Speaker 1: Why is it so hard to reverse engineer the brain?
Speaker 1: Can't we just measure the signals and all of the
Speaker 1: brain cells and then figure out the neural code. And
Speaker 1: if not, why not? And what does this have to
Speaker 1: do with solving vision loss and eavesdropping on the activity
Speaker 1: of cells using other cells and communication between brains using
Speaker 1: something other than conversation or observing and understanding and maybe
Speaker 1: changing our own experience of the world. Welcome to Intercosmos
Speaker 1: with me David Eagleman. I'm a neuroscientist and author at
Speaker 1: Stanford and in these episodes, we sail deeply into our
Speaker 1: three pounds universe to understand the mysterious creatures inside the
Speaker 1: eighty six billion neurons that are chattering along with tiny
Speaker 1: electrical and chemical signals producing our experience. Now, today's question
Speaker 1: is how do you actually get inside the brain to
Speaker 1: study it? After all, we know that the brain is
Speaker 1: the root of all of our thoughts and hopes and
Speaker 1: dreams and aspirations and our consciousness. And the reason we
Speaker 1: know this is because even very small bits of damage
Speaker 1: to the brain change who you are and how you
Speaker 1: think and whether you're conscious. Note that other parts of
Speaker 1: your body, like your heart, can get completely replaced by
Speaker 1: a machine and you are no different. Or you can
Speaker 1: lose your arms and your legs and you can still
Speaker 1: be conscious, or you can get a kidney replacement and
Speaker 1: you're still thinking about your life and your family and
Speaker 1: what you need to do tomorrow. But even a tiny
Speaker 1: bit of damage to the brain caused by let's say
Speaker 1: a stroke or a tumor or a traumatic brain injury,
Speaker 1: even a small bit of damage can change you entirely.
Speaker 1: Even if you don't lose your consciousness, you might lose
Speaker 1: your ability to think clearly, or to speak, or to move,
Speaker 1: or to recognize animals or understand music, or understand the
Speaker 1: concept of a mirror, or a thousand other things that
Speaker 1: have taught us over the centuries about the complex landscape
Speaker 1: of this three pound inner cosmos. So we know the
Speaker 1: brain is necessary for our cognition and experience, but we
Speaker 1: didn't get to that understanding through detailed studies of the
Speaker 1: intricate circuitry, but instead mostly through observations of crude damage.
Speaker 1: So there's still an enormous amount that we don't understand
Speaker 1: about how the whole system works. We only have a
Speaker 1: sense of how it breaks. It would be like if
Speaker 1: you were a space salien and you looked at cell
Speaker 1: phones and discovered that if you zap the phone with
Speaker 1: your laser, then it doesn't make calls anymore. Okay, that's important,
Speaker 1: but it doesn't tell you how telecommunication works in terms
Speaker 1: of base stations and frequency bands and compression and sim
Speaker 1: cards and everything else. For that, you would need to
Speaker 1: take off the cover of the cell phone to figure
Speaker 1: out what the billions of transistors are actually doing. And
Speaker 1: that's really our modern challenge in neuroscience to study this
Speaker 1: incredibly detailed system more directly. So why is progress still
Speaker 1: so slow on that front? Well, it turns out it's
Speaker 1: very hard to study the brain's trillions of neurons directly,
Speaker 1: this pink, magical computational material that mother nature has refined
Speaker 1: through hundreds of millions of years evolution. Why because this
Speaker 1: is the computational core, and so mother nature has protected
Speaker 1: it in armored bunker plating. So that's the first challenge.
Speaker 1: The brain is tightly protected inside the prison of our skull.
Speaker 1: But that's only part of the challenge, and that can
Speaker 1: be addressed by careful neurosurgery. The bigger difficulty is that
Speaker 1: even when we can get in there by drilling a
Speaker 1: little hole in the skull. What we find is an
Speaker 1: incredibly densely packed device made of very sophisticated units that
Speaker 1: are microscopically small, and there are almost one hundred billion
Speaker 1: of them, which is about twelve times more than there
Speaker 1: are people on the planet. And each one of these
Speaker 1: neurons is sending very tiny electrical signals tens or hundreds
Speaker 1: of times per second, and these signals zoomed down axons
Speaker 1: and cause chemicals neurotransmitters to be released. And it's not
Speaker 1: generally clear how to read this insanely dense circuitry to
Speaker 1: understand how these trillions of incredibly small signals racing around
Speaker 1: in there lead to a particular outcome at the scale
Speaker 1: of a human like you move your arm, or you
Speaker 1: have a craving for pistachios, or suddenly you're reminded of
Speaker 1: the poem osomandias or whatever. What is the relationship between
Speaker 1: this small scale and the large scale? So how do
Speaker 1: neuroscientists try to decode this incredible complexity. The answer is
Speaker 1: by marrying the technology that we have like computers, directly
Speaker 1: to the cells of the brain. And this is what
Speaker 1: we generally call a brain computer interface or BCEI. We
Speaker 1: use that term to refer to essentially anything that allows
Speaker 1: direct communication between the brain and to an external device.
Speaker 1: So people use these to control wheelchairs or robotic arms,
Speaker 1: or type directly onto a screen or speak through a
Speaker 1: synthetic voice. The idea is to use BCIs to restore
Speaker 1: functions in people who have lost them, like paralysis or blindness,
Speaker 1: and someday perhaps to enhance the capabilities of healthy people. Now,
Speaker 1: how does a BCI actually work. People sometimes think about
Speaker 1: BCIs as measuring electrical activity on the scalp with an
Speaker 1: EEG electroncephalogram, and that counts, but you don't get very
Speaker 1: much detail from the outside of the skull. So the
Speaker 1: more sophisticated forms of BCIs involves measuring brain activity directly
Speaker 1: from the cells. And the main way to do this
Speaker 1: is with small metal electrodes that you insert into the
Speaker 1: brain tissue. And with these electrodes you can send little
Speaker 1: electrical zapps to stimulate the neurons, and you can can
Speaker 1: also listen to hear when the neurons themselves are giving
Speaker 1: off small electrical signals. Now, this has been a technology
Speaker 1: that researchers and neurosurgeons have used for many decades, but
Speaker 1: it's still a challenge because you have to drill a
Speaker 1: hole in the skull and these little, tiny metal electrodes.
Speaker 1: Although they're tiny, they're actually pretty big from the point
Speaker 1: of view of neurons. From the point of view of
Speaker 1: the neurons, it's like inserting a tree trunk. It damages
Speaker 1: the tissue. Now you've probably heard of companies like Neurlink.
Speaker 1: They're still inserting electrodes just like neurosurgeons have done for decades,
Speaker 1: but they're working to make them smaller and finer and
Speaker 1: robotically inserted, and also wireless in their communications so the
Speaker 1: information can go back and forth without having a cable there.
Speaker 1: So it's a better version of the same idea of
Speaker 1: sticking electronics into the brain. But are there new ideas
Speaker 1: about how to read and write to brain cells, about
Speaker 1: how to interface with the brain. Today, we're going to
Speaker 1: talk about what is at the cutting edge, and so
Speaker 1: for that I called a colleague of mine who is
Speaker 1: shaping the future of BCI technology, Max Hodak. Max is
Speaker 1: an unusually brave thinker. He started studying brain machine interfaces
Speaker 1: as an undergraduate, and while most people would be thrilled
Speaker 1: to simply be a part of that. He was already
Speaker 1: thinking about the ways that parts of the science were
Speaker 1: inefficient and could be improved. Some years later, he went
Speaker 1: on to be a part of the co founding team
Speaker 1: at Neuralink and he became the president, and then four
Speaker 1: years ago he left to found his own company, Science Corporation.
