Altered empathy processing in frontotemporal dementia A task-based fMRI study

A lack of empathy, and particularly its affective components, is a core symptom of behavioural variant frontotemporal dementia (bvFTD). Visual exposure to images of a needle pricking a hand (pain condition) and Q-tips touching a hand (control condition) is an established functional magnetic resonance imaging (fMRI) paradigm used to investigate empathy for pain (EFP; pain condition minus control condition). EFP has been associated with increased blood oxygen level dependent (BOLD) signal in regions known to become atrophic in the early stages in bvFTD, including the anterior insula and the anterior cingulate. We therefore hypothesized that patients with bvFTD would display altered empathy processing in the EFP paradigm. Here we examined empathy processing using the EFP paradigm in 28 patients with bvFTD and 28 sex and age matched controls. Participants underwent structural MRI, task-based and resting-state fMRI. The Interpersonal Reactivity Index (IRI) was used as a measure of different facets of empathic function outside the scanner. The EFP paradigm was analysed at a whole brain level and using two regions-of-interest approaches, one based on a metanalysis of affective perceptual empathy versus cognitive evaluative empathy and one based on the controĺs activation pattern. In controls, EFP was linked to an expected increase of BOLD signal that displayed an overlap with the pattern of atrophy in the bvFTD patients (insula and anterior cingulate). Additional regions with increased signal were the supramarginal gyrus and the occipital cortex. These latter regions were the only ones that displayed increased BOLD signal in bvFTD patients. BOLD signal increase under the affective perceptual empathy but not the cognitive evaluative empathy region of interest was significantly greater in controls than in bvFTD patients. The controĺs rating on their empathic concern subscale of the IRI was significantly correlated with the BOLD signal in the EFP paradigm, as were an informantś ratings of the patientś empathic concern subscale. This correlation was not observed on other subscales of the IRI or when using the patient's self-ratings. Finally, controls and patients showed different connectivity patterns in empathy related networks during resting-state fMRI, mainly in nodes overlapping the ventral attention network. Our results indicate that reduced neural activity in regions typically affected by pathology in bvFTD is associated with reduced empathy processing, and a predictor of patientś capacity to experience affective empathy.

Addressing climate change with behavioral science: A global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

EEGManyPipelines: A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild

The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project, and how it might have a lasting impact on the field.

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Distorted meta-analytic findings on peer influence: A reanalysis

In a recent meta-analysis, Giletta et al. (2021) [1] found a positive effect of peers' behavior at time 1 on target youths' behavior at time 2 while adjusting for target youths' behavior at time 1 and claimed to have quantified peer influence. However, it is established that controlled cross-lagged effects could be due to correlations with measurement errors and reversion in the direction of the mean rather than due to true decreasing or increasing effects. Here, in a reanalysis of the same meta-analytic data as used by Giletta et al., we found that peer influence, as operationalized by Giletta et al., may have been distorted (i.e. spurious). We do not claim that peer influence does not exist, but it may be hard, maybe not even possible, to prove by analyses of observational data that it does exist. Difficulties to prove causal effects by analyses of observational data is common for all areas of research and not specific for research on peer influence.

Unmasking artifactual links: A reanalysis reveals No direct causal relationship between self-esteem and quality of social relations

A meta-analysis conducted by Harris and Orth (2020) found positive prospective cross-lagged effects between quality of social relations and self-esteem in included longitudinal studies. Harris and Orth concluded that the link between self-esteem and quality of social relations is reciprocal and characterized by a positive feedback loop. However, meta-analytic effects were estimated while controlling for a prior measurement of the outcome and such effects are known to be susceptible to artifactual (i.e. spurious) effects due to correlations with measurement errors and reversion to mediocrity. We reanalyzed the same data and found paradoxical effects indicating, simultaneously, both increasing and decreasing effects between self-esteem and social relations. These findings suggest that prospective effects between self-esteem and quality of social relations are artifactual rather than due to a true reciprocal effect. Thus, these findings have important theoretical implications and challenge both the risk regulation model, which posits that self-esteem has a causal effect on quality of social relations, and the sociometer theory, which claims that quality of relations is the cause and self-esteem the effect. The present results prompt further investigation into the underlying mechanisms driving these artifactual associations. Additionally, the study highlights the importance of considering methodological limitations in future meta-analyses to improve the accuracy of causal inferences.

