Evidence map›Paper›PMID 25331600›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2016

The Role of Corticostriatal Systems in Speech Category Learning.

Han-Gyol Yi, W Todd Maddox, Jeanette A Mumford, Bharath Chandrasekaran

Abstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Article
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  3. Article
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  5. Article
  6. The nature of non-native speech sound representations.The Journal of the Acoustical Society of America · 2022
    Review
  7. Non-sensory Influences on Auditory Learning and Plasticity.Journal of the Association for Research in Otolaryngology : JARO · 2022
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Role of the striatum in incidental learning of sound categories.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  18. Reading and the Neurocognitive Bases of Statistical LearningScientific studies of reading : the official journal of the Society for the Scientific Study of Reading · 2019
    Article
  19. Article
  20. Task and distribution sampling affect auditory category learning.Attention, perception & psychophysics · 2018
    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

4 authors.

Han-Gyol YiDepartment of Communication Sciences & Disorders, Moody College of Communication, The University of Texas at Austin, Austin, TX, USA.
W Todd MaddoxDepartment of Psychology, College of Liberal Arts, The University of Texas at Austin, Austin, TX, USA.
Jeanette A MumfordDepartment of Psychology, College of Liberal Arts, The University of Texas at Austin, Austin, TX, USA.
Bharath ChandrasekaranDepartment of Communication Sciences & Disorders, Moody College of Communication, 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
A computational neuroscience approach to frontal compensation in decision-makingR01AG043425 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI SCHNYER, DAVID M, WORTHY, DARRELL A. · 2014 to 2019
$1.7M
NIA NIH HHS R01 AG043425NIDA NIH HHS DA032457NIDA NIH HHS R01 DA032457NIDCD NIH HHS R01 DC013315NIDCD NIH HHS R01DC013315 834
6 · The paper itself

Abstract

One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning.

Indexed as

Formative FeedbackMultilingualismAcoustic StimulationAdolescentAdultBrain MappingFemaleHumansLearningMagnetic Resonance ImagingMaleNeural PathwaysPrefrontal CortexPutamenSpeech PerceptionYoung Adultcategory learningcorticostriatal systemsfMRIputamen.speech

Identifiers

PMID25331600
PMCPMC4785939

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.