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.

iTBS reveals the roles of domain-general cognitive control and language-specific brain regions during word formation rule learning.

Repeated exposure to word forms and meanings improves lexical knowledge acquisition. However, the roles of domain-general and language-specific brain regions during this process remain unclear. To investigate this, we applied intermittent theta burst stimulation over the domain-general (group left dorsolateral prefrontal cortex) and domain-specific (Group L IFG) brain regions, with a control group receiving sham intermittent theta burst stimulation. Intermittent theta burst stimulation effects were subsequently assessed in functional magnetic resonance imaging using an artificial word learning task which consisted of 3 learning phases. A generalized psychophysiological interaction analysis explored the whole brain functional connectivity, while dynamic causal modeling estimated causal interactions in specific brain regions modulated by intermittent theta burst stimulation during repeated exposure. Compared to sham stimulation, active intermittent theta burst stimulation improved word learning performance and reduced activation of the left insula in learning phase 2. Active intermittent theta burst stimulation over the domain-general region increased whole-brain functional connectivity and modulated effective connectivity between brain regions during repeated exposure. This effect was not observed when active intermittent theta burst stimulation was applied to the language-specific region. These findings suggest that the domain-general region plays a crucial role in word formation rule learning, with intermittent theta burst stimulation enhancing whole-brain connectivity and facilitating efficient information exchange between key brain regions during new word learning.

A developmental model of audio-visual attention (MAVA) for bimodal language learning in infants and robots.

A social individual needs to effectively manage the amount of complex information in his or her environment relative to his or her own purpose to obtain relevant information. This paper presents a neural architecture aiming to reproduce attention mechanisms (alerting/orienting/selecting) that are efficient in humans during audiovisual tasks in robots. We evaluated the system based on its ability to identify relevant sources of information on faces of subjects emitting vowels. We propose a developmental model of audio-visual attention (MAVA) combining Hebbian learning and a competition between saliency maps based on visual movement and audio energy. MAVA effectively combines bottom-up and top-down information to orient the system toward pertinent areas. The system has several advantages, including online and autonomous learning abilities, low computation time and robustness to environmental noise. MAVA outperforms other artificial models for detecting speech sources under various noise conditions.

Using the online version of the Trier Social Stress Test to investigate the effect of acute stress on functional lateralization.

How stress affects functional hemispheric asymmetries is relevant because stress represents a risk factor for the development of mental disorders and various mental disorders are associated with atypical lateralization. Using three lateralization tasks, we investigated whether functional hemispheric asymmetries in the form of hemispheric dominance for language (verbal dichotic listening task), emotion processing (emotional dichotic listening task), and visuo-spatial attention (line bisection task) were affected by acute stress in healthy adults. One hundred twenty right-handed men and women performed these lateralization tasks in randomized order after exposure to a mild online stressor (i.e., an online variant of the Trier Social Stress Test (TSST), TSST-OL) and a non-stressful online control task (friendly TSST-OL, fTSST-OL) in a within-subjects design. Importantly, the verbal and the emotional dichotic listening tasks were presented online whereas the line bisection task was completed in paper-pencil form. During these tasks, we found the expected hemispheric asymmetries, indicating that online versions of both the verbal and the emotional dichotic listening task can be used to measure functional hemispheric asymmetries in language and emotion processing remotely. Even though subjective and physiological markers confirmed the success of the online stress manipulation, replicating previous studies, we found no stress-induced effect on functional hemispheric asymmetries. Thus, in healthy participants, functional hemispheric asymmetries do not seem to change flexibly in response to acute stress.

Growing inequities by immigration group among older adults: population-based analysis of access to primary care and return to in-person visits during the COVID-19 pandemic in British Columbia, Canada.

