Evidence map›Paper›PMID 25324740›Full record

ArticleFrontiers in integrative neuroscience2014

A simple computational principle predicts vocal adaptation dynamics across age and error size.

Conor W Kelly, Samuel J Sober

Abstract read
In one paragraph

Article in Frontiers in integrative neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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 · 2018
    Article
  5. Article
  6. Article
  7. Dopaminergic Contributions to Vocal Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2016
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Conor W KellyDepartment of Biology, Emory University Atlanta, GA, USA.
Samuel J SoberDepartment of Biology, Emory University Atlanta, GA, USA.

Funding

Vocal motor control and sensorimotor learning - behavior, muscles, and neuronsR01NS084844 · NINDS · EMORY UNIVERSITY · PI SOBER, SAMUEL · 2013 to 2023
$3.8M
Systems and Computational Neuroscience at Emory UniversityP30NS069250 · NINDS · EMORY UNIVERSITY · PI CALABRESE, RONALD L · 2009 to 2010
$1.2M
NINDS NIH HHS P30 NS069250NINDS NIH HHS R01 NS084844
6 · The paper itself

Abstract

The brain uses sensory feedback to correct errors in behavior. Songbirds and humans acquire vocal behaviors by imitating the sounds produced by adults and rely on auditory feedback to correct vocal errors throughout their lifetimes. In both birds and humans, acoustic variability decreases steadily with age following the acquisition of vocal behavior. Prior studies in adults have shown that while sensory errors that fall within the limits of vocal variability evoke robust motor corrections, larger errors do not induce learning. Although such results suggest that younger animals, which have greater vocal variability, might correct large errors more readily than older individuals, it is unknown whether age-dependent changes in variability are accompanied by changes in the speed or magnitude of vocal error correction. We tested the hypothesis that auditory errors evoke greater vocal changes in younger animals and that a common computation determines how sensory information drives motor learning across different ages and error sizes. Consistent with our hypothesis, we found that in songbirds the speed and extent of error correction changes dramatically with age and that age-dependent differences in learning were predicted by a model in which the overlap between sensory errors and the distribution of prior sensory feedback determines the dynamics of adaptation. Our results suggest that the brain employs a simple and robust computational principle to calibrate the rate and magnitude of vocal adaptation across age-dependent changes in behavioral performance and in response to different sensory errors.

Indexed as

age-related changeserror correctionpitch-shiftsensorimotor adaptationsensorimotor integrationsongbirdvocal learning

Identifiers

PMID25324740
PMCPMC4178380

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.