Replacing academic journals

Replacing traditional journals with a more modern solution is not a new idea. Here, we propose ways to overcome the social dilemma underlying the decades of inaction. Any solution needs to not only resolve the current problems but also be capable of preventing takeover by corporations: it needs to replace traditional journals with a decentralized, resilient, evolvable network that is interconnected by open standards and open-source norms under the governance of the scholarly community. It needs to replace the monopolies connected to journals with a genuine, functioning and well-regulated market. In this new market, substitutable service providers compete and innovate according to the conditions of the scholarly community, avoiding sustained vendor lock-in. Therefore, a standards body needs to form under the governance of the scholarly community to allow the development of open scholarly infrastructures servicing the entire research workflow. We propose a redirection of money from legacy publishers to the new network by funding bodies broadening their minimal infrastructure requirements at recipient institutions to include modern infrastructure components replacing and complementing journal functionalities. Such updated eligibility criteria by funding agencies would help realign the financial incentives for recipient institutions with public and scholarly interest.

[Same data - different conclusions: Analytical flexibility in medical research can be considerable]

Analysis of research data entails many choices. As a result, a space of different analytical strategies is open to researchers. Different justifiable analyses may not give similar results. The method of multiple analysts is a way to study the analytical flexibility and behaviour of researchers under naturalistic conditions, as part of the field known as metascience. Analytical flexibility and risks of bias can be counteracted by open data sharing, pre-registration of analysis plans, and registration of clinical trials in trial registers. These measures are particularly important for retrospective studies where analytical flexibility can be greatest, although pre-registration is less useful in this context. Synthetic datasets can be an alternative to pre-registration when used to decide what analyses should be conducted on real datasets by independent parties. All these strategies help build trustworthiness in scientific reports, and improve the reliability of research findings.

Dangers of including outcome at baseline as a covariate in latent change score models: Results from simulations and empirical re-analyses

Latent change score modeling is a type of structural equation modeling used for estimating change over time. Often change is regressed on the initial value of the outcome variable. However, similarly to other regression analyses, this procedure may be susceptible to regression to the mean. The present study employed simulations as well as re-analyses of previously published data, claimed to indicate reciprocal promoting effects of vocabulary and matrix reasoning on each other's longitudinal development. Both in simulations and empirical re-analyses, when adjusting for initial value on the outcome, latent change score modeling tended to indicate an effect of a predictor on the change in an outcome even when no change had taken place. Furthermore, analyses tended to indicate a paradoxical effect on change both forward and backward in time. We conclude that results from latent change score modeling are susceptible to regression to the mean when adjusting for the initial value on the outcome. Researchers are recommended not to regress change on the initial value included in the calculation of the change score when employing latent change score modeling but, instead, to define this parameter as a covariance.

The Psychological Science Accelerator's COVID-19 rapid-response dataset

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.

Questioning the vulnerability model: Prospective associations between low self-esteem and subsequent depression ratings may be spurious

BACKGROUND

According to the vulnerability model, low self-esteem makes people more depressed. Support for the vulnerability model comes almost exclusively from analyses using cross-lagged panel models, showing a negative effect of initial self-esteem on subsequent depression ratings when adjusting for initial depression. However, it is well known that such adjusted effects are susceptible to regression toward the mean.

METHODS

Data from four waves of measurements in five different samples (total N = 2703) were analyzed with two different cross-lagged panel models, two different random intercept cross-lagged panel models, and two different latent change score models, predicting change forwards as well as backwards in time.

RESULTS

High initial self-esteem predicted both decreased and increased depression ratings between measurements and an increase in self-esteem between measurements predicted a concurrent decrease in depression ratings.

LIMITATIONS

Only data from two western countries, Switzerland and USA, were analyzed. Whether the main finding, that a prospective effect of self-esteem on subsequent depression ratings might be spurious, applies to other countries and cultures remains an open question.

CONCLUSIONS

Due to the incongruent results, any causal effect of self-esteem on depression ratings, and thus the vulnerability model as such, cannot be corroborated by the data and models analyzed here. Instead, we propose, tentatively, that prospective associations between self-esteem and depression ratings may be spurious due to a combination of reasons, including regression toward the mean. The indication that depression might not be affected by measures to improve individuals' self-esteem is of clinical relevance.