BACKGROUND: The onset of the COVID-19 pandemic drove a rapid and widespread shift to virtual care, followed by a gradual return to in-person visits. Virtual visits may offer more convenient access to care for some, but others may experience challenges accessing care virtually, and some medical needs must be met in-person. Experiences of the shift to virtual care and benefits of in-person care may vary by immigration experience (immigration status and duration), official language level, and age. We examined use of virtual care and return to in-person visits in the Canadian province of British Columbia (BC), comparing patterns by age and across immigration groups, including length of time in Canada and language level (official languages English and French) at time of arrival. METHODS: We used linked administrative health and immigration data to examine total primary care visits (virtual or in-person) and return to in-person visits during the COVID-19 pandemic (2019/20-2021/2) in BC. We examined the proportion of people with any primary care visits and with any in-person visits within each year as measures of access to primary care. We estimated the odds of any primary care visits and any in-person visits by immigration group and official language level assessed prior to arrival: non-immigrants, long-term immigrants, recent immigrants (< 5 years) with high assessed official language level and recent immigrants (< 5 years) with low assessed official language level (assessed prior to arrival), stratified by age. RESULTS: In general, changes in access to primary care (odds of any visits and odds of any in-person visits) were similar across immigration groups over the study period. However, we observed substantial disparities in access to primary care by immigration group among people aged 60 + , particularly in recent immigrants with low official language level (0.42, 0.40-0.45). These disparities grew wider over the course of the pandemic. CONCLUSION: Though among younger adults changes in access to primary care between 2019-2021 were similar across immigration groups, we observed significant and growing inequities among older adults, with particularly limited access among adults who immigrated recently and with low assessed official language level. Targeted interventions to ensure acceptable, accessible care for older immigrants are needed.

Language use predicts symptoms of fragile X-associated tremor/ataxia syndrome in men and women with the FMR1 premutation.

Fragile X-associated tremor/ataxia syndrome (FXTAS) is an age-related neurodegenerative disorder caused by a premutation of the FMR1 gene on the X chromosome. Despite the pervasive physical and cognitive effects of FXTAS, no studies have examined language in symptomatic males and females, limiting utility as an outcome measure in clinical trials of FXTAS. The goal of this work is to determine (a) the extent to which male and female FMR1 premutation carriers with FXTAS symptoms differ in their language use and (b) whether language production predicts FXTAS symptoms. Thirty-one individuals with the FMR1 premutation (21M, 10F), ages 58-85 years with some symptoms of FXTAS, were recruited from a larger cross-sectional study. Participants completed a five-minute monologic language sample. Language transcripts were assessed for rate of dysfluencies, lexical-semantics, syntax, and speech rate. Multivariable linear and ordinal regressions were used to predict FXTAS-associated symptoms, cognitive functioning, and executive functioning. Males and females did not differ in their language use. Language production predicted FXTAS symptom severity, cognitive functioning, and executive functioning. Language production difficulties may co-occur with FXTAS-associated symptoms and may be a viable outcome measure in future clinical trials, with future research needed.

Hyperscanning shows friends explore and strangers converge in conversation.

During conversation, people often endeavor to convey information in an understandable way (finding common ground) while also sharing novel or surprising information (exploring new ground). Here, we test how friends and strangers balance these two strategies to connect with each other. Using fMRI hyperscanning, we measure a preference for common ground as convergence over time and exploring new ground as divergence over time by tracking dyads' neural and linguistic trajectories over the course of semi-structured intimacy-building conversations. In our study, 60 dyads (30 friend dyads) engaged in a real-time conversation with discrete prompts and demarcated turns. Our analyses reveal that friends diverge neurally and linguistically: their neural patterns become more dissimilar over time and they explore more diverse topics. In contrast, strangers converge: neural patterns and language become more similar over time. The more a conversation between strangers resembles the exploratory conversations of friends, the more they enjoy it. Our results highlight exploring new ground as a strategy for a successful conversation.

Understanding the Role of Eye Movement Pattern and Consistency in Isolated English Word Reading Through Hidden Markov Modeling.

