tutor signal timing

Understanding how neural circuits generate sequential activity is a longstanding challenge. While foundational theoretical models have shown how sequences can be stored as memories in neural networks with Hebbian plasticity rules, these models considered only a narrow range of Hebbian rules. Here, we introduce a model for arbitrary Hebbian plasticity rules, capturing the diversity of spike-timing-dependent synaptic plasticity seen in experiments, and show how the choice of these rules and of neural activity patterns influences sequence memory formation and retrieval. In particular, we derive a general theory that predicts the tempo of sequence replay. This theory lays a foundation for explaining how cortical tutor signals might give rise to motor actions that eventually become "automatic." Our theory also captures the impact of changing the tempo of the tutor signal. Beyond shedding light on biological circuits, this theory has relevance in artificial intelligence by laying a foundation for frameworks whereby slow and computationally expensive deliberation can be stored as memories and eventually replaced by inexpensive recall.

Synaptic weight dynamics underlying memory consolidation: implications for learning rules, circuit organization, and circuit function

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We propose two biologically plausible implementations for this reset that suggest novel roles for core elements of the cerebellar circuit.

Significance Statement

How are memories transformed over time? We propose a simple organizing principle for how long term memories are moved from an initial to a final site of storage. We show that successful transfer occurs when the late site of memory storage is endowed with synaptic plasticity rules that stably accumulate changes in activity occurring at the early site of memory storage. We instantiate this principle in a simple computational model that is representative of brain circuits underlying a variety of behaviors. The model suggests how a neural circuit can store new memories while preserving core features of older ones, and suggests novel roles for core elements of the cerebellar circuit.

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

Goal-directed vocal planning in a songbird

Songbirds' vocal mastery is impressive, but to what extent is it a result of practice? Can they, based on experienced mismatch with a known target, plan the necessary changes to recover the target in a practice-free manner without intermittently singing? In adult zebra finches, we drive the pitch of a song syllable away from its stable (baseline) variant acquired from a tutor, then we withdraw reinforcement and subsequently deprive them of singing experience by muting or deafening. In this deprived state, birds do not recover their baseline song. However, they revert their songs toward the target by about 1 standard deviation of their recent practice, provided the sensory feedback during the latter signaled a pitch mismatch with the target. Thus, targeted vocal plasticity does not require immediate sensory experience, showing that zebra finches are capable of goal-directed vocal planning.

Transient sensorimotor projections in the developmental song learning period

Memory recall and guidance are essential for motor skill acquisition. Like humans learning to speak, male zebra finches learn to sing by first memorizing and then matching their vocalization to the tutor's song (TS) during specific developmental periods. Yet, the neuroanatomical substrate supporting auditory-memory-guided sensorimotor learning has remained elusive. Here, using a whole-brain connectome analysis with activity-dependent viral expression, we identified a transient projection into the motor region, HVC, from neuronal ensembles responding to TS in the auditory forebrain, the caudomedial nidopallium (NCM), in juveniles. Virally induced cell death of the juvenile, but not adult, TS-responsive NCM neurons impaired song learning. Moreover, isolation, which delays closure of the sensory, but not the motor, learning period, did not affect the decrease of projections into the HVC from the NCM TS-responsive neurons after the song learning period. Taken together, our results suggest that dynamic axonal pruning may regulate timely auditory-memory-guided vocal learning during development.

Daily singing of adult songbirds functions to maintain song performance independently of auditory feedback and age

Many songbirds learn to produce songs through vocal practice in early life and continue to sing daily throughout their lifetime. While it is well-known that adult songbirds sing as part of their mating rituals, the functions of singing behavior outside of reproductive contexts remain unclear. Here, we investigated this issue in adult male zebra finches by suppressing their daily singing for two weeks and examining the effects on song performance. We found that singing suppression decreased the pitch, amplitude, and duration of songs, and that those song features substantially recovered through subsequent free singing. These reversible song changes were not dependent on auditory feedback or the age of the birds, contrasting with the adult song plasticity that has been reported previously. These results demonstrate that adult song structure is not stable without daily singing, and suggest that adult songbirds maintain song performance by preventing song changes through physical act of daily singing throughout their life. Such daily singing likely functions as vocal training to maintain the song production system in optimal conditions for song performance in reproductive contexts, similar to how human singers and athletes practice daily to maintain their performance.

