B (3:28)

That is a really interesting question. And one of the reasons neurosurgery is a little bit of black box is in many ways, people consider it sort of like extreme medicine. It's like a very small group of physicians that are taking care of patients. Fairly severe indications, a really rarefied field that takes very long training. In addition. But let's say we go back 100 years. We're talking about the era of Harvey Cushing, who's considered really the father of modern neurosurgery. I think that was a clear inflection point in the history of medicine, in the history of neuroscience, in the history of neurosurgery, really the beginning of what we would call modern neurosurgery. Why I think that Cushing was so powerful was his observation, in addition to his ability to do extraordinary surgeries. So in addition to being really an astute observer, in addition to being an incredibly technically skilled surgeon, I think he was also an incredible internist, too, diagnosing some of the first pituitary tumors and the effects of those on endocrine function. And then really, the era of modern tools of craniotomy, opening the skull to get access to brain tumors, and everything followed since then. The main categories of neurosurgery have to do with tumors, the vascular system, which are aneurysms and strokes and blood clot, spine. And then probably the most recent one is the one we call functional, which actually has to do with understanding the functions of the brain circuit, but also intervening to change how they work using deep brain stimulation or other ablation methods. And those are the really exciting new developments.

A (5:08)

And I think Harvey Cushing would be credited for the development of the electrocautery as well, wouldn't he?

B (5:12)

Absolutely.

A (5:13)

It's hard to imagine that you could operate without one of those things.

B (5:17)

Yeah. And not just in the brain, but anywhere in the body.

A (5:18)

Anywhere in the body.

B (5:19)

Yeah. It's like the key of controlling bleeding in any surgery, but particularly in the brain. It's a tricky thing. And so Harvey Cushing was just the starting point of modern neurosurgery. Then there's Wilder Penfield, who was an American, but really did some incredible work in creating the Montreal Neurological Institute. And that was really the beginning of what we'd call, consider modern epilepsy surgery, so surgeries that are designed to stop people from having seizures. And he popularized this thing that we all learn in medical school called the homunculus. It's this picture right of the little man there, and essentially the part of our brain that controls every muscle in our body and how it's laid out in that particular part of the brain, it's something that we all learn. He was also a brilliant scientist who helped us understand some of the basic things that we know about language and from a technical perspective, really popularized and developed the concept of awake brain surgery. And that's really something that's captivated me since medical school and what I now specialize in now.

A (6:26)

So let's fast forward a little bit into an era before you and I were in medical school. Call it the 70s and the 80s. What was the state of the art, call it 40, 50 years ago, with respect to the vascular management, the oncologic management of masses in the brain relative to today. So exclusive of the interventional side of things, just in terms of being able to operate on the brain, where were the plateaus in technology?

B (6:53)

What's interesting about it is some of the things that we do now are almost identical to the way that Cushing did it over 100 years ago. And then some of it is radically different. So one of the workhorse surgeries that we do is called a craniotomy. And that basically means where you remove a piece of bone temporarily, you place it at the end of the procedure to access something like a brain tumor that's in the frontal or temporal lobe. That's still being performed today and still really indicated. But where we are now, there's ways of using laser probes through very small incisions to get to deep targets in the brain to ablate them. There are ways of now even using focus ultrasound that can be targeted to specific nuclei in deep parts of the brain in order to control someone's tremor, for example. This is what we'd consider a relatively non invasive approach to do a neurosurgery. So things have changed radically, I would say. One other area where we have seen tremendous disruption actually is in the vascular neurosurgery field. So back in the 80s and 90s, you'd have a large craniotomy and incision probably about 7 to 9 inches long. Removal a piece of bone and then using an operative microscope to dissect down to the deepest parts where the blood vessels are coming to fix, let's say an aneurysm, which is essentially a ballooning of a blood vessel that when it ruptures, can be fatal. And so that is a lot of what I trained on. Nowadays, 90% of those procedures are now done through a catheter in the groin that's visualized. We put coils into the aneurysms to help secure them. We can now do stents. Huge change, actually. Now it's been able to now being able to retrieve and dissolve clots that are causing acute, severe strokes. Those are probably the most dramatic things that we've seen someone come in, not able to talk, paralyzed on half side of the body. In the old days, we would just give some medications, keeping our fingers crossed that that would work. It rarely worked. It was really the minority of cases that had helped. But nowadays there's a much bigger fraction of patients where you can put the device in, retrieve the stroke. And these are really game changing things when someone can go home the next day after such a huge thing. So we're starting to see things like stroke become more like heart attacks. The cath labs are not just treating heart attacks, but they're also treating what we call brain attacks or strokes. So some things are relatively similar to 100 years ago, and then some things have just been totally changed.

A (9:33)

So if 30 years ago a neurosurgeon was doing a craniotomy virtually every time they were addressing pathology, today it might be less than half the time.

B (9:43)

Yeah, that's right.

A (9:45)

That's not a dissimilar parallel to what we see in other parts of surgery. I was just talking to a vascular surgeon a couple of weeks ago, finished his training around the time I did, and I said, you know, how many open surgical procedures are you doing? You know, I was talking about AAA's and all sorts of, you know, fempops and things like that. And he said, yeah, we do very little open these days. It's virtually all done with stents, which again, even ca like carotid arteries, the whole thing. I was really blown away at how little they are operating now. Meaning operating in an open sense. Obviously, they're still intervening.

B (10:17)

Yeah, absolutely. I think what's happened with surgery is that this is not a trend. This is the force of evolution that is guiding us towards things that are more minimally invasive, less collateral damage to get to the targets and getting people back to life sooner. And it's a very exciting time, actually, to be in medicine with all this technology that's coming on board. If you're okay with that change, it's absolutely thrilling time. Yeah.

A (10:43)

Now, I know this is not your field of interest, so feel free to say, yeah, I don't know enough about it, but whenever I think of the brain, I think of GBMs. I think of these awful tumors, which I guess for the listener, we can explain what that is. So maybe tell folks what a GBM is, why a GBM is truly one of the cancers that gives cancer a bad name. And I guess my real question for you is, given that traditional surgery has historically never worked for this tumor, you simply can't resolve it. And you think about the transition away from craniotomy, big open procedure. Is there anything on the horizon for GBMS to render them less lethal?

B (11:19)

Yeah. So GBM stands for glioblastoma multiforme. And it's a mouthful of. If you break it down, what it's referring to, the glial part of that word refers to the cell origin. The brain has different types of cells. And if you look in the big buckets, there's neurons, which are the ones that primarily are the ones that allow us to do thinking and function. And then there's a large population of support cells that we call glia. And that's that first part. Glioblastoma originates from those support cell population. Multiforme refers to these original descriptions, histologically, of the tumors that really showed multiple form, multiple histology. Some of the key features of it are the necrosis. The tumor grows so quickly that it outstrips its blood supply, and in its wake, it leaves cell death, what we call necrosis. So, like Hugh alluded to, it really is a terrible disease and condition. We are making progress and specifically around understanding what causes. So just 10 years ago, you would remove one of these tumors, you send it to the lab, and you could get the diagnosis that this is a glioblastoma. Now, in most academic medical centers, you'll also get a genetic profile of the tumor. So nowadays we actually know specifically what kind of mutations are involved in the tumor. And that's going to be really critical for this next chapter, which is using those genetic alterations actually to tailor and personalize chemotherapy and more. So this has big implications because we're now moving from an era where we use a visualization of the histology now to this molecular profiling, which is more Mechanistic. The new chemo agents are really going to be targeting mechanisms, as opposed to general things like cell cycle and metabolism and things like that. So these are the things that are changing, and we need it to change faster. There are also really exciting things that we're seeing around, new ways to train the immune cells to target things. It turns out that glioblastomas actually suppress parts of the immune system. So they kind of like growing in stealth, and they activate molecules and cells in a cloaked way that can't be recognized by immune cells anymore. And so if we can basically allow the tumors to be recognized by the immune system, that could be something that really unlocks therapy in the future, too. But the things that we do know that work pretty well right now, at least in terms of prolonging survival for patients, and really meaningful survival actually still is around the surgery. We do know that the more extensive the resection, the longer the survival is. And that's been really well characterized now, but it's not curative. Like you said, we can remove 99% or even 100 and beyond what we see on the MRI. Unfortunately, there's usually microscopic cells that go beyond what we can see on the MRI that are still there and over time will repopulate the tumor. It is a really complicated and tough disease, but we're working really hard on it.

A (14:25)

Do we have any idea what predisposes an individual to this from a risk perspective? Short answer is no, because it afflicts young, it afflicts old. I mean, I've watched children die of this, teenagers, people in midlife, people at the end of life. It seems to have no apparent pattern.

B (14:40)

Yeah. And part of that has to do with its mechanisms. It's not something that we consider as a heritable risk, but what it does rely on is a set of mutations, and it's rarely the same set. Right.

A (14:53)

It's a very polygenic condition.

B (14:54)

Exactly. And that's what makes it really tricky to treat. When we talk about glioblastoma, we're actually not talking about one thing. We're talking about a system of genetic alterations that together have cascaded into the form that we see.

A (15:10)

And I suspect we'll come back to this, Eddie, but you've alluded to chemotherapeutic agents that can be used, whether it's to treat glioblastoma or anything else, including mets of other epithelial cancers that spread to the brain. The blood brain barrier poses a challenge for treatment. Do you think the future lies in Treatment within the csf. So treating directly inside intrathecally or directly into the central nervous system, or do you think it's designing drugs that cross the blood brain barrier? I mean, what do you think the future looks like?

B (15:41)

I think it's going to look like all of the above. This is a situation where we do need to look at all possible options. This is not like the kind of thing where we're thinking like non invasive or minimally invasive. Really something that will work is the first priority. One of the technologies I'm really interested in following how this develops, and we're doing research on this at UCSF is using focus ultrasound. So most people know about ultrasound to diagnose, but if you change the energy profile of it, you can actually use acoustic energy through an ultrasound to actually open up the blood brain barrier in targeted parts of the brain. And so there is a lot of development on using that as a way to do delivery as opposed to putting a catheter or something directly in the brain. And then with that set of new agents that can be really molecularly specific to get to targets. Once you open up that blood brain.

A (16:34)

Barrier, what attracted you to neurosurgery? Was it something you knew you wanted to do when you went to medical school or did you figure it out while there?

B (16:40)

I had a sense it was probably latent. I always knew that I was really interested in neuroscience, the general field. It wasn't until I was in medical school that I was actually exposed to it. And I remember really clearly in my first year, I had this neuroanatomy, Professor Diane Raulson, who was really incredibly kind person who was patient with me as we were learning. You probably remember in med school, like learning hundreds of different parts of the brain, anatomy, all of which I've forgotten.

A (17:12)

I know there's a brain stem somewhere in there.