Exhaustion disorder: scoping review of research on a recently introduced stress-related diagnosis

BACKGROUND

Symptoms related to chronic stress are prevalent and entail high societal costs, yet there is a lack of international consensus regarding diagnostics and treatment. A new stress-related diagnosis, exhaustion disorder, was introduced into the Swedish version of ICD-10 in 2005. Since then, use of the diagnosis has increased rapidly.

AIMS

To create the first comprehensive synthesis of research on exhaustion disorder to report on the current state of knowledge. Preregistration: Open Science Framework (http://www.w3.org/1999/xlink">osf.io), doi 10.17605/OSF.IO/VFDKW.

METHOD

A PRISMA-guided scoping review of all empirical studies of exhaustion disorder was conducted. Searches were run in the MEDLINE, PsycInfo and Web of Science databases. Data were systematically charted and thematically categorised based on primary area of investigation.

RESULTS

Eighty-nine included studies were sorted into six themes relating to lived experience of exhaustion disorder (n = 9), symptom presentation and course (n = 13), cognitive functioning (n = 10), biological measures (n = 24), symptom measurement scales (n = 4) and treatment (n = 29). Several studies indicated that individuals with exhaustion disorder experience a range of psychiatric and somatic symptoms beyond fatigue, but robust findings within most thematic categories were scarce. The limited number of studies, lack of replication of findings and methodological limitations (e.g. small samples and scarcity of specified primary outcomes) preclude firm conclusions about the diagnostic construct.

CONCLUSIONS

More research is needed to build a solid knowledge base for exhaustion disorder. International collaboration regarding the conceptualisation of chronic stress and fatigue is warranted to accelerate the growth of evidence.

Regression to the mean in latent change score models: an example involving breastfeeding and intelligence

Background

Latent change score models are often used to study change over time in observational data. However, latent change score models may be susceptible to regression to the mean. Earlier observational studies have identified a positive association between breastfeeding and child intelligence, even when adjusting for maternal intelligence.

Method

In the present study, we investigate regression to the mean in the case of breastfeeding and intelligence of children. We used latent change score modeling to analyze intergenerational change in intelligence, both from mothers to children and backward from children to mothers, in the 1979 National Longitudinal Survey of Youth (NLSY79) dataset (N = 6283).

Results

When analyzing change from mothers to children, breastfeeding was found to have a positive association with intergenerational change in intelligence, whereas when analyzing backward change from children to mothers, a negative association was found.

Conclusions

These discrepant findings highlight a hidden flexibility in the analytical space and call into question the reliability of earlier studies of breastfeeding and intelligence using observational data.

Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI.

ENIGMA-Sleep: Challenges, opportunities, and the road map

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

Consensus-based guidance for conducting and reporting multi-analyst studies

Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.

International transfers of personal data for health research following Schrems II: a problem in need of a solution

On 16 July 2020, the Court of Justice of the European Union issued their decision in the Schrems II case concerning Facebook's transfers of personal data from the EU to the US. The decision may have significant effects on the legitimate transfer of personal data for health research purposes from the EU. This article aims: (i) to outline the consequences of the Schrems II decision for the sharing of personal data for health research between the EU and third countries, particularly in the context of the COVID-19 pandemic; and, (ii) to consider certain options available to address the consequences of the decision and to facilitate international data exchange for health research moving forward.

Dangers of residual confounding: a cautionary tale featuring cognitive ability, socioeconomic background, and education

BACKGROUND

Cognitive ability and socioeconomic background (SEB) have been previously identified as determinants of achieved level of education. According to a "discrimination hypothesis", higher cognitive ability is required from those with lower SEB in order to achieve the same level of education as those with higher SEB. Support for this hypothesis has been claimed from the observation of a positive association between SEB and achieved level of education when adjusting for cognitive ability. We propose a competing hypothesis that the observed association is due to residual confounding.

METHODS

To adjudicate between the discrimination and the residual confounding hypotheses, data from the 1997 National Longitudinal Survey of Youth (NLSY97, N = 8984) was utilized, including a check of the logic where we switched predictor and outcome variables.

RESULTS

The expected positive association between SEB and achieved level of education when adjusting for cognitive ability (predicted by both hypotheses) was found, but a positive association between cognitive ability and SEB when adjusting for level of education (predicted only by the residual confounding hypothesis) was also observed.

CONCLUSIONS

These results highlight the potential use of reversing predictors and outcomes to test the logic of hypothesis testing, and support a residual confounding hypothesis over a discrimination hypothesis in explaining associations between SEB, cognitive ability, and educational outcome.

