Neuroscientist Miguel Nicolelis on connecting brains and machines (28-02-2016)

Brazilian neuroscientist Miguel Nicolelis about the possible to create an organic computer and a brain net by connecting human brains.

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00:00:00 Speaker 1: Well, can digital machines emulate human behavior?
00:00:03 Speaker 2: No, not a chance, not ever, never, actually.
00:00:11 Speaker 1: And why is that?
00:00:12 Speaker 2: Well, because we are not machines, and our brains do not work through algorithms,
00:00:20 and we don't work in binary logic. So we have components of our minds that are analog, very important components.
00:00:29 And we all know that digital processes, they can approximate, but they cannot emulate analog processes,
00:00:36 particularly processes like the ones that take place in our minds.
00:00:46 The brain is a very complex system and is formed by 100 billion elements connected to each other,
00:00:55 which are continuously adapting to the statistics of their outside world.
00:00:59 And this adaptation, that we call plasticity, makes it impossible for a digital machine that needs code to run.
00:01:02 So there is no software and hardware in the brain, that's the other thing.
00:01:11 Speaker 1: It's like an organic computer.
00:01:12 Speaker 2: Yeah, it's an organic computer, the brain computes with the organic tissue that it has,
00:01:20 and that kind of computation is not reducible to an algorithm. So there is no singularity coming for the human race.
00:01:29 There are other problems that computers can bring to the human race, but not replacing our minds.
00:01:35 Speaker 1: Because it would deny us evolution of the brain.
00:01:38 Speaker 2: Absolutely,
00:01:40 a brain is a system that is a product of an evolutionary process that involved millions of random steps that cannot be
00:01:50 simulated in a laboratory or in a machine. And my concern is not that digital computers will reproduce the brain.
00:01:58 My main concern is that because the brain is so adaptable, so plastic, and it absorbs everything that is relevant,
00:02:07 that gives the brain an evolutionary advantage and a survival advantage, that we may,
00:02:13 because we are continuously exposed to computers, digital machines,
00:02:16 and now this exposure is becoming almost overwhelming, that we may start reducing our human condition to mimic machines.
00:02:26 And what is going to be rewarded out there is behaviors that are similar to machines.
00:02:31 And so the brain would simulate machines and behave like machines, produce behaviors like machines,
00:02:37 eliminating the most important things that define our human condition.
00:02:43 Speaker 1: Yep, I understand that, and when you look at the brain, when did your fascination for the brain start?
00:02:50 Speaker 2: Actually, my fascination started when I read a science fiction book by Isaac Asimov
00:02:56 when I was in high school here in Brazil.
00:02:59 And it was a kind of boring book, because I like Isaac Asimov for the science fiction books.
00:03:04 But then I found his book, The Brain, and it was one of a few books that he wrote that is not really science fiction,
00:03:10 and it was a description. And in that book, there was no dynamics, there was no physiology, there was mainly anatomy.
00:03:17 But I realized that I was, for the first time, introduced to the thing that really creates everything.
00:03:24 And then when I went to medical school, I started working with computers, microcomputers.
00:03:28 They were just coming out in the 80s here in Brazil.
00:03:32 And I thought, for a moment, okay, I'm going to work on applications, on computers in medicine, because I liked,
00:03:38 very much, that.
00:03:40 And then I thought, well, but the ultimate computing device is the brain,
00:03:44 and at that time I didn't really know much about either computers or the brain.
00:03:50 But I decided that I wanted to understand the brain first, and that was 35 years ago.
00:03:57 I'm still trying to understand the brain first.
00:04:00 Speaker 1: Yeah, because first, you are fascinated by brain, you are investigating the brain, but then the next step,
00:04:20 also, you start to understand the brain.
00:04:20 Speaker 2: Yeah, well, when I came to neuroscience in 82, 83, again, there was no dynamics,
00:04:20 there was no time in the brain. Most of the descriptions were very static.
00:04:24 We talk of maps, columns, areas, subareas, secrets, but there was no flow, there was no changing.
00:04:33 Plasticity was reported in 83 by, now one of my heroes and my good friend, Jon Kaas, and his colleague, Mike Merzenich,
00:04:41 two papers that were rejected everywhere,
00:04:44 and they only got published in a new journal because people didn't want to see it.
00:04:47 Proof that the adult brain was changing, it was adapting to lesions in the periphery, that's how they showed it.
00:04:56 And I wasn't aware of this paper until 85, but when I saw the paper, two papers, actually, I start wondering,
00:05:06 this is totally different that what I have been reading.
00:05:11 And that's when I went for my PhD here in Brazil, after medical school.
00:05:16 And I realized that what I wanted to look into the brain was the dynamics of the brain, because I had a hint.
00:05:23 It was very faint, it was not a very concrete thing, that there was much more to plasticity than just what Jon
00:05:31 and Mike had reported.
00:05:33 It turned out that plasticity is pretty much what matters in the brain, it's the central concept of the brain.
00:05:39 So I'm absolutely shocked that these guys have not won a Nobel Prize yet.
00:05:44 People have won Noble Prizes lately for minute, tiny things.
00:05:49 These guys discovered the essence of what the brain is about.
00:05:53 Speaker 1: And when you look, because when you start to understand the brain,
00:05:58 I suppose you can also understand the immense possibilities when you combine brains, when you think in brains.
00:06:05 How does that work with you, because you're one of few experts?
00:06:09 Speaker 2: Well, when I went to the US, I met another phenomenal guy, John Chapin, and we had the same idea.
00:06:18 We were one of the few people in the world at that time, today it's common ground, but at that time, in fact, people,
00:06:25 when they heard what we wanted to do, record from multiple neurons,
00:06:28 multiple brain cells simultaneously in behaving animals so we could look at the dynamics of the circuit.
00:06:34 Some of our colleagues, more senior colleagues thought that we were nuts, that we were crazy,
00:06:39 that there was no point in moving from recording the electrical signals of one neuron to many neurons.
00:06:45 So John and I had a lot of opposition, and our careers were on the fringe at that time.
00:06:51 And he was already an established guy, but even so, he was young, and I was just a nobody coming from Brazil,
00:06:59 a postdoc.
00:07:00 But it turned out that what we discussed in the early 90s in the studies that we published then, I think,
00:07:08 are now pretty much at the center of neuroscience, at the edge.
00:07:15 And in, almost, desperation, in 97, we had many papers published, but people are now really paying attention to them.
00:07:20 We discussed, one day,
00:07:22 that we needed a new preparation to convince our colleagues that this thing that we were talking about,
00:07:28 population coding, was much more relevant than anything that had been done before, in terms of single neurons.
00:07:34 And that's when we came up with the idea of brain-machine interfaces, of linking brains to devices.
00:07:38 It was a preparation, an experimental paradigm that we created to test the notion that to control a device,
00:07:46 either a real limb, a leg or arm, or an artificial device, the brain requires lots of neurons, not a single cell,
00:07:55 and we proved that quantitatively.
00:07:57 When you let the animals use only one neuron to control complex device, nothing happened.
00:08:04 But when you get a population of cells working together,
00:08:07 they were able to use just the brain activity to control devices.
00:08:11 Speaker 1: Yeah, and you did that with rats?
00:08:15 Speaker 2: We did with rats first.
00:08:15 And a year later we did, that was the first paper and pretty much interfaces in modern age, with the constitute,
00:08:21 define the term.
00:08:21 I publish a paper in Nature in 2000 that actually started with a description of this goal that you see here.
00:08:29 To explain what a population code means because this was a goal scored in which eight players touched the ball without
00:08:37 any Italian being able to touch it.
00:08:39 And none of the individual players knew the outcome of the play until Carlos Oberto kicked the ball
00:08:46 and the goal was scored, so that's what I was trying.
00:08:49 The message, the metaphor, was to explain that none of the individual neurons knows what is going on.
00:08:53 It's the population, it's the team, that knows the outcome.
00:08:58 So I started a paper and in the middle of the paper I said, well, what John and I have proposed a year ago,
00:09:03 we call it brain machine interface, and the term was created in there.