Lesions in a songbird vocal circuit increase variability in song syntax

Complex skills like speech and dance are composed of ordered sequences of simpler elements, but the neuronal basis for the syntactic ordering of actions is poorly understood. Birdsong is a learned vocal behavior composed of syntactically ordered syllables, controlled in part by the songbird premotor nucleus HVC (proper name). Here, we test whether one of HVC's recurrent inputs, mMAN (medial magnocellular nucleus of the anterior nidopallium), contributes to sequencing in adult male Bengalese finches (Lonchura striata domestica). Bengalese finch song includes several patterns: (1) chunks, comprising stereotyped syllable sequences; (2) branch points, where a given syllable can be followed probabilistically by multiple syllables; and (3) repeat phrases, where individual syllables are repeated variable numbers of times. We found that following bilateral lesions of mMAN, acoustic structure of syllables remained largely intact, but sequencing became more variable, as evidenced by 'breaks' in previously stereotyped chunks, increased uncertainty at branch points, and increased variability in repeat numbers. Our results show that mMAN contributes to the variable sequencing of vocal elements in Bengalese finch song and demonstrate the influence of recurrent projections to HVC. Furthermore, they highlight the utility of species with complex syntax in investigating neuronal control of ordered sequences.

Anterior forebrain pathway in parrots is necessary for producing learned vocalizations with individual signatures

Parrots have enormous vocal imitation capacities and produce individually unique vocal signatures. Like songbirds, parrots have a nucleated neural song system with distinct anterior (AFP) and posterior forebrain pathways (PFP). To test if song systems of parrots and songbirds, which diverged over 50 million years ago, have a similar functional organization, we first established a neuroscience-compatible call-and-response behavioral paradigm to elicit learned contact calls in budgerigars (Melopsittacus undulatus). Using variational autoencoder-based machine learning methods, we show that contact calls within affiliated groups converge but that individuals maintain unique acoustic features, or vocal signatures, even after call convergence. Next, we transiently inactivated the outputs of AFP to test if learned vocalizations can be produced by the PFP alone. As in songbirds, AFP inactivation had an immediate effect on vocalizations, consistent with a premotor role. But in contrast to songbirds, where the isolated PFP is sufficient to produce stereotyped and acoustically normal vocalizations, isolation of the budgerigar PFP caused a degradation of call acoustic structure, stereotypy, and individual uniqueness. Thus, the contribution of AFP and the capacity of isolated PFP to produce learned vocalizations have diverged substantially between songbirds and parrots, likely driven by their distinct behavioral ecology and neural connectivity.

Dynamic top-down biasing implements rapid adaptive changes to individual movements

Complex behaviors depend on the coordinated activity of neural ensembles in interconnected brain areas. The behavioral function of such coordination, often measured as co-fluctuations in neural activity across areas, is poorly understood. One hypothesis is that rapidly varying co-fluctuations may be a signature of moment-by-moment task-relevant influences of one area on another. We tested this possibility for error-corrective adaptation of birdsong, a form of motor learning which has been hypothesized to depend on the top-down influence of a higher-order area, LMAN (lateral magnocellular nucleus of the anterior nidopallium), in shaping moment-by-moment output from a primary motor area, RA (robust nucleus of the arcopallium). In paired recordings of LMAN and RA in singing birds, we discovered a neural signature of a top-down influence of LMAN on RA, quantified as an LMAN-leading co-fluctuation in activity between these areas. During learning, this co-fluctuation strengthened in a premotor temporal window linked to the specific movement, sequential context, and acoustic modification associated with learning. Moreover, transient perturbation of LMAN activity specifically within this premotor window caused rapid occlusion of pitch modifications, consistent with LMAN conveying a temporally localized motor-biasing signal. Combined, our results reveal a dynamic top-down influence of LMAN on RA that varies on the rapid timescale of individual movements and is flexibly linked to contexts associated with learning. This finding indicates that inter-area co-fluctuations can be a signature of dynamic top-down influences that support complex behavior and its adaptation.

Reversible inhibition of the basal ganglia prolongs repetitive vocalization but only weakly affects sequencing at branch points in songbirds

Although vocal signals, including languages and songbird syllables, are composed of a finite number of acoustic elements, diverse vocal sequences are composed of a combination of these elements, which are linked together by syntactic rules. However, the neural basis of syntactic vocalization generation remains poorly understood. Here, we report that inhibition using tetrodotoxin (TTX) and manipulations of gamma-aminobutyric acid (GABA) receptors within the basal ganglia Area X or lateral magnocellular nucleus of the anterior neostriatum (LMAN) alter and prolong repetitive vocalization in Bengalese finches (Lonchura striata var. domestica). These results suggest that repetitive vocalizations are modulated by the basal ganglia and not solely by higher motor cortical neurons. These data highlight the importance of neural circuits, including the basal ganglia, in the production of stereotyped repetitive vocalizations and demonstrate that dynamic disturbances within the basal ganglia circuitry can differentially affect the repetitive temporal features of songs.

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.

