Pushkin. My guest today is a brain surgeon who also has a PhD in electrical engineering from MIT, which is to say he is extremely well prepared to figure out how to implant electronic devices in people's brains, which is what he's doing, and in fact, as it happens, he's actually been preparing to do this kind of his whole life.
You know, I sort of was born into the business. My dad is a neurologist who started on his career as an electrical engineer. You know, electrophysiology, clinical neuroscience and neurology and our surgery. I've been a part of my life forever as far as I can remember. And you know, brain computer interfaces the way we talk about them today didn't exist in the nineteen eighties, but the fundamentals were there, and so that's been percolating in some way forever.
I'm Jacob Oldstein and this is What's Your Problem, the show where I talk to people who are trying to make technological progress. My guest today is Ben Rapaport. He's the co founder and chief science officer at Precision Neuroscience. Ben's problem is this, can you build a device that allows someone who is paralyzed to use a computer with only their thoughts and can you do it without sticking needles into their brain. Before he started Precision, Ben was
a co founder of Neuralink. Neuralink is probably the best known brain computer interface company, and it was founded in twenty sixteen, right around the moment when modern AI was just emerging. And Ben told me the AI revolution was really what inspired the foundation of Neuralink.
The kind of founding principles of neuralink were, you know, here's here's a point in time when we're thinking broadly about how the human brain is going to interact with artificial intelligence. And if breakthrough is an artificial intelligence are scaling at an exponential rate, you know, how's the human brain going to keep up with that? How are we going to keep communicating with artificial intelligence in a way that is feasible and productive.
So that's a really different that's not how can we help people who are paralyzed. That's a much more sort of cognitive centric. It's about like the nature of human thought in the context of AI.
So that was the that's kind of the raison deetra of neuralink, and it was a little different from a human focused medically oriented focus that Precision has taken. And these different focuses can you know, can and will coexist in an ecosystem in which multiple brain computer interface core technology has become widely available and are the standard to
become the standard of care. But it became clear to me that that there was a need to also focus an effort within the community of bring computer interfaces on
treating patients with untreatable diseases. That was the origin, you know, brain computer interfaces was really bringing this science and technology to a point where you know, people who today we think have has having really no treatment options, people with paralysis or an ability to speak, for example, from als, you know, really unlocking a world of possibilities for those people.
But we really wanted to focus on those applications within bringing computer interfaces, and doing that, in my view, required making a few different design decisions than what we've made at Neuralink. You know, so those were the founding principles of Precision.
You leave Neuralink to found Precision. Tell me tell me about what you you know, what you're setting out to create at Precision when you're launching the company, Like, what is it that you want to do and how is it different than what everybody else is doing.
Yeah. The goal then and is today to build a safe, scalable brain computer interface that can become the standard of care in the treatment of patients people with a variety of diseases of the brain and nervous system that today are untreatable. That that includes various forms of paralysis and inability to communicate.
And tell me about the tell me about the technology, like, tell me about the thing you're building and how it's different from what other people are building.
Our philosophy has been that in order for a brain computer interface to really work in the real world and to unlock the potential of this technology for many millions of people. First, of course, it has to be incredibly safe. We see the use of the views of the term minimally invasive a lot, but really in my view, has to not damage the brain.
So what does that mean in practice?
Yeah, the tissue interface with the electrode involves kind of like little needles of the electrics are little needles and they penetrate into the brain. And there's been a lot of innovation in doing it, trying to do that very safely, But in my view, the most safe version of that is a version that just kind of caresses the brain
but doesn't penetrate it. And it was at first thought, you know, certainly when we found a precision, many people thought that it was not possible to extract high quality signals from the brain without penetrating, and we and others have shown that, in fact, it's not only possible to
do but has many advantages. So not that it's the only way or necessarily better or worse, but from the standpoint of people who have untreatable diseases and already have a very low threshold for damage to the brain, not doing any incremental damage to the brain for us is very very important. So that was sort of part one of precision.
Is there before we get to part two? Is there a trade off? I mean, do you lose some amount of sensitivity or resolution? Is that the basic trade off?
