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Language learning in the adult brain: A neuroanatomical meta-analysis of lexical and grammatical learning.

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Citation: Neuroimage. 193:178-200, 2019 Jun.PMID: 30826361Institution: MedStar National Rehabilitation NetworkForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: *Brain/ah [Anatomy & Histology] | *Brain/ph [Physiology] | *Language | *Learning/ph [Physiology] | Functional Neuroimaging | HumansYear: 2019ISSN:

1053-8119

Name of journal: NeuroImageAbstract: Copyright (c) 2019 Elsevier Inc. All rights reserved.Language learning as an adult, though often difficult, is quite common. Nevertheless, the neural substrates of this process remain unclear, even though identifying them should clarify how language is learned and could lead to improved success at this endeavor. We addressed this gap by conducting multiple neuroanatomical meta-analyses to synthesize the functional neuroimaging literature of language learning. We focused on learning lexical and grammatical knowledge, two building blocks of language. Lexical and grammatical learning yielded overlapping activation in frontal (e.g., BA 44/45) and posterior parietal regions. Only lexical learning showed ventral occipito-temporal (ventral stream) activation, while only grammatical learning showed basal ganglia (anterior caudate/putamen) activation. To further elucidate the neurocognition of grammar learning, we also tested specific predictions of the declarative/procedural model of language. Consistent with the model, grammar learning predicted to rely especially on declarative memory (e.g., with explicit training) showed hippocampal involvement, while grammar learning predicted to rely particularly on procedural memory (e.g., with implicit training) showed anterior caudate/putamen involvement. Finally, given the prevalence of research on artificial grammars, we performed separate analyses of artificial grammar and non-artificial grammar (e.g., miniature language) paradigms. These yielded overlapping activation, especially in BA 44, underscoring the validity of artificial grammars as models for grammar learning in natural languages. In sum, the study elucidates the empirical and theoretical landscape of language learning and has applied implications.All authors: Shattuck KF, Tagarelli KM, Turkeltaub PE, Ullman MTFiscal year: FY2019Digital Object Identifier:

https://dx.doi.org/10.1016/j.neuroimage.2019.02.061

Date added to catalog: 2019-05-21

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Item type	Current library	Collection	Call number	Status	Date due	Barcode
Journal Article	MedStar Authors Catalog	Article		Available		30826361

Language learning as an adult, though often difficult, is quite common. Nevertheless, the neural substrates of this process remain unclear, even though identifying them should clarify how language is learned and could lead to improved success at this endeavor. We addressed this gap by conducting multiple neuroanatomical meta-analyses to synthesize the functional neuroimaging literature of language learning. We focused on learning lexical and grammatical knowledge, two building blocks of language. Lexical and grammatical learning yielded overlapping activation in frontal (e.g., BA 44/45) and posterior parietal regions. Only lexical learning showed ventral occipito-temporal (ventral stream) activation, while only grammatical learning showed basal ganglia (anterior caudate/putamen) activation. To further elucidate the neurocognition of grammar learning, we also tested specific predictions of the declarative/procedural model of language. Consistent with the model, grammar learning predicted to rely especially on declarative memory (e.g., with explicit training) showed hippocampal involvement, while grammar learning predicted to rely particularly on procedural memory (e.g., with implicit training) showed anterior caudate/putamen involvement. Finally, given the prevalence of research on artificial grammars, we performed separate analyses of artificial grammar and non-artificial grammar (e.g., miniature language) paradigms. These yielded overlapping activation, especially in BA 44, underscoring the validity of artificial grammars as models for grammar learning in natural languages. In sum, the study elucidates the empirical and theoretical landscape of language learning and has applied implications.

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