A few weeks ago, a research paper out of MIT (the college) crossed my desk that most investors would have ignored.
It was about worms.
Specifically, it was about a team that had successfully mapped the entire brain of a microscopic worm — every neuron, every connection.
Then it laid out what it would take to scale that process from a worm… to a mouse… and eventually, to a human.
Now, here’s where things get interesting for us.
For decades, mapping the human brain has been one of science’s biggest challenges. And while we’re still years away from a definitive solution, we’re starting to see the missing piece fall into place that could break the whole field wide open: brain-computer interfaces.
These are systems that allow the brain to communicate directly with machines — turning thought into action and speech.
Right now, the headlines focus on major players like Elon Musk’s Neuralink— buffeted by twelve patients, a $9B valuation, and IPO rumors.
Sam Altman also committed $250 million to his own brain-chip startup earlier this year.
The reporting surrounding these companies often leans toward the dramatic: the merging of mind and machine, the next frontier of artificial intelligence, the possibility of restoring lost functions or even augmenting human cognition.
It is a story that lends itself to headlines. But it is also, in some ways, a misleading one. The visible pieces of this emerging field — the implants, the interfaces — represent only its final layer.
What they’re hiding is a much larger system that must exist before they can function in any meaningful way.
This is where the real opportunity lies for us. And in order to understand, we need to dig deeper than the headlines…
The Critical Systems Holding This Breakthrough Back
Once I got over my initial excitement after reading the report and considering what it might mean, I did what traders do: I moved straight to the supply chain.
The MIT thesis, perhaps unintentionally, offers a map of this growing system.
It identifies several areas that must advance together: structural imaging, which captures the physical wiring of the brain; functional imaging, which records activity; molecular analysis, which explains how neurons behave; and computational infrastructure, which integrates and simulates these layers.
Each of these parts has made significant progress in isolation. What’s new is the recognition that they are dependent on each other so that major progress in one without the others is unlikely.
This interdependence means that what we’re really looking at is a set of bottlenecks that are overlooked in the broader narrative.
This is exactly the kind of shift we focus on inside the Masters in Trading Challenge — learning how to move past the obvious story and identify where the real edge sits before it becomes consensus.
It’s not about predicting the headline outcome. It’s about understanding what has to happen underneath it—and positioning early. If you want to see exactly how we approach setups like this, you can learn more about the Masters in Trading Challenge here.
One of the clearest examples of this shows up in imaging. Imaging a brain at sufficient resolution is not simply a matter of improving a single machine. It requires scaling entire systems — microscopes, data pipelines, processing algorithms — by orders of magnitude.
The thesis suggests that even mapping a mouse brain would require dozens of high-throughput electron microscopes operating continuously for years.
And for a human brain? That demands far more extensive infrastructure that’s currently lacking.
The Next “Genome Project” Is Already Taking Shape
Building these systems are not incremental challenges. They resemble, in scale and coordination, the kinds of efforts more commonly associated with large public works or scientific “moonshots.”
The Human Genome Project – the effort to map all human DNA that turned biology into a data-driven science and made genetic research dramatically faster and cheaper – is often cited as an analogy.
When it was all said and done, that project required more than a decade and billions of dollars to complete.
Brain emulation, if pursued at a similar scale, would likely demand comparable levels of investment and collaboration.
If the history of technological change offers any guidance, it is that the most transformative shifts rarely occur where attention is first directed.
They unfold, instead, in the spaces beneath the surface, where small advances accumulate until they alter what is possible.
The sensors. The chips. The imaging systems.
That’s where capital is starting to flow.
Right now, I’m tracking 14 names tied to this theme — 10 public, 4 private.
In today’s essay, I’m breaking down all fourteen names across three buckets:
- Two to start with today
- Eight to build deeper exposure
- And four private companies to watch as they approach public markets.
Let’s dive in…
Bucket 1 – Start Here
If you only buy two names from this basket, start here.
Butterfly Network (BFLY): ~$500M market cap
BFLY produces handheld, chip-based ultrasound devices used in brain imaging. And unlike some of the other names on this list, this early-stage player is already bringing in sound business.
Last quarter, BFLY turned profitable for the first time, with revenue growing 41% year-over-year to $31.5M.
That momentum is only increasing as BFLY secures more contracts around its signature tech. Its ultrasound chip is licensed into Forest Neurotech, an Eric Schmidt-backed brain-computer interface project – and that’s just one key partnership among many.
At a $500M market cap – with real revenue and BCI exposure – the risk/reward looks cleaner than most.
How I’d Play It
Start a position and add on pullbacks to support. This isn’t a moonshot—it’s a functioning business with an underappreciated catalyst.
Quantum-Si (QSI): ~$194M market cap
This is the asymmetric bet. It offers the only commercial single-molecule protein sequencer currently available on the market.
The MIT research identifies protein sequencing as a gating technology for brain mapping. Right now, this is the only U.S.-listed way to access it. With revenue at just $2.4 million, this is a company firmly in its earliest stages with massive growth ahead.
How I’d Play It
Keep position size small. Treat it like a call option, not a core holding. If the thesis works, the upside could be significant. If not, downside risk is real.
Bucket 2 – Add These to Go Deeper
These names round out the basket if you want broader exposure. It’s a mix of small-cap volatility and large-cap stability.
Hyperfine (HYPR): $127M market cap
HYPR provides the only FDA-cleared portable brain MRI system on the market – its Swoop device, which brings imaging directly to the bedside.
HYPR’s reach is beginning to expand beyond the U.S. Just this year, the startup received approval in India to sell its devices, opening up a large new market.
HYPR is one of the smallest small-caps on this list. And it always trades on news.
With that approval and a surge in value since March, HYPR remains one of the best early land-grab opportunities in this basket.