B (17:14)

There's somewhere. Something like that. Yeah. So that's part of our ritual, right, in medical school to learn all of those terms and locations. But as you know, certain teachers just make such a huge difference. She took me to the operating room one day and I saw one of my mentors. At the time I was just a student, but he ultimately became my mentor, Dr. Berger, doing Awake surgery on a patient with a glioblastoma. The surgery itself, I thought was pretty interesting, but the part that left me awestruck and the part that basically made it very hard for me to sleep for a couple days was really just seeing an exposed brain. What the cortex looks like. The cortex is the outermost part of the brain. It pulsates, it moves. But those are not from the mechanics of the brain itself. Those are all just from the breathing and the heart rate, et cetera, the blood flows coming through. So the thing that really struck off for me was seeing a patient talking and not fully comprehending, but really being in awe of the computations that must be happening in this part of the brain. And it's not like you're looking at a computer. You're looking at essentially an organ composed of biological cells, 86 billion, to be precise. You know, how many neurons there are in the human brain. So that scene, to me, was deeply inspiring, and I was basically hooked. I was so hooked that I didn't really understand what I was signing up for, because the training for it after that was pretty difficult, I have to say. Seven years, but it was worth it. I love every minute of it. And I'm still learning, of course. Whereas at the very beginning of a new inflection point in neurosurgery, which is understanding how the human brain works, there.

A (18:59)

Was an epiphany you had at some point in residency, wasn't there?

B (19:03)

Well, I think there's an epiphany about. We have this access, really privileged access to use the information, what we call brain mapping. Basically, we do the brain mapping because we want to be very precise about how we're approaching, for example, brain tumor or a spot of the brain that's causing seizures. And we do the brain mapping so that we can map out the areas that are really important for language or the ability to move your arm. That's what we call the brain mapping. And we want to identify those areas so we can protect them during the surgery. At the same time, do the maximal resection. Like we spoke about earlier, the more that we can remove the tumor, the longer the survival. The more that we can remove of the seizure zone, the more likely someone is going to be cured of their epilepsy. But in neurosurgery, there can always be a cost, and that cost would be paralysis or aphasia, which is a condition where you lose the ability to speak. We're always trying to balance, is it worth it to go that extra couple of millimeters versus not. And in many cases, these are really profoundly important decisions that have to be made right then and there in the operating room. And brain mapping is the way that we figure this out. In the old days, Wilder Penfield, 150 years ago, 120 years ago, would use an electrical stimulator and would apply it to the cortex. And that will temporarily activate or disrupt the function of a specific part of the brain while someone is trying to speak or move. And that's traditionally how we've done mapping. And that's one of the tools, the techniques we still use today in order to make sure patients are safe during these procedures. One of the revelations I had during residency, of course, is that I think we can do a lot more than just applying stimulators to do the mapping. We've developed technologies to record from the brain that allows us to not only do the mapping, but, but also is really the first window that we have of understanding essentially how neurons work, how they convey information about words. For example, like in the conversation we're having, there's a part of your brain in the temporal lobe, which is right above your ear on both sides, the one on the left in particular, you're right handed, so 99% of right handers are dominant for language on the left side. And there's this one spot in the temporal lobe, which is just about 2cm above your left ear that's processing all the words that I'm speaking to you right now. And so we've used this technology not only to map those critical functions. That's where the science was, I would say, about 10 or 15 years ago, figuring out where these functions are in the brain. And now we've moved the science to understanding how those areas work by a progressive evolution of new technologies to get us to higher and higher resolution. And what I mean by that is we can measure the neural activity of cells and cell populations and then link them to, for example, different consonants and vowels. And that's been really an extremely exciting development in human neuroscience.

A (22:08)

I want to back up and just have people understand how you even do awake surgery, because the traditional way that surgery is done requires general anesthesia. And general anesthesia typically requires three things. It requires one type of medication to blunt pain, another type of medication to block memory, and another type of medication to paralyze you. Now, of course, if things go wrong and things have gone wrong, sometimes patients are paralyzed, but they feel pain, but they can't communicate it. And these are these catastrophic but fortunately very rare events that occur in anesthesia. But correct anesthesia is done where a patient has no sense of time or memory of anything. They can't feel anything, and they can't move, which means they're actually safe. That's to save them as well. Help us understand how it is that you can do surgery without all three of those conditions being present, like I.

B (23:03)

Said in the beginning, this is extreme form of medicine, extreme form of surgery. And the way that, in a nutshell, it can be done is the brain itself doesn't have any pain receptors. So the pain receptors are the ones that are in our nerves, that are in the scalp, that are throughout our body. These are actually the way that we perceive pain and touch. I think it's paradoxical to many people at first, but the brain itself, which is processing that information in the body, actually doesn't have those receptors itself. So the way that we typically do this is to numb the scalp. We use things like when you go to the dentist's office, like lidocaine, we can inject around the site of the incision. The bone, by the way, doesn't have any pain receptors itself either. The membrane on top of the brain that we call the dura does have some pain receptors. So sometimes we have to be sensitive around that and do some local anesthesia around the dura. And interestingly, the brain tissue itself doesn't. There are some other areas, like around the blood vessels that can be sensitive. The membrane, the dura, is sensitive. So there are areas, but they can be numb. And so this is a really important fact that allows us to do these surgeries awake when it's necessary.

A (24:21)

So the patient is rolled. And I've seen these. And I'm just blanking on. Exactly. The procedure. So the patient is rolled into the. Or, they're not intubated. Correct.

B (24:30)

They're never intubated during this.

A (24:32)

Yeah. This is a patient who is laying there wide awake. No endotracheal tube.

B (24:38)

Right.

A (24:39)

Maybe a Foley catheter for some comfort.

B (24:41)

Yes, Foley catheter.

A (24:42)

Okay.

B (24:42)

Yeah. And usually Foleys are not that comfortable.

A (24:44)

Exactly.

B (24:45)

But primarily so that we can monitor the urine output during the surgery.

A (24:48)

You begin by making your incision. I mean, drawing where you want to make your incision, and then literally just doing this as though it's a local, like you're having a lipoma removed or something. You're literally just covering the lidocaine and epinephrine across the scalp. You're bovying down to where you need to go. Once you get to the bone, you can start to literally put a hole in and start to saw across your holes.

B (25:12)

Yeah. Just to add a little bit more detail to that, which is that usually the head is fixed. So it's not like someone's sitting in a chair and we're just doing this while they're moving around. But we have a head holder that.

A (25:24)

Fixes the head, the patient is somewhat sedated, and then you can lift the sedation.

B (25:28)

Yeah, exactly right. And so we do a light level of sedation, like propofol or like propofol, but at much, much lower dose. So it's not a general anesthesia dosing. It's a very, very light dosing, the party dose.

A (25:42)

And that way it allows the anesthesiologist to stop it when you say, hey, because we might need an hour to get in. At that point, it's okay for them to be in la la land, but then I want it off once we have to get inside.

B (25:54)

Absolutely. The period that someone is actually awake during the surgery is usually only an hour or two, even if the surgery's like six or eight hours long. And primarily for comfort, we'll do sedation at the very beginning. We'll have the sedation turned off so the patient can be fully awake for.

A (26:10)

The napping, and then you can ramp up the sedation to finish the procedure and close them. But again, it's all done at the level of a colonoscopy, not the level of general anesthesia. That's right, yeah. Again, we were talking before the podcast how my second month of general surgery, I did neurosurgery, meaning we rotated through it. And one of the things that blew my mind was how. It sounds silly, but when you look at textbooks and you study the homunculus and you look at all of the vasculature, and then you actually look at the brain, it's just like any other organ. It's just kind of a blah. It's like looking at the pancreas for the first time. You're like, that's it. How do I know where everything is? I guess what makes it different is there's probably no part of the body where the real estate matters so much. When you're operating on other parts of the body. For example, if you're operating on the heart, you can really see what you're doing. You know where the left anterior descending artery is. You know where the occlusion is. And even though it's very technically complicated surgery, there is complete anatomic clarity of what is happening. I think the thing that struck me the most the first time I saw neurosurgery was, how the hell do they know what they're doing? Like, how many billion cells did we just lop off there? And obviously, this speaks to what you're talking about from a functional standpoint, but a lot of times you're not doing that. So if A patient has a meningioma or some other tumor. How do you bracket that trade off? So do you sort of say, look, there are places where you never want to have a tumor. For example, right above my left ear. That would be a really difficult place to have to resect because the real estate is so precious. And that's where we're going to probably recommend doing an open awake procedure to help guide us. Is that how you're using that?

B (27:54)

That's exactly right. And so the real estate is critical. That's an understatement. But that being said, there is some really expensive real estate in there, and there's also some cheaper real estate.

A (28:05)

But that's. I guess that's my point, Eddie. It's like. That's sort of like telling me about Manhattan.

B (28:10)

Yeah.

A (28:11)

Like there's no cheap real estate in Manhattan. There happen to be areas that are $10,000 a square foot, but there's probably nothing less than 4,000 a square foot.

B (28:20)

So there's this popular idea that we only need 10% of our brain. I'm sure you've heard this.

A (28:25)

I've heard this, and I don't know what it means. It sounds like malarkey to me.

B (28:28)

Right.

A (28:28)

That might mean to stay alive, to respire, you might only need 10% of your brain.

B (28:33)

So what it really means is that there is maybe about 10 or 15% that is very critical for our basic functions, our ability to move, to talk, to see, et cetera. It's actually a lot more than that. But it's also referring to this point that there are parts of our brain actually, that are extremely redundant with other parts of the brain. So the frontal lobes, for example, we do surgeries there routinely. And oftentimes people really have no effect.

A (29:00)

Even in terms of judgment? Even in terms of.

B (29:02)

Absolutely, yeah.

A (29:04)

Because we always think of the frontal lobe as where we have sort of executive function and where we have the ability. We always joke, like one of my friends in med school, we said he had no frontal lobe.

B (29:13)

Exactly.

A (29:13)

He just couldn't stop saying the most inappropriate things.

B (29:16)

And don't get me wrong, the frontal lobe actually has a lot of critical function for executive decision making, impulse control, et cetera. But my point is that it's redundant, meaning that different parts of the frontal lobe actually have similar purposes and similar role. And so, for the most part, a lot of our patients can accommodate a fairly large surgery, sometimes even removing the entire frontal lobe.

A (29:38)

Both sides?

B (29:39)

No, not both sides, really. Usually these pathologies are only on one side.

A (29:43)

If you took the entire frontal lobe from the left or right side. Would there be a substantial difference?

B (29:49)

I've done that many times, just so you know. And it really depends on the case and scenario. If someone's been having something that's slower growing there, and there's been time for the brain to reorganize what we call plasticity, a lot of those functions will essentially no longer be in that right frontal lobe and they've moved to the left side.

