Cross-linguistic and acoustic-driven effects on multiscale neural synchrony to stress rhythms.

We investigated how neural oscillations code the hierarchical nature of stress rhythms in speech and how stress processing varies with language experience. By measuring phase synchrony of multilevel EEG-acoustic tracking and intra-brain cross-frequency coupling, we show the encoding of stress involves different neural signatures (delta rhythms = stress foot rate; theta rhythms = syllable rate), is stronger for amplitude vs. duration stress cues, and induces nested delta-theta coherence mirroring the stress-syllable hierarchy in speech. Only native English, but not Mandarin, speakers exhibited enhanced neural entrainment at central stress (2 Hz) and syllable (4 Hz) rates intrinsic to natural English. English individuals with superior cortical-stress tracking capabilities also displayed stronger neural hierarchical coherence, highlighting a nuanced interplay between internal nesting of brain rhythms and external entrainment rooted in language-specific speech rhythms. Our cross-language findings reveal brain-speech synchronization is not purely a "bottom-up" but benefits from "top-down" processing from listeners' language-specific experience.

Large language models predict human sensory judgments across six modalities.

Determining the extent to which the perceptual world can be recovered from language is a longstanding problem in philosophy and cognitive science. We show that state-of-the-art large language models can unlock new insights into this problem by providing a lower bound on the amount of perceptual information that can be extracted from language. Specifically, we elicit pairwise similarity judgments from GPT models across six psychophysical datasets. We show that the judgments are significantly correlated with human data across all domains, recovering well-known representations like the color wheel and pitch spiral. Surprisingly, we find that a model (GPT-4) co-trained on vision and language does not necessarily lead to improvements specific to the visual modality, and provides highly correlated predictions with human data irrespective of whether direct visual input is provided or purely textual descriptors. To study the impact of specific languages, we also apply the models to a multilingual color-naming task. We find that GPT-4 replicates cross-linguistic variation in English and Russian illuminating the interaction of language and perception.

Test preparation breeds success: Two quasi-experimental interventions in the context of the Swiss aptitude test for medical-school admissions.

BACKGROUND: In Switzerland, the scholastic aptitude test for medical-school selection takes place in three languages. This study examined the effects of two quasi-experimental interventions that aimed to reduce existing differences in test results between the French- and German-speaking language candidates. METHODS: Between 2018 and 2023, the population of applicants to Swiss medical schools consisted of N = 18'824 German- and French-speaking individuals. Based on a quasi-experimental design, we examined the effects of two interventions regarding preparatory material, in these cohorts. The first intervention (2022) consisting of practice trials in baccalaureate schools in the canton of Fribourg enabled French-speaking candidates primarily from the canton of Fribourg to prepare more intensively with official tasks. Practice trials enable future candidates to complete a published test version under original conditions and thus prepare how to approach the real test. The second intervention (2023) released new preparatory material in all languages for one group of tasks for which differences between the language groups were more pronounced than in the other tasks. The test provider offered this material for free download together with existing preparation materials and thereby enabled more intensive preparation. RESULTS: After the first intervention, the initially small to medium-sized mean differences in z-transformed test scores between French-speaking candidates from Fribourg and German-speaking candidates were nearly eliminated (from 0.39 to 0.05). Also for French-speaking candidates from outside of the canton of Fribourg, the mean differences were smaller than before the intervention (0.48 before, 0.39 after first intervention). After the second intervention, particularly the mean differences in test scores between German-speaking and French-speaking candidates from outside of Fribourg were further reduced (to 0.24). CONCLUSIONS: The two interventions regarding material for preparing to participate in the aptitude test affected candidates' test scores. They reduced the gap between German- and French-speaking candidates showing that the additional benefits of commercial offers for test preparation are limited. Hence, offering comparable official preparation material to all language groups enhances test fairness.

Implementing a Diet Risk Score (DRS) for Spanish-Speaking Adults in a Clinical Setting: A Feasibility Study.