Generative models of birdsong learning link circadian fluctuations in song variability to changes in performance

Learning skilled behaviors requires intensive practice over days, months, or years. Behavioral hallmarks of practice include exploratory variation and long-term improvements, both of which can be impacted by circadian processes. During weeks of vocal practice, the juvenile male zebra finch transforms highly variable and simple song into a stable and precise copy of an adult tutor's complex song. Song variability and performance in juvenile finches also exhibit circadian structure that could influence this long-term learning process. In fact, one influential study reported juvenile song regresses towards immature performance overnight, while another suggested a more complex pattern of overnight change. However, neither of these studies thoroughly examined how circadian patterns of variability may structure the production of more or less mature songs. Here we relate the circadian dynamics of song maturation to circadian patterns of song variation, leveraging a combination of data-driven approaches. In particular we analyze juvenile singing in learned feature space that supports both data-driven measures of song maturity and generative developmental models of song production. These models reveal that circadian fluctuations in variability lead to especially regressive morning variants even without overall overnight regression, and highlight the utility of data-driven generative models for untangling these contributions.

Motor constellation theory: A model of infants' phonological development

Every normally developing human infant solves the difficult problem of mapping their native-language phonology, but the neural mechanisms underpinning this behavior remain poorly understood. Here, motor constellation theory, an integrative neurophonological model, is presented, with the goal of explicating this issue. It is assumed that infants' motor-auditory phonological mapping takes place through infants' orosensory "reaching" for phonological elements observed in the language-specific ambient phonology, via reference to kinesthetic feedback from motor systems (e.g., articulators), and auditory feedback from resulting speech and speech-like sounds. Attempts are regulated by basal ganglion-cerebellar speech neural circuitry, and successful attempts at reproduction are enforced through dopaminergic signaling. Early in life, the pace of anatomical development constrains mapping such that complete language-specific phonological mapping is prohibited by infants' undeveloped supralaryngeal vocal tract and undescended larynx; constraints gradually dissolve with age, enabling adult phonology. Where appropriate, reference is made to findings from animal and clinical models. Some implications for future modeling and simulation efforts, as well as clinical settings, are also discussed.

Thalamocortical contribution to flexible learning in neural systems

Animal brains evolved to optimize behavior in dynamic environments, flexibly selecting actions that maximize future rewards in different contexts. A large body of experimental work indicates that such optimization changes the wiring of neural circuits, appropriately mapping environmental input onto behavioral outputs. A major unsolved scientific question is how optimal wiring adjustments, which must target the connections responsible for rewards, can be accomplished when the relation between sensory inputs, action taken, and environmental context with rewards is ambiguous. The credit assignment problem can be categorized into context-independent structural credit assignment and context-dependent continual learning. In this perspective, we survey prior approaches to these two problems and advance the notion that the brain's specialized neural architectures provide efficient solutions. Within this framework, the thalamus with its cortical and basal ganglia interactions serves as a systems-level solution to credit assignment. Specifically, we propose that thalamocortical interaction is the locus of meta-learning where the thalamus provides cortical control functions that parametrize the cortical activity association space. By selecting among these control functions, the basal ganglia hierarchically guide thalamocortical plasticity across two timescales to enable meta-learning. The faster timescale establishes contextual associations to enable behavioral flexibility, while the slower one enables generalization to new contexts.

Shared mechanisms of auditory and non-auditory vocal learning in the songbird brain

Songbirds and humans share the ability to adaptively modify their vocalizations based on sensory feedback. Prior studies have focused primarily on the role that auditory feedback plays in shaping vocal output throughout life. In contrast, it is unclear how non-auditory information drives vocal plasticity. Here, we first used a reinforcement learning paradigm to establish that somatosensory feedback (cutaneous electrical stimulation) can drive vocal learning in adult songbirds. We then assessed the role of a songbird basal ganglia thalamocortical pathway critical to auditory vocal learning in this novel form of vocal plasticity. We found that both this circuit and its dopaminergic inputs are necessary for non-auditory vocal learning, demonstrating that this pathway is critical for guiding adaptive vocal changes based on both auditory and somatosensory signals. The ability of this circuit to use both auditory and somatosensory information to guide vocal learning may reflect a general principle for the neural systems that support vocal plasticity across species.