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 12 May 2020. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.c.4878591.v1.

Cortical thickness and resting-state cardiac function across the lifespan: A cross-sectional pooled mega-analysis

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research.

Spontaneous eye movements during eyes-open rest reduce resting-state-network modularity by increasing visual-sensorimotor connectivity

During wakeful rest, individuals make small eye movements during fixation. We examined how these endogenously driven oculomotor patterns impact topography and topology of functional brain networks. We used a dataset consisting of eyes-open resting-state (RS) fMRI data with simultaneous eye tracking. The eye-tracking data indicated minor movements during rest, which correlated modestly with RS BOLD data. However, eye-tracking data correlated well with echo-planar imaging time series sampled from the area of the eye-orbit (EO-EPI), which is a signal previously used to identify eye movements during exogenous saccades and movie viewing. Further analyses showed that EO-EPI data were correlated with activity in an extensive motor and sensorimotor network, including components of the dorsal attention network and the frontal eye fields. Partialling out variance related to EO-EPI from RS data reduced connectivity, primarily between sensorimotor and visual areas. It also produced networks with higher modularity, lower mean connectivity strength, and lower mean clustering coefficient. Our results highlight new aspects of endogenous eye movement control during wakeful rest. They show that oculomotor-related contributions form an important component of RS network topology, and that those should be considered in interpreting differences in network structure between populations or as a function of different experimental conditions.

We studied how subtle eye movements made during fixation, in absence of any other task, are related to resting-state connectivity measured using fMRI. We used a dataset for which eye tracking and BOLD resting-state were acquired simultaneously. We correlated brain activity with both eye-tracking metrics as well as time series sampled from the area of the eye orbits (EO-EPI). Eye-tracking data correlated well with the EO-EPI data. Furthermore, EO-EPI correlated with BOLD signal in sensorimotor and visual brain systems. Removing variance related to EO-EPI reduced connectivity between sensorimotor and visual areas and resulted in more modular resting-state networks. Our findings show that oculomotor-related contributions are an important component of resting-state network topology, and that they can be studied using EPI data from the eye orbits.

Fostering global data sharing: highlighting the recommendations of the Research Data Alliance COVID-19 working group

The systemic challenges of the COVID-19 pandemic require cross-disciplinary collaboration in a global and timely fashion. Such collaboration needs open research practices and the sharing of research outputs, such as data and code, thereby facilitating research and research reproducibility and timely collaboration beyond borders. The Research Data Alliance COVID-19 Working Group recently published a set of recommendations and guidelines on data sharing and related best practices for COVID-19 research. These guidelines include recommendations for clinicians, researchers, policy- and decision-makers, funders, publishers, public health experts, disaster preparedness and response experts, infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations), and other potential users. These guidelines include recommendations for researchers, policymakers, funders, publishers and infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations). Several overarching themes have emerged from this document such as the need to balance the creation of data adherent to FAIR principles (findable, accessible, interoperable and reusable), with the need for quick data release; the use of trustworthy research data repositories; the use of well-annotated data with meaningful metadata; and practices of documenting methods and software. The resulting document marks an unprecedented cross-disciplinary, cross-sectoral, and cross-jurisdictional effort authored by over 160 experts from around the globe. This letter summarises key points of the Recommendations and Guidelines, highlights the relevant findings, shines a spotlight on the process, and suggests how these developments can be leveraged by the wider scientific community.

Oxazepam and cognitive reappraisal: A randomised experiment

Background

Cognitive reappraisal is a strategy for emotional regulation, important in the context of anxiety disorders. It is not known whether anxiolytic effects of benzodiazepines affect cognitive reappraisal.

Aims

We aimed to investigate the effect of 25 mg oxazepam on cognitive reappraisal.

Methods

In a preliminary investigation, 33 healthy male volunteers were randomised to oxazepam or placebo, and then underwent an experiment where they were asked to use cognitive reappraisal to upregulate or downregulate their emotional response to images with negative or neutral emotional valence. We recorded unpleasantness ratings, skin conductance, superciliary corrugator muscle activity, and heart rate. Participants completed rating scales measuring empathy (Interpersonal Reactivity Index, IRI), anxiety (State-Trait Anxiety Inventory, STAI), alexithymia (Toronto Alexithymia Scale-20, TAS-20), and psychopathy (Psychopathy Personality Inventory-Revised, PPI-R).

