Action potential. When. A cell receives enough of the right kind of neurotransmitter, input a chain. Reaction is triggered that, causes an action potential to fire and the. Neuron to in turn relay messages to its own downstream, synapses. Action. Potentials, produce an electric field that spreads from the neuron and can be detected by placing, electrodes nearby. Allowing. Recording, of the information, represented by a neuron. You. You. You. You. You. You. You. Hello. Everybody. So. That that, video was not too Shutterstock that was actually near. Link, so. That. That's actual video from the company so if you want to get a sense for what it's like, to work in your link that video is indicative of the atmosphere. Of your link. It's an incredibly talented team and you're gonna hear a lot from from, them tonight so, we're gonna actually go quite into. Depth on, what. We're doing why we're doing how, we're doing it and. I'm. Just incredibly, impressed with the. Caliber. Of talent. At, your link and. The. In fact the the main reason for doing, this presentation is, recruiting. So. We really want to have. The the best talent, in the world come. And work at near link anyone. That's interested in trying to solve this problem and that's. Actually. Primary, purpose for this. This, presentation, so. Okay. So. The why of neuro-link. Just. To go over it is. I. Think. It's important for us to address. Brain, related diseases. The. Everyone. If they if you survive cancer and heart disease odds. Are that you will have some. Brain related disorder so, be like Alzheimer's. Or dementia and if, you don't friends. And family will for sure. And I think unless we have. Some sort of brain. Machine interface, that. Can solve. Brain. Ailments of all kinds whether it's an accident or. Congenital. Or, any. Kind of brain, related disorder, or. A spinal sore if you know somebody who's. Broken. Their neck broken their spine. We. Can solve that with. A chip. And and. This is something that I think most people don't. Quite. Understand, yet and we're. Gonna go over in detail how, this is possible. But. I think, there's there's. An incredible amount we can do to. Solve. Brain. Disorders, acted, damage, and, all, this will, occur actually, and. It quite slowly. So. Do, what emphasize that it's not gonna be like suddenly. Neuro-link, we'll have this incredible, neuro lace and start, taking over people's brains okay. It. Will take a long time. So. And. You'll see it coming, so, getting. Getting FDA approval, for implantable. Or devices of any kind is quite quite difficult, and. This will be a slow process where. We will gradually. Increase the. Issues. That we solve until. Ultimately. We. Can do a full brain. Machine interface. Meaning. That, we can in. Eltham. Utley. Yeah. This is gonna sound pretty weird but. Achieve. A sort of symbiosis with, artificial intelligence, so. This is not a mandatory thing. This. Is the thing that you can choose to have if you want and. And. This, is something I think it's gonna be really important, at. A, civilization level, scale. So. And. I've said, a lot about AI over the years, but. I think even in a benign AI. Scenario, we. Will be left behind, and, so. Hopefully. It is a benign scenario. But. I think with. A, high, bandwidth brain-machine interface I think we can actually, go along for the ride. And we, can effectively. Have. The option of merging, with AI and. This is extremely important. And. If. You think about your limbic system and your cortex, your. Limbic system is kind of your. Primal. Needs and once it's, like where your a lot of your emotions are coming from and then, the cortex is like the the. Thinking planning part of your brain and I haven't met anyone who yes, who wants to get rid of either the cortex or the Olympic system so. Clearly. They worked we're together well even though your cortex is in, principle far. Smarter. Than your limbic system. Everybody. Wants to keep the limbic system and their cortex so, hopefully. We. Can have a tertiary layer which, is the kind, of digital super. Intelligence there and. In fact you already have this layer so. It's your phone and, your laptop and, the, constraint, is just, how. Well, you interface, that the input and output speed. So. The. Alpha speed is especially slow since. Most people typing, with thumbs these days so. You, have a very slow output speed your. Input speed is much faster due to vision but, the. Thing that will ultimately constrain, our ability to be. Somatic, with AI is, bandwidth. So. In, the. Limit after after, solving a bunch of brain related.
Diseases. There. Is the the existential. It's. Mitigation, of the existential, threat of AI. Or. Yeah. This is the point of it. So. Creating. A well line future this. Is that that's the idea. Of. Nearly 100, billion cells called neurons, neurons. Come, in many complex, shapes but, generally, they have a dendritic Arbor, a cell. Body called a soma and an. Axon. The. Neurons, of your brain connect, to form a large network through axon, dendrite, junctions, called synapses. At. These connection, points the neurons communicate with, each other using chemical, signals, called neurotransmitters. Neurotransmitters. Are released from, the end of an axon, in response, to an electrical, spike called an action potential. When, a cell receives enough of the right kind of neurotransmitter, input, a chain. Reaction is triggered that, causes an action potential to fire and the. Neuron to in turn relay messages to its own downstream, synapses. Action. Potentials, produce an electric, field that spreads from the neuron and can be detected by placing, electrodes nearby. Allowing. Recording, of the information, represented by a neuron. I really, would play that twice. It's. So good you have to play a twin. Well. I think it like a lot of people in the audience you, know there's a wide range of knowledge. About neurons, I. Mean. Some, people view the brain is like this incredibly mystical thing that cannot you cannot interface the brain but and and then some people are aware of the brain, simulation such. As occurs for Parkinson's, patients. So. Try. To try to address the broad range of understanding. So. I. Mean, you're on but. Like yeah. There's a whole idea what if we were just a brain-in-a-vat, this. Is often posed by philosophers. Except. We are a brain-in-a-vat, and that's it that, VAT is us golf. Everything. That you perceive. Feel. Here. Think, it's. It's all action. Potentials, it's, all just it's neural spikes, and. It. Feels so real, it. Feels very real, but. But it's it's this that these are all impulses. From neurons what's. Called a a spike, and, a. Goal, is to record. From and stimulate. Spikes. In neurons, and do. So in a, way that is orders. Of magnitude more, than. Anything, has been done to date and. Safe. And. Good. Enough that you can. It's. Not like. A major operation, it's sort of equivalent to just. Of a lasik type, of thing so wait. Where you can sort of sit down machine does its thing and here, you can walk away with. Within, a few, hours that's. It and you're not even in a hospital so. So. Like, this basically. It's. How the key points, that we're taking away the. System that we were designed in version one is. Capable of on the order of 10,000. Electrodes, so. Each, each chip which is four by four millimeters is capable, of a thousand. Electrodes. Or has thousand electrodes. And we, think during, up to ten is feasible so. This. Is in contrast to. The. The. Best fda-approved, system. Which is like a Parkinson's. Deep, brain stimulation a thing, which would have on the order of ten electrodes, so. The. System even in version one that, we're going. To unveil today, is capable, of a, thousand. Times more. Electrodes. Than the. The. Best system out there and they're all read, and write, so. This is this is really quite I think I mean for something to be a thousand, times more than, what is public approved, is quite a big difference, and. And. This will this will get better with. Subsequent. Yes. Subsequent. Versions. The. Slide may seem a little generic. Like. Everything's got robots electronics, and algorithms at this point, but.
