Difficulties when Assessing Birdsong Learning Programmes under Field Conditions: A Re-Evaluation of Song Repertoire Flexibility in the Great Tit

There is a remarkable diversity of song-learning strategies in songbirds. Establishing whether a species is closed- or open-ended is important to be able to interpret functional and evolutionary consequences of variation in repertoire size. Most of our knowledge regarding the timing of vocal learning is based on laboratory studies, despite the fact that these may not always replicate the complex ecological and social interactions experienced by birds in the wild. Given that field studies cannot provide the experimental control of laboratory studies, it may not be surprising that species such as the great tit that were initially assumed to be closed-ended learners have later been suggested to be open-ended learners. By using an established colour-ringed population, by following a standardized recording protocol, and by taking into account the species' song ecology (using only recordings obtained during peak of singing at dawn), we replicated two previous studies to assess song repertoire learning and flexibility in adult wild great tits elicited by social interactions. First, we performed a playback experiment to test repertoire plasticity elicited by novel versus own songs. Additionally, in a longitudinal study, we followed 30 males in two consecutive years and analysed whether new neighbours influenced any change in the repertoire. Contrary to the previous studies, song repertoire size and composition were found to be highly repeatable both between years and after confrontation with a novel song. Our results suggest that great tits are closed-ended learners and that their song repertoire probably does not change during adulthood. Methodological differences that may have led to an underestimation of the repertoires or population differences may explain the discrepancy in results with previous studies. We argue that a rigorous and standardized assessment of the repertoire is essential when studying age- or playback-induced changes in repertoire size and composition under field conditions

Rapid Effects of Hearing Song on Catecholaminergic Activity in the Songbird Auditory Pathway

Catecholaminergic (CA) neurons innervate sensory areas and affect the processing of sensory signals. For example, in birds, CA fibers innervate the auditory pathway at each level, including the midbrain, thalamus, and forebrain. We have shown previously that in female European starlings, CA activity in the auditory forebrain can be enhanced by exposure to attractive male song for one week. It is not known, however, whether hearing song can initiate that activity more rapidly. Here, we exposed estrogen-primed, female white-throated sparrows to conspecific male song and looked for evidence of rapid synthesis of catecholamines in auditory areas. In one hemisphere of the brain, we used immunohistochemistry to detect the phosphorylation of tyrosine hydroxylase (TH), a rate-limiting enzyme in the CA synthetic pathway. We found that immunoreactivity for TH phosphorylated at serine 40 increased dramatically in the auditory forebrain, but not the auditory thalamus and midbrain, after 15 min of song exposure. In the other hemisphere, we used high pressure liquid chromatography to measure catecholamines and their metabolites. We found that two dopamine metabolites, dihydroxyphenylacetic acid and homovanillic acid, increased in the auditory forebrain but not the auditory midbrain after 30 min of exposure to conspecific song. Our results are consistent with the hypothesis that exposure to a behaviorally relevant auditory stimulus rapidly induces CA activity, which may play a role in auditory responses

A reafferent and feed-forward model of song syntax generation in the Bengalese finch

Adult Bengalese finches generate a variable song that obeys a distinct and individual syntax. The syntax is gradually lost over a period of days after deafening and is recovered when hearing is restored. We present a spiking neuronal network model of the song syntax generation and its loss, based on the assumption that the syntax is stored in reafferent connections from the auditory to the motor control area. Propagating synfire activity in the HVC codes for individual syllables of the song and priming signals from the auditory network reduce the competition between syllables to allow only those transitions that are permitted by the syntax. Both imprinting of song syntax within HVC and the interaction of the reafferent signal with an efference copy of the motor command are sufficient to explain the gradual loss of syntax in the absence of auditory feedback. The model also reproduces for the first time experimental findings on the influence of altered auditory feedback on the song syntax generation, and predicts song- and species-specific low frequency components in the LFP. This study illustrates how sequential compositionality following a defined syntax can be realized in networks of spiking neurons

Unstable neurons underlie a stable learned behavior

Motor skills can be maintained for decades, but the biological basis of this memory persistence remains largely unknown. The zebra finch, for example, sings a highly stereotyped song that is stable for years, but it is not known whether the precise neural patterns underlying song are stable or shift from day to day. Here we demonstrate that the population of projection neurons coding for song in the premotor nucleus, HVC, change from day to day. The most dramatic shifts occur over intervals of sleep. In contrast to the transient participation of excitatory neurons, ensemble measurements dominated by inhibition persist unchanged even after damage to downstream motor nerves. These observations offer a principle of motor stability: spatiotemporal patterns of inhibition can maintain a stable scaffold for motor dynamics while the population of principal neurons that directly drive behavior shift from one day to the next

VoICE: A semi-automated pipeline for standardizing vocal analysis across models

The study of vocal communication in animal models provides key insight to the neurogenetic basis for speech and communication disorders. Current methods for vocal analysis suffer from a lack of standardization, creating ambiguity in cross-laboratory and cross-species comparisons. Here, we present VoICE (Vocal Inventory Clustering Engine), an approach to grouping vocal elements by creating a high dimensionality dataset through scoring spectral similarity between all vocalizations within a recording session. This dataset is then subjected to hierarchical clustering, generating a dendrogram that is pruned into meaningful vocalization “types” by an automated algorithm. When applied to birdsong, a key model for vocal learning, VoICE captures the known deterioration in acoustic properties that follows deafening, including altered sequencing. In a mammalian neurodevelopmental model, we uncover a reduced vocal repertoire of mice lacking the autism susceptibility gene, Cntnap2. VoICE will be useful to the scientific community as it can standardize vocalization analyses across species and laboratories