Results

Upregulation to negative-valence images in the cognitive reappraisal task caused increased unpleasantness ratings, corrugator activity, and heart rate compared to downregulation. Upregulation to both negative- and neutral-valence images caused increased skin conductance responses. Oxazepam caused lower unpleasantness ratings to negative-valence stimuli, but did not interact with reappraisal instruction on any outcome. Self-rated trait empathy was associated with stronger responses to negative-valence stimuli, whereas self-rated psychopathic traits were associated with weaker responses to negative-valence stimuli.

Conclusions

While 25 mg oxazepam caused lower unpleasantness ratings in response to negative-valence images, we did not observe an effect of 25 mg oxazepam on cognitive reappraisal.

The new accounting for expected adjusted effect test (AEAE test) has higher positive predictive value than a zero-order significance test

OBJECTIVE

The present simulation study aimed to assess positive predictive value (PPV) and negative predictive value (NPV) for our newly introduced Accounting for Expected Adjusted Effect test (AEAE test) and compare it to PPV and NPV for a traditional zero-order significance test.

RESULTS

The AEAE test exhibited greater PPV compared to a traditional zero-order significance test, especially with a strong true adjusted effect, low prior probability, high degree of confounding, large sample size, high reliability in the measurement of predictor X and outcome Y, and low reliability in the measurement of confounder Z. The zero-order significance test, on the other hand, exhibited higher NPV, except for some combinations of high degree of confounding and large sample size, or low reliability in the measurement of Z and high reliability in the measurement of X/Y, in which case the zero-order significance test can be completely uninformative. Taken together, the findings demonstrate desirable statistical properties for the AEAE test compared to a traditional zero-order significance test.

#EEGManyLabs: Investigating the replicability of influential EEG experiments

There is growing awareness across the neuroscience community that the replicability of findings about the relationship between brain activity and cognitive phenomena can be improved by conducting studies with high statistical power that adhere to well-defined and standardised analysis pipelines. Inspired by recent efforts from the psychological sciences, and with the desire to examine some of the foundational findings using electroencephalography (EEG), we have launched #EEGManyLabs, a large-scale international collaborative replication effort. Since its discovery in the early 20th century, EEG has had a profound influence on our understanding of human cognition, but there is limited evidence on the replicability of some of the most highly cited discoveries. After a systematic search and selection process, we have identified 27 of the most influential and continually cited studies in the field. We plan to directly test the replicability of key findings from 20 of these studies in teams of at least three independent laboratories. The design and protocol of each replication effort will be submitted as a Registered Report and peer-reviewed prior to data collection. Prediction markets, open to all EEG researchers, will be used as a forecasting tool to examine which findings the community expects to replicate. This project will update our confidence in some of the most influential EEG findings and generate a large open access database that can be used to inform future research practices. Finally, through this international effort, we hope to create a cultural shift towards inclusive, high-powered multi-laboratory collaborations.

A comparison of models with weight, height, and BMI as predictors of mortality

Introduction

Body mass index (BMI) is a composite variable of weight and height, often used as a predictor of health outcomes, including mortality. The main purpose of combining weight and height in one variable is to obtain a measure of obesity independent of height. It is however unclear how accurate BMI is as a predictor of mortality compared with models including both weight and height or a weight × height interaction as predictors.

Methods

The current study used conscription data on weight, height, and BMI of Swedish men (N = 48,904) in 1969/70 as well as linked data on mortality (3442 deaths) between 1969 and 2008. Cox proportional hazard models including combinations of weight, height, and BMI at conscription as predictors of subsequent all-cause and cause-specific mortality were fitted to data.

Results

An increase by one standard deviation on weight and BMI were associated with an increase in hazard for all-cause mortality by 5.4% and 11.5%, respectively, while an increase by one standard deviation on height was associated with a decrease in hazard for all-cause mortality by 9.4%. The best-fitting model indicated lowest predicted all-cause mortality for those who weighed 60.5 kg at conscription, regardless of height. Further analyses of cause-specific mortality suggest that this weight seems to be a compromise between lower optimal weights to avoid cancer and CVD mortality and a higher optimal weight to not die by suicide.

Conclusions

According to the present findings, there are several ways to make better use of measured weight and height than to calculate BMI when predicting mortality.

