Taboo language across the globe: A multi-lab study.

The use of taboo words represents one of the most common and arguably universal linguistic behaviors, fulfilling a wide range of psychological and social functions. However, in the scientific literature, taboo language is poorly characterized, and how it is realized in different languages and populations remains largely unexplored. Here we provide a database of taboo words, collected from different linguistic communities (Study 1, N = 1046), along with their speaker-centered semantic characterization (Study 2, N = 455 for each of six rating dimensions), covering 13 languages and 17 countries from all five permanently inhabited continents. Our results show that, in all languages, taboo words are mainly characterized by extremely low valence and high arousal, and very low written frequency. However, a significant amount of cross-country variability in words' tabooness and offensiveness proves the importance of community-specific sociocultural knowledge in the study of taboo language.

Narcissus reflected: Grey and white matter features joint contribution to the default mode network in predicting narcissistic personality traits.

Despite the clinical significance of narcissistic personality, its neural bases have not been clarified yet, primarily because of methodological limitations of the previous studies, such as the low sample size, the use of univariate techniques and the focus on only one brain modality. In this study, we employed for the first time a combination of unsupervised and supervised machine learning methods, to identify the joint contributions of grey matter (GM) and white matter (WM) to narcissistic personality traits (NPT). After preprocessing, the brain scans of 135 participants were decomposed into eight independent networks of covarying GM and WM via parallel ICA. Subsequently, stepwise regression and Random Forest were used to predict NPT. We hypothesized that a fronto-temporo parietal network, mainly related to the default mode network, may be involved in NPT and associated WM regions. Results demonstrated a distributed network that included GM alterations in fronto-temporal regions, the insula and the cingulate cortex, along with WM alterations in cerebellar and thalamic regions. To assess the specificity of our findings, we also examined whether the brain network predicting narcissism could also predict other personality traits (i.e., histrionic, paranoid and avoidant personalities). Notably, this network did not predict such personality traits. Additionally, a supervised machine learning model (Random Forest) was used to extract a predictive model for generalization to new cases. Results confirmed that the same network could predict new cases. These findings hold promise for advancing our understanding of personality traits and potentially uncovering brain biomarkers associated with narcissism.

Predicting narcissistic personality traits from brain and psychological features: A supervised machine learning approach.

Narcissism is a multifaceted construct often linked to pathological conditions whose neural correlates are still poorly understood. Previous studies have reported inconsistent findings related to the neural underpinnings of narcissism, probably due to methodological limitations such as the low number of participants or the use of mass univariate methods. The present study aimed to overcome the previous methodological limitations and to build a predictive model of narcissistic traits based on neural and psychological features. In this respect, two machine learning-based methods (Kernel Ridge Regression and Support Vector Regression) were used to predict narcissistic traits from brain structural organization and from other relevant normal and abnormal personality features. Results showed that a circuit including the lateral and middle frontal gyri, the angular gyrus, Rolandic operculum, and Heschl's gyrus successfully predicted narcissistic personality traits (p < 0.003). Moreover, narcissistic traits were predicted by normal (openness, agreeableness, conscientiousness) and abnormal (borderline, antisocial, insecure, addicted, negativistic, machiavellianism) personality traits. This study is the first to predict narcissistic personality traits via a supervised machine learning approach. As such, these results may expand the possibility of deriving personality traits from neural and psychological features.

Virtual Reality-based Cognitive Intervention for Enhancing Executive Functions in Community-dwelling Older Adults

With the rapid growth of the older population globally, it is anticipated that age-related cognitive decline in the prodromal phase and more severe pathological decline will increase. Moreover, currently, no effective treatment options for the disease exist. Thus, early and timely prevention actions are promising and prior strategies to preserve cognitive functions by preventing symptomatology from increasing the age-related deterioration of the functions in healthy older adults. This study aims to develop the virtual reality-based cognitive intervention for enhancing executive functions (EFs) and examine the EFs after training with the virtual reality-based cognitive intervention in community-dwelling older adults. Following inclusion/exclusion criteria, 60 community-dwelling older adults aged 60–69 years were involved in the study and randomly divided into passive control and experimental groups. Eight 60 min virtual reality-based cognitive intervention sessions were held twice a week and lasted for 1 month. The EFs (i.e., inhibition, updating, and shifting) of the participants were assessed by using standardized computerized tasks, i.e., Go/NoGo, forward and backward digit span, and Berg’s card sorting tasks. Additionally, a repeated-measure ANCOVA and effect sizes were applied to investigate the effects of the developed intervention. The virtual reality-based intervention significantly improved the EFs of older adults in the experimental group. (AU)

