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.
Biological markers of risk taking are prominent targets for clinical, developmental, and longitudinal research. With respect to brain function, several regions are considered central for risky choice, yet insights into the neural basis of risk taking stem primarily from studies using single measures. Considering that recent studies suggested different risk-taking measures cannot be used interchangeably, it is currently unclear whether core regions of the brain involved in risk show a measure-dependent functional dissociation. Reporting results from the imaging subsample (N = 116 young adults) of the Basel–Berlin Risk Study, we examine (1) the conjunction of average neural representations of experience-based risky choice in the Balloon Analogue Risk Task and description-based risky choice in monetary gambles, (2) the preservation of individual activation differences across the two measures, and (3) the explanatory power of the neural correlates of risky choice for behavior. Our results suggest common group-level activation increases in nucleus accumbens, inconsistent individual differences in regional activation across measures, and limited explanatory power of neural indices for behavior, within and across measures. Our findings help clarify commonalities and differences between the neural representation of experienced and described risk, and thus should inform research designs targeting individual differences in risk taking.
Maladaptive risk taking can have severe individual and societal consequences; thus, individual differences are prominent targets for intervention and prevention. Although brain activation has been shown to be associated with individual differences in risk taking, the directionality of the reported brain–behavior associations is less clear. Here, we argue that one aspect contributing to the mixed results is the low convergence between risk-taking measures, especially between the behavioral tasks used to elicit neural functional markers. To address this question, we analyzed within-participant neuroimaging data for two widely used risk-taking tasks collected from the imaging subsample of the Basel–Berlin Risk Study ( N = 116 young human adults). Focusing on core brain regions implicated in risk taking (nucleus accumbens, anterior insula, and anterior cingulate cortex), for the two tasks, we examined group-level activation for risky versus safe choices, as well as associations between local functional markers and various risk-related outcomes, including psychometrically derived risk preference factors. While we observed common group-level activation in the two tasks (notably increased nucleus accumbens activation), individual differences analyses support the idea that the presence and directionality of associations between brain activation and risk taking varies as a function of the risk-taking measures used to capture individual differences. Our results have methodological implications for the use of brain markers for intervention or prevention.
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