Familiarity of an environment prevents song suppression in isolated zebra finches.

Despite the wide use of zebra finches as an animal model to study vocal learning and production, little is known about impacts on their welfare caused by routine experimental manipulations such as changing their social context. Here we conduct a post-hoc analysis of singing rate, an indicator of positive welfare, to gain insights into stress caused by social isolation, a common experimental manipulation. We find that isolation in an unfamiliar environment reduces singing rate for several days, indicating the presence of an acute stressor.

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.

Learning the sound inventory of a complex vocal skill via an intrinsic reward.

Reinforcement learning (RL) is thought to underlie the acquisition of vocal skills like birdsong and speech, where sounding like one's "tutor" is rewarding. However, what RL strategy generates the rich sound inventories for song or speech? We find that the standard actor-critic model of birdsong learning fails to explain juvenile zebra finches' efficient learning of multiple syllables. However, when we replace a single actor with multiple independent actors that jointly maximize a common intrinsic reward, then birds' empirical learning trajectories are accurately reproduced.

Interactive extraction of diverse vocal units from a planar embedding without the need for prior sound segmentation.

Annotating and proofreading data sets of complex natural behaviors such as vocalizations are tedious tasks because instances of a given behavior need to be correctly segmented from background noise and must be classified with minimal false positive error rate. Low-dimensional embeddings have proven very useful for this task because they can provide a visual overview of a data set in which distinct behaviors appear in different clusters. However, low-dimensional embeddings introduce errors because they fail to preserve distances; and embeddings represent only objects of fixed dimensionality, which conflicts with vocalizations that have variable dimensions stemming from their variable durations.

Sensory substitution reveals a manipulation bias.

Sensory substitution is a promising therapeutic approach for replacing a missing or diseased sensory organ by translating inaccessible information into another sensory modality. However, many substitution systems are not well accepted by subjects. To explore the effect of sensory substitution on voluntary action repertoires and their associated affective valence, we study deaf songbirds to which we provide visual feedback as a substitute of auditory feedback.

Fast Retrograde Access to Projection Neuron Circuits Underlying Vocal Learning in Songbirds.

Understanding the structure and function of neural circuits underlying speech and language is a vital step toward better treatments for diseases of these systems. Songbirds, among the few animal orders that share with humans the ability to learn vocalizations from a conspecific, have provided many insights into the neural mechanisms of vocal development. However, research into vocal learning circuits has been hindered by a lack of tools for rapid genetic targeting of specific neuron populations to meet the quick pace of developmental learning.

Undirected singing rate as a non-invasive tool for welfare monitoring in isolated male zebra finches.

Research on the songbird zebra finch (Taeniopygia guttata) has advanced our behavioral, hormonal, neuronal, and genetic understanding of vocal learning. However, little is known about the impact of typical experimental manipulations on the welfare of these birds. Here we explore whether the undirected singing rate can be used as an indicator of welfare.

Nearest neighbours reveal fast and slow components of motor learning.

Changes in behaviour resulting from environmental influences, development and learning are commonly quantified on the basis of a few hand-picked features (for example, the average pitch of acoustic vocalizations), assuming discrete classes of behaviours (such as distinct vocal syllables). However, such methods generalize poorly across different behaviours and model systems and may miss important components of change. Here we present a more-general account of behavioural change that is based on nearest-neighbour statistics, and apply it to song development in a songbird, the zebra finch.

Tissue Clearing and Light Sheet Microscopy: Imaging the Unsectioned Adult Zebra Finch Brain at Cellular Resolution.

The inherent complexity of brain tissue, with brain cells intertwining locally and projecting to distant regions, has made three-dimensional visualization of intact brains a highly desirable but challenging task in neuroscience. The natural opaqueness of tissue has traditionally limited researchers to techniques short of single cell resolution such as computer tomography or magnetic resonance imaging. By contrast, techniques with single-cell resolution required mechanical slicing into thin sections, which entails tissue distortions that severely hinder accurate reconstruction of large volumes.

Expansion Light Sheet Microscopy Resolves Subcellular Structures in Large Portions of the Songbird Brain.

Expansion microscopy and light sheet imaging (ExLSM) provide a viable alternative to existing tissue clearing and large volume imaging approaches. The analysis of intact volumes of brain tissue presents a distinct challenge in neuroscience. Recent advances in tissue clearing and light sheet microscopy have re-addressed this challenge and blossomed into a plethora of protocols with diverse advantages and disadvantages.

Learning auditory discriminations from observation is efficient but less robust than learning from experience.

Social learning enables complex societies. However, it is largely unknown how insights obtained from observation compare with insights gained from trial-and-error, in particular in terms of their robustness. Here, we use aversive reinforcement to train "experimenter" zebra finches to discriminate between auditory stimuli in the presence of an "observer" finch.

Author Correction: Deep sleep maintains learning efficiency of the human brain.

This corrects the article DOI: 10.1038/ncomms15405.

Songbirds work around computational complexity by learning song vocabulary independently of sequence.

While acquiring motor skills, animals transform their plastic motor sequences to match desired targets. However, because both the structure and temporal position of individual gestures are adjustable, the number of possible motor transformations increases exponentially with sequence length. Identifying the optimal transformation towards a given target is therefore a computationally intractable problem.