00:09:07 A year later we did it on monkeys, in our monkeys, and in Rhesus monkeys.
00:09:13 In 2004 we did a first human demonstration of this concept in an interoperative procedure in Parkinson patients just
00:09:19 for a few minutes. It was the first human demonstration that everything we had seen in monkeys was applicable.
00:09:25 Speaker 1: And what was it that you saw then?
00:09:27 Speaker 2: Well we saw this symphony, this neural symphony.
00:09:29 The dynamic properties that we saw in rats and monkeys were there in humans. It was the same thing.
00:09:37 And the same mathematical computational approach that we used to link the brain with a device would work in humans.
00:09:45 And so that is when we realized that we had something gigantic and that it was not just a basic science apparatus
00:09:54 or paradigm.
00:09:54 We had touched something that could have clinical relevance
00:09:59 and it could advance neuroscience to realms that we never thought about before.
00:10:04 Speaker 1: And what, when you look beyond 2016-2017, where are we headed for?
00:10:08 Speaker 2: I don't think anybody can answer that.
00:10:14 Nobody can answer that question honestly because every day things are changing,
00:10:19 but it's a completely different neuroscience. It's a completely different brain research.
00:10:24 If you look at the Brain Initiative in the United States, that I'm not part of, never got invited to be,
00:10:31 everything that initiative's about is what John and I did.
00:10:34 It's about recording more and more neurons, studying only circuits, paying attention about dynamics, elasticity,
00:10:41 creating technology to visualize thousands, millions of neurons.
00:10:45 However the emphasis is mainly on technology and I think the emphasis should be in the questions.
00:10:51 It should be in the real science. Curiosity should be the emphasis I think.
00:10:57 But as you know technology in the US has become a monster,
00:11:01 almost a religion to the point that some people predict that we will be replaced by technology.
00:11:06 Which is against the idea that no derivative of a biological system can be more complex than the biological system that
00:11:14 created that derivative.
00:11:16 Technology is just a projection of our mind, it can never be more complex than the mind who created this technology.
00:11:23 Speaker 1: When you look at the framework, okay I can understand that you don't want to be a part of it I can imagine.
00:11:29 Speaker 2: Yeah.
00:11:29 Speaker 1: But you, yourself, are developing in the neuroscience, big steps. Can you explain?
00:11:36 Speaker 2: Well, sure, we first started with pretty much an interface concept right.
00:11:43 We discovered that we could link brains of rats, monkeys and humans to a upper limb robotic device.
00:11:50 There was a physical robot. A seven degree of freedom industrial robot and it worked. That was the first thing.
00:11:57 But then we said why it need to be upper limb? Why could it be lower limb? Nobody went for it.
00:12:02 We are the only lab, one of the few labs in the world, perhaps two or three labs in the world that said okay.
00:12:08 Let's try for legs and it works. And then we say why it has to be a robot? Why can it not be a virtual device?
00:12:16 Can a brain incorporate a virtual device as if it were a part of the subject's body? A real flesh and bone.
00:12:24 And it worked.
00:12:24 We put an avatar of limbs and legs or arms and the monkeys treated that after a while as if there were a third
00:12:34 or a fourth so we had monkeys with four limbs. Two biological and two virtual, same thing with legs.
00:12:41 Then we said well the actuator doesn't need to be next to the monkey. So we put an actuator in Japan.
00:12:47 A robot in Japan and we had a monkey in the United States controlling across the globe.
00:12:52 And, lo and behold, the monkey assimilated the legs of the robot as if there were his own legs.
00:13:01 And you could stop the treadmill when the monkey was walking at Duke.
00:13:05 And he would still keep imagining movements for the robot to work in Japan as long as it give reward.
00:13:12 You know, monkeys are like us, they need a bribe to work.
00:13:16 And as long as it keep giving them juice or grapes they will do that.
00:13:22 So then we went further and said why does it need to be just one brain?
00:13:27 Could we have multiple brains collaborating mentally to achieve this movement? So that's what we call a brain act.
00:13:35 And we just published a year ago showing the three monkeys that don't even know that they are next to each other
00:13:43 because in different rooms they don't know the existence of the other guys.
00:13:45 They can mentally collaborate to make a virtual arm,
00:13:49 make certain movements that inform the monkeys how they should do it.
00:13:55 And so if you give monkey one the job of controlling the x and y dimensions of the movement,
00:14:12 this is a 3D movement so x, y, and z.
00:14:12 Monkey one does x and y, monkey two does y and z and monkey three does the x and z.
00:14:12 You need at least two monkeys to get a 3D out of this, but if you get a third guy it looks much better,
00:14:17 the results much better and they can get all reward very quickly and at the same time.
00:14:22 Well, the monkeys get together, they synchronize their brains and they work as if they were part of a single brain.
00:14:30 And this experiment, I think our colleagues have not seen it, they thought it was just, some of them,
00:14:36 thought it was just a trick, just some kind of a Hollywood kind of thing. It's not.
00:14:41 We actually used that to show how a single brain may synchronize to operate. Because there's a big mystery.
00:14:48 How multiple areas of your brain actually come together, at the precise moment in time, to do a job.
00:14:54 To make my arms move, to make me speak, to make me reason. Nobody knows. Nobody knows how this synchronization happens.
00:15:01 Well, it turns out that if you put multiple brains separately and you give a common feedback to them, they synchronize.
00:15:09 So I think we found a very profound rule of when millions of people watching TV, the same TV show around the country,
00:15:20 around the globe and they all synchronize.
00:15:24 And when your in a stadium, seeing the same match, the fans, they all synchronize.
00:15:30 So I think we found what is going on, what happens when multiple individuals are recruited to be part of a structure.
00:15:37 And that's the reason why I'm calling this the structure being that multiple ants working together, bees
00:15:43 or birds flying together in a flock, fish swimming together to many humans in a movie theater or a stadium.
00:15:52 I'm calling these our organic computer because it's a synchronized device that is computing In a domain analog,
00:16:04 that digital computers cannot get there.
00:16:06 So that's how we have evolved of this, and of course, five years ago,
00:16:12 we decided okay there's clinical relevance of this thing.
00:16:15 And we make people benefit from brain machine interfaces by restoring mobility to them.
00:16:21 That's the reason you see this lab here, that's why we came to Brazil and decided to this for the World Cup first,
00:16:28 but the project has continued.
00:16:29 And our biggest discovery with brain machine I think in a decade is that if apparently through exposed chronically,
00:16:37 to a user of a brain machine interface or paradigm in which you are controlling with your mind something
00:16:45 and you're getting rich visual and tactile feedback.
00:16:48 You start getting for a paralyzed person with a lesion in the spinal cord, you might start getting recovery of motor
00:16:55 and tactile behaviors below the level of the lesion, which has never been demonstrated with other techniques.
00:17:02 So these are chronic patients, many years after the accident and yet in almost 80% of them, after two years,
00:17:10 we are seeing that they are recovering control of muscles in the legs.
00:17:14 They now can feel their bodies below the level of the lesion.
00:17:19 I think is related to the training that they were exposed to.
00:17:22 Yeah what I'm saying is we did create an exoskeleton, a robotic vest controlled by brain activity.
00:17:30 And we instrumented this exoskeleton to deliver feedback back to the subject.
00:17:35 So the subject, every time he steps on the ground,
00:17:39 there are sensors in the surface of the foot to the exo that detect the pressure of the contact.
00:17:45 That pressure signal is then delivered to the skin on the arm of the patients because it's one of the few parts of the
00:17:51 body where they originally had tactile sensation.
00:17:54 And by adapting the parameters of the speed and the magnitude of this pressure wave on the skin,
00:18:04 we induced the phenomena of phantom limb sensation.
00:18:05 So we fooled the brain of these guys to feel through their arms their legs.
00:18:10 So they report to use they're walking with their own legs and they are touching the ground
00:18:14 and they can even tell you what the ground is.