Tools to briefly assess diet among US Spanish-speaking adults are needed to identify individuals at risk for cardiometabolic disease (CMD) related to diet. Two registered dietitian nutritionists (RDNs) recruited bilingual medical students to translate the validated Diet Risk Score (DRS) into Spanish (DRS-S). Participants were recruited from a federally qualified health center. Students administered the DRS-S and one 24-h recall (Automated Self-Administered 24-Hour (ASA24®) Dietary Assessment Tool) on one day; a second recall was administered within 1 week. Recalls were scored using the Healthy Eating Index (HEI)-2015, a measure of adherence to the Dietary Guidelines for Americans. Spearman correlations, weighted kappa, and ANOVA were conducted using SAS 9.4 to assess the relative validity of the DRS-S. Thirty-one Spanish-speaking adults (female: n = 17, 53%; mean age: 58 (42-69)) completed assessments. The mean DRS-S was 9 (SD = 4.2) (max: 27; higher score = higher risk) and the mean HEI-2015 score was 65.7 (SD = 9.7) (max: 100; higher score = lower risk), with significant agreement between measures (r: -0.45 (p = 0.01)), weighted kappa: -0.3 (p = 0.03). The DRS-S can be used in resource-constrained settings to assess diet for intervention and referral to RDNs. The DRS-S should be tested in clinical care to assess the impact of dietary changes to reduce CMD risk.

Language experience shapes predictive coding of rhythmic sound sequences.

Perceptual systems heavily rely on prior knowledge and predictions to make sense of the environment. Predictions can originate from multiple sources of information, including contextual short-term priors, based on isolated temporal situations, and context-independent long-term priors, arising from extended exposure to statistical regularities. While the effects of short-term predictions on auditory perception have been well-documented, how long-term predictions shape early auditory processing is poorly understood. To address this, we recorded magnetoencephalography data from native speakers of two languages with different word orders (Spanish: functor-initial vs Basque: functor-final) listening to simple sequences of binary sounds alternating in duration with occasional omissions. We hypothesized that, together with contextual transition probabilities, the auditory system uses the characteristic prosodic cues (duration) associated with the native language's word order as an internal model to generate long-term predictions about incoming non-linguistic sounds. Consistent with our hypothesis, we found that the amplitude of the mismatch negativity elicited by sound omissions varied orthogonally depending on the speaker's linguistic background and was most pronounced in the left auditory cortex. Importantly, listening to binary sounds alternating in pitch instead of duration did not yield group differences, confirming that the above results were driven by the hypothesized long-term 'duration' prior. These findings show that experience with a given language can shape a fundamental aspect of human perception - the neural processing of rhythmic sounds - and provides direct evidence for a long-term predictive coding system in the auditory cortex that uses auditory schemes learned over a lifetime to process incoming sound sequences.

Quality of Male and Female Medical Content on English-Language Wikipedia: Quantitative Content Analysis.

BACKGROUND: Wikipedia is the largest free online encyclopedia and the seventh most visited website worldwide, containing >45,000 freely accessible English-language medical articles accessed nearly 1.6 billion times annually. Concerns have been expressed about the balance of content related to biological sex on Wikipedia. OBJECTIVE: This study aims to categorize the top 1000 most-read (most popular) English-language Wikipedia health articles for June 2019 according to the relevance of the article topic to each sex and quality. METHODS: In the first step, Wikipedia articles were identified using WikiProject Medicine Popular Pages. These were analyzed on 13 factors, including total views, article quality, and total number of references. In the second step, 2 general medical textbooks were used as comparators to assess whether Wikipedia's spread of articles was typical compared to the general medical coverage. According to the article's content, we proposed criteria with 5 categories: 1="exclusively female," 2="predominantly female but can also affect male individuals," 3="not sex specific or neutral," 4=predominantly male but can affect female individuals," and 5="exclusively male." RESULTS: Of the 1000 Wikipedia health articles, 993 (93.3%) were not sex specific and 67 (6.7%) were sex specific. There was no statistically significant difference in the number of reads per month between the sex-specific and non-sex-specific articles (P=.29). Coverage of female topics was higher (50/1000, 5%) than male topics (17/1000, 1.7%; this difference was also observed for the 2 medical textbooks, in which 90.2% (2330/2584) of content was not sex specific, female topics accounted for 8.1% (209/2584), and male topics for accounted for 1.7% (45/2584; statistically significant difference; Fisher exact test P=.03). Female-category articles were ranked higher on the Wikipedia medical topic importance list (top, high, or mid importance) than male-category articles (borderline statistical significance; Fisher exact test P=.05). Female articles had a higher number of total and unique references; a slightly higher number of page watchers, pictures, and available languages; and lower number of edits than male articles (all were statistically nonsignificant). CONCLUSIONS: Across several metrics, a sample of popular Wikipedia health-related articles for both sexes had comparable quality. Wikipedia had a lower number of female articles and a higher number of neutral articles relative to the 2 medical textbooks. These differences were small, but statistically significant. Higher exclusively female coverage, compared to exclusively male coverage, in Wikipedia articles was similar to the 2 medical textbooks and can be explained by inclusion of sections on obstetrics and gynecology. This is unlike the imbalance seen among biographies of living people, in which approximately 77.6% pertain to male individuals. Although this study included a small sample of articles, the spread of Wikipedia articles may reflect the readership and the population's content consumption at a given time. Further study of a larger sample of Wikipedia articles would be valuable.