Deep sleep maintains learning efficiency of the human brain.

It is hypothesized that deep sleep is essential for restoring the brain's capacity to learn efficiently, especially in regions heavily activated during the day. However, causal evidence in humans has been lacking due to the inability to sleep deprive one target area while keeping the natural sleep pattern intact. Here we introduce a novel approach to focally perturb deep sleep in motor cortex, and investigate the consequences on behavioural and neurophysiological markers of neuroplasticity arising from dedicated motor practice.

A Bayesian Account of Vocal Adaptation to Pitch-Shifted Auditory Feedback.

Motor systems are highly adaptive. Both birds and humans compensate for synthetically induced shifts in the pitch (fundamental frequency) of auditory feedback stemming from their vocalizations. Pitch-shift compensation is partial in the sense that large shifts lead to smaller relative compensatory adjustments of vocal pitch than small shifts.

A Neural Code That Is Isometric to Vocal Output and Correlates with Its Sensory Consequences.

What cortical inputs are provided to motor control areas while they drive complex learned behaviors? We study this question in the nucleus interface of the nidopallium (NIf), which is required for normal birdsong production and provides the main source of auditory input to HVC, the driver of adult song. In juvenile and adult zebra finches, we find that spikes in NIf projection neurons precede vocalizations by several tens of milliseconds and are insensitive to distortions of auditory feedback. We identify a local isometry between NIf output and vocalizations: quasi-identical notes produced in different syllables are preceded by highly similar NIf spike patterns.

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.

Linear Methods for Efficient and Fast Separation of Two Sources Recorded with a Single Microphone.

This letter addresses the problem of separating two speakers from a single microphone recording. Three linear methods are tested for source separation, all of which operate directly on sound spectrograms: (1) eigenmode analysis of covariance difference to identify spectro-temporal features associated with large variance for one source and small variance for the other source; (2) maximum likelihood demixing in which the mixture is modeled as the sum of two gaussian signals and maximum likelihood is used to identify the most likely sources; and (3) suppression-regression, in which autoregressive models are trained to reproduce one source and suppress the other. These linear approaches are tested on the problem of separating a known male from a known female speaker.

Reconstruction of vocal interactions in a group of small songbirds.

The main obstacle for investigating vocal interactions in vertebrates is the difficulty of discriminating individual vocalizations of rapidly moving, sometimes simultaneously vocalizing individuals. We developed a method of recording and analyzing individual vocalizations in free-ranging animals using ultraminiature back-attached sound and acceleration recorders. Our method allows the separation of zebra finch vocalizations irrespective of background noise and the number of vocalizing animals nearby.

A higher sensory brain region is involved in reversing reinforcement-induced vocal changes in a songbird.

Many animals exhibit flexible behaviors that they can adjust to increase reward or avoid harm (learning by positive or aversive reinforcement). But what neural mechanisms allow them to restore their original behavior (motor program) after reinforcement is withdrawn? One possibility is that motor restoration relies on brain areas that have a role in memorization but no role in either motor production or in sensory processing relevant for expressing the behavior and its refinement. We investigated the role of a higher auditory brain area in the songbird for modifying and restoring the stereotyped adult song.

Evidence for a causal inverse model in an avian cortico-basal ganglia circuit.

Learning by imitation is fundamental to both communication and social behavior and requires the conversion of complex, nonlinear sensory codes for perception into similarly complex motor codes for generating action. To understand the neural substrates underlying this conversion, we study sensorimotor transformations in songbird cortical output neurons of a basal-ganglia pathway involved in song learning. Despite the complexity of sensory and motor codes, we find a simple, temporally specific, causal correspondence between them.

Dynamic alignment models for neural coding.

Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH).

Activity in a premotor cortical nucleus of zebra finches is locally organized and exhibits auditory selectivity in neurons but not in glia.

Motor functions are often guided by sensory experience, most convincingly illustrated by complex learned behaviors. Key to sensory guidance in motor areas may be the structural and functional organization of sensory inputs and their evoked responses. We study sensory responses in large populations of neurons and neuron-assistive cells in the songbird motor area HVC, an auditory-vocal brain area involved in sensory learning and in adult song production.

At the interface of the auditory and vocal motor systems: NIf and its role in vocal processing, production and learning.

Communication between auditory and vocal motor nuclei is essential for vocal learning. In songbirds, the nucleus interfacialis of the nidopallium (NIf) is part of a sensorimotor loop, along with auditory nucleus avalanche (Av) and song system nucleus HVC, that links the auditory and song systems. Most of the auditory information comes through this sensorimotor loop, with the projection from NIf to HVC representing the largest single source of auditory information to the song system.

An efficient coding hypothesis links sparsity and selectivity of neural responses.

To what extent are sensory responses in the brain compatible with first-order principles? The efficient coding hypothesis projects that neurons use as few spikes as possible to faithfully represent natural stimuli. However, many sparsely firing neurons in higher brain areas seem to violate this hypothesis in that they respond more to familiar stimuli than to nonfamiliar stimuli. We reconcile this discrepancy by showing that efficient sensory responses give rise to stimulus selectivity that depends on the stimulus-independent firing threshold and the balance between excitatory and inhibitory inputs.