Evidence map›Paper›PMID 26052304›Full record

ArticleFrontiers in psychology2015

Enhanced cognitive and perceptual processing: a computational basis for the musician advantage in speech learning.

Kirsten E Smayda, Bharath Chandrasekaran, W Todd Maddox

Abstract read
In one paragraph

Article in Frontiers in psychology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. The nature of non-native speech sound representations.The Journal of the Acoustical Society of America · 2022
    Review
  4. Auditory and visual category learning in musicians and nonmusicians.Journal of experimental psychology. General · 2022
    Article
  5. Article
  6. Acoustic noise and vision differentially warp the auditory categorization of speech.The Journal of the Acoustical Society of America · 2019
    Article
  7. Article
  8. Article
  9. Performance Pressure Enhances Speech Learning.Applied psycholinguistics · 2016
    Article
  10. Article
  11. 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

3 authors.

Kirsten E SmaydaDepartment of Psychology, The University of Texas at Austin Austin, TX USA.
Bharath ChandrasekaranDepartment of Psychology, The University of Texas at Austin Austin, TX USA ; Department of Communication Sciences and Disorders, The University of Texas at Austin Austin, TX USA.
W Todd MaddoxDepartment of Psychology, The University of Texas at Austin Austin, TX USA.

Funding

Supplement to cortical contributions to frequency-following response generation and modulationR01DC013315 · NIDCD · UNIVERSITY OF TEXAS AT AUSTIN · PI ABEL, TAYLOR JOHN, CHANDRASEKARAN, BHARATH · 2014 to 2025
$5.5M
Genetic Influences on Dual Processing Modes of Reward and Punishment LearningR01DA032457 · NIDA · UNIVERSITY OF TEXAS AT AUSTIN · PI BEEVERS, CHRISTOPHER G · 2012 to 2016
$2.2M
NIDA NIH HHS R01 DA032457NIDCD NIH HHS R01 DC013315
6 · The paper itself

Abstract

Long-term music training can positively impact speech processing. A recent framework developed to explain such cross-domain plasticity posits that music training-related advantages in speech processing are due to shared cognitive and perceptual processes between music and speech. Although perceptual and cognitive processing advantages due to music training have been independently demonstrated, to date no study has examined perceptual and cognitive processing within the context of a single task. The present study examines the impact of long-term music training on speech learning from a rigorous, computational perspective derived from signal detection theory. Our computational models provide independent estimates of cognitive and perceptual processing in native English-speaking musicians (n = 15, mean age = 25 years) and non-musicians (n = 15, mean age = 23 years) learning to categorize non-native lexical pitch patterns (Mandarin tones). Musicians outperformed non-musicians in this task. Model-based analyses suggested that musicians shifted from simple unidimensional decision strategies to more optimal multidimensional (MD) decision strategies sooner than non-musicians. In addition, musicians used optimal decisional strategies more often than non-musicians. However, musicians and non-musicians who used MD strategies showed no difference in performance. We estimated parameters that quantify the magnitude of perceptual variability along two dimensions that are critical for tone categorization: pitch height and pitch direction. Both musicians and non-musicians showed a decrease in perceptual variability along the pitch height dimension, but only musicians showed a significant reduction in perceptual variability along the pitch direction dimension. Notably, these advantages persisted during a generalization phase, when no feedback was provided. These results provide an insight into the mechanisms underlying the musician advantage observed in non-native speech learning.

Indexed as

category learningmusicOPERAplasticityspeech

Identifiers

PMID26052304
PMCPMC4439769

What OpenQuestion holds

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LicenceCC BY
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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.