Language development

Communication is challenging for disabled individuals, but with advancement of brain-computer interface (BCI) systems, alternative communication systems can be developed. Current BCI spellers, such as P300, SSVEP, and MI, have drawbacks like reliance on external stimuli or conversation irrelevant mental tasks. In contrast to these systems, Imagined speech based BCI systems rely on directly decoding the vowels/words user is thinking, making them more intuitive, user friendly and highly popular among Brain-Computer-Interface (BCI) researchers...

African immigrants are moving to high-income nations such as Canada in greater numbers in search of a better life. These immigrants frequently struggle with several issues, including limited social support, shifts in gender roles/status, cultural conflicts with their children, and language barriers. We used participatory action research (PAR) to gather data about Sub-Saharan African immigrants residing in Alberta, Canada, with a focus on their viewpoints, difficulties, and experiences of parenting children in Canada...

With recent advancements in robotic surgery, notable strides have been made in visual question answering (VQA). Existing VQA systems typically generate textual answers to questions but fail to indicate the location of the relevant content within the image. This limitation restricts the interpretative capacity of the VQA models and their ability to explore specific image regions. To address this issue, this study proposes a grounded VQA model for robotic surgery, capable of localizing a specific region during answer prediction...

Background: Music therapy is increasingly examined in randomized controlled trials (RCTs) and shows potential in treating post-traumatic stress disorder (PTSD). Objective: This systematic review and meta-analysis critically evaluates the current clinical evidence supporting the efficacy and acceptability of music therapy for PTSD. Method: RCTs comparing music therapy in addition to care as usual (CAU) versus either CAU alone or CAU combined with standard psychotherapy/pharmacotherapy for PTSD were retrieved from major English - and Chinese-language databases...

Children exhibit preferences for familiar accents early in life. However, they frequently have more difficulty distinguishing between first language (L1) accents than second language (L2) accents in categorization tasks. Few studies have addressed children's perception of accent strength, or the relation between accent strength and objective measures of pronunciation distance. To address these gaps, 6- and 12-year-olds and adults ranked talkers' perceived distance from the local accent (i.e., Midland American English)...

Many studies have explored children's acquisition of temporal adverbs. However, the extent to which children's early temporal language has discursive instead of solely temporal meanings has been largely ignored. We report two corpus-based studies that investigated temporal adverbs in Finnish child-parent interaction between the children's ages of 1;7 and 4;11. Study 1 shows that the two corpus children used temporal adverbs to construe both temporal and discursive meanings from their early adverb production and that the children's usage syntactically broadly reflected the input received...

The challenge of information overload in the legal domain increases every day. The COLIEE competition has created four challenge tasks that are intended to encourage the development of systems and methods to alleviate some of that pressure: a case law retrieval (Task 1) and entailment (Task 2), and a statute law retrieval (Task 3) and entailment (Task 4). Here we describe our methods for Task 1 and Task 4. In Task 1, we used a sentence-transformer model to create a numeric representation for each case paragraph...

Transformer neural networks show promising capabilities, in particular for uses in materials analysis, design, and manufacturing, including their capacity to work effectively with human language, symbols, code, and numerical data. Here, we explore the use of large language models (LLMs) as a tool that can support engineering analysis of materials, applied to retrieving key information about subject areas, developing research hypotheses, discovery of mechanistic relationships across disparate areas of knowledge, and writing and executing simulation codes for active knowledge generation based on physical ground truths...

OBJECTIVES: Addressing the lack of German-language instruments, this study aims to develop a questionnaire that enables the measurement of work values. According to the theory of basic human values (Schwartz, 1992), a culturally fitting questionnaire is validated by covering constructs in the four broader dimensions of Social, Prestige, Intrinsic, and Extrinsic work values. Convergent, discriminant and incremental congruent validity are assessed. METHOD: Data were collected in a cross-sectional online-based panel survey...

Alongside an explosion in research and development related to large language models, there has been a concomitant rise in the creation of pretraining datasets-massive collections of text, typically scraped from the web. Drawing on the field of archival studies, we analyze pretraining datasets as informal archives-heterogeneous collections of diverse material that mediate access to knowledge. We use this framework to identify impacts of pretraining data creation and use beyond directly shaping model behavior and reveal how choices about what is included in pretraining data necessarily involve subjective decisions about values...

