Measuring Emotions in Electronic Markets

Although the importance of emotions in economic decision-making is being widely accepted, it is still unclear how and to what extent emotional processing affects economic behavior. In this paper, we propose a new methodological framework for behavioral IS studies that we call physioeconomics, by which it is possible to measure psychophysiological correlates of human emotions during controlled laboratory experiments. In contrast to brain imaging technologies as in NeuroIS, the analysis of autonomic physiological parameters can be achieved with a comparatively low amount of measurement overhead and, thus, allows collecting empirical data for much larger sample sizes. Therefore, this approach is particularly qualified for the study of emotions in electronic markets. In order to show that physioeconomics is able to provide insightful results we apply this method in an exemplary auction experiment in which we compare bidders’ arousal throughout the bidding process and in response to winning or losing

Brain Responses during the Anticipation of Dyspnea

Dyspnea is common in many cardiorespiratory diseases. Already the anticipation of this aversive symptom elicits fear in many patients resulting in unfavorable health behaviors such as activity avoidance and sedentary lifestyle. This study investigated brain mechanisms underlying these anticipatory processes. We induced dyspnea using resistive-load breathing in healthy subjects during functional magnetic resonance imaging. Blocks of severe and mild dyspnea alternated, each preceded by anticipation periods. Severe dyspnea activated a network of sensorimotor, cerebellar, and limbic areas. The left insular, parietal opercular, and cerebellar cortices showed increased activation already during dyspnea anticipation. Left insular and parietal opercular cortex showed increased connectivity with right insular and anterior cingulate cortex when severe dyspnea was anticipated, while the cerebellum showed increased connectivity with the amygdala. Notably, insular activation during dyspnea perception was positively correlated with midbrain activation during anticipation. Moreover, anticipatory fear was positively correlated with anticipatory activation in right insular and anterior cingulate cortex. The results demonstrate that dyspnea anticipation activates brain areas involved in dyspnea perception. The involvement of emotion-related areas such as insula, anterior cingulate cortex, and amygdala during dyspnea anticipation most likely reflects anticipatory fear and might underlie the development of unfavorable health behaviors in patients suffering from dyspnea

A call for evidence-based security tools

Since the 2001 attacks on the twin towers, policies on security have changed drastically, bringing about an increased need for tools that allow for the detection of deception. Many of the solutions offered today, however, lack scientific underpinning. We recommend two important changes to improve the (cost) effectiveness of security policy. To begin with, the emphasis of deception research should shift from technological to behavioural sciences. Secondly, the burden of proof should lie with the manufacturers of the security tools. Governments should not rely on security tools that have not passed scientific scrutiny, and should only employ those methods that have been proven effective. After all, the use of tools that do not work will only get us further from the truth

A Longitudinal Study

Adverse experiences interact with individual vulnerability in the etiology of mental disorders, but due to the paucity of longitudinal studies, their precise interplay remains unclear. Here, we investigated how individual differences in threat responsiveness modulated adjustments in negative affect during the COVID-19 pandemic. Participants (N = 441) underwent a fear conditioning and generalization experiment between 2013 and 2020 and were reassessed regarding anxiety and depression symptoms after the pandemic outbreak. Participants showed increased levels of negative affect following pandemic onset, which were partly modulated by laboratory measures of threat responsiveness. Decreased differentiation of threat and safety signals in participants with higher prepandemic depression and anxiety scores in the laboratory assessment were most predictive of increased symptom levels after the onset of the pandemic. However, effects were small and should be replicated in independent samples to further characterize how individual differences in threat processing interact with adverse experiences in the development of psychopathology.Peer Reviewe

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

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

Artificial faces predict gaze allocation in complex dynamic scenes

Both low-level physical saliency and social information, as presented by human heads or bodies, are known to drive gaze behavior in free-viewing tasks. Researchers have previously made use of a great variety of face stimuli, ranging from photographs of real humans to schematic faces, frequently without systematically differentiating between the two. In the current study, we used a Generalized Linear Mixed Model (GLMM) approach to investigate to what extent schematic artificial faces can predict gaze when they are presented alone or in competition with real human faces. Relative differences in predictive power became apparent, while GLMMs suggest substantial effects for real and artificial faces in all conditions. Artificial faces were accordingly less predictive than real human faces but still contributed significantly to gaze allocation. These results help to further our understanding of how social information guides gaze in complex naturalistic scenes

