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Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning

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 l...

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Autores principales: Soares, Ana Paula, Gutiérrez-Domínguez, Francisco-Javier, Vasconcelos, Margarida, Oliveira, Helena M., Tomé, David, Jiménez, Luis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538775/
https://www.ncbi.nlm.nih.gov/pubmed/33173474
http://dx.doi.org/10.3389/fnhum.2020.577991
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author Soares, Ana Paula
Gutiérrez-Domínguez, Francisco-Javier
Vasconcelos, Margarida
Oliveira, Helena M.
Tomé, David
Jiménez, Luis
author_facet Soares, Ana Paula
Gutiérrez-Domínguez, Francisco-Javier
Vasconcelos, Margarida
Oliveira, Helena M.
Tomé, David
Jiménez, Luis
author_sort Soares, Ana Paula
collection PubMed
description 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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spelling pubmed-75387752020-11-09 Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning Soares, Ana Paula Gutiérrez-Domínguez, Francisco-Javier Vasconcelos, Margarida Oliveira, Helena M. Tomé, David Jiménez, Luis Front Hum Neurosci Human Neuroscience 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. Frontiers Media S.A. 2020-09-23 /pmc/articles/PMC7538775/ /pubmed/33173474 http://dx.doi.org/10.3389/fnhum.2020.577991 Text en Copyright © 2020 Soares, Gutiérrez-Domínguez, Vasconcelos, Oliveira, Tomé and Jiménez. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Human Neuroscience
Soares, Ana Paula
Gutiérrez-Domínguez, Francisco-Javier
Vasconcelos, Margarida
Oliveira, Helena M.
Tomé, David
Jiménez, Luis
Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning
title Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning
title_full Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning
title_fullStr Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning
title_full_unstemmed Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning
title_short Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning
title_sort not all words are equally acquired: transitional probabilities and instructions affect the electrophysiological correlates of statistical learning
topic Human Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538775/
https://www.ncbi.nlm.nih.gov/pubmed/33173474
http://dx.doi.org/10.3389/fnhum.2020.577991
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