cognitIoN AND BEHAVIOR tion of regions 33.H.C SPECI e28135021 d1.4 34 072 D.Y.von Cremon.Neuroad.23. mann,R.J Dolar 7.M 36. wen I.W.Robbins. d MG.H Coles,PsychoL Rev.109.679 a 8 and les y2器0rnJDcohenPrhopbr igna J.Comp.Neure 25% 25.8 银the 38 a.11.1011 10.H.G B Brocks.Lett.70 Exp. tpre-as Fieh 13 C.B.Holr M G Neurosdi.3.$16 Ed.(C d.N 14 E.Meyer 5d485199 401-42 20 23T (2002 242002 25E1 i24167 。 19. s1 (2 20. 41.473(2004 h Fo () the th 29. d16 linto the 32.JG.Kerns et al.Science 303,1023 (2004) REVIEW Neuroeconomics:The Consilience of Brain and Decision Paul W.Glimcher1*and Aldo Rustichini? prmeactooe,ndn ce are c is the emerging fiel neu csin which c nce the to be mists and ps are or amount of that win sses that cor ect sensation and action by mec by which Expected value=(0.5×2)+(0.25×4) nt develop- (0.125×8). =1+1+1+ The full unde f utility wil needed to fashion mo come from biology and psycho ogy by as it was in behavior follov wed by a bottom ses that upgraded thesocial science is willing to ould this Consider the famous St.Petersburg para must begin with a set of assu mptions that ome conomists USA. New York University explain this behavio e ends tail and the ease lin hut rather grow ersity of M USA esota.Minneapolis.MN 55455 but ne vly as amo should be addn thtoss is the first to land heads up.you get of a given amount might be a power function VOL 306 15 OCTOBER 2004 4474. S. Ito, V. Stuphorn, J. W. Brown, J. D. Schall, Science 302, 120 (2003). 5. K. Shima, J. Tanji, Science 282, 1335 (1998). 6. J. O’Doherty, M. L. Kringelbach, E. T. Rolls, J. Hornak, C. Andrews, Nature Neurosci. 4, 95 (2001). 7. M. Ullsperger, D. Y. von Cramon, J. Neurosci. 23, 4308 (2003). 8. C. B. Holroyd, M. G. H. Coles, Psychol. Rev. 109, 679 (2002). 9. C. B. Holroyd, J. T. Larsen, J. D. Cohen, Psychophys￾iology 41, 245 (2004). 10. H. Gemba, K. Sasaki, V. B. Brooks, Neurosci. Lett. 70, 223 (1986). 11. M. Ullsperger, D. Y. Von Cramon, Cortex, in press. 12. N. Picard, P. L. Strick, Cereb. Cortex 6, 342 (1996). 13. C. B. Holroyd, S. Nieuwenhuis, R. B. Mars, M. G. H. 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This research was supported by a TALENT grant (E.A.C.) and a VENI grant (S.N.) of the Netherlands Organization for Scientific Research and by the Priority Program Executive Functions of the German Research Foundation (M.U.). Helpful comments by S. Bunge are gratefully acknowledged. Supporting Online Material www.sciencemag.org/cgi/content/full/306/5695/443/ DC1 Materials and Methods Table S1 References REVIEW Neuroeconomics: The Consilience of Brain and Decision Paul W. Glimcher1* and Aldo Rustichini2 Economics, psychology, and neuroscience are converging today into a single, unified discipline with the ultimate aim of providing a single, general theory of human behavior. This is the emerging field of neuroeconomics in which consilience, the accordance of two or more inductions drawn from different groups of phenomena, seems to be operating. Economists and psychologists are providing rich conceptual tools for understanding and modeling behavior, while neurobiologists provide tools for the study of mechanism. The goal of this discipline is thus to understand the processes that connect sensation and action by revealing the neurobiological mechanisms by which decisions are made. This review describes recent develop￾ments in neuroeconomics from both behavioral and biological perspectives. The full understanding of utility will come from biology and psychology by reduction to the elements of human behavior followed by a bottom-up synthesis, not from the social sciences by top-down inference and guesswork based on intuitive knowledge. It is in biology and psychology that econo￾mists and social scientists will find the premises needed to fashion more predictive models, just as it was in physics and chemistry that research￾ers found the premises that upgraded biology. (p. 206) (1) Consider the famous St. Petersburg para￾dox (2). Which of the following would you prefer, /40 or a lottery ticket that pays according to the outcomes of one or more fair coin tosses: heads you get /2 and the game ends, tails you get another toss and the game repeats, but now if the second toss lands heads up you get /4, and so on. If the nth toss is the first to land heads up, you get 2n dollars. The game continues, however long it takes, until the coin lands heads up. We can assess the average objective, or expected, value of this lottery by multiplying the probability of a win on each flip by the amount of that win: Expected value 0 ð0:5 2Þþð0:25 4Þ þ ð0:125 8ÞI 0 1 þ 1 þ 1 þ I This simple calculation reveals that the expected value of the lottery is infinite even though the average person is willing to pay less than /40 to play it. How could this be? For an economist, any useful explanation must begin with a set of assumptions that renders behavior formally tractable to coher￾ent theoretical and mathematical analysis. Economists therefore explain this behavior by assuming that the desirability of money does not increase linearly, but rather grows more and more slowly as the total amount at stake increases. For example, the desirability of a given amount might be a power function 1 Center for Neural Science, New York University, New York, NY 10003, USA. 2 Department of Econom￾ics, University of Minnesota, Minneapolis, MN 55455, USA. *To whom correspondence should be addressed. E-mail: glimcher@cns.nyu.edu C OGNITION AND B EHAVIOR www.sciencemag.org SCIENCE VOL 306 15 OCTOBER 2004 447 S PECIAL S ECTION