Organizational Conservation and Flexibility in the Evolution of Birdsong and Avian Motor Control

Birds and mammals have independently evolved complex behavioral and cognitive capabilities yet have markedly different brain structures. An open question is to what extent, despite these differences in anatomy, birds and mammals have evolved similar neural solutions to complex motor control and at what level of organization these similarities might lie. Courtship song in songbirds, a learned motor skill that is similar to the fine motor skills of many mammals including human speech, provides a powerful system in which to study the links connecting the development and evolution of cells, circuits, and behavior. Until recently, obtaining cellular-resolution views of the specialized neural circuitry that subserves birdsong was impossible due to a lack of molecular tools for songbirds. However, the ongoing revolution in cellular profiling and genomics offers unprecedented opportunities for molecular analysis in organisms that lack a traditional genetic infrastructure but have tractable, well-defined behaviors. Here, I describe recent efforts to understand the evolutionary relationships between birdsong control circuitry and mammalian neocortical circuitry using new approaches to measure gene expression in single cells. These results, combined with foundational work relating avian and mammalian brains at a range of biological levels, present an emerging view that amniote pallium evolution is a story of diverse neural circuit architectures employing conserved neuronal elements within a conserved topological framework. This view suggests that one locus of pallial neural circuit evolution lies at the intersection between the gene regulatory programs that regulate regional patterning and those that specify functional identity. Modifications to this intersection may underlie the evolution of pallial motor control in birds in general and to the evolutionary and developmental relationships of these circuits to the avian pallial amygdala.

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.

Plasticity of stereotyped birdsong driven by chronic manipulation of cortical-basal ganglia activity

Cortical-basal ganglia (CBG) circuits are critical for motor learning and performance, and are a major site of pathology. In songbirds, a CBG circuit regulates moment-by-moment variability in song and also enables song plasticity. Studies have shown that variable burst firing in LMAN, the output nucleus of this CBG circuit, actively drives acute song variability, but whether and how LMAN drives long-lasting changes in song remains unclear. Here, we ask whether chronic pharmacological augmentation of LMAN bursting is sufficient to drive plasticity in birds singing stereotyped songs. We show that altered LMAN activity drives cumulative changes in acoustic structure, timing, and sequencing over multiple days, and induces repetitions and silent pauses reminiscent of human stuttering. Changes persisted when LMAN was subsequently inactivated, indicating plasticity in song motor regions. Following cessation of pharmacological treatment, acoustic features and song sequence gradually recovered to their baseline values over a period of days to weeks. Together, our findings show that augmented bursting in CBG circuitry drives plasticity in well-learned motor skills, and may inform treatments for basal ganglia movement disorders.

The Rules of Cerebellar Learning: Around the Ito Hypothesis

As a tribute to Masao Ito, we propose a model of cerebellar learning that incorporates and extends his original model. We suggest four principles that align well with conclusions from multiple cerebellar learning systems. (1) Climbing fiber inputs to the cerebellum drive early, fast, poorly-retained learning in the parallel fiber to Purkinje cell synapse. (2) Learned Purkinje cell outputs drive late, slow, well-retained learning in non-Purkinje cell inputs to neurons in the cerebellar nucleus, transferring learning from the cortex to the nucleus. (3) Recurrent feedback from Purkinje cells to the inferior olive, through interneurons in the cerebellar nucleus, limits the magnitude of fast, early learning in the cerebellar cortex. (4) Functionally different inputs are subjected to plasticity in the cerebellar cortex versus the cerebellar nucleus. A computational neural circuit model that is based on these principles mimics a large amount of neural and behavioral data obtained from the smooth pursuit eye movements of monkeys.

Digitomotography in children with oro-facial dysfunction (OFD, oro-facial myofunctional disorders) and childhood apraxia of speech (CAS)

BACKGROUND

Oro-facial dysfunctions (OFDs; oro-facial myofunctional disorders) in children and childhood apraxia of speech (CAS) often cause severe problems in articulation, chewing, swallowing and oral posture.

OBJECTIVES

Pathognomonic symptoms could yet not be identified, but central problems in planning, programming, timing and automating oro-facial, as well as other fine motor skills, are assumed to be affected.

METHODS

To investigate the nature of motor and coordinative deficits in OFD and CAS, digitomotography was applied. The testing focused on recording frequency, force, rhythm and regularity of the index finger including speeded and metronome tapping tasks. 25 children with OFD (7 girls and 18 boys, age 7.9 ± 2.3) and 5 children with CAS (0 girls and 5 boys, age 7.6 ± 2.3), and 31 healthy controls (12 girls and 19 boys, age 9.3 ± 2.2) were tested. Statistical significance was accepted at α = 0.05. ANOVA test, non-parametric Mann-Whitney U test, Kruskal-Wallis test and Spearman's rank correlation coefficient were used.

RESULTS

Cross-sectional data revealed consistent significant differences between children with OFD and healthy controls concerning frequency, force, rhythm and regularity of index finger tapping. Individuals with CAS showed particularly low results. Tapping results correlated with disease burden.

CONCLUSION

These findings support that underlying superordinated sensorimotor deficits exist. This may help phenotyping and influence diagnostical and therapeutical approaches.

