No abstract

No abstract

SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. 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 dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.

Individuals’ risk attitudes are known to guide choices about uncertain options. However, in the presence of others’ decisions, these choices can be swayed and manifest as riskier or safer behavior than one would express alone. To test the mechanisms underlying effective social ‘nudges’ in human decision-making, we used functional neuroimaging and a task in which participants made choices about gambles alone and after observing others’ selections. Against three alternative explanations, we found that observing others’ choices of gambles increased the subjective value (utility) of those gambles for the observer. This ‘other-conferred utility’ was encoded in ventromedial prefrontal cortex, and these neural signals predicted conformity. We further identified a parametric interaction with individual risk preferences in anterior cingulate cortex and insula. These data provide a neuromechanistic account of how information from others is integrated with individual preferences that may explain preference-congruent susceptibility to social signals of safety and risk.

The COVID-19 pandemic has led many people to suffer from emotional distress. Previous studies suggest that women process and express affective experiences, such as fear, with a greater intensity compared to men. We administered an online survey to a sample of participants in the United States that measures fear of COVID-19, perceptions about health and financial risks, and preventative measures taken. Despite the empirical fact that men are more likely to experience adverse health consequences from COVID-19, women report greater fear and more negative expectations about health-related consequences of COVID-19 than men. However, women are more optimistic than men regarding the financial consequences of the pandemic. Women also report more negative emotional experiences generally during the pandemic, particularly in situations where other people or the government take actions that make matters worse. Though women report taking more preventative measures than men in response to the pandemic, gender differences in behavior are reduced after controlling for fear. These results shed light on how differences in emotional experiences of the pandemic may inform policy interventions.

No abstract

No abstract

Experimental work in economics prompted the development of theories of other-regarding behavior. In this article we reanalyze two classic public goods experiments and focus on the nature of individuals' responses to others' behavior in order to help distinguish alternative motives for giving, including altruism, warm glow, reciprocity, and inequality aversion. Analysis that allows for asymmetric feedback responses generates support for inequality aversion motives but little for reciprocity (matching), altruism, and warm glow. We conclude that individual-level analysis of existing public goods data can provide more insightful, informative estimates of treatment effects.