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Integrating when and what information in the left parietal lobe allows language rule generalization

A crucial aspect when learning a language is discovering the rules that govern how words are combined in order to convey meanings. Because rules are characterized by sequential co-occurrences between elements (e.g., “These cupcakes are unbelievable”), tracking the statistical relationships between t...

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Autores principales: Orpella, Joan, Ripollés, Pablo, Ruzzoli, Manuela, Amengual, Julià L., Callejas, Alicia, Martinez-Alvarez, Anna, Soto-Faraco, Salvador, de Diego-Balaguer, Ruth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660506/
https://www.ncbi.nlm.nih.gov/pubmed/33137084
http://dx.doi.org/10.1371/journal.pbio.3000895
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author Orpella, Joan
Ripollés, Pablo
Ruzzoli, Manuela
Amengual, Julià L.
Callejas, Alicia
Martinez-Alvarez, Anna
Soto-Faraco, Salvador
de Diego-Balaguer, Ruth
author_facet Orpella, Joan
Ripollés, Pablo
Ruzzoli, Manuela
Amengual, Julià L.
Callejas, Alicia
Martinez-Alvarez, Anna
Soto-Faraco, Salvador
de Diego-Balaguer, Ruth
author_sort Orpella, Joan
collection PubMed
description A crucial aspect when learning a language is discovering the rules that govern how words are combined in order to convey meanings. Because rules are characterized by sequential co-occurrences between elements (e.g., “These cupcakes are unbelievable”), tracking the statistical relationships between these elements is fundamental. However, purely bottom-up statistical learning alone cannot fully account for the ability to create abstract rule representations that can be generalized, a paramount requirement of linguistic rules. Here, we provide evidence that, after the statistical relations between words have been extracted, the engagement of goal-directed attention is key to enable rule generalization. Incidental learning performance during a rule-learning task on an artificial language revealed a progressive shift from statistical learning to goal-directed attention. In addition, and consistent with the recruitment of attention, functional MRI (fMRI) analyses of late learning stages showed left parietal activity within a broad bilateral dorsal frontoparietal network. Critically, repetitive transcranial magnetic stimulation (rTMS) on participants’ peak of activation within the left parietal cortex impaired their ability to generalize learned rules to a structurally analogous new language. No stimulation or rTMS on a nonrelevant brain region did not have the same interfering effect on generalization. Performance on an additional attentional task showed that this rTMS on the parietal site hindered participants’ ability to integrate “what” (stimulus identity) and “when” (stimulus timing) information about an expected target. The present findings suggest that learning rules from speech is a two-stage process: following statistical learning, goal-directed attention—involving left parietal regions—integrates “what” and “when” stimulus information to facilitate rapid rule generalization.
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spelling pubmed-76605062020-11-18 Integrating when and what information in the left parietal lobe allows language rule generalization Orpella, Joan Ripollés, Pablo Ruzzoli, Manuela Amengual, Julià L. Callejas, Alicia Martinez-Alvarez, Anna Soto-Faraco, Salvador de Diego-Balaguer, Ruth PLoS Biol Research Article A crucial aspect when learning a language is discovering the rules that govern how words are combined in order to convey meanings. Because rules are characterized by sequential co-occurrences between elements (e.g., “These cupcakes are unbelievable”), tracking the statistical relationships between these elements is fundamental. However, purely bottom-up statistical learning alone cannot fully account for the ability to create abstract rule representations that can be generalized, a paramount requirement of linguistic rules. Here, we provide evidence that, after the statistical relations between words have been extracted, the engagement of goal-directed attention is key to enable rule generalization. Incidental learning performance during a rule-learning task on an artificial language revealed a progressive shift from statistical learning to goal-directed attention. In addition, and consistent with the recruitment of attention, functional MRI (fMRI) analyses of late learning stages showed left parietal activity within a broad bilateral dorsal frontoparietal network. Critically, repetitive transcranial magnetic stimulation (rTMS) on participants’ peak of activation within the left parietal cortex impaired their ability to generalize learned rules to a structurally analogous new language. No stimulation or rTMS on a nonrelevant brain region did not have the same interfering effect on generalization. Performance on an additional attentional task showed that this rTMS on the parietal site hindered participants’ ability to integrate “what” (stimulus identity) and “when” (stimulus timing) information about an expected target. The present findings suggest that learning rules from speech is a two-stage process: following statistical learning, goal-directed attention—involving left parietal regions—integrates “what” and “when” stimulus information to facilitate rapid rule generalization. Public Library of Science 2020-11-02 /pmc/articles/PMC7660506/ /pubmed/33137084 http://dx.doi.org/10.1371/journal.pbio.3000895 Text en © 2020 Orpella et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Orpella, Joan
Ripollés, Pablo
Ruzzoli, Manuela
Amengual, Julià L.
Callejas, Alicia
Martinez-Alvarez, Anna
Soto-Faraco, Salvador
de Diego-Balaguer, Ruth
Integrating when and what information in the left parietal lobe allows language rule generalization
title Integrating when and what information in the left parietal lobe allows language rule generalization
title_full Integrating when and what information in the left parietal lobe allows language rule generalization
title_fullStr Integrating when and what information in the left parietal lobe allows language rule generalization
title_full_unstemmed Integrating when and what information in the left parietal lobe allows language rule generalization
title_short Integrating when and what information in the left parietal lobe allows language rule generalization
title_sort integrating when and what information in the left parietal lobe allows language rule generalization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7660506/
https://www.ncbi.nlm.nih.gov/pubmed/33137084
http://dx.doi.org/10.1371/journal.pbio.3000895
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