Eleven strategies for making reproducible research and open science training the norm at research institutions.

Reproducible research and open science practices have the potential to accelerate scientific progress by allowing others to reuse research outputs, and by promoting rigorous research that is more likely to yield trustworthy results. However, these practices are uncommon in many fields, so there is a clear need for training that helps and encourages researchers to integrate reproducible research and open science practices into their daily work. Here, we outline eleven strategies for making training in these practices the norm at research institutions. The strategies, which emerged from a virtual brainstorming event organized in collaboration with the German Reproducibility Network, are concentrated in three areas: (i) adapting research assessment criteria and program requirements; (ii) training; (iii) building communities. We provide a brief overview of each strategy, offer tips for implementation, and provide links to resources. We also highlight the importance of allocating resources and monitoring impact. Our goal is to encourage researchers - in their roles as scientists, supervisors, mentors, instructors, and members of curriculum, hiring or evaluation committees - to think creatively about the many ways they can promote reproducible research and open science practices in their institutions.

Don't miss the chance to reap the fruits of recent advances in behavioral genetics.

In her target article, Burt revives a by now ancient debate on nature and nurture, and the ways to measure, disentangle, and ultimately trust one or the other of these forces. Unfortunately, she largely dismisses recent advances in behavior genetics and its huge potential in contributing to a better prediction and understanding of complex traits in social sciences.

A data multiverse analysis investigating non-model based SCR quantification approaches.

Electrodermal signals are commonly used outcome measures in research on arousal, emotion, and habituation. Recently, we reported on heterogeneity in skin conductance response quantification approaches and its impact on replicability. Here we provide complementary work focusing on within-approach heterogeneity of specifications for skin conductance response quantification. We focus on heterogeneity within the baseline-correction approach (BLC) which appeared as particularly heterogeneous-for instance with respect to the pre-CS baseline window duration, the start, and end of the peak detection window. We systematically scrutinize the robustness of results when applying different BLC approach specifications to one representative pre-existing data set (N = 118) in a (partly) pre-registered study. We report high agreement between different BLC approaches for US and CS+ trials, but moderate to poor agreement for CS- trials. Furthermore, a specification curve of the main effect of CS discrimination during fear acquisition training from all potential and reasonable combinations of specifications (N = 150) and a prototypical trough-to-peak (TTP) approach indicates that resulting effect sizes are largely comparable. A second specification curve (N = 605 specific combinations) highlights a strong impact of different transformation types. Crucially, however, we show that BLC approaches often misclassify the peak value-particularly for CS- trials, leading to stimulus-specific biases and challenges for post-processing and replicability of CS discrimination across studies applying different approaches. Lastly, we investigate how negative skin conductance values in BLC, appearing most frequently for CS- (CS- > CS+ > US), correspond to values in TTP quantification. We discuss the results considering prospects and challenges of the multiverse approach and future directions.

Serotonin transporter gene methylation predicts long-term cortisol concentrations in hair.

Epigenetic signatures, such as DNA methylation (DNAM), have been implicated in long-term dysregulation of the hypothalamus-pituitary-adrenal (HPA) axis and related health risks. Based on a wealth of neuroendocrine studies on genetic polymorphisms in the serotonin transporter gene (SLC6A4), this locus constitutes a key candidate to explore associations of DNAM patterns and HPA-axis functioning. The few studies addressing this link so far exclusively relied on spot measurements of HPA-axis activity, which may not adequately reflect cortisol output over prolonged periods of time. To address this gap, hair cortisol concentrations (HCC), a valid measure of integrated long-term cortisol levels, were utilized to investigate endocrine correlates of SLC6A4 DNAM in 183 adults. Whole blood samples were drawn for DNAM analyses of 83 CpG sites within a 799-bp promoter-associated CpG island of SLC6A4 via bisulfite pyrosequencing. In addition, all participants were genotyped for the serotonin transporter polymorphism (5-HTTLPR). First, results revealed a significant negative association of SLC6A4 DNAM and HCC. Second, there was no significant main effect of 5-HTTLPR genotype on HCC when analyses were conducted on the basis of both bi-allelic classification and the 5-HTTLPR/rs25531 mini-haplotype. Third, the current data revealed a significant interaction of SLC6A4 DNAM and 5-HTTLPR genotype on HCC. Comparable to the pattern we had previously observed concerning cortisol stress reactivity, the S allele relates to increased HCC in individuals displaying low levels of SLC6A4 DNAM. By contrast, no such effect occurred under conditions of high SLC6A4 DNAM, indicating that epigenetic changes may compensate for genotype-dependent differences in long-term cortisol output. Together, respective findings support the idea of an epigenetic contribution to long-term HPA-axis activity and further highlight the usefulness of combining genetic and epigenetic information in future neuroendocrine studies.