Language delay and communication deficits are a core characteristic of the fragile X syndrome (FXS) phenotype. To date, the literature examining early language development in FXS is limited potentially due to barriers in language assessment in very young children. The present study is one of the first to examine early language development through vocal production and the language learning environment in infants and toddlers with FXS utilizing an automated vocal analysis system. Child vocalizations, conversational turns, and adult word counts in the home environment were collected and analyzed in a group of nine infants and toddlers with FXS and compared to a typically developing (TD) normative sample. Results suggest infants and toddlers with FXS are exhibiting deficits in their early language skills when compared to their chronological expectations. Despite this, when accounting for overall developmental level, their early language skills appear to be on track. Additionally, FXS caregivers utilize less vocalizations around infants and toddlers with FXS; however, additional research is needed to understand the true gap between FXS caregivers and TD caregivers. These findings provide preliminary information about the early language learning environment and support for the feasibility of utilizing an automated vocal analysis system within the FXS population that could ease data collection and further our understanding of the emergence of language development.
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http://dx.doi.org/10.3390/brainsci9020027 | DOI Listing |
PLoS One
January 2025
School of Emergency Management, Institute of Disaster Prevention, Sanhe, Hebei, China.
With the increasing number of patients with Alzheimer's Disease (AD), the demand for early diagnosis and intervention is becoming increasingly urgent. The traditional detection methods for Alzheimer's disease mainly rely on clinical symptoms, biomarkers, and imaging examinations. However, these methods have limitations in the early detection of Alzheimer's disease, such as strong subjectivity in diagnostic criteria, high detection costs, and high misdiagnosis rates.
View Article and Find Full Text PDFLanguage is a sophisticated cognitive skill that relies on the coordinated activity of cerebral cortex. Acquiring a second language creates intricate modifications in brain connectivity. Although considerable studies have evaluated the impact of second language acquisition on brain networks in adulthood, the results regarding the ultimate form of adaptive plasticity remain inconsistent within the adult population.
View Article and Find Full Text PDFPrior research has indicated musicians show an auditory processing advantage in phonemic processing of language. The aim of the current study was to elucidate when in the auditory cortical processing stream this advantage emerges in a cocktail-party-like environment. Participants (n = 34) were aged 18-35 years and deemed to be either a musician (10+-year experience) or nonmusician (no formal training).
View Article and Find Full Text PDFAm J Speech Lang Pathol
January 2025
Department of Speech and Hearing Science, The Ohio State University, Columbus.
Purpose: Vocabulary access is important for individuals who use augmentative and alternative communication (AAC), especially for children in the early stages of language learning. This study sought to understand how accurate speech-language pathologists (SLPs), teachers, and parents are in predicting the vocabulary needed by early symbolic communicators who use AAC in three contexts.
Method: Ten groups, each with a child who used AAC as their primary mode of communication and who was classified as an early symbolic communicator and their parent, teacher, and SLP, participated.
Alzheimers Dement
January 2025
Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.
Introduction: The automated analysis of connected speech using natural language processing (NLP) emerges as a possible biomarker for Alzheimer's disease (AD). However, it remains unclear which types of connected speech are most sensitive and specific for the detection of AD.
Methods: We applied a language model to automatically transcribed connected speech from 114 Flemish-speaking individuals to first distinguish early AD patients from amyloid negative cognitively unimpaired (CU) and then amyloid negative from amyloid positive CU individuals using five different types of connected speech.
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