Abdellaoui, M., Bleichrodt, H., LâHaridon, O. & van Dolder, D. Measuring loss aversion under ambiguity: a method to make prospect theory completely observable. J. Risk Uncertain. 53, 1â20 (2016).
- Bao, C. et al. The rat frontal orienting ï¬eld dynamically encodes value for economic decisions under risk. Nat. Neurosci. 26, 1942â1952 (2023).
Paper not yet in RePEc: Add citation now
Barberis, N., Huang, M. & Thaler, R. H. Individual preferences, monetary gambles, and stock market participation: a case for narrow framing. Am. Econ. Rev. 96, 1069â1090 (2006).
- Bavard, S. & Palminteri, S. The functional form of value normalization in human reinforcement learning. Elife 12, e83891 (2023).
Paper not yet in RePEc: Add citation now
- Bellemare, M. G., Dabney, W. & Munos, R. A distributional perspective on reinforcement learning. In Proceedings of the 34th International Conference on Machine Learning 449â458 (PMLR, 2017).
Paper not yet in RePEc: Add citation now
- Bhatia, S. Sequential sampling and paradoxes of risky choice. Psychon. Bull. Rev. 21, 1095â1111 (2014).
Paper not yet in RePEc: Add citation now
Brooks, P. & Zank, H. Loss averse behavior. J. Risk Uncertain. 31, 301â325 (2005).
- Bugallo, M. F. et al. Adaptive importance sampling: the past, the present, and the future. IEEE Signal Process. Mag. 34, 60â79 (2017).
Paper not yet in RePEc: Add citation now
- Burke, C. J. et al. Dopamine receptor-speciï¬c contributions to the computation of value. Neuropsychopharmacology 43, 1415â1424 (2018).
Paper not yet in RePEc: Add citation now
- Busemeyer, J. R. & Townsend, J. T. Decision ï¬eld theory: a dynamiccognitive approach to decision making in an uncertain environment. Psychol. Rev. 100, 432â459 (1993).
Paper not yet in RePEc: Add citation now
- Cannard, C., Wahbeh, H. & Delorme, A. Electroencephalography correlates of well-being using a low-cost wearable system. Front. Hum. Neurosci. 15, 745135 (2021).
Paper not yet in RePEc: Add citation now
Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1â32 (2017).
- Chang, C. C. & Lin, C. J. LIBSVM: a ary for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 27 (2011).
Paper not yet in RePEc: Add citation now
- Chen, X. & Stuphorn, V. Inactivation of medial frontal cortex changes risk preference. Curr. Biol. 28, 3709â3715.e3 (2018).
Paper not yet in RePEc: Add citation now
- Ciranka, S. & Hertwig, R. Environmental statistics and experience shape risk-taking across adolescence. Trends Cogn. Sci. 27, 1076â1091 (2023).
Paper not yet in RePEc: Add citation now
- Colvin, K. F. Kruschke, J. K. (2011). Doing Bayesian data analysis: a tutorial with R and BUGS. Burlington, MA: Academic Press. J. Educ. Meas. 50, 315â318 (2013).
Paper not yet in RePEc: Add citation now
Dabney, W. et al. A distributional code for value in dopamine-based reinforcement learning. Nature 577, 671â675 (2020).
- Ding, X. et al. Classifying major depression patients and healthy controls using EEG, eye tracking and galvanic skin response data. J. Affect. Disord. 251, 156â161 (2019).
Paper not yet in RePEc: Add citation now
- Duits, P. et al. Updated meta-analysis of classical fear conditioning in the anxiety disorders. Depress. Anxiety 32, 239â253 (2015).
Paper not yet in RePEc: Add citation now
- Eldar, E., Hauser, T. U., Dayan, P. & Dolan, R. J. Striatal structure and function predict individual biases in learning to avoid pain. Proc. Natl. Acad. Sci. USA. 113, 4812â4817 (2016).
Paper not yet in RePEc: Add citation now
- Eldar, E., Roth, C., Dayan, P. & Dolan, R. J. Decodability of reward learning signals predicts mood ï¬uctuations. Curr. Biol. 28, 1433â1439.e7 (2018).
Paper not yet in RePEc: Add citation now
- Eldar, E., Rutledge, R. B., Dolan, R. J. & Niv, Y. Mood as representation of momentum. Trends Cogn. Sci. 20, 15â24 (2016).
Paper not yet in RePEc: Add citation now
- Enisman, M. & Kleiman, T. The relative difï¬culty of resolving motivational conï¬icts is affective context-dependent. Emotion 24, 1358â1375 (2024).
Paper not yet in RePEc: Add citation now
- Enisman, M., Levy, A. & Kleiman, T. Hand movement trajectories illustrate the mechanism underlying Kurt Lewinâs distinction between approachâapproach and avoidanceâavoidance motivational conï¬icts. J. Pers. Soc. Psychol. 127, 239â258 (2024).
Paper not yet in RePEc: Add citation now
- Erdman, A. & Eldar, E. The computational psychopathology of emotion. Psychopharmacology 240, 3173â3189 (2023).