In isolated English word reading, readers have the optimal performance when their initial eye fixation is directed to the area between the beginning and word center, that is, the optimal viewing position (OVP). Thus, how well readers voluntarily direct eye gaze to this OVP during isolated word reading may be associated with reading performance. Using Eye Movement analysis with Hidden Markov Models, we discovered two representative eye movement patterns during lexical decisions through clustering, which focused at the OVP and the word center, respectively. Higher eye movement similarity to the OVP-focusing pattern predicted faster lexical decision time in addition to cognitive abilities and lexical knowledge. However, the OVP-focusing pattern was associated with longer isolated single letter naming time, suggesting conflicting visual abilities required for identifying isolated letters and multi-letter words. In contrast, in both word and pseudoword naming, although clustering did not reveal an OVP-focused pattern, higher consistency of the first fixation as measured in entropy predicted faster naming time in addition to cognitive abilities and lexical knowledge. Thus, developing a consistent eye movement pattern focusing on the OVP is essential for word orthographic processing and reading fluency. This finding has important implications for interventions for reading difficulties.

Exploring Early Number Abilities With Multimodal Transformers.

Early number skills represent critical milestones in children's cognitive development and are shaped over years of interacting with quantities and numerals in various contexts. Several connectionist computational models have attempted to emulate how certain number concepts may be learned, represented, and processed in the brain. However, these models mainly used highly simplified inputs and focused on limited tasks. We expand on previous work in two directions: First, we train a model end-to-end on video demonstrations in a synthetic environment with multimodal visual and language inputs. Second, we use a more holistic dataset of 35 tasks, covering enumeration, set comparisons, symbolic digits, and seriation. The order in which the model acquires tasks reflects input length and variability, and the resulting trajectories mostly fit with findings from educational psychology. The trained model also displays symbolic and non-symbolic size and distance effects. Using techniques from interpretability research, we investigate how our attention-based model integrates cross-modal representations and binds them into context-specific associative networks to solve different tasks. We compare models trained with and without symbolic inputs and find that the purely non-symbolic model employs more processing-intensive strategies to determine set size.

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.

Beyond the here and now: hunter-gatherer socio-spatial complexity and the evolution of language.

Human evolutionary ecology stands to benefit by integrating theory and methods developed in movement ecology, and in turn, to make contributions to the broader field of movement ecology by leveraging our species' distinct attributes. In this paper, we review data and evolutionary models suggesting that major changes in socio-spatial behaviour accompanied the evolution of language. To illustrate and explore these issues, we present a comparison of GPS measures of the socio-spatial behaviour of Hadza hunter-gatherers of northern Tanzania to those of olive baboons (Papio anubis), a comparatively small-brained primate that is also savanna-adapted. While standard spatial metrics show modest differences, measures of spatial diversity, landscape exploration and spatiotemporal displacement between individuals differ markedly. Groups of Hadza foragers rapidly accumulate a vast, diverse knowledge pool about places and things over the horizon, contrasting with the baboon's narrower and more homogeneous pool of ecological information. The larger and more complex socio-spatial world illustrated by the Hadza is one where heightened cognitive abilities for spatial and episodic memory, navigation, perspective taking and communication about things beyond the here and now all have clear value.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

The Effect of Metacognitive Intervention on the Listening Performance and Metacognitive Awareness of High- and Low-Working Memory Capacity EFL Learners.

EFL listening comprehension has been a stark challenge for language learners, but little is known about the combined effect of individual differences, such as working memory capacity, and metacognitive intervention. Thus, the present experimental study investigates the effect of metacognitive intervention on the listening performance and metacognitive awareness of high- and low-WMC EFL learners. For this purpose, Oxford Placement Tests were distributed among 120 male Iranian EFL learners, of which 94 were identified as intermediate. Then, backward visual digit span tests were administered to measure their working memory capacity. Based on the median of all scores, 80 learners were selected and randomly assigned to two experimental groups and two control groups each with 20 participants. Next, their performance on the International English Language Testing System and the Metacognitive Awareness Listening Questionnaire was measured before and after the 8-session metacognitive intervention. Results showed that high-WMC experimental learners had a higher gain with a large effect size in terms of listening performance compared with all the other groups. In addition, the experimental group learners reported the significantly higher use of the metacognitive strategies with a moderate effect size. Interestingly, low-WMC learners' listening performance and metacognitive awareness also improved as a result of the intervention. Our findings bear pedagogical significance in that individual differences in WMC should be considered more in both EFL language classes and the future line of research involving the metacognitive intervention.