Not Threads. So. The. Feel. Like I'm in transcendence. There's. Actually, I wasn't transcendence. So, there's, there's very tiny threads that. Are about. About. A tenth roughly. Of, the cross-sectional, area of a human, hair so they're extremely tiny, threads in, fact, the threads that we. Have, it, likes it even in version one are about. The same size as a neuron so. If you're gonna go stick something in your brain you, you wanted to not be giant you, want to be tiny and. To, be approximately, on, par, with the things that are already there the neurons so, this is about. The size of, of. A neuron, but. Each thread, and. Then you, really need this to be done with the robot because, it's very tiny and it needs to be very precise so, you don't and you don't want to pierce a blood vessel so when you're in so, each thread that, the robot looks looks. Sort, of basically, through a microscope. And puts. A, inserts. Each electrode. Specifically. Bypassing. Any. Vasculature. You know any kind of like blood vessel. And. And making sure it's like inserted. Without. Causing, trauma or. Minimal trauma. Yeah. It's not zero but, you. Won't notice it that's, the important part you. Won't like you know. Yeah. Bill. Thing. So. And. Yeah. As the algorithms. So. Just give you a sense of scale this, is how tiny the threads are. That. Is not even a big finger that is a small finger. So. The. The these, threads are just like like I said very small in their hair and. There's a thousand of them and. This. Is what what the robot looks like as. It's. Sort of. Quite. Quite a complex device but it I, it'll. Comes down to a very tiny tiny point. So. Just. Like you. See the robot the. Robots on the left and. And. Then the. What. Looks like the needles for insertion next, to a penny but, in fact that the the actual needle that gets inserted is way, way tinier, it's that little tiny thing at the where. The arrow is pointing that's, actually the size of the the needle it's, about 24, microns in diameter. Extremely. Extremely small. It's. So small you can't really even see it within. The picture with the penny. And. Then this is a your, raid on uranium. Not. Really, that's, a car. So. You. Get a sense for the. Robot. Doing the, electrode. Insertion. But. That's a very zoomed in view, so. They're. All very very tiny and the robot is very selectively, applying, them very delicately. And. And. Then. This. Is what. The. Chip. Looks like. Action. Potentials. So. The each, one of those represents one. Electrode so, there. Would be up to ten thousands of these. That. These lines. Yeah. So. I. Guess. Like. It's always difficult to take there's, gonna be a list there's a lot more in this presentation so in terms of things I think are important to bear in mind this. I, think has a very good purpose which. Is to cure important diseases and. Ultimately, to, help, secure humanity's. Future. As. A civilization relative. To AI, the. Threads. Are very tiny, and. There's. A lot of them and they're, very carefully, placed, and. The. The operation, on. A per chip basis. It. Involves, just a a, to. Me a two millimeter incision. Which, is dilated, to eight millimeters and. Then the the Chavez place plays, through that and then we add it, goes, back to being two millimeters and you can basically good shot you're. In need of stitch, so. And. Then the the interface to the. To. The to the chip is Wireless, so, you have no wires poking out of your head very very important.
So. You it's. It's basically bluetooth to, your phone, because. We'll have to watch the App Store updates for that one. Who make sure we don't have a driver issue. Updating. So. The. Key, is like this this is something that. It. Is gonna be not. Not stress for our girls not stressful to to put in should. Work well hopefully and I would check. It out very carefully before it becomes obviously, fda-approved and. I. And, it's wireless so. You. The this this I think has tremendous. Potential and. We. Hope to have. This. Aspirationally. And in, a human patient. Before. The end of next year so. This is not not, far. And, then. As I mentioned earlier this is the main, purpose of this presentation, is, recruiting, and we. Need very, Tallinn very. Tell people in all these areas so it's, a lot, of very, challenge people are needed to make this ultimately. Successful. And. Then, speaking. Of talented people let, me hand it over to max. Yeah. Thank. You, thank. You, I'm. Max Hodak I'm the president, of neurolink I. Remember, a couple years ago when we. Started. Talking about the. Idea of neural link and that there might be a company and whether this was even a good idea I mean my first reaction was that I wasn't sure that this actually was a good idea that the technology, was there yet and I think it's Elon, has this incredible, like, incredible. Optimism where. He'll pierce through these imagined, constraints, and show you that really a lot more is capable, lot more is possible than you really think is. Today, and you. Have to be very careful telling them that something's impossible it better be limited by a law of physics or you're going to end up looking stupid. And. So. I. So. I've wanted. To build a neural. Interface has really been like a central. Goal, of my life basically as long as I can remember this is it I think like we talked about AI being potentially the last invention that we have I think that a high-bandwidth BMI might be like really the first invention, in many ways of like the next chapter of of us it's just real. Like has Elon alluded to early everything, about your experience, your thoughts your memories it's, all in your brain and represented, in the, firing statistics, of action potentials so. Alright, so just what is a BMI and we'll go through this really like fairly, quickly I think so there's you start with hopefully, a brain and a machine.
