A predisposed motor bias shapes individuality in vocal learning.

The development of individuality during learned behavior is a common trait observed across animal species; however, the underlying biological mechanisms remain understood. Similar to human speech, songbirds develop individually unique songs with species-specific traits through vocal learning. In this study, we investigate the developmental and molecular mechanisms underlying individuality in vocal learning by utilizing F1 hybrid songbirds (Taeniopygia guttata cross with Taeniopygia bichenovii), taking an integrating approach combining experimentally controlled systematic song tutoring, unbiased discriminant analysis of song features, and single-cell transcriptomics. When tutoring with songs from both parental species, F1 hybrid individuals exhibit evident diversity in their acquired songs. Approximately 30% of F1 hybrids selectively learn either song of the two parental species, while others develop merged songs that combine traits from both species. Vocal acoustic biases during vocal babbling initially appear as individual differences in songs among F1 juveniles and are maintained through the sensitive period of song vocal learning. These vocal acoustic biases emerge independently of the initial auditory experience of hearing the biological father's and passive tutored songs. We identify individual differences in transcriptional signatures in a subset of cell types, including the glutamatergic neurons projecting from the cortical vocal output nucleus to the hypoglossal nuclei, which are associated with variations of vocal acoustic features. These findings suggest that a genetically predisposed vocal motor bias serves as the initial origin of individual variation in vocal learning, influencing learning constraints and preferences.

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.

Familial bias and auditory feedback regulation of vocal babbling patterns during early song development.

Learned vocalizations are a crucial acoustic biosignal conveying individual traits in many species. Songbirds learn song patterns by listening to a tutor song and performing vocal practice during a sensitive developmental period. However, when and how individual differences in song patterns develop remain unknown. Here, we report that individual differences in vocal output exist even at the earliest song development stage, called subsong. Experiments involving the manipulation of both breeding pairs and song tutoring conditions revealed that the parental pair combination contributes to generating familial differences in syllable duration and variability in the subsong of offspring. Furthermore, after deafening, juveniles immediately changed their subsong by shortening the syllable durations but maintained the individual variability of their subsong temporal patterns, suggesting both auditory-sensitive modification and independent intrinsic regulation of vocal output. These results indicate that the temporal patterns of subsong are not merely disordered vocalization but are regulated by familial bias with sensitivity to auditory feedback, thus generating individual variability at the initiation of vocal development.

A quantitative method for analyzing species-specific vocal sequence pattern and its developmental dynamics.

BACKGROUND: Songbirds are a preeminent animal model for understanding the neural basis underlying the development and evolution of a complex learned behavior, bird song. However, only a few quantitative methods exist to analyze these species-specific sequential behaviors in multiple species using the same calculation method. NEW METHOD: We report a method of analysis that focuses on calculating the frequency of characteristic syllable transitions in songs. This method comprises two steps: The first step involves forming correlation matrices of syllable similarity scores, named syllable similarity matrices (SSMs); these are obtained by calculating the round-robin comparison of all the syllables in two songs, while maintaining the sequential order of syllables in the songs. In the second step, each occurrence rate of three patterns of binarized "2 rows×2 columns" cells in the SSMs is calculated to extract information on the characteristic syllable transitions. RESULTS: The SSM analysis method allowed obtaining species-specific features of song patterns and intraspecies individual variability simultaneously. Furthermore, it enabled quantitative tracking of the developmental trajectory of the syllable sequence patterns. COMPARISON WITH EXISTING METHOD: This method enables us to extract the species-specific song patterns and dissect the regulation of song syntax development without human-biased procedures for syllable identification. This method can be adapted to study the acoustic communication systems in several animal species, such as insects and mammals. CONCLUSIONS: This present method provides a comprehensive qualitative approach for understanding the regulation of species specificity and its development in vocal learning.