Quality Measurement of Consumer Health Questions: Content and Language Perspectives.

BACKGROUND: Health information consumers increasingly rely on question-and-answer (Q&A) communities to address their health concerns. However, the quality of questions posted significantly impacts the likelihood and relevance of received answers. OBJECTIVE: This study aims to improve our understanding of the quality of health questions within web-based Q&A communities. METHODS: We develop a novel framework for defining and measuring question quality within web-based health communities, incorporating content- and language-based variables. This framework leverages k-means clustering and establishes automated metrics to assess overall question quality. To validate our framework, we analyze questions related to kidney disease from expert-curated and community-based Q&A platforms. Expert evaluations confirm the validity of our quality construct, while regression analysis helps identify key variables. RESULTS: High-quality questions were more likely to include demographic and medical information than lower-quality questions (P<.001). In contrast, asking questions at the various stages of disease development was less likely to reflect high-quality questions (P<.001). Low-quality questions were generally shorter with lengthier sentences than high-quality questions (P<.01). CONCLUSIONS: Our findings empower consumers to formulate more effective health information questions, ultimately leading to better engagement and more valuable insights within web-based Q&A communities. Furthermore, our findings provide valuable insights for platform developers and moderators seeking to enhance the quality of user interactions and foster a more trustworthy and informative environment for health information exchange.

Mirror invariance in the subsequent acquisition of a script with separate forms for reading and writing.

PURPOSE: Does suppression of mirror-invariance in one script generalize to a subsequently learned script? METHOD: We examined mirror invariance in writing and recognition among native Latin-scriptal children and adults (n = 181) learning the Hebrew print script (for reading), and among a subset (n = 92) also learning the Hebrew cursive script (for writing). Hebrew-Latin biscriptal Israeli adults (n = 17) provided comparison. RESULTS: For the most part, mirror invariance was more evident in Hebrew print than in Latin in both writing and recognition among native Latin-scriptals. The number of previously acquired scripts had no effect. Letters' text-frequency inversely affected written mirror-error frequency. Written reversal errors were less frequent in cursive; orientation recognition was more fluent in print. CONCLUSIONS: Mirror-invariance suppression in one's native script does not generalize to a subsequently acquired script. Factors affecting mirror-invariance suppression in the subsequent script include its form and function and individual letters' text-frequency.

Introduction to the Forum: Native Language, Dialect, and Foreign Accent in Dysarthria.

This timely collection is an international effort to serve as a foundation to encourage research that offers insights into the interaction between language variation and motor speech disorders. Specifically, this forum aimed to provide a platform that (a) explores and demonstrates the role of language variation in the manifestation of dysarthria, (b) considers language variation in clinical assessment and management, and (c) promotes awareness of diverse language backgrounds of people with dysarthria. The forum contains six articles, spanning a variety of research designs (cross-sectional, pre- and post-treatment), kinds of articles (tutorial, research article, commentary), and a range of languages from around the world (English, French, Korean Portuguese, Spanish).

Commonalities and variations in emotion representation across modalities and brain regions.