But. The machine is just a stand-in for the outside world it could be it could be another brain it could it software, it could be a robotic, arm but, you want to receive energy. From that world and in part, through the senses like vision and audition and impart energy back into the world through things like motor control and. That. That language that they used to communicate, are they putting aside the hardware. For a second it's very important understand what that is because people ask that code can I talk to my dog or I do these things but it's, more understand what that language is and that language in, the. Most general sense is information. To. A first approximation everything. Is information but. We just consider here the information represented in neurons and so, consider two like toy neurons one, so. These lines are imagine action potentials, and so imagine a neuron that fires very, regularly like a metronome like this doesn't tell us anything there's no information conveyed in this signal we don't learn anything from it on the. Opposite end of the spectrum imagine, or that fire is completely randomly, this also doesn't tell us anything this also doesn't carry any information, now. We know that this is these two degenerate cases are not what neurons do because. If, you, fit a model from recorded neural activity to, behavior. Of things like a cursor, of a patient. Or a subject, that's implanted and you correlate these then, you can build a graph that looks like this and this. Is a figure from a classic paper in this field from like the academic heritage of this field from 2003. I think that actually some of the authors of this paper in the audience today and, you. Can see it's the x-axis, is number of neurons and the R is the goodness of fit and you can see that as you add neurons the quality, of the model improves, this tells us that neurons, care, and their spike trains carry information about, things. Here. To ask them to us fairly quickly that's because what they were fitting here was just 2d cursor control which has simple dynamics and if, you have tasks that are more complicated then you need more neurons. So. The classic definition of, information is a difference that makes a difference it's just some piece of information or knowledge that tells you something it's like a very abstract concept. It's, such like information theory is such a deep rabbit hole if you haven't seen it before the original paper mathematical. Theory of communication it's. Like it's very readable I highly recommend it you'll, start seeing information everywhere. It will totally change the way you view the world because the world is information, as. We've talked about before and. Understanding. Information also gets, this question of well why do you have to have an implantable device why don't you have AG or wearable, or an optical thing and, the answer of course is like well what's like these, are different information carriers and what information are they carrying and. We. Know that like if you open a back issue of the Journal of Neuroscience and, you understand, how some species of bird encode, sound localization, or something, you'll find a discussion of spikes and we, as far as we know everything, that we care, about is found in the statistics, of spikes so that's what we focus on there. Are other things like fMRI, or EEG, these, are different information carriers carrying, different information, which, we think is it. Which we believe is impoverished relative to spikes and that's the scientific consensus, and so, the question for all these different things is well what information, is found in your carrier we focus on spikes that means we have to be inside the brain because the. There's no ceiling that we're aware of on that with respect to that, like grand vision of your perception, your thoughts everything, like. Motor, output and you like. Really. And. So. Why does that mean that you have to be inside the brain so you want spikes, well. People, have studied if you take a neuron and. You. Put an electrode, on that, specific, neuron so you have a ground truth electrical potential of the that. One neuron and then. You place an extracellular electrode nearby, which is what our electrodes, and the Ute are a and other people are like we're, not in the cell we're near the cells and then. You.
Measure. How far away from a neuron can you be when. You know what the ground truth spiking activity is can you no longer see the spikes and. It. Turns out that the answer is about 60 microns, which. Is like, 0.06. It's, it's, very small it's a lot less than a millimeter. So. You have to be firmly, under the skull like you're not there's no wearable, that is going to get you spikes this is a physics constraint as far as we're aware and. So. Now I want to I just want to talk, about briefly, that there, like, normally didn't come out of nowhere, there's a long academic, heritage, of research here the cochlear, implant has reached millions of patients since the 50s. For, deaf. Patients, over. A hundred thousand patients have received deep brain stimulation, for parkinson's and essential tremor and dystonia now other other, indications, and about. Twenty patients have. Received the Ute RA which is a little hundred electrode, rigid, metal, silicon device and, even. Though it has very few channels they've been able to do some really cool stuff with it there's videos on YouTube of BrainGate. Patients, doing things like controlling tablet computers or even texting each other through. Through, Utah raised just. From these the small number of electrodes and so. There's. Many of the people on the team that normally came from this academic like, this, academic work I got, my start working in a lab at Duke University studying. The, how. Mappings, between, brain. And and like. The screen space change so if you make it so that the joystick goes like, the cursor goes sideways and you push forward instead of up like how does the brain change the representation, so, the point is that there, are lots of people that have been looking at this problem from lots of angles for decades and we're, in the greatest sense building, on the shoulders of giants here. And. So the question is why not use one of those devices why, not use a Utah or, deep brain stimulator, implanted pulse, generator and there's. It's, just in the Utah rate case the the rigid sharp metal electrodes, produce, a fairly, strong immune response and this doesn't end up hurting the patient but it does mean that you lose the ability to record single spikes over, some period of time usually. Between one and a couple of years there's. Also a big percutaneous, connector, through the scalp so you need to plug in big external electronics, and you're never really confident, that the rusco infection is is gone, for the duration that you have the implant. Deep. Brain stimulators, solve just solve a very different type of problem they are very effective for some Parkinson's patients but, they have only a couple electrodes, and they're really geared towards injecting, large amounts of current not recording single spikes, so. They're really very different the. DBS is really just a very different type of platform. For a very different type of problem so we had to go back to the drawing board and start over to build. Something that met the goals that you along laid out for us we. Knew as Elin, mentioned that whatever we built we wanted it to be completely, wireless. Whoo, you know what any connectors, or wires coming through the skin it, had to be something that would last for a long period of time not something that you'd have to take out at two three or four years in, it. Had to have practical bandwidth, so we talked about high bandwidth or ultra high bandwidth like what matters is that it for the tasks that you're after there is practical, bandwidth that allows you to effectively do that thing whether that's cursor control or typing, or robotic arm or maybe in the future vision, and, it has to be usable, at home it can't be something that you go into a clinic, at the hospital, for two hours a week and under tight supervision of technicians, plug you into the amplifiers, and turn it on that's, be saying that you can live with and, so. Two and half years ago we were nowhere close to any, of that this. Is a photo of some of the prototypes that we've gone through over. That, over that time so we started on the, far. Left, that's the entirely, passive board, that has 64, electrodes on, it and connects. Two connectors that go to big, external, amplifiers, and then. We added integrated, electronics, with our first custom chip that's also 64, 64, channels and. Then, there's a big leap to the the device that Elon showed a photo of earlier that, has 3072. Electrodes, and a fully implantable package with just a USB C port coming out and. Then. We. We, took a step back in channel count B's room we have to optimize safety, longevity, and bandwidth all together and so in order to optimize, some of those other things we, moved to an easier to manufacture system, as 1536.