So we always get this question, you know, right, No, it's absolutely it's a good question, right, And so there's this false dichotomy. I think that more penetration into the brain equals higher quality signal, and if you don't do that, then you somehow sacrifice signal quality. But it's really not a one dimensional as one dimensional as that if you're
a neuroscientist, then there's a trade off. If you care about recording from one neuron out of time, and you're studying the behavior of individual neurons, and you care about that, then you want what we called intracortical penetrating microelectrodes, the ones that can come up up close to an individual neuron and listen to those individual action potentials. And that's
something that neuroscientists care about. So you don't want to use the same electrodes that we use for a precision But but if what you care about is is treating paralysis or sources of communication, what you care about is stable, high quality signals over a long period of time. And in that area, arguably, just based on the data, you know, the cortical surface electrodes that we use at precision are
at least as good, if not better. And I think you know, I will tell because there's a few of these different systems that are now out there in the real world. What's really exciting is that this has come out of the laboratory, out of animal experiment territory, into human pilot clinical trials that we and neuralink and synchron and others are engaged and that's really where it's at.
So tell me where you are now. I know you've done some amount of experimental work in people, right what is the frontier of your work right now?
Yeah, we've now implanted our electrode raise in almost thirty patients over the last two years. These are pilot studies across four major medical centers and the US that are partnering with US, and all of those studies are really they're temporary placements of the electrodes. So there are studies that are run in nations who have volunteered to have the electrodes placed alongside clinical standard electrodes as part of
a under resurgical procedure that they're already undergoing. And we've been using those opportunities to basically validate the quality of electroctavity that we can record on those electrodes and to demonstrate that our algorithms can in fact basically decode intention and thought as intended by health essentially healthy volunteers.
So the array itself, like, what does it look like?
So the brain lives in the skull, so it's a it is a soft tissue that's kind of jelly like inconsistency, and so the best way to generally interface with it is with something also that is soft and flexible. And the surface of the brain is many of us have seen in pictures, is curved or undulating, and so our electrode array is a thin polymer that's many times thinner
even than a human hair. So it's a film, and embedded in that film are tiny little dots of platinum, each one connected to it very very very thin platinum wire. And so that film with the tiny little dots of platinum inside, can be placed over the brain surface and
it conforms to that curved surface. So each of those little platinum electrodes touches the surface of the brain at a very discreete point, and so it can record the electrical activity from the area of the brain just under that its touching basically.
Okay, So in these trials, you put this implant on a patient's brain and then what.
So let me describe maybe one of the paradigms that we use at one of our partner sites. So ian Cahegus is the neurosurgeon at Penn who's our partner, and he is a surgeon who specializes in the treatment of Parkinson's disease. One of the ways of treating Parkinson's disease is a procedure called deep brain stimulation, in which electrodes are placed deep within the brain to stimulate those areas
that are responsible for modulating the tremor. Doctor ca Vegas, among many others, performs these procedures at least a part of them awake in order to make sure effectively that the exact right place is being targeted and the brain doesn't feel pain. And so it's not only possible but
beneficial to do these procedures at least partially awake. So in those procedures, we take a basically a fifteen minute window and doctor Ahigis places the precisional electrode directly over the motor cortex, a portion of the motor cortex that controls hand movement. And this has provided for us and for the community, the highest resolution picture of the human motor cortex and the awake human ever in the history
of the world. So you know, the area of the brain of the motor cortex that controls hand movement is about the size of a postage stamp. And critically to understand is the neurons that are responsible for coordinating those movements. They all live within a two milimeters your layer of tissue that's just at the surface of the brain. So all that critical computation and activity is happening very very close to the surface. And so it's good.
For you, good for us method. So so what actually happens. So you have a patient who's there, you put your array on the on the portion of their motor cortex that controls hand movements, and then you say, wiggle your finger.
Exactly, so we say, we say, we say, basically, you know, we asked. We walk the patient through making a certain number of gestures, you know, open hand, close hand, make a peace sign, and we watch, and I say metaphorically watch, We watch what the patient is doing, and we watch what is happening on the surface of the brain. And and here is you know, where modern machine learning plays a tremendous role, because this exactly, you know, this is the AI portion of it, because this is this is
the so called training data. So this this is a calibration phase in which our algorithms learn what the brain's signals to the hand look like in a given patient.
