Context-dependent sensory modulation underlies Bayesian vocal sequence perception

T Sainburg, TS McPherson, EM Arneodo, S Rudraraju… - bioRxiv, 2022 - biorxiv.org
bioRxiv, 2022biorxiv.org
Vocal communication in both songbirds and humans relies on categorical perception of
smoothly varying acoustic spaces. Vocal perception can be biased by expectation and
context, but the mechanisms of this bias are not well understood. We developed a
behavioral task in which songbirds, European starlings, are trained to to classify smoothly
varying song syllables in the context of predictive syllable sequences. We find that syllable-
sequence predictability biases perceptual categorization following a Bayesian model of …
Vocal communication in both songbirds and humans relies on categorical perception of smoothly varying acoustic spaces. Vocal perception can be biased by expectation and context, but the mechanisms of this bias are not well understood. We developed a behavioral task in which songbirds, European starlings, are trained to to classify smoothly varying song syllables in the context of predictive syllable sequences. We find that syllable-sequence predictability biases perceptual categorization following a Bayesian model of probabilistic information integration. We then recorded from populations of neurons in the auditory forebrain while birds actively categorized song syllables, observing large proportions of neurons that track the smoothly varying natural feature space of syllable categories. We observe that predictive information in the syllable sequences dynamically modulates sensory neural representations. These results support a Bayesian model of perception where predictive information acts to dynamically reallocate sensory neural resources, sharpening acuity (i.e. the likelihood) in high-probability regions of stimulus space.
One-Sentence Summary
Predictive information in vocal sequences biases Bayesian categorical perception through rapid sensory reorganization.
Graphical Abstract
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