Black brain engraving drawing front view isolated on yellow orange background

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I’m on a “quest for brain identifiability”

Enrico Amico, EPFL
pick your brain

"Brain prints" reveal how your mind changes over time

Scientists have just learned more about a new, unique biometric: the brain print. Like a fingerprint, neural patterns reveal we all have unique brains.

It’s a cruel fact of life that we’re really not as unique as we think we are — apart from one crucial exception: the tiny ridges of our fingertips.

Discovered by physician Marcello Malpighi in the 17th century, the topographical pattern of ridges and sweat glands found on each person's fingertips are an identifier unlike any other. No matter what disguise you don or transformation you undergo, these tiny prints can find you in a crowd.

Now scientists have identified a new unique identifier that can help them better understand where the “self” originates and even track the progression of disease: the brain print.

At first glance, human brains look remarkably similar. Dual hemisphere-d and undulating with fleshy folds, picking your brain out of a line-up would be a difficult task. However, if you look deeper at the neural networks built into these brains — called connectomes — you’ll find something quite different, Ecole Polytechnique Fédérale de Lausanne computational neuroscientist Enrico Amico says.

“Identification [can be] made solely on their functional connectomes, which are essentially sets of numbers, a summary of brain activity,” Amico tells Inverse. “And yet, there is a “fingerprint” in these numbers that allows [us] to identify my brain from yours.”

These unique networks are represented as colorful matrixes and are unique for each brain, Amico says. He details his findings in a paper published Friday in Science Advances on this topic.

Could you pick your brain out of a lineup? Using a “brain print,” you might be able to.

Enrico Amico

“That is why I got interested in this concept: I wanted to dig deeper into what makes our brains unique,” Amico continues. “I started [a] ‘quest for brain identifiability.’”

What’s new — Researchers at Yale University began studying these connection points several years ago and found that someone could identify an individual from these brain prints alone with 95 percent accuracy. However, most of this work focused on comparing fMRI data that had been collected over a long period of time.

For Amico and his team, this raised several questions, namely: How might time impact these results?

“It has been shown that over months, even years, brain fingerprints are quite stable,” Amico says. “They may, however, fluctuate at shorter time scales, i.e., during our time in the scanner.”

For Amico, this raised questions such as “when do brain prints actually appear” and ‘do different areas of the brain appear at different moments’?

“Nobody knew the answer,” Amico says.

Scientists have known for centuries that our fingerprints are unique. Now, we’re learning how a “brain print” might be as well.

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Why it matters — These brain prints are unlikely to morph into a Black Mirror-esque horror in the near future, Amico avows, but they could serve a crucial role in helping scientists better understand neurological diseases like Alzheimer's.

“Based on my initial findings, it seems that the features that make a brain fingerprint unique steadily disappear as the disease progresses,” Amico says. “It gets harder to identify people based on their connectomes. It’s as if a person with Alzheimer’s loses his or her brain identity.”

Identification of these brain print changes could lead to early detection of such neurodegenerative diseases.

What they did — To better understand how our brain prints morph and change, Amico and colleagues studied the fMRI data of 100 different participants in a resting state. Crucially, instead of collecting this data for five minutes or more, the team looked at only 1 minute and 40 seconds of neural activity.

Not only did the team find that brain prints could be recorded in under two minutes, but they noticed that different parts of the brain demonstrated “bursts of identifiability” at different times. The brain’s more primitive sensory areas, for example, were the first to be identifiable. This includes parts of the brain responsible for visual and spatial attention.

Interestingly, the brain’s frontal cortex — which is associated with higher-order cognitive functions — was last to appear.

What’s next — While there is something poetic about learning your brain is identifiably unique, Amico admits that there is potential to abuse this brain print in the wrong hands — think police surveillance in Minority Report. Luckily, this possibility is still unlikely at this point.

“In theory, yes, if you had a connectome database for every brain on the planet, it should be possible to track and identify people based on their brain scan,” Amico says. “This technique [going] into the wrong hands is a scary thought.”

Your brain print could one day be used against you if we’re not careful.

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For now though, Amico says his lab is focused on the medical benefits of these brain prints. Beyond Alzheimer’s, researchers could use these prints to study the brain activity of stroke patients and those with drug addictions.

“The quest for brain fingerprints has just started, and its potential is limitless: this is just one small step towards understanding what and when makes our brain unique,” he says.

Abstract: The extraction of “fingerprints” from human brain connectivity data has become a new frontier in neuroscience. However, the time scales of human brain identifiability are still largely unexplored. We here investigate the dynamics of brain fingerprints along two complementary axes: (i) What is the optimal time scale at which brain fingerprints integrate information and (ii) when best identification happens. Using dynamic identifiability, we show that the best identification emerges at longer time scales; however, short transient “bursts of identifiability,” associated with neuronal activity, persist even when looking at shorter functional interactions. Furthermore, we report evidence that different parts of connectome fingerprints relate to different time scales, i.e., more visual-somatomotor at short temporal windows and more frontoparietal-DMN driven at increasing temporal windows. Last, different cognitive functions appear to be meta-analytically implicated in dynamic fingerprints across time scales. We hope that this investigation will advance our understanding of what makes our brains unique.
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