Channels In a USB C port and those last two are the focus of the paper that we, released today. And. So we've we've learned a lot from these record, a lot of data through these like these are actually, used everyday at der link to record, neural data and, work with it and they. Taught us a lot about the architecture, that, we think is the basis for our first human product that we're calling n1 and the central. Component, of that is the n1 sensor. This. Is it's a little hermetic. Package it's about, it's, when, it's fully assembled this is missing an outer mold. It's. Into an 8 millimeter, diameter, force. Millimeter, tall cylinder, and at. Each of these has 1024. Electrodes. And we can stim and record through through every one of those channels. Exploding. It opening. It up a little bit you can see there's there's the thin film, which has the threads that heal I'm talked about which is the wisp going off to the side there's. A hermetic, substrate. And then that gets welded later to a package, that goes over top and that's mated to our custom electronics and, we'll go into more detail. Leaders that work on each of these talked about these in more detail over the the, restless' presentation. So. Yeah I mean this is just to not to belabor the point I know that Elon really. Hammered. This in but these things are very very small they're, like they're not you, can't you can't manipulate these this is one photo this is not two photos drawing together and you. Really can't manipulate these with your hands that that part at the top is, just. A backing, material, that's, surgical, packaging they're they're peeled off the threads were peeled off that one at a time by the robot to, placed into the brain and. Then. Yeah and we had to build it a surgical, robot and. The first impetus. For this is just you, have to place these threads you can't manipulate these threads you need a robot and then that turned out to that grew into, understanding. Where the blood vessels are and imaging into the tissue and the surface of the brain moves because you're breathing and you have a heartbeat and there's lots of complexity, of dealing with this incredibly high entropy substrate, and it's. Not all off flow to the robot it's the robots under the supervision of a human neurosurgeon, who. Lays out where, the threads are placed but, it would not be for the surgery, is not possible without the robot and. So. The N one implant. We. Can place a Zeeland mention many of these possibly. Up to ten in one hemisphere for, our first patients for looking at four four, sensors three. In motor areas and one in a somatosensory, area which. Are connected via very, small, wires tunneled, under the scalp to an inductive coil behind the ear and. That. Connects wirelessly through the skin to a wearable device that we call the link which contains, a Bluetooth radio and a battery and this. Is importantly the only battery and radio in the implant so if you take this off the implant shuts off and if. There's software. Upgrades, or security. Issues it's much easier to upgrade the firmware on the pod than it is to try, and change the implant. It'll. Be controlled through an iPhone app you won't. Have to go to a doctor's office and have them have an exotic programmer, to to, configure it and the. First thing that you'll have to do is learn to use it like imagine if you've never had arms and suddenly you have an arm and you, have to pick up a glass on the table that's like not a cognitive, task you just like how how do you you can't think your way through that and so, it's kind of a trippy experience at the beginning where like patients at, first it just kind of wanders around and, then they figure, out how to break the symmetry and they learn how to control it and, and. That's like it's a long process it's like learning to touch type or play piano and. So. The for the first product. Where. We're really focusing, on three. Distinct types of control. The first is giving, patients the ability to control their mobile device B as we heard from over and over again from patient groups that if you. Have to have a care taker around the pressed buttons for you what's the point you might as well have them do the thing you have to get self sufficient using, using. The devices on your own and then. Redirect. The output from from your phone to a keyboard, or a mouse on a normal computer it'll just show up as a as, a Bluetooth mouse or a Bluetooth keyboard like any keyboard or mouse that you can use on any computer, and as. Elon mentioned this, is now this is a for looking statement there's a whole FDA process we have to go through we haven't done that yet.
This. Is this is like these. Are aspirations, but, we are working as hard as we can towards our, first in human clinical study, next year and. Again. These are plans but, the the primary indication for that will be complete. Paralysis by, spinal by upper, cervical spinal cord injury and we're. Expecting that those patients will get four 1024, channel sensors one. Each in primary, motor cortex some. At supplementary. Motor area and, dorsal, premotor, cortex which or two motor planning areas and closed-loop. Feedback into, primary somatosensory cortex. Which is like, if when you type or or walk, or pick up a pen you don't there's aren't visually guided movements, you have your, body has all these senses of where, it is in space and pressure and temperature and lots of other feedback and and we think for really high fluent. Control you have to provide that back to the brain for the synthetic effectors, also and of. Course fully Wireless and able to use it at home we think that there's a huge, difference between, something that you get to use two hours a week at the hospital versus, something that you're living, with every day and your brain is adapting to as much as the, device is adapting to your brain and. So. To, bring up the. Other other, colleagues this team is like incredibly. Lucky to get to work with this team we're going to go into a little bit more detail, on. In, that decoupling, implantation from the electrodes is incredibly important the, reason that you have these issues where things like these electric like a tungsten micro wires get rejected is, they're stiff and they happen they're stiff and sharp and they they tear the brain and they have to because they have to get into the brain and so. If you can decouple the process of getting it into the brain from what is left there where it can be much softer and have material properties like the brain and maybe be coated in things that help the brain recognize, it as itself that's. That's really important and then. The, thin film polymer leads the threads themselves, are really cool material science, and and, we're. Going to wear deets on that and then, we'll, also talk more about the chips and then, a little bit more on just the neuroscience, of how information is represented in in firing statistics, in your brain and. So with that I'd like to welcome. Dr., Matthew, MacDougall. Thanks. Max, I'm. Dr., Matthew MacDougall, I'm head neurosurgeon, at neural Inc when. I'm not at neural Inc I'm a brain, and spine surgeon, here in San Francisco at CPMC California. Pacific Medical Center. Before. That I was at Stanford where. I worked in labs that have implanted. And designed, advanced, brain computer, interfaces I. Originally. Became a neurosurgeon, because I wanted to help people live happier. Healthier longer. Lives. I've. Been humbled in practice. By, how powerless we are to treat many. Of the most debilitating. Neurologic. Diseases. People. Afflicted with spinal cord injury schizophrenia. Autism. And, a, host of other neurologic, conditions, have. Far too few options I. Work. With neural Inc because. We for the first time in history have. The potential to solve some of these problems. Before. We get to. How. We get the device in we. Have to talk about the our guiding principle, at knurling, safety. Everything. We do it in our link is filtered through the question, will. This make me more likely to want to get one will, it make me more likely to recommend this to my family and friends this. Approach impacts, every, design decision we, make. So. Well for the immediate future knurlings, devices, will only be intended, for patients with serious unmet. Medical needs. Our. Design philosophy is, that this should be safe enough that it, can be an elective procedure. So. What have we done to try to make it safe for.
