ArticleFrontiers in computational neuroscience2015
A circular model for song motor control in Serinus canaria.
Article in Frontiers in computational neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Timing of Speech in Brain and Glottis and the Feedback Delay Problem in Motor Control.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Hidden neural states underlie canary song syntax.Nature · 2020Article
- The neurobiology of innate, volitional and learned vocalizations in mammals and birds.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Review
- Accelerated redevelopment of vocal skills is preceded by lasting reorganization of the song motor circuitry.eLife · 2019Article
- Nonlinear dynamics in the study of birdsong.Chaos (Woodbury, N.Y.) · 2017Article
- Temperature manipulation of neuronal dynamics in a forebrain motor control nucleus.PLoS computational biology · 2017Article
- From perception to action in songbird production: dynamics of a whole loop.Current opinion in systems biology · 2017Article
- Rhythmic syllable-related activity in a songbird motor thalamic nucleus necessary for learned vocalizations.PloS one · 2017Article
- Breathtaking Songs: Coordinating the Neural Circuits for Breathing and Singing.Physiology (Bethesda, Md.) · 2016Review
- An integrated model for motor control of song in Serinus canaria.Journal of physiology, Paris · 2016Article
- Average activity of excitatory and inhibitory neural populations.Chaos (Woodbury, N.Y.) · 2016Article
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5 authors.
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Abstract
Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture.
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