Humans express emotions through various modalities such as facial expressions and natural language. However, the relationships between emotions expressed through different modalities and their correlations with neural activities remain uncertain. Here, we aimed to unveil some of these uncertainties by investigating the similarity of emotion representations across modalities and brain regions. First, we represented various emotion categories as multi-dimensional vectors derived from visual (face), linguistic, and visio-linguistic data, and used representational similarity analysis to compare these modalities. Second, we examined the linear transferability of emotion representation from other modalities to the visual modality. Third, we compared the representational structure derived in the first step with those from brain activities across 360 regions. Our findings revealed that emotion representations share commonalities across modalities with modality-type dependent variations, and they can be linearly mapped from other modalities to the visual modality. Additionally, emotion representations in uni-modalities showed relatively higher similarity with specific brain regions, while multi-modal emotion representation was most similar to representations across the entire brain region. These findings suggest that emotional experiences are represented differently across various brain regions with varying degrees of similarity to different modality types, and that they may be multi-modally conveyable in visual and linguistic domains.

Language networks of normal-hearing infants exhibit topological differences between resting and steady states: An fNIRS functional connectivity study.

Task-related studies have consistently reported that listening to speech sounds activate the temporal and prefrontal regions of the brain. However, it is not well understood how functional organization of auditory and language networks differ when processing speech sounds from its resting state form. The knowledge of language network organization in typically developing infants could serve as an important biomarker to understand network-level disruptions expected in infants with hearing impairment. We hypothesized that topological differences of language networks can be characterized using functional connectivity measures in two experimental conditions (1) complete silence (resting) and (2) in response to repetitive continuous speech sounds (steady). Thirty normal-hearing infants (14 males and 16 females, age: 7.8 ± 4.8 months) were recruited in this study. Brain activity was recorded from bilateral temporal and prefrontal regions associated with speech and language processing for two experimental conditions: resting and steady states. Topological differences of functional language networks were characterized using graph theoretical analysis. The normalized global efficiency and clustering coefficient were used as measures of functional integration and segregation, respectively. We found that overall, language networks of infants demonstrate the economic small-world organization in both resting and steady states. Moreover, language networks exhibited significantly higher functional integration and significantly lower functional segregation in resting state compared to steady state. A secondary analysis that investigated developmental effects of infants aged 6-months or below and above 6-months revealed that such topological differences in functional integration and segregation across resting and steady states can be reliably detected after the first 6-months of life. The higher functional integration observed in resting state suggests that language networks of infants facilitate more efficient parallel information processing across distributed language regions in the absence of speech stimuli. Moreover, higher functional segregation in steady state indicates that the speech information processing occurs within densely interconnected specialized regions in the language network.

The influence of enjoyment, boredom, and burnout on EFL achievement: Based on latent moderated structural equation modeling.

In recent years, the boom in the field of positive psychology in second language acquisition research has seen an increasing number of scholars focusing on the individual well-being of second language learners alongside their learning effectiveness. Despite this growing interest, there is a need to further investigate the specific emotional factors influencing academic achievement in foreign language learning. This study investigates the impact of three emotions-enjoyment, boredom, and burnout-on academic achievement, and the moderating role of academic buoyancy. Data were collected from 563 college English-as-a-foreign-language (EFL) students from China's mainland using latent moderated structural equation modeling with Mplus. The results of the latent bivariate correlation analysis showed significant correlations between EFL learning emotions, academic buoyancy, and test performance. In the latent moderated structural equations model, enjoyment and burnout predicted test performance. Moreover, academic buoyancy moderated the relationships between enjoyment and test performance, and between burnout and test performance. EFL test performance was highest when enjoyment and buoyancy were both high, or when burnout and buoyancy were both low. These findings highlight the importance of fostering positive emotions and resilience in language learners to enhance their academic performance, offering valuable insights for educators and policymakers aiming to improve foreign language education.

Bridging Language Barriers in COVID-19 Research: Descriptive Study of AccesoCovid.com's Reach and User Engagement.