00:18:16 They can tell when the ground is grass or the ground is sand or if it's hot asphalt,
00:18:23 so the street floors they can distinguish with this system. But then we only wanted originally to restore mobility.
00:18:31 Put them in a device link the device to their brains and get them to walk again.
00:18:35 That was original game, but we always did the neurological examination as a routine,
00:18:41 and we didn't expect to see any change.
00:18:44 Well six months, a month after the World Cup, six months after the training started we started,
00:18:50 we start seeing that these guys were having motor contractions of muscles below the level the lesion.
00:18:57 And seven of these guys had a complete clinical lesion, which means after ten years, that you shouldn't see anything.
00:19:07 You shouldn't see motor contractions, voluntary motor contractions and muscles,
00:19:10 they should not have tactile feelings and they should not have visceral feelings.
00:19:15 So they couldn't feel, for instance, the women could not feel when their period days of the month are.
00:19:22 Well, we're still getting reports from the two women in the project, look, I can feel one of my periods coming.
00:19:28 I actually can feel that I need to go to the bathroom now, I can control my bladder now,
00:19:32 several of them start telling us. And then when we did a motor test, we measure quantitatively the contraction force.
00:19:40 All the sudden we had a woman with 20 newtons of force,
00:19:44 which is the little kind of force that you need to make to start moving.
00:19:48 And we start looking at individual muscles and we could detect the contractions.
00:19:52 So we redid the classification, it's called ASIA.
00:19:54 ASIA is the American Spinal Cord Injury classification standard,
00:19:58 gold standard of classifying patients all over the world.
00:20:03 These guys were, seven of them were ASIA A, which means complete paralysis, and one was ASIA B,
00:20:09 which is sort of intermediate.
00:20:11 Well, in six months 50% of them were promoted to ASIA C, which is partial spinal cord injury. Two years later.
00:20:21 Speaker 1: We're now talking?
00:20:21 Speaker 2: Yeah, we're now talking about guys that can.
00:20:25 Speaker 1: 2017, 2016, 2015?
00:20:26 Speaker 2: Yeah, we started training them in November 2013.
00:20:30 So six months after the training started, one month after the world cup, after we lost to the Dutch,
00:20:36 and I shouldn't say that on camera and lose my passport but it was something in the food to sick.
00:20:44 But in any event, one month after the World Cup ended and we had done our demo, which was seen by 1.2 billion people,
00:20:53 we re-did the neurological test.
00:20:55 And lo and behold, half of the patients had muscle contractions that they could control,
00:21:01 they could actually generate movements that visual, you can see the movements.
00:21:05 And when you put them upright they could simulate walking, and we keep doing it, we keep doing the training.
00:21:13 Now this December we completed two years of training.
00:21:17 We redid the neurological exam, and now 78% of the patients have recovered movement.
00:21:24 So, six out of eight have muscle control below the level, it's not complete,
00:21:32 but it's something that has never been seen.
00:21:34 So, the hypothesis that we have based on studies that were forgotten in the 60s and 70s,
00:21:41 an Australian Pathologists had done a lot of autopsies in Australian spinal cord injury patients that died of natural
00:21:49 causes.
00:21:50 And he realized that in about 60% of the patients there are classified clinically as being complete paralyzed,
00:21:58 there is at least 2 to 20% of fibers of nerves in the spinal cord that is still connected.
00:22:08 They're not totally destroyed but they're quiet very likely, they went blank.
00:22:10 I think our training, now when I read this paper, my hypothesis is that the training,
00:22:16 the intensive training that we did with brain interface of the patients, turned on neurons again in the brain
00:22:23 and these neurons they start sending messages down to the spinal cord to these axons they required.
00:22:28 But it's still there so it's plasticity, it's what John Carls and Mike Merzenik predicted.
00:22:31 Speaker 1: So what would that mean when you think through that and look at future? What are the possibilities?
00:22:39 Speaker 2: The possibilities are tremendous because there are 25 million people in this condition,
00:22:44 spinal cord injury paralysis in the world.
00:22:47 Imagine now if a large percentage of them can recover some movement, some control, because for instance,
00:22:53 one of our patients, one of the women in the group.
00:22:57 Since now she had perineal sensation, she decided to become pregnant and she actually could feel the delivery.
00:23:05 She had bladder control, so she went to work, two of our patients got jobs because now they could get out of the house,
00:23:12 they didn't need to wear diapers anymore. We don't think about it, we had one patient that was hypertense.
00:23:19 He's normal tense now, because the cardiovascular system performs better when we are upright.
00:23:25 And since he's one house a day,
00:23:27 two days a week is enough for the kind of vascular system to recover the blood vessels to open up,
00:23:33 so his blood pressure went down. So being up and walking is a major behavior for we humans.
00:23:40 And this guy's lost weight, and some of them were overweight because of being in a wheelchair too long, a decade or so.
00:23:47 Speaker 1: And when you look further, because it's very important, I understand that, and it's major breakthrough.
00:23:51 But then you look further, when you are able to understand the brain, connect brains, What holds the future for us?
00:23:58 Speaker 2: There are many things. I mean, you saw the prototype of our brainette for humans.
00:24:08 So we are about to get a patient, a naive patient who hasn't been trained yet in our paradigm.
00:24:16 Which takes some weeks, but we want to reduce this training time. Because the beginner, the training is very difficult.
00:24:23 The patient has to really concentrate and in the beginning is a little frustrating,
00:24:26 because the brain has forgotten what is to walk.
00:24:30 Actually the brain has forgotten what is the concept of having lower limbs.
00:24:34 So to virtual reality training we need to re-introduce to the brain the concept, yeah, you have legs.
00:24:40 This body has legs and they move, and we do that by having the patient try to control a avatar of himself, or herself,
00:24:48 walking on virtual space, and it takes many weeks for the patients to get this done.
00:24:53 Well, we are going to start linking the brain of this patient, in non invasive way, with EEG, as you saw,
00:24:59 with a physical therapist that is really well trained in that task.
00:25:03 A normal person would now, I wouldn't say normal, but a person that can walk by herself.
00:25:08 And we are going to link the brains.
00:25:11 And in the beginning of the training 90% or 95% of the signal comes from the healthy physical therapist.
00:25:18 And 5 or 10% comes from the patient who has a spinal cord injury.
00:25:22 So he's going to, his brain's going to, get rewarded faster.
00:25:27 And he's going to have the impression that he's controlling the device.
00:25:29 And I think that motivation, the context, is a driving force for plasticity.
00:25:34 My prediction is that we are going to accelerate the learning curve, because we are going to accelerate plasticity.
00:25:38 So the brain map is going to have a very practical, clinical application almost instantaneously.
00:25:43 Speaker 1: But then also you can use it for different things.
00:25:43 You can start steering things in the world just by thinking.
00:25:45 Speaker 2: Yes, the problem is that a non-invasive technology that we use, EEG, the one that you just put in this,
00:25:57 doesn't have the same resolution in the same information content, it's not as rich in information.
00:26:05 We have to play so much magical tricks to get information out of the signal.
00:26:08 So, it's not as rich as implanting things in the head.
00:26:10 I'm not suggesting that we implant people in the head just so they play video games, but yes,
00:26:15 it's proof of concept the mental collaboration If we get better non-invasive techniques that become portable.
00:26:22 I mean, EEG now is wireless, as you saw, you can have wireless broadcasting.
00:26:29 We have a paper coming this week, although that uses invasive technology in monkeys.
00:26:36 Showing that monkeys can learn to drive wheelchairs in an open space in our lab mentally.
00:26:42 So you see a monkey sitting on the wheelchair and she is driving,
00:26:45 or he's driving the wheelchair to the pod where we are delivering grapes.
00:26:50 But every movement of the wheelchair is coming from the mind of the monkey, via a wireless link.
00:26:58 So it's 500 neurons firing wirelessly, broadcasting the signal wirelessly,
00:27:03 so the motors of the wheelchair turn around and go to the pod.
00:27:07 Speaker 1: But then in that space you can also connect several brains together.