So there's a characteristic signature, electrical signature that happens in the moments before an action is done, and it's a little bit different in each person, and learning that signature for that person allows us to recognize when the brain is telling the hand to make a particular gesture, when the fingers are supposed to move in a particular way, when the hand opens and closes, and after about three to five minutes of training, we then have a trained
algorithm that can recognize not just movement, but the intention to move. And so we then use the balance of the time that we have with those patients to ask the patient to move and validate that we're predicting the correct movement, and then to imagine movement without moving, and that too we can accurately predict. And so these procedures become the basically healthy volunteer test bed for patients who can't actually move, the paralyzed patients that we'll be treating
within the next couple of years. So that's that's the nature of this first phase of pilot trials.
You mentioned that each person is different in terms of the patterns of neuron activity for each hand motion. In this context, how different is it like kind of like a Southern accent versus a New York accent. Is it like an entirely different language if that kind of metaphor work.
Yeah, No, that's a perfect metaphor. And it's it's kind of like that. So you know, you if you're trying to learn a new language or a dialect, you know that there are words, and you know that they're spoken in a particular frequency range, so you kind of know what to listen for, and you kind of know the cadence. So when there's a word, you know that's a word, but you might not know what it means until you listen in to conversation and you've seen the context.
So so like pretty different. Like it wouldn't work to just make a generic algorithm and put her on my brain.
Because it doesn't work to make a generic algorithm. But that's an area where there's been a lot of just fascinating development. And so a good example of this is, you know, Siri works out of the box for most people pretty well, right.
Talk into your eye, right, it works.
Right, It works pretty well, and then you need to train it to make it better, and then it listens to you in the background and gets even better. And so that that's a good that's a good analogy. So it is possible for us to build, you know, a translation algorithm that works somewhat out of the box, but we build into it a calibration phase that knows something about the structure of brain signals and how they interact
with and relate to movement or speech. And that's what basically allows us to use only relatively small amounts of calibration data. I mean, you know, we can do a lot with a small amount of calibration data.
So you're doing a sort of pilot study. Now, when what's the next big step?
So I want to be careful about what I say before it happens. But we do anticipate being able to in the very near future extend what are now short duration file with studies that last only the span of time that we have access to the brain within a standard androsurgical procedure, which is relatively short. We anticipate having ways of extending that with regulatory approval, to hopefully many
days and weeks within the calendar year. And then, of course, this is all in the service of permanent implants that wirelessly communicate with the outside world, and that will be the basis of our pivotal clinical trial a couple of years hence.
Still to come. On the show, Ben and I discussed the possibility of using brain computer interfaces in healthy people, also the meaning of consciousness. Just before the break, Ben mentioned that pivotal clinical trial that they're building up to, and so I asked him what exactly they're going to be doing in that trial.
So the first clinical application is going to be for the treatment of severe paralysis, okay, And the device will be an implant that has the electrodes on the brain and an implant within the chestwell that provides power and data transfer to the outside world to communicate with the
external devices like a computer. And that system will allow, for example, a person with a spinal cord injury really to hold the desk job that will allow them to operate effectively a word processing program, email, serve the internet, have a zoom conversation, operate and expel a sales spreadsheet, use PowerPoint, have the ability to re enter the workforce with a level of personal and economic self sufficiency that allows them to, you know, certain freedoms that they don't have,
and that our core to being a part of modern society. That is, for us a major goal. Number one, I'm quite sure that past the technolog becomes provenly safe and effective, that other disorders and conditions that are perhaps less dramatic, you know, will benefit from this and in other forms of technology. And part three is there's a lot that
I'm sure that we're not even imagining right now. You know, the brain computer interface, at least the precision system is really in some ways a platform technology because it's it translates the wet and difficult to access, delicate, you know, biological signals of the brain into robust digital bitstreams and allows us to compute on them in a scalable way. The brain computer interface is not a substitute for a keyboard in a mouse. It's not a substitute for a
gestural interface or a voice interface. It's another kind of interface with the brain, just like it was would have been impossible to predict based on the keyboard, a loan, or the graphical user interface alone, all of the different applications that have emerged. I think, as long as we build a safe, reliable interface and make that responsibly available kind of skuy's the limit. And I can't even hazard to guess at some of the things that will come next.