Ante el rápido crecimiento de la población mayor a nivel mundial se prevé un aumento del deterioro cognitivo propio de la edad en la fase prodrómica y un mayor deterioro patológico. Además no hay en la actualidad opciones eficaces de tratamiento de la enfermedad. Por tanto, las medidas preventivas tempranas y puntuales suponen estrategias prometedoras para preservar las funciones cognitivas al evitar que la sintomatología aumente el deterioro de las funciones asociado a la edad de personas mayores sanas. El presente estudio tiene como obejetivo desarrollar una intervención cognitiva basada en la realidad virtual para mejorar las funciones ejecutivas (FE) y examinarlas tras el entrenamiento de intervención cognitiva con realidad virtual en personas mayores que viven en su domicilio. Teniendo en cuenta criterios de inclusión y exclusión se contó para el estudio con 60 personas mayores de entre 60 y 69 años que vivían en su domicilio, a los que se asignó aleatoriamente a un grupo de control pasivo y a un grupo experimental. (AU)

Relating mathematical abilities to numerical skills and executive functions in informal and formal schooling.

BACKGROUND: The current evidence on an integrative role of the domain-specific early mathematical skills and number-specific executive functions (EFs) from informal to formal schooling and their effect on mathematical abilities is so far unclear. The main objectives of this study were to (i) compare the domain-specific early mathematics, the number-specific EFs, and the mathematical abilities between preschool and primary school children, and (ii) examine the relationship among the domain-specific early mathematics, the number-specific EFs, and the mathematical abilities among preschool and primary school children. METHODS: The current study recruited 6- and 7-year-old children (Ntotal = 505, n6yrs = 238, and n7yrs = 267). The domain-specific early mathematics as measured by symbolic and nonsymbolic tasks, number-specific EFs tasks, and mathematics tasks between these preschool and primary school children were compared. The relationship among domain-specific early mathematics, number-specific EFs, and mathematical abilities among preschool and primary school children was examined. MANOVA and structural equation modeling (SEM) were used to test research hypotheses. RESULTS: The current results showed using MANOVA that primary school children were superior to preschool children over more complex tests of the domain-specific early mathematics; number-specific EFs; mathematical abilities, particularly for more sophisticated numerical knowledge; and number-specific EF components. The SEM revealed that both the domain-specific early numerical and the number-specific EFs significantly related to the mathematical abilities across age groups. Nevertheless, the number comparison test and mental number line of the domain-specific early mathematics significantly correlated with the mathematical abilities of formal school children. These results show the benefits of both the domain-specific early mathematics and the number-specific EFs in mathematical development, especially at the key stages of formal schooling. Understanding the relationship between EFs and early mathematics in improving mathematical achievements could allow a more powerful approach in improving mathematical education at this developmental stage.

Virtual Reality-based Cognitive Intervention for Enhancing Executive Functions in Community-dwelling Older Adults.

With the rapid growth of the older population globally, it is anticipated that age-related cognitive decline in the prodromal phase and more severe pathological decline will increase. Moreover, currently, no effective treatment options for the disease exist. Thus, early and timely prevention actions are promising and prior strategies to preserve cognitive functions by preventing symptomatology from increasing the age-related deterioration of the functions in healthy older adults. This study aims to develop the virtual reality-based cognitive intervention for enhancing executive functions (EFs) and examine the EFs after training with the virtual reality-based cognitive intervention in community-dwelling older adults. Following inclusion/exclusion criteria, 60 community-dwelling older adults aged 60-69 years were involved in the study and randomly divided into passive control and experimental groups. Eight 60 min virtual reality-based cognitive intervention sessions were held twice a week and lasted for 1 month. The EFs (i.e., inhibition, updating, and shifting) of the participants were assessed by using standardized computerized tasks, i.e., Go/NoGo, forward and backward digit span, and Berg's card sorting tasks. Additionally, a repeated-measure ANCOVA and effect sizes were applied to investigate the effects of the developed intervention. The virtual reality-based intervention significantly improved the EFs of older adults in the experimental group. Specifically, the magnitudes of enhancement were observed for inhibitory as indexed by the response time, F(1) = 6.95, p < .05, ηp2 = .11, updating as represented by the memory span, F(1) = 12.09, p < .01, ηp2 = .18, and the response time, F(1) = 4.46, p = .04, ηp2 = .07, and shifting abilities as indexed by the percentage of correct responses, F(1) = 5.30, p = .03, ηp2 = .09, respectively. The results indicated that the simultaneous combined cognitive-motor control as embedded in the virtual-based intervention is safe and effective in enhancing EFs in older adults without cognitive impairment. Nevertheless, further studies are required to investigate the benefits of these enhancements to motor functions and emotional aspects relating to daily living and the well-being of older populations in communities.