00:27:09 Speaker 2: Yes, we already have an experiment in the lab where two monkeys are collaborating,
00:27:15 each monkey has its own wheelchair. And they only get rewarded if both of them get to the pod.
00:27:20 So the faster monkey helps the slower monkey to get themselves together at the pod at the same time.
00:27:28 So we are already showing the brain working between two monkeys.
00:27:31 Speaker 1: Yeah, but not between humans?
00:27:33 Speaker 2: No in humans we are using for clinical rehab at this point.
00:27:37 But yes, it's conceivable that if we improve the bandwidth
00:27:43 and we improve methods to extract information from the brain, in a non invasive way,
00:27:49 you could have over the Internet millions of people collaborating on a common task.
00:27:53 Speaker 1: So how does the future of your neuroscientific work looks like and the effects of it?
00:28:04 Speaker 2: That's a very good question. I think in one direction we are going to increase the clinical applications.
00:28:11 Because what we saw for spinal chord injury, I think, may be applicable to stroke victims.
00:28:17 It may be applicable to other neurological disorders that require plasticity.
00:28:21 And in fact, I have a theory that I'm about to publish and I'm going to put in my new book, that most neurologic
00:28:28 and psychiatric disorders, independently of their etiology, or the cause of this disease, let's say Parkinson's Disease.
00:28:37 We know that you develop Parkinson's if the cells that contain a particular chemical, dopamine, start dying, okay?
00:28:44 But once they start dying, what we discovered in animals, and then in humans,
00:28:48 is that the lack of dopamine produces like a epileptic seizure, a low level chronic seizure that explains the tremor
00:28:56 and the difficulty to move.
00:28:59 Well we discovered if we put a microchip in the spinal cord and send electric pulses at the right frequency,
00:29:05 tiny electrical pulses that are very high frequency, we disrupt the seizure and the animals
00:29:10 and the patients seem to get better.
00:29:12 So I think this kind of concept that neurological disorders are disorders of neural timing, how they fire together.
00:29:19 If they fire too much, it's not good together.
00:29:22 So I think that I'm going to, in one part of my work, increase the scope.
00:29:28 Use the brain machine interfaces to treat neurological disorders.
00:29:31 That's one, from a basic science point of view, I have two other branches.
00:29:38 One is to push very hard to understand the kind of computation that the brain does that is different from digital
00:29:44 machines.
00:29:46 So I'm building models,
00:29:47 analog models of the brain to particularly study more detailed interaction of the brain magnetic fields.
00:29:54 With the neurons and see if this analog digital interaction, what I like to say,
00:30:00 a recursive analog digital interaction, explains why the brain is different from a digital machine as one line of work.
00:30:09 And the other is to continue to push the envelope on trying to see how large secrets in behaving animals operate.
00:30:16 So, our lab is has now the world record in number of neurons recorded simultaneously.
00:30:22 We getting close to 2,000 neurons now,
00:30:26 but I think we need to increase this to about a 100,000 to a million to start getting close to a picture.
00:30:33 It's like when you do a camera, a movie, and you have just a few pixels of the image, you cannot see it very well.
00:30:39 But if you increase the number of pixels, you start seeing the granularity, you start seeing more
00:30:45 and more of the image, but you're not necessarily need to have all of the pixels of the photograph, or the movie,
00:30:51 to see what is going on.
00:30:53 So I think if we cross the barrier of a million neurons recording simultaneously,
00:30:59 we're going to see a lot of the movie that goes on in the brain.
00:31:03 Speaker 1: Recording simultaneously?
00:31:04 Speaker 2: Recording simultaneously. Yeah, exactly. That's what I mean.
00:31:08 Speaker 1: Yeah and the.
00:31:10 Speaker 1: [INAUDIBLE]
00:31:11 Speaker 1: Can you take me through steps in this lab we filmed?
00:31:25 Speaker 2: Sure, what you're filming, in reality,
00:31:26 is a simulation of the five different steps that our patients undergo when they do the training.
00:31:33 Okay so first, as I said, we need to reinsert in the brain the concept of having legs. So that's basically what we do.
00:31:45 We put them in a virtual reality environment that you're going to see in a moment.
00:31:52 And the patients start interacting with the avatar. We started just with the global concept of walking.
00:31:57 But now we are actually simulating control of the specific muscles of walking,
00:32:02 which we never thought these patients would be able to do with their brains.
00:32:06 They're getting specializing control individual legs with one side of the brain,
00:32:11 for instance the right side controlling the left leg, left side controlling the right leg.
00:32:16 But we discovered that we can do physical therapy by simulating muscle contractions on the video.
00:32:23 So they see a muscle of the leg contracting, and we develop the ability to contract individual muscles,
00:32:29 which is we never thought that would happen. So that's the first step, is the virtual reality.
00:32:34 Then they go to that robotic device, the robot standing on the treadmill.
00:32:40 To learn what is to be inside of a robot,
00:32:43 because you should not underestimate how different it is to be encased in a robotic device.
00:32:50 It's a complete different feeling of what you are.
00:32:54 And since we are providing tactile feedback,
00:32:56 they are getting tactile feedback from their legs inside of a stand-alone robot.
00:33:01 So that takes several months of feeling at ease, normal.
00:33:07 So then we have an intermediate step, where they go and stay in this system that we call zero gravity, zero G.
00:33:17 Where they are upright without a robot and they are practicing with just to be upright.
00:33:23 And trying to move with some orthosis that we fabricate and we give to them to practice,
00:33:30 because they're going to be in an exoskeleton.
00:33:32 We have another step that is just a mix of virtual reality and a stand-alone robot.
00:33:39 And finally, they get into the exoskeleton, just at the end of the process.
00:33:45 And it takes a few months for them to get to that point.
00:33:49 And in the exoskeleton,
00:33:50 they now are using everything they've learned in the previous steps to use the brain activity to control, to trigger,
00:33:58 the movements of the exoskeleton. Now they can trigger individual legs.
00:34:02 And they are getting the feedback from the feet as they walk on the ground.
00:34:07 And sometimes they walk on the ground just looking at a mirror to see their bodies walking upright,
00:34:13 because that helps shape the brain's image of the body.
00:34:17 Sometimes they have goggles because they walk in a virtual reality environment, even though they are in a exoskeleton.
00:34:25 And sometimes they are just walking, doing about 50-some steps back and forth in this laboratory space.
00:34:32 Speaker 1: By thinking, by using their brain.
00:34:34 Speaker 2: By thinking, yes. And that's exactly what we did. This is the third prototype that we have.
00:34:41 The first prototype was used during the demo of the World Cup.
00:34:44 But of course, we had to struggle with FIFA, because FIFA never gave us the conditions to actually do what we wanted,
00:34:52 and I don't need to go into the details.
00:34:54 But from a three minute demo we are down to 29 seconds,
00:34:58 which is almost virtually impossible to do a robotic demonstration.
00:35:02 But what's important in that is that Juliano Pinto, the guy who actually delivered the opening kick of the World Cup,
00:35:08 he trained on the pitch, on the grass for days, and he delivered 57 kicks.
00:35:14 Speaker 1: In the exoskeleton-
00:35:15 Speaker 2: In the exoskeleton, he had 57 attempts and he got 56 correct. Which show that we're in the right direction.
00:35:25 That people can get used to these devices, and they can actually start performing at a very high level of accuracy.
00:35:33 And of course, we just started slow, just with walking straight.
00:35:37 Now we are going to think about, we are already planning turns and other movements that the patients want to have.
00:35:46 But we are learning very quickly now.
00:35:48 So the beginning was very difficult, because some of these patients that you saw were in a wheelchair for a decade.
00:35:54 With no hope of nothing. And I can show you some of the movies that they have of the movements that they can make now.
00:36:04 You would be shocked what a paralyzed-
00:36:05 Speaker 1: By using their brains.
00:36:05 Speaker 2: No, no I'm talking about their own movements without the exo.
00:36:09 When you put them up now in the zero G again, and in the beginning you put them up and say move,
00:36:14 and nothing would happen. They would stand and nothing would happen.
