Guilt is effectively induced by a written auto-biographical essay but not reduced by experimental pain.

Introduction The aim of the present study was (1) to validate the method of guilt-induction by means of a written auto-biographical essay and (2) to test whether experimental pain is apt to alleviate the mental burden of guilt, a concept receiving support from both empirical research and clinical observation. Methods Three independent groups of healthy male participants were recruited. Group allocation was not randomized but within group pain/sham administration was counterbalanced over the two test-days. Groups were tested in the following consecutive order: Group A: guilt induction, heat-pain/sham, N = 59; Group B: guilt induction, cold-pressure-pain/sham, N = 43; Group C: emotionally neutral induction, heat-pain/sham, N = 39. Guilt was induced on both test-days in group A and B before pain/sham administration. Visual analog scale (VAS) guilt ratings immediately after pain/sham stimulation served as the primary outcome. In a control group C the identical heat-pain experiment was performed like in group A but a neutral emotional state was induced. Results A consistently strong overall effect of guilt-induction (heat-pain: p < 0.001, effect size r = 0.71; CPT-pain p < 0.001, r = 0.67) was found when compared to the control-condition (p = 0.25, r = 0.08). As expected, heat- and cold-pressure-stimuli were highly painful in all groups (p < 0.0001, r = 0.89). However, previous research supporting the hypothesis that pain is apt to reduce guilt was not replicated. Conclusion Although guilt-induction was highly effective on both test-days no impact of pain on behavioral guilt-ratings in healthy individuals could be identified. Guilt induction per se did not depend on the order of testing. The result questions previous experimental work on the impact of pain on moral emotions

Enhancing precision in human neuroscience

Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability – in science in general, but also specifically in human neuroscience – have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience

Evaluation of an eye tracking setup for studying visual attention in face-to-face conversations

Many eye tracking studies use facial stimuli presented on a display to investigate attentional processing of social stimuli. To introduce a more realistic approach that allows interaction between two real people, we evaluated a new eye tracking setup in three independent studies in terms of data quality, short-term reliability and feasibility. Study 1 measured the robustness, precision and accuracy for calibration stimuli compared to a classical display-based setup. Study 2 used the identical measures with an independent study sample to compare the data quality for a photograph of a face (2D) and the face of the real person (3D). Study 3 evaluated data quality over the course of a real face-to-face conversation and examined the gaze behavior on the facial features of the conversation partner. Study 1 provides evidence that quality indices for the scene-based setup were comparable to those of a classical display-based setup. Average accuracy was better than 0.4° visual angle. Study 2 demonstrates that eye tracking quality is sufficient for 3D stimuli and robust against short interruptions without re-calibration. Study 3 confirms the long-term stability of tracking accuracy during a face-to-face interaction and demonstrates typical gaze patterns for facial features. Thus, the eye tracking setup presented here seems feasible for studying gaze behavior in dyadic face-to-face interactions. Eye tracking data obtained with this setup achieves an accuracy that is sufficient for investigating behavior such as eye contact in social interactions in a range of populations including clinical conditions, such as autism spectrum and social phobia