So I think there's a there's a whole generation of discovery and innovation waiting to happen after we get this across the line into patients to become standard of care.
Could you imagine it being used in healthy people for you know, the computer and the brain application.
Yeah, I could eventually, in a sense, I would love that to be the case.
I think I'm ambivalent about that one. Tell me why you'd love that to be.
The case, Well, because it will have meant that we've.
Well, yes, it'll mean your thing works really well, it is wildly safe.
Yes, that's true, right, Yeah, So we build with that goal in mind in a way, right, just because in order for something to be accepted by an eble body person who has zero risk tolerance, right and basically only downside, if something goes wrong or doesn't work properly, you need it to work just in a bulletproof way. That's that's the kind of system that we're trying to engineer.
Yes, from that point of view, it makes perfect sense. Then if that is true, then then you have built a wildly safe and effective device exactly.
So, if you and I were having this conversation and you said to me, gosh, I would love to write. I mean that would mean that all those doubts had been erased. And in order to erase those doubts, we have to prove certain things to the world, and that's that's really our job.
Would you would you want if you were healthy? Would you want to have your device in your brain? If it were safe and effective?
I would have to do certain things that that the device can't do yet, yeah, rush, but I wouldn't definitely wouldn't rerule it out when we get there. And I mean it's like sometimes with technology, it's it's hard to wrap your mind around what's going to happen in a generation, right too little kids and we're always talking about like should the kids actually get to use an iPhone?
Hold out for as long as you can so, right, because so it's not exactly a choice, right, that's the that's the thing you think, like, oh an iPhone?
That's my point. By the way, I'm very very permissive and me too.
You know what finished me was COVID, Like we held out really strong and then COVID hit did ason.
So but the reason I bring that up is that, you know, like our parents could not even have conceived of even that question, right.
Yes, But I mean the other way to think about that is, like, you know, I'm pro progress and pro technology, but like having kids makes me wish iPhones didn't exist, right, makes me wish like, sure, give them a flip phone so they can text their friends that call me if something goes wrong. But well, you know, I don't know. But on the other hand, I make podcasts for a little.
It's an interesting discussion, right, and you know, we sometimes joke, but somehow kids are born now knowing how to swipe and navigate the phone interface. Right. So my point is that in twenty years it's going to be a different conversation. There's a lot of kids of people in the company, and they know what we're doing, you know, like girls know what we're doing, and their view and the technology
is different. They see it as something that exists, and when you're bored into it, you have kind of a different sense of what's okay and what's normal. And that's the generation that's growing up today is going to grow up with bring computer interfaces just being a normal thing.
Yeah, maybe your grandkids will feel about bring computer interfaces the way your kids feel about iPhones.
It's going to happen faster than that.
We'll be back in a minute with the lightning rim tell me about the metabolic factors limiting performance in marathon runners.
Okay, right, so that was a paper that I wrote now more than a decade ago. So I'm a dedicated marathon runner and I run forty something marathons over twenty plus years. There's a longer story, which we don't have time for now, is to I wrote that paper.
Give me what's the short version of that story of why you wrote the paper.
The short version is it shouldn't be metabolically possible to run a marathon because interest everybody. Everybody thinks the paradox is that you know, you can't eat enough pasta to get through twenty six miles.
Uh, just like if you do the math, there's not enough energy stored in the body.
If you do the simple math. There seems to be a paradox that you can't you can't eat enough pasta to run the marathon. Right, everybody thinks you got to run eat passive before you run the marathon. It turns out that can't really eat enough pasta to run a marathon. So how is it even possible, okay, And the reason it's possible is that you're burning some fat as you go.
And then everybody knows that there's this phenomenon of hitting the wall where you know, many runners collapse or have a major impact at some point, you know, along the way, usually about two thirds the way through the race, where they just can't keep going or it can't keep going at the same pace that they started the race. And why does that happen. That happens because they're not burning carbohydrates as the fuel substrate, or they can't burn them
at the same rate that they started the race. So how do you not hit the wall? How do you avoid that phenomenon? And basically you need to run at a pace that basically burns both fuel substrates fat and the carbohydrate at a rate that basically you just exhaust your carbohydrates stores at mile twenty six point two. So that's one of the core rate limiting metabolic factors in marathon.
