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Learning Words While Listening to Syllables: Electrophysiological Correlates of Statistical Learning in Children and Adults
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In: Front Hum Neurosci (2022)
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DATA: Developmental Differences in the Online Statistical Learning of Complex Speech Streams: An ERP Study with Children and Adults ...
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DATA: Developmental Differences in the Online Statistical Learning of Complex Speech Streams: An ERP Study with Children and Adults ...
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DATA: Learning Words While Listening to Syllables: Electrophysiological Correlates of Statistical Learning in Children and Adults ...
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DATA: Unraveling the Processes Underlying Statistical Learning Through a 2-AFC Task: The Usefulness of ERPs ...
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DATA: Unraveling the Processes Underlying Statistical Learning Through a 2-AFC Task: The Usefulness of ERPs ...
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DATA: Learning Words While Listening to Syllables: Electrophysiological Correlates of Statistical Learning in Children and Adults ...
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DATA: Not all words are equally acquired: Transitional probabilities and instructions affect the electrophysiological correlates of statistical learning ...
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DATA: Not all words are equally acquired: Transitional probabilities and instructions affect the electrophysiological correlates of statistical learning ...
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Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning
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In: Front Hum Neurosci (2020)
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Abstract:
Statistical learning (SL), the process of extracting regularities from the environment, is a fundamental skill of our cognitive system to structure the world regularly and predictably. SL has been studied using mainly behavioral tasks under implicit conditions and with triplets presenting the same level of difficulty, i.e., a mean transitional probability (TP) of 1.00. Yet, the neural mechanisms underlying SL under other learning conditions remain largely unknown. Here, we investigated the neurofunctional correlates of SL using triplets (i.e., three-syllable nonsense words) with a mean TP of 1.00 (easy “words”) and 0.50 (hard “words”) in an SL task performed under incidental (implicit) and intentional (explicit) conditions, to determine whether the same core mechanisms were recruited to assist learning. Event-related potentials (ERPs) were recorded while participants listened firstly to a continuous auditory stream made of the concatenation of four easy and four hard “words” under implicit instructions, and subsequently to another auditory stream made of the concatenation of four easy and four hard “words” drawn from another artificial language under explicit instructions. The stream in each of the SL tasks was presented in two consecutive blocks of ~3.5-min each (~7-min in total) to further examine how ERP components might change over time. Behavioral measures of SL were collected after the familiarization phase of each SL task by asking participants to perform a two-alternative forced-choice (2-AFC) task. Results from the 2-AFC tasks revealed a moderate but reliable level of SL, with no differences between conditions. ERPs were, nevertheless, sensitive to the effect of TPs, showing larger amplitudes of N400 for easy “words,” as well as to the effect of instructions, with a reduced N250 for “words” presented under explicit conditions. Also, significant differences in the N100 were found as a result of the interaction between TPs, instructions, and the amount of exposure to the auditory stream. Taken together, our findings suggest that triplets’ predictability impacts the emergence of “words” representations in the brain both for statistical regularities extracted under incidental and intentional instructions, although the prior knowledge of the “words” seems to favor the recruitment of different SL mechanisms.
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Keyword:
Human Neuroscience
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URL: http://www.ncbi.nlm.nih.gov/pubmed/33173474
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538775/
https://doi.org/10.3389/fnhum.2020.577991
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| 11 |
Not all words are equally acquired: transitional probabilities and instructions affect the electrophysiological correlates of statistical learning
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