BACKGROUND: Docosahexaenoic acid (DHA) plays a crucial role in the growth and functional development of the infant brain. However, the impact of additional DHA supplementation on neurodevelopment in infants remains controversial in randomized controlled trials. In this systematic review and meta-analysis, we aimed to investigate the effects of prenatal and postnatal DHA supplementation on neurodevelopment. METHODS: We systematically searched the MEDLINE, EMBASE, and Cochrane Library electronic databases using a predefined strategy until 8 February 2024...

Artificial neural networks have emerged as computationally plausible models of human language processing. A major criticism of these models is that the amount of training data they receive far exceeds that of humans during language learning. Here, we use two complementary approaches to ask how the models' ability to capture human fMRI responses to sentences is affected by the amount of training data. First, we evaluate GPT-2 models trained on 1 million, 10 million, 100 million, or 1 billion words against an fMRI benchmark...

In computational neurolinguistics, it has been demonstrated that hierarchical models such as recurrent neural network grammars (RNNGs), which jointly generate word sequences and their syntactic structures via the syntactic composition, better explained human brain activity than sequential models such as long short-term memory networks (LSTMs). However, the vanilla RNNG has employed the top-down parsing strategy, which has been pointed out in the psycholinguistics literature as suboptimal especially for head-final/left-branching languages, and alternatively the left-corner parsing strategy has been proposed as the psychologically plausible parsing strategy...

The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap...

To learn new words, particularly verbs, child learners have been shown to benefit from the linguistic contexts in which the words appear. However, cross-linguistic differences affect how this process unfolds. One previous study found that children's abilities to learn a new verb differed across Korean and English as a function of the sentence in which the verb occurred (Arunachalam et al., 2013). The authors hypothesized that the properties of word order and argument drop, which vary systematically in these two languages, were driving the differences...

UNLABELLED: Hearing is an active process in which listeners must detect and identify sounds, segregate and discriminate stimulus features, and extract their behavioral relevance. Adaptive changes in sound detection can emerge rapidly, during sudden shifts in acoustic or environmental context, or more slowly as a result of practice. Although we know that context- and learning-dependent changes in the spectral and temporal sensitivity of auditory cortical neurons support many aspects of flexible listening, the contribution of subcortical auditory regions to this process is less understood...

Large language models (LLMs) have been proposed to support many healthcare tasks, including disease diagnostics and treatment personalization. While AI models may be applied to assist or enhance the delivery of healthcare, there is also a risk of misuse. LLMs could be used to allocate resources based on unfair, inaccurate, or unjust criteria. For example, a social credit system uses big data to assess "trustworthiness" in society, punishing those who score poorly based on evaluation metrics defined only by a power structure (corporate entity, governing body)...

Infant cerebral blood flow (CBF) delivers nutrients and oxygen to fulfill brain energy consumption requirements for the fastest period of postnatal brain development across lifespan. However, organizing principle of whole-brain CBF dynamics during infancy remains obscure. Leveraging a unique cohort of 100+ infants with high-resolution arterial spin labeled MRI, we found the emergence of the cortical hierarchy revealed by highest-resolution infant CBF maps available to date. Infant CBF across cortical regions increased in a biphasic pattern with initial rapid and sequentially slower rate, with break-point ages increasing along the limbic-sensorimotor-association cortical gradient...

Background: Recent socio-demographic shifts in the United States have underscored the growing importance of informal caregiving and raised concerns about caregivers' health and well-being. This study aims to deepen our understanding of the health dimensions of caregivers, considering their diverse backgrounds. Objective: To examine five key health dimensions (physical, cognitive, mental, social, and sexual health) of caregivers, and to identify potential disparities based on ethnoracial and linguistic differences...

The development of programming skills and computational thinking in the formal educational context is one of the most recent horizons set by many educational systems worldwide. Although the first computational thinking initiatives are being applied from the earliest school ages, this research focuses on the secondary education level. Specifically, the objective is the following: to analyse the implementation of Arduino, as well as the benefits and opportunities it brings to secondary school students. For this purpose, documentary research has been undertaken applying a systematic review according to the PRISMA 2020 framework following the PiCoS strategy...