ArticlePloS one2017
A Bayesian Account of Vocal Adaptation to Pitch-Shifted Auditory Feedback.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Spontaneous variability predicts compensative motor response in vocal pitch control.Scientific reports · 2022Article
- The Role of the Dorsolateral Prefrontal Cortex for Speech and Language Processing.Frontiers in human neuroscience · 2021Article
- Chance, long tails, and inference in a non-Gaussian, Bayesian theory of vocal learning in songbirds.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- What drives the perceptual change resulting from speech motor adaptation? Evaluation of hypotheses in a Bayesian modeling framework.PLoS computational biology · 2018Article
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2 authors.
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Abstract
Motor systems are highly adaptive. Both birds and humans compensate for synthetically induced shifts in the pitch (fundamental frequency) of auditory feedback stemming from their vocalizations. Pitch-shift compensation is partial in the sense that large shifts lead to smaller relative compensatory adjustments of vocal pitch than small shifts. Also, compensation is larger in subjects with high motor variability. To formulate a mechanistic description of these findings, we adapt a Bayesian model of error relevance. We assume that vocal-auditory feedback loops in the brain cope optimally with known sensory and motor variability. Based on measurements of motor variability, optimal compensatory responses in our model provide accurate fits to published experimental data. Optimal compensation correctly predicts sensory acuity, which has been estimated in psychophysical experiments as just-noticeable pitch differences. Our model extends the utility of Bayesian approaches to adaptive vocal behaviors.
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