Background: In their daily communication, bilinguals switch between two languages, a process that involves the selection of a target language and minimization of interference from a nontarget language. Previous studies have uncovered the neural structure in bilinguals and the activation patterns associated with performing verbal conflict tasks. One question that remains, however is whether this extra verbal switching affects brain function during nonverbal conflict tasks.
Methods: In this study, we have used fMRI to investigate the impact of bilingualism in children performing two nonverbal tasks involving stimulus-stimulus and stimulus-response conflicts. Three groups of 8-11-year-old children--bilinguals from birth (2L1), second language learners (L2L), and a control group of monolinguals (1L1)--were scanned while performing a color Simon and a numerical Stroop task. Reaction times and accuracy were logged.
Results: Compared to monolingual controls, bilingual children showed higher behavioral congruency effect of these tasks, which is matched by the recruitment of brain regions that are generally used in general cognitive control, language processing or to solve language conflict situations in bilinguals (caudate nucleus, posterior cingulate gyrus, STG, precuneus). Further, the activation of these areas was found to be higher in 2L1 compared to L2L.
Conclusion: The coupling of longer reaction times to the recruitment of extra language-related brain areas supports the hypothesis that when dealing with language conflicts the specialization of bilinguals hampers the way they can process with nonverbal conflicts, at least at early stages in life.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107382 | PMC |
http://dx.doi.org/10.1002/brb3.246 | DOI Listing |
Sci Rep
January 2025
EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, 11586, Riyadh, Saudi Arabia.
During the Covid-19 pandemic, the widespread use of social media platforms has facilitated the dissemination of information, fake news, and propaganda, serving as a vital source of self-reported symptoms related to Covid-19. Existing graph-based models, such as Graph Neural Networks (GNNs), have achieved notable success in Natural Language Processing (NLP). However, utilizing GNN-based models for propaganda detection remains challenging because of the challenges related to mining distinct word interactions and storing nonconsecutive and broad contextual data.
View Article and Find Full Text PDFJ Epidemiol Community Health
January 2025
The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
Background: The prevalence of congenital heart defects (CHD) in Down syndrome (DS) varies considerably across studies (from 16% to 84%). This study aimed to estimate the prevalence of CHD in people with DS (CHD-DS).
Methods: PubMed, Web of Science and the Chinese National Knowledge Infrastructure databases were searched through to 5 January 2023.
Spine J
January 2025
Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha 410008, China. Electronic address:
Background: In clinical practice, distinguishing between spinal tuberculosis (STB) and spinal tumors (ST) poses a significant diagnostic challenge. The application of AI-driven large language models (LLMs) shows great potential for improving the accuracy of this differential diagnosis.
Purpose: To evaluate the performance of various machine learning models and ChatGPT-4 in distinguishing between STB and ST.
J Speech Lang Hear Res
January 2025
Department of Psychology, University of Lethbridge, Alberta, Canada.
Purpose: This study investigates how Mandarin-English bilingual students in Canada produce Mandarin tones and how this is influenced by factors such as tone complexity, cross-linguistic influences, and speech input.
Method: Participants were 82 students enrolled in a Chinese bilingual program in Western Canada. Students were recruited from Grades 1, 3, and 5 and divided into two groups based on their home language backgrounds: The heritage language group had early and strong input in Mandarin, and the second language (L2) group received mostly English input at home.
Am J Speech Lang Pathol
January 2025
Good Samaritan Medical Center Foundation, Lafayette, CO.
Purpose: The aim of this study was to gauge the impacts of cognitive empathy training experiential learning on traumatic brain injury (TBI) knowledge, awareness, confidence, and empathy in a pilot study of speech-language pathology graduate students.
Method: A descriptive quasi-experimental convergent parallel mixed methods design intervention pilot study (QUAL + QUANT) was conducted with a diverse convenience sample of 19 first- and second-year speech-language pathology graduate students who engaged in a half-day TBI point-of-view simulation. The simulation was co-constructed through a participatory design with those living with TBI based on Kolb's experiential learning model and followed the recommendations for point-of-view simulation ethics.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!