How I’d Play It
Add HYPR for direct brain imaging exposure. Watch upcoming guidance for signs of international traction.
NVIDIA (NVDA): $5.6T market cap
Most investors own NVIDIA for AI, but few connect it to the brain race. That’s about to change.
NVIDIA’s Holoscan is an important application in the brain imaging race. For those who don’t know, it’s an AI-enabled sensor processing platform designed for real-time edge computing that can be deployed in various use cases – from security applications to the medical field.
Many of the top BCI players are building their tech on top of NVIDIA’s Holoscan. BCI manufacturer Synchron’s interface runs on NVIDIA Holoscan. And another BCI startup, Merge Labs, is expected to train models on its chips.
Regardless of which platform wins, NVIDIA sits upstream.
How I’d Play It
If you already own it, you have exposure. If not, this is another reason to consider it.
Micron (MU): $560B market cap
This is the memory bottleneck trade. Compute has scaled far faster than memory over the last three decades. That gap is becoming critical for both AI and brain emulation.
Micron is the clearest U.S.-listed play on high-bandwidth memory. And with so many clients for its chips already being participants in the modern brain race, this stock is one of the best ways to gain early exposure today.
How I’d Play It
It’s cyclical. Look to buy on weakness.
Medtronic (MDT): $100B market cap
Medtronic partnered with Precision Neuroscience, gaining exposure to BCIs without building the technology internally.
That’s a massive edge in a market where the biggest BCI makers are still dealing with major cost overruns and costly implementation failures.
Medtronic is already a giant in the space. With this partnership in place, MDT represents a more conservative way to trade the theme.
How I’d Play It
Useful for portfolios seeking income and lower volatility with some upside optionality.
Nautilus Biotechnology (NAUT): $331.6M market cap
This stock is a complementary play to QSI. NAUT approaches protein sequencing differently but targets the same bottleneck. And a recent partnership with Baylor College adds early validation.
How I’d Play It
Smaller position than QSI. Treat both as a paired bet.
Bruker (BRKR): $5.56B market cap
This is a “picks and shovels” name that’s been setting off my UOA Monitor for weeks.
In fact, I just recently recommended the trade on Masters in Trading LIVE as the perfect way to gain early exposure to the BCI trend.
This stock already has massive penetration in the space. Its microscopy systems are used across leading brain-mapping labs. It’s a medium-sized player with a lot of room to run.
How I’d Play It
A more stable position relative to smaller biotech names.
Thermo Fisher (TMO): $174.5B market cap
One of only two companies globally producing the high-throughput electron microscopes used in connectomics research. A long-term compounder.
How I’d Play It
A steady, long-duration hold with lower volatility.
Broadcom (AVGO): $2.01T market cap
AVGO provides custom AI chips and networking infrastructure for hyperscalers. While not a direct BCI play, it supports the systems that make brain-scale computation possible.
How I’d Play It
Similar to NVIDIA—core infrastructure exposure.
Bucket 3 – Watching, But Not Yet Public
These are private companies to monitor for IPO activity. When one files, expect ripple effects across the entire basket.
Neuralink
Private: ~$9B valuation
Elon Musk’s BCI company has twelve patients implanted. So far, it’s one of the most regulatorily compliant and well capitalized names in the space, already backed by FDA Breakthrough Device designation.
How I’d Play It
Not publicly tradable yet. When it files, expect rapid repricing across related equities.
Synchron
Private: Pre-IPO
Synchron offers a less invasive interface delivered via the jugular vein – all backed by Jeff Bezos and Bill Gates. As I alluded to at the top, Synchron also has several major partnerships in place with companies like NVIDIA and Apple Vision Pro.
HOW I’D PLAY IT
Watch for IPO filing. Potentially lower-risk than Neuralink due to its approach.
Precision Neuroscience
Private: Pre-IPO
Precision is working on a surface-level brain interface developed by a former Neuralink engineer. And it just recently received FDA clearance and partnered with Medtronic – all great signs as it works its way to a potential IPO.
How I’d Play It
Indirect exposure exists through Medtronic. Consider direct exposure if it goes public.
Colossal Biosciences
Private: Pre-IPO
Colossal is connected to Harvard geneticist George Church. While it’s not a pure BCI play, the company is part of a broader biotech ecosystem that could intersect with neural research.
How I’d Play It
Highly speculative. Monitor for developments.
One last note: I’m long QSI. I do not currently hold the other names listed here. This reflects my research and watchlist—not a recommendation to buy or sell any security. Small-cap stocks in this space can be highly volatile. Do your own research and consult a licensed professional before investing.
What Happens Next
History shows that when a complex problem becomes a matter of engineering—when it can be broken down into discrete constraints—capital flows to the solutions. And that all happens often before the broader narrative fully takes hold.
Today, much of this ecosystem remains underfollowed and, in some cases, mispriced relative to its potential role in the broader shift.
That won’t last.
As progress in these underlying technologies becomes more visible — through partnerships, breakthroughs, and eventually public listings — the market will connect the dots.
When it does, the repricing is unlikely to be gradual.
For investors, the takeaway is straightforward: Focus less on the outcome and more on what must happen for that outcome to exist.
That’s where the opportunity is today.
And if you’re interested in learning more about the system that discovered all these names…
That knowledge is waiting for you inside the Masters in Trading Options Challenge.
The Challenge is where we take everything you’ve learned in my articles and daily LIVEs — fixed risk, thesis-driven exits, laddered entries, defined-duration trades, and emotional discipline — and put it into practice in a structured, step-by-step environment.
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Just click here to check out what the Masters in Trading Options Challenge has in store for you.
Remember, the creative trader wins.
Jonathan Rose,
Founder, Masters in Trading
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