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AbstractMutualism is a developmental theory that posits positive reciprocal relationships between distinct cognitive abilities during development. It predicts that abilities such as language and reasoning will influence each other's rates of growth. This may explain why children with Language Disorders also tend to have lower than average non‐verbal cognitive abilities, as poor language would limit the rate of growth of other cognitive skills. The current study tests whether language and non‐verbal reasoning show mutualistic coupling in children with and without language disorder using three waves of data from a longitudinal cohort study that over‐sampled children with poor language at school entry (N = 501, 7–13 years). Bivariate Latent Change Score models were used to determine whether early receptive vocabulary predicted change in non‐verbal reasoning and vice‐versa. Models that included mutualistic coupling parameters between vocabulary and non‐verbal reasoning showed superior fit to models without these parameters, replicating previous findings. Specifically, children with higher initial language abilities showed greater growth in non‐verbal ability and vice versa. Multi‐group models suggested that coupling between language and non‐verbal reasoning was equally strong in children with language disorder and those without. This indicates that language has downstream effects on other cognitive abilities, challenging the existence of selective language impairments. Future intervention studies should test whether improving language skills in children with language disorder has positive impacts on other cognitive abilities (and vice versa), and low non‐verbal IQ should not be a barrier to accessing such intervention.

Methodological innovations have allowed researchers to consider increasingly sophisticated statistical models that are better in line with the complexities of real-world behavioral data. However, despite these powerful new analytic approaches, sample sizes may not always be sufficiently large to deal with the increase in model complexity. This difficult modeling scenario entails large models with a limited number of observations given the number of parameters. Here, we describe a particular strategy to overcome this challenge: regularization, a method of penalizing model complexity during estimation. Regularization has proven to be a viable option for estimating parameters in this small-sample, many-predictors setting, but so far it has been used mostly in linear regression models. We show how to integrate regularization within structural equation models, a popular analytic approach in psychology. We first describe the rationale behind regularization in regression contexts and how it can be extended to regularized structural equation modeling. We then evaluate our approach using a simulation study, showing that regularized structural equation modeling outperforms traditional structural equation modeling in situations with a large number of predictors and a small sample size. Next, we illustrate the power of this approach in two empirical examples: modeling the neural determinants of visual short-term memory and identifying demographic correlates of stress, anxiety, and depression. ; R. A. Kievit is supported by the Sir Henry Wellcome Trust (Grant 107392/Z/15/Z) and by an MRC Programme Grant (SUAG/014/RG91365). This project has also received funding from the European Union's Horizon 2020 Research and Innovation program (Grant 732592).

AbstractLiteracy acquisition is a complex process with genetic and environmental factors influencing cognitive and neural processes associated with reading. Previous research identified factors that predict word reading fluency (WRF), including phonological awareness (PA), rapid automatized naming (RAN), and speech‐in‐noise perception (SPIN). Recent theoretical accounts suggest dynamic interactions between these factors and reading, but direct investigations of such dynamics are lacking. Here, we investigated the dynamic effect of phonological processing and speech perception on WRF. More specifically, we evaluated the dynamic influence of PA, RAN, and SPIN measured in kindergarten (the year prior to formal reading instruction), first grade (the first year of formal reading instruction) and second grade on WRF in second and third grade. We also assessed the effect of an indirect proxy of family risk for reading difficulties using a parental questionnaire (Adult Reading History Questionnaire, ARHQ). We applied path modeling in a longitudinal sample of 162 Dutch‐speaking children of whom the majority was selected to have an increased family and/or cognitive risk for dyslexia. We showed that parental ARHQ had a significant effect on WRF, RAN and SPIN, but unexpectedly not on PA. We also found effects of RAN and PA directly on WRF that were limited to first and second grade respectively, in contrast to previous research reporting pre‐reading PA effects and prolonged RAN effects throughout reading acquisition. Our study provides important new insights into early prediction of later word reading abilities and into the optimal time window to target a specific reading‐related subskill during intervention.

