Evidence map›Paper›PMID 27523024›Full record

ArticleDevelopmental science2017

Brain bases of morphological processing in Chinese-English bilingual children.

Ka I Ip, Lucy Shih-Ju Hsu, Maria M Arredondo, Twila Tardif, Ioulia Kovelman

Abstract read
In one paragraph

Article in Developmental science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
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

20 citing papers in PubMed.

  1. Article
  2. A Shared Neural Mechanism for Abstract Grammatical Computations across Languages in Bilinguals.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
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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

5 authors.

Ka I IpDepartment of Psychology, University of Michigan, USA.
Lucy Shih-Ju HsuDepartment of Psychology, University of Hong Kong, Hong Kong.
Maria M ArredondoDepartment of Psychology, University of Michigan, USA.
Twila TardifDepartment of Psychology, University of Michigan, USA.
Ioulia KovelmanDepartment of Psychology, University of Michigan, USA.

Funding

Understanding literacy acquisition through immersion in foreign languagesR01HD078351 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HENDREN, ROBERT LEE, HOEFT, FUMIKO · 2015 to 2020
$3.0M
NICHD NIH HHS R01 HD078351
6 · The paper itself

Abstract

Can bilingual exposure impact children's neural circuitry for learning to read? To answer this question, we investigated the brain bases of morphological awareness, one of the key spoken language abilities for learning to read in English and Chinese. Bilingual Chinese-English and monolingual English children (N = 22, ages 7-12) completed morphological tasks that best characterize each of their languages: compound morphology in Chinese (e.g. basket + ball = basketball) and derivational morphology in English (e.g. re + do = redo). In contrast to monolinguals, bilinguals showed greater activation in the left middle temporal region, suggesting that bilingual exposure to Chinese impacts the functionality of brain regions supporting semantic abilities. Similar to monolinguals, bilinguals showed greater activation in the left inferior frontal region [BA 45] in English than Chinese, suggesting that young bilinguals form language-specific neural representations. The findings offer new insights to inform bilingual and cross-linguistic models of language and literacy acquisition.

Indexed as

Brain MappingLanguage DevelopmentMultilingualismAcoustic StimulationAdolescentAwarenessBrainChildFemaleHumansImage Processing, Computer-AssistedLinguisticsMagnetic Resonance ImagingMaleOxygenReadingOxygen

Identifiers

PMID27523024
PMCPMC5309206

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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.