Speaker 1: When I visited him at Science Corporation recently, many of
Speaker 1: the things I saw there would have seemed like science
Speaker 1: fiction fantasy just a few years ago. So here's my
Speaker 1: interview with Max Hodak. You started a company called Science Corp,
Speaker 1: which will refer to as Science and tell us about
Speaker 1: science because it's so exciting what you're doing there.
Speaker 2: Our main focus at Sciences is restoring vision to people
Speaker 2: that have gone blind because they've lost the rods and
Speaker 2: cones in the retina. And I this was not something
Speaker 2: I'd not worked on the retina before, but I had
Speaker 2: this thesis that that the technology was there that this
Speaker 2: would be possible. There's I think two different ways to
Speaker 2: do this that people have been thinking about in the retina.
Speaker 2: There's a technical optogenetics, where you use a gene therapy
Speaker 2: to deliver a little bit of DNA to the cells
Speaker 2: of the optic nerve to make them light sensitive. That
Speaker 2: then you could activate with a laser, or you could
Speaker 2: put an electrical stimulator under the retina and drive the
Speaker 2: remaining the cells that are still there electrically.
Speaker 1: And the mean for just one saying, the retina is
Speaker 1: the lawn of cells at the back of the eyeballer
Speaker 1: catching the photons that are coming in through the front.
Speaker 1: And so if you've got a problem where let's say
Speaker 1: those cells have died for whatever reason, lots of reasons,
Speaker 1: then what you're talking about is how do you how
Speaker 1: do you get those cells to catch the photons and
Speaker 1: send their signals back along the optic nerve.
Speaker 2: Yeah, so I think you know to take a step back.
Speaker 2: If you're thinking about getting vision into the brain, there's
Speaker 2: a couple of different places you could think to do it.
Speaker 2: The first is the retina. So the back of the
Speaker 2: eye is the retina, which is this really nice two
Speaker 2: D sheet of neurons and a big cable going into
Speaker 2: the brain. So in some ways this is like a
Speaker 2: really ideal interface to the brain. Evolution has done this
Speaker 2: to give us vision. The first stop of the optic
Speaker 2: nerve out of the eye is a structure in the
Speaker 2: thalamus called the lateral janiculate nucleus, which is a very
Speaker 2: deep structure in the brain. It's very old evolutionarily, and
Speaker 2: there's about one point five million cells in the optic nerve.
Speaker 2: There's about about the same number of cells in the thalamus.
Speaker 2: And then from there you go out to a much
Speaker 2: larger number of neurons in cortex called primary visual cortex.
Speaker 2: And so if you want to supply vision to the brain,
Speaker 2: in some sense synthetically your choices are really in the retina,
Speaker 2: in the in the LGN, or in V one, and
Speaker 2: everywhere past the optic nerve gets much much harder. Nobody
Speaker 2: has ever really shown the restoration of form vision by
Speaker 2: directly stimulating either the LGN or V one. I mean,
Speaker 2: people haven't even really shown the restoration of form vision
Speaker 2: simulating the optic nerve. The device that we're bringing to
Speaker 2: market now that just recently finished to face three clinical
Speaker 2: trial sits under the retina and stimulates a layer of
Speaker 2: cells called the retinal bipolar cells, which are the first
Speaker 2: cells past the rods and cones. And so this is
Speaker 2: really in many ways the first opportunity to get a
Speaker 2: visual signal back into the signaling pathways into the brain.
Speaker 1: So let's back up. So how does your device work.
Speaker 2: So the device is called Prima. It's a pretty cool idea.
Speaker 2: So it's a tiny little solar panel chip about two
Speaker 2: millimeters by two millimeters, so it's really very small, and
Speaker 2: there's if you look. If you look at it, you'll
Speaker 2: see all these little hex grids on it, these little
Speaker 2: hex tiles. Each one of those TXT tiles is a
Speaker 2: photodiode and an electrode. So what we do is you
Speaker 2: implant this under the retina in the back of the
Speaker 2: eye where the rods and concept degenerated, and the patient
Speaker 2: wears glasses that have a laser projector on them, and
Speaker 2: the laser projector projects the scene with laser energy onto
Speaker 2: the implant in the back of the eye, and wherever
Speaker 2: the laser energy is absorbed, it stimulates, and wherever there's
Speaker 2: darkness in the scene that it doesn't. And so this
Speaker 2: is a cool idea because there's no implanted battery, there's
Speaker 2: no wires, there's no PCBs, there's no electronics other than
Speaker 2: this tiny little chip. Because you send it both energy
Speaker 2: and information simultaneously in the laser pulse and so this
Speaker 2: is like, it's tough to imagine how you would do
Speaker 2: this more simply than this. And when you look at
Speaker 2: past devices, so like a little over a decade ago,
Speaker 2: there was a company called Second Site that had a
Speaker 2: retinal stimulator that is probably what people would be most
Speaker 2: famous when people think about retinal prustcs. So it worked
Speaker 2: very differently than than the science prima implant. First of all,
Speaker 2: it targeted a different layer of cells. It targeted the
Speaker 2: optic nerve rather than the bip our cells, which are
Speaker 2: just much harder to stimulate naturalistically in this way. And
Speaker 2: the second is because it wasn't it was a conventional
Speaker 2: electrical implant. You had this big titanium box attached to
Speaker 2: the side of the eye. You had cables going in
Speaker 2: through through the eyeball to power it. This was a
Speaker 2: four and a half hour surgery. Being able to just
Speaker 2: put this little two by two millimeter chip of silicon
Speaker 2: fully wirelessly under the eye with a little inserted tool
Speaker 2: is a totally different game and it's and the clinical
Speaker 2: trial results I think really speak for themselves. The first
Speaker 2: time ever in the history of the world, as far
Speaker 2: as we know, that blind patients have been able to
Speaker 2: read again.
Speaker 1: Oh that's so amazing. So all of the electronics and
Speaker 1: all that stuff is in the glasses themselves, which are
Speaker 1: capturing the scene like a camera and zapping it back
Speaker 1: with a laser to the chip.
Speaker 2: Yeah yeah, powering it, Yeah, basically like a solar cell.
Speaker 1: Congratulations on all your progress with that. It's an incredible device.
Speaker 3: Yeah.
Speaker 2: And also I should say we didn't develop this from
Speaker 2: a scratch ourselves. We acquired this from another company called Pixium,
Speaker 2: which was based in Paris and had done has started
Speaker 2: the clinical trial. Originally the technology came from a I
Speaker 2: love at Stanford scientist Daniel Planker in the Electrical Engineering
Speaker 2: department who came up with the idea, did the early
Speaker 2: work at Stanford that was licensed by Pixium. They started
Speaker 2: the clinical trial which we acquired and have finished and
Speaker 2: finished the clinical trial and to bring in to market.
Speaker 1: Right, I mean, I'm so I'm so jazzed that you
Speaker 1: guys are doing that or bringing it to market and
Speaker 1: making making this across the finish line. So that's what
Speaker 1: you're doing in the retina for people who have lost vision.
Speaker 1: Tell me what you're doing with uh reading from neurons?
Speaker 1: So before just before we get there. So the challenge
Speaker 1: with brain computer interfaces has always been, well several One
Speaker 1: of them is that you know, mother nature has wrapped
Speaker 1: the brain in this armored bunker plating, so it's hard
Speaker 1: to get to. But then when you get in there,
Speaker 1: you've got eighty six billion neurons and you have to
Speaker 1: figure out who's saying what. And the traditional way to
Speaker 1: do this is to dunk an electrode in there, which
Speaker 1: really damages the tissue. So obviously people have been trying
Speaker 1: to make electrodes thinner and thinner. But you've got an
Speaker 1: idea that you're working on which is amazing. Tell us
Speaker 1: about that.
Speaker 2: Yeah, so that I can like, there's no free space
Speaker 2: in the brain. The brain is wet, it squished together.
