Neural signatures of phonetic learning in adulthood: a magnetoencephalography study
Open accessAbstract
The present study used magnetoencephalography (MEG) to examine perceptual learning of American English /r/ and /l/ categories by Japanese adults who had limited English exposure. A training software program was developed based on the principles of infant phonetic learning, featuring systematic acoustic exaggeration, multi-talker variability, visible articulation, and adaptive listening. The program was designed to help Japanese listeners utilize an acoustic dimension relevant for phonemic categorization of /r-l/ in English. Although training did not produce native-like phonetic boundary along the /r-l/ synthetic continuum in the second language learners, success was seen in highly significant identification improvement over twelve training sessions and transfer of learning to novel stimuli. Consistent with behavioral results, pre-post MEG measures showed not only enhanced neural sensitivity to the /r-l/ distinction in the left-hemisphere mismatch field (MMF) response but also bilateral decreases in equivalent current dipole (ECD) cluster and duration measures for stimulus coding in the inferior parietal region. The learning-induced increases in neural sensitivity and efficiency were also found in distributed source analysis using Minimum Current Estimates (MCE). Furthermore, the pre-post changes exhibited significant brain-behavior correlations between speech discrimination scores and MMF amplitudes as well as between the behavioral scores and ECD measures of neural efficiency. Together, the data provide corroborating evidence that substantial neural plasticity for second-language learning in adulthood can be induced with adaptive and enriched linguistic exposure. Like the MMF, the ECD cluster and duration measures are sensitive neural markers of phonetic learning.
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Adults can improve nonnative phonetic perception under more social training conditions, and MEG shows neural efficiency increases after training.
“Training studies show that adults can improve nonnative phonetic perception when training occurs under more social learning conditions, and MEG measures before and after training indicate that neural efficiency increases after training (Zhang et al., 2009).”
From Brain mechanisms in early language acquisition (2010) · cites this paper as Zhang et al., 2009
The Discussion reports improved English /r–l/ identification by Japanese adults, and the Abstract reports pre–post MEG changes consistent with increased neural efficiency. But the Materials and Methods describe computer-based training with infant-directed-speech features, not training under social learning conditions. Those features may make the training more socially informed, but the paper does not establish the claimed social condition. (LLM, conf=0.87)
Experimental — accuracy not yet measuredInduced brain rhythms are linked to attention and cognitive effort, and adult MEG studies show increased cognitive effort when processing nonnative speech.
“The induced brain rhythms have been linked to attention and cognitive effort, and are of primary interest since MEG studies with adults have shown that cognitive effort is increased when processing nonnative speech (Zhang et al., 2005; 2009).”
From Brain mechanisms in early language acquisition (2010) · cites this paper as Zhang et al., 2009
The Discussion (Relationships between Brain Plasticity, Neural Sensitivity and Efficiency; page unavailable) reports greater overall MEG activation in Japanese than American adults processing the /r-l/ contrast, consistent with less efficient processing of that nonnative contrast. It does not establish increased cognitive effort directly or link induced brain rhythms to attention and effort; its attention-related discussion concerns regional activation. (LLM, conf=0.82)
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Stenbacka, L., Vanni, S., Uutela, K., & Hari, R. (2002) · NeuroImage · doi:10.1006/nimg.2002.1151 · Cited by 49 · see citing works
Vallabha, G. K., & McClelland, J. L. (2007) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/cabn.7.1.53 · Cited by 47 · see citing works
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A comparison of functional MRI and magnetoencephalography for receptive language mapping
Billingsley‐Marshall, R. L., Clear, T., Mencl, W. E., Simos, P. G., Swank, P. R., Men, D., Sarkari, S., Castillo, E. M., & Papanicolaou, A. C. (2006) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2006.10.020 · Cited by 42 · see citing works
Attention modulates hemispheric differences in functional connectivity: Evidence from MEG recordings
Gootjes, L., Bouma, A., Strien, J. W. V., Scheltens, P., & Stam, C. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.09.015 · Cited by 41 · see citing works
Attentional influences on functional mapping of speech sounds in human auditory cortex
Obleser, J., Elbert, T. R., & Eulitz, C. (2004) · BMC Neuroscience · doi:10.1186/1471-2202-5-24 · Cited by 34 · see citing works
Papanicolaou, A. C., Castillo, E., Breier, J. I., Davis, R. N., Simos, P. G., & Diehl, R. L. (2003) · NeuroImage · doi:10.1016/s1053-8119(02)00020-4 · Cited by 34 · see citing works
Plastic cortical changes induced by learning to communicate with non-speech sounds
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Self-citationEffects of audio-visual training on the identification of English /r/ and /l/ by Japanese speakers
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Effect of Formant Frequency Onset Variation on the Differentiation of Synthesized /w/ and /r/ Sounds
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Multiplicative Correction of Subject Effect as Preprocessing for Analysis of Variance
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Flagged first, then by citations
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The anatomy of language: a review of 100 fMRI studies published in 2009
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Brain mechanisms in early language acquisition
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“Work in my laboratory ledme to advance the concept of neural commitment, the idea that neural circuitry and overall architecture develops early in infancy to detect the phonetic and prosodic patterns of speech (Kuhl, 2004; Zhang et al., 2005, 2009).”
BackgroundSelf-citationFoundations for a new science of learning
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Self-citationTracing the Trajectory of Sensory Plasticity across Different Stages of Speech Learning in Adulthood
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Toward a dual-learning systems model of speech category learning.
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- Authors
- Zhang, Y., Kuhl, P. K., Imada, T., Iverson, P., Pruitt, J., Stevens, E. B., Kawakatsu, M., Tohkura, Y., & Nemoto, I.
- Affiliations
- University of Minnesota (US)
- University of Washington (US)
- Tokyo Denki University (JP)
- University College London (GB)
- Microsoft (United States) (US)
- National Institute of Informatics (JP)
- Corresponding author
- Zhang, Yang
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-05-15
- Volume
- 46
- Issue
- 1
- Pages
- 226-240
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2811417
- OpenAlex
- W2146843281
- Cited by
- 132
- References
- 113
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 5 · 2023: 7 · 2022: 7 · 2021: 11 · 2020: 8 · 2019: 3 · 2018: 6 · 2017: 15 · 2016: 7 · 2015: 9 · 2014: 12 · 2013: 7 · 2012: 9
- FWCI
- 12.25
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Science Foundation
- University of Minnesota
- University of Washington
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD037954)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neuroscience and Music Perception
- Keywords
- phonetic learning, perceptual learning, second language acquisition, Japanese listeners, neuroplasticity, inferior parietal cortex, equivalent current dipole, speech discrimination, transfer of learning, adult second language learning
- MeSH terms
- Adult, Brain, Female, Humans, Learning, Male, Neuronal Plasticity, Phonetics, Signal Processing, Computer-Assisted, Magnetoencephalography
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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