Starters, We've created very small, threads, they. Displace a lot less tissue than the traditional methods in my. Regular practice, today I routinely, implant, large deep brain stimulator, electrodes, into, the brains of my patients, they're. Big enough to have about a one and a hundred chance of causing a significant, hemorrhage. They. Displace, and, disrupt, enough brain tissue that you. Can often see, neurologic. Consequences. Just from placing the wire. We. Can do better than that. Neural. Links threads are so thin that they're difficult to see with the naked eye they're, much smaller than the width of a human hair, they're. Small enough that a human surgeon can't, actually implant them without help so. We created help. Knurling. Developed a tool that we're extremely proud of the robotic inserter. Inspired. By designs conceived, of in labs here in the bay at UCSF, and Berkeley. We, developed, this, robot that can rapidly, and precisely, insert. Hundreds, of individual. Threads representing, thousands, of distinct, electrodes, into, the cortex in less than an hour. This. Tool allows a surgeon, to aim between, the blood vessels they'll cover the surface of the brain with micron, scale precision. The. Region of the brain shown in this video. Represents. Only. A few millimeters, of surface of the brain. As. You can see the brain surface moves with the heartbeat and breathing, the. Robot tracks and adjusts for this movement. Using. This tool we can greatly reduce the risk of harming cortical vessels and causing. Bleeding. Here, the robot is selecting, individual, electrode threads and placing them into the brain in the pre-planned location, with, remarkable, accuracy and repeatability. Using. This system we've been able to rapidly place, thousands. Of electrodes, into the cortex without causing noticeable, bleeding, we. Also have an in-house histology, team, that, examines, brain tissue to help, us choose electrode, profiles, and materials, to, help, us minimize, tissue, damage. When. You think of traditional neurosurgery. You probably think of something very, invasive. Traditional. Surgery, on. The brain isn't something that patients ever look forward to, or. Are excited, about except, in the most dire circumstances. Usually. A clamp. Is attached, to the skull to, keep it rigidly immobilized, to the operating table, we. Often shave all, or, most of the patients hair. Patients. Can end up with large visible scars, at. Neuro-link we want to create an entirely different patient. Experience, something.
More Like LASIK no. Scars, no. Big scars no, hospital, stays no short procedures, sorry. No. Hospital, stays very short procedures, and of, course in the end you get to keep all your hair we. Even want this to be possible under conscious sedation, that. Means you can get rid of the complexity, and the risk of general anesthesia as well as many of the unpleasant side effects nausea. Sore. Throat from a breathing tube. To. Be absolutely, clear our, first clinical, trial patients are going to receive an experience, much more like traditional neurosurgery. But. Our aim is to simplify the procedure down. To the injection of local anesthetic, a very. Small opening on the skin a, painless. Opening, in the skull below. Quick. And precise, placement, of threads into the cortex and then. We fill that hole, in the skull with the sensor allowing the scalp to be closed up over, it. Behind. The ear will make a small incision to, insert the coil we. Will tunnel tiny, wires under, the scalp to connect the sensors to the coil. That's. The process I. Believe. That, neural ink is going to be able to provide us. In the medical community. With. A platform that can finally, enable, us to treat some of these very difficult, to. Treat diseases also. To understand, them better I hope. You find this as exciting, as I find it, if. You feel you might be able to help us don't. Hesitate to contact us. To. Talk more about the technology behind all this I'd like to introduce Vanessa, Tolosa, director. Of our neural interfaces group. Hi. I'm Vanessa Llosa, I'll lead the neural interface group, at neural Inc our team, consists, of engineers. And material scientists, who are responsible for making the probes that get implanted, into tissue the. Packaging, for the electronics, and integrating. These two components together, we. Also do all the testing and characterization, of these parts, before. Joining neural, Inc I led, a neuro tech team, at, Lawrence Livermore National Lab. There. We worked on a wide, range of, neuro first static technologies, that, were used both in the academic and clinical settings, I decided. To join neural Inc because. I saw an opportunity to. Take all of this exciting work that we were seeing in neuro tech research and actually. Make, them accessible to patients at. A much faster time, rate than what. Medical device companies have traditionally, been able to do. With. That in mind. At. Noir link we set out to create a, fully, implantable, neural interface, with, thousands, of channels. That. Are, capable of single. Spike resolution. This. Device must last a long time in the body to, do this it must be small, flexible. And made, of biocompatible materials. That will minimize the brain's immune response. To. Protect the electronics, from the caustic environment, of the body it, must have airtight, packaging also known as hermetic, Packaging the, device, must also be able to both record, from and stimulate. Neurons this. Is essential, for a highly functioning, BMI. Finally. The, manufacturing, process, must be scalable, and capable, of making micrometer. Sized features. Consistently. Currently. There are no research, or commercial, commercial devices that meet all of our requirements. So. We built one out. Of microfabricated. Thin film polymers. Just. Like in, semiconductor. Chip manufacturing. We use a layer by layer process. That, generally, consists, of three repeating steps, we're, either always depositing, material, patterning. Material through photolithography or, etching, away a material. Depending. On the complexity of the design these. Steps could be repeated over a hundred times and to make things more challenging we are limited to materials, that are safe for the body in. Our. Current design we. Have a three metal layer process that. Results in a five micron, thick and ten, to my 40, micron wide probe, to, give you an idea of how small this is red. Blood cells have a diameter of about 8 microns, and, an. Average strand, of hair is about a hundred microns, yet. In the small footprint we're able to fit our electrodes, our wires, and insulation, for each of those wires. With. Micro fabrication we can drive features, down to the size of an electron beam so. This is great because we want to make our probes as small as possible essentially, we want it to be invisible to the brain but. There are other factors that limit the size of our probes for, example as we make the wire smaller it increases, the resistance of, those wires and as a resistance, increases, it makes it more difficult for us to separate our signals from our noise. Similarly. There are other technical. Challenges, and trade-offs that are related to higher. Channel counts and manufacturing, yield electrode.
Size And material and tissue much safety. At. Neuro-link, we have an incredible, team that's been tackling, these challenges and, have been able to make high channel, counts polymer. Probes in. This. Image is a silicon wafer that. Holds ten of these, arrays these polymer, arrays, in this. Design each. Of those arrays has, over 3,000, channels so what that means is in this one wafer we've manufactured, over 30,000, electrodes, and over 30,000, insulated, wires this, is something that can't be done with, the way current medical devices are being made. That. Rainbow effect, is caused. By the. Small feature sizes, on these devices that are interacting. With the nanometer, sized. Wavelengths, of light that are reflecting, off of them. If. You, were to zoom in on the ends of one of these arrays you'll, see these this region where we put. All of our electrodes, so each of these vertical, filaments, that end in a loop is what, we refer to as a thread and each of these threads can be placed independently, into the brain using our robot during surgery. This. Design is called linear edge. It's. One of over 20 designs that we've made for, our R&D work, we've, progressively, been increasing, the number. Of electrodes, per thread without, significantly. Increasing. The width of each of these threads at the base. We've. Been able to do this by adding, layers, and. Reducing. The sizes of the of the wires down. To a small as 350. Nanometers, this. Is less than the wavelength of visible light. Because. We're using a lithographic, process essentially. If we can draw. It we can also make it. So. In one end of our probes are the electrodes, on the other end or where. We connect the probes to the electronic, package earth, to the electronics, through conductive, feeders this. Substrate, is part of the Hermetic electronics, package, standard. Methods of connecting the probes to the electronics, package usually. Involves, some kind of large plugin, type connector, or a polymer. Based glue that, bonds the two components, together.