00:36:17 Now you put them in here, and some of these patients can actually, you see them doing this with their own legs.
00:36:25 Suggesting that we reconnected the brain to the spinal cord. Not reconnected anatomically.
00:36:33 Anatomically, there were some nerves that survived there probably. We reconnected it functionally.
00:36:38 The brain can send a message, and the message is getting to the muscles somehow.
00:36:41 Speaker 1: Yeah, and when you look outside the lab to the world, I'd really like the way that you,
00:36:45 how you look at the world and materialize your knowledge and your love for the brain and painting and writing
00:36:57 and looking at software. How do you see that?
00:36:58 Speaker 2: Yeah, well this is something that happened the last five years or so.
00:37:01 What I taught in all my six years, my study of neuroscience was too limited to what most neuroscientists do.
00:37:09 Electrical signals of the brain, computational strategies and behavior.
00:37:14 And then I start thinking deeply with the help of my good friend, Ronald Cicurel, a retired mathematician
00:37:21 and now a philosopher in Switzerland.
00:37:24 And I just came to a realization one day in Montreal when I visit him, while we do our work together and walking.
00:37:32 That actually, when we talk about the brain we should not be limited to the kind of neurophysiological,
00:37:39 neuroanatomical, or neurolingual that neuroscientist talk about.
00:37:43 Certainly I realized that the brain is the center of the human cosmology. The brain is the true creator of everything.
00:37:51 And I start thinking about the whole universe as just raw information, like an empty canvas.
00:37:59 And the brain as the true painter, the human brain. So I don't know if there are other brains out there.
00:38:06 But everything that we have, the history of the planets, the history of the cosmos, the history of the human race,
00:38:15 the theory of evolution, everything that we have conceived since the first human came out of the trees
00:38:23 and started walking.
00:38:24 If you could somehow sum the amount of information
00:38:28 and knowledge processed by every single human brain that ever existed or exists, or will exist, that's the universe.
00:38:37 That's the human universe. And I start thinking about a changing viewpoint.
00:38:44 So first, we thought the Earth was the center of the universe.
00:38:46 Then we thought it was the sun, and then we thought it was the Milky Way.
00:38:51 But then we thought, no, no the center of the universe is the big bang where everything came.
00:38:55 Of course there was something like the big bang, there must have been.
00:38:58 I actually started thinking that the center of the universe, at least for our reference, is our mind,
00:39:04 is the human brain. And I start thinking about everything around us as information, as raw information.
00:39:12 And information that, to get any meaning, to get any description, needs a brain.
00:39:18 And it so happens that the only one that we know is the human brain.
00:39:21 So I have a theoretical experiment we've run on that if some other intelligent lifeform would come in contact with us,
00:39:31 and we actually could talk or communicate somehow.
00:39:34 That lifeform,
00:39:35 assuming he had a brain that evolved through completely different laws of evolution in a different environment,
00:39:43 would tell us a story of the cosmos that is not necessarily ours.
00:39:48 And a complete different cosmology would be confronted with ours.
00:39:53 So I actually think the neuroscience in this century may give us hope.
00:39:59 To bring humanity, the human condition to the center of our lives.
00:40:03 In a position, not in a position but to balance another movement that exist in the world right now.
00:40:10 That seems to say that technology may be able to solve everything.
00:40:15 That technology may be able to educate our kids, take care of the elderly. Run our air ports, run our universities.
00:40:22 Run our knowledge gathering and eventually some loonies say, may replace us. And I think this is crazy, this is insane.
00:40:33 Technology is projection of a much more complex thing called a brain.
00:40:39 When we create a machine like this or create a car, a plane, a computer, or a robot.
00:40:46 We are just projecting our abstraction to a tangible device that is infinitively less complicated than the creator.
00:40:56 So the creator is the mind, the human mind.
00:41:00 And that's the reason I start thinking and I'm not talking about philosophy.
00:41:03 I'm not a philosopher, I know nothing about philosophy.
00:41:07 I'm talking about as a neuroscientist trying to use what I know about the brain to actually say that the brain has a
00:41:12 point of view. The brain is not a passive decoder of the environment.
00:41:17 The brain shaped through evolution, was shaped through evolution by an environment, by our genes, by mutations
00:41:23 and everything. But as we are born and we grow in the early phases of our lives, we start developing a model of reality.
00:41:33 And an interpretation of reality, and we start painting this empty canvas and we give a meaning to it
00:41:46 and we create a story. And we create history too.
00:41:46 And that's a much more profound in my opinion view of the brain and the role of neuroscience then we taught before.
00:41:55 And it changes I think the balance. If we believe in this, the human condition becomes a much more precious.
00:42:03 A single life becomes much more precious than we thought before.
00:42:08 Because, the epic of a single life first of all, can not be reproduced ever and it will never happen again.
00:42:17 It's like a book that will never be written again
00:42:20 and I think it gives us a little more recognition as human beings than currently I see the world going on.
00:42:31 And if I can just to finish, if you read the Iliad or the Odyssey,
00:42:36 which are considered the pinnacle of human condition, a description of the human condition.
00:42:43 When a soldier, a Greek soldier would die in Troy in a battle, Homer describes who he was.
00:42:51 Who are the parents, who are the children that he's leaving?
00:42:54 What is the whole history of that individual that will never be recovered?
00:42:58 So, compare that to the news of a death in the newspaper today which is just a number, nothing.
00:43:06 Homer, God forbid, 3,000 years ago knew better what the human condition is than we probably know now.
00:43:16 We are losing that and I think that process of losing it is part of our brains thinking that it is really nice
00:43:25 and good. And is worth it to mimic computers instead of maintaining our integrity. Our human condition integrity.
00:43:34 Speaker 1: So in your neuroscientific field with several neuroscientists working, are you unique at this?
00:43:44 Speaker 2: No.
00:43:44 Speaker 1: In looking at-
00:43:45 Speaker 2: In terms of the way I look at the brain?
00:43:48 Speaker 1: Yeah.
00:43:48 Speaker 2: No, no, I think there are many people.
00:43:50 Speaker 1: Yeah.
00:43:51 Speaker 2: Of course there are nuances.
00:43:54 It's a big field and the brain is very complicated and there are subtleties from a neurophysiological point of view.
00:44:04 For instance, people believe that we should go deeper into the molecularly structure of the brain.
00:44:09 I find this fine from an intellectual point of view of course studying individual synapses and everything.
00:44:15 I just don't think any of this will allow us to explain how the system works.
00:44:19 The system is truly non-linear and if you start studying just a molecule,
00:44:25 you're not going to be able to track it back to the system.
00:44:28 It's gonna be impossible, the number of non-linearities that you have to face.
00:44:32 So but there are many people that are realizing what we are discussing just now.
00:44:36 It's not just I would say honestly, there is not a mainstream yet.
00:44:41 But neither was population coding 30 years ago when I started.
00:44:46 People gave me no hope of having a career in studying populations of neurons, and here I am.
00:44:54 So I'm used to the idea that you may start with notions and concepts that are not mainstream,
00:44:59 and you need to demonstrate that they're worth. That's part of what science is about.
00:45:04 The problem is science is becoming extremely conservative. And it's very difficult to break through with new ideas.
00:45:09 It's much more difficult than when I started, when I was a kid but we're stubborn.
00:45:14 Speaker 1: Yeah, what are you standing in for? Your ratio works standing in five years.
00:45:21 What is the future of your neuroscientific field?
00:45:23 Speaker 2: Well I think as you can see here, this is going very quickly.
00:45:27 The clinical applications I think are going to grow tremendously.
00:45:31 I think that basic science is going to evolve in the sense that we are going to.
00:45:36 I mean we are accelerating the curve of the number of neurons that we can record simultaneously.
00:45:40 It used to be a very flat, straight line. It took us 30 year to get to 1,000, 2,000.
00:45:47 But now things are accelerating cuz we are learning better ways to do this.
00:45:54 My ambition to the end of my life is to be able to actually formulate this theory.
00:46:00 A comprehensive theory of the mind of the brain, the way we talk just a minute ago.