Co-speech head nods are used to enhance prosodic prominence at different levels of narrow focus in French.

Previous research has shown that prosodic structure can regulate the relationship between co-speech gestures and speech itself. Most co-speech studies have focused on manual gestures, but head movements have also been observed to accompany speech events by Munhall, Jones, Callan, Kuratate, and Vatikiotis-Bateson [(2004). Psychol. Sci. 15(2), 133-137], and these co-verbal gestures may be linked to prosodic prominence, as shown by Esteve-Gibert, Borrás-Comes, Asor, Swerts, and Prieto [(2017). J. Acoust. Soc. Am. 141(6), 4727-4739], Hadar, Steiner, Grant, and Rose [(1984). Hum. Mov. Sci. 3, 237-245], and House, Beskow, and Granström [(2001). Lang. Speech 26(2), 117-129]. This study examines how the timing and magnitude of head nods may be related to degrees of prosodic prominence connected to different focus conditions. Using electromagnetic articulometry, a time-varying signal of vertical head movement for 12 native French speakers was generated to examine the relationship between head nod gestures and F0 peaks. The results suggest that speakers use two different alignment strategies, which integrate both temporal and magnitudinal aspects of the gesture. Some evidence of inter-speaker preferences in the use of the two strategies was observed, although the inter-speaker variability is not categorical. Importantly, prosodic prominence itself is not the cause of the difference between the two strategies, but instead magnifies their inherent differences. In this way, the use of co-speech head nod gestures under French focus conditions can be considered as a method of prosodic enhancement.

Latent Relations at Steady-state with Associative Nets.

Models of word meaning that exploit patterns of word usage across large text corpora to capture semantic relations, like the topic model and word2vec, condense word-by-context co-occurrence statistics to induce representations that organize words along semantically relevant dimensions (e.g., synonymy, antonymy, hyponymy, etc.). However, their reliance on latent representations leaves them vulnerable to interference, makes them slow learners, and commits to a dual-systems account of episodic and semantic memory. We show how it is possible to construct the meaning of words online during retrieval to avoid these limitations. We implement a spreading activation account of word meaning in an associative net, a one-layer highly recurrent network of associations, called a Dynamic-Eigen-Net, that we developed to address the limitations of earlier variants of associative nets when scaling up to deal with unstructured input domains like natural language text. We show that spreading activation using a one-hot coded Dynamic-Eigen-Net outperforms the topic model and reaches similar levels of performance as word2vec when predicting human free associations and word similarity ratings. Latent Semantic Analysis vectors reached similar levels of performance when constructed by applying dimensionality reduction to the Shifted Positive Pointwise Mutual Information but showed poorer predictability for free associations when using an entropy-based normalization. An analysis of the rate at which the Dynamic-Eigen-Net reaches asymptotic performance shows that it learns faster than word2vec. We argue in favor of the Dynamic-Eigen-Net as a fast learner, with a single-store, that is not subject to catastrophic interference. We present it as an alternative to instance models when delegating the induction of latent relationships to process assumptions instead of assumptions about representation.

Incremental Discourse-Update Constrains Number Agreement Attraction Effect.

While a large body of work in sentence comprehension has explored how different types of linguistic information are used to guide syntactic parsing, less is known about the effect of discourse structure. This study investigates this question, focusing on the main and subordinate discourse contrast manifested in the distinction between restrictive relative clauses (RRCs) and appositive relative clauses (ARCs) in American English. In three self-paced reading experiments, we examined whether both RRCs and ARCs interfere with the matrix clause content and give rise to the agreement attraction effect. While the standard attraction effect was consistently observed in the baseline RRC structures, the effect varied in the ARC structures. These results collectively suggest that discourse structure indeed constrains syntactic dependency resolution. Most importantly, we argue that what is at stake is not the static discourse structure properties at the global sentence level. Instead, attention should be given to the incremental update of the discourse structure in terms of which discourse questions are active at any given moment of a discourse. The current findings have implications for understanding the way discourse structure, specifically the active state of discourse questions, constrains memory retrieval.