Ante el rápido crecimiento de la población mayor a nivel mundial se prevé un aumento del deterioro cognitivo propio de la edad en la fase prodrómica y un mayor deterioro patológico. Además no hay en la actualidad opciones eficaces de tratamiento de la enfermedad. Por tanto, las medidas preventivas tempranas y puntuales suponen estrategias prometedoras para preservar las funciones cognitivas al evitar que la sintomatología aumente el deterioro de las funciones asociado a la edad de personas mayores sanas. El presente estudio tiene como obejetivo desarrollar una intervención cognitiva basada en la realidad virtual para mejorar las funciones ejecutivas (FE) y examinarlas tras el entrenamiento de intervención cognitiva con realidad virtual en personas mayores que viven en su domicilio. Teniendo en cuenta criterios de inclusión y exclusión se contó para el estudio con 60 personas mayores de entre 60 y 69 años que vivían en su domicilio, a los que se asignó aleatoriamente a un grupo de control pasivo y a un grupo experimental. Se realizaron ocho sesiones de 60 minutos de intervención cognitiva con realidad virtual dos veces por semana durante un mes. Las FE (i.e., la inhibición, actualización y cambio) de los participantes se evaluaron mediante tareas informatizadas estandarizadas, i.e., Go/NoGo, amplitud de dígitos hacia delante y hacia atrás y clasificación de cartas de Berg. Además, se utilizó un ANCOVA de medidas repetidas y el tamaño del efecto para medir el efecto de la intervención desarrollada. La intervención con realidad virtual mejoró significativamente las funciones ejecutivas de los mayores del grupo experimental. En concreto se observaron más mejoras en inhibición, reflejada en el tiempo de respuesta, F(1) = 6.95, p < .05, ηp2 = .11, actualización, representada por la amplitud de memoria, F(1) = 12.09, p < .01, ηp2 = .18, y el tiempo de respuesta, F(1) = 4.46, p = .04, ηp2 = .07, y las habilidades de cambio, como refleja el porcentaje de respuestas correctas, F(1) = 5.30, p = .03, ηp2 = .09, respectivamente. Los resultados indican que el control cognitivo-motor combinado simultáneamente, tal y como se aplica en la intervención virtual, es seguro y eficaz para conseguir aumentar las funciones ejecutivas de personas mayores sin deterioro cognitivo. No obstante, se necesitan más estudios para investigar los beneficios de estas mejoras en las funciones motoras y los aspectos emocionales de la vida cotidiana, así como el bienestar de las personas mayores que viven en la comunidad.

Resting-state EEG datasets of adolescents with mild, minimal, and moderate depression.

OBJECTIVES: To measure depressive severity of 85 Thai adolescents by using the the Beck Depression Inventory-II and the Patient Health Questionnaire-9 and to record the resting-state EEG of these participants. DATA DESCRIPTION: The current data note provides raw data of behavioral (i.e., group, BDI-II score, and PHQ-9 score) and electrophysiological parameters (i.e., absolute and relative EEG powers over 64 electrode sites) of 30, 27, and 28 participants with minimal, mild, and moderate depression, respectively. These data are especially useful to investigate the behavioral and electrophysiological markers of adolescents with subclinical depression. It can also be utilized in comparative analysis among age groups, and races.

Verbal and visuospatial short-term and working memory data across a 43-year period (1973-2016) worldwide: Flynn and anti-Flynn effects.

