JOURNAL ARTICLE
The Relevance of Dual Language Experience in Interhemispheric Brain Connectivity in Older Adults.
Published In: Archives of Clinical Neuropsychology, 2024, v. 39, n. 7. P. 931 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Rosselli, Monica; Lang, Merike; Baty, Zachary M; Velez-Uribe, Idaly; Velasquez, Karen; Barker, Warren W; Duara, Ranjan; Newman, David; Asken, Breton M; Armstrong, Melissa; Curiel, Rosie; Loewenstein, David A; Smith, Glenn; Coombes, Stephen A 3 of 3
Abstract
This article examines the impact of dual language experience on interhemispheric brain connectivity in older adults by analyzing corpus callosum (CC) volumes and white matter integrity in bilingual and monolingual individuals. The study involved 196 participants clinically diagnosed as cognitively normal, mild cognitive impairment (MCI), or dementia, with neuroimaging measures including T1-weighted scans and diffusion MRI assessing fractional anisotropy (FA) and free water (FW) in frontal and temporal transcallosal tracts (TCATT). Results showed that bilinguals had larger anterior CC volumes and higher FA values in the supplementary motor area (SMA) and inferior temporal lobe tracts, particularly among those with dementia, indicating better white matter integrity. Additionally, correlations were found between these neuroimaging markers and cognitive as well as language proficiency measures, suggesting bilingualism may contribute to increased neural reserve in aging.
Additional Information
- Source:Archives of Clinical Neuropsychology. 2024/10, Vol. 39, Issue 7, p931
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:0887-6177
- DOI:10.1093/arclin/acae067.013
- Accession Number:184163304
- Copyright Statement:Copyright of Archives of Clinical Neuropsychology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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