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Brain activity can serve as unique identifier, says study

Categories Biometric R&D  |  Biometrics News

A team of researchers at Yale University have discovered that images of brain activity scanned by using functional magnetic resonance imaging (fMRI) can act as a signature pattern to accurately identify certain individuals, according to a report by The Conversation.

Published in the journal Nature Neuroscience, the study details a technique that measures neural activity via blood flow in the brain while people are awake and mentally active.

“In most past studies, fMRI data have been used to draw contrasts between, say, patients and healthy controls,” said Emily S Finn, PhD Candidate in Neuroscience at Yale University and co-author of the study. “We have learned a lot from these sorts of studies, but they tend to obscure individual differences which may be important.”

Finn and her team analyzed hundreds of fMRI image scans taken of 126 participants supplied by the Human Connectome Project, where they were able to successfully identify individuals based on their ‘connectivity profile’.

The team looked at activity across 268 different regions in the brain by scanning each participant six times.

During certain sessions, the researchers asked participants to perform a cognitive task during the fMRI scan, while in other sessions, participants remained at rest during the scan.

Based on these tests, the researchers were able to identify individual participants with up to 99 percent accuracy when comparing scans of the same individual conducting a similar cognitive task.

However, their accuracy rate dropped to approximately 80 percent if the scan showed the same individual performing a disparate task or being at rest.

“Until this, we really didn’t know the extent to which each unique individual has a unique pattern of connectivity,” said Russell Poldrack, a cognitive neuroscientist at Stanford University and advisor to the Human Connectome Project.

Aside from simply identifying an individual, the study also proves that brain activity can serve as subtle clues about an individual’s level of intelligence.

Although the fMRI data itself doesn’t simply indicate someone’s intelligence, connectivity patterns in brain activity show a correlation as to how well people perform in an intelligence test, said the researchers.

“[T]he uniqueness seems to be tied to cognitive function in some way,” said Poldrack, adding that stronger connections found in participants’ prefrontal and parietal lobes correlate to higher intelligence test scores.

The team hopes that these connectivity profiles could be used at some point in the future in personalized medicine as a method of customizing interventions and therapies for people based on their unique connectivity profile.

“We have hundreds of drugs for treating neuropsychiatric illness, but there’s still a lot of trial and error and failed treatments,” said Finn. “This might be another tool.”

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