A (30:08)

Wow. What is the mechanism by which that happens?

B (30:11)

Time and function, meaning these things don't happen overnight. They take sometimes weeks and years. But basically what happens is some neurons get lost over time and then others will compensate in terms of that function.

A (30:26)

But how does that actually happen? So let's posit that we have a slow growing lesion in the left frontal lobe. What is the left frontal lobe doing to communicate with the right frontal lobe? To say, hey, these neurons are being compromised. Their function is deteriorating. You guys need to pick up the slack. How is that message being transmitted?

B (30:47)

Part of it is that both parts of the frontal lobe, for people, most people are both doing the function most of the time. So it's not like it's just transferring the information. It's that both sides were originally involved in those functions. And then one side gets weaker and the other one has to pick up that slack. At a cellular level, this is what we call synaptic plasticity. The weights, you know, essentially make up who we are. These are just the weights that neurons use to communicate with one another. All of our learning is towards shaping that weighting of synapses that occur where neurons touch each other. And that can happen, that can change throughout our life. Every time we learn a new word, those are new synapses that have formed that were never there. New connections. Precisely. From the left to the right side, there is this structure that we call the corpus callosum. It's an information highway that connects the left part of our brain from the right side. There was a Nobel Prize, Roger Sperry, who'd done really incredible early experiments describing patients who had surgeries where you split that. And in certain instances you have this phenomena where people essentially have two functioning brains, but they're not communicating to each other. So it does require that there is this connection between the two areas where they're being reorganized.

A (32:09)

Now, outside of epilepsy, why else would the corpus be severed?

B (32:13)

That's really the main one that we use it for.

A (32:16)

Can you describe how patients that undergo that procedure behave? It's very fascinating.

B (32:22)

So there's A phenomenon that we call a dissociation syndrome. The clinical indication, the medical indication for why someone would undergo this nowadays is that some patients with seizures have severe seizures where they fall down, what we call drop attacks. And usually what that means is that the seizure is spreading so quickly across the brain that people lose the tone in the body and then basically fall. And why that becomes a problem, the injury of the seizures is that people actually injure themselves. So it's not uncommon for people who have these kind of seizures actually to be wearing helmets all the time because they're at such high risk of falling.

A (33:03)

These are just medically recalcitrant seizures. They cannot be prevented with any degree of.

B (33:09)

That's right. That's absolutely right.

A (33:10)

I see.

B (33:11)

Without any kind of medication, and these are particularly ones that there's not one small spot that's causing the seizure. It's the whole half or quadrant of the brain. But the problem is what a seizure is, is basically when you have this very uncontrolled synchrony of a large mass of the brain cells. So normally, if you think about the brain and the neurons within the brain, it's like people in a stadium. They're having their individual conversations. That's the way the brain normally works. But let's say all of a sudden everyone's doing a wave and something hyper coordinated. All of those normal conversations are now gone. The brain has now become hijacked by this other phenomena where everything has become very coordinated. That's why people lose consciousness, because all the normal function is basically shut down. And the way that it can become synchronized is through its connectivity. Every cell connecting to its adjacent cell and every cell connected to all the other cells in the brain through the things like the corpus callosum that connects the left to the right. And so when you get that hypersynchrony, people can essentially lose consciousness almost instantaneously. So one of the reasons, historically, why the corpus callosotomy was invented in the very first place was to sever the connection between the left and right hemisphere.

A (34:33)

Which doesn't stop the seizure, it just limits the spread.

B (34:36)

That's exactly right. It doesn't stop the seizure, but what it does is stops the propagation, the very fast propagation of the seizure from one side to the other. And in order for someone to lose consciousness, you basically have to have both sides of the hemisphere or a deeper structure like the thalamus that's basically in order to have consciousness. You have to have both hemispheres out in order to lose consciousness, or a deeper structure in the thalamus or something like that. And so these kind of drop attack seizures are ones that people black out, fall. And one way you can actually dramatically stop a lot of that is disconnecting the left from the right hemisphere.

A (35:17)

And so how does that patient, how is their life different, aside from the fact that hopefully their drop seizures are gone? What's the change in the way that their left and right behave now? Disconnected most of the time.

B (35:29)

When we do this nowadays, we disconnect about the anterior two thirds of the corpus callosum. And the reason why we don't typically transect the whole corpus callosum is because of some of the side effects that people can have. And it's what we call a dissociation syndrome, where you can basically have a dissociation between what the left brain is doing in the right brain. So, for example, someone essentially feeling something on the right hand, which is processed by the left part of the brain, and the right part of the brain really having no awareness of what's going on. People can get by with that, but it does affect how they can get along. So nowadays we try to just do the front part of it and leave the back part. That helps reduce some of those side effects.

A (36:15)

But does it solve the initial problem of the seizures? Yes.

B (36:18)

No, it doesn't cure the seizures, but it really just stops the propagation of the seizures so that people don't lose consciousness.

A (36:24)

Sorry. By leaving one third in the posterior still adjacent, it prevents the propagation across the hemispheres.

B (36:31)

In many, many cases. In some cases nowadays, still, we have to do a total callosotomy. It's a very delicate surgery because the corpus callosum that connects the left and the right, it's not sitting on the top of the brain. It's actually.

A (36:43)

Yeah, it's very deep.

B (36:44)

It's very deep. So to get there, you actually have to physically separate the left and right hemisphere. We do that from the top. We do a craniotomy that's centered over the midline, but it can't be right over the midline because we have a large draining vein there called the superior sagittal sinus. So we have to either choose the left side or the right side. And then we have to very carefully separate the left from the right and through that narrow corridor, transect those connections.

A (37:11)

And what's directly underneath it that prevents you from just running that Bovie. A little too hot?

B (37:17)

Oh, well, there is a blood vessel that runs along the top of the corpus callosum. And that's actually the most critical Part of the surgery is that we separate those two branches, those pericollosal arteries. Those arteries are really important because they supply the part of the brain, the medial frontal cortex. And the part of that, that is part of the motor cortex actually is what supplies and controls our legs. So if you have a stroke, let's say as a side effect or complication of that procedure, then someone would be paralyzed in the leg. So it's a fun, delicate surgery. It's amazing to see that exposure of the corpus callosum. It's glistening white. That's how we can see it. And it's very distinct from the cortex because it's really clear white. That white comes from the myelin. It's a heavily, heavily myelinated structure because it's conveying information from the left side of our brain to the right side on the order of milliseconds, a super fast connection.

A (38:15)

Do you ever think philosophically about what the implications are for human consciousness by the fact that you can do a complete transection of the corpus and seemingly produce two people?

B (38:26)

That's right. Or potentially two consciousnesses?

A (38:29)

Yeah. What does that mean?

B (38:31)

Well, I think that goes back to a harder question of how do you define what consciousness is in the first place? And this is where there's a lot of philosophical debate about that.

A (38:40)

Do you trouble yourself with such debates?

B (38:42)

Not really.

A (38:43)

I can't because I can't wrap my head around it. It's above my pay grade.

B (38:47)

I do think about it from the practical, clinical perspective, not so much the philosophical. The clinical one is like, is a patient in a coma or not and why and how do we get them out of that? Traumatic brain injury, certain strokes, epilepsy, et cetera. We think about consciousness from that perspective literally all the time, every day. But from the philosophical, I don't lose a lot of sleep over that one.

A (39:13)

I lose a little bit of sleep over it. Let's talk a little bit about brain computer interface. You've mentioned it already. I hope I'm not insulting people when I say this, but if we're going to be brutally honest, we should at least acknowledge that that medicine to date has been pretty unimpressive when it comes to treating neurodegenerative disease. So whether we're talking about Alzheimer's disease or even other non degenerative forms of dementia, whether we're talking about Parkinson's disease, Lou Gehrig's disease, I mean, we just don't seem to be able to treat these diseases. So whatever medications we throw at these things, maybe in the case of Parkinson's disease, we can delay progression a little bit. But would you agree with that assessment that the traditional approach to treating these diseases has been largely unsuccessful?

B (39:58)

I would largely agree. With a caveat that I think a lot of progress is being made to understand what's going on. And from that, I think there's a lot of promising therapies. I would generally agree that within neurology and neurosurgery, traditionally, therapy has really been designed to stop things from getting worse or slowing down progression. Replacing function has never really been possible until very recently.

A (40:26)

Yeah, I guess what I want to understand from you, because I think this is something that you know more about than anyone, or certainly among the people who would know the most about it, is do we need to revisit our approach to these diseases more from an engineering perspective than from a peripherally administered medication perspective? So the traditional approach to treating disease would be medication. You take an injection, you take a pill, you take something and you hope that enough of it gets across the blood brain barrier and it starts to treat the condition at hand. But it's hard to look at a patient with Parkinson's disease, which is a motor defect disease, admittedly, that stems from the cns, and not at least think this is a functional condition. Why isn't there, or is there an engineering approach that could be taken to this?

B (41:19)

It's a good question. And let me put it this way. Medications are always going to be a really important goal, not only to reduce symptoms, but hopefully find cures. But there's this whole other class of therapies that are coming online that have to do with this other property of brain cells, which is very different than, let's say, the pancreas or the liver. It's the electrical side of the equation. So there's the chemical and biological side, but then there's this electrical side. And the brain is an electrical organ. Our thoughts are really dependent on these electrochemical kind of processes that happen at individual neurons and the collection of them. So there's this large and growing field that we call neural engineering that is really trying to use computers, sensors, chips, in order to interpret, eavesdrop on how the neurons are signaling to each other, regardless of their pathology or the biology. But just what are they saying to one another? Can we eavesdrop on that? Can we interpret it? Can we decode it? And then more importantly, can we use that information actually to guide more normal signaling? Why this is potentially important is that at the end of the day, the function is from that electrical Activity, it's the propagation of those action potential by neurons which gives rise to our thoughts, our ability to communicate, our ability to walk, move our arm. Without that, it's not there. So I would say neuroengineering as a complementary to the biological or pharmaceutical approaches.

A (43:03)

Eddie, if you and I were mapped simultaneously together, this question might not even make sense. So please feel free to adjust the question to make it logical. But I think you'll understand what I'm trying to ask. All of the electrical activity of my brain could be mapped to a computer, and the same could be done with yours. And we were thinking the same thing. So it was an experiment where we were both told to think the same thing. Peter. Eddie, we both want you to think about sitting on a beach with your feet in the sand. It's hot. As descriptive as you want it to be. Would the outputs on the computer screen be similar? Would the computer be able to appreciate similar electrical output? Or could two people that are doing the best job they can to have the same thoughts not be able to produce that? In other words, is there a one to one map of thought to electrical activity?