Fostering global data sharing: highlighting the recommendations of the Research Data Alliance COVID-19 working group

The systemic challenges of the COVID-19 pandemic require cross-disciplinary collaboration in a global and timely fashion. Such collaboration needs open research practices and the sharing of research outputs, such as data and code, thereby facilitating research and research reproducibility and timely collaboration beyond borders. The Research Data Alliance COVID-19 Working Group recently published a set of recommendations and guidelines on data sharing and related best practices for COVID-19 research. These guidelines include recommendations for researchers, policymakers, funders, publishers and infrastructure providers from the perspective of different domains (Clinical Medicine, Omics, Epidemiology, Social Sciences, Community Participation, Indigenous Peoples, Research Software, Legal and Ethical Considerations). Several overarching themes have emerged from this document such as the need to balance the creation of data adherent to FAIR principles (findable, accessible, interoperable and reusable), with the need for quick data release; the use of trustworthy research data repositories; the use of well-annotated data with meaningful metadata; and practices of documenting methods and software. The resulting document marks an unprecedented cross-disciplinary, cross-sectoral, and cross-jurisdictional effort authored by over 160 experts from around the globe. This letter summarises key points of the Recommendations and Guidelines, highlights the relevant findings, shines a spotlight on the process, and suggests how these developments can be leveraged by the wider scientific community.

A combined fMRI and EMG study of emotional contagion following partial sleep deprivation in young and older humans

Sleep deprivation is proposed to inhibit top-down-control in emotion processing, but it is unclear whether sleep deprivation affects emotional mimicry and contagion. Here, we aimed to investigate effects of partial sleep deprivation on emotional contagion and mimicry in young and older humans. Participants underwent partial sleep deprivation (3 h sleep opportunity at the end of night), crossed-over with a full sleep condition in a balanced order, followed by a functional magnetic resonance imaging and electromyography (EMG) experiment with viewing of emotional and neutral faces and ratings of emotional responses. The final sample for main analyses was n = 69 (n = 36 aged 20–30 years, n = 33 aged 65–75 years). Partial sleep deprivation caused decreased activation in fusiform gyri for angry faces and decreased ratings of happiness for all stimuli, but no significant effect on the amygdala. Older participants reported more anger compared to younger participants, but no age differences were seen in brain responses to emotional faces or sensitivity to partial sleep deprivation. No effect of the sleep manipulation was seen on EMG. In conclusion, emotional contagion, but not mimicry, was affected by sleep deprivation. Our results are consistent with the previously reported increased negativity bias after insufficient sleep.

The Stockholm sleepy brain study: effects of sleep deprivation on cognitive and emotional processing in young and old. https://clinicaltrials.gov/ct2/show/NCT02000076.

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

Gray Matter Volume Correlates of Sleepiness: A Voxel-Based Morphometry Study in Younger and Older Adults

BACKGROUND

Subjectively experienced sleepiness is a problem in society, possibly linked with gray matter (GM) volume. Given a different sleep pattern, aging may affect such associations, possibly due to shrinking brain volume.

PURPOSE

The purpose of the present study was to investigate the association between subjectively rated sleepiness and GM volume in thalamus, insula, hippocampus, and orbitofrontal cortex of young and older adults, after a normal night's sleep.

METHODS

Eighty-four healthy individuals participated (46 aged 20-30 years, and 38 aged 65-75 years). Morphological brain data were collected in a 3T magnetic resonance imaging (MRI) scanner. Sleepiness was rated multiple times during the imaging sessions.

RESULTS

In older, relative to younger, adults, clusters within bilateral mid-anterior insular cortex and right thalamus were negatively associated with sleepiness. Adjustment for the immediately preceding total sleep time eliminated the significant associations.

CONCLUSION

Self-rated momentary sleepiness in a monotonous situation appears to be negatively associated with GM volume in clusters within both thalamus and insula in older individuals, and total sleep time seems to play a role in this association. Possibly, this suggests that larger GM volume in these clusters may be protective against sleepiness in older individuals. This notion needs confirmation in further studies.