Speaker 2: Evolution has really compressed as much as much as it
Speaker 2: can into as small a space and an energy budget
Speaker 2: as it possibly can, and so there's there has not
Speaker 2: really left holes that we can take advantage of in there.
Speaker 2: Evolution is extremely good at its job, and there's limits
Speaker 2: how small you can make an electrode. You can't make
Speaker 2: a like one nanometer wire because as a wire, just
Speaker 2: any electrical wire gets smaller, the resistance increases there's just
Speaker 2: real limits how small you can make a recording electrode
Speaker 2: before you lose the ability to distinguish the signal that
Speaker 2: you care the biological activity from the background noise. And
Speaker 2: then on the stimulation side, this is actually worse because
Speaker 2: there's real limits how small you can make a stimulating
Speaker 2: electrode before you start splitting water in the brain and
Speaker 2: producing hydrogen and oxygen, and like, you really don't want
Speaker 2: to be doing this, And so we think about, like,
Speaker 2: what does an ideal neural interface look like. I think
Speaker 2: one of the high level intuitions that I started with was, Yeah,
Speaker 2: the brain is encased in this dark vault of a skull,
Speaker 2: but it has to communicate with the world.
Speaker 3: There's like you, the.
Speaker 2: Brain is not telepathically connected to the outside world. I mean,
Speaker 2: it's also important to realize that you're not seeing the
Speaker 2: world out there, right, You're only ever seeing in perceiving
Speaker 2: information that's arrived at the brain.
Speaker 3: And so how does it get there.
Speaker 2: All of the information that flows in or out of
Speaker 2: the brain flows through a relatively small number of cables.
Speaker 2: There's twelve cranial nerves and thirty one spinal nerves. The
Speaker 2: optic nerve is cranial nerve two. The vestibular cochlear nerve
Speaker 2: that carries hearing in balance is also called nerve eight.
Speaker 2: And kind of thinking about you've got this relatively small
Speaker 2: number of wires, we can think about attaching to those
Speaker 2: like we do for getting vision into the brain through
Speaker 2: the remnants of nerve too. But this also kind of
Speaker 2: got in the back of my mind going this idea
Speaker 2: of can we grow a thirteenth cranial nerve that really
Speaker 2: feels like the ideal neural interface. Biology has given us
Speaker 2: other examples of fiber bundles that get information in and
Speaker 2: out of the brain for really any purpose that the
Speaker 2: brain needs. It, is it possible to add a thirteenth
Speaker 2: biological wire that, instead of having an eye at the
Speaker 2: other end or having a bunch of muscles at the
Speaker 2: other end, had a USBC port basically, And so the
Speaker 2: high level intuition here is like, what can we add
Speaker 2: to the brain? How does the brain do this? Like
Speaker 2: how does nature do this on its own? And the
Speaker 2: answers it uses neurons, And so this kind of prompts
Speaker 2: a question what happens if we add more neurons to
Speaker 2: the brain and the answers, they grow in and wire
Speaker 2: up and give you these bidirectional chemical synapses. And so
Speaker 2: this has led to an approach that we call biohybrid
Speaker 2: like biohybrid neural interfaces, and it really feels like it
Speaker 2: has the scalability that many conventional methods don't. Now there
Speaker 2: are alternatives to electrodes, So tell us what a biohybrid
Speaker 2: interface is. So a biohybrid neural interface is when we
Speaker 2: take heavily engineered stem cell derived neurons in a dish,
Speaker 2: we load those into the electronic device, and then what
Speaker 2: you place into the brain is just the ingrafted cells.
Speaker 2: So we're not placing any metal or any like, no
Speaker 2: electronic or mechanical component goes into the brain.
Speaker 1: Instead, you're growing.
Speaker 2: We basically graft these these cells onto the brain through
Speaker 2: an appropriate starting point, and then those grow out form
Speaker 2: new connections just as kind of more more of the brain.
Speaker 1: And this is because mother nature is really good at
Speaker 1: growing cells into groups of other cells and so on.
Speaker 1: So you're taking advantage of that.
Speaker 2: Yeah, we're letting biology do as much as the heavy
Speaker 2: lifting as we can. Now, this creates other problems, but
Speaker 2: the and I think smart people can say, well, now
Speaker 2: you have a really complicated selling engineering problem to solve.
Speaker 2: But if you can solve that in the meaningful way
Speaker 2: that you have to, yeah, you can get biologies do
Speaker 2: a lot of work for you.
Speaker 1: Yeah. So these cells that you're putting on there and
Speaker 1: growing in you have heavily engineered these cells. So tell
Speaker 1: us about that. Yeah.
Speaker 2: So there's a couple of things you need to do.
Speaker 2: The first is it needs to be matched to the
Speaker 2: immune system. Now, if you don't do this, it's you
Speaker 2: can still make a cell therapy for a patient, but
Speaker 2: you need to do it on an individualized patient basis
Speaker 2: per patient. This is very expensive. It can take a
Speaker 2: very long time to make edit the other edits that
Speaker 2: we need. And so the first set of editing that
Speaker 2: we do is to make the neurons hypommunogenic, meaning that
Speaker 2: they don't bother the immune system when you put them
Speaker 2: in a patient.
Speaker 1: So how do you do that?
Speaker 2: This is a much longer topic. There's these things called
Speaker 2: major histoic compatibility complexes, and we need to suppress some
Speaker 2: protein expression and force some other protein expression to basically
Speaker 2: tell the immune system not to eat you and and
Speaker 2: also that you are fine.
Speaker 1: And how far along are you on that pathway? Is
Speaker 1: that solved?
Speaker 2: I mean, I wouldn't say that that's a solved problem.
Speaker 2: I would say as a as a fields, there's several
Speaker 2: standalone companies that their ip is hypo immune agenic stem cells,
Speaker 2: and so we are i'd say, pretty close to the
Speaker 2: state of the art in the field, but it's not perfect.
Speaker 3: Now.
Speaker 2: In the brain, the immune system tends to leave you
Speaker 2: alone more than many other areas like this is, for example,
Speaker 2: a lot of the work that's been done in gene
Speaker 2: therapy so far has been done in the eye because
Speaker 2: the immune system tends not to overreact in the eye
Speaker 2: because when it does in a patient and a subject
Speaker 2: goes blind, this historically is a bad thing. And so
Speaker 2: there's some areas where you tend to get more autoimmune
Speaker 2: reactions in some are Some are anatomy where this happens less.
Speaker 2: The brain is one of the areas where because around
Speaker 2: the time of the surgery you're treating them with systemic
Speaker 2: immunosuppressants anyway, and then once the bloodburned bearer has healed,
Speaker 2: it being approximately hypominogenic is probably fine.
Speaker 1: Okay, So you do that to these cells, you engineer
Speaker 1: them that way, and then you stick them on so
Speaker 1: that they grow in. But of course you're keeping the
Speaker 1: cell bodies outside and then what are you doing with those?
Speaker 2: Yeah, So the next edit that we make is we
Speaker 2: add a protein called a light gated ion channel also
Speaker 2: as an option to these cells, which allows us to
Speaker 2: fire them using light.
Speaker 3: And this is pretty important.
Speaker 2: So when we have so the device that the cell
Speaker 2: is embedded in has two components around each cell. It
Speaker 2: has a recording electrode which allows us to detect the
Speaker 2: date of the cell, and it has a tiny little
Speaker 2: micro LED kind of like you'd have in like your
Speaker 2: phone screen next to the cell. And so when we
Speaker 2: want to fire a neuron, we turn on the LED
Speaker 2: and that depolarizes the cell and sends a pulse into
Speaker 2: the brain. And when that neuron receives input from the brain,
Speaker 2: because it's grown out both inputs and outputs, we can
Speaker 2: detect that with the electrode, and so being able to
Speaker 2: optically stimulate using light and electrically record use it in
Speaker 2: an electrode. A capacity of electrode allows us to minimize
Speaker 2: crosstalk between these so that we can do them both simultaneously.