B (43:54)

The short answer is actually both. So in that example that you gave, if both of us are looking at the same picture of a scene on the beach. Yes. The same part of our brain is going to be processing those images. In the very back of the brain that we call the occipital lobe, the primary visual cortex is going to be parsing that space into what we call retinotopic space, like essentially where those different pixels are located in the image. That part is going to be highly conserved, not identical, but highly conserved between your brain and mine. It's where these computations go further upstream, where they become much, much more differentiated, much more specific to our brain. Much more dependent actually on our history, history of thoughts, our personality, everything that's interacting with the rest of the brain. I'll give you a great example. The way that you may hear Spanish or French or German is going to be very different than someone who is a native speaker of those languages. Your brain is going to process some of those sounds. You'll hear them, but you're not going to be able to pick out the words very easily.

A (45:07)

Or the way I hear an engine versus the way my wife hears an engine.

B (45:11)

Absolutely.

A (45:12)

I love the sound. She's mildly annoyed by the sound. We're hearing the same thing.

B (45:16)

Absolutely, yeah. So there are parts that are going to be very similar, like how we process some of the sensory attributes and then the further you go deep into the system, the more it becomes very, very tailored. Some of this is hardwired. The way that our visual system early on, a lot of it is hardwiring. It's heavily influenced by what we see.

A (45:38)

Seeing a snake should automatically produce a negative response. That doesn't have to be learned in theory. I assume evolution has probably hardwired us for that.

B (45:47)

There are some things that are instinctual.

A (45:50)

Certain odors we'd be hardwired not to like. Things that are going to smell rotten or something like that.

B (45:54)

Oh yeah, absolutely. There's a lot of those things that are very intuitive.

A (45:57)

Now going back to the. We're showing you the picture of the beach. How much do you change over time? So if we did that experiment when you were 10, 20, 30, 40, 50, would that also change?

B (46:10)

It will change, but less, I think, over time. These things become refined and over time actually lose their refinement. So as we age, some of those representations actually become less clear. If we talk about hearing, for example, there are a lot of people in the population over time it's very hard for them to be in a crowded restaurant where there's a lot of background noise, competing conversations going on. And yet these individuals can have perfect hearing.

A (46:37)

So signal processing is becoming the problem.

B (46:39)

That's exactly right. It's not an ear problem per se, it's a perceptual problem and largely in the brain. And that has to do with how that information, like the fidelity of those.

A (46:51)

Is that a harbinger of something bad independently?

B (46:54)

No. But we do know that when people have that problem, they tend to be more socially isolated. So there's a lot of secondary things that happen. We do know that when people have hearing loss and it's unrecognized, a lot of people have unrecognized hearing loss. And what people don't fully appreciate is that if you don't have access to communication, to conversation, your brain is not getting those same signals. It's becoming deprived. And what we do know through many studies now is that the cognitive effects of that hearing loss actually can be quite profound. It accelerates age related memory loss.

A (47:36)

We actually internally in our practice believe that that is causal to cognitive decline. Now there was a study that came out about two years ago that suggested it wasn't. Although the study had a partial retraction, the methodology was a little flawed, but to my knowledge, I don't know if it's been repeated. The question being, of course, is if you correct hearing loss, let's say you randomize A group of people with early mci and you correct hearing loss, do you correct or prevent or reverse it? And again, if there's causality there, you would expect that you would. What about with visual. As people get older and they develop cataracts or things of those nature and their visual acuity goes down, does it have the same effect on depriving them of enough neural stimulation to maintain, or is it not as much because it's not a language issue?

B (48:25)

It's not as much. And I'm less aware in the prevalence of something that's age related, just in the visual cortex, for example.

A (48:33)

So let's go back to brain computer interface. How would you explain this to somebody at a party if they said that sounds pretty high tech, but what is it?

B (48:40)

Okay, let's just break apart the terms. Brain refers to really any kind of thing that interfaces with the cortex or the deeper structures. The computer is a digital device on the outside. A lot of people now call this bci, brain computer interface for short. It's a very messy term because it could mean a lot of different things. I think in a nutshell, what it means is for most people, a system that is recording from the brain, whether it's non invasive from the scalp or something that's fully invasive within the brain itself, and connecting those signals to a computer that analyzes the signal and then does something with it. In many cases of BCI research, the application is, for example, to remove a computer cursor. Or the research that we've done is to replace speech words for someone who's severely paralyzed and unable to talk anymore. And so it's about interpreting brain signals and then using a computer to interpret those signals and then transform them into a form that's useful to us.

A (49:49)

So in that example you gave, you're describing a patient with aphasia who can't speak.

B (49:56)

Let me be very specific about that. So a lot of the work that we've done is on people that have a severe form of paralysis and aphasia. We typically refer to as someone who's got, let's say, a stroke. In the language centers of the brain, where we focus recently is on patients that have a severe form of paralysis, like als. So there the problem is they have largely normal language, but they can't get those.

A (50:20)

Can't get the motor signal out, can't.

B (50:22)

Get the motor signal out to the vocal tract, the lips, the tongue, the jaw, the larynx, those descending fibers are severely affected by als. They degenerate. And that's why people Progressively become paralyzed and lose ability to speak. An important part of that is that they lose ability to speak, but they still have full cognition.

A (50:42)

Yeah. And for that individual, by attaching a computer to their brain, you're able to hopefully extract in written cursive text, whatever, across the computer screen what they're wishing to say.

B (50:57)

That's right.

A (50:58)

Okay, let's talk about how that could possibly be done. You mentioned earlier there are at least two broad ways to extract that information. A non invasive way, where presumably you're putting electrodes all over a head that's as well shorn as mine. Alternatively, a very invasive way where you actually remove the scalp and you lay these things on the cortex itself. Correct.

B (51:21)

Yeah. So the range would be eeg, which is where sensors are placed on the scalp directly recording non invasively. You can remove them at any time. And then the far other extreme is electrodes that are actually placed into the brain. The most ecog. ECOG would be electrodes that are on the brain surface. That's short for electrocorticography. And that's where we've done the vast majority of our work in my lab.

A (51:49)

And that's just placed on the surface of the cortex, under the dura. On the cortex.

B (51:53)

That's absolutely correct. So what's nice about that is that you don't have the injury to the brain itself from the insertion of the electronic electrodes. It's a stable recording over time. We now use ECOG devices to essentially help people with seizures, for example, where you can basically have a pacemaker now that records from the brain surface and then stimulates to help stop the seizures.

A (52:16)

And this is a fully implanted device.

B (52:18)

It's moving towards that. So the work that we've done in our clinical trial is using an array that's surgically placed but connected through a port. We call it a percutaneous port because it's actually physically attached and anchored to the skull. An array on the brain. It comes out the dura and is anchored in the skull.

A (52:40)

Where does the port exit the body?

B (52:41)

Right on the top of the scalp.

A (52:43)

How do you prevent infection with such a close.

B (52:45)

Yeah, it's a really good question. And that's what the main problem with this early prototype bci. And it's our group, there's other groups around the world that are using similar things primarily to show if it's possible actually to code brain activity for useful purposes. So what's happening right now in the field is a lot of these technologies are now going to become wireless over time. But you're absolutely right. One of the main reasons is that we want to move away from the percutaneous. We want to move away from the ports, which are infection risks on top of other problems, and move to things that are fully implantable, fully wireless.

A (53:25)

How long do you feel you're away from that?

B (53:27)

Basically, about a year. Okay. We've been working on it for quite some time. And so it's a really interesting time where we're seeing a convergence of like, what's possible with electrical engineering, high bandwidth wireless process way beyond what we can do with Bluetooth. Advanced electronics that now allow us to print some of these sensors on a substrate that is thinner than a piece of paper, really, really small, and on a substrate that can conform to the convolutions, the different peaks and valleys of the human cortical surface.

A (54:01)

So what is the trade off between ECOG and sensors inserted directly in the brain? What's the resolution difference?

B (54:09)

Well, that's a very important question that we and many other people are trying to figure out right now. Most of the time when people are putting an electrode into the brain, there has to be some gain for that. And usually that's for recording a higher resolution, usually trying to record the activity of single neurons. A single cell.

A (54:31)

How can you isolate a single cell?

B (54:34)

Really small electrodes, super small electrodes. We do a lot of work with this in our research. The challenge for the field, it's just been that it's very hard to stably record from single cells more than a couple of hours or days. So that's one challenge. The other challenge is that when you put the electrodes into the brain, it can create a reaction. Those glial cells that we talked about the very beginning, those support cells, they actually have immune function as well. They detect that there is a foreign body and they'll activate and they'll react to it, create a scar around the electrodes. So the advantage of having electrodes in the brain to do this very microscopic kind of recording is that you can get a finer signal from single cells. The disadvantage is that it can create a reaction that reduces the fidelity of those signals over time. One of the reasons we've been most interested in using these sensors on the brain cortex is that we've learned over time that if you don't have the electrodes penetrating through the pial surface of the cortex, that's the outermost, very thin membrane that's covering the cortex. If you don't have anything going through that, you can avoid a lot of those immune reactions, avoid a Lot of that scarring, preserve the function that's underlying. But this is something that we're actively trying to understand.

A (55:53)

So just to give me a sense of magnitude, if EEG on the surface is 1:1 unit of resolution, what would ECOG be and what would implanted electrode be? Is it 1 10, 100? What's the scale at which you're thinking of that resolution?

B (56:10)

Well, I would say from the scalp, let's say we just arbitrarily call that one. And then you think about what you could do with the ECOG. I think we're really talking about, let's say, 1,000 times better resolution. We've been able to answer very fundamental questions, actually, about how the brain works using those kind of surface recordings in a way that's impossible with surface scalp electrodes. And then once you go take that further to single neurons, then you've got another resolution, probably 6 to 5000.

A (56:41)

The big jump is just going from an EEG to an ECoG directly to the brain. That's a three log change, whereas you're a 5x change going deeper.

B (56:51)

And so one of the reasons for that is the skull and the scalp are a major loss of signal. The signals are small to begin with, so once you're trying to interpret them through the skull or scalp, they're basically gone and very diffuse too. So trying to understand like where they came from in any precise way is almost impossible. When you're recording directly on the surface, you're basically at the source itself, the cellular level. The single cell recordings are terrific for trying to understand that ultra fine resolution. Primarily in the case that we use them for, is for research, primarily to understand what's happening at those units. But still to this day, there's really no way that you can chronically and stably record from the same cells because.

A (57:37)

Of the immune reaction.

B (57:38)

Also because of how fine of a problem it is, how precise it has to be. We're talking about a single cell a couple of microns in diameter, and you've got an electrode. Any micro motion at all, anything changes that. And so typically, what we see with a lot of those systems that record from those is there's a lot of turnover from day to day or hour.

A (58:02)

To hour, meaning you're drifting between which neuron you're recording in.

B (58:05)

That's exactly, yes.