00:46:08 And that's what I'm doing right now. I'm spending a lot of time writing and reading.
00:46:13 I'm reading literature on communication, Marshall Mcluhan for instance,
00:46:17 I became fascinated by what he used to say in the 60s and 70s about the media being the message.
00:46:24 And how communication has changed our nature.
00:46:29 And from the moving from the oral tradition of poetry of the Greeks, to written manuscripts, then to the print,
00:46:39 to the radio, telegraph, telegraph, to the radio, TV, Internet. I think that actually he got it.
00:46:46 He didn't know anything about the brain, but some of his writings in the 60s
00:46:50 and 70s actually got how relevant communication is to synchronized brains.
00:46:56 Speaker 1: I understand that and the human brain net, is that going to be a fact?
00:47:02 Speaker 2: Well, we're doing as a clinical application that's what we are doing right now
00:47:08 and I want to see how that goes first.
00:47:11 I want to see if it is advantageous to the patients because that's a very concrete
00:47:15 and tangible problem to improve training.
00:47:18 But suppose you have a phasic patient, a patient that suffered stroke that destroyed the left side of the brain,
00:47:25 the cortex and he cannot talk. But the right hemisphere is there.
00:47:30 And there's some language capability left on the right hemisphere.
00:47:34 Suppose you can connect this guy with someone else who can speak.
00:47:38 And you can synthesize voice by having a brain net, working with that stroke patient.
00:47:44 Maybe you can improve the training on the right hemisphere, by plasticity because we know it happens,
00:47:50 even in an adult patient.
00:47:51 If you didn't have any lesion on this side, just this,
00:47:55 you may try to improve the language skills of the right hemisphere. So that's another thing that I want to start soon.
00:48:04 Because they are ten times more stroke victims in the world than spinal chord injury victims.
00:48:10 So you're talking about a quarter of a billion people in the world with stroke consequences.
00:48:16 Speaker 1: So when you develop what you are doing in the way that you can see that more
00:48:24 and more you can have parts of the brain that people for some reason compute or it's almost dead,
00:48:32 you can reactivate it by somebody else?
00:48:34 Speaker 2: Exactly, either by combining the brains with someone else. Suppose you're sibling.
00:48:40 Your wife or your daughter or your son help you in the training. And eventually, it becomes a surrogate.
00:48:47 Now you can talk through this combination or you can communicate.
00:48:51 Because there are lots of patients also that become totally detached from the world.
00:48:56 They're concious, their brains are working, and so they are absolutely conscious.
00:49:00 But for instance, all the muscles, Lou Gehrig's disease or ALS, all the muscles of the body are paralyzed.
00:49:09 So they cannot blink, they cannot talk, they cannot breathe, but they're conscious and their brain is fine.
00:49:10 Their central part of the brain is totally fine. And these patients can barely communicate.
00:49:18 There is a brain machine interface for those patients that my friend in Germany took
00:49:21 and use brain bomb were created by the same time that we were doing experiments with rats.
00:49:26 We didn't even know each other at that time. That works, but it's phenomenal. In news he's a hero for this community.
00:49:33 But it can be improved, and then things can be better, faster. So I think that's where we can go.
00:49:41 Speaker 1: When you look at the brain, the importance of creativity, of intuition.
00:49:47 Speaker 2: Yeah, and that's one of my concerns. Computers are not creative, computers don't generate knowledge, we do.
00:49:55 We get raw information and combine it in ways that cannot be predicted.
00:49:59 And that's the reason, as we talked before, I like painting.
00:50:02 Because painters, I loved when they asked Picasso what the painting meant,
00:50:08 one of the particular paintings that he had that day. And Picasso said, well, if I knew I would not have painted.
00:50:14 And this is it, this is deeper than probably he meant for me as a neuroscientist because it's true.
00:50:21 I think his painting is more of an analog description of what we're thinking and what we're feeling.
00:50:27 This is a projection to the outside world of some internal state of the mind
00:50:34 and that's why I think this transition that we discussed.
00:50:39 The impressionist and in modern art, it was an explosion of form, form disappeared.
00:50:44 While the old guys tended to be very careful about reproducing every corner, every shadow of a scene, of a person,
00:50:54 modern art removed the concept of shape from painting and sculpturing because it didn't matter anymore.
00:51:03 That was a completely different expression, surrealism, cubism.
00:51:07 This is totally linked to the mind view of the brain in the sense of trying to project what is inside rather than
00:51:16 taking a shot of what is out there.
00:51:19 In photography of course, good these guys are business, the guys who painted everything.
00:51:25 As poor amateurs like to still paint this thing. But art, you talk about creativity, art.
00:51:34 My concern is that if we become just computers, art will disappear. Computers don't do art. They tried to mimic.
00:51:41 They can compose artificial music, they can do some text, but they don't carry the human condition in those letters
00:51:49 and those brushes, no?
00:51:52 We do, and I fear that a complete total allegiance
00:51:58 and reliance on technology may destroy the human capability of being creative. Of doing art, of doing the unexpected.
00:52:06 Speaker 1: And a conscious way of brains working together like in soccer or-
00:52:12 Speaker 2: Well, when you saw the soccer fans in the stadium, I think they are.
00:52:18 I created this metaphor and this operational definition of an organic computer.
00:52:24 An organic computer is basically multiple brains that get synchronized in nature by whatever signal.
00:52:31 Visual, tactile, auditory.
00:52:33 That makes them operate as a whole so the flock of birds is my best metaphor or school of fish.
00:52:41 The flock, if you look at the flock,
00:52:43 it's very interesting because you're minimizing the chances of reaching individual to be attacked by a predator.
00:52:52 But the birds change position in the flock. Sometimes they have to go to the front and break the air, they get tired.
00:52:59 They move to the internal center of the flock where they are most protected cuz they're tired.
00:53:07 But there are birds that have to fly on the edge, and at the edge they are more vulnerable.
00:53:11 But they are always rotating.
00:53:12 So there's dynamics in this thing that it seems to be minimizing the chances of being caught.
00:53:19 If you're flying by yourself, a falcon may get you. An eagle may get you much easier.
00:53:25 And as a flock, they are able to get to a source of food,
00:53:29 and they may get there easier than just individual birds looking, so birds and fish have memory like we do.
00:53:40 Speaker 1: So tell me about your other brain projects in Natal.
00:53:43 Speaker 2: Well, Natal is a completely different thing.
00:53:46 It's a parallel track on my life, that it started in 2002, end of 2002, beginning of 2003,
00:53:52 when President Lula was elected here in Brazil.
00:53:55 I was already for a long time in the United States, 14 years already in the United States,
00:54:00 I saw an opportunity to actually return to Brazil and do something.
00:54:06 Not just to do science in Brazil, but to use science as a completely different thing. As a agent of social development.
00:54:14 In a part of Brazil that is well known for Brazilians as being the most underdeveloped part of the country,
00:54:21 in the northeast of the country. And I wanted to prove that human talent is everywhere.
00:54:27 That you could go and just drop from a parachute in a place and you start creating scientific infrastructure.
00:54:36 And you invest in high level education. In a way, that will transform the social reality of the community.
00:54:41 So I chose a small town in the outskirts of the capital of the human artist state and the capital is Natal.
00:54:50 But the city's actually named Macaiba. And so it's the name of a palm tree that is typical division.
00:54:56 And you have 65 inhabitants and the worst human and development indexes in the state
00:55:05 and so we're going to launch here in one of the worst in the country.
00:55:07 And what we did was to go there and to create in parallel to an institute to do neuroscience, like any institute.
00:55:14 To use the knowledge we have as there are scientist who design an education program that actually starts in the
00:55:21 prenatal care of the mothers of our future students.
00:55:26 So because human mortality, women mortality rate was very high, particularly pregnant women mortality rate.
00:55:35 So at that time about 90 women per 100,000 deliveries would die.
00:55:39 So very high, 20, 30 times higher than you should have normally.
00:55:46 We create a clinic, a women's clinic, to oversee the prenatal care of all the women in the region.