Paper not yet in RePEc: Add citation now
- Erdman, A. et al. Experience-based risk taking is primarily shaped by prior learning rather than by decision-making. https://doi.org/10. 5281/zenodo.15462472 (GitHub, 2025)
Paper not yet in RePEc: Add citation now
- Erdman, A. et al. Experience-based risk taking is primarily shaped by prior learning rather than by decision-making. ï¬gshare. Dataset. https://doi.org/10.6084/m9.ï¬gshare.28891112 (2025).
Paper not yet in RePEc: Add citation now
Gächter, S., Johnson, E. J. & Herrmann, A. Individual-level loss aversion in riskless and risky choices. Theory Decis. 92, 599â624 (2022).
- Garcia, B., Cerrotti, F. & Palminteri, S. The description-experience gap: a challenge for the neuroeconomics of decision-making under uncertainty. Philos. Trans. R. Soc. B: Biol. Sci. 376, 20190665 (2021).
Paper not yet in RePEc: Add citation now
- Gorter, J. & Schilp, P. Risk preferences over small stakes: evidence from deductible choice. SSRN. (2012).
Paper not yet in RePEc: Add citation now
- Gronau, Q. F. et al. A tutorial on bridge sampling. J. Math. Psychol. 81, 80â97 (2017).
Paper not yet in RePEc: Add citation now
- Guarniero, P., Johansen, A. M. & Lee, A. The iterated auxiliary particle ï¬lter. J. Am. Stat. Assoc. 112, 1636â1647 (2017).
Paper not yet in RePEc: Add citation now
- Hertwig, R. & Erev, I. The description-experience gap in risky choice. Trends Cogn. Sci. 13, 517â523 (2009).
Paper not yet in RePEc: Add citation now
Holt, C. A. & Laury, S. K. Risk aversion and incentive effects. Am. Econ. Rev. 92, 1644â1655 (2002).
- Hoogerheide, L., Opschoor, A. & Van Dijk, H. K. A class of adaptive importance sampling weighted EM algorithms for efï¬cient and robust posterior and predictive simulation. J. Econ. 171, 101â120 (2012).
Paper not yet in RePEc: Add citation now
Hoy, C. W. et al. Asymmetric coding of reward prediction errors in human insula and dorsomedial prefrontal cortex. Nat. Commun. 14, 8522 (2023).
- Hunkin, H., King, D. L. & Zajac, I. T. Evaluating the feasibility of a consumer-grade wearable EEG headband to aid assessment of state and trait mindfulness. J. Clin. Psychol. 77, 2777â2797 (2021).
Paper not yet in RePEc: Add citation now
- Huys, Q. J. M. et al. Bonsai trees in your head: How the pavlovian system sculpts goal-directed choices by pruning decision trees. PLoS Comput. Biol. 8, e1002410 (2012).
Paper not yet in RePEc: Add citation now
- Hyman, S. E., Malenka, R. C. & Nestler, E. J. Neural mechanisms of addiction: the role of reward-related learning and memory. Annu. Rev. Neurosci. 29, 565â598 (2006).
Paper not yet in RePEc: Add citation now
- Jaskir, A. & Frank, M. J. On the normative advantages of dopamine and striatal opponency for learning and choice. Elife 12, e85107 (2023).
Paper not yet in RePEc: Add citation now
- Kacelnik, A. & Bateson, M. Risky theories - The effects of variance on foraging decisions. Am. Zool. 36, 402â434 (1996).
Paper not yet in RePEc: Add citation now
Kahneman, D. & Tversky, A. An analysis of decision under risk. Econometrica 47, 263â291 (1979).
Kontek, K. & Lewandowski, M. Range-dependent utility. Manag. Sci. 64, 2812â2832 (2018).
- Krigolson, O. E. et al. Using Muse: rapid mobile assessment of brain performance. Front. Neurosci. 15, 634147 (2021).
Paper not yet in RePEc: Add citation now
- Krigolson, O. E., Williams, C. C., Norton, A., Hassall, C. D. & Colino, F. L. Choosing MUSE: validation of a low-cost, portable EEG system for ERP research. Front. Neurosci. 11, 109 (2017).
Paper not yet in RePEc: Add citation now
- Levy, A., Enisman, M., Perry, A. & Kleiman, T. Midfrontal theta as an index of conï¬ict strength in approach-approach vs avoidanceavoidance conï¬icts. Soc. Cogn. Affect. Neurosci. 18, nsad038 (2023).
Paper not yet in RePEc: Add citation now
- Lowet, A. S., Zheng, Q., Matias, S., Drugowitsch, J. & Uchida, N. Distributional reinforcement learning in the brain. Trends Neurosci. 43, 980â997 (2020).
Paper not yet in RePEc: Add citation now
- MacLean, R. R., Pincus, A. L., Smyth, J. M., Geier, C. F. & Wilson, S. J. Extending the balloon analogue risk task to assess naturalistic risk taking via a mobile platform. J. Psychopathol. Behav. Assess. 40, 107â116 (2018).
Paper not yet in RePEc: Add citation now
Markowitz, H. The utility of wealth. J. Polit. Econ. 60, 151â158 (1952).