Speaker 1: And they're sandwiched in between this. So the cell body
Speaker 1: is sandwiched in between the little light and the little
Speaker 1: recording electrode. And so you can say, for this guy,
Speaker 1: I want to turn him on now, and I want
Speaker 1: to record what he's doing through time.
Speaker 2: Yeah, it's not quite exactly one to one, but it's
Speaker 2: pretty close.
Speaker 1: Great, And how many neurons can you grow in there
Speaker 1: at once?
Speaker 2: Well, I mean this is so there's the number of
Speaker 2: electrodes in the device, or number of channels in the device,
Speaker 2: and then there's the number of cells, and then there's
Speaker 2: the number of synapses that you get the brain. And
Speaker 2: these are slightly different things. So the chips that we're
Speaker 2: working with right now have four thousand electrodes per FIN,
Speaker 2: and so we're thin is one of these one of
Speaker 2: these little sandwiches. Yeah, and so it's actually it's really
Speaker 2: eight thousand per because it's four thousand microelids and four
Speaker 2: thousand electrodes. But we call this a four thousand channel
Speaker 2: fin and we're working on stacks of these to scale
Speaker 2: this up to hundreds of thousands of channels in one
Speaker 2: in a couple millimeters by a couple millimeters. But I mean,
Speaker 2: you could load this with a half a milli liter
Speaker 2: of cells, which easily millions of cells, and those can
Speaker 2: form many billions of synapses through the brain.
Speaker 1: Do each of these cells form about let's say, ten
Speaker 1: thousand synapses or.
Speaker 2: I mean it's tough to count them. I mean you
Speaker 2: can get there's the order of magnitude. People think it's
Speaker 2: like maybe about a thousand synapses per cell, but I
Speaker 2: mean we can't. These are tough to actually count.
Speaker 1: Right, If you had a million neurons in there, you'd
Speaker 1: get a billion synapses in the brain.
Speaker 3: Yeah, back of the envelope.
Speaker 1: Back of the envelope. And then so what you'd be
Speaker 1: able to do is stimulate exactly as you want to, Okay,
Speaker 1: fire number three hundred and seventy nine, now, fire number
Speaker 1: one hundred and fifteen, and son, and then record the
Speaker 1: activity going on there so you can read and write.
Speaker 3: Yeah, so you can read and write. And it's a
Speaker 3: fairly complex.
Speaker 2: So you've got this transform between the activate the activities
Speaker 2: and the cells and your device and what's going on
Speaker 2: in the brain. We don't think of it in terms
Speaker 2: of the single unit activity. In the beginning of the field,
Speaker 2: we were really thinking in terms of single neurons, and
Speaker 2: in the very beginning, the first experiments that were done
Speaker 2: in animals didn't have a model of brain activity really
Speaker 2: at all. What they did is they place electrodes in
Speaker 2: the brain and then say, when this neuron fires, the
Speaker 2: cursor should go up, and when this neuron fires, the
Speaker 2: cursor should go down, and you just can learn to
Speaker 2: separate these things. So the brain is very plastic under feedback.
Speaker 2: Now that works for a very small number of channels,
Speaker 2: and of course the subject isn't learning to modulate those
Speaker 2: neurons specifically. They're actually modulating big groups of neurons around
Speaker 2: where the electrode is, and so as you go to
Speaker 2: higher level control, that doesn't really work anymore. But the
Speaker 2: brain has these abstract informational representations of things like intended
Speaker 2: motor activity or face recognition or other things that objects
Speaker 2: that it thinks about, and so we're still at the
Speaker 2: early stages of learning to use these devices. Really different
Speaker 2: type of BCI, But how we think what we think
Speaker 2: we're seeing is these cells would really join these cortical
Speaker 2: representations and then just become part of part of the brain,
Speaker 2: and you can do neuroscience on them like you would
Speaker 2: any other part of the brain, except that the soel
Speaker 2: body is right there in your device and really easy
Speaker 2: to observe.
Speaker 1: What are the biggest challenges that you're facing in terms
Speaker 1: of bridging these digital systems and these biological systems.
Speaker 2: There's many of the hard problems here are not the
Speaker 2: really obvious sexy ones. In fact, actually I realized the
Speaker 2: other other week that the very first piece of writing
Speaker 2: that I put on the Internet was kind of this
Speaker 2: like sophomore literally as a software I call it, but
Speaker 2: the software grant about how like back in circa two
Speaker 2: thousand and eight, everyone felt like the hard problems here
Speaker 2: were understanding the neural code and like real science to
Speaker 2: study these like deep neuroscience questions, and it was kind
Speaker 2: of for the technicians to figure out how to get
Speaker 2: the electrodes in the brain, whereas actually the problem is
Speaker 2: how do you get these electrodes in the brain. And
Speaker 2: certainly the neuroscience has advanced a lot, and the neuroscience
Speaker 2: is very cool, but a lot of the problems here
Speaker 2: are things like packaging, which is a fancy term for
Speaker 2: when you place an electronic device in the body, it's
Speaker 2: going to be it's going to be attacked, it's going
Speaker 2: to be degraded, it gets encapsulated in scar tissue that
Speaker 2: neurons are pulled away from you. There's these very harsh
Speaker 2: chemical environments that try to attack and destroy your device.
Speaker 2: It's important to realize that there are no truly passive
Speaker 2: surfaces anywhere in the body, like even bone is constantly
Speaker 2: getting remodeled and turned over and regenerated, and so when
Speaker 2: you place one of these non regenerating device in the body,
Speaker 2: it's going to be attacked. And so now we have
Speaker 2: we have much better materials than we did ten years ago,
Speaker 2: specifically things like silicon carbide, which is really annoying material
Speaker 2: to work with, but a very good encapsulant that does
Speaker 2: not degrade in the body in the same way as
Speaker 2: these older polymer king capsulans do. It's like, if you
Speaker 2: look at the history of Prima part of like how
Speaker 2: did PIXI them, the company we.
Speaker 3: Bought this get here?
Speaker 2: They actually had an approved device in the I want
Speaker 2: to say twenty fourteen twenty fifteen called Iris, which was
Speaker 2: a different retinal prosthesis and it worked very differently. It
Speaker 2: had a conventional electronics package, It required a battery, but
Speaker 2: it was it was got on market and then was
Speaker 2: withdrawn and it was withdrawn because of packaging failures. Basically,
Speaker 2: the device didn't have an acceptable lifespan in human patients
Speaker 2: once on the market, and that was like they were
Speaker 2: using materials that were available at the time, which was
Speaker 2: before we figured out, as I feel, how to work
Speaker 2: with things like silicon carbide. And that is an example
Speaker 2: of a problem that enabled Prima to work. So Prima
Speaker 2: is a full carbid encapsulation and it should last I
Speaker 2: mean there's now dat out to six years and some
Speaker 2: patients and it should outlast these patients.
Speaker 3: It should last decades.
Speaker 1: Amazing.
Speaker 2: And so that's an example of like a big area
Speaker 2: of progress in the last few years that people wouldn't
Speaker 2: really think of.
Speaker 1: And so, what are some surprising findings or unexpected obstacles
Speaker 1: that you've run into while doing let's say the biohybrid electrodes.
