Abstract:In songbirds, learning to sing is a highly social process that likely involves social reward. Here, we tested the hypothesis that during song learning, the reward value of hearing a particular song predicts the degree to which that song will ultimately be learned. We measured the early song preferences of young male zebra finches (Taeniopygia guttata) in an operant key-pressing assay; each of two keys was associated with a higher likelihood of playing the song of the father or that of another familiar adult (“… Show more
“…Across species, songs are composed of hierarchically-organized acoustic units; notes are grouped to form “syllables,” and sequences of syllables form song 32 – 39 . Quantitative studies of estrildid song have largely focused on one or two species 13 , 30 – 33 , 36 – 38 , 40 , and either composite measures 41 – 44 or individual features, such as fundamental frequency 45 , 46 . Figure 1 Phylogeny, sample spectrograms of song, and frequency power spectra of each species’ song in the 7 studied species.…”
Birdsong is a longstanding model system for studying evolution and biodiversity. Here, we collected and analyzed high quality song recordings from seven species in the family Estrildidae. We measured the acoustic features of syllables and then used dimensionality reduction and machine learning classifiers to identify features that accurately assigned syllables to species. Species differences were captured by the first 3 principal components, corresponding to basic frequency, power distribution, and spectrotemporal features. We then identified the measured features underlying classification accuracy. We found that fundamental frequency, mean frequency, spectral flatness, and syllable duration were the most informative features for species identification. Next, we tested whether specific acoustic features of species’ songs predicted phylogenetic distance. We found significant phylogenetic signal in syllable frequency features, but not in power distribution or spectrotemporal features. Results suggest that frequency features are more constrained by species’ genetics than are other features, and are the best signal features for identifying species from song recordings. The absence of phylogenetic signal in power distribution and spectrotemporal features suggests that these song features are labile, reflecting learning processes and individual recognition.
“…Across species, songs are composed of hierarchically-organized acoustic units; notes are grouped to form “syllables,” and sequences of syllables form song 32 – 39 . Quantitative studies of estrildid song have largely focused on one or two species 13 , 30 – 33 , 36 – 38 , 40 , and either composite measures 41 – 44 or individual features, such as fundamental frequency 45 , 46 . Figure 1 Phylogeny, sample spectrograms of song, and frequency power spectra of each species’ song in the 7 studied species.…”
Birdsong is a longstanding model system for studying evolution and biodiversity. Here, we collected and analyzed high quality song recordings from seven species in the family Estrildidae. We measured the acoustic features of syllables and then used dimensionality reduction and machine learning classifiers to identify features that accurately assigned syllables to species. Species differences were captured by the first 3 principal components, corresponding to basic frequency, power distribution, and spectrotemporal features. We then identified the measured features underlying classification accuracy. We found that fundamental frequency, mean frequency, spectral flatness, and syllable duration were the most informative features for species identification. Next, we tested whether specific acoustic features of species’ songs predicted phylogenetic distance. We found significant phylogenetic signal in syllable frequency features, but not in power distribution or spectrotemporal features. Results suggest that frequency features are more constrained by species’ genetics than are other features, and are the best signal features for identifying species from song recordings. The absence of phylogenetic signal in power distribution and spectrotemporal features suggests that these song features are labile, reflecting learning processes and individual recognition.
“…Animals use species-speci c sounds to exchange social information in complex notes are grouped to form "syllables," and sequences of syllables form song [39][40][41][42][43][44][45][46]. Quantitative studies of estrildid song have largely focused on one or two species [13,[37][38][39][40][43][44][45]47], and either composite measures [48][49][50][51] or individual features, such as fundamental frequency [52,53].…”
Birdsong is a longstanding model system for studying evolution, and has recently emerged as a measure of biodiversity loss due to deforestation and climate change. Here, we collected and analyzed high quality song recordings from seven species in the family Estrildidae. We measured the acoustic features of syllables and then used dimensionality reduction and machine learning classifiers to identify features that accurately assigned syllables to species. Species differences were captured by the first 3 principal components, corresponding to basic spectral features, spectral shape, and spectrotemporal features. We then identified the measured features underlying classification accuracy. We found that fundamental frequency, mean frequency, spectral flatness, and syllable duration were the most informative features for species identification. Next, we tested whether specific acoustic features of species’ songs predicted phylogenetic distance. We found significant phylogenetic signal in syllable spectral features, but not in spectral shape or spectrotemporal features. Results indicate that spectral features are more constrained by species’ genetics than are other features, and are the best signal features for identifying species from song recordings. The absence of phylogenetic signal in spectral shape and spectrotemporal features suggests that these song features are labile, reflecting learning-processes and individual recognition.
“…This choice is clearly based on social, not genetic, factors, as young birds will copy the song of a foster father even when the biological father can be heard in the same room 7 . Even before they begin to sing, juvenile male zebra finches form strong preferences for the song of their adult male caregiver 8 , 9 . Young birds will key-press more to hear the song of their chosen tutor than to hear another familiar male, and the magnitude of this preference predicts how well that song will be learned 8 .…”
Section: Introductionmentioning
confidence: 99%
“…Even before they begin to sing, juvenile male zebra finches form strong preferences for the song of their adult male caregiver 8 , 9 . Young birds will key-press more to hear the song of their chosen tutor than to hear another familiar male, and the magnitude of this preference predicts how well that song will be learned 8 . These studies represent only a small fraction of a large literature suggesting that the mechanisms underlying song learning may share features in common with human vocal development—namely that song learning relies on social reward.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, the role of oxytocin in attraction to social cues may be conserved across species and developmental stages. Accordingly, we and others have hypothesized that, in songbirds, oxytocin receptors (OTR) mediate attraction and attention to tutor song, thus facilitating song learning 1 , 8 , 18 – 21 .…”
In species with vocal learning, acquiring species-typical vocalizations relies on early social orienting. In songbirds, for example, learning song requires dynamic social interactions with a “tutor” during an early sensitive period. Here, we hypothesized that the attentional and motivational processes that support song learning recruit the oxytocin system, which is well-understood to play a role in social orienting in other species. Juvenile male zebra finches naïve to song were each tutored by two unfamiliar adult males. Before exposure to one tutor, juveniles were injected subcutaneously with oxytocin receptor antagonist (OTA; ornithine vasotocin) and before exposure to the other, saline (control). Treatment with OTA reduced behaviors associated with approach and attention during tutoring sessions. Using a novel operant paradigm to measure preference while balancing exposure to the two tutor songs, we showed that the juveniles preferred to hear the song of the control tutor. Their adult songs more closely resembled the control tutor’s song, and the magnitude of this difference was predicted by early preference for control over OTA song. Overall, oxytocin antagonism during exposure to a tutor seemed to bias juveniles against that tutor and his song. Our results suggest that oxytocin receptors are important for socially-guided vocal learning.
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