The goal of this study is to estimate the variability of neuroscientific results across analysis teams. In particular, we collected fMRI data from n=119 participants on two versions of a mixed gambles task. For the data analysis, research groups versed in fMRI analysis will be given the raw data to independently estimate the brain activations according to nine ex ante hypothesized brain regions. The main outcome variable will be the number of teams reporting a statistically significant whole-brain corrected result for each hypothesis. In addition, we will run prediction markets for all hypotheses, providing an estimate of peer beliefs about the results.
November 2018 | Distribution of data to the analysis teams.
February 2019 | Deadline for submission of data analyses.
May 2019 | Prediction markets are open for 10 days.
June 2019 | Payout of traders on the prediction markets.
The project will be run by research teams from California Institut of Technology, Stanford University, the Stockholm School of Economics, Tel Aviv University, and the University of Innsbruck. The fMRI data was collected during winter and spring 2018 at Tel Aviv University. The contact person for the analysis teams is Rotem Botvinik-Nezer, from Tel Aviv University.
Camerer, C. F., Dreber, A., Forsell, E., Ho, T. H., Huber, J., Johannesson, M., Kirchler, M., Almenberg, J., Altmejd, A., Chan, T., Heikensten, E., Holzmeister, F., Imai, T., Isaksson, S., Nave, G., Pfeiffer, T., Razen, M., & Wu, H. (2016). Evaluating replicability of laboratory experiments in economics. Science 351(6280): 1433-1436.
Camerer, C. F., Dreber, A., Holzmeister, F., Ho, T. H., Huber, J., Johannesson, M., Kichler, M., Nave, G., Nosek, B. A., Pfeiffer, T., Altmejd, A., Buttrick, N., Chan, T., Chen, Y., Forsell, E., Gampa, A., Heikensten, E., Hummer, L., Imai, T., Isaksson, S., Manfredi, D., Rose, J., Wagenmakers, E.-J., & Wu, H. (2018). Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour 2(9): 637-644.
Canessa, N., Crespi, C., Motterlini, M., Baud-Bovy, G., Chierchia, G., Pantaleo, G., Tettamanti, M., & Cappa, S. F. (2013). The Functional and Structural Neural Basis of Individual Differences in Loss Aversion. Journal of Neuroscience 33(36): 14307–14317.
De Martino, B, Camerer, C. F., & Adolphs, R. (2010). Amygdala Damage Eliminates Monetary Loss Aversion. Proceedings of the National Academy of Sciences 107(8): 3788-3792.
Dreber, A., Pfeiffer, T., Almenberg, J., Isaksson, S., Wilson, B., Chen, Y., Nosek, B. A., & Johannesson, M. (2015). Using Prediction Markets to Estimate the Reproducibility of Scientific Research. Proceedings of the National Academy of Sciences 112: 15343-15347.
Tom, S. M., Fox, C. R., Trepel, C., & Poldrack, R. A. (2007). The Neural Basis of Loss Aversion in Decision-Making under Risk. Science 315(5811): 515–518.