A new study published in Nature Neuroscience has led to the development of a method of distinguishing individuals based on their unique brain activity, or "brainprints," with up to 99 percent accuracy, according to Scientific American.
The technique uses functional connectivity MRI (fcMRI) to take tiny images of areas of the brain where activity is synchronized, and group them into different categories called nodes. Afterwards, the researchers compare the activity levels in each node and determine how well each node is connected.
"Functional connectivity profiles act as a 'fingerprint' that can accurately identify subjects from a large group," the researchers wrote in the paper.
The results were even able to help the researchers predict how well individuals perform on intelligence tests, according to Sputnik International.
Despite the effectiveness of the technique in identifying people based on their brain activity, the researchers don't expect it to be used for this purpose.
"We don't need to put people in a scanner to know who they are," said Emily Finn, lead researcher of the study. "We can identify people by looking at them or fingerprinting them."
"It's just a proof of principle to show there's sufficient information in these scans to tell the difference between people," said Xilin Shen, co-author of the study. "Starting to focus on individuals is a fantastic idea, that's really going to be the future."
The researchers are hoping that the data will help diagnose people who have or are more susceptible to developing brain disease, according to the States Chronicle.