The language environment to which children are exposed has an impact on later language abilities as well as on brain development; however, it is unclear how early such impacts emerge. This study investigates the effects of children's early language environment and socioeconomic status (SES) on brain structure in infancy at 6 and 30 months of age (both sexes included). We used magnetic resonance imaging to quantify concentrations of myelin in specific fiber tracts in the brain. Our central question was whether Language Environment Analysis (LENA) measures from in-home recording devices and SES measures of maternal education predicted myelin concentrations over the course of development. Results indicate that 30-month-old children exposed to larger amounts of in-home adult input showed more myelination in the white matter tracts most associated with language. Right hemisphere regions also show an association with SES, with older children from more highly educated mothers and exposed to more adult input, showing greater myelin concentrations in language-related areas. We discuss these results in relation to the current literature and implications for future research. This is the first study to look at how brain myelination is impacted by language input and socioeconomic status early in development. We find robust relationships of both factors in language-related brain areas at 30 months of age.
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http://dx.doi.org/10.1523/JNEUROSCI.1034-22.2023 | DOI Listing |
Heliyon
January 2025
Laboratory of Social and Solidarity Economy Governance and Development (LARESSGD), Department of Economics, Faculty of Law Economics and Social Sciences, Cadi Ayyad University, Marrakech, Morocco.
Early school dropout rates in Morocco exhibit widespread spatial imbalances leading to adverse consequences. Indeed, there is thus a pressing need to investigate the factors contributing to the phenomenon. To this end, this study conducts a multivariate spatial analysis of 75 provinces in Morocco.
View Article and Find Full Text PDFLangmuir
January 2025
Department of Chemical and Materials Engineering, University of Kentucky, Lexington, Kentucky 40506, United States.
Antibiofouling peptide materials prevent the nonspecific adsorption of proteins on devices, enabling them to perform their designed functions as desired in complex biological environments. Due to their importance, research on antibiofouling peptide materials has been one of the central subjects of interfacial engineering. However, only a few antibiofouling peptide sequences have been developed.
View Article and Find Full Text PDFDev Sci
March 2025
MARCS Institute for Brain, Behaviour, and Development, Western Sydney University, Sydney, Australia.
The classical view is that perceptual attunement to the native language, which emerges by 6-10 months, developmentally precedes phonological feature abstraction abilities. That assumption is challenged by findings from adults adopted into a new language environment at 3-5 months that imply they had already formed phonological feature abstractions about their birth language prior to 6 months. As phonological feature abstraction had not been directly tested in infants, we examined 4-6-month-olds' amodal abstraction of the labial versus coronal place of articulation distinction between consonants.
View Article and Find Full Text PDFJ Urban Health
January 2025
Department of Environmental Medicine and Climate Science, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, Box 1057, New York, NY, 10029, USA.
Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging.
View Article and Find Full Text PDFGROUP ACM SIGCHI Int Conf Support Group Work
January 2025
College of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, USA.
Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time sensor technologies. However, current solutions often require PVI to switch between multiple apps and tools for tasks like image recognition, navigation, and obstacle detection, which can hinder a seamless and efficient user experience. In this paper, we present NaviGPT, a high-fidelity prototype that integrates LiDAR-based obstacle detection, vibration feedback, and large language model (LLM) responses to provide a comprehensive and real-time navigation aid for PVI.
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