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

Experimentally elevated corticosterone increases song output and complexity in common mynas

Vocalization is an important communication tool that can reflect many aspects of an individual's internal and external condition. This is especially true for birds. Previous research has shown that bird calls and songs change in response to a variety of potential stressors, although the extent and direction of the changes depend on the nature of the stressor and the environment. Circulating glucocorticoids, such as corticosterone, often increase in response to stressors and mediate some of the observed changes via alterations of the individual's physiological state. Acute elevations of corticosterone often occur as a physiological response to short-term stressors; however, the effects of this elevation on adult vocalizations have not been well documented. Here, we experimentally elevated corticosterone at two different levels using a noninvasive method and examined the effects on the vocal communication of male and female adult common mynas (Acridotheres tristis). Corticosterone elevation temporarily increased song output and some measures of song complexity, while call output decreased. These effects were dosage dependent (higher corticosterone levels had a stronger effect), most evident 40 min after ingestion, and some vocal changes were sex-specific. Future studies should investigate whether the changes in vocal performance due to elevated glucocorticoids have consequences for the birds' behavior, reproductive success, and survival.

Neural population dynamics in songbird RA and HVC during learned motor-vocal behavior

Complex, learned motor behaviors involve the coordination of large-scale neural activity across multiple brain regions, but our understanding of the population-level dynamics within different regions tied to the same behavior remains limited. Here, we investigate the neural population dynamics underlying learned vocal production in awake-singing songbirds. We use Neuropixels probes to record the simultaneous extracellular activity of populations of neurons in two regions of the vocal motor pathway. In line with observations made in non-human primates during limb-based motor tasks, we show that the population-level activity in both the premotor nucleus HVC and the motor nucleus RA is organized on low-dimensional neural manifolds upon which coordinated neural activity is well described by temporally structured trajectories during singing behavior. Both the HVC and RA latent trajectories provide relevant information to predict vocal sequence transitions between song syllables. However, the dynamics of these latent trajectories differ between regions. Our state-space models suggest a unique and continuous-over-time correspondence between the latent space of RA and vocal output, whereas the corresponding relationship for HVC exhibits a higher degree of neural variability. We then demonstrate that comparable high-fidelity reconstruction of continuous vocal outputs can be achieved from HVC and RA neural latents and spiking activity. Unlike those that use spiking activity, however, decoding models using neural latents generalize to novel sub-populations in each region, consistent with the existence of preserved manifolds that confine vocal-motor activity in HVC and RA.

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.

Distinct patterns of activity within columns of the periaqueductal gray are associated with functionally distinct birdsongs

Male songbirds produce female-directed songs in spring that convey a state of sexual motivation. Many songbirds also sing in fall flocks in affiliative/gregarious contexts in which song is linked to an intrinsic positive affective state. The periaqueductal gray (PAG) in mammals, which is organized into functional columns, integrates information from multiple brain regions and relays this information to vocal motor areas so that an animal emits a vocal signal reflective of its affective state. Here, we test the hypothesis that distinct columns in the songbird PAG play roles in the distinct affective states communicated by sexually motivated and gregarious song. We quantified the numbers of immediate early gene ZENK-positive cells in 16 PAG subregions in male European starlings (Sturnus vulgaris) after singing gregarious or sexually motivated song. Results suggest that distinct PAG columns in songbirds context-specifically regulate song, agonistic, and courtship behaviors. A second exploratory, functional tract-tracing study also demonstrated that inputs to the PAG from specific subregions of the medial preoptic nucleus may contribute to gregarious song and behaviors indicative of social dominance. Together, findings suggest that conserved PAG columns and inputs from the preoptic nucleus may play a role in context-specific vocal and other social behaviors.

Beyond the three-chamber test: toward a multimodal and objective assessment of social behavior in rodents

MAIN: In recent years, substantial advances in social neuroscience have been realized, including the generation of numerous rodent models of autism spectrum disorder. Still, it can be argued that those methods currently being used to analyze animal social behavior create a bottleneck that significantly slows down progress in this field. Indeed, the bulk of research still relies on a small number of simple behavioral paradigms, the results of which are assessed without considering behavioral dynamics. Moreover, only few variables are examined in each paradigm, thus overlooking a significant portion of the complexity that characterizes social interaction between two conspecifics, subsequently hindering our understanding of the neural mechanisms governing different aspects of social behavior. We further demonstrate these constraints by discussing the most commonly used paradigm for assessing rodent social behavior, the three-chamber test. We also point to the fact that although emotions greatly influence human social behavior, we lack reliable means for assessing the emotional state of animals during social tasks. As such, we also discuss current evidence supporting the existence of pro-social emotions and emotional cognition in animal models. We further suggest that adequate social behavior analysis requires a novel multimodal approach that employs automated and simultaneous measurements of multiple behavioral and physiological variables at high temporal resolution in socially interacting animals. We accordingly describe several computerized systems and computational tools for acquiring and analyzing such measurements. Finally, we address several behavioral and physiological variables that can be used to assess socio-emotional states in animal models and thus elucidate intricacies of social behavior so as to attain deeper insight into the brain mechanisms that mediate such behaviors. CONCLUSIONS: In summary, we suggest that combining automated multimodal measurements with machine-learning algorithms will help define socio-emotional states and determine their dynamics during various types of social tasks, thus enabling a more thorough understanding of the complexity of social behavior.