00:55:56 And to give an idea, we start from nothing. Now we are doing 12,000 appointments a year.
00:56:03 And we had already 60,000 appointments since we started.
00:56:06 Which means that pretty much every woman in that city that got pregnant in the last six,
00:56:12 seven years had gone through our prenatal care system.
00:56:15 It's all free of charge, it's all public, and it's the best prenatal care you can get that medicine can offer.
00:56:21 Because as neuroscientists we knew then if you don't provide the best possible prenatal care,
00:56:28 any problems that a child will have during pregnancy cannot be fixed.
00:56:33 It's very difficult, it's almost impossible right now.
00:56:36 Any learning disability or any other malformation of the brain it will not be corrected.
00:56:40 So how could you have a neuroscience based education program that doesn't offer these students a chance to be born with
00:56:48 the highest possible neurobiological protection to achieve happiness.
00:56:54 Because that's my definition of education is the pathway to happiness.
00:56:57 So we created this education program that starts in prenatal care
00:57:00 and then we start enrolling 1500 kids a year to three schools that we created.
00:57:08 Two in that state and one in another state, in Viyella. Where the kids go in one part of the day to public school.
00:57:15 Which in Brazil is not full time. It's just four, five hours a day.,
00:57:19 But on the other period of the day they would come to our schools.,
00:57:23 In our schools in Macahiba, Natal, [INAUDIBLE] Zaire are all lab science oriented.
00:57:29 Even to learn portuguese you learn in a lab.
00:57:33 We basically make these guys, these students from that time from 10 to 15 years old.
00:57:40 When we open our new school in the campus, of the brain, that we were building is a 100 hectares campus in that region.
00:57:47 It's taking us seven years to finish that. The school is going to be from zero to 17.
00:57:52 So from the moment they are born, they can go to the nursery, to the moment they finish high school,
00:57:59 they are going to be in our school, if they want.
00:58:02 Then, we are going to have an undergrad program in the campus for kids that want to pursue a scientific career.
00:58:10 Master's, PhD, and postdoctoral training.
00:58:14 So we're going to have a program that means that a kid can be there for 30 years, if they want.
00:58:17 But in the case of this science education program that we created on the opposite period of the day from public school
00:58:27 these kids became Protagonists in their own education.
00:58:31 They basically got involved in learning as a pleasant experience.
00:58:35 And they develop an ethics of learning that we never saw in the region,
00:58:41 in the most parts of Brazil because they don't go to our schools because they have to, they go because they want to.
00:58:46 And that school became a school not only for science but for developing citizens.
00:58:53 Citizens they are fully aware of their rights.
00:58:55 Fully aware of their responsiblity in society and fully aware that science
00:58:59 and knowledge can be the passports for their happiness, for their further education.
00:59:05 And this thing multiplied to a point that we have already 11,000 kids that have gone through this schooling system.
00:59:11 And for the first time in the place history, Macahiba, in the neighborhoods next to it,
00:59:18 these kids are gaining access to the best universities in Brazil.
00:59:22 In their vision, public universities where they could never make it cuz they never could pass the admissions exam.
00:59:28 Even though our schools don't have exams, we don't do tests. We don't believe in tests.
00:59:32 We don't believe in the Anglo-Saxon punitive way of teaching.
00:59:36 We believe in the Finnish way, without knowing we have replicated a Finnish approach to a location in Brazil.
00:59:43 Without knowing until very recently that we're very similar parallels with one caveat that the Finnish have not learned
00:59:49 yet. We do the education since the prenatal care. So and now the women, our partners too.
00:59:57 We created a community that is very supportive of everything we do because different from universities in the world
01:00:04 that really are this beautiful paradises of knowledge
01:00:08 but the surrounding parts of the university have nothing to do with the university
01:00:11 and have no idea what is going on inside the doors. I see that particularly in United States and even here in Brazil.
01:00:18 We create a campus that has no walls. It's totally powerless to the community.
01:00:25 And the community has learned the value of science.
01:00:28 Because science is not for paper, books, applications, acquisition, knowledge.
01:00:32 Science in Matal, in Macahiba, we demonstrate that science can also be an agent of social and economic transformation.
01:00:39 Because in addition to promoting education in women's health, we have created a whole cascade of jobs,
01:00:46 an entire production line of suppliers, people that make construction work because we are building a campus.
01:00:54 So it is very nice to see the fathers of our children building this campus, they work for the construction company,
01:01:02 that has built. And the first build, they're gigantic buildings. They're 12000 square meter research institute.
01:01:10 And then there are 12000 square meter school.
01:01:13 Speaker 1: Very good, quite impressive. I think when I hear you, I think dreaming It's very important.
01:01:25 Speaker 2: Yeah.
01:01:25 Speaker 1: For science.
01:01:25 Speaker 2: The soup title of my new book about the Natal, Macahiba project is how to be a utopia.
01:01:27 A scientific social utopia because in our days utopia has become almost like a curse word, a negative word.
01:01:39 And I disagree frontally with that.
01:01:42 I think we have to have utopias and dreams, even if we don't fulfill them completely.
01:01:47 It's very important to be engaged in one, because of the process makes us want to get out of our house
01:01:52 and go out here in this pretty tough cruel world and actually do something complete.
01:01:59 And in Natal, I think that's what happened. We had Brazilians coming from all over the country.
01:02:06 Teachers, scientists, physicians, administrators, technicians who believed in the utopia
01:02:14 and now they can put their hands on these walls and they can see these kids getting to the university.
01:02:20 And so, it's a very rewarding experience.
01:02:23 In fact, it's one of the things that when I go to Natal, I feel the real meaning of science.
01:02:30 When I look and hear these patients and I go to Natal, I actually feel it was worth it, these 35 years of work.
01:02:38 Neuroscience you also need dreaming, I suppose.
01:02:40 Absolutely, yeah, we need dreaming for a variety of reasons but in neuroscience, yes.
01:02:46 I think if you equate, as we discussed before, if we equate neuroscience
01:02:49 or any science just with technology development, you're missing the most important part of it.
01:02:55 It's this dream, it's this creativity, it's trying to answer questions that nobody has ever asked
01:03:01 or nobody ever had an answer for.
01:03:04 So the first time that John and I recorded 26 neurals simultaneously in a little rat, in our labs,
01:03:11 in the middle of the night.
01:03:12 First,
01:03:13 he told me that there was a good thing we could share a lawyer for our divorces because we're there five in the morning
01:03:18 recording a rat brain. And our wives will never believe that we're actually doing it.
01:03:23 But the second thing we thought, both of us in Philadelphia in 91 was this is going to change everything
01:03:31 and nobody knew. But we knew, we were the first one to see those 26 neurons fine together.
01:03:36 And it may sound little but for us that was the universe, that was the thing that changed our lives.
01:03:43 Speaker 1: You were talking about technology being, people that only believe in technology for a solution.
01:03:49 And that sends off thinking of Silicon Valley.
01:03:52 Speaker 2: Well yeah, I think those guys are living in a bubble.
01:03:56 They're very interesting things that they have created
01:03:58 and they're very interesting things that have changed the world that have created
01:04:03 but they're not the gods of the universe. That they think they are And a lot of hopeless and arrogance there too.
01:04:08 There's a very, a lot of talent people and a lot of gifted people.
01:04:13 But you just need to go to San Francisco
01:04:15 and ask the opinions of the people who live in San Francisco before this thing explodes, Silicon Valley,
01:04:21 and what is going on there.
01:04:23 Because a lot of people there believe that technology will solve all our problems, and that's not true.
01:04:28 Our problems will be solved by the good old-fashioned way of humans interacting
01:04:34 and trying to find a consensus to live together.
01:04:36 Through democracy, through political engagement, through social engagement,
01:04:42 through recognizing that the knowledge of the body is more With the same opportunities
01:04:46 and work to increase the opportunities to everybody.
01:04:50 And try to look for a way so everybody can seek happiness and achieve a good amount of it, not perhaps everything,
01:04:58 but a good amount, everybody makes life decent for everybody.