A (58:07)

Does that imply then that, I mean, just taking a step back, you said 82 billion neurons in our brain, so you put the probe into one and it moves over to the next one, and the next one and the next One one like me would naively assume they're all the same. Those are like three row homes that are basically all identical on the Upper west side. We're not talking about Tribeca here. Does it really matter if the probe moves between those three? Sounds like the answer is yes, but I'm curious as to why the answer.

B (58:39)

Is yes, because we now know that cells that are right next to each other can have some very different information. Now, that being said, when you go through a column of the cortex, a column is this vertical organization. Typically, what we're thinking about when we look at is the two dimension of the surface. But there's a third dimension of information processing, which is the different layers of the cortex we call the lamina. And typically, in some of the sensory areas, for example, if you put an electrode, it's primarily going to be tuned to the same information across those different neurons across that depth. So you're right. In certain areas, you may have neurons that are tuned to the exact identical thing. And for decoding purposes, that may actually not be a big deal to have it not very stationary over time. In other instances where you're trying to code from areas where it's a lot more intermixed, it could have really profound implications where you have to recalibrate the algorithms that the machine is doing to interpret the signals every couple of hours or days.

A (59:42)

So when you do ecog, how do you direct the sensor at the part of the brain you want to go to? Because I assume it has to be far more nuanced than just where you slap it on the cortex.

B (59:55)

Yeah, we're definitely getting into details, and I love that, Peter, about you. You're not afraid of getting into the details. This alludes to one of the things we were talking about earlier. The part of my brain and the part of your brain that is responsible for speaking, especially in the motor control part, is largely the same. It's in the same ballpark. There's a lot of variation when we come down to the details, the microgeography, but it's in the same. Largely in the same city. If we're talking about geography, where your house is versus my house, et cetera, that's going to be a little bit varied within that. One of the nice features about using ECOG or electrocorticography is that you can put an array over that entire area safely and you can sample very, very densely across the entire city, let's say. And so it doesn't really matter. Actually, at the end of the day, if one person's There and the other's. Basically, you're going to cover it.

A (60:49)

That seems to actually be a feature, not a bug. Right. I mean, the bug is you give up the resolution at what's happening in the kitchen of that house. But you now get to look at all the houses.

B (61:01)

Exactly. And you get to do it in a way that's very safe and scalable.

A (61:05)

I mean, the biggest thing you give up is 80% of the resolution.

B (61:08)

Roughly.

A (61:08)

Yeah. So with ECOG, tell me how many words per minute you could capture from a patient with ALS.

B (61:20)

What we did in our clinical trial at UCSF.

A (61:23)

Was this the 2023 paper?

B (61:25)

Yes.

A (61:25)

Okay. This is the nature paper.

B (61:27)

That's right. We published a paper in 2023. We worked with a participant named Ann. She had a very severe brainstem stroke about 20 years ago.

A (61:39)

How old was Anne?

B (61:40)

She was in her 20s. It wasn't long after she had gotten married, just a couple months after her second daughter was born. She was playing volleyball with her friends. Collapsed, taken to the hospital, she survived the injury.

A (61:56)

Was it a vertebral arteries?

B (61:58)

Yes. That's a dissection. Yeah.

A (62:00)

Okay. This is just.

B (62:01)

Your memory from medical school is actually pretty good. This is impressive. But back to Ann. Absolutely devastating. Just so people understand, vertebral artery. Everyone's heard of the carotid arteries. Okay. The carotid arteries come up through our neck, and they primarily give the blood flow to the front part of the brain. The vertebral artery is an equally, if not more important, set of arteries that supply the brainstem, which connects the brain to the spinal cord and the back of the brain. So we have these two pairs of really important blood vessels that come to our brain, the carotid and then the vertebral arteries. Ann had an injury while she was playing, and it was really just unfortunate, but she had this stroke in the vertebral artery that block the blood supply to the brainstem. So, functionally, what this means.

A (62:52)

Can I ask a naive question? Does it have to be bilateral to cause the injury? Or if it happens on one side, can the other side not profuse around the circle of Willis? Why does that injury happen?

B (63:03)

Just to be even more precise about this, unlike the carotid artery, the vertebral arteries, you have a left and right vertebral artery. They come up through your neck, and then they go through the base of the skull through the foramen magnum, essentially where the spinal cord is coming through the base of the skull. When they enter the skull, they become one artery. It's called the basilar artery and the basilar artery, and the small perforating arteries that come off that supply the brainstem are absolutely critical.

A (63:35)

So it depends where the dissection occurs. If it occurs before the bifurcation, you're probably fine. If it occurs above the bifurcation or where they join, it's not the bifurcation.

B (63:44)

But, yes, actually, you're right. There are many cases. In fact, sometimes we, for various reasons, actually have to occlude a vertebral artery, and then the other one, just collateral, gives a collateral flow. The basilar, however, doesn't have that kind of insurance.

A (64:00)

Yeah, it's mission critical.

B (64:01)

Doesn't have that insurance policy, no backup. It's such a critical structure, and when there's a problem there, it's usually actually, like, terminal. Ann survived this stroke. She was left quadriplegic, meaning she couldn't move her arms and legs. But in addition to that, she couldn't speak because the nerves that come through the brain, down through the brainstem and go to the cranial nerves, which supply the vocal tract, those were also directly affected.

A (64:31)

And yet, just. Again, you'll have to pardon my profound ignorance. Those would be lower cranial nerves.

B (64:38)

That's right.

A (64:39)

Three, four, five. The ones for the diaphragm were intact, so she could still breathe on her own. But what is it? 7, 8, 9. Would have been compromised, which is why she couldn't speak, or something in that neighborhood.

B (64:51)

Yeah. So it's the cranial nerves in particular around the lower ones and those distributions that allow the control of the tongue. That's the hypoglossal nerve. That's number 12. It's number 10, the vagus. But it's not precisely the nerves.

A (65:07)

It's actually the brainstem nuclei where the nerves originate.

B (65:10)

That's exactly right.

A (65:11)

And that's not something one predicts from any type of stroke. It's simply the nature of what part of the brainstem was affected.

B (65:18)

That's exactly right.

A (65:18)

And was the paralysis a result of her cerebellum also having infarcts? No, no, it was all brainstem, really.

B (65:25)

Just brainstem.

A (65:26)

Good.

B (65:27)

Yeah, precisely the part that we call the pons.

A (65:29)

Devastating.

B (65:30)

Devastating.

A (65:31)

So for 20 years, Anne is now in her 40s in a wheelchair, unable to speak.

B (65:38)

Right. So I think some important things about this are that it was actually about 18 years after her stroke that she decided to participate in our trial. And we had talked actually a year earlier. She said, I really want to wait to participate in this trial because I want to wait until my daughter graduates, and then I can do this with you guys.

A (65:59)

And I assume she said that because the risk of something catastrophic happening was high enough that she felt she needed to wait.

B (66:06)

Well, she's a mom. She wanted to be there for her daughter. And she had a year before the graduation. And she reached out to us because we had an earlier participant, also with a brainstem stroke that we treated, that we did this trial that I'm about to describe, and she read about it, and so she reached out to us.

A (66:23)

How did she communicate at that point in time?

B (66:25)

So the main way that she communicates is through devices that can track her eye movements. Those are translated to a pointer that can point on a screen to individual letters or words. And so it's a very painstaking way of communicating. One thing I've learned about Ann is she's just a tremendous person, positive person. She's just a force of nature. She recently actually used that same system to write a book chapter. Just incredible. Okay. So we started this trial called the Bravo trial. It was something that we worked with the FDA very closely to get approved because it requires a brain surgery. It requires this percutaneous port that we talked about. The reason we were able to get it approved in this form was that a lot of the components that we were using were actually existing medical materials. So the safety of it was largely already known in terms of its biocompatibility. Its biostability. What was not known is that if someone has not spoken for a decade or two, whether or not those parts of the brain actually would still work.

A (67:35)

Yeah. It's really interesting because we know that if a person loses their sight for X number of years, I'm guessing that the occipital lobe doesn't work the same way. It's not processing the information. So it. I don't know that it actually physically atrophies, but I'm guessing that the neurons aren't firing the same way. Right?

B (67:58)

That's right.

A (67:59)

So what would be interesting is we just don't know if Ann's inner monologue is still happening the same way.

B (68:06)

Right.

A (68:06)

That's a very interesting question.

B (68:08)

And I think that ultimately that was the biggest risk, actually. There's a lot of emphasis on the technology, but the basic biology of how the brain works and whether that information is still being processed, I think are really the more important ones, actually. And so what we did was we did a surgery where we implanted an array of 253 ECOG sensors. These are the sensors that are densely spaced how many? 253. So we're talking about something about the surface area of a credit card. And it's filled with electrode sensors that are spaced about 3 millimeters apart. Each sensor is about a millimeter in diameter. And so basically you've got this credit card sized array that was placed on the part of her brain that processes words, in particular, the motor production of the words, the parts that control the lips, the jaw, the larynx, the tongue. Areas that were functionally disconnected from her vocal tract because of this stroke in the brainstem, which connects the brain to those muscles. We did the surgery about three weeks later, we started our research sessions with her. We connected the cable. It's basically an HDMI cable that is attached to a head stage. The head stage transforms the analog signals from her brain. These are small voltage recordings.

A (69:38)

I know I get into the weeds a bit much, but I think it's kind of interesting in signal processing. Can you explain why the brain is analog and why you have to convert that to digital?

B (69:48)

Well, to some degree, there's a level that it is digital. Like when we talk about action potentials are digital single neurons. Action potentials, like firing. Yes or no. Like a digital form. But when we're recording a lot of these, especially at the ecog, it's an analog, it's looking at the average of these from a population of, let's say, a couple thousand of those neurons activating. And the work that we've done actually over the last decade and a half, which led up to this, using methods like ECoG, we've learned from that there's a map, what we alluded to in the very beginning, like the homunculus, but a mini homunculus that is corresponding to those parts of the vocal tract, the larynx, the tongue, the jaw. We figured out essentially how those signals correspond to every consonant and vowel in English about a decade ago, that was the impetus for actually starting this clinical trial, was that we essentially had identified what the neural code was like, what part of the brain and how that neural activity corresponds to all the movements that create syllables.

A (70:54)

For example, how big a data set was required to create that knowledge?

B (70:59)

Probably about 36.

A (71:02)

That's incredible.

B (71:02)

Participants data to just get the basic idea of the world.

A (71:06)

And is this something where if that were 36,000, it would be how much better?