BACKGROUND: The COVID-19 pandemic underscored the challenge of swiftly disseminating research findings to a global audience. Language barriers further exacerbated disparities in access to timely scientific information, particularly for non-English speaking communities. The majority of COVID-19 research was published in English, limiting accessibility for Spanish-speaking populations. OBJECTIVE: This paper aims to assess the reach and effectiveness of AccesoCovid.com, a platform designed to disseminate up-to-date COVID-19 research in both English and Spanish, addressing the language gap in scientific communication. METHODS: AccesoCovid.com was developed through a partnership between the University of California, San Francisco (UCSF) and Universidad Nacional Autónoma de México (UNAM). The website's performance and user engagement were evaluated using Google Analytics over a span of 2 years. Key metrics included user language preference, geographical distribution, and site traffic. The website summarized and translated 1032 articles on various COVID-19 topics, such as "Pharmaceutical Interventions and Vaccines." RESULTS: From February 2021 to February 2023, the platform attracted 57,000 users. Of the 43,000 unique new visitors, 84.2% (n=36,219) hailed from Spanish-speaking regions. The majority accessed the site organically through search engines, with 88.4% (n=38,000) of users arriving this way, while 5000 (11.6%) users accessed the site directly. Most users (n=30,894, 72.1%) preferred the Spanish version of the site. The website's most accessed category was "Pharmaceutical Interventions and Vaccines," followed by "Clinical Presentation and Management" and "Mental Health." Regarding language distribution, 72.1% (n=30,894) of users primarily used Spanish; 21.4% (n=9215) used English; and 6.7% (n=2891) spoke other languages, including Portuguese, Chinese, and German. Geographically, the website attracted visitors from 179 countries, with the highest visitor counts from Mexico (n=12,342, 28.7%), Spain (n=6405, 14.9%), the United States (n=4416, 10.3%), and Peru (n=3821, 8.9%). CONCLUSIONS: AccesoCovid.com successfully bridged a critical language gap in the dissemination of COVID-19 research. Its success underscores the pressing need for multilingual scientific resources. The platform demonstrated significant user engagement and reach, particularly in Spanish-speaking countries. This highlights the potential for similar platforms to ensure equitable access to scientific knowledge across diverse linguistic communities. Future efforts should focus on expanding to other languages and conducting formal evaluations to enhance user satisfaction and impact.

Le Petit Prince Hong Kong (LPPHK): Naturalistic fMRI and EEG data from older Cantonese speakers.

Currently, the field of neurobiology of language is based on data from only a few Indo-European languages. The majority of this data comes from younger adults neglecting other age groups. Here we present a multimodal database which consists of task-based and resting state fMRI, structural MRI, and EEG data while participants over 65 years old listened to sections of the story The Little Prince in Cantonese. We also provide data on participants' language history, lifetime experiences, linguistic and cognitive skills. Audio and text annotations, including time-aligned speech segmentation and prosodic information, as well as word-by-word predictors such as frequency and part-of-speech tagging derived from natural language processing (NLP) tools are included in this database. Both MRI and EEG data diagnostics revealed that the data has good quality. This multimodal database could advance our understanding of spatiotemporal dynamics of language comprehension in the older population and help us study the effects of healthy aging on the relationship between brain and behaviour.

Medical education in Hindi and indigenous languages in India: Issues and challenges.

In October 2022, the launch of first year MBBS books in Hindi language in the state of Madhya Pradesh in India kick started the debate on the introduction of Hindi/local language in medical education, which is currently being imparted in English. Opinions have been divided among the supporters of Hindi and local languages as well as opponents of this move. However, several issues need to be addressed before wider implementation of the policy of imparting medical education in Hindi/local languages. Right from infrastructure, human resource, economic impact, academic impact, international effects to legal issues have to be kept in mind and stakeholders must discuss these before implementation. A subsequent reversal of this policy, either through executive orders or judicial intervention, could lead to irreparable loss to students enrolled and trained in Hindi/local language.

The performance of OpenAI ChatGPT-4 and Google Gemini in virology multiple-choice questions: a comparative analysis of English and Arabic responses.