01:05:03 And to believe that we're going to solve all of the problems of the universe through Facebook, Twitter, or to robots,
01:05:10 or artificial intelligence is iudicrous.
01:05:12 Is in fact, in my opinion, a new wave of where you have to reduce human value,
01:05:23 you have to devalue the human contribution.
01:05:24 Because then, if you deduce human cost of labor, you increase profits to infinity as a very well-known equation.
01:05:33 You cannot eliminate human value, it is obvious.
01:05:37 But so in some senses, in a very main sense, some of the prophecies that is gurus like Kurzweil
01:05:47 and others have made that we are going to be replaced are not only foolish and not based on any scientific data.
01:05:57 They're dangerous in my opinion, they actually confront us with the fact that there has to be an answer to that,
01:06:03 and the answer is that we are humans.
01:06:06 And our most value, most precious capabilities are not out there for a digital computer to replace.
01:06:17 Speaker 1: It's neglecting the value of the brain.
01:06:19 Speaker 2: It's neglecting the value of the human species, in my opinion.
01:06:22 Millions and millions, billions of years of evolution they took us from a piece of rock,
01:06:31 or star dust to a thinking creative, non-conformist human brain.
01:06:40 And it's destroying the fabric of humanity in my opinion. So, we need to be aware of it and confirm these guys.
01:07:00 Speaker 1: [INAUDIBLE] I think.
01:07:00 Speaker 2: Yeah.
01:07:00 Speaker 3: Maybe it's a bit off track, but most of the time when you interview brain specialists. It's very brainy.
01:07:04 Speaker 2: Yeah.
01:07:04 Speaker 3: That when we look around here, all the metaphors, so to speak, or what we see,
01:07:07 is actually very cooperate-able, very with the body, very connected to movement.
01:07:11 And so, it's not, even when you say the brain is the center of the universe, it's so much acted out through all these-
01:07:31 Speaker 2: Yeah, well that's the difference of a technician and a scientist.
01:07:34 My professor here in Brazil, which was the father of neuroscience in Brazil, Cesar Te Maria.
01:07:39 Always told me, there's a big difference between a technician and a scientist.
01:07:42 A technician builds gizmos and runs things like a robot.
01:07:46 A scientist thinks like a human, and thinks about science in broader terms than just a specific field
01:07:54 or a specific area of his or her work.
01:07:59 I think we scientists almost need, by default, to have a very profound and deep intellectual background
01:08:07 and we need to think about the consequences of what we do. The legacy of what we do and the way our science is used.
01:08:14 We didn't talk about this, but there's a very near danger of weaponizing the brain.
01:08:18 And I'm totally opposed to it because this is the last frontier.
01:08:23 And I don't want to see what I did, what I created, called brain meshing interfaces, being used to harm or kill people.
01:08:31 So-
01:08:31 Speaker 1: [INAUDIBLE]
01:08:32 Speaker 2: Well, you can imagine this is happening now in some places,
01:08:36 particularly in the United States where Department of Defense is thinking about using brain machine interfaces to
01:08:41 create weapons. That humans can control just by thinking.
01:08:45 And I firmly oppose this and I think that neuroscientists speak out against this kind of use of this research.
01:08:54 Speaker 1: It's a good question. Or a good statement you're saying, because that is true.
01:09:05 The moment you cross the border of knowledge again-
01:09:05 Speaker 2: Yes. And our only hope is society.
01:09:08 Because we scientists push the envelope to discover what is possible, but is society's duty
01:09:13 and right to regulate what can be done with this knowledge around the world.
01:09:18 Speaker 1: When you say the human brain interface concept, you said? That's more than connecting therapist and patient?
01:09:30 Speaker 2: Yeah, what people are thinking there is totally, I mean, it's totally for me unethical.
01:09:38 Speaker 1: What are they thinking of?
01:09:40 Speaker 2: Well,
01:09:40 they're thinking about implanting soldiers with electrodes to record brain activity we can use to control guns
01:09:45 or weapons or whatever. I don't know the details because I refuse to even listen to the details.
01:09:51 But this is a debate that has to be done among scientists and society not only among neuroscientists yes.
01:09:58 Speaker 1: You mean, you create an exoskeleton, but you put it inside.
01:10:07 Speaker 2: No no, you get signals from the brain to control a machine gun or a missile launcher device, god knows what,
01:10:15 I don't know, or an exoskeleton for a soldier to go to war.
01:10:17 And that's not what I had in mind when I created this technology. This is what I had in mind.,
01:10:23 Speaker 1: Cuz when you envision, not this part, but [CROSSTALK] but
01:10:26 when you envision a world where this brain nets with work, how far can it go?
01:10:38 Speaker 2: Well, at this point I told you I don't have, it's just superstitions and hints,
01:10:44 and gut feeling to describe it. I cannot tell you precisely what it could go.
01:10:50 I think about as I told you, potential applications that can be beneficial to mankind,
01:10:57 and to people that are suffering from disorders or diseases.
01:11:00 But I don't even think of sci-fi scenarios that are harmful.
01:11:05 Speaker 1: [INAUDIBLE]
01:11:06 Speaker 2: Well, I think that if we could communicate better.
01:11:11 If we could find a way of communication that is more natural
01:11:14 and better perhaps we will figure it out that we all the same,
01:11:19 that we have the same fears no matter where you came from, we have same aspirations, we have same desires,
01:11:23 we are all human by the way.
01:11:25 And I look at things like the refugee crisis in Europe,
01:11:32 perhaps by brain to brain communicating we realize that we are all coming from the same place and, by the way,
01:11:40 the place was Africa. And so, race prejudice, prejudice based on economic differences, on religion.
01:11:52 All these things would disappear if we could somehow convince people that what goes through in our brains is the same
01:11:59 thing, it's the same stuff. And what our brains produce is the same.
01:12:04 Speaker 1: So, when you look in the future brain communication will be more and more elaborate?
01:12:08 Speaker 2: I hope it could become more and more elaborate.
01:12:14 In fact, if you read Arthur Clarke's 3001, the last book of his series that is titled 2001.
01:12:22 He starts the book with something called brain caps in 3001 and people communicate by brain caps in 3001.
01:12:29 He would be happy to know that we're a thousand years early in getting some of the stuff to work.
01:12:42 Of course, what he described I don't think will ever happen,
01:12:54 but it's interesting to see that neuroscience can even compete with science fiction.
01:12:56 Speaker 3: Elaborating on that last one, the film Avatar came out in 2008 and it seems now 2015 we're already on that-
01:13:01 Speaker 2: I always wanted to ask Cameron where he got the idea. Because he claims he had a dream.
01:13:04 We had published many scientific papers before he had that dream I think.
01:13:13 So,
01:13:13 I always wonder where he got that idea of having a guy in a machine controlling an avatar because this was out there.
01:13:15 I would be very, very curious to ask him where he really got the idea.
01:13:22 Speaker 1: And he-
01:13:22 Speaker 2: That's the director of the film, you know? Cameron.
01:13:24 Speaker 3: But as far as the technical aspect is concern-
01:13:28 Speaker 2: No, there are many things there that are not possible of course and he just made it up.
01:13:35 Which is the advantage od science fiction to us, we cannot make it up.
01:13:38 Speaker 1: Yeah, but when you really work, collaborate on what you are doing and what other neuroscientists are doing,
01:13:45 we work on the frontier of knowledge in that sense. It's unimaginable what is possible when it works-
01:13:54 Speaker 2: Yeah, as I tell all my students always, imagination is always the limit here.
01:13:58 Speaker 1: Yeah.
01:13:59 Speaker 2: And in this labs we're not here to do the mundane and the incremental things,
01:14:05 we are here to push the limit of neuroscience.
01:14:08 Speaker 1: So, the imagination is the only limit when you look at the possibilities.
01:14:15 Speaker 2: Yes, but of course, the time scale is not tomorrow.
01:14:19 But I like to work with people that likes the deal, the deal of thinking far ahead and trying to make it happen.
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