Improvement in indices of cellular protection after psychological treatment for social anxiety disorder

Telomere attrition is a hallmark of cellular aging and shorter telomeres have been reported in mood and anxiety disorders. Telomere shortening is counteracted by the enzyme telomerase and cellular protection is also provided by the antioxidant enzyme glutathione peroxidase (GPx). Here, telomerase, GPx, and telomeres were investigated in 46 social anxiety disorder (SAD) patients in a within-subject design with repeated measures before and after cognitive behavioral therapy. Treatment outcome was assessed by the Liebowitz Social Anxiety Scale (self-report), administered three times before treatment to control for time and regression artifacts, and posttreatment. Venipunctures were performed twice before treatment, separated by 9 weeks, and once posttreatment. Telomerase activity and telomere length were measured in peripheral blood mononuclear cells and GPx activity in plasma. All patients contributed with complete data. Results showed that social anxiety symptom severity was significantly reduced from pretreatment to posttreatment (Cohen's d = 1.46). There were no significant alterations in telomeres or cellular protection markers before treatment onset. Telomere length and telomerase activity did not change significantly after treatment, but an increase in telomerase over treatment was associated with reduced social anxiety. Also, lower pretreatment telomerase activity predicted subsequent symptom improvement. GPx activity increased significantly during treatment, and increases were significantly associated with symptom improvement. The relationships between symptom improvement and putative protective enzymes remained significant also after controlling for body mass index, sex, duration of SAD, smoking, concurrent psychotropic medication, and the proportion of lymphocytes to monocytes. Thus, indices of cellular protection may be involved in the therapeutic mechanisms of psychological treatment for anxiety.

Cross-sectional associations between inflammation, sickness behaviour, health anxiety and self-rated health in a Swedish primary care population

This study investigated associations between inflammatory markers, sickness behaviour, health anxiety and self-rated health in 311 consecutive primary care patients. Poor self-rated health was associated with high sickness behaviour ( ρ = 0.28, P < 0.001; ρ = 0.42, P = 0.003) and high health anxiety ( ρ = 0.31, P < 0.001; ρ = –0.32, P = 0.003). High levels of interleukin 6 were associated with poor self-rated health in men ( ρ = 0.26, P = 0.009). Low levels of interleukin-6 were associated with poor self-rated health in women ( ρ = –0.15, P = 0.04), but this association was non-significant when adjusted for health anxiety ( ρ = –0.08, P = 0.31). These results are consistent with the theory that interoceptive processes draw on both inflammatory mediators and the state of sickness behaviour in inferring health state.

Sleep restriction caused impaired emotional regulation without detectable brain activation changes-a functional magnetic resonance imaging study

Sleep restriction has been proposed to cause impaired emotional processing and emotional regulation by inhibiting top-down control from prefrontal cortex to amygdala. Intentional emotional regulation after sleep restriction has, however, never been studied using brain imaging. We aimed here to investigate the effect of partial sleep restriction on emotional regulation through cognitive reappraisal. Forty-seven young (age 20-30) and 33 older (age 65-75) participants (38/23 with complete data and successful sleep intervention) performed a cognitive reappraisal task during fMRI after a night of normal sleep and after restricted sleep (3 h). Emotional downregulation was associated with significantly increased activity in the dorsolateral prefrontal cortex (p _FWE < 0.05) and lateral orbital cortex (p _FWE < 0.05) in young, but not in older subjects. Sleep restriction was associated with a decrease in self-reported regulation success to negative stimuli (p < 0.01) and a trend towards perceiving all stimuli as less negative (p = 0.07) in young participants. No effects of sleep restriction on brain activity nor connectivity were found in either age group. In conclusion, our data do not support the idea of a prefrontal-amygdala disconnect after sleep restriction, and neural mechanisms underlying behavioural effects on emotional regulation after insufficient sleep require further investigation.

Estimating statistical power, posterior probability and publication bias of psychological research using the observed replication rate

In this paper, we show how Bayes' theorem can be used to better understand the implications of the 36% reproducibility rate of published psychological findings reported by the Open Science Collaboration. We demonstrate a method to assess publication bias and show that the observed reproducibility rate was not consistent with an unbiased literature. We estimate a plausible range for the prior probability of this body of research, suggesting expected statistical power in the original studies of 48-75%, producing (positive) findings that were expected to be true 41-62% of the time. Publication bias was large, assuming a literature with 90% positive findings, indicating that negative evidence was expected to have been observed 55-98 times before one negative result was published. These findings imply that even when studied associations are truly NULL, we expect the literature to be dominated by statistically significant findings.