Song learning and plasticity in songbirds

Birdsong provides a fascinating system to study both behavioral and neural plasticity. Oscine songbirds learn to sing, exhibiting behavioral plasticity both during and after the song-learning process. As a bird learns, its song progresses from a plastic and highly variable vocalization into a more stereotyped, crystallized song. However, even after crystallization, song plasticity can occur: some species' songs become more stereotyped over time, whereas other species can incorporate new song elements. Alongside the changes in song, songbirds' brains are also plastic. Both song and neural connections change with the seasons in many species, and new neurons can be added to the song system throughout life. In this review, we highlight important research on behavioral and neural plasticity at multiple timescales, from song development in juveniles to lifelong modifications of learned song.

Neuroendocrine patterns underlying seasonal song and year-round territoriality in male black redstarts

BACKGROUND

The connection between testosterone and territoriality in free-living songbirds has been well studied in a reproductive context, but less so outside the breeding season. To assess the effects of seasonal androgenic action on territorial behavior, we analyzed vocal and non-vocal territorial behavior in response to simulated territorial intrusions (STIs) during three life-cycle stages in free-living male black redstarts: breeding, molt and nonbreeding. Concurrently, we measured changes in circulating testosterone levels, as well as the mRNA expression of androgen and estrogen receptors and aromatase in the preoptic, hypothalamic and song control brain areas that are associated with social and vocal behaviors.

RESULTS

Territorial behavior and estrogen receptor expression in hypothalamic areas did not differ between stages. But plasma testosterone was higher during breeding than during the other stages, similar to androgen receptor and aromatase expression in the preoptic area. The expression of androgen receptors in the song control nucleus HVC was lower during molt when birds do not sing or sing rarely, but similar between the breeding and the nonbreeding stage. Nevertheless, some song spectral features and the song repertoire differed between breeding and nonbreeding. Territorial behavior and song rate correlated with the expression of steroid receptors in hypothalamic areas, and in the song control nucleus lMAN.

CONCLUSIONS

Our results demonstrate seasonal modulation of song, circulating testosterone levels, and brain sensitivity to androgens, but a year-round persistency of territorial behavior and estrogen receptor expression in all life-cycle stages. This suggests that seasonal variations in circulating testosterone concentrations and brain sensitivity to androgens is widely uncoupled from territorial behavior and song activity but might still affect song pattern. Our study contributes to the understanding of the complex comparative neuroendocrinology of song birds in the wild.

The Adjustment of Anterior Forebrain Pathway (AFP) to Birdsong Is Phased during Song Learning and Maintenance

Anterior forebrain pathway (AFP), a basal ganglia-dorsal forebrain circuit, significantly impacts birdsong, specifically in juvenile or deaf birds. Despite many physiological experiments supporting AFP's role in song production, the mechanism underlying it remains poorly understood. Using a computational model of the anterior forebrain pathway and song premotor pathway, we examined the dynamic process and exact role of AFP during song learning and distorted auditory feedback (DAF). Our simulation suggests that AFP can adjust the premotor pathway structure and syllables based on its delayed input to the robust nucleus of the archistriatum (RA). It is also indicated that the adjustment to the synaptic conductance in the song premotor pathway has two phases: normal phases where the adjustment decreases with an increasing number of trials and abnormal phases where the adjustment remains stable or even increases. These two phases alternate and impel a specific effect on birdsong based on AFP's specific structures, which may be associated with auditory feedback. Furthermore, our model captured some characteristics shown in birdsong experiments, such as similarities in pitch, intensity, and duration to real birds and the highly abnormal features of syllables during DAF.

Variable but not random: temporal pattern coding in a songbird brain area necessary for song modification

Practice of a complex motor gesture involves motor exploration to attain a better match to target, but little is known about the neural code for such exploration. We examine spiking in a premotor area of the songbird brain critical for song modification and quantify correlations between spiking and time in the motor sequence. While isolated spikes code for time in song during performance of song to a female bird, extended strings of spiking and silence, particularly bursts, code for time in song during undirected (solo) singing, or "practice." Bursts code for particular times in song with more information than individual spikes, and this spike-spike synergy is significantly higher during undirected singing. The observed pattern information cannot be accounted for by a Poisson model with a matched time-varying rate, indicating that the precise timing of spikes in both bursts in undirected singing and isolated spikes in directed singing code for song with a temporal code. Temporal coding during practice supports the hypothesis that lateral magnocellular nucleus of the anterior nidopallium neurons actively guide song modification at local instances in time.NEW & NOTEWORTHY This paper shows that bursts of spikes in the songbird brain during practice carry information about the output motor pattern. The brain's code for song changes with social context, in performance versus practice. Synergistic combinations of spiking and silence code for time in the bird's song. This is one of the first uses of information theory to quantify neural information about a motor output. This activity may guide changes to the song.

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.