But. As we increase density. And decrease. The the footprint, becomes. Impossible, to receive, to, achieve hermiticity, in standard. Medical device connected connectors, this. Is due to several reasons. One. Of them is how. These. Substrates are currently manufactured. Hermetic. Feedthroughs consists. Of holes. That, have, been packed with conductive, materials, and are embedded in an insulating, substrate, as you. Drill more holes and, pack them more tightly together these. Brittle, substrates, typically made of ceramics, become, more susceptible to cracking, also. As you make the hole smaller it becomes more difficult to fill them with this conductive, material, without. Getting non hermetic, voids. Standard. Processing, also requires, exposure, to high temperatures typically. Over 700, degrees Celsius at these, high temperatures the, coefficient, of thermal expansion or, CTE mismatch between, the insulator and the conductor, can. Cause circumferential. Cracking, or interfacial, gaps during, the cooling phase. We're. Able to get, around these problems by. Developing, a new process. So. Rather, than making the, probes and then, the substrates and then connecting them together. Instead. We micro fabricate, them together. Into, one monolithic component. This. Provides a tight seal at densities, that current. Methods with. Standard. Materials for medical devices can't, achieve, so. Far we've used this process to make a hermetic. Thin film substrate, with over a thousand, connections over a 2.4, millimeter, by two point four millimeter, footprint. Next. We assemble the electronics, and then. Also attach a wired lid, using, a laser welding, process these. Two steps have, required. A lot. Of internal. Development, as well the. Result is, the. Sensor that's ready for final, assembly and implants. Into the body. Next. You'll, hear from my colleague DJ our customer about our custom electronics. Thank. You Vanessa, my. Name is DJ Shaw and I'm the director of implant, systems and neuro-link my. Team focuses, on building chips and systems, to get neural signals recorded from our electrode out of the brain and also, to put information into, the brain, before. Neural link I was at UC Berkeley where I co invented, neural dos which, is a technology to power and communicate, with small, implantable. Systems using ultrasound waves. Typical. Chip life cycle from design to verification to. Tape out is approximately. One to several years a. Neural. Link we, had the ability to co.design, or chip with the rest of the system and the. Type feedback loop from this organization, has enabled our small, team of analog, and digital chip, designers to, tape out a new. Design every three months on average, that. Means over. The past 24. Months we've. Done eight papers in total representing. 15 different chips that have been designed, fabricated. Tested. And used in development. The. Artwork, that you see on the top of the slide is of some of the actual chips that we've made so far. For. Any custom, chips we make the architecture, can vary substantially but, the basic ideas are the same. Neural. Signals recorded from the electrode, typically look like the one on the slide and in, order for us to extract the information that, we care about we, need to first amplify. Filter. And digitize. Those neural signals and use. Digital logic to process, and send out the bits we want for BMI. We. Also need ways to diagnose. Any issues with our electrodes, and be able to drive stem stimulation.
Engine To, inject charge to the brain when required. Our. Latest trip is called n1 system-on-chip, and it. Is, physically. Small measuring. Only 20, millimeter squares or 4 by 5 millimeters. It. Is low power. Highly. Configurable and, it. Has, 1024. Simultaneous, record, and stimulation, capable, channel and. It. Has on chip spike detection. To. Dive deeper, into n1, SOC I like, to highlight three key innovations, and they. Are. One. Analog. Pixel. Two. On chip. Spike detection, and, three. Stimulation. On every channel. The. First is analog pixel. Before. We can convert analog neural. Signals into digital bits, we, need to amplify and filter them and this, is where the analytics, will comes in, we. Want to have one analog pixel per electrode so that we can configure them independently, so, in the case of n1 SOC, there, are 1,024. And all pixels, and. All. The pixels also take up a significant, portion of the physical space on the trip and how. Well they work determines. Both the signal quality and the, characteristics. Of the overall neural interface. The. Goal of analog design is the analog pixel design is to, make it as small as possible so we can fit more as, low. Power as possible so, we generate less heat and have longer battery runtimes, and, as. Low noise as possible so we get the best signals. Now. The. Challenge, here is that. These goals are at odds with each other. For. Example we, want to achieve lower, noise on the amplifier so. That more expects can be detected. But. As transistors, get smaller it becomes harder, to get lower noise while keeping the power the same or less. Since. The start of neural link we've gone through three, major revisions, to the, analog pixel progressively. Improving, both the size and power while. Maintaining performance. Over. The past 24. Months we. Had Sevenfold improvements. In the size of the analog pixel and our. Latest pixel, on the right is at, least five, times smaller than the, known state of the art of similar architecture with, one pixel, dedicated, per electrode, as published. In the academic literature. Second. Innovation is on shift spike detection. Once. The signals are amplified, they're converted, and digitized, to zeros and ones by our on chip analog to digital converters. As. You'll hear in a second spikes. Or action, potentials, shown in this slide are often, critical, for. Certain BMI tasks. Currently. There are several different methods for detecting, spikes such as thresholding. Or more, sophisticated methods such as principal. Component analysis, and. Neural. Link one. Of the robust ways that we came up with is by, directly characterizing, the shape and it's worth noting that this is different than template matching and that it gives us more, information in, a general way in. Certain. Cases we can actually identify different.
