ArticleCerebral cortex (New York, N.Y. : 1991)2025
Dynamic changes in electrical brain activity during passive learning of foreign speech sound discrimination.
Article in Cerebral cortex (New York, N.Y. : 1991), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Cross-Night Modulation of Change Detection ERPs to Foreign Speech Sound Features During N2 Sleep.The European journal of neuroscience · 2026Article
- Rapid Mandarin Tone Learning in Passive and Active Listening: A Magnetoencephalography Study.The European journal of neuroscience · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
Previous brain research on phonetic learning of foreign speech sounds has focused on learning outcomes, mostly neglecting the dynamical neural changes during learning. In the present study, Finnish-speaking participants listened passively to a repeated presentation of vowel /a/ with infrequent changes in Mandarin tone for 2 h per day for 4 consecutive days while their brain activity was recorded using electroencephalography. While our previous study has reported the brain activity changes from test recordings conducted before and after the sound exposure, we here analyzed the data recorded during the exposure. We investigated learning dynamics across daily exposure sessions using event-related potentials and multivariate pattern analysis and within sessions using a sliding average across trials. Both mismatch negativity and P3a-markers of change detection and preattentive attention shifts-exhibited learning-related changes in both the event-related potential analysis and multivariate pattern analysis. Changes in multivariate pattern analysis were evident after the first 2-h training session, while event-related potential-based effects emerged later. During the daily exposure sessions, the mismatch negativity amplitude gradually decreased over the first 3 d, whereas the P3a amplitude exhibited an opposite trend, showing a significant increase, and only on day 1. These findings demonstrate dynamic neural changes driven by passive exposure and pave the way for investigating learning processes across multiple levels of analysis, including event-related potential, single-trial dynamics, and machine learning-based methods.
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