An avian cortical circuit for chunking tutor song syllables into simple vocal-motor units

How are brain circuits constructed to achieve complex goals? The brains of young songbirds develop motor circuits that achieve the goal of imitating a specific tutor song to which they are exposed. Here, we set out to examine how song-generating circuits may be influenced early in song learning by a cortical region (NIf) at the interface between auditory and motor systems. Single-unit recordings reveal that, during juvenile babbling, NIf neurons burst at syllable onsets, with some neurons exhibiting selectivity for particular emerging syllable types. When juvenile birds listen to their tutor, NIf neurons are also activated at tutor syllable onsets, and are often selective for particular syllable types. We examine a simple computational model in which tutor exposure imprints the correct number of syllable patterns as ensembles in an interconnected NIf network. These ensembles are then reactivated during singing to train a set of syllable sequences in the motor network.

Young songbirds learn to imitate their parents’ songs. Here, the authors find that, in baby birds, neurons in a brain region at the interface of auditory and motor circuits signal the onsets of song syllables during both tutoring and babbling, suggesting a specific neural mechanism for vocal imitation.

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.

Principles of operation of a cerebellar learning circuit

We provide behavioral evidence using monkey smooth pursuit eye movements for four principles of cerebellar learning. Using a circuit-level model of the cerebellum, we link behavioral data to learning's neural implementation. The four principles are: (1) early, fast, acquisition driven by climbing fiber inputs to the cerebellar cortex, with poor retention; (2) learned responses of Purkinje cells guide transfer of learning from the cerebellar cortex to the deep cerebellar nucleus, with excellent retention; (3) functionally different neural signals are subject to learning in the cerebellar cortex versus the deep cerebellar nuclei; and (4) negative feedback from the cerebellum to the inferior olive reduces the magnitude of the teaching signal in climbing fibers and limits learning. Our circuit-level model, based on these four principles, explains behavioral data obtained by strategically manipulating the signals responsible for acquisition and recall of direction learning in smooth pursuit eye movements across multiple timescales.

Optimal spectral templates for triggered feedback experiments

In the field of songbird neuroscience, researchers have used playback of aversive noise bursts to drive changes in song behavior for specific syllables within a bird’s song. Typically, a short (~5–10 msec) slice of the syllable is selected for targeting and the average spectrum of the slice is used as a template. Sounds that are sufficiently close to the template are considered a match. If other syllables have portions that are spectrally similar to the target, false positive errors will weaken the operant contingency. We present a gradient descent method for template optimization that increases the separation in distance between target and distractors slices, greatly improving targeting accuracy. Applied to songs from five adult Bengalese finches, the fractional reduction in errors for sub-syllabic slices was 51.54±22.92%. At the level of song syllables, we use an error metric that controls for the vastly greater number of distractors vs. target syllables. Setting 5% average error (misses + false positives) as a minimal performance criterion, the number of targetable syllables increased from 3 to 16 out of 61 syllables. At 10% error, targetable syllables increased from 11 to 26. By using simple and robust linear discriminant methods, the algorithm reaches near asymptotic performance when using 10 songs as training data, and the error increases by <2.3% on average when using only a single song for training. Targeting is temporally precise, with average jitter of 3.33 msec for the 16 accurately targeted syllables. Because the algorithm is concerned only with the problem of template selection, it can be used as a simple and robust front end for existing hardware and software implementations for triggered feedback.

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.

Transcriptional regulatory divergence underpinning species-specific learned vocalization in songbirds

Learning of most motor skills is constrained in a species-specific manner. However, the proximate mechanisms underlying species-specific learned behaviors remain poorly understood. Songbirds acquire species-specific songs through learning, which is hypothesized to depend on species-specific patterns of gene expression in functionally specialized brain regions for vocal learning and production, called song nuclei. Here, we leveraged two closely related songbird species, zebra finch, owl finch, and their interspecific first-generation (F1) hybrids, to relate transcriptional regulatory divergence between species with the production of species-specific songs. We quantified genome-wide gene expression in both species and compared this with allele-specific expression in F1 hybrids to identify genes whose expression in song nuclei is regulated by species divergence in either cis- or trans-regulation. We found that divergence in transcriptional regulation altered the expression of approximately 10% of total transcribed genes and was linked to differential gene expression between the two species. Furthermore, trans-regulatory changes were more prevalent than cis-regulatory and were associated with synaptic formation and transmission in song nucleus RA, the avian analog of the mammalian laryngeal motor cortex. We identified brain-derived neurotrophic factor (BDNF) as an upstream mediator of trans-regulated genes in RA, with a significant correlation between individual variation in BDNF expression level and species-specific song phenotypes in F1 hybrids. This was supported by the fact that the pharmacological overactivation of BDNF receptors altered the expression of its trans-regulated genes in the RA, thus disrupting the learned song structures of adult zebra finch songs at the acoustic and sequence levels. These results demonstrate functional neurogenetic associations between divergence in region-specific transcriptional regulation and species-specific learned behaviors.

