A few months ago, when it looked as if the financial maelstrom had mostly passed – after the Bear Stearns bailout, things calmed down – I decided to write an article about Read Montague and the weird habits of dopamine neurons. While these brain cells are often used to explain the computation of rewards, until I visited Montague’s lab I had no idea that dopamine neurons could also help explain the perpetual cycle of boom and bust on Wall Street.
The experiment went like this: Each subject was given $100 and some basic information about the “current” state of the stock market. After choosing how much money to invest, the players watched nervously as their investments either rose or fell in value. The game continued for 20 rounds, and the subjects got to keep their earnings. One interesting twist was that instead of using random simulations of the stock market, Montague relied on distillations of data from famous historical markets. Montague had people “play” the Dow of 1929, the Nasdaq of 1998, and the S&P 500 of 1987, so the neural responses of investors reflected real-life bubbles and crashes.
The scientists immediately discovered a strong neural signal that drove many of the investment decisions. The signal was fictive learning. Take, for example, this situation. A player has decided to wager 10 percent of her total portfolio in the market, which is a rather small bet. Then she watches as the market rises dramatically in value. At this point, the regret signal in the brain — a swell of activity in the ventral caudate, a reward area rich in dopamine neurons — lights up. While people enjoy their earnings, their brain is fixated on the profits they missed, figuring out the difference between the actual return and the best return “that could have been.” The more we regret a decision, the more likely we are to do something different the next time around. As a result investors in the experiment naturally adapted their investments to the ebb and flow of the market. When markets were booming, as in the Nasdaq bubble of the late 1990s, people perpetually increased their investments.
But fictive learning isn’t always adaptive. Montague argues that these computational signals are also a main cause of financial bubbles. When the market keeps going up, people are naturally inclined to make larger and larger investments in the boom. And then, just when investors are most convinced that the bubble isn’t a bubble — many of Montague’s subjects eventually put all of their money into the booming market — the bubble bursts. The Dow sinks, the Nasdaq collapses. At this point investors race to dump any assets that are declining in value, as their brain realizes that it made some very expensive prediction errors. That’s when you get a financial panic.
For years, Wall Street assumed that the mortgage securities bought by the big financial firms were virtually risk-free. That assumption, of course, was completely wrong. What we’re seeing now on Wall Street is the emotion of regret running rampant, as everyone wonders what other “risk-free” investments are about to implode. A financial panic is just the after-effect of a costly dopaminergic prediction error.