Swiss neurotech startups team up to deliver personalized light stimulation for instant mental focus using smartphone flashlights and ear-EEG technology.
BRNLIT.ai’s breakthrough alpha wave stimulator, made possible by your smartphone flashlight and the IDUN Guardian ear-EEG platform, promises to boost your mental focus in less time than it takes to make a cup of coffee.
Last month, in the heart of Switzerland’s booming deeptech ecosystem, Matthias Jehle and Rubin Pfeifer, founding members of the BRNLIT.AI team, paid a visit to our Zurich headquarters. What started as a friendly meetup over pizza became an illuminating demonstration of how our two innovative companies are pushing the boundaries of what’s possible when technology meets the human brain.
Individualized Alpha Frequencies: the Neuroscience of Instant Focus
Research done at Cambridge University in 2023 and published in Cerebral Cortex by Michael et al. established that alpha oscillations (8-13 Hz) function as fundamental 'gating mechanisms' in the human visual cortex, regulating neural information through rhythmic inhibition and disinhibition cycles. These oscillations have characteristic 'peak' and 'trough' phases; troughs represent moments of disinhibition when neurons are more excitable and responsive to incoming stimuli.
Alpha frequency varies substantially across individuals (7.5-12.5 Hz in healthy adults), and this variability has functional significance. The Cambridge researchers investigated whether this personalization matters for learning by comparing three conditions: stimuli presented at the trough phase of individually-matched alpha frequency, at the peak phase of individually-matched frequency, or at the trough phase of non-matched frequency.
The results were striking: only the trough-phase, individually-matched condition produced enhanced learning. Specifically, participants showed 28% faster learning rates and improvements in early visual processing compared to other conditions. Critically, the learning benefits persisted when participants were retested 24 hours after training, suggesting genuine skill acquisition rather than temporary performance enhancement.
Where IDUN and BRNLIT.AI Come In: From Lab to Real World
BRNLIT.AI's approach builds on established findings that alpha oscillations regulate cortical excitability and that individual alpha frequency is functionally meaningful. By calibrating smartphone light stimulation to each user's IAF, the technology aims to optimize neural states for attention. While laboratory research like the Cambridge study demonstrates benefits of individualized entrainment during concurrent tasks, translating these findings to practical, real-world focus enhancement represents an active frontier in applied neuroscience.
This is where the IDUN Guardian becomes essential. BRNLIT.AI's personalized approach requires accurate EEG measurement of each individual's alpha frequency, yet traditional EEG caps aren't practical for consumer applications. During onboarding, the IDUN Guardian's in-ear EEG measures users' alpha frequencies with precision comparable to laboratory equipment, enabling truly individualized calibration rather than generic, one-size-fits-all protocols.
The onboarding works as follows: BRNLIT.AI's experimental setup includes a strobe-like light and an IDUN Guardian ear-EEG device, both connected and synchronized to a laptop computer. A subject is invited to sit comfortably, with closed yes, in a darkened room, while wearing the Guardian. The light flashes, cycling through a range of alpha frequencies, while IDUN hardware records brain activity and IDUN software analyzes the data to find which is the characteristic alpha frequency of that particular subject.
Once this individualized alpha frequency has been identified, it is loaded onto the subject's smartphone via the BRNLIT.AI app, with which the subject can, at any time, choose to receive stimulation through the phone's light.
A Meeting of the Minds in Zurich
The importance of this personalization became strikingly clear during Katja Junker's onboarding session. Despite years of monitoring her own brain activity, she had never observed strong alpha waves, until BRNLIT.AI's light stimulation was precisely tuned to her individual frequency using IDUN Guardian data. For the first time, she witnessed robust alpha activity, validating what the Cambridge research suggests: even small frequency mismatches (±1 Hz) can mean the difference between effective and ineffective intervention.
This moment perfectly illustrates why our technologies complement each other so well. BRNLIT.AI provides the intervention: the precise light patterns designed to shift brain state. The IDUN Guardian provides the measurement: real-time, unobtrusive monitoring of whether that intervention is actually working.
The Technical Symphony: How Light Meets Brainwaves
To understand how this partnership works, imagine your brain as a complex orchestra. Different sections (brain regions) are playing different parts (neural oscillations), and the result is a kind of chaotic harmony. Alpha waves represent a particularly important section of this orchestra; much like the percussion section of our orchestra, they set the tempo for focused attention.
BRNLIT.AI’s light stimulation acts like a very sophisticated metronome, sending visual cues at precisely the right frequency to encourage your brain’s “alpha section” to play in sync. But here’s the critical part: you need to know if the orchestra is actually following the conductor.
That’s where the IDUN Guardian’s in-ear EEG monitoring becomes essential: our earbuds can detect alpha wave activity from the ear canal, enabling the light stimulator to be tuned to the precise frequency that elicits greatest alpha activation in a particular user.
Real-World Impact: Beyond the Laboratory
The implications of this technology partnership extend far beyond academic curiosity. In our increasingly distracted world, the ability to rapidly achieve and maintain focused attention represents a significant competitive advantage — whether you’re a student preparing for exams, a knowledge worker tackling complex projects, or an athlete preparing for peak performance.
Traditional focus enhancement methods often require significant time investment. Meditation, while scientifically proven to enhance attention, typically requires weeks or months of consistent practice before users see meaningful benefits. Pharmaceutical interventions like stimulants work quickly but come with side effects and potential dependency issues.
The BRNLIT.AI approach, optimized through IDUN Guardian feedback, offers a third path: rapid, personalized, and side-effect-free focus enhancement that works with your brain’s natural processes rather than against them.
Given the waste of productive time, estimated at 316 hours per person per year, attributable to focus lost to the distractions of the modern era, this technology is poised to generate substantial added value very quickly.
Looking Forward: The Future of Cognitive Enhancement
As we wrapped up our pizza and said our goodbyes, we couldn’t help but reflect on the broader implications of what we’d witnessed. The convergence of precise brain measurement and personalized stimulation represents more than just a neat technical achievement, it’s a glimpse into a future where cognitive enhancement becomes as routine and accessible as adjusting the lighting in your workspace.
The path forward isn’t without challenges. Regulatory frameworks for neurotechnology are still evolving, and questions about long-term effects of brain stimulation remain under investigation. But partnerships like ours with BRNLIT.AI demonstrate how the neurotech industry can advance responsibly through rigorous measurement, personalized approaches, collaborative innovation, and a commitment to the highest ethical standards.
Perhaps most importantly, this collaboration reinforces a fundamental principle that drives both our companies: that by providing ordinary people with better tools to understand and optimize their own brain function, we’re empowering them to truly push the envelope of their own potential.
About the Author
Philip Egger, PhD is IDUN’s Data Science Lead