A new functional brain-age clock is attempting to measure how well the brain is aging and whether interventions can change its trajectory.
What if your brain could have its own biological age and, more importantly, what if that number could change?
That is the question behind Brain Years, a functional brain-age model developed through a collaboration between neurotechnology company Sens.ai and the Buck Institute for Research on Aging. Rather than looking only at the brain’s structure, the approach asks a more practical question: how well is the brain actually functioning? It is an important distinction. An MRI can show what the brain looks like. A functional assessment tries to understand what it can do.
For Dr Eric Verdin, president and CEO of the Buck Institute, that distinction is central to the wider problem of measuring aging. Traditional medicine tends to tell us whether a measurement falls inside a normal range. Aging science is increasingly interested in something more dynamic: where a person is heading.
“If you’re in the normal range, you know, there’s no taking into account of the trajectory and how close you are to becoming abnormal,” Verdin explains on the latest episode of Longevity.Technology UNLOCKED. That idea of trajectory sits at the heart of Brain Years.
Turning brain signals into a number
Sens.ai CEO Paola Telfer and her team spent years collecting EEG and performance data from users in real-world settings, rather than relying solely on tightly controlled laboratory conditions. That created a different kind of challenge. Before AI could make sense of the data, the company needed to make sure the data itself was worth trusting.
“We knew that it’s garbage in, garbage out with AI,” Telfer says.
The company developed its own sensors and refined the system to detect when the signal might be compromised; for example, if someone is moving, chewing gum, talking or blinking excessively. The resulting dataset spans people from their early teens to their late 80s. But the real work began after the data had been collected.
The Brain Years model examines hundreds of variables derived from EEG, event-related potentials and performance during standardized tasks. Rather than deciding in advance that one particular brain signal must be the answer, the researchers used machine learning to determine which combinations were most strongly associated with chronological age and functional capacity. The result is a score intended to describe functional brain age relative to chronological age. Think of it less like an odometer and more like a weather forecast. Your chronological age tells you how long you have been alive; a brain-age clock attempts to provide another view of where your brain currently sits and potentially where it is going.
The harder question: can the clock move?
This is where the story becomes more interesting. A clock that merely tells you that your brain is older or younger than expected could be useful, but it would remain largely descriptive. The bigger promise is whether the measurement can track changes following an intervention.
Early data from Sens.ai and the Buck Institute suggests there may be something worth investigating. Telfer says an intervention study showed “5.18 years of reversal on the Brain Years measure after a two-month intervention.” But Verdin is careful about what that means.
“You’ll never hear me claiming that we’ve reverted aging,” he says. The next step, he argues, is a properly designed prospective, placebo-controlled trial that can establish whether the change represents a genuine alteration in brain aging rather than simply an improvement in test performance. That caution matters. An aging clock is ultimately a model built from measurements. If the number changes, the crucial question is whether biology changed with it.
The researchers also want to compare Brain Years with other approaches, including MRI-based clocks and blood-based proteomic measures. In other words, the future may not belong to one definitive aging clock, but to several imperfect windows that collectively give us a clearer picture.
From dementia prevention to everyday brain health
There is also something quietly radical about starting the conversation before dementia. Brain aging is often discussed as though it begins when cognitive decline becomes clinically obvious. Telfer argues for a much earlier intervention point, encompassing issues such as attention, anxiety and burnout. And that opens up a different vision of longevity medicine: not waiting for the brain to fail before measuring it, but tracking function while there is still plenty of room to intervene.
Sens.ai’s commercial path is increasingly focused on clinics, where Telfer sees the technology as a more portable and repeatable complement to expensive imaging and specialist interpretation. Verdin, meanwhile, places it within what he calls “Scientific wellness” – consumer-facing interventions subjected to the kind of scientific rigor usually associated with medicine.
That middle ground could prove important. Longevity has never suffered from a shortage of things people can buy. What it has lacked is reliable ways to determine whether those things work.
The promise of a functional brain clock, then, is not really the number itself. It is the possibility of turning brain health from something we periodically worry about into something we can measure, follow and potentially improve, while there is still time to do something about it.
Longevity.Technology UNLOCKED returns every Monday with conversations about the science, technology and ideas reshaping how we age. Catch the latest episode on Apple Podcasts, Spotify and YouTube, with our weekly longevity news roundup landing every Friday.