Speaker 2: I mean, biology is just it's when it works, it
Speaker 2: can do a lot of things that we humanity is
Speaker 2: just not at that level of capability yet. But also
Speaker 2: in neural engineering or either whether that means systems neuroscience
Speaker 2: or BCI, you'll start in mice and then maybe you'll
Speaker 2: work in an intermediate species like pigs and then eventually
Speaker 2: end up in monkeys, then end up in humans. And
Speaker 2: when you have an electrode or even something like optogenetics
Speaker 2: that works basically the same in mice as a dozen
Speaker 2: monkeys as it does in humans. When you're engrafting neurons
Speaker 2: into the brain, I mean, there's a big difference between
Speaker 2: mouse neurons and human neurons and macac neurons are different
Speaker 2: thing entirely, and so you end up having to redo
Speaker 2: a bunch of this work in each species that you
Speaker 2: work in, and so there's every time we switch species,
Speaker 2: there's a lot to relearn. And fifteen years ago now
Speaker 2: probably something like that, there is a major discovery of
Speaker 2: the ability to turn any cell into a stem cell. Again,
Speaker 2: this was a discovery called induced plury potency, won the
Speaker 2: Nobel Prize a while ago, and that works really well
Speaker 2: in rodents, it works really well in human cells. Turning
Speaker 2: a macaque skin cell into an ips is like there's
Speaker 2: just a bunch of little tricks that don't work as well.
Speaker 2: And so the biology is pretty deep in all of
Speaker 2: these areas.
Speaker 1: It's surprising that those are different, but you know, just
Speaker 1: given the evolutionary shared history.
Speaker 2: But yes, yeah, I mean there's a lot that's conserved,
Speaker 2: but there's also a lot of little things that are
Speaker 2: slightly different.
Speaker 1: Yeah, quite right. So big congratulations on where Prima is
Speaker 1: right now. That's so exciting. On the biohybrid electrodes, it
Speaker 1: said you have growing neurons into the brain and then
Speaker 1: being able to read and write that way. When do
Speaker 1: you think that's going to be ready in humans? What's
Speaker 1: your prediction.
Speaker 2: I think that the first human ingraftment will happen around
Speaker 2: twenty thirty, okay, so I think like probably five years, okay.
Speaker 1: And what is the first thing you're going to tackle
Speaker 1: once it gets into humans?
Speaker 2: Well, I mean it should be it's a communication device,
Speaker 2: and so motory coding, speech to coding, all of that
Speaker 2: should be possible. And so I think in the near
Speaker 2: term it's you're looking at the figure of merit for
Speaker 2: any brain computer interface for communication is a bandwidth measured
Speaker 2: in bits per second. The record for keyboard and mouse
Speaker 2: kind of low dimension motority coding is about seven bits
Speaker 2: per second, which is I think neuralinks current participants. There's
Speaker 2: a group at UC Davis led by saying Nick Card
Speaker 2: and Sergey Staviski, who recently showed speech to coding from
Speaker 2: pridal cortex that gets about twenty to twenty five e
Speaker 2: bits per second. Human language is routinely rated at forty
Speaker 2: bits per second, So you think that you can as
Speaker 2: them tote towards that, and so I think in the
Speaker 2: near term what we're looking for is a forty bit
Speaker 2: per second communication prosthesis. Longer term, this is where neural
Speaker 2: engineering and BCI diverge a little bit, and there's a
Speaker 2: lot of interest internally at looking at how is this
Speaker 2: applicable in stroke or other areas where you've lost cells
Speaker 2: where conventional BCI techniques really won't work in the same way,
Speaker 2: and potentially even organic nerd degenerative diseases, But those are
Speaker 2: very hard and I don't want over promise on the
Speaker 2: timeline there.
Speaker 1: Now, if we were just going to blue sky here,
Speaker 1: part of the mythology about BCIs is that at some
Speaker 1: point everyone will have one of these for summer, you know,
Speaker 1: for communicating faster with their cell phone or their computer
Speaker 1: or whatever. To what degree do you think that's hype
Speaker 1: versus let's imagine one hundred years from now, where do
Speaker 1: you realistically see think it's going to be in terms
Speaker 1: of the amount of market it has.
Speaker 2: Yeah, I mean one hundred years from now. I have
Speaker 2: this event horizon somewhere between twenty thirty and twenty thirty
Speaker 2: five now that I just can't see beyond, and kind
Speaker 2: of for my entire life, I always kind kind of
Speaker 2: like see the future, and we are clearly in the
Speaker 2: takeoff era now, and this is not I don't think
Speaker 2: I'm saying anything that contrarian, at least in Silicon Valley,
Speaker 2: but one hundred years from now is almost impossible for
Speaker 2: me to imagine.
Speaker 3: Now.
Speaker 2: With that said, I don't think that healthy forty year
Speaker 2: olds are going to be getting holes drilled in their
Speaker 2: skull anytime soon. My view is that it'll be a
Speaker 2: long time before these things are really augmentative, much less
Speaker 2: elective procedures. But everybody eventually becomes a patient. There's some
Speaker 2: point as you get older. For example, the main indication
Speaker 2: of prima is age related macular degeneration, which is very
Speaker 2: common and if someone lives into their late seventies or eighties,
Speaker 2: is actually pretty prevalent, and so for many many of
Speaker 2: these things. Eventually there will come a time when it
Speaker 2: makes sense. I mean we consider retinal prostisis and cochlear
Speaker 2: prosteces also BCIs when I look at, say twenty years
Speaker 2: from now, the things that I that are very much research.
Speaker 2: This is not a thing that's happening in the next
Speaker 2: five years. But if you can get a neural interface
Speaker 2: with the bandwidth of that say like the two hemispheres
Speaker 2: are connected, which is about one hundred million fibers on
Speaker 2: both sides that project across the midline to connect the
Speaker 2: two hemispheres of your brain into a single thing. If
Speaker 2: you can get something of that bandwidth, which is probably
Speaker 2: only tens of megabits, then this takes you into really
Speaker 2: interesting territory about really being able to redraw the borders
Speaker 2: around brains and gets at this thing called the binding problem.
Speaker 3: And that feels less than twenty years away for me.
Speaker 2: This feels not like the next five years, but not
Speaker 2: not to the distant future like within people's lifespans today.
Speaker 1: So let's stile click on that tell us about the
Speaker 1: binding problem and how you think this addresses that.
Speaker 2: But I mean, I don't have a solution for the
Speaker 2: binding problem. Is if the brain is made up of
Speaker 2: a lot of different neurons and a lot of different
Speaker 2: areas kind of connected together. Why do we Where does
Speaker 2: this unified perception come from? You? You see the world,
Speaker 2: you can think about it, you hear things. All of
Speaker 2: this is fit together into a coherent hole for you.
Speaker 1: When the bluebird flies past you, the blue doesn't come
Speaker 1: off of the bird, and the chirping doesn't seem like
Speaker 1: it's coming from somewhere else. It seems like a unified object. Yeah, exactly,
Speaker 1: even though even though blue is processed apparently in one
Speaker 1: part of your brain and the motion another part, and
Speaker 1: the chirping in a different part. Yeah, okay.
Speaker 2: And so in some there's some sense in which almost
Speaker 2: all communication is about creating correlations between brains. There's we're
Speaker 2: having a conversation right now. There's concept spaces in my
Speaker 2: brain that are being active that I developed from education,
Speaker 2: like learning English learning, math learning, science, doing these things,
Speaker 2: and I can serialize these neural activations to vibrations over
Speaker 2: the air, send over to you, receive through your ears
Speaker 2: that then activate these correlations in your brain that allow
Speaker 2: us to share these concepts. But we don't. Our brains
Speaker 2: don't become one thing. And so there's there's some point
Speaker 2: between the types of correlations that you get between the
Speaker 2: hemispheres of a brain and the types of correlations that
Speaker 2: we get between brains that are in dialogue. And where
Speaker 2: does this Where is that crossing point? We don't know today,
Speaker 2: but I think that biohybrid devices have the potential to
Speaker 2: get close to there, and that takes us to really
Speaker 2: different regimes than kind of conventional VCI technology.
