Skip to Content

An Old Head May Not Be Wiser

Brain imaging and economic research suggest that older people make less predictable decisions about money.
December 15, 2010

The common perception is that older people are more conservative investors than their younger counterparts. But brain imaging studies combined with economic analysis are causing neuroscientists to question that idea. Recent research suggests that sometimes older people make riskier and less logical investment decisions than younger people, and that specific changes in the brain associated with aging may underlie those decisions.

Financial gambles: Certain parts of the brain (highlighted in yellow) are more variable, or “noisy,” in older adults making investment decisions.

A better understanding of these changes could help scientists figure out what forms of information are most useful to older people seeking to make sound financial decisions—an issue that could soon have a greater social impact than ever before.

“Huge demographic changes are taking place all over the world,” says Gregory Samanez Larkin, a postdoctoral researcher at Vanderbilt University and codirector of the Scientific Research Network on Decision Neuroscience and Aging, a multidisciplinary, multi-center effort funded by the National Institute on Aging. “Very soon there will be a much larger percentage of people over age 65, and that has economic implications.” Financial regulatory agencies are interested in the research, says Larkin, and are funding neuroscientists as they seek ways to help older people make better investment decisions.

“The natural idea is that older people are more risk-averse, but they are not uniformly more risk-averse. In some cases, they are more risk-seeking,” says Scott Huettel, codirector of the Center for Neuroeconomic Studies at Duke University.

Economic literature over the last five to 10 years suggests that older people’s investments on average tend to perform poorly relative to the risk they are taking on. “They don’t make as good decisions and don’t use the information as well,” says Huettel.

Larkin, Huettel, and others are combining brain imaging and traditional economic theory to understand the physiological changes responsible for these trends. The brain tends to shrink with age, and certain cognitive functions, such as working memory—the ability to hold information in the brain for a short time—decline. “But we are learning that is just a part of making financial decisions, and it may not even be the deciding factor,” says Brian Knutson, assistant professor of psychology and neuroscience at Stanford University.

In an experiment published earlier this year, Knutson and Larken asked people of varying ages to pick stocks while lying in a magnetic resonance brain scanner. Participants got feedback on the stocks’ performance throughout the task. The researchers knew from previous research that a certain part of the brain called the nucleus accumbens is more active when people anticipate making money or taking a financial risk. Another part is more active when they anticipate losing money or avoiding a risk.

When the researchers compared participants’ performance with a mathematical model designed to maximize economic gains, they found that older people’s performance deviated more from the model. The activity in the older group’s nucleus accumbens was also more variable. “That noisiness could account for the random stock picking,” says Knutson. In fact, the individuals whose brain activity was the noisiest—those whose nucleus accumbens varied most with respect to anticipation of a reward—made the most serious investment mistakes.

Researchers point out that the noisy brain activity was specific to that part of the brain. “It’s not kind of profile you think you’d see if someone had dementia or couldn’t remember things,” says Knutson. (They also emphasize that the participants were not investment professionals; the study was designed to assess the behavior of people who are relatively naive about investments and lack the aid of an adviser. So there’s no need to switch to a younger financial planner, they say.)

The next step is to use these basic findings to try to improve decision-making. “To make this line of research relevant, we have to turn it into some kind of application,” says Hauke Heekeren, a neuroscientist at the Max Planck Institute for Human Development. “We would want to know whether we have to use a different format to deliver information about insurance or ways to allocate retirement savings to get the same quality of decision.”

In a follow-up experiment to be published in January 2011, Larkin and collaborators did present information in different formats. “The noisy brain activity suggests that the representation of the value of these options in the brain is noisy,” says Larkin. “That means the way people are updating this information is imprecise, and they are carrying this forward [into the next round of calculations].”

In the follow-up study, researchers showed participants either a line graph of the history of a stock’s performance or a gauge that integrated the stock’s past performance. Both visual aids obviate the need to keep mental track of the stock’s performance.

“Both of these things worked better than what we did before,” resulting in more successful investment decisions, says Larkin. With the added information, older people performed just as well as younger people who were given the original task. (However, younger people still outperformed their senior counterparts when given the same historical information.)

Larkin now hopes to figure out how to use the research more directly. He recently won a grant from the Financial Industry Regulatory Authority (FINRA), the largest independent regulator of securities firms doing business in the United States, to study victims of investment fraud who are older than 55. The FINRA has a number of ongoing fraud-prevention programs, and, Larkin says, “we hope this research will help tailor some of these prevention programs.”

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.