WEBVTT - What will Computer Implants do for our Brains?

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<v Speaker 1>Guess what, Mango? What's up? Will do you remember back

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<v Speaker 1>in the episode where we asked will we ever live

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<v Speaker 1>without sleep? We talked about how sleep appears to be

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<v Speaker 1>this really critical component of our brain's memory consolidation. Right, yeah, definitely. Well,

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<v Speaker 1>I started thinking about some of those rat brain monitoring

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<v Speaker 1>studies again because I was reading about these two neuroscientists

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<v Speaker 1>at Wake Forest Baptist Medical Center in North Carolina. Their

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<v Speaker 1>names are Sam Deadweiler and Robert Hampson, and they've been

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<v Speaker 1>studying rat brains for a few decades now. But one

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<v Speaker 1>of their studies on what's going on in these tiny

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<v Speaker 1>rat naggins suggests some fascinating implications for the future of

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<v Speaker 1>adding technology to the human brain. How's that? Well, all right,

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<v Speaker 1>so let me set this up here. So, in a study,

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<v Speaker 1>they got two sets of rats that are trained to

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<v Speaker 1>run between two areas of their cage and on one

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<v Speaker 1>side of the cage, they learned to press these levers

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<v Speaker 1>at a certain sequence and that helps them get a reward. However,

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<v Speaker 1>over time, one set of these is trained to wait

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<v Speaker 1>for up to thirty seconds before they could press the

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<v Speaker 1>appropriate lever to get their reward. Now, the second set

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<v Speaker 1>didn't have a wait. But when the second set was

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<v Speaker 1>forced to experience a delay of their own, they were

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<v Speaker 1>completely thrown off and they forgot which lever they needed

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<v Speaker 1>to push. So here's where the crazy part comes in.

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<v Speaker 1>The brain activity in the first set of rats. You know,

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<v Speaker 1>these are the ones that had to learn to wait.

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<v Speaker 1>They had been recorded, you know, once they'd learned the

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<v Speaker 1>lever to push, and then using electrodes dead Wilder and

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<v Speaker 1>Hampson stimulated this same series of brain activity for the

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<v Speaker 1>second set of rats, and this time they began behaving

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<v Speaker 1>as though they had been trained like the first set

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<v Speaker 1>of rats, and began choosing the right lever despite the

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<v Speaker 1>fact that they had not actually been trained to do this.

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<v Speaker 1>That's insane. Yeah, It's as though they had memories and

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<v Speaker 1>planet of things they had not actually experienced. And this

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<v Speaker 1>got me thinking, you know, as this evolves, what will

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<v Speaker 1>it mean for humans? And how are scientists currently using

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<v Speaker 1>machines in the human brain? And what are our brains

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<v Speaker 1>capable of when computers are built in These are just

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<v Speaker 1>a few of the questions will be asking him today's episode.

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<v Speaker 1>So let's get started, hey, their podcast listeners, welcome to

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<v Speaker 1>Part Time Genius I'm Will Pearson and as always I'm

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<v Speaker 1>joined by my good friend Man Guesh Ticketer and on

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<v Speaker 1>the other side of the soundproof glass, eating but apparently

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<v Speaker 1>not sharing a big old bag of Smarties as our

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<v Speaker 1>friend and producer Tristan McNeil. And that seems fitting because

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<v Speaker 1>in today's episode we're going to be talking about the

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<v Speaker 1>incredible advances and understanding the human brain, as well as

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<v Speaker 1>hacking the brain with technology so that we can treat

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<v Speaker 1>diseases like Alzheimer's and Parkinson's as well as those who

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<v Speaker 1>have been affected by stroke, but also just to see

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<v Speaker 1>how much more the brain is capable of if given

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<v Speaker 1>some additional firepower. Yeah, I'm sure this is just the

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<v Speaker 1>first of a ton of episodes we'll do on the brain,

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<v Speaker 1>but there's just something so fascinating about the research happening

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<v Speaker 1>right now, and so many things that once seemed like

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<v Speaker 1>science fiction that are now possible. So that's what we

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<v Speaker 1>decided to focus on. Yeah, and I'm so excited to

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<v Speaker 1>have a real superstar in this field on with us

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<v Speaker 1>in a bid. His name is John krak Our, and

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<v Speaker 1>he's a neuroscientist and neurologist at Johns Hopkins and he's

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<v Speaker 1>also the director of the Brain Learning, Animation and Movement Laboratory,

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<v Speaker 1>also known as BLAMAM. The best aconem in the business,

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<v Speaker 1>and obviously he's so interesting. I can't wait to get

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<v Speaker 1>him on the line. But before we do, we need

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<v Speaker 1>to back up just a little and and talk about

