The nursing home operator runs brain health programs for hundreds of residents and still can’t say for sure which ones are actually improving. The rehabilitation provider clears the patient to return to activity based on symptoms, not whether the underlying deficit has actually resolved. The sports organization has to decide, in real time, whether an athlete is truly prepared to perform under pressure, often with little more than instinct and a stopwatch. The drug company can point to trial results, but not how a patient actually does at home, three months later, under real-world conditions.
Different markets, different interventions, the same uncomfortable admission: none of them have a reliable way to measure whether what they’re doing is actually working.
This is the blind spot that the brain health industry would rather not talk about.
Investment is flooding into interventions at an accelerated pace. Governments, health systems, research institutions and venture capital are funding the next generation of drugs, therapies, wearable devices and cognitive training platforms. But the measurement infrastructure needed to prove that something works has not been up to par. Organizations are spending a lot of money and still operate largely based on intuition when it comes to results. That’s the silent sign that brain health is entering its infrastructural era, whether the field has caught up with it or not.
The structural problem of how we measure brain performance
The standard approach to measuring brain health separates the brain and the body. Cognitive measures capture memory, attention, processing speed, and executive function. Motor measurements capture balance, reaction time, gait, and coordination. Both have real clinical value. Both also overlook what really determines whether someone can function in the real world.
Human performance is not clearly divided into cognitive and motor columns. Independence, recovery, and readiness depend on neuromotor control: the brain’s ability to process information and execute movements simultaneously under changing conditions. It is the system that governs whether someone can navigate an unpredictable environment without falling, whether an athlete can perform under pressure, whether a worker can maintain performance in a physically active and cognitively demanding role.
When measurements assess the brain and body separately, they miss what happens at the intersection, and that’s exactly where the risk lies. Individuals may appear cognitively intact while significant changes in neuromotor function are already occurring. Athletes may approve return-to-play protocols as long as persistent deficits persist. Patients may appear stable on paper, while the functional changes that drive their actual risk remain invisible to the tools used to assess them.
The sign almost always appears before the symptoms. Neuromotor control is where it comes up first, and it’s the one thing that almost nothing on the market is designed to measure.
The landscape of brain health interventions is expanding in all directions at once, and the number of organizations making significant claims about brain health outcomes is growing faster than the field’s shared ability to validate those claims. New pharmaceutical candidates for cognitive decline, digital therapies, wearable devices, AI-powered measurement tools, longevity protocols with brain health as a central pillar, workplace performance programs, concussion management systems – all of this is moving rapidly and would all benefit from a common way to prove it’s working.
This imbalance has real consequences. Without longitudinal measurement of brain performance, program providers and operators hit the same wall from different directions:
Intervention decisions are made without a baseline. If you never established what a patient’s or resident’s neuromotor function was like before an intervention, you have nothing to compare the change to.
Return to activity decisions are based on incomplete data. Protocols based on symptom resolution or isolated cognitive and motor scores may clarify individuals who still have significant functional deficits.
The results of the program are difficult to prove. Operators investing in brain health programming must demonstrate results to residents, patients, payers and boards of directors. Without a consistent measurement framework, it is difficult to make that argument convincingly.
The investigation hits the same ceiling. Studies measuring the impact of medications, therapies, or training programs on cognition have rarely had access to a reliable measure of neuromotor function as an outcome variable, limiting both the questions researchers can ask and the conclusions they can draw.
A different approach is emerging: measuring the brain and body together, because that’s where the meaningful information really lies. Testing memory or balance in isolation only tells part of the story. The full picture only appears when the brain is measured under load, coordinating with the body in real time. That’s neuromotor control: the brain’s ability to process information and execute movements simultaneously under changing conditions. It’s the layer that reveals how the brain and body really work together, and it’s the layer that most measurement tools still miss.
Instead of two isolated scores, the integrated neuromotor measurement produces a single Brain Performance Score™, a profile of how a person’s brain controls movement under cognitive load, baselined and tracked over time.
The applications cover almost every environment that touches brain health. For senior and active aging housing operators, it’s a way to demonstrate whether programming results in functional improvement, not just participation. For rehabilitation providers, it is an objective input into return-to-activity decisions that goes beyond a symptom checklist. For sports performance and occupational health, it is a readiness benchmark based on neuromotor function rather than assumptions.
None of this is speculative. Sensorimotor neuroscience connecting neuromotor control to functional outcomes spans more than two decades and more than 50 peer-reviewed studies. What is missing is not science. It’s a way to bring that science into everyday clinical and operational settings that is simple enough to use without specialized training, intuitive enough that the results make sense at a glance, and standardized enough that a score means the same thing in a senior living facility as it does in a secondary setting.
Every era of healthcare innovation ends up ranked the same way: not by who has the most interventions, but by who can prove those interventions work. Vital signs became central to medicine for exactly that reason. Blood pressure. Heart rate. Oxygen saturation. None of them replaced clinical judgment. They gave him something to lean on.
Brain health hasn’t had its version of that yet. Organizations that develop measurement capacity now, before the mandate and not in response to it, will be the ones that set the standard to which everyone else will eventually be held. Those who wait will be measured against a bar they could not help define.
That change is already underway, quietly, in a handful of environments that most of the industry has not yet noticed. And that’s really exciting. Brain health is entering its infrastructure era: the point at which a field stops wondering if something works and starts being able to demonstrate it, for every patient, every program, every intervention that deserves the chance to show its value. Organizations willing to move toward that goal will not only be at the forefront; They will be the ones who finally give this entire field the language it lacks to describe its own progress.
About Reed Hanoun
Reed Hanun is a four-time founder and multi-exit entrepreneur with over 25 years turning innovative ideas into scalable platforms that change the way the world measures human performance. His career as a founder spans Hanoun Medical, MyTrak Health and 3motionAI, three companies that crossed the frontier of human performance measurement. In Nero AIis building what everyone was aiming for: a global standard to make neuromotor control measurable, trainable, and trackable across the spectrum of human life.