- Mason, L., Eldar, E. & Rutledge, R. B. Mood instability and reward dysregulation-a neurocomputational model of bipolar disorder. JAMA Psychiatry 74, 1275â1276 (2017).
Paper not yet in RePEc: Add citation now
- Meertens, R. M. & Lion, R. Measuring an individualâs tendency to take risks: the risk propensity scale. J. Appl. Soc. Psychol. 38, 1506â1520 (2008).
Paper not yet in RePEc: Add citation now
Meier, A. N. Emotions and risk attitudesâ . Am. Econ. J. Appl. Econ. 14, 54â84 (2022).
- Michely, J., Eldar, E., Erdman, A., Martin, I. M. & Dolan, R. J. Serotonin modulates asymmetric learning from reward and punishment in healthy human volunteers. Commun. Biol. 5, 968 (2022). Article https://doi.org/10.1038/s41467-025-61609-0 Nature Communications| (2025)16:6310 46. Harmer, C. J., Goodwin, G. M. & Cowen, P. J. Why do antidepressants take so long to work? A cognitive neuropsychological model of antidepressant drug action. Br. J. Psychiatry 195, 102â108 (2009).
Paper not yet in RePEc: Add citation now
Michely, J., Eldar, E., Martin, I. M. & Dolan, R. J. A mechanistic account of serotoninâs impact on mood. Nat. Commun. 11, 2335 (2020).
- Mishra, S. & Lalumière, M. L. Individual differences in risk-propensity: associations between personality and behavioral measures of risk. Pers. Individ. Dif. 50, 869â873 (2011).
Paper not yet in RePEc: Add citation now
- Moeller, M., Grohn, J., Manohar, S. & Bogacz, R. An association between prediction errors and risk-seeking: theory and behavioral evidence. PLoS Comput. Biol. 17, e1009213 (2021).
Paper not yet in RePEc: Add citation now
- Niv, Y., Edlund, J. A., Dayan, P. & OâDoherty, J. P. Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain. J. Neurosci. 32, 551â562 (2012).
Paper not yet in RePEc: Add citation now
- Oba, T., Katahira, K. & Ohira, H. A learning mechanism shaping risk preferences and a preliminary test of its relationship with psychopathic traits. Sci. Rep. 11, 20844 (2021).
Paper not yet in RePEc: Add citation now
- Platt, M. L. & Huettel, S. A. Risky business: the neuroeconomics of decision making under uncertainty. Nat. Neurosci. 11, 398â403 (2008).
Paper not yet in RePEc: Add citation now
- Potenza, M. N. et al. Gambling disorder. Nat. Rev. Dis. Prim. 5, 51 (2019).
Paper not yet in RePEc: Add citation now
- Schölkopf, B., Smola, A. J., Williamson, R. C. & Bartlett, P. L. New support vector algorithms. Neural Comput. 12, 1207â1245 (2000).
Paper not yet in RePEc: Add citation now
- Schaffarczyk, M., Rogers, B., Reer, R. & Gronwald, T. Validity of the polar H10 sensor for heart rate variability analysis during resting state and incremental exercise in recreational men and women. Sensors 22, 6536 (2022).
Paper not yet in RePEc: Add citation now
- Sidelinger, L., Zhang, M., Frohlich, F. & Daughters, S. B. Day-to-day individual alpha frequency variability measured by a mobile EEG device relates to anxiety. Eur. J. Neurosci. 57, 4101â4115 (2023).
Paper not yet in RePEc: Add citation now
- Solomyak, L., Sharp, P. B. & Eldar, E. Training diversity promotes absolute-value-guided choice. PLoS Comput. Biol. 18, e1010664 (2022).
Paper not yet in RePEc: Add citation now
- Treloar Padovano, H., Janssen, T., Emery, N. N., Carpenter, R. W. & Miranda, R. Risk-taking propensity, affect, and alcohol craving in adolescentsâ daily lives. Subst. Use Misuse 54, 1365â1375 (2019).
Paper not yet in RePEc: Add citation now
- Wang, Z., Bovik, A. C., Sheikh, H. R. & Simoncelli, E. P. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13, 600â612 (2004).
Paper not yet in RePEc: Add citation now
Weber, B. J. & Chapman, G. B. Playing for peanuts: why is risk seeking more common for low-stakes gambles? Organ. Behav. Hum. Decis. Process. 97, 31â46 (2005).
- Wulff, D. U., Mergenthaler-Canseco, M. & Hertwig, R. A metaanalytic review of two modes of learning and the descriptionexperience gap. Psychol. Bull. 144, 140â176 (2018).
Paper not yet in RePEc: Add citation now
- Yang, J. H. & Liao, R. M. Dissociable contribution of nucleus accumbens and dorsolateral striatum to the acquisition of risk choice behavior in the rat.Neurobiol. Learn. Mem. 126, 67â77 (2015).
Paper not yet in RePEc: Add citation now
Zalocusky, K. A. et al. Nucleus accumbens D2R cells signal prior outcomes and control risky decision-making. Nature 531, 642â646 (2016).