And that, I mean, so, what was it that you figured out that got published in whatever it was Plus.
Yes, I figured that out, and I figured out how to model that mathematically.
And did it affect the way people run?
Marathons well effected the way I run marathons?
And how did you change your running strategy based on your own research?
I learned how to pace myself in a more quantitative way, and I learned how to have a structure. My pre race died and my training diet in a way that was much better than I had in the years before that.
Did you get faster?
I got sick dificantly faster.
Yeah.
I run a bunch of some three hour marathons around the time I figured that all out.
That is a very fast marathon.
And for a period of time, I don't know if it's still the case, but maybe embarrassingly that was my It still is I think my only single author paper, and for a period of time it was most cited paper.
Well, you know, Einstein's most cited paper is the one where he describes entanglement and basically says, this proves that quantum is not a complete description of reality because there's no way it could be true and he was wrong.
Right, can't aspire to that necessarily, But anyway.
What's one tip that comes out of that? Like, do I is there like a model I could plug in? I ran my first marathon this year. I did not know about your paper. Is there something you can tell me, just qualitatively from it that I'm doing wrong?
Yeah, take a look. There's a little formula there basically that allows the average person to estimate their optimal marathon pace.
Boston ma On or New York Marathon. What do you like better?
Well, you know, I'm a native. I've run both many times. I've run Boston for the last twenty four years consecutively, and I've run New York. I think, I forget now how many times more than ten? And I love them both, And I'm not going to go I'm not going to say in public which one I love more. But they're very different. They're very different, and yeah that's all. That's all. That's all I'll say. But they are wonderful races and a lot of special things about both.
What is one thing we don't understand about the brain that you wish we understood?
So the question of what is consciousness? I think has been a big one in philosophy and neuroscience for a long long time. Right, you know, I think that the tools of bring computer interfaces are probably have already given, but certainly we'll be giving us in the next couple of years ways to answer that in a really rigorous
and quantitative way. And not just that, but I think to have an impact in disorders of consciousness, and so I think that's an area where rank of beer interfaces are going to have perhaps a surprisingly major impact.
What's a disorder of consciousness? I don't think I know that phrase, like help me, what does that mean?
Well, you know, I think many people are familiar with the koma, right, so people who are alive but not compismentus in the in the ways that you and I are when we're talking. That's just a dramatic example of that.
Has the work you've done, I mean, either as a as a brand surgeon or as in developing brain computer interfaces, how has that changed the way you think about consciousness?
If it has, I'm not sure it has yet, but at least not in a race I want to talk about in public. But I mean, watch this space carefully.
Say one more thing about that. That's it's very intriguing to me. I feel like there's something you're thinking that you're not saying.
I think a lot of it is public, and I
think in a really really interesting way. So i'd highlight some recent work or recently published work by Negoschiff and others demonstrating that some people who seem to be in a minimally conscious state actually have the ability to communicate if you give them the tools to do so, and that just has profound implications for the diagnosis of certain types of severe brain injury, for prognosticating, you know, the subsequent course of people who have such injuries, and all
kinds of philosophical, ethical, and really just most importantly practical aspects of how do we take care of people with that kind of severe brain injury, many of whom pose tremendously difficult questions to family and caregivers who can't predict what's going to happen next and can't communicate with their loved ones. And there's always this question in such situations, you know, is that the person we knew still there? And will that person come back, so to speak or not?
And answering that question, this is one aspect of getting at what is consciousness and how does it flunctually and how do we quantify it, and how do we read or restore it when it's lost or damaged. So, you know, that has been the realm of philosophy for most of human history, and I think it is very exciting for me now that's that's changed in the last several years.
And I do think that the technology of Breaker Beeterer interfaces is going to have an impact in making some of the discoveries that have come to light actionable.
Ben Rappaport is the co founder and chief science officer at Precision Neuroscience. Today's show was produced by Gabriel hunter Cheng. It was edited by Lyddya jene Kott and engineered by Sarah Brumer. You can email us at problem at Pushkin dot FM. I'm Jacob Goldstein and we'll be back next week with another episode of What's Your Problem MHM.