B (71:12)

Hopefully perfect. Like near perfect. We'll get to that because that's where things are going. Okay, how does this scale? How do we use the information from other individuals to help n of 1 for example. But in Ann's particular case, we started from the beginning. We actually didn't use that data. We knew that it was possible. We knew what the nature of that data in that code would look like. And then at the same time that we're doing all of this research, Peter, AI is developing in parallel all of these tools that we now are using every day, transcribing our voice right now into text. We use that technology. We can actually use those same technologies that generate voices called speech synthesis. We've used a lot of the same tools, machine learning tools, that are in modern day AIs. We're now applying them on the brain activity and trying to use them to not translate, for example, text and synthesized speech. But now the equation is different. It's translating from brain activity to synthesized speech. The input is not text. The input is the ECOG activity across.

A (72:24)

These 253 sensors, which of course is the logical extension. If you ignore the cost of computer. Is there an advantage to doing it that way because you take out an intermediary step?

B (72:37)

Yes, it's because we know that the ballpark is there, but we know that everyone's brain at that detail level, if you're going to reconstruct their words, you can't just be in the ballpark. You have to know basically what each leaf of grass on that ballpark is doing. And that's highly variable across individuals.

A (72:58)

So what is AI? Just trying to think about what the machine has to do. What is its training set?

B (73:06)

I'll walk you through. So the way that we trained the algorithm, the way that we started this was we would give Ann prompts on a screen in text, and basically we would ask her to try to say it.

A (73:19)

Can she move her lips?

B (73:20)

She can move a little bit, but she can't speak. So she can move her jaw, her lips, but none of it is intelligible. She has what we call anarthria, basically, she can vocalize a little bit, but none of it is intelligible in any form.

A (73:33)

I see. But if her inner monologue, if you put up the word the cow jumped over the fence. And she says, and in her mind the signal is the cow jumped over the fence, then I totally see how it works.

B (73:46)

Yeah.

A (73:47)

At that point, you have infinite training data. You would basically just have her read War and Peace.

B (73:51)

Right. So let me just clarify. The area that we are decoding from is not the part of the brain that is processing either inner monologue or reading. It really is this part that is about this volitional Intent.

A (74:06)

Oh, that's such a good point.

B (74:07)

Right. So it's not about her perception. It's not the reading.

A (74:11)

So when I'm reading, the cow jumped over the fence. If I just go, what part of my brain is internalizing the cow jumped over the fence?

B (74:19)

Well, your visual cortex.

A (74:20)

Yeah.

B (74:21)

And then as it goes further, it's going into some of the language areas, but it's not necessarily activating the lips, jaw, and the larynx, the areas that are paralyzed. And so we're tapping into a part of the brain that is really.

A (74:33)

So this is a hard exercise. This takes a lot of effort on her part.

B (74:36)

A lot. So let me describe actually what that was. So for days, what we would do is have a sentence on a screen, and we'd give her the start time and the end time. And during that, she would just look at the sentence. She'd given a go cue and then try to say it. Nothing intelligible comes out. She may or may not be moving the lips job. But just try to say. And that turns out to be very important. Oh, my God. Like, you can't just think about it.

A (75:04)

You can't just read it.

B (75:05)

Wow. You have to actually try to say it. And that's what she did. So we started with a very simple vocabulary of about 27 words. The words that we chose are the NATO code words alpha, bravo, Charlie, delta, echo. We did that because we could measure basically, the accuracy of the decoder that was analyzing those brain signals and translating them into those 26 different code words. And on the first day, we were able to train the algorithm on a data set of maybe about an hour and a half to get to about 50% accuracy.

A (75:44)

Does 50% accuracy mean she could get half of them right? Or anytime you showed her one, there was a 50% chance it would be correct?

B (75:55)

Both what you just said is, in our sense, identical.

A (75:58)

Okay. But there wasn't a bias towards a subset of them that she was always getting right and others that she was always getting wrong?

B (76:04)

There actually was a bias. Yeah. Actually, if I get into details, yes, some of them were more discriminable than others.

A (76:10)

And was it based on the number of syllables?

B (76:13)

Yes, actually, it was based on that and some of the phonetic properties. But one of the reasons why NATO code words for us was a really useful training task for us is because NATO code words were developed in the first place by the military to improve communication accuracy. The reason why we actually use those code words is, is because sometimes if you just say A, B, D, z, there's a lot of confusion. So that's why we actually use those code words. It increases the discriminability and intelligibility where a lot of those settings, you just can't make those errors. For example, pilots and the call numbers, for example. So we use that because it has high discriminability. And on that first day, I think we got about 50%.

A (76:59)

This is going straight to voice, this is going to text.

B (77:02)

This is straight to text. Okay, yeah. And so we're just trying to figure out, could we decode which word it was and it was displayed in text.

A (77:10)

That's the first day.

B (77:11)

50%. That's the first day, yeah. And then over the next, I would say about six days, the performance just got better and better. And then by about like a week into this, she was up into the 95, 100% range. So that was unexpected. It was incredible to see the performance increase so quickly. But that did take a full week.

A (77:34)

Ask a question now, and I'm sure that the NATO code is not designed for this purpose, but presumably one could concoct a series of words that contain within them the full range of tones, of phonetics, of syllable juxtapositions that would allow you to use the smallest possible training data to get the largest possible outcome. Does that make sense?

B (78:03)

Absolutely.

A (78:04)

How would one even develop such a thing? Because this is a novel problem, Right.

B (78:08)

It's actually really important and more profound actually than you may realize. What you're referring to is the generative property of speech and language. And what I mean by generative is that you can take these individual elements like consonants and vowels, which by themselves have no meaning at all and give rise to all possible meaning from just different combinations of them. Just like DNA. DNA, we've got four base pairs, essentially as a code for all of life.

A (78:36)

Except DNA is so much easier because it's finite and the rules are always the same. You can define all the rules. Here you have, there's only four base pairs and they can only combine in two ways. And everyone has a one to one mapping with what it's going to become. Here you have 26 letters. They can combine in a near infinite ways. And then there are all these dumb exceptions, right?

B (79:03)

So that's where the AI comes in. Let me just explain a little bit about how the algorithm works. Because what you asked about actually is very, very much at the heart of the way that we do this. So we don't go from the brain activity directly to speech and words and sentences in the very beginning with the NATO. That's what we do. You can use an algorithm called a classifier. It's going to look at the pattern activity and then just say, okay, it looks mostly like beta. Another one looks mostly like echo. Another one looks like Charlie. Okay. But to get to expressive normal speech, you need something that actually can open up much more combinatorial potential to generate sequences of syllables, words, and sentences. So what we did was we built a decoder that translates the brain activity patterns in very small segments, 10 to 20 millisecond little chunks of brain data, really small signals, small windows of signals. And the machine learning is looking at those small windows and making an educated guess. How does the mapping of that brain activity relate to a given consonant or vowel? Now, I'm using consonant, vowel just because it's easy to understand. The reality is we used a speech.

A (80:24)

Unit like a phoneme or something like that.

B (80:26)

A phoneme? Yeah, but actually something that was statistically derived from a speech recognition algorithm. It was statistically derived. It was not something that was linguistically or that you read about. It's really a computational unit that we know. If you can decode 100 of these units, you can generate fluent, comprehensible speech. So we used AI actually to derive what those units would be in the first place. We took a speech recognition system that Meta had made open source about five years ago. It's one of the leading speech recognition algorithms. We took essentially the neurons and what they do in that neural network, and then we try to map those actually to the brain activity patterns. That's on the very front end. The first step of the decoding, it's translating the neural activity patterns to these individual speech units that are just 10 to 20 milliseconds long. And then it, of course, knows the sequence of these units over time because it's part of the algorithm calculation. And we use something called a language model, which is something that all of us are now familiar with. When you're texting, it autocorrects your speech. Why? Because it's got a model of English in there and that it knows what the particular sequence of things should be like. And so even if a lot of the data is kind of fuzzy, as more data accumulates, you get a sequence, and then it can basically use a best guess over time, what we call a probabilistic inference of what was the most likely word or phoneme at any given time point. And ultimately we could construct sentences.

A (81:56)

Did you get a sense from Anne as to how her level of fatigue with this progressed? In other words, what becomes the bottleneck? Does it get easier and easier for her to go through this talking motion as she practices more? Is it just like any other muscle that we think of that has sort of atrophied, and now she's sort of getting her talking back in shape?

B (82:20)

It is a bit of that. We're trying to make that easier over time. I think in the beginning days, we're trying everything to get it to work. And a lot of it, again, has to do with this volitional intent to speak. That turns out to be the most critical thing. One of the things that I thought was really interesting also was we were doing so much decoding through these tasks that over time, actually a couple months into this, and it reported to us actually the strength of her orofacial muscles, her jaw, the tongue, they were actually getting stronger through this constant therapy, constant rehabilitation. And so I think right now, everything is about just decoding the brain activity to an artificial digital thing. But I do think that in the future, BCIs are also going to be a way that we can do rehabilitation. It's a way that we have this direct readout of what the brain is trying to do. You can essentially build a prosthetic that helps people speak. But in the process, someone who hasn't spoken for a while will regain some of that natural strength over time. So that's a new indication that we're thinking about in the future, how to use this technology, actually to augment and accelerate rehabilitation.

A (83:35)

If Ann had that stroke today, how different, if at all, would this process look? If you were working with a person who hadn't spent 20 years or 18.

B (83:46)

Years without speaking, there's no question that I think it would work faster. There's less to learn. For her, not speaking for 18 years basically meant that she basically had to relearn how to speak, and we had to keep up with her relearning. Her brain was probably reorganizing, relearning, actually some of those fundamental things. And she could see the feedback of essentially whether or not what she was trying to say was right or wrong. And it was very intense work. So we're trying to make that easier over time. But I think certainly the more preserved, the more recent that activity is. Those memories, the synapses we talked about earlier, the more stable, the more functional they are, the easier it is to actually decode them.

A (84:35)

So what will be this ceiling for the current technology? How many words per minute and at what resolution or accuracy do you think the current technology, because this was ecog in her case. Correct.

B (84:49)

Right.

A (84:50)

Where do you think it's going to go? Where will this asymptote?

B (84:52)

We're seeing a lot of progress in this field. At the same time or soon after what we were doing, there were other groups that basically could see similar effects. Ours was primarily from the brain surface. Other groups, close colleagues of mine, were able to now do this with electrodes that were inside the brain using these intracortical arrays. So it seems that it's possible with different approaches. I think what is going to be a key question is what's going to be the right form moving in the future for many patients with ANN, we were able to get about 80 words per minute on average. So sometimes much faster than that comparison.

A (85:33)

How many words can you and I speak comfortably?

B (85:36)

You and I are probably doing about 150, 160 words per minute right now. Wow.

A (85:40)

So she could speak at half the rate you could speak at. That's pretty amazing.

B (85:45)

Yeah. And it's not like the speech was coming out super slow. It's just that there's this built in latency time that we use to translate the brain activity into those words and sentences. And what we published in 23, you.

A (85:58)

Had a very short latency in your more recent paper. Paper, didn't you?