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

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

Discrete Evaluative and Premotor Circuits Enable Vocal Learning in Songbirds

Virtuosic motor performance requires the ability to evaluate and modify individual gestures within a complex motor sequence. Where and how the evaluative and premotor circuits operate within the brain to enable such temporally precise learning is poorly understood. Songbirds can learn to modify individual syllables within their complex vocal sequences, providing a system for elucidating the underlying evaluative and premotor circuits. We combined behavioral and optogenetic methods to identify 2 afferents to the ventral tegmental area (VTA) that serve evaluative roles in syllable-specific learning and to establish that downstream cortico-basal ganglia circuits serve a learning role that is only premotor. Furthermore, song performance-contingent optogenetic stimulation of either VTA afferent was sufficient to drive syllable-specific learning, and these learning effects were of opposite valence. Finally, functional, anatomical, and molecular studies support the idea that these evaluative afferents bidirectionally modulate VTA dopamine neurons to enable temporally precise vocal learning.

A natural history of skills

The dorsal pallium (a.k.a. cortex in mammals) makes a loop circuit with the basal ganglia and the thalamus known to control and adapt behavior but the who's who of the functional roles of these structures is still debated. Influenced by the Triune brain theory that was proposed in the early sixties, many current theories propose a hierarchical organization on the top of which stands the cortex to which the subcortical structures are subordinated. In particular, habits formation has been proposed to reflect a switch from conscious on-line control of behavior by the cortex, to a fully automated subcortical control. In this review, we propose to revalue the function of the network in light of the current experimental evidence concerning the anatomy and physiology of the basal ganglia-cortical circuits in vertebrates. We briefly review the current theories and show that they could be encompassed in a broader framework of skill learning and performance. Then, after reminding the state of the art concerning the anatomical architecture of the network and the underlying dynamic processes, we summarize the evolution of the anatomical and physiological substrate of skill learning and performance among vertebrates. We then review experimental evidence supporting for the hypothesis that the development of automatized skills relies on the BG teaching cortical circuits and is actually a late feature linked with the development of a specialized cortex or pallium that evolved in parallel in different taxa. We finally propose a minimal computational framework where this hypothesis can be explicitly implemented and tested.

Vocal tract constancy in birds and humans

Humans perceive speech as being relatively stable despite acoustic variation caused by vocal tract (VT) differences between speakers. Humans use perceptual 'vocal tract normalisation' (VTN) and other processes to achieve this stability. Similarity in vocal apparatus/acoustics between birds and humans means that birds might also experience VT variation. This has the potential to impede bird communication. No known studies have explicitly examined this, but a number of studies show perceptual stability or 'perceptual constancy' in birds similar to that seen in humans when dealing with VT variation. This review explores similarities between birds and humans and concludes that birds show sufficient evidence of perceptual constancy to warrant further research in this area. Future work should 1) quantify the multiple sources of variation in bird vocalisations, including, but not limited to VT variations, 2) determine whether vocalisations are perniciously disrupted by any of these and 3) investigate how birds reduce variation to maintain perceptual constancy and perceptual efficiency.

A subcortical circuit linking the cerebellum to the basal ganglia engaged in vocal learning

Speech is a complex sensorimotor skill, and vocal learning involves both the basal ganglia and the cerebellum. These subcortical structures interact indirectly through their respective loops with thalamo-cortical and brainstem networks, and directly via subcortical pathways, but the role of their interaction during sensorimotor learning remains undetermined. While songbirds and their song-dedicated basal ganglia-thalamo-cortical circuitry offer a unique opportunity to study subcortical circuits involved in vocal learning, the cerebellar contribution to avian song learning remains unknown. We demonstrate that the cerebellum provides a strong input to the song-related basal ganglia nucleus in zebra finches. Cerebellar signals are transmitted to the basal ganglia via a disynaptic connection through the thalamus and then conveyed to their cortical target and to the premotor nucleus controlling song production. Finally, cerebellar lesions impair juvenile song learning, opening new opportunities to investigate how subcortical interactions between the cerebellum and basal ganglia contribute to sensorimotor learning.

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.