Neurons From the same electrode, based, on their shapes. Our. Analog pixel, can capture the entire neural signals sampled at 20,000, samples per second with 10 bits of resolution. Resulting. In over 200, megabits per second, of neural data for. Each, 1,024. Channels that we would that. We record. In. Our previous systems that you heard about we. Were able to stream this entire broadband, signals through a single USBC, connector and cable and we, performed, real-time spec detection, on an. Equal machine running our optimized decode. Now. We. Wanted to completely, eliminate connectors. And cables for, n1 so. We had to modify. Our algorithms, to fit. Into the, hardware by scaling, both, making. It both scaleable and also low-power. And. Then, we were able to also implement this algorithm in our n1 SOC. Our. Algorithms, can compress neural data by more than 200 times and it, only takes nine hundred, nanoseconds, to compute which. Is faster. Than. The time it takes for the brain to realize that happen. Finally. It was important, for us to enable stimulation. From every channel that we can record from and make it configurable, and high-resolution. To. Make this work we custom-designed, stimulation. Engine for electrical stimulation. That can coexist alongside our analog pixels, our. Stimulation. Engine has point, to micro amp of amplitude. Resolution, and 7.8. Microsecond, of time resolution. There. Is a 16, to one ratio of electrode. To stimulation engine so we can't stimulate every channel simultaneously. But, we can within, each. Stem, pulse usually, in milliseconds, and we, can also stimulate any combination. Of 64, channels at the same time. So. In summary looking. Through our n1, SOC. It. Has, 1024. Analog pixels that we can record from simultaneously. With, 7.2. Micro volt RMS noise, while, only consuming, 6.6, micro out of power. It. Has on chip, analog to digital converters. On. Chip. Spike detection, that can compress neural data more than 200 times and it only takes nine hundred nanoseconds, to compute. Stimulation. Engine with point 2 micro amp of amplitude, and 7.8, microsecond, of time resolution. And. Finally. Diagnostics, for electrode, and impedance measurement. All. Of, these functionalities, that. I outlined are, integrated. Into a single. 4. By 5 millimeter. Silicon. Die. Next. My colleague flip will, tell you more about what can be done with these signals. Thanks. DJ. My. Name is filip sabes and I'm the senior scientist, at neural ink before. Neuro-link. I was at UCSF, where I was a professor. Of physiology. There, for, 16, years I ran, a lab that studied, how the brain processes sensory, and motor, signals, we. Developed, new. Neuro, technologies, and. We. Studied how to take those, tools and use, them for neural, engineering applications. Today. I'm going to tell you about, how it is that we can use those amazing. Devices that, Vanessa and DJ just told you about to. Communicate, with, the brain. Now. Specifically, I want to tell you about two things. First. I. Want. To show you that. The. Work that we're doing doesn't, come out of thin air we're. Building on over. A century, of neuroscience, research and decades. Of neural engineering research. These. Provide a solid foundation for, the sorts of things that that, we're talking about. Second. I. I. Want. To show, you why we believe that. Even. More advanced applications are. Possible, with, more advanced devices now. When. He long contacted, me over, two and a half years ago now and. Told. Me about his vision for the company I knew. That I wanted to join for. These two reasons because. I knew that, the. Technology was, at a point where. With the right team and the, right to right vision, and a. Long term vision we. Could do the sorts of things that we're talking about and I, knew that. With, that team we could do things that no one had even dreamed about yet. Okay. So. The. First thing I want to show you is. A. Video. Many. Of you who are seeing this I've, seen videos like this before so, you know what it is but, if you don't know what this is I have, the distinct, pleasure. Of telling, you that right now what you're looking at is the brain at work. Eat, this, is in fact traces. Of a bunch of electrodes that came off of one of our devices a bunch of electrodes from a single thread and.
Each. Trace shows you, a voltage waveform, in time, as, it's coming off of one of those threads. Now. If we focus in on one. Of those traces. The. First thing you may notice is that, there are. These. Big voltage, deflections. That happen periodically and these are the spikes that, max and Ilana and others have talked about. These. Spikes. Occur again, when a neuron has, an action potential and this. Is the fundamental element of communication, within the brain and this, is the thing that we want to tap into this is what we want to be able to record, now. As DeeDee just told you, we. Have algorithms that, can detect, these spikes in real, time as they're, happening and that. Allows us to collect data that, looks something like this this. Is what we call a spike raster, so. Each, row there represents. One channel of recording and time. Goes from, left to right and. Each of those little tick marks is the time of a single spike in action potential. All. Right so presumably there's some information somewhere in there how do we get at it what are we going to do with it. Well. For the first application. Which max told you about which, is allowing, paralyzed, individuals, to be able to control a computer what. We want to do is we want to reach into, primary, motor cortex and record, the activity, that's happening their primary. Motor cortex is the part of the brain that sends signals down the spinal cord and to the muscles to drive movement of course it does that with, action potentials, and, in. Particular, we want to record from the hand, and arm portions. Of primary, motor cortex. So. Imagine. Imagine. That you. Have a person sitting. Holding a mouse and they're, sitting still and then. They make an outward movement with their mouse and then. They reach back, what. Would you see in the brain well. Here's. A here's a synthetic. Neuron I made data up but but. It gives you the idea here's, a synthetic neuron that shows that, in. In the background activity when, the person's at rest maybe there's some firing but, when that neuron when, that person reaches outward that neuron starts to fire a lot and when. He reaches back the. Neuron becomes quiet so, this is what we call a neuron, that's tuned to, a particular, direction of movement. Now. Maybe. We'll record from another neuron and this, neuron may have a different pattern it may be tuned to the return movement and not to the outward movement so it fires more on the return. What. If we ask the person to do that movement again. What. We would see is a, similar, pattern of activation so, the neuron on top still, fires, more for outward movement in the Baram neuron on the bottom still, fires more for the return movement but, you'll notice that the patterns are different and that's because neural, activity in the brain is random, it has stochasticity. Which. Means that even though the person may be intending, to do the exact same thing from one movement to the next the. Neural code the neural representation, at the level of an individual, neuron is noisy, and this, is just one of the reasons why we need to record from lots of neurons in order, to be able to gain a high fidelity readout, of what the intention is so.
