How a Focus on Rich Educated People Skews Brain Studies
Neuroimaging studies have traditionally scanned a thin and unrepresentative slice of humanity—but that’s changing.
Ed Yong, The Atlantic
Oct 31, 2017
In 1986, the social psychologist David Sears warned his colleaguesthat their habit of almost exclusively studying college students was producing a strange and skewed portrait of human nature. He was neither the first to make that critique, nor the last: Decades later, other psychologists noted that social sciences tended to focus on people from WEIRD societies—that is, Western, educated, industrialized, rich, and democratic. The results of such studies are often taken to represent humanity at large, even though their participants are drawn from a “particularly thin and rather unusual slice” of it.
The same concerns have been raised in virtually every area of science that involves people. Geneticists have learned more about the DNA of people in Europe and North America than those in the rest of the world, where the greatest genetic diversity exists. The so-called Human Microbiome Project was really the Urban-American Microbiome Project, given that its participants were almost entirely from St. Louis and Houston.
Neuroscience faces the same problems. When scientists use medical scanners to repeatedly peer at the shapes and activities of the human brain, those brains tend to belong to wealthy and well-educated people. And unless researchers take steps to correct for that bias, what we get is an understanding of the brain that’s incomplete, skewed, and, well, a little weird.
Kaja LeWinn, from the University of California, San Francisco, demonstrated this by reanalyzing data from a large study that scanned 1,162 children ages 3 to 18 to see how their brain changed as they grew up. The kids came from disproportionately wealthy and well-educated families, so LeWinn adjusted the data to see what it would look like if they had been more representative of the U.S. population. That's called “weighting,” and it’s a common strategy that epidemiologists use to deal with skews in their samples. As an easy example, if you ended up recruiting twice as many boys as girls, you’d assign the girls twice as much “weight” as the boys.
When LeWinn weighted her data for factors such as sex, ethnicity, and wealth, the results looked very different from the original set. The brain as a whole developed faster than previously thought, and some parts matured earlier relative to others.
Natalie Brito, from New York University, says that this study “clearly shows how our interpretation of brain development changes based off who is being represented within the sample.” She adds that most neuroscientists would acknowledge or agree that representative samples are a good thing, but that there practical reasons why such samples are hard to get. Most obviously, brain-scanning studies are very expensive, so most of them are small and rely on “samples of convenience”—that is, whoever’s easiest to recruit.