Group and individual variability in speech production networks during delayed auditory feedback

Altering reafferent sensory information can have a profound effect on motor output. Introducing a short delay [delayed auditory feedback (DAF)] during speech production results in modulations of voice and loudness, and produces a range of speech dysfluencies. The ability of speakers to resist the effects of delayed feedback is variable yet it is unclear what neural processes underlie differences in susceptibility to DAF. Here, susceptibility to DAF is investigated by looking at the neural basis of within and between subject changes in speech fluency under 50 and 200 ms delay conditions. Using functional magnetic resonance imaging, networks involved in producing speech under two levels of DAF were identified, lying largely within networks active during normal speech production. Independent of condition, fluency ratings were associated with midbrain activity corresponding to periaqueductal grey matter. Across subject variability in ability to produce normal sounding speech under a 200 ms delay was associated with activity in ventral sensorimotor cortices, whereas ability to produce normal sounding speech under a 50 ms delay was associated with left inferior frontal gyrus activity. These data indicate whilst overlapping cortical mechanisms are engaged for speaking under different delay conditions, susceptibility to different temporal delays in speech feedback may involve different processes.

Expression of the potassium-chloride co-transporter, KCC2, within the avian song system

Songbirds learn to produce vocalizations early in life by listening to, then copying the songs of conspecific males. The anterior forebrain pathway, homologous to a basal ganglia-forebrain circuit, is essential for song learning. The projection between the striato-pallidal structure, Area X, and the medial portion of the dorsolateral thalamic nucleus (DLM) is strongly hyperpolarizing in adults, due to a very negative chloride reversal potential (Person & Perkel, Neuron 46:129-140, 2005). The chloride reversal potential is determined, in part, by the expression level of a neuron-specific potassium-chloride cotransporter, KCC2, which is developmentally upregulated in mammals. To determine whether a similar upregulation in KCC2 expression occurs at the Area X to DLM synapse during development, we examined the expression level of KCC2 in adult zebra finches across the song system as well as during development in the Area X - DLM synapse. We demonstrate that KCC2 is expressed in a subset of neurons throughout the song system, including HVC (used as a proper name), robust nucleus of the arcopallium (RA), lateral magnocellular nucleus of the anterior nidopallium (LMAN), Area X, and DLM. The majority of pallidal-like projection neurons in Area X showed KCC2 immunoreactivity. In adults, KCC2 expression was robust within DLM, and was upregulated between 14 and 24 days post hatching, before the onset of song learning. Light and electron microscopic analysis indicated that KCC2 immunoreactivity is strongly associated with the plasma membrane. Thus, in the song system as in the mammalian brain, KCC2 expression is well placed to modulate the GABAA reversal potential.

A Basal Ganglia Circuit Sufficient to Guide Birdsong Learning

Learning vocal behaviors, like speech and birdsong, is thought to rely on continued performance evaluation. Whether candidate performance evaluation circuits in the brain are sufficient to guide vocal learning is not known. Here, we test the sufficiency of VTA projections to the vocal basal ganglia in singing zebra finches, a songbird species that learns to produce a complex and stereotyped multi-syllabic courtship song during development. We optogenetically manipulate VTA axon terminals in singing birds contingent on how the pitch of an individual song syllable is naturally performed. We find that optical inhibition and excitation of VTA terminals are each sufficient to reliably guide learned changes in song. Inhibition and excitation have opponent effects on future performances of targeted song syllables, consistent with positive and negative reinforcement of performance outcomes. These findings define a central role for reinforcement mechanisms in learning vocalizations and demonstrate minimal circuit elements for learning vocal behaviors. VIDEO ABSTRACT.

Draft genome assembly of the Bengalese finch, Lonchura striata domestica, a model for motor skill variability and learning

Background

Vocal learning in songbirds has emerged as a powerful model for sensorimotor learning. Neurobehavioral studies of Bengalese finch (Lonchura striata domestica) song, naturally more variable and plastic than songs of other finch species, have demonstrated the importance of behavioral variability for initial learning, maintenance, and plasticity of vocalizations. However, the molecular and genetic underpinnings of this variability and the learning it supports are poorly understood.

Findings

To establish a platform for the molecular analysis of behavioral variability and plasticity, we generated an initial draft assembly of the Bengalese finch genome from a single male animal to 151× coverage and an N50 of 3.0 MB. Furthermore, we developed an initial set of gene models using RNA-seq data from 8 samples that comprise liver, muscle, cerebellum, brainstem/midbrain, and forebrain tissue from juvenile and adult Bengalese finches of both sexes.

Conclusions

We provide a draft Bengalese finch genome and gene annotation to facilitate the study of the molecular-genetic influences on behavioral variability and the process of vocal learning. These data will directly support many avenues for the identification of genes involved in learning, including differential expression analysis, comparative genomic analysis (through comparison to existing avian genome assemblies), and derivation of genetic maps for linkage analysis. Bengalese finch gene models and sequences will be essential for subsequent manipulation (molecular or genetic) of genes and gene products, enabling novel mechanistic investigations into the role of variability in learned behavior.

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.

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.