Speaker 1: Let me just make sure I understand what you said.
Speaker 1: So the idea is, if you're reading and writing from
Speaker 1: my brain and from your brain, we can get closer
Speaker 1: to being a single brain.
Speaker 2: Well, like, yeah, the question is like, where does that happen?
Speaker 2: What makes I mean? People back in This has done
Speaker 2: less commonly now, but it was never really done that commonly.
Speaker 2: But people used to cut the connection between the two
Speaker 2: hemispheres of the brain to treat epilepsy. You could prevent
Speaker 2: a seizure from spreading from one to the other. And
Speaker 2: those split brain patients were really interesting to study.
Speaker 3: Because you could.
Speaker 2: You could ask kind of the right hand a question
Speaker 2: which would go to the left hemisphere, and then you
Speaker 2: could ask the other hand, which was coming from the
Speaker 2: other hemisphere, to kind of answer, and you get the
Speaker 2: sense that there's two agents going on.
Speaker 3: In one head.
Speaker 1: Yeah, one in each hemisphere.
Speaker 2: And so if you take that then the opposite direction,
Speaker 2: what do you get? I think is really interesting.
Speaker 1: You're saying, put four hemispheres together and yeah you get Yeah,
Speaker 1: Now who would do this? Who would volunteer for example,
Speaker 1: two spouses for example?
Speaker 3: Yeah, exactly.
Speaker 2: So I think this is in the beginning this this
Speaker 2: is going to be something like you've got like a
Speaker 2: long married couple one has a terminal disease. Can you
Speaker 2: make the loss of that brain like having a stroke
Speaker 2: you recover from, rather than the that rather than lights out?
Speaker 1: Oh wow, and we double click on that story. What
Speaker 1: would the narrative be there?
Speaker 2: Well, I mean you get so the if you have
Speaker 2: if you can build these super organisms and get kind
Speaker 2: of equilibration of representation over some extended period of time.
Speaker 2: I mean, people already store memories in their spouse's brains
Speaker 2: that then they can access and recall later. Right, this
Speaker 2: is about creating correlations between brains, and so there's some
Speaker 2: they suspect that there's some nonlinearity in there where you
Speaker 2: get something really different, but of course we don't know
Speaker 2: exactly where that is yet. I mean, this is a
Speaker 2: tricky field because there's a fine line between doing very
Speaker 2: like we're right now in the process of preparing twelve
Speaker 2: hundred pages of regulatory documentation that is like very nuanced
Speaker 2: in exactly how you do these tests to verify these
Speaker 2: like things that have passed clinical trials that are in
Speaker 2: almost fifty patients in six countries, and then you kind
Speaker 2: of play some of these technologies out not even that
Speaker 2: long five ten years, and you sound like a lunatic.
Speaker 2: But that's part of why this is such an exciting field.
Speaker 1: I think, right, what would you see so I know,
Speaker 1: I know the event horizon for both of us is,
Speaker 1: you know, not more much more than a decade out.
Speaker 1: But what would you see is the societal benefits that
Speaker 1: could happen from this, you know, at whatever time scale,
Speaker 1: for example, connecting brains or something. Have you thought about
Speaker 1: what that could what that would turn into not just responuses,
Speaker 1: but for society.
Speaker 2: I mean at the end of that is this idea
Speaker 2: of substrate independence, which is the thing like when I,
Speaker 2: like I see a person, there's two parts of this.
Speaker 2: There's the there's the robot, and there's an agent. And
Speaker 2: I'm going to be pretty pretty disappointed if I get
Speaker 2: murdered by my pancreas, which is like basically a support
Speaker 2: structure for like keeping the agent going. And so there's
Speaker 2: I think this takes us to Okay, if we're serious
Speaker 2: about exploring the universe, I think we have to adapt
Speaker 2: ourselves the environment rather than bringing little pressurized bottles of
Speaker 2: Earth with us everywhere we go. Because our like once
Speaker 2: great grandparents grew up on a planet that happened to
Speaker 2: have those things, and so I think this is like
Speaker 2: very profound technology.
Speaker 1: So substrate independence, just for the audience, means getting off
Speaker 1: of this wet biological stuff and onto something more robust,
Speaker 1: like a silicon chip or something. In other words, getting
Speaker 1: your mind into something that can survive space travel.
Speaker 2: Which could be other biological brains, or it could be
Speaker 2: an engineered system. Brains are composed of ordinary matter assembled
Speaker 2: by the rules of chemistry.
Speaker 3: There's no magic in there.
Speaker 2: They're very complicated and we don't have obviously complete explanations
Speaker 2: for how they work. But they're ultimately physical systems, and
Speaker 2: so there's something that they're doing that's producing this experience
Speaker 2: that ultimately must be explainable.
Speaker 1: And so what you're doing with the electrodes, the biohybrid
Speaker 1: electrodes in the brain. How does this lead to substrate independence?
Speaker 2: Well, the idea is that if you can get like,
Speaker 2: if you can really, in some profound sense, lose track
Speaker 2: of where one brain ends in another begins, then where
Speaker 2: does this take you. I have no idea what that
Speaker 2: experience will feel like, but I'm pretty confident that that
Speaker 2: device is going to get made in the next decade.
Speaker 3: And this is research.
Speaker 2: This is not a there's nothing to sell here yet,
Speaker 2: but it's the type of frontier that is enabled by
Speaker 2: the types of devices that are getting made now and
Speaker 2: that and there's I think enough near term commercial revenue
Speaker 2: from things like the from the visual pres thesis to
Speaker 2: fund this.
Speaker 3: This stuff happening.
Speaker 1: So if you're able to read from the brain, then
Speaker 1: you can take that data and put it into a
Speaker 1: different substrate.
Speaker 2: Whether that requires so to do that, that requires new
Speaker 2: physics that we don't understand today. We'd have to really
Speaker 2: understand what is the brain doing that is producing this
Speaker 2: ordered experience that we have. But I strongly suspect that
Speaker 2: intelligence and consciousness are separate or independent. Is possible to
Speaker 2: have a pure experience in the absence of adaptive behavior
Speaker 2: and it's possible to have very apparent adaptive behavior and
Speaker 2: the absence of experience, So these things are separate now.
Speaker 2: In order to have true substrate independence, like you could
Speaker 2: build a silicon based system that is as good as
Speaker 2: our brains. This requires a physics and neuroscience breakthrough that
Speaker 2: will produce several Nobel prizes that we don't have yet.
Speaker 3: But I do think that that is not one hundred
Speaker 3: years away.
Speaker 2: I think that there's really compelling threads of research that
Speaker 2: are being pulled on that have the potential to produce
Speaker 2: those equations. But even if we don't get those equations,
Speaker 2: if you can build brain to brain connections, then you
Speaker 2: don't need them, because you know that brains are good
Speaker 2: enough and if you can assemble, if you can connect
Speaker 2: them together, then that is another approach with some drawbacks and.
Speaker 3: Some like big head starts.
Speaker 1: Do you think people would volunteer to connect their brain
Speaker 1: to someone else's I'm not sure. I'm not sure I
Speaker 1: would enjoy connect with everything.
Speaker 3: I don't know.
Speaker 2: I mean, I don't think that this is for everybody. Also,
Speaker 2: this is on a thing that exists today. I think
Speaker 2: that this is a really interesting thing on the horizon
Speaker 2: that is like enough to notice. So like, oh that, like,
Speaker 2: if that's possible, what does that mean? But I think
Speaker 2: it's tough to to I think really anticipate it too much.
Speaker 3: Right now, you.
Speaker 1: Onz wrote that one of the main goals in neuroscience
Speaker 1: is to understand the physics of consciousness so that we
Speaker 1: can engineer experience. So tell us what you mean by that.
