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Language development in infancy: How neural methods can clarify what we know from behavior alone| title | Language development in infancy: How neural methods can clarify what we know from behavior alone |
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| start_date | 2022/12/12 |
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| schedule | 14h |
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| online | yes |
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| visio | https://us02web.zoom.us/j/83888993899?pwd=ZFZ0STdQVmhESkI2bnVabWRWV0RpQT09 |
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| location_info | Zoom conference |
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| details | invité par Jessica Dubois |
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| summary | Studies of language development in infancy made major advances in the past 50 years by relying on a variety of behavioral methods, such as non-nutritive sucking, head-turning, and eye-tracking. These methods have revealed sophisticated abilities in the first 6 months of infancy, including phonetic discrimination, word recognition, and the beginnings of grammar learning as infants extract the distributional properties of their native language. However, these behavioral methods have limitations – they rarely provide a measure of an individual infant’s performance and they do not reveal the neural mechanism that underlies the development of these behavioral milestones. I will first review what we know about these milestones in the first two years of life among both monolinguals and bilinguals. Then I will summarize how modern neuroimaging methods developed to study the adult brain may provide a window on language development in the infant brain. These neuroimaging methods include EEG/MEG, fNIRS (functional near-infrared spectroscopy), and most recently fMRI in awake infants. These studies can apply machine-learning techniques to both univariate and multivariate signals from the brain, as well as functional connectivity among brain regions, to decode mental states on a trial-by-trial basis. These methods are powerful tools not only for studies of normative development, but also for studies of clinical populations. I will end by highlighting several examples that apply these methods to studies using naturalistic movie-watching paradigms. |
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| responsibles | Blancho |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2022/12/07 17:12 UTC |
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