Traditional economic theory assumes that human beings behave rationally. That is, that they understand their own preferences, make perfectly consistent choices over time, and try to maximize their own well-being. This peculiar assumption has its roots in dusty essays like "Exposition of a New Theory on the Measurement of Risk" (from 1738) by Daniel Bernoulli and scholarly tomes like Theory of Games and Economic Behavior by John von Neumann and Oskar Morgenstern (published in 1944). The idea has some validity: traditional economic theory is good at predicting some market behaviors, such as how the demand for products like gasoline will change after a tax hike. But it's not very good at describing more-complex phenomena like stock-price fluctuations or why people gamble against the odds.

The problem, of course, is that people don't always behave rationally. They make decisions based on fear, greed, and envy. They buy plasma TVs and luxury vehicles they can't afford. They don't save enough for retirement. They indulge in risky behavior such as gambling. Economists understand this as well as anyone, but in order to keep their mathematical models tractable, they make simplifying assumptions. Then they try to adjust their equations by adding terms that account for "irrational" behavior. But if economists could develop models that accounted for the subtleties of the human brain, they might be able to predict complex behaviors more accurately. This, in turn, might have any number of practical applications: investment bankers could hedge against financial euphoria like the Internet boom; advertisers could sell products more winningly.