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 ().

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.

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.

Songbirds can learn flexible contextual control over syllable sequencing.

The flexible control of sequential behavior is a fundamental aspect of speech, enabling endless reordering of a limited set of learned vocal elements (syllables or words). Songbirds are phylogenetically distant from humans but share both the capacity for vocal learning and neural circuitry for vocal control that includes direct pallial-brainstem projections. Based on these similarities, we hypothesized that songbirds might likewise be able to learn flexible, moment-by-moment control over vocalizations.

Cellular transcriptomics reveals evolutionary identities of songbird vocal circuits.

Birds display advanced behaviors, including vocal learning and problem-solving, yet lack a layered neocortex, a structure associated with complex behavior in mammals. To determine whether these behavioral similarities result from shared or distinct neural circuits, we used single-cell RNA sequencing to characterize the neuronal repertoire of the songbird song motor pathway. Glutamatergic vocal neurons had considerable transcriptional similarity to neocortical projection neurons; however, they displayed regulatory gene expression patterns more closely related to neurons in the ventral pallium.

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.

Learning is enhanced by tailoring instruction to individual genetic differences.

It is widely argued that personalized instruction based on individual differences in learning styles or genetic predispositions could improve learning outcomes. However, this proposition has resisted clear demonstration in human studies, where it is difficult to control experience and quantify outcomes. Here, we take advantage of the tractable nature of vocal learning in songbirds () to test the idea that matching instruction to individual genetic predispositions can enhance learning.

The Avian Basal Ganglia Are a Source of Rapid Behavioral Variation That Enables Vocal Motor Exploration.

The basal ganglia (BG) participate in aspects of reinforcement learning that require evaluation and selection of motor programs associated with improved performance. However, whether the BG additionally contribute to behavioral variation ("motor exploration") that forms the substrate for such learning remains unclear. In songbirds, a tractable system for studying BG-dependent skill learning, a role for the BG in generating exploratory variability, has been challenged by the finding that lesions of Area X, the song-specific component of the BG, have no lasting effects on several forms of vocal variability that have been studied.

Zebra finches are sensitive to combinations of temporally distributed features in a model of word recognition.

Discrimination between spoken words composed of overlapping elements, such as "captain" and "captive," relies on sensitivity to unique combinations of prefix and suffix elements that span a "uniqueness point" where the word candidates diverge. To model such combinatorial processing, adult female zebra finches were trained to discriminate between target and distractor syllable sequences that shared overlapping "contextual" prefixes and differed only in their "informative" suffixes. The transition from contextual to informative syllables thus created a uniqueness point analogous to that present between overlapping word candidates, where targets and distractors diverged.

An automated approach to the quantitation of vocalizations and vocal learning in the songbird.

Studies of learning mechanisms critically depend on the ability to accurately assess learning outcomes. This assessment can be impeded by the often complex, multidimensional nature of behavior. We present a novel, automated approach to evaluating imitative learning.

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.

Genetic variation interacts with experience to determine interindividual differences in learned song.

Learning reflects the influence of experience on genetically determined circuitry, but little is known about how experience and genetics interact to determine complex learned phenotypes. Here, we used vocal learning in songbirds to study how experience and genetics contribute to interindividual differences in learned song. Previous work has established that such differences in song within a species depend on learning, but in principle some of these differences could also depend on genetic variation.

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.

Discrete Circuits Support Generalized versus Context-Specific Vocal Learning in the Songbird.

Motor skills depend on the reuse of individual gestures in multiple sequential contexts (e.g., a single phoneme in different words).

Timing during transitions in Bengalese finch song: implications for motor sequencing.

To investigate mechanisms of action sequencing, we examined the relationship between timing and sequencing of syllables in Bengalese finch song. An individual's song comprises acoustically distinct syllables organized into probabilistic sequences: a given syllable potentially can transition to several different syllables (divergence points), and several different syllables can transition to a given syllable (convergence points). In agreement with previous studies, we found that more probable transitions at divergence points occur with shorter intersyllable gaps.

Auditory-induced neural dynamics in sensory-motor circuitry predict learned temporal and sequential statistics of birdsong.

Predicting future events is a critical computation for both perception and behavior. Despite the essential nature of this computation, there are few studies demonstrating neural activity that predicts specific events in learned, probabilistic sequences. Here, we test the hypotheses that the dynamics of internally generated neural activity are predictive of future events and are structured by the learned temporal-sequential statistics of those events.

An Adapting Auditory-motor Feedback Loop Can Contribute to Generating Vocal Repetition.

Consecutive repetition of actions is common in behavioral sequences. Although integration of sensory feedback with internal motor programs is important for sequence generation, if and how feedback contributes to repetitive actions is poorly understood. Here we study how auditory feedback contributes to generating repetitive syllable sequences in songbirds.

Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences.

The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood.

Neural encoding and integration of learned probabilistic sequences in avian sensory-motor circuitry.

Many complex behaviors, such as human speech and birdsong, reflect a set of categorical actions that can be flexibly organized into variable sequences. However, little is known about how the brain encodes the probabilities of such sequences. Behavioral sequences are typically characterized by the probability of transitioning from a given action to any subsequent action (which we term "divergence probability").

Translating birdsong: songbirds as a model for basic and applied medical research.

Songbirds, long of interest to basic neuroscience, have great potential as a model system for translational neuroscience. Songbirds learn their complex vocal behavior in a manner that exemplifies general processes of perceptual and motor skill learning and, more specifically, resembles human speech learning. Song is subserved by circuitry that is specialized for vocal learning and production but that has strong similarities to mammalian brain pathways.

Vocal learning is constrained by the statistics of sensorimotor experience.

The brain uses sensory feedback to correct behavioral errors. Larger errors by definition require greater corrections, and many models of learning assume that larger sensory feedback errors drive larger motor changes. However, an alternative perspective is that larger errors drive learning less effectively because such errors fall outside the range of errors normally experienced and are therefore unlikely to reflect accurate feedback.

Variable sequencing is actively maintained in a well learned motor skill.

Variation in sequencing of actions occurs in many natural behaviors, yet how such variation is maintained is poorly understood. We investigated maintenance of sequence variation in adult Bengalese finch song, a learned skill with rendition-to-rendition variation in the sequencing of discrete syllables (i.e.

Covert skill learning in a cortical-basal ganglia circuit.

We learn complex skills such as speech and dance through a gradual process of trial and error. Cortical-basal ganglia circuits have an important yet unresolved function in this trial-and-error skill learning; influential 'actor-critic' models propose that basal ganglia circuits generate a variety of behaviours during training and learn to implement the successful behaviours in their repertoire. Here we show that the anterior forebrain pathway (AFP), a cortical-basal ganglia circuit, contributes to skill learning even when it does not contribute to such 'exploratory' variation in behavioural performance during training.