Across scientific disciplines, there is a rapidly growing recognition of the need for more statistically robust, transparent approaches to data visualization. Complementary to this, many scientists have called for plotting tools that accurately and transparently convey key aspects of statistical effects and raw data with minimal distortion. Previously common approaches, such as plotting conditional mean or median barplots together with error-bars have been criticized for distorting effect size, hiding underlying patterns in the raw data, and obscuring the assumptions upon which the most commonly used statistical tests are based. Here we describe a data visualization approach which overcomes these issues, providing maximal statistical information while preserving the desired 'inference at a glance' nature of barplots and other similar visualization devices. These "raincloud plots" can visualize raw data, probability density, and key summary statistics such as median, mean, and relevant confidence intervals in an appealing and flexible format with minimal redundancy. In this tutorial paper, we provide basic demonstrations of the strength of raincloud plots and similar approaches, outline potential modifications for their optimal use, and provide open-source code for their streamlined implementation in R, Python and Matlab ( https://github.com/RainCloudPlots/RainCloudPlots). Readers can investigate the R and Python tutorials interactively in the browser using Binder by Project Jupyter. ; MA is supported by a Lundbeckfonden Fellowship (R272-2017-4345), the AIAS-COFUND II fellowship programme that is supported by the Marie Skłodowska-Curie actions under the European Union's Horizon 2020 (Grant agreement no 754513), and the Aarhus University Research Foundation, and thanks Lincoln Colling for insightful statistical discussions. KW is funded by the Alan Turing Institute under the EPSRC grant EP/N510129/1. RAK is supported by the Wellcome Trust (grant number 107392/Z/15/Z).

Electronic slideshow presentations are often faulted anecdotally, but little empirical work has documented their faults. In Study 1 we found that eight psychological principles are often violated in PowerPoint® slideshows, and are violated to similar extents across different fields – for example, academic research slideshows generally were no better or worse than business slideshows. In Study 2 we found that respondents reported having noticed, and having been annoyed by, specific problems in presentations arising from violations of particular psychological principles. Finally, in Study 3 we showed that observers are not highly accurate in recognizing when particular slides violated a specific psychological rule. Furthermore, even when they correctly identified the violation, they often could not explain the nature of the problem. In sum, the psychological foundations for effective slideshow presentation design are neither obvious nor necessarily intuitive, and presentation designers in all fields, from education to business to government, could benefit from explicit instruction in relevant aspects of psychology.

Cardiovascular health declines with age, increasing the risk of hypertension and elevated heart rate in middle and old age. Here, we used multivariate techniques to investigate the associations between cardiovascular health (diastolic blood pressure, systolic blood pressure, and heart rate) and white matter macrostructure (lesion volume and number) and microstructure (as measured by diffusion-weighted imaging) in the cross-sectional, population-based Cam-CAN cohort (N = 667, aged 18-88). We found that cardiovascular health and age made approximately similar contributions to white matter health and explained up to 56% of variance therein. Lower diastolic blood pressure, higher systolic blood pressure, and higher heart rate were each strongly, and independently, associated with white matter abnormalities on all indices. Body mass and exercise were associated with white matter health, both directly and indirectly via cardiovascular health. These results highlight the importance of cardiovascular risk factors for white matter health across the adult lifespan and suggest that systolic blood pressure, diastolic blood pressure, and heart rate affect white matter health via separate mechanisms. ; DF, DN, JBR, DP and RAK are supported by the UK Medical Research Council. The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) was supported by the Biotechnology and Biological Sciences Research Council (grant number BB/H008217/1). RAK is supported by the Sir Henry Wellcome Trust (grant number 107392/Z/15/Z) and MRC Programme Grant MC-A060-5PR60. This project has also received funding from the European Union's Horizon 2020 research and innovation programme (grant agreement number 732592).

Available online: 22 November 2017 ; Assessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions. We illustrate the use of LCS models with two empirical examples. In a lifespan cognitive training study (COGITO, N = 204 (N = 32 imaging) on two waves) we observe correlated change in brain and behaviour in the context of a high-intensity training intervention. In an adolescent development cohort (NSPN, N = 176, two waves) we find greater variability in cortical thinning in males than in females. To facilitate the adoption of LCS by the developmental community, we provide analysis code that can be adapted by other researchers and basic primers in two freely available SEM software packages (lavaan and Omega nyx). ; Sir Henry Wellcome Trust [107392/Z/15/Z] ; UK Medical Research Council Programme [MC-A060-5PR61] ; Wellcome Trust [095844/Z/11/Z] ; European Union's Horizon 2020 research and innovation programme [732592]