Reliability and consistency affect the integration of visual depth cues

Abstract Originalsprache (englisch) Visual perception relies on a two-dimensional projection of the viewed scene on the retinas of both eyes. Thus, visual depth has to be reconstructed from a number of different cues that are subsequently integrated to obtain robust depth percepts. Existing models of sensory integration are mainly based on the reliabilities of individual cues and disregard potential cue interactions. In the current study, an extended Bayesian model is proposed that takes into account both cue reliability and consistency. Four experiments were carried out to test this model's predictions. Observers had to judge visual displays of hemi-cylinders with an elliptical cross section, which were constructed to allow for an orthogonal variation of several competing depth cues. In Experiment 1 and 2, observers estimated the cylinder's depth as defined by shading, texture, and motion gradients. The degree of consistency among these cues was systematically varied. It turned out that the extended Bayesian model provided a better fit to the empirical data compared to the traditional model which disregards covariations among cues. To circumvent the potentially problematic assessment of single-cue reliabilities, Experiment 3 used a multiple-observation task, which allowed for estimating perceptual weights from multiple-cue stimuli. Using the same multiple-observation task, the integration of stereoscopic disparity, shading, and texture gradients was examined in Experiment 4. It turned out that less reliable cues were downweighted in the combined percept. Moreover, a specific influence of cue consistency was revealed. Shading and disparity seemed to be processed interactively while other cue combinations could be well described by additive integration rules. These results suggest that cue combination in visual depth perception is highly flexible and depends on single-cue properties as well as on interrelations among cues. The extension of the traditional cue combination model is defended in terms of the necessity for robust perception in ecologically valid environments and the current findings are discussed in the light of emerging computational theories and neuroscientific approaches.Abstract deutsch Da die visuelle Wahrnehmung auf einer zweidimensionalen, retinalen Projektion der betrachteten Szenerie beruht, muss räumliche Tiefe aus verschiedenen Tiefenhinweisen erschlossen werden. Die Kombination dieser Merkmale führt nachfolgend zu einem stabilen Perzept. Aktuelle Modelle sensorischer Integration schreiben den Reliabilitäten einzelner Tiefenmerkmale eine prominente Rolle zu, vernachlässigen dabei jedoch deren Interaktionen untereinander. In der vorliegenden Studie wurde ein erweitertes Bayesianisches Modell erarbeitet und in vier Experimenten überprüft, das sowohl Reliabilität als auch Konsistenz verschiedener Wahrnehmungskanäle berücksichtigt. Probanden schätzten die räumliche Tiefe visuell präsentierter Halbzylinder mit elliptischer Grundfläche ein. In den Experimenten 1 und 2 wurden partiell konsistente Schattierungs-, Textur- und Bewegungsinformationen verwendet. Die gewonnenen empirischen Daten ließen sich gut durch das erweiterte Integrationsmodell erklären, was die Bedeutung der Konsistenz von Tiefenkriterien unterstützt. Um auf die problematische Messung der Reliabilitäten einzelner Tiefenhinweise verzichten zu können, wurde in Experiment 3 ein neueres Verfahren erfolgreich umgesetzt, mit dem sich perzeptuelle Gewichte einzelner Merkmale in komplexen Stimuli schätzen lassen. Dieses Verfahren wurde auch in Experiment 4 angewandt, um die Integration von stereoskopischer Disparität, Schattierungs- und Texturgradienten zu untersuchen. Die Reliabilität einzelner Tiefenkriterien wirkte sich proportional auf deren Gewichtung aus. Merkmalsinteraktionen spielten jedoch nur in Bezug auf konsistente Schattierungs- und Disparitätsinformation eine entscheidende Rolle. Andere Merkmalskombinationen ließen sich gut auf Basis einer additiven Integration beschreiben. Diese Resultate wurden in der vorliegenden Studie auf der Basis von theoretischen, neurowissenschaftlichen Ansätzen und psychophysiologischen Befunden diskutiert. Sie belegen die Flexibilität visueller Tiefenwahrnehmung und unterstreichen die Bedeutsamkeit individueller Merkmalseigenschaften sowie deren Interaktionen im Rahmen intrasensorischer Integrationsprozesse

Alcohol facilitates detection of concealed identity information

The Concealed Information Test (CIT) is a well-validated means to detect whether someone possesses certain (e.g., crime-relevant) information. The current study investigated whether alcohol intoxication during CIT administration influences reaction time (RT) CIT-effects. Two opposing predictions can be made. First, by decreasing attention to critical information, alcohol intoxication could diminish CIT-effects. Second, by hampering the inhibition of truthful responses, alcohol intoxication could increase CIT-effects. A correlational field design was employed. Participants (n = 42) were recruited and tested at a bar, where alcohol consumption was voluntary and incidental. Participants completed a CIT, in which they were instructed to hide knowledge of their true identity. BAC was estimated via breath alcohol ratio. Results revealed that higher BAC levels were correlated with higher CIT-effects. Our results demonstrate that robust CIT effects can be obtained even when testing conditions differ from typical laboratory settings and strengthen the idea that response inhibition contributes to the RT-CIT effect