Secular gain and drop in cognitive test performances over time have been observed and called respectively the Flynn and anti-Flynn effects. The current datasets include raw data from an investigation of the Flynn and/or anti-Flynn effects on verbal and visuospatial short-term and working memory reported in 'The Flynn effect for verbal and visuospatial short-term and working memory: A cross-temporal meta-analysis' (Wongupparaj, Wongupparaj, Kumari, Morris, 2017) [1]. Specifically, the datasets totally contain 1754 individual samples (n = 139,677) across a 43-year period from forward/backward digit span (F/BDS) and forward/backward Corsi-block span (CBS) tests. Mean memory test scores, standard deviation scores, types of memory tests, years of publication, mean ages, male percentages, types of publication, types of countries, platforms of memory tests, and sample sizes were collected and included in the datasets. DS and CBS data are unique in that they can provide a rich source of trends concerning changing short-term and working memory test scores across memory types, test platforms, age groups, gender, and countries. Further, these data can be of use for investigation of psychometric properties for the memory tests.

IQ score gains over 65 years worldwide: Cross-temporal meta-analysis datasets.

The observed gain in IQ scores over time has been examined and supported. Nonetheless, this phenomenon (also called Flynn effect) may depend on age groups and country types. This article provides raw data from three standardized intelligence tests, namely, Coloured Progressive Matrices (CPM), Standard Progressive Matrices (SPM), and Advanced Progressive Matrices (APM). The datasets contain mean IQ scores from APM, CPM, and SPM, and standard deviations, sample sizes, years of publication, participants' groups, types of countries, country-based samples, and gender of participants. This data was obtained from 199, 369, and 176 individual study samples for CPM, SPM, and APM, respectively, and covered a period of 65 years (1950-2014). There were 202,468 participants in total. An analysis and interpretation of results based on a cross-temporal meta-analysis for mean IQ scores from CPM, SPM, and APM over time can be found in the article "A Cross-Temporal Meta-Analysis of Raven's Progressive Matrices: Age groups and developing versus developed countries" (Wongupparaj, Kumari, Morris, 2015) [1]. These datasets can provide an extensive overview of the literature on Flynn effect across age groups, countries, and gender. In addition, they can serve as a useful starting point for further meta-analyses of IQ scores derived from CPM, SPM, and APM.

Pre-schoolers' visual perception and attention networks influencing naming speed: An individual difference perspective.

Naming speed is considered to be one of the essential components used to predict reading capacity in school. The current study examined how visual perception and attention networks influence naming speed, and analyzed the relationship between visual perception and attention networks. The total number of participants was 163 Thai preschool children between the ages of five and seven years selected through multistage random sampling. Visual perception, attention networks, and naming speed were assessed using the Developmental Test of Visual Perception 3 (DTVP-3), Attention Network Task (ANT), and Rapid Automatized Naming (RAN), respectively. Structural equation modeling was used to test naming speed hypotheses. The hypothesis of a causal model was supported by the evidence generated by this study. A direct positive association between both visual perception and attention networks to naming speed was observed. Compared with attention networks, visual perception had a higher significant effect on naming speed performance. Consequently, children who have higher visual perception are more likely to demonstrate a better naming speed performance. These results indicate that visual perception is strongly urged to naming speed, as doing so can help predict children's reading readiness before they start learning to read.

Individual differences in working memory and general intelligence indexed by P200 and P300: A latent variable model.

A robust relationship between working memory (WM) and general intelligence (g) has been well established. Nevertheless, explanations for this relationship in terms of underlying neurocognitive processes are still inadequate. This study addresses this issue using an individual differences approach in which Central Executive System (CES) and Short-Term Storage (STS) components of WM are measured comprehensively and examined for their relationship with g via event-related potentials components (P200 and P300) as mediators. Participants (n = 115) completed tests of the WM, CES and STS, as well as g. P200 and P300 components were recorded during 3-back WM task performance. Structural equation modelling showed significant negative associations between the P200 latency for target stimuli and CES shifting processes, and between the P300 amplitude for target stimuli and CES inhibition and updating processes. The relationship between CES processes and g was mediated in a localized fashion by the P300 amplitude. These findings further support the notion that the CES has a multidimensional structure and, importantly, reveal that the inhibition and updating functions of the CES are crucial in explaining the relationship between WM and g. Negative relations between ERP indices (P200 latency and P300 amplitude for target stimuli) and g support a neural efficiency hypothesis related to high intelligence.