The future of large language models in social science research: Reply to Berger (2024) and Carrillo et al. (2024).

In their commentaries, Berger (2024) and Carrillo et al. (2024) raise several thoughtful questions regarding machine-assisted hypothesis generation in the social sciences. We discuss their ideas and build upon them. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Adults Adapt to Child Speech in Causative Semantics.

Causation is a core feature of human cognition and language. How children learn about intricate causal meanings is yet unresolved. Here, we focus on how children learn verbs that express causation. Such verbs, known as lexical causatives (e.g., break and raise), lack explicit morphosyntactic markers indicating causation, thus requiring that the child generalizes the causal meaning from the context. The language addressed to children presumably plays a crucial role in this learning process. Hence, we tested whether adults adapt their use of lexical causatives to children when talking to them in day-to-day interactions. We analyzed naturalistic longitudinal data from 12 children in the Manchester corpus (spanning from 20 to 36 months of age). To detect semantic generalization, we employed a network approach with semantics learned from cross-situational contexts. Our results show an increasing trend in the expansion of causative semantics, observable in both child speech and child-directed speech. Adults consistently maintain somewhat more intricate causative semantic networks compared to children. However, both groups display evolving patterns. Around 28-30 months of age, children undergo a reduction in the degree of causative generalization, followed by a slightly time-lagged adjustment by adults in their speech directed to children. These findings substantiate adults' adaptation in child-directed speech, extending to semantics. They highlight child-directed speech as a highly adaptive and subconscious teaching tool that facilitates the dynamic processes of language acquisition.

Language sentiment predicts changes in depressive symptoms.

The prevalence of depression is a major societal health concern, and there is an ongoing need to develop tools that predict who will become depressed. Past research suggests that depression changes the language we use, but it is unclear whether language is predictive of worsening symptoms. Here, we test whether the sentiment of brief written linguistic responses predicts changes in depression. Across two studies (N = 467), participants provided responses to neutral open-ended questions, narrating aspects of their lives relevant to depression (e.g., mood, motivation, sleep). Participants also completed the Patient Health Questionnaire (PHQ-9) to assess depressive symptoms and a risky decision-making task with periodic measurements of momentary happiness to quantify mood dynamics. The sentiment of written responses was evaluated by human raters (N = 470), Large Language Models (LLMs; ChatGPT 3.5 and 4.0), and the Linguistic Inquiry and Word Count (LIWC) tool. We found that language sentiment evaluated by human raters and LLMs, but not LIWC, predicted changes in depressive symptoms at a three-week follow-up. Using computational modeling, we found that language sentiment was associated with current mood, but language sentiment predicted symptom changes even after controlling for current mood. In summary, we demonstrate a scalable tool that combines brief written responses with sentiment analysis by AI tools that matches human performance in the prediction of future psychiatric symptoms.

Culture shapes how we describe facial expressions.

From Darwin through Wittgenstein to contemporary scientific investigations, it has been argued humans tend to view facial expressions through a mentalistic lens. According to this view, when looking at someone's expressive face, we see emotion and are unable to describe the face in behavioral terms, i.e., name the details of facial movements. At the same time, however, a growing body of work shows cultures in fact differ in the degree of importance they attribute to mental states and willingness to discuss them. Is this variation reflected in the linguistic coding of facial expressions? To explore this, we conducted two facial expression naming tasks targeting mental states and facial movements with speakers of Maniq (Austroasiatic, Thailand) and Polish (Indo-European, Poland), representing highly diverse linguistic and cultural settings. We found that, while Polish speakers conformed with the predicted orientation towards mental states, this did not hold for Maniq speakers. The Maniq were instead oriented towards behavioral aspects of faces, naming them more frequently, more precisely, and with higher consensus, compared to the Polish. These differences are carved into the Maniq and Polish lexicons, suggesting diverse cultures exhibit differential specialization in verbalizing expressive faces.