B (86:01)

That's exactly right. In the 23 paper, our decoding strategy was to take this sequence of decoded phonetic elements and we could look at that sequence and then apply the decoding algorithm in the language model to reconstruct full sentences. And then we could even synthesize them, in fact, impersonalize them actually to her pre injury voice. In a more recent study that we just published this year, we were able to do this in a streaming way with less than a second latency between each phonetic element. So it's not like we're waiting for the whole sentence to occur, but we're doing decoding on the fly and it's intelligible and fast and that will get.

A (86:42)

The words up to what you think.

B (86:44)

As quickly as she can try to say them, basically.

A (86:46)

And this is all with the same hardware.

B (86:48)

This is with the same hardware, totally.

A (86:50)

Different algorithm on the intracranial. Obviously there's a big material science push to come up with the most immunologically inert substance possible. That's your challenge there. But with the ecog, is there another hardware step function you're waiting for?

B (87:08)

Not really. I mean, I think the thing that's most exciting about this is that we have the technology now. We gotta optimize it in the Right. Form factor.

A (87:16)

I mean, I guess it's just moving to a fully implantable device so you don't have to deal with the infection risk.

B (87:21)

So we need to have the array that will have a lot more channels actually. So last time I talked about a credit card size with 253. We'd like to have something that has 4x that amount of sensors.

A (87:34)

This seems completely achievable when you think about what Nvidia is doing or tsmc. I mean, that strikes me as very solvable.

B (87:41)

It is. And we are doing it right now with any medical device. You got to put it all together and improve it. So we've taken these components that have very high bandwidth wireless connected to this array. And I think in many ways we've done the hard part already. Like what Ann did, what Pancho did. He was one of our earlier participants. What Walter doing. These are incredible people that were really the first people in the world actually to be able to achieve this. Real pioneers. That was the hard part. The hard part is always the first time.

A (88:12)

Yeah, for sure. It's the proof of concept.

B (88:14)

It's the proof of concept. Everything now is actually just about optimization, to be honest with you.

A (88:19)

Do you think of this more as an engineering problem now?

B (88:21)

It is, yes.

A (88:23)

Let's now expand it so you have the proof of concept for the engineering problem that says brain works, motor system doesn't work, we can extract speech. What about these other problems that we talked about at the outset? What about als? Not for speech, but for respiratory function. A patient with ALS is, I assume, I don't actually believe it or not know much about it, but I assume that they ultimately succumb to respiratory complications and whether it be aspirations or things like that. So if we could overcome that problem and bypass the degenerative motor neurons. Is there an engineering solution to ALS based on the type of technology we're seeing today?

B (89:10)

When we say solution, I mean to preserve communication for someone.

A (89:14)

Well, I would say let's go even beyond the ability to talk, but the ability to breathe normally, for example, and ultimately the ability to not lose motor function outside of the cns. Yeah.

B (89:26)

So to do that basically is another couple of step functions in engineering where you basically are talking about bypassing pretty significant section of the nervous system. So you're going to tap into the brain to get some of the control signals. Some of this you don't even need to tap into the brain for breathing. A lot of it is, as you know, is wired. We're not thinking about it. Certainly central Pattern generators in the brainstem, for example, are really important for that breathing pattern.

A (89:53)

This might sound naive, Eddie, but why is it that we couldn't wire into all of the cranial nerves outside of the cranium and create a respiratory system that is fully automated? Like almost think of an AI CD for the diaphragm and chest wall.

B (90:09)

So we've spent almost all of our time really talking about the brain side. But then you can imagine another whole new enterprise and endeavor of building the electronics that not necessarily even tap into the nerves, the cranial nerves, let's say, or the cervical nerves that go to the diaphragm, but you bypass those too, and you go directly to the muscles. Yeah, exactly. So there is a field. We're not directly doing this research ourselves, but it's highly relating to where the future is. It's called fes, Functional Electrical Stimulation. So coupling the brain computer interface, the device that's decoding the brain activity, translating into the control signals, and then actually acting on the muscles through stimulating electrodes that are in the muscles themselves and doing that coordinated movement. Breathing, actually is a really interesting one because it's not as complex. It's like restoring our hand.

A (91:04)

It's interesting. Everybody assumes today if you really want to be in the forefront of technology, you need to be on the CS side. But the truth of the matter is you need just as much horsepower on the bioengineering side here. Electrical engineering, biomedical engineering, mechanical engineering. I mean, these are material science. I mean, these are. This type of problem is the intersection of everything that is high tech, from AI to computer science, to all disciplines of engineering, coupled with medicine. And you have to have the surgeon, too.

B (91:34)

That's exactly right. I think that you hit the nail on the head because in many ways that's the challenge, actually, more than the technology itself is really. How do you get the engineer in the room with a neurosurgeon, with a neurologist, the neuroscientist, all thinking in a really concerted way about solving this problem. And then what you're going to see in the future, actually, is that this is going to evolve more and more as a biological problem. Thinking about biology is the next technology solution. Engineered cells that are interfacing with the brain as opposed to metal electrodes, new ways of doing computing that are through biology, that are not through semiconductors, that I think ultimately is where things are going to go in the future.

A (92:15)

Well, say more about that. I mean, this is. There are some people that are already talking about this, but I'd like people to understand more what you mean by that. Because it's complicated.

B (92:23)

It is complicated. What I'm talking about really is I think, the next couple of steps. But one of the reasons why this comes up is that you actually said it really precisely before. Okay, you've got this electrode system. Let's say you're recording from one cell. Best case scenario, you beat an electronic system that can maybe do 10, maybe 40 in the future. A thousand channels, but the denominator is 86 billion. We're not in the scale, not in the same regime of scale. Biology has done that all along. Biology has solved a lot of these scaling problems. Cells that have the same genetic programming multiply because of their environment. Other factors have become specialized for a specific function. That's how our brain is. Each individual cell has the same genetic program, but because of its locomialieu ends up having a different identity, different purpose. And so I think that is really thinking outside of the electronical engineering, really moving into the realm of bioengineering. And this field is moving pretty fast. There's a whole field that we call organoids. This is creating mini brains from cell cultures or stem cells, building miniature brains, primarily being used as models of disease right now, but also as ways to test new drugs. But we're going to see these now interfacing with the world of brain computer interfaces. And so I think that that's part of the future for sure. It's very exciting. It's not near term, but there certainly is something about the future of technologies actually in biology.

A (94:01)

What is your stretch goal for the field in 2030? So, stretch goal meaning? I define that as things have to go well, but we're not talking science fiction.

B (94:11)

By 2030, I hope that we have these systems actually available to a much broader market. We have shown in a research setting, very controlled setting, that this can be done. The proof of concept, what really needs to be done is a lot of hard engineering to make this practical, usable, useful for people with a variety of different neurological conditions. Not just als, but spinal cord injury, stroke, multiple sclerosis. And that's a challenge. Everyone may have a very specific need. We need to be able to solve that. It is an optimization. It can be solved. That's what I'd love to see by 2030. Let's get a couple of these across the finish line so that they're actually out in the world helping people.

A (95:00)

Is there a current company or set of companies that are the natural owner to solving this problem based on their existing expertise, or is what you're talking about basically new companies that have to become capitalized and do this de novo. Who would be the natural owner of this?

B (95:17)

I think it's both. So the most famous probably is neuralink, Elon Musk's company, that has a very specific approach where you have a robot that is surgically inserting and sewing electrodes into the brain and trying to record from that very finest resolution. And I think there's a lot of progress with that, but also we've seen a lot of challenges. It's a really hard technical problem to solve at that scale. There's a variety of other companies in that vein. One of the things that we're working on is a highly customized ECOG approach, because basically we already know that it works from a lot of the work that we've done, and we can make it a lot higher resolution than we've done before and make it much safer with a fully implantable system. And then we're going to see more and more over time that this is going to become less and less invasive. Just like we were talking at the very beginning of our conversation, Surgeries have become less invasive over time. Brain computer interfaces will become less invasive. We're at the very beginning of this story. Getting the most amount of data right now is the most important with highly invasive approaches. But I think as time goes on, we're going to back out from that invasiveness. That's always how things evolve, to make it more generalizable, easier, and safer for people to do.

A (96:35)

Now, when you say less invasive, do you think there will ever be a day when you can do this off an EEG on the surface, or do you think, no, it will be more like minimally invasive surgery to open surgery, where instead of a craniotomy, we're going to bore a single hole in there, we're going to put a small, tiny chip in through the dura, implant it on there, and we're done. The latter, the resolution at the outside of the skull is probably never going to be good enough.

B (97:00)

We're talking about a physics problem I think a lot of people have tried to solve.

A (97:05)

Batteries will never store energy nearly as well as hydrocarbons. Full stop.

B (97:10)

That level of resolution that we have from the scalp, in theory, I think, but in practice, no one has been able to crack that. A lot of smart people have worked on that problem.

A (97:20)

Interesting.

B (97:21)

I do know that devices can continue to be miniaturized. I know that surgery can continue to be safer. So we will see this point in history where devices at Some point are not going to just be about medical applications. They'll be essentially enhancement level. There's huge ethical questions that we're going to have to deal with when that time comes. We're not there right now, but I would bet on the technology. We're not talking about breaking any rules and laws of physics in order to get there. We're just talking about scaling electronic or miniaturizing it in a way that is just a smaller form factor. But over time everything becomes less invasive.

A (98:00)

So I'm sure you get asked this question all the time. But going back to the origin of Ann's story, so many people suffer brain injuries. If you could wave a magic wand, you would just hope for some regeneration of the injuried portion of her brain. And my guess is in the case of Ann, the actual total volume of cells that are damaged is quite small. It could be this half the size of your thumb. Right. I mean it's a relatively small, but it just happened to be in the most precious part of real estate in her entire body. So do we know or do you have any point of view on the potential future of stem cell like interventions for the purpose of regeneration, specifically in the cns?

B (98:43)

Yeah, I mean this is an area that I think got a lot of focus and attention maybe about 10 or 15 years ago. And I would say largely the results were pretty modest.

A (98:53)

Yeah, at best.

B (98:54)

Yeah, at best. It's coming back now because of a lot of cell based therapies, organoids, building miniature models of brains on cell cultures. Basically I think the first things that we're going to see and where I am seeing some promise is very focal delivery in replacing cells that have been lost in small targets of the brain. So back to Parkinson's disease where you've got degeneration of dopaminergic neurons and the substantia nigra. The goal is can you replace and basically transplant some stem cells into that part of the brain?

A (99:32)

Remind me why the cells in the substantia nigra, do we know what's killing them?

B (99:37)

It could be multiple fold. It's partly genetic. There are certain genes that predispose to degeneration, there are certain environmental toxins that can cause the degeneration and then there's like a huge bucket. We still don't know what's causing that. But at the end of the day there is a degeneration of those very specialized cells. Most of the treatments are around dopamine replacement medications.