Birdsong and the Neural Regulation of Positive Emotion

Birds are not commonly admired for emotional expression, and when they are, the focus is typically on negative states; yet vocal behavior is considered a direct reflection of an individual's emotional state. Given that over 4000 species of songbird produce learned, complex, context-specific vocalizations, we make the case that songbirds are conspicuously broadcasting distinct positive emotional states and that hearing songs can also induce positive states in other birds. Studies are reviewed that demonstrate that that the production of sexually motivated song reflects an emotional state of anticipatory reward-seeking (i.e., mate-seeking), while outside the mating context song in gregarious flocks reflects a state of intrinsic reward. Studies are also reviewed that demonstrate that hearing song induces states of positive anticipation and reward. This review brings together numerous studies that highlight a potentially important role for the songbird nucleus accumbens, a region nearly synonymous with reward in mammals, in positive emotional states that underlie singing behavior and responses to song. It is proposed that the nucleus accumbens is part of an evolutionarily conserved circuitry that contributes context-dependently to positive emotional states that motivate and reward singing behavior and responses to song. Neural mechanisms that underlie basic emotions appear to be conserved and similar across vertebrates. Thus, these findings in songbirds have the potential to provide insights into interventions that can restore positive social interactions disrupted by mental health disorders in humans.

Using seasonality and birdsong to understand mechanisms underlying context-appropriate shifts in social motivation and reward

Social motivation and reward are dynamic and flexible, shifting adaptively across contexts to meet changing social demands. This is exceptionally apparent when seasonal contexts are considered in seasonally breeding songbirds as they cycle from periods of sexual motivation and reward during the breeding season to periods of extreme gregariousness outside the breeding season when non-sexual social interactions gain reward value, motivating birds to form flocks. Here we review evidence demonstrating a key integrative role for the medial preoptic area (mPOA) in the seasonally-appropriate adjustment of behaviors, with seasonal changes in dopamine activity in mPOA adjusting social motivation and changes in opioid activity modifying social reward. Experiments demonstrate that dramatic seasonal fluctuations in steroid hormone concentrations alter patterns of opioid- and dopamine-related protein and gene expression in mPOA to modify social motivation and reward to meet seasonal changes in social demands. These studies of birdsong and seasonality provide new insights into neural and endocrine mechanisms underlying adaptive changes in social motivation and reward and highlight an underappreciated, evolutionarily conserved role for the mPOA in important social behaviors in non-reproductive contexts.

Neurally driven synthesis of learned, complex vocalizations

Brain machine interfaces (BMIs) hold promise to restore impaired motor function and serve as powerful tools to study learned motor skill. While limb-based motor prosthetic systems have leveraged nonhuman primates as an important animal model,^1-4 speech prostheses lack a similar animal model and are more limited in terms of neural interface technology, brain coverage, and behavioral study design.^5-7 Songbirds are an attractive model for learned complex vocal behavior. Birdsong shares a number of unique similarities with human speech,^8-10 and its study has yielded general insight into multiple mechanisms and circuits behind learning, execution, and maintenance of vocal motor skill.^11-18 In addition, the biomechanics of song production bear similarity to those of humans and some nonhuman primates.^19-23 Here, we demonstrate a vocal synthesizer for birdsong, realized by mapping neural population activity recorded from electrode arrays implanted in the premotor nucleus HVC onto low-dimensional compressed representations of song, using simple computational methods that are implementable in real time. Using a generative biomechanical model of the vocal organ (syrinx) as the low-dimensional target for these mappings allows for the synthesis of vocalizations that match the bird's own song. These results provide proof of concept that high-dimensional, complex natural behaviors can be directly synthesized from ongoing neural activity. This may inspire similar approaches to prosthetics in other species by exploiting knowledge of the peripheral systems and the temporal structure of their output.