Study hints at fingerprints for the brain

Great minds think alike, the saying goes. But a new study by School of Medicine researchers suggests something else: every mind thinks a bit differently. A team led by R. Todd Constable, Ph.D., professor of radiology and biomedical imaging, has discovered that subtle individual variations in brain function define one-of-a-kind “fingerprints” that distinguish one person from another.

Constable and colleagues constructed diagrams using data from functional magnetic resonance imaging (fMRI), a non-invasive technique that detects brain activity. The data indicated which parts of the brain were effective in tandem at any given time, and the connectivity patterns turned out to be highly distinctive.

“That was an unexpected finding, just how unique these brain systems are,” Constable says. The differences were apparent even between identical twins, he says. The results were published in Nature Neuroscience in October.

In the study, two Constable lab members, neuroscience graduate student Emily Finn and Xilin Shen, Ph.D., associate research scientist, analyzed fMRI data from 126 healthy young adults who were scanned multiple times over 2 days. By measuring the strength of more than 35,000 connections between 268 different brain regions, Finn and Shen produced what they call connectivity profiles for each person in the study. The surprise came when they compared all those profiles: they found that each was different enough that they could identify with confidence any one person based solely on the person’s profile. The profiles identified people consistently, even when the scans were done on different days or while subjects were doing some kind of mental task, rather than just resting in the scanner.

The connectivity profiles were not just unique: they were also informative. The researchers found connectivity fingerprints that tracked how people scored on a test of fluid intelligence, the type of brainpower used for on-the-spot problem solving. “It’s not just that everyone has a different pattern of these connections, but also that they are relevant to some kind of real world output of the brain,” Finn says.

In a second study, also published in Nature Neuroscience, Finn and psychology graduate student Monica Rosenberg teamed up to apply the same profiling approach to look at a different cognitive ability, the capacity for sustained attention. They found a set of brain connections associated with high or low performance on an attention test among Yale student volunteers. Then, they showed that the same fMRI-based profile could predict the presence and severity of symptoms of attention deficit hyperactivity disorder (ADHD) in adults and children in China, who were scanned completely independently.

Finn says she is interested in whether the connectivity profiles might be useful to predict something even harder to measure than intelligence or attention, like the risk of future disease or the trajectory of disease. She says she and her colleagues are now looking at another set of scans from people at high risk of developing schizophrenia. “They were scanned before they developed the full blown illness, and we are asking if we can use connectivity profiles to predict who went on to develop the illness,” Finn says.

One open question is whether a person’s connectivity fingerprint is fixed, or whether it could change over time. “We do know that connectivity patterns change a lot through development and as a function of age,” Constable says. “But would your pattern change enough so that we could no longer identify you? We don’t know that yet.”