Speaker 2: Yeah, So to be clear, I don't think that's like
Speaker 2: the only goal of neuroscience. I think there's lots people
Speaker 2: working in neuroscience that are thinking about other stuff and
Speaker 2: have never asked themselves those questions. But I think that,
Speaker 2: I mean, arguably one of the kind of end goals
Speaker 2: of technology is is recursion in the sense of we
Speaker 2: gain the gain the ability to observe and manipulate kind
Speaker 2: of our own existence, and we I think, like Earth
Speaker 2: is small and intensely contested, and space is large, and
Speaker 2: the speed of light is low, and there's like you
Speaker 2: never run out of real estate, and like in the matrix,
Speaker 2: and so getting to a point where we can we
Speaker 2: really have we have control over our like the nature
Speaker 2: of our experience feels like kind of a logical endpoint
Speaker 2: of a lot of what we've seen over the last
Speaker 2: like since the beginning of the technological revolution.
Speaker 1: So, how is what you're doing with the biohybrid electrodes.
Speaker 1: How will this get us closer to understanding something about
Speaker 1: the physics of consciousness? Oh?
Speaker 2: Well, I mean one thing, one thing that I think
Speaker 2: is true about about consciousness is that there's a good
Speaker 2: chance that to really know one will have to see
Speaker 2: it for yourself. I think that the problem, one of
Speaker 2: the problems that has made it so hard to study
Speaker 2: is not it's not that it's magic or that there's
Speaker 2: like some metaphysical thing that makes it inherently impossible, but
Speaker 2: that there's no measurements that we can take that will
Speaker 2: tell us things, because you can always if you believe
Speaker 2: that intelligence and adaptive behavior is separate from phenomenal experience,
Speaker 2: then if you run a behavioral experiment in an animal,
Speaker 2: you can always see some explanation for what's happening without
Speaker 2: resorting to saying anything about conciousness. And when we do
Speaker 2: experiments in animals, we don't talk about what they see
Speaker 2: or perceive. We say they can use the information or
Speaker 2: they can learn the information. And so when you think
Speaker 2: about what experiments can you really run that would allow
Speaker 2: you to know if you've learned something this This often
Speaker 2: looks like, can we add a new sensory mode? Can
Speaker 2: we It's also pretty tough to imagine a sense that
Speaker 2: you don't have, because again evolution is very good at
Speaker 2: its job and it's really fit filled this available time
Speaker 2: and space. But for example, it's sense that you don't have.
Speaker 2: Is a true vector sense, So the ability to see
Speaker 2: a field, like a three D field out in the environment,
Speaker 2: and we don't have this because you don't have the
Speaker 2: sense organs to do this.
Speaker 3: We don't make measurements out of a distance. We only get
Speaker 3: measurements that arrive to you.
Speaker 2: If we had some way to get this signal, say
Speaker 2: from remote sensors or other things, then you could get
Speaker 2: the information. So what would a true vector sense feel
Speaker 2: like to experience? And so at the point where we
Speaker 2: can implement that and make and then make that available
Speaker 2: to you, and then way that you see it, you're
Speaker 2: I guess this was this was a new information, and
Speaker 2: I'm experiencing it directly and I can use it intuitively,
Speaker 2: and there's no other way.
Speaker 3: I could have experienced this.
Speaker 2: I think that is like the type of proof of
Speaker 2: concept for knowing that you've gotten some of that model.
Speaker 2: And I think that this isn't I don't think that
Speaker 2: you can do this with conventional electrodes. I think that
Speaker 2: you need something like a biohybrid neural interface to get
Speaker 2: to that level. Why when you electrically stimulate vision into
Speaker 2: the brain. So let's say that you put an electrode
Speaker 2: in primary visual cortex. If you inject charge through this,
Speaker 2: you can absolutely get a flash of light somewhere in
Speaker 2: the visual field. And if you do this in an animal,
Speaker 2: you can get them to look to the way you
Speaker 2: put the flash of light, and so you can say, okay,
Speaker 2: I got some visual signal into the brain. The problem
Speaker 2: is that these flashes of light, these are known as phosphenes.
Speaker 2: And what a phosphine really is is when you stimulate
Speaker 2: lots of neurons simultaneously, you average them together. And so
Speaker 2: if you have a neuron that represents like red and
Speaker 2: some part of the visual field, next to something that
Speaker 2: represents like a spatial frequency, next to something that represents
Speaker 2: like emotion, like an orientation emotion, and you drive all
Speaker 2: of these simultaneously, you kind of average them. Basically nothing
Speaker 2: that the only information that's remaining is is i thing
Speaker 2: called writing a topic, which is where in the visual
Speaker 2: field was it? And if you do that, then you're limited.
Speaker 2: You throw away almost all of the information that you
Speaker 2: could have conveyed. And when you do this, also, like
Speaker 2: this very continuous stimulation tends to produce the most intense
Speaker 2: immune responses to electrodes that you get. And so these
Speaker 2: these writing electrodes tend to be very encapsulated. And so
Speaker 2: you want something that gives you access to hundreds of
Speaker 2: thousands or millions of neurons and the at single cell
Speaker 2: informational resolution in ways that will the brain will really
Speaker 2: adapt to informationally, and electrodes don't get that type of
Speaker 2: specific stimulation, certainly not at the hundreds and nobody's ever
Speaker 2: done something like one hundred thousand electrodes for stimulation. And
Speaker 2: there's the other technique, optogenetics, where you do this with
Speaker 2: an optic stimulator.
Speaker 3: This requires genetically modifying the host brain.
Speaker 2: You have to use a gene therapy to deliver this
Speaker 2: new protein to the cells of the brain. This is
Speaker 2: not a thing that is really done in humans and cortex,
Speaker 2: and there's reasons that that is that it's going to
Speaker 2: be really difficult, and so there isn't I don't as
Speaker 2: from where I said, I don't see another technology that
Speaker 2: is really capable of getting hundreds of thousands or millions
Speaker 2: of neurons at single cell resolution in a way that
Speaker 2: is long term stable, in a way that allows those
Speaker 2: neurons to learn the signal that you're trying to give them.
Speaker 1: What philosophical questions keep you up at night?
Speaker 2: So there's a question that whenever I go to like
Speaker 2: things where I see my friends, there's a question that
Speaker 2: splits the table evenly every time, which is is a
Speaker 2: destructively scanned upload you? So these expanded you with think
Speaker 2: side of things that my friends and I call the
Speaker 2: transporter problems. And in some sense they're very simple, which
Speaker 2: is like if you have if you take like a
Speaker 2: scan of a brain, but at the end the brain
Speaker 2: is no more, and then you can use this to
Speaker 2: build a perfectly biophysically accurate like atomic simulation of that person.
Speaker 2: Does this make you feel better about dying of cancer?
Speaker 2: And for me, the answer to that is no. And
Speaker 2: I think many people and faced actually with that situation,
Speaker 2: would conclude no.
Speaker 1: This is no as in you feel you will have
Speaker 1: died if you got destroyed, yet there was a replica
Speaker 1: of you that got booted up a second later.
Speaker 3: Yeah, exactly.
Speaker 2: This is like I'll be survived by my friends, which
Speaker 2: is great, but doesn't necessarily make me feel a lot
Speaker 2: better about my specific situation.
Speaker 1: Right. In other words, the replica that gets booted up
Speaker 1: a second later thinks, wow, I'm max. It was just
Speaker 1: over there and now I'm over here. But the question
Speaker 1: is do you get any benefit from that?
Speaker 3: Exactly?
