Literature DB >> 33137084

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

Joan Orpella1,2,3,4, Pablo Ripollés4,5,6, Manuela Ruzzoli7,8, Julià L Amengual9, Alicia Callejas1,10, Anna Martinez-Alvarez1,2,3,11, Salvador Soto-Faraco5,12, Ruth de Diego-Balaguer1,2,3,12.   

Abstract

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.

Entities:  

Year:  2020        PMID: 33137084      PMCID: PMC7660506          DOI: 10.1371/journal.pbio.3000895

Source DB:  PubMed          Journal:  PLoS Biol        ISSN: 1544-9173            Impact factor:   8.029


  67 in total

Review 1.  Control of goal-directed and stimulus-driven attention in the brain.

Authors:  Maurizio Corbetta; Gordon L Shulman
Journal:  Nat Rev Neurosci       Date:  2002-03       Impact factor: 34.870

2.  Temporal aspects of stimulus-driven attending in dynamic arrays.

Authors:  Mari Riess Jones; Heather Moynihan; Noah MacKenzie; Jennifer Puente
Journal:  Psychol Sci       Date:  2002-07

3.  How the deployment of attention determines what we see.

Authors:  Anne Treisman
Journal:  Vis cogn       Date:  2006-08-01

4.  Basal ganglia contribution to rule expectancy and temporal predictability in speech.

Authors:  Sonja A Kotz; Maren Schmidt-Kassow
Journal:  Cortex       Date:  2015-03-14       Impact factor: 4.027

5.  Implicit temporal predictability enhances pitch discrimination sensitivity and biases the phase of delta oscillations in auditory cortex.

Authors:  Sophie K Herbst; Jonas Obleser
Journal:  Neuroimage       Date:  2019-09-17       Impact factor: 6.556

Review 6.  Anticipated moments: temporal structure in attention.

Authors:  Anna C Nobre; Freek van Ede
Journal:  Nat Rev Neurosci       Date:  2017-12-07       Impact factor: 34.870

Review 7.  Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research.

Authors:  Simone Rossi; Mark Hallett; Paolo M Rossini; Alvaro Pascual-Leone
Journal:  Clin Neurophysiol       Date:  2009-10-14       Impact factor: 3.708

8.  Measuring individual differences in statistical learning: Current pitfalls and possible solutions.

Authors:  Noam Siegelman; Louisa Bogaerts; Ram Frost
Journal:  Behav Res Methods       Date:  2017-04

9.  Redefining "Learning" in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?

Authors:  Noam Siegelman; Louisa Bogaerts; Ofer Kronenfeld; Ram Frost
Journal:  Cogn Sci       Date:  2017-10-07

10.  Temporal Attention as a Scaffold for Language Development.

Authors:  Ruth de Diego-Balaguer; Anna Martinez-Alvarez; Ferran Pons
Journal:  Front Psychol       Date:  2016-02-02
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  1 in total

1.  Differential activation of a frontoparietal network explains population-level differences in statistical learning from speech.

Authors:  Joan Orpella; M Florencia Assaneo; Pablo Ripollés; Laura Noejovich; Diana López-Barroso; Ruth de Diego-Balaguer; David Poeppel
Journal:  PLoS Biol       Date:  2022-07-06       Impact factor: 9.593

  1 in total

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