Background: Brain health is a multi-faceted concept used to describe brain physiology, cognitive function, mental health and well-being. Diseases of the brain account for one third of the global burden of disease and are becoming more prevalent as populations age. Diet, social interaction as well as physical and cognitive activity are lifestyle factors that can potentially influence facets of brain health. Yet, there is limited knowledge about the population's awareness of brain health and willingness to change lifestyle to maintain a healthy brain. This paper introduces the Global Brain Health Survey protocol, designed to assess people's perceptions of brain health and factors influencing brain health. Methods: The Global Brain Health Survey is an anonymous online questionnaire available in 14 languages to anyone above the age of 18 years. Questions focus on (1) willingness and motivation to maintain or improve brain health, (2) interest in learning more about individual brain health using standardized tests, and (3) interest in receiving individualized support to take care of own brain health. The survey questions were developed based on results from a qualitative interview study investigating brain health perceptions among participants in brain research studies. The survey includes 28 questions and takes 15-20 min to complete. Participants provide electronically informed consent prior to participation. The current survey wave was launched on June 4, 2019 and will close on August 31, 2020. We will provide descriptive statistics of samples distributions including analyses of differences as a function of age, gender, education, country of residence, and we will examine associations between items. The European Union funded Lifebrain project leads the survey in collaboration with national brain councils in Norway, Germany, and Belgium, Brain Foundations in the Netherlands and Sweden, the National University of Ostroh Academy and the Women's Brain Project. Discussion: Results from this survey will provide new insights in peoples' views on brain health, in particular, the extent to which the adoption of positive behaviors can be encouraged. The results will contribute to the development of policy recommendations for supporting population brain health, including measures tailored to individual needs, knowledge, motivations and life situations.

Background: Brain health is a multi-faceted concept used to describe brain physiology, cognitive function, mental health and well-being. Diseases of the brain account for one third of the global burden of disease and are becoming more prevalent as populations age. Diet, social interaction as well as physical and cognitive activity are lifestyle factors that can potentially influence facets of brain health. Yet, there is limited knowledge about the population's awareness of brain health and willingness to change lifestyle to maintain a healthy brain. This paper introduces the Global Brain Health Survey protocol, designed to assess people's perceptions of brain health and factors influencing brain health. Methods: The Global Brain Health Survey is an anonymous online questionnaire available in 14 languages to anyone above the age of 18 years. Questions focus on (1) willingness and motivation to maintain or improve brain health, (2) interest in learning more about individual brain health using standardized tests, and (3) interest in receiving individualized support to take care of own brain health. The survey questions were developed based on results from a qualitative interview study investigating brain health perceptions among participants in brain research studies. The survey includes 28 questions and takes 15–20 min to complete. Participants provide electronically informed consent prior to participation. The current survey wave was launched on June 4, 2019 and will close on August 31, 2020. We will provide descriptive statistics of samples distributions including analyses of differences as a function of age, gender, education, country of residence, and we will examine associations between items. The European Union funded Lifebrain project leads the survey in collaboration with national brain councils in Norway, Germany, and Belgium, Brain Foundations in the Netherlands and Sweden, the National University of Ostroh Academy and the Women's Brain Project. Discussion: Results from this survey will provide new insights in peoples' views on brain health, in particular, the extent to which the adoption of positive behaviors can be encouraged. The results will contribute to the development of policy recommendations for supporting population brain health, including measures tailored to individual needs, knowledge, motivations and life situations.

Background: Brain health is a multi-faceted concept used to describe brain physiology, cognitive function, mental health and well-being. Diseases of the brain account for one third of the global burden of disease and are becoming more prevalent as populations age. Diet, social interaction as well as physical and cognitive activity are lifestyle factors that can potentially influence facets of brain health. Yet, there is limited knowledge about the population's awareness of brain health and willingness to change lifestyle to maintain a healthy brain. This paper introduces the Global Brain Health Survey protocol, designed to assess people's perceptions of brain health and factors influencing brain health. Methods: The Global Brain Health Survey is an anonymous online questionnaire available in 14 languages to anyone above the age of 18 years. Questions focus on (1) willingness and motivation to maintain or improve brain health, (2) interest in learning more about individual brain health using standardized tests, and (3) interest in receiving individualized support to take care of own brain health. The survey questions were developed based on results from a qualitative interview study investigating brain health perceptions among participants in brain research studies. The survey includes 28 questions and takes 15–20 min to complete. Participants provide electronically informed consent prior to participation. The current survey wave was launched on June 4, 2019 and will close on August 31, 2020. We will provide descriptive statistics of samples distributions including analyses of differences as a function of age, gender, education, country of residence, and we will examine associations between items. The European Union funded Lifebrain project leads the survey in collaboration with national brain councils in Norway, Germany, and Belgium, Brain Foundations in the Netherlands and Sweden, the National University of Ostroh Academy and the Women's Brain Project. Discussion: Results from this survey will provide new insights in peoples' views on brain health, in particular, the extent to which the adoption of positive behaviors can be encouraged. The results will contribute to the development of policy recommendations for supporting population brain health, including measures tailored to individual needs, knowledge, motivations and life situations.