Data availability, reusability, and analytic reproducibility: evaluating the impact of a mandatory open data policy at the journal Cognition

Access to data is a critical feature of an efficient, progressive and ultimately self-correcting scientific ecosystem. But the extent to which in-principle benefits of data sharing are realized in practice is unclear. Crucially, it is largely unknown whether published findings can be reproduced by repeating reported analyses upon shared data ('analytic reproducibility'). To investigate this, we conducted an observational evaluation of a mandatory open data policy introduced at the journal Cognition. Interrupted time-series analyses indicated a substantial post-policy increase in data available statements (104/417, 25% pre-policy to 136/174, 78% post-policy), although not all data appeared reusable (23/104, 22% pre-policy to 85/136, 62%, post-policy). For 35 of the articles determined to have reusable data, we attempted to reproduce 1324 target values. Ultimately, 64 values could not be reproduced within a 10% margin of error. For 22 articles all target values were reproduced, but 11 of these required author assistance. For 13 articles at least one value could not be reproduced despite author assistance. Importantly, there were no clear indications that original conclusions were seriously impacted. Mandatory open data policies can increase the frequency and quality of data sharing. However, suboptimal data curation, unclear analysis specification and reporting errors can impede analytic reproducibility, undermining the utility of data sharing and the credibility of scientific findings.

A Practical Guide for Transparency in Psychological Science

The credibility of scientific claims depends upon the transparency of the research products upon which they are based (e.g., study protocols, data, materials, and analysis scripts). As psychology navigates a period of unprecedented introspection, user-friendly tools and services that support open science have flourished. However, the plethora of decisions and choices involved can be bewildering. Here we provide a practical guide to help researchers navigate the process of preparing and sharing the products of their research (e.g., choosing a repository, preparing their research products for sharing, structuring folders, etc.). Being an open scientist means adopting a few straightforward research management practices, which lead to less error prone, reproducible research workflows. Further, this adoption can be piecemeal – each incremental step towards complete transparency adds positive value. Transparent research practices not only improve the efficiency of individual researchers, they enhance the credibility of the knowledge generated by the scientific community.

Effects of late-night short-sleep on in-home polysomnography: relation to adult age and sex

Bedtime is frequently delayed by many factors in life, and a homeostatic response to the delay may compensate partly for increased time awake and shortened sleep. Because sleep becomes shorter with age and women complain of disturbed sleep more often than men, age and sex differences in the homeostatic response to a delayed bedtime may modify the homeostatic response. The purpose of the present study was to investigate the effect of late-night short-sleep (3 h with awakening at about 07:00 hours) on in-home recorded sleep in men and women in two age groups (20-30 and 65-75 years). Results (N = 59) showed that late-night short-sleep was associated with an increase in percentage of N3 sleep and a decrease in percentage of rapid eye movement sleep, as well as decreases in several measures of sleep discontinuity and rapid eye movement density. Men showed a smaller decrease in percentage of rapid eye movement sleep than women in response to late-night short-sleep, as did older individuals of both sexes compared with younger. Older men showed a weaker percentage of N3 sleep in response to late-night short-sleep than younger men. In general, men showed a greater percentage of rapid eye movement sleep and a lower percentage of N3 sleep than women, and older individuals showed a lower percentage of N3 sleep than younger. In particular, older men showed very low levels of percentage of N3 sleep. We conclude that older males show less of a homeostatic response to late-night short-sleep. This may be an indication of impaired capacity for recovery in older men. Future studies should investigate if this pattern can be linked to gender-associated differences in morbidity and mortality.

The effect of sleep restriction on empathy for pain: An fMRI study in younger and older adults

Age and sleep both affect emotional functioning. Since sleep patterns change over the lifespan, we investigated the effects of short sleep and age on empathic responses. In a randomized cross-over experimental design, healthy young and older volunteers (n = 47 aged 20–30 years and n = 39 aged 65–75 years) underwent functional magnetic resonance imaging (fMRI) after normal sleep or night sleep restricted to 3 hours. During fMRI, participants viewed pictures of needles pricking a hand (pain) or Q-tips touching a hand (control), a well-established paradigm to investigate empathy for pain. There was no main effect of sleep restriction on empathy. However, age and sleep interacted so that sleep restriction caused increased unpleasantness in older but not in young participants. Irrespective of sleep condition, older participants showed increased activity in angular gyrus, superior temporal sulcus and temporo-parietal junction compared to young. Speculatively, this could indicate that the older individuals adopted a more cognitive approach in response to others’ pain. Our findings suggest that caution in generalizability across age groups is needed in further studies of sleep on social cognition and emotion.