Felix Henninger

Mousetrap: An integrated, open-source mouse-tracking package

Mouse-tracking – the analysis of mouse movements in computerized experiments – is becoming increasingly popular in the cognitive sciences. Mouse movements are taken as an indicator of commitment to or conflict between choice options during the decision process. Using mouse-tracking, researchers have gained insight into the temporal development of cognitive processes across a growing number of psychological domains. In the current article, we present software that offers easy and convenient means of recording and analyzing mouse movements in computerized laboratory experiments. In particular, we introduce and demonstrate the mousetrap plugin that adds mouse-tracking to OpenSesame, a popular general-purpose graphical experiment builder. By integrating with this existing experimental software, mousetrap allows for the creation of mouse-tracking studies through a graphical interface, without requiring programming skills. Thus, researchers can benefit from the core features of a validated software package and the many extensions available for it (e.g., the integration with auxiliary hardware such as eye-tracking, or the support of interactive experiments). In addition, the recorded data can be imported directly into the statistical programming language R using the mousetrap package, which greatly facilitates analysis. Mousetrap is cross-platform, open-source and available free of charge from https://github.com/pascalkieslich/mousetrap-os.

The reversed description-experience gap: Disentangling sources of presentation format effects in risky choice

Previous literature has suggested that risky choice patterns in general--and probability weighting in particular--are strikingly different in experience-based as compared with description-based formats. In 2 reanalyses and 3 new experiments, we investigate differences between experience-based and description-based decisions using a parametric approach based on cumulative prospect theory (CPT). Once controlling for sampling biases, we consistently find a reversal of the typical description-experience gap, that is, a reduced sensitivity to probabilities and increased overweighting of small probabilities in decisions from experience as compared with decisions from descriptions. This finding supports the hypothesis that regression to the mean effects in probability estimation are a crucial source of differences between both presentation formats. Further analyses identified task specific information asymmetry prevalent in gambles involving certainty as a third source of differences. We present a novel conceptualization of multiple independent sources of bias that contribute to the description-experience gap, namely sampling biases and task specific information asymmetry on the one hand, and regression to the mean effects in probability estimation on the other hand.

Psynteract: A flexible, cross-platform, open framework for interactive experiments

We introduce a novel platform for interactive studies, that is, any form of study in which participants’ experiences depend not only on their own responses, but also on those of other participants who complete the same study in parallel, for example a prisoner’s dilemma or an ultimatum game. The software thus especially serves the rapidly growing field of strategic interaction research within psychology and behavioral economics. In contrast to all available software packages, our platform does not handle stimulus display and response collection itself. Instead, we provide a mechanism to extend existing experimental software to incorporate interactive functionality. This approach allows us to draw upon the capabilities already available, such as accuracy of temporal measurement, integration with auxiliary hardware such as eye-trackers or (neuro-)physiological apparatus, and recent advances in experimental software, for example capturing response dynamics through mouse-tracking. Through integration with OpenSesame, an open-source graphical experiment builder, studies can be assembled via a drag-and-drop interface requiring little or no further programming skills. In addition, by using the same communication mechanism across software packages, we also enable interoperability between systems. Our source code, which provides support for all major operating systems and several popular experimental packages, can be freely used and distributed under an open source license. The communication protocols underlying its functionality are also well documented and easily adapted to further platforms. Code and documentation are available at https://github.com/psynteract/.

Lead Us (Not) into Temptation: Testing the Motivational Mechanisms Linking Honesty-Humility to Cooperation: Honesty-Humility and Temptation

Over the past decades, there has been considerable interest in individual differences in cooperative behaviour and how these can be explained. Whereas the Honesty–Humility dimension from the HEXACO model of personality has been identified as a consistent predictor of cooperation, the underlying motivational mechanisms of this association have remained unclear—especially given the confound between the temptation to exploit others and the fear of being exploited as motivational drivers of defection in social dilemmas. In a reanalysis and a new experiment, we tease apart these mechanisms by manipulating the rank order of pay–offs in a symmetric two–person game paradigm, essentially implementing the classic prisoners dilemma, stag hunt, and chicken games. Results revealed that Honesty–Humility predicted cooperation specifically in the games in which temptation was a potential motivator of defection, whereas it did not account for cooperation in those games in which only fear implied defection. Our findings thereby shed light on the underlying motivational mechanisms of the Honesty–Humility–cooperation link and, more generally, demonstrate how economic games can be used to disentangle such mechanisms. Copyright