A (99:58)

And how close do you think we are towards transplant?

B (100:03)

It's Already been done, actually like 20, 30 years ago.

A (100:05)

Oh, really? I wasn't wrong.

B (100:06)

Yeah.

A (100:07)

Using fetal grafts, they just didn't take.

B (100:09)

Some of them took. In fact, some patients got benefit from it. The side effects were also fairly severe.

A (100:15)

What kind of side effects?

B (100:16)

If you have too much dopamine, you can actually get dyskinesias. So hyper movement. So one of the cardinal symptoms of Parkinson's hypomovement. Yeah. Bradykinesia, specifically, where you have slowed movements. Slow to initiate movements as well. But if you have cells that are just pumping out dopamine, they can also be putting out too much and you get the opposite effect. So it's not as simple as just putting them in there. They actually have to be tuned in the right way to put out the right levels. So there's a new generation of new therapies that we're really interested in trialing at UCSF that are much better cell models, Much better control of dopamine that's involved. We have much better delivery systems.

A (100:58)

Could you imagine that? Could you imagine engineering your way out of Parkinson's disease?

B (101:02)

We're working on it.

A (101:03)

What about synthetic cells where you completely get to control it? So again, you have the substrate problem, but if it's truly a synthetic cell, then presumably it can make dopamine as well, as opposed to an implantable slow leak dopamine that you come up with some slick way to refill. But what do you think is more likely, the more pure engineering approach or the more biologic transplant approach where you just try to tune it?

B (101:26)

The near term, of course, is taking some cell cultures that are not purely synthesized. That still I think is a huge goal outside of just brain. Like, can you generate a cell de novo without some origins?

A (101:38)

And does that require immune modulation?

B (101:40)

Oh, absolutely.

A (101:41)

So it's a full transplant.

B (101:42)

Yeah. So a lot of these patients initially will be on immunosuppression for that, but.

A (101:48)

That'S also improved a lot as immunosuppressive as if they had a kidney transplant or a liver. Heart transplant.

B (101:55)

Yes.

A (101:55)

Wow.

B (101:56)

Yeah, I think that's primarily right now, the level of precaution. There is progress being made in trying to make these things as least immunogenic as possible. That's where a lot of the engineering actually is focused on, is just make it the least immunogenic to avoid a rejection scenario. So I am excited about that. And that's some of the biological engineering that I was talking about. Biotechnology or the future of technology. We really coming back to the biology, moving a little Bit away from the electrical engineering.

A (102:26)

So in 15 years, in 2040, you're still going to be operating. You'll probably be in the final decade or 15 years of your career. So by a surgeon's standards, plenty of work to do. What do you think the world looks like in 2040? Which major problems that stand in front of you today do you expect to fall and what will be the implications?

B (102:49)

I think that the course that things are changing and how many things are being unlocked right now, we're close. I think we're really getting close. Some of these things are not standard because of the side effect profiles are too severe, but they can have therapeutic efficacy. We need to do that. Tuning this optimization, there's a lot of proof of concept out there, but like I alluded to earlier before, 99% of the work is in the optimization in that engineering. I do think that now that we understand what are the molecular and genetic drivers of a disease as devastating as glioblastoma, we will have way more powerful tools that will hopefully make it a chronic condition as opposed to a life, a death sentence in 18 months on average. That being said, with surgeries we can get out to years, many years, but a goal would be to make it chronic, potentially cure by essentially attacking the mechanisms we now know, the genes that are altered. We need to be able to turn on the immune system to recognize. Huge amount of effort in trying to figure this out. I do think, and I'm very optimistic around neurodegenerative disorders. There's just so many promising things, including.

A (104:01)

The cognitive ones like Alzheimer's.

B (104:03)

I think earlier diagnosis and earlier treatment is going to be the first thing where we're going to have the best effects. That is a really difficult one. But around Parkinson's, where there is a focal problem, you can regenerate those cells.

A (104:16)

So you're more optimistic on the movement disorders than you are the cognitive disorders.

B (104:22)

That's right. Partly it's because the target in the cell loss is very focal. We can get cells through surgery. When we're talking about Alzheimer's, it's a bit trickier because it involves multiple systems in the brain simultaneously. There are studies even using electrical stimulation in parts of the brain that are really important for encoding memory. These things are promising, but I think for these really step functions, and what everyone wants is to either stall the disease or reverse it. It's going to take more time, but I do think the early detection is going to be a game changer.

A (104:54)

A little off topic, but it's come up through the story of Ann. Do you have a point of view on things that place people at risk for vestibular artery dissections? For example, for whatever reason, whether it's just a wives tail or not? I've always been afraid of having anybody ever adjust my neck for fear of having a vestibular artery dissection. Is there any truth to that as a risk? Are there other things that people should be aware of, given the low probability but very, very high severity of such an injury?

B (105:23)

It's not a wives tale. It's actually statistically proven that certain kind of chiropractic movements around the neck can cause an injury to the wall of the vertebral artery. And that term dissection means that the wall of the artery has dissected. There's usually multiple different layers to that vessel wall. And what happens with the dissection is the vessel is injured and then blood actually starts splitting the wall of the artery more up until the point where it becomes occluded. And so it's a very, very dangerous situation and like you said, a critical part of the brainstem. So generally we recommend not severe aggressive movements, but sometimes you can't see it actually around sports where you have a very high velocity movement around imposture around the neck. And so those are the other cases where you can see it. That being said, this is very low incidence.

A (106:19)

Yeah.

B (106:20)

Low probability of happening. It's not at the level that you could really tell people to avoid certain sports or anything like that.

A (106:27)

If we could bring Harvey Cushing back from the dead, then you could have dinner with him tonight. What do you think he would say if he saw what was going on in the field that he created?

B (106:38)

I think that there would be one part of him that is looking at some of the surgeries that we do where we're still doing craniotomies. And Hugh would say that looks pretty similar to what we did 150 years ago. I think that's part of his genius. The fact that we still do it means that it still works and it's still safe, gets people through. A lot of that credit goes to Dr. Cushing. But there will be things that I don't think he could have ever conceived. The way that we're retrieving blood clots that are reversing strokes, what we're doing with brain computer interfaces, decoding brain activity, the substrate of thought to replace communication for people who are paralyzed, I think that that would have been very hard to really imagine back then, primarily because our knowledge was so Limited. And electronics was nowhere even close to being able to imagine what could be done now. So a lot of what we're seeing actually relies on technology that has evolved, like artificial intelligence. A lot of the work that we did on decoding the brain just couldn't work, even though we had the hardware maybe 10 or 20 years ago, probably even earlier than that. The decoding was not possible until this modern machine learning. These things are just accelerating very, very fast right now.

A (107:58)

When I was a resident, I used to have this very famous picture on my wall of the five physicians who were sort of the founding physicians at Hopkins. So, of course, you had Halstead in surgery and Osler in medicine, and I think Kelly was gynecology, and then there was a pathologist. And, of course, Cushing was the understudy of Halsted before he left for Harvard. I honestly think if you could bring all of them back to life today to see how much each of their fields had progressed, I think that Cushing would be the one most blown away because. And maybe I'm wrong and some historian will correct me, but I really think that what we've talked about today is, to your point, unimaginable. So, of course, Osler would see medications that he never could have conceived of. Right. He would never conceive of a GLP1 agonist and the profound effect it could have on weight loss. He could never conceive at the time that there would be a medication that could eradicate cholesterol, let alone an injection once every six months that could do it.

B (109:02)

He might have not even conceived obesity back then.

A (109:05)

That's a good point. Although he was tasting urine, so he certainly knew about diabetes. But, yeah, I think the mental leap to where we are. Although, look, maybe the pathologist would have never imagined the genomic sequencing that we could do with tumors today. Of course, back then, it was all histology. So it is amazing to me how much medicine has changed in a hundred years. Of course, it doesn't take a leap to imagine that if we're still around as a species in a hundred years, the next hundred years is going to offer far bigger changes.

B (109:37)

Absolutely. I mean, the pace of acceleration now is unprecedented. The underlying reason why I think Cushing would be the one that would be the hardest to understand what's happening now is because we are talking about the brain. We are talking about an organ system that we're just starting to fathom and put our heads around sort of the complexity for the last 150 years. Neurosurgery has really actually been about how do you avoid injuring the brain, how do you take a tumor out of it, how do you deal with the plumbing, which is the vascular system, the blood supply? But if you think about it, the biggest open ended questions are really being addressed right now in the coming decades. How does the brain itself work? And then how do we tap into that to address a large variety of neurological and psychiatric conditions? The history of neurosurgery was actually primarily about trying to avoid injury, stay outside of the brain, et cetera. Now it's much more inward looking, trying to understand actually how the system works, how the organ works. And it's a super exciting time because every time we unlock essentially a function of a certain part of the brain, there's a very high probability that there's going to be a therapy, either through a brain computer interface or through a new biological approach. Every time we unlock a new mechanism, there'll be something that we can do to treat it. And that's what the future is going to look like.

A (111:06)

One of my hidden agendas of this podcast is to encourage as many young people as possible to go into medicine. And I understand that today medicine is not nearly as attractive a career as it was 20 years ago, 30 years ago, 50 years ago, and that the best and the brightest are typically going elsewhere. But I think a podcast like this, as are many of the podcasts I do with doctors, I really hope it showcases that we need the best and the brightest to go into this. And again, this is not saying we don't need another brilliant person doing AI or investment banking or law or wherever else the top people go. But there is really an opportunity to bend the arc of civilization by choosing a career in medicine. And what you're doing, Eddie, is really on the forefront of that, especially the way it combines all disciplines of science, medicine and technology. It's just, it's super exciting.

B (111:59)

Thanks, Peter. Yeah, I'm really excited for that too.

A (112:02)

Thanks for coming. I really appreciate this discussion.

B (112:04)

Thanks for having me.

A (112:06)

Thank you for listening to this week's episode of the Drive. Head over to Peteratti md.com if you want to dig deeper into this episode. You can also find me on YouTube, Instagram and Twitter, all with the handle PeterAttiaMD. You can also leave us review on Apple Podcasts or whatever podcast player you use. This podcast is for general informational purposes only and does not constitute the practice of medicine, nursing or other professional healthcare services, including the giving of medical advice. No doctor patient relationship relationship is formed. The use of this information and the materials linked to this podcast is at the user's own risk. The content on this podcast is not intended to be a substitute for professional medical advice, diagnosis, or treatment. Users should not disregard or delay in obtaining medical advice from any medical condition they have, and they should seek the assistance of their healthcare professionals for any such conditions. Finally, I take all conflicts of interest very seriously. For all of my disclosures and the companies I invest in or Advise, please visit PeterAttiamD.com about where I keep an up to date and active list of all disclosures.