Evidence map›Paper›PMID 27737775›Full record

ArticleNeuropsychologia2017

Native-language N400 and P600 predict dissociable language-learning abilities in adults.

Zhenghan Qi, Sara D Beach, Amy S Finn, Jennifer Minas, Calvin Goetz, Brian Chan, John D E Gabrieli

Open access · bronzeAbstract read
In one paragraph

Article in Neuropsychologia, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 32 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Zhenghan QiMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: zqi@mit.edu.
Sara D BeachProgram in Speech and Hearing Bioscience and Technology, Division of Medical Sciences, Harvard University, Cambridge, MA 02138, USA. Electronic address: beach@g.harvard.edu.
Amy S FinnMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: amy.finn@utoronto.ca.
Jennifer MinasMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: jminas@mit.edu.
Calvin GoetzMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: cgoetz@mit.edu.
Brian ChanMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: brianc07@mit.edu.
John D E GabrieliMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: gabrieli@mit.edu.
Massachusetts Institute of Technology · USHarvard University · USMcGovern Institute for Brain Research · US

Funding

TRAINING FOR SPEECH AND HEARING SCIENCEST32DC000038 · NIDCD · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Gwenaelle S Geleoc · 1992 to 2026
$21.8M
NIDCD NIH HHS T32 DC000038
6 · The paper itself

Abstract

Language learning aptitude during adulthood varies markedly across individuals. An individual's native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information.

Indexed as

Brain MappingLanguageAcoustic StimulationAdultElectroencephalographyEvoked PotentialsFemaleHumansIndividualityLearningMaleSemanticsTime FactorsVerbal LearningVocabularyYoung AdultAdult language learningEvent-related potentialIndividual differencesN400P600

Identifiers

PMID27737775
PMCPMC5885768
OpenAlexW2532441722

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.