OBJECTIVE: The integration of artificial intelligence (AI) in healthcare education is inevitable. Understanding the proficiency of generative AI in different languages to answer complex questions is crucial for educational purposes. The study objective was to compare the performance ChatGPT-4 and Gemini in answering Virology multiple-choice questions (MCQs) in English and Arabic, while assessing the quality of the generated content. Both AI models' responses to 40 Virology MCQs were assessed for correctness and quality based on the CLEAR tool designed for evaluation of AI-generated content. The MCQs were classified into lower and higher cognitive categories based on the revised Bloom's taxonomy. The study design considered the METRICS checklist for the design and reporting of generative AI-based studies in healthcare. RESULTS: ChatGPT-4 and Gemini performed better in English compared to Arabic, with ChatGPT-4 consistently surpassing Gemini in correctness and CLEAR scores. ChatGPT-4 led Gemini with 80% vs. 62.5% correctness in English compared to 65% vs. 55% in Arabic. For both AI models, superior performance in lower cognitive domains was reported. Both ChatGPT-4 and Gemini exhibited potential in educational applications; nevertheless, their performance varied across languages highlighting the importance of continued development to ensure the effective AI integration in healthcare education globally.

Measurement method research of Chinese texts' difficulty based on two-characters continuations.

Two-characters continuation, which is a string with two characters emerging in linear sequence, can break through the encapsulation and independence of long solidified language chunks (words and phrases). In this way, two-characters continuation can measure the information of not only static language units (words and phrases) but also their combination in the text. Therefore, two-characters continuation is used as a measurement unit for investigating Chinese text's difficulty, to enhance the accuracy of measuring text's difficulty. Three different measurement methods of text's difficulty are proposed, which are respectively based on "continuation index of character", "new and stable two-characters continuation" and "emerging tendency of two-characters continuation". The results show that compared to other two methods, the measurement method of text's difficulty based on new and stable two-characters continuations has better effectiveness, whose accuracies for measuring text's difficulty with 6 levels, 3 levels and 2 levels difficulties can reach 36.4%, 64.6% and 79.6%, respectively. In addition, compared to Jiang and Wu's research works, the above measurement method also shows a better effectiveness.

Theta-band neural oscillations reflect cognitive control during language processing.

As we interpret language moment by moment, we often encounter conflicting cues in the input that create incompatible representations of sentence meaning, which must be promptly resolved. Although ample evidence suggests that cognitive control aids in the resolution of such conflict, the methods commonly used to assess cognitive control's involvement in language comprehension provide limited information about the time course of its engagement. Here, we show that neural oscillatory activity in the theta-band (∼3-8 Hz), which is associated with cognitive control in nonlinguistic tasks like Stroop and Flanker, provides a real-time index of cognitive control during language processing. We conducted time-frequency analyses of four electroencephalogram data sets, and consistently observed that increased theta-band power was elicited by various kinds of linguistic conflict. Moreover, increases in the degree of conflict within a sentence produced greater increases in theta activity. These effects emerged as early as 300 ms from the onset of the initiating event, indicating rapid cognitive-control recruitment during sentence processing in response to conflicting representations. Crucially, the effect patterns could not be ascribed to processing difficulty that is not due to conflict (e.g., semantic implausibility was neither necessary nor sufficient to elicit theta activity). We suggest that neural oscillations in the theta-band offer a reliable way to test specific hypotheses about cognitive-control engagement during real-time language comprehension. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Personality in Swahili culture: A psycho-lexical approach to trait structure in a language deprived of typical trait-descriptive adjectives.

This study was an endeavor to map out a personality trait structure of the Swahili language that may be used to develop indigenous eastern African personality assessment instruments. We followed the psycho-lexical approach where we not only identified trait terms from the Swahili dictionary but also from free descriptions collected from indigenous Swahili speakers. In combination, these two routines led to a pool of 3,732 personality-relevant terms, which was reduced in several steps to a set of 948 terms, identified as the most relevant trait-descriptive terms, including a small set of 26 adjectives, a large set of 531 nouns, and a substantial set of 391 verbs. This working set of 948 terms was lastly reduced to a final set of 661 most useful terms, converted into brief communicable sentences based on 439 nouns (comprising 250 type nouns and 189 attribute nouns), 199 verbs, and 23 adjectives. The list of 661 items was used to collect self and peer ratings from 480 university and high school students. An analysis of ratings on the 661 items revealed a six-factor personality trait structure that included Virtue, Imprudence, Negative Valence, Self-importance, Deceptiveness, and Attentive Conversation. Separate analyses were done using the type nouns, the attribute nouns, and the verbs, to assess the differential contribution of these word classes to the makeup of these Swahili Six. (PsycInfo Database Record (c) 2024 APA, all rights reserved).