Speaker 2: And so from its perspective, it's probably right. And I
Speaker 2: think that people respond to this while saying like, well,
Speaker 2: every night you lose consciousness, you wake up in the
Speaker 2: next morning, you've broken some continuity there, which I think
Speaker 2: is like also totally fair. That's like also not that's true,
Speaker 2: but still doesn't really make me feel better. And so
Speaker 2: the two camps here are my agency living on in
Speaker 2: the world, which can be done through some other, some model,
Speaker 2: some replication of me that makes me feel like my
Speaker 2: influence will persist, versus I will accept drift in the
Speaker 2: personality in the agency as long as I get continuity.
Speaker 2: And so that's like the brain to brain connection there
Speaker 2: is like you'll get significant personality drift because you're kind
Speaker 2: of averaging together to people to some degree, but you
Speaker 2: get continuity or is this living on an agency without continuity?
Speaker 3: Is that good?
Speaker 2: And what's interesting is people's brains seem to make a
Speaker 2: choice on this early in their life and they are
Speaker 2: unable to see the other one. They're very convinced that
Speaker 2: this is like one of these two things is nonsensical.
Speaker 2: And so my read on this is that this is
Speaker 2: a there's a choice of metaphysics that's being made here
Speaker 2: and from which you reason. So this is a kind
Speaker 2: of a choice that your brain has made that allows
Speaker 2: you to see something and then from there you start reason.
Speaker 2: And so you can't like really talk your way through this,
Speaker 2: But I think these are kind of the two tribes
Speaker 2: that like metaphysical tribes here, And my guess is that
Speaker 2: kind of people get converted to continuity when faced when
Speaker 2: it becomes like a real thing. But that's the that's
Speaker 2: a philosophical question for which I don't know there's a
Speaker 2: right answer that keeps debate going.
Speaker 1: And do you feel any differently about the problem if
Speaker 1: you were degraded into your atoms and then those atoms
Speaker 1: were beamed over somewhere and then reconstructed, But it's still you.
Speaker 1: You're degraded and you're rebuilt up. Does that make a
Speaker 1: difference for you?
Speaker 3: Yeah?
Speaker 2: I mean, so this is this is the second transporter problem.
Speaker 2: Is if you send the atoms, does this make it better?
Speaker 2: And I think really the thing that I don't know?
Speaker 2: I mean, I think so. There's a show that I
Speaker 2: love that recently came to Netflix, was really hard to
Speaker 2: watch for a while called Pantheon.
Speaker 3: Highly highly recommended.
Speaker 2: I think Pantheon is probably the best depiction of how
Speaker 2: I think the next like fifteen years might go that
Speaker 2: I've ever seen in fiction.
Speaker 3: It's adult animation.
Speaker 2: It's by that it's based on a series of short
Speaker 2: stories by Ken Lew who is probably best known as
Speaker 2: the English language translator for the Three Body Problem series.
Speaker 2: And that show is amazing but also terrible metaphysics. It's
Speaker 2: a destructive upload, it's like, but the characters also realize this.
Speaker 2: There's graffiti on a building at one point that says
Speaker 2: like Dina live forever, which I don't find that compelling
Speaker 2: of value proposition, but it's an interesting depiction of a
Speaker 2: world where you kind of get to the other side
Speaker 2: of that of that choice of metaphysics to the degree
Speaker 2: that people aren't worrying about it anymore, and from the
Speaker 2: backwards looking perspective it works out fine. And so that's
Speaker 2: certainly one potential view there. The other is that what
Speaker 2: if you really believe what matters is continuity, then what
Speaker 2: you have to do is you kind of have to
Speaker 2: get a seed brain on both sides of the transporter,
Speaker 2: briefly establish brain to brain link to get the continuity
Speaker 2: through it, and then that's enough. As long as there's
Speaker 2: a brief moment of continuity, then that kind of gets
Speaker 2: you through that philosophically.
Speaker 1: Oh interesting, So this is where you might do your
Speaker 1: four hemisphere trick.
Speaker 2: Exactly, Well, yeah, I mean typically mean and that in
Speaker 2: the case where it's really like an adom for adam reconstruction,
Speaker 2: and the representations are already shared, then you wouldn't need
Speaker 2: any time. If you did this with two people do
Speaker 2: for that to really make sense, there'd be some time
Speaker 2: to get representational like drift between them. It's funny because
Speaker 2: if we talk about these things are interesting and are
Speaker 2: genuinely becoming from the realm of science fiction where they
Speaker 2: some of them still are today, and to the realm
Speaker 2: of engineering, which not all of this is today, but
Speaker 2: also only clear Like we don't at work, we don't
Speaker 2: really spend a lot of time thinking about like the
Speaker 2: future of humanity. It is mostly, as I often say,
Speaker 2: debugging Linux drivers, yeah, and writing regulatory documentation.
Speaker 1: So what drives you in your work?
Speaker 2: I mean, look, if you really believe that these things
Speaker 2: are possible within our lifetimes, I just like AI is
Speaker 2: also very exciting. There are other exciting things happening.
Speaker 3: In the world.
Speaker 2: But when you really believe that these things could actually
Speaker 2: be possible, I think it is tough to think about
Speaker 2: a lot else.
Speaker 1: That was Max Odak, founder and CEO of Science Corporation.
Speaker 1: He's working on the challenge of how to read and
Speaker 1: write from the brain, and really there are only a
Speaker 1: handful of people who are doing that. With the smarts
Speaker 1: and entrepreneurial bravery of Max, he and his team are
Speaker 1: at the cutting edge of integrating with the brain, whether
Speaker 1: that's by turning pixels into lasers and stimulating a tiny
Speaker 1: implant in the back of the eye, or growing neurons
Speaker 1: into the brain that ingratiate themselves into the network in
Speaker 1: a way that you can spy on the activity there.
Speaker 1: You can check out more about his company in the
Speaker 1: show notes at Eagleman dot com, slash podcast, and Max's
Speaker 1: website is science dot xyz. So let's wrap up at
Speaker 1: its core, the idea of growing cells into the brain
Speaker 1: as a brain computer interface. This challenges the comment intuition
Speaker 1: of a division between biology and machinery, and more generally, however,
Speaker 1: we make interfaces to the brain, these open the possibility
Speaker 1: that we'll be able to someday not only interpret what
Speaker 1: it is to be a human, but also enhance that
Speaker 1: and that in the future, even things like our thoughts,
Speaker 1: which seem unassailably private and ineffable. Things like thoughts might
Speaker 1: soon traverse digital pathways the way any data flows through
Speaker 1: a network. What does it mean when a thought leaves
Speaker 1: the confines of the skull? The story of BCIs is
Speaker 1: just beginning, and it's not just a story about the technology.
Speaker 1: It's the story of a whole new channel of communication.
Speaker 1: It's about translating the language of neurons into the language
Speaker 1: of computers, or perhaps eventually into the brains of other people.
Speaker 1: It's about giving voice to the mute, it's about giving
Speaker 1: movement to the paralyzed, and it's about giving wings to
Speaker 1: our imagination. So The work by Max and others in
Speaker 1: the BCI space invites us to consider whether our brains
Speaker 1: have to always remain isolated entities, or whether they can
Speaker 1: interface with a broader universe. This work reminds us that
Speaker 1: the brain doesn't always have to be merely an imprisoned
Speaker 1: container for thought, but instead a living, dynamic interface with
Speaker 1: the world, one that's going to soon enough, maybe in
Speaker 1: our lifetimes, reach far beyond the biological limits to which
Speaker 1: we have become accustomed. Go to Eagleman dot com slash
Speaker 1: podcast for more information and to find further reading. Send
Speaker 1: me an email at podcasts at eagleman dot com with
Speaker 1: questions or discussion, and check out and subscribe to Inner
Speaker 1: Cosmos on YouTube for videos of each episode and to
Speaker 1: leave comma until next time. I'm David Eagleman, and this
Speaker 1: is Inner Cosmos.