Background: Brain health is a multi-faceted concept used to describe brain physiology, cognitive function, mental health and well-being. Diseases of the brain account for one third of the global burden of disease and are becoming more prevalent as populations age. Diet, social interaction as well as physical and cognitive activity are lifestyle factors that can potentially influence facets of brain health. Yet, there is limited knowledge about the population's awareness of brain health and willingness to change lifestyle to maintain a healthy brain. This paper introduces the Global Brain Health Survey protocol, designed to assess people's perceptions of brain health and factors influencing brain health. Methods: The Global Brain Health Survey is an anonymous online questionnaire available in 14 languages to anyone above the age of 18 years. Questions focus on (1) willingness and motivation to maintain or improve brain health, (2) interest in learning more about individual brain health using standardized tests, and (3) interest in receiving individualized support to take care of own brain health. The survey questions were developed based on results from a qualitative interview study investigating brain health perceptions among participants in brain research studies. The survey includes 28 questions and takes 15–20min to complete. Participants provide electronically informed consent prior to participation. The current survey wave was launched on June 4, 2019 and will close on August 31, 2020. We will provide descriptive statistics of samples distributions including analyses of differences as a function of age, gender, education, country of residence, and we will examine associations between items. The European Union funded Lifebrain project leads the survey in collaboration with national brain councils in Norway, Germany, and Belgium, Brain Foundations in the Netherlands and Sweden, the National University of Ostroh Academy and the Women's Brain Project. Discussion: Results from this survey will provide new insights in peoples' views on brain health, in particular, the extent to which the adoption of positive behaviors can be encouraged. The results will contribute to the development of policy recommendations for supporting population brain health, including measures tailored to individual needs, knowledge, motivations and life situations.

Background: Brain health is a multi-faceted concept used to describe brain physiology, cognitive function, mental health and well-being. Diseases of the brain account for one third of the global burden of disease and are becoming more prevalent as populations age. Diet, social interaction as well as physical and cognitive activity are lifestyle factors that can potentially influence facets of brain health. Yet, there is limited knowledge about the population's awareness of brain health and willingness to change lifestyle to maintain a healthy brain. This paper introduces the Global Brain Health Survey protocol, designed to assess people's perceptions of brain health and factors influencing brain health. Methods: The Global Brain Health Survey is an anonymous online questionnaire available in 14 languages to anyone above the age of 18 years. Questions focus on (1) willingness and motivation to maintain or improve brain health, (2) interest in learning more about individual brain health using standardized tests, and (3) interest in receiving individualized support to take care of own brain health. The survey questions were developed based on results from a qualitative interview study investigating brain health perceptions among participants in brain research studies. The survey includes 28 questions and takes 15-20 min to complete. Participants provide electronically informed consent prior to participation. The current survey wave was launched on June 4, 2019 and will close on August 31, 2020. We will provide descriptive statistics of samples distributions including analyses of differences as a function of age, gender, education, country of residence, and we will examine associations between items. The European Union funded Lifebrain project leads the survey in collaboration with national brain councils in Norway, Germany, and Belgium, Brain Foundations in the Netherlands and Sweden, the National University of Ostroh Academy and the Women's Brain Project. Discussion: Results from this survey will provide new insights in peoples' views on brain health, in particular, the extent to which the adoption of positive behaviors can be encouraged. The results will contribute to the development of policy recommendations for supporting population brain health, including measures tailored to individual needs, knowledge, motivations and life situations.