Ok So let's say we record from a bunch of neurons it might look something like this if. You look at that you might think that looks pretty messy and it's not clear what's going on but. I'm, gonna do a little trick I want to take those neurons I want to rearrange them so that they're in the order of the, tuning, that they have but, just as I told you about those two neurons and, if you do that look what happens now. Suddenly structure, emerges, and I. Think you'll agree looking at that but there's information in, that stack of neurons that tells you about the movement and that's. Exactly what we want to do we want to do that kind of magic in an, automated way to read out and to, read out the movement, the. Way we do that is by building something that we call decoding. Algorithms, these are mathematical algorithms, that, we tune based on data like these to. Be able to take in just those raster's, of spiking activity and output. The, movement that's that the person wants to make. Okay. So. For. These little fake data I built a sit very very simple decoder and sure, enough it's, able to to. Capture the intended movement this is what we want to do on, bigger scale no. You. Might say to yourself I don't, understand your talk about moving but I thought it was about paralyzed people right so how does that work well. It turns out we know from, a lot of prior research but. Even if you're not actually making the movement even if you're just thinking about the movement or even, if you're watching someone else make movement the, cells and motor cortex respond, in a similar way so we, can build up these decoding, algorithms just from from those kind of data and then. A paralyzed person can, think about moving the mouse and the. Cursor will move, now. This. This. Kind of decoding, has, been done in a. Fair. Number of academic, labs including my own before, I came here and in. Humans in academic, studies. Well. What, we want what knurlings goal though is to. Be able to do this with a clinical device, that. People can take home and use on their own and there's. Orders of magnitude, more channels. Or, orders of magnitude more neurons that we're recording from, with. That we think the people will, be able to get naturalistic. Control over, the computers not just a mouse but, also keyboard, game, controllers, and potentially other devices that's, what we're trying to do. And. I've told you about the arm and hand area of motor cortex but. The. Devices that we're talking about because, of their high bandwidth, and. The, ability to tailor the location, of each and devote individual. Electrode to, a person's, individualized, cortical. Anatomy we. Should, be able to reach anywhere in motor cortex so. For example there. Are areas at. The base of motor cortex that, are responsible, for driving activation, of the speech articulate, errs there, was a recent lovely study from UCSF that, showed. That, from. Activity, like that you can actually decode. Speech. So, you can you can decode the movement of the articulator, and from, that you can create synthetic speech. So. Potentially. With a device like this you could restore, speech to a paralyzed person who's, no longer able to talk, but. There's no reason in principle that we can't reach all of motor cortex. And. That. Would give us access to, any movement, that a person thinks about any movement at all a person. Could imagine, running, or dancing. Or even kung-fu and, we, would be able to decode that signal. So. That, could give, a paralyzed, person the, ability to control say for example a 3d, avatar, that they could use for online gaming for, sports. It, could allow them to control a wide range of assistive, robotic devices and, ultimately.
If. And, when the, technology for, spinal. Cord nerve, or muscle, stimulation. Gets, far enough ultimately, it, could be used to, restore, that individual's, control of their own body. Okay. I've. Talked about readout but, we, remember, we want bi-directional, information we don't only want to read information out of the brain we want to be able to put it back into the brain now. Some of you that may seem a little bit fantastical. That you could write information into, the brain but, actually the the basic building box of that technology are already there. This. Is the same image, that you saw before of an electrode next to a cell it, turns out if you pass a tiny amount of current through that electrode, what, happens is that you activate, cells, nearby you. Cause them to to, fire an action potential one or many, and. That. Is the technology that. Is already being used widely outside. The brain say, for example for cochlear implants, which, have been used for decades to restore hearing to the death and more, recently in. The. Eye to, restore vision to the blind in a fairly, rudimentary way as I'll tell, you more later but. In, addition you can use the same technology, in. The brain. For. Example to, restore the sense of touch or to restore vision and I'm. Going to tell you very briefly about those two applications. So. Let's start with. The sense of touch consider, this little bit of tissue, that of brain that I've just highlighted here that's at the border between motor and somatosensory cortex. So. If we blow that up. What. You can see. Is that. Somatosensory. Cortex, has a very special property it has what we refer to as spatial spatial. Map and. What I mean by that is that there are regions that, encode the palm of the hand and each, of the five digits for example so. If we were to stimulate, at, one little location, say in the thumb part of the. Cortex, the, person would feel a sense, of touch of pressure on their, thumb or if, we were to stimulate, two sites on. The palm in the palm area of cortex, you might feel a couple of points or touches on your hand this. Kind of technology has been demonstrated in, in, many academic labs and in. A recent really. Nice paper it was shown that. With. Subjects, controlling, a robot arm through. BMI. Getting. Tactile. Feedback of when, that arm or, when the hand of that arm was grasping an object improved. The ability to pick up and place objects, with the robot so this is this, is the kind of thing that can really help decoding. So. Imagine what we could do if we're, able to take our device and cover, all of somatosensory, cortex, we. Could give rich, sensation, of objects. Of haptic feedback when, you're manipulating, objects we could maybe feel, different textures. But. It's not just about improving the user experience. It's. Also about getting, to the level of functionality that we want, imagine. For a second imagine typing. Now. Imagine typing with your fingers, anesthetized. That's. Going to be pretty hard so. That haptic, feedback that, sense of sensory feedback during, movement is going to be important going forward and. And. Yeah okay. So. That. Sensory feedback for. The hand we, can also potentially. Provide, visual feedback so. Visual. Cortex just like somatosensory. Cortex, has maps so. There's. A spatial map in visual cortex which is here in orange in the back of the brain so for example if we stimulate a particular, point in cortex, we might see a, flash, of light in. A little, punctate spot in front of us and this. Was demonstrated many years ago in. In. By neurosurgeons, and it's been used in academic labs and that we call that a phosphine, and you. Know if you stimulate. Another area look at a phosphine in a different location so, the. Idea here is that you could stimulate a bunch of different areas and you could create kind of like a dock dot matrix image. Of the visual world which, could provide a rudimentary, form of vision and there, are academic, labs and even, companies that are working on technology just, like this, but. There. Isn't just one map in visual cortex actually there are a bunch of different maps there's a good example of how the brain works is, a spatial, map but, there are also there, are also maps telling, you about the orientation of edges. In the field their maps telling you about color, there, are maps telling, you about the size and speed of objects, moving, so. What. We want is a device, that has, sensors, that are small enough electrodes, that are small enough and a, high enough density that. We can tap into that rich collection. Of maps, with. Our stimulation, devices so. That we can do better than just dot matrix so. That we can actually create, rich. Visual feedback for. The blind that's that's the long-term goal. Okay. That's, just again. One more example of the way that these devices can be used. So. I've talked about recording. Signals. And I've talked about stimulating.
You. Can combine those two to treat a variety of. Neurological. Disorders. Max, talked earlier about deep, brain stimulation. To. Treat say, for example Parkinson's disease, and many. People have have, those devices in. Academic. Labs have recently shown that you can do better with. Stimulation, you can treat better if, you. Also are able to record the state of the brain say, for motor cortex and use that to sha
2019-07-18