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<v Speaker 1>how we got where we are in terms of the

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<v Speaker 1>technology being added to our neural systems. I mean, not

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<v Speaker 1>our specifically, but humans in general. Right right, Well, you know,

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<v Speaker 1>it's crazy to realize that two thousand seventeen marks sixty

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<v Speaker 1>years since the first human trials for cochlear implants. These

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<v Speaker 1>implants were designed with electrodes positioned in the inner ear

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<v Speaker 1>to transmit sound to the brain, and then in nineteen

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<v Speaker 1>sixty four, after those trials, the first cochlear implant was

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<v Speaker 1>tested in a human volunteer. This was a huge step

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<v Speaker 1>in helping us to see that electronic devices could be

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<v Speaker 1>built to take sense reinformation and you know, such as sound,

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<v Speaker 1>to translate it into a language that the brain could

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<v Speaker 1>then process. So I really had no idea than that

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<v Speaker 1>long and and of course today they are much more

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<v Speaker 1>sophisticated cochlear implants helping tens of thousands of new patients

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<v Speaker 1>every year. Yeah, we should probably quickly note that there

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<v Speaker 1>are two general types of neural implants. First, you have

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<v Speaker 1>input devices, you know, like we described with cochlear implants.

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<v Speaker 1>These are the kind that takes sensory information from the

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<v Speaker 1>outside world and pass that along to our nervous system

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<v Speaker 1>via electrical signals. And then you have retinal implants, which

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<v Speaker 1>are also pretty amazing and they're another form of input device.

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<v Speaker 1>And then you'll also find devices that are used to

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<v Speaker 1>help control seizures, you know from epilepsy or maybe tremors

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<v Speaker 1>caused by Parkinson's against signals brought in from the outside world. Sure,

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<v Speaker 1>and and the progress they're making on treating things like

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<v Speaker 1>Parkinson's through deep brain stimulation implants is incredible. So I

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<v Speaker 1>didn't realize that there have now been over a hundred

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<v Speaker 1>thousand people treated with these. And for our listeners when

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<v Speaker 1>Will and I were at Mental Floss, we have really

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<v Speaker 1>teamed up with National Geographic to help demystify brain surgery.

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<v Speaker 1>We did the show called Brain Surgery Live, where we

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<v Speaker 1>followed the story of this wonderful man who had been

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<v Speaker 1>suffering from Parkinson's tremors for over a decade and we

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<v Speaker 1>got to see how when surgeons inserted electrodes into the

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<v Speaker 1>patient's basil ganglia, which is this area of the brain

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<v Speaker 1>that's most affected by Parkinson's, and then when they stimulated

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<v Speaker 1>those electrodes with a battery, the patient's tremors stopped completely.

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<v Speaker 1>Like it was one of the most miraculous things I've

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<v Speaker 1>ever seen. This gentleman who couldn't easily hold a piece

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<v Speaker 1>of paper because he was shaking so much, suddenly had

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<v Speaker 1>these tremors turned off, and he had so much dexterity,

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<v Speaker 1>Like he sent a message to his family from the

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<v Speaker 1>operating room on an iPad and it was just incredible. Yeah,

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<v Speaker 1>it definitely was. Alright, So so those are all examples

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<v Speaker 1>of input devices. So now let's talk about output devices,

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<v Speaker 1>which have come along more recently. And you know, these

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<v Speaker 1>are the devices that take information in the opposite direction.

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<v Speaker 1>They read and record brain activity and then translate that

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<v Speaker 1>into signals for some outside use. You stay controlling a

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<v Speaker 1>prosthetic arm, for example. And I know this is much

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<v Speaker 1>more recent, but we're still talking to a couple of decades, right, Yeah,

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<v Speaker 1>I'm pretty sure it was. Which is the your most

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<v Speaker 1>people associate with the release of Mariah Carey and Boys,

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<v Speaker 1>Two Men's One Sweet Day. I mean, you remember what

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<v Speaker 1>a huge year that was because of that, But you know,

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<v Speaker 1>it was also the year that researchers first and planted

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<v Speaker 1>electrodes into the brain of a monkey and then helped

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<v Speaker 1>it use a prosthetic arm. And as we mentioned earlier

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<v Speaker 1>back in our will We Ever Live Without Sleep? Episode,

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<v Speaker 1>we talked about how we've gotten so much better at

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<v Speaker 1>observing brain patterns and can actually see the same areas

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<v Speaker 1>of the brain light up as we run through those

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<v Speaker 1>memories again during sleep, and that helps us consolidate those

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<v Speaker 1>memories well in a similar kind of observation. When they

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<v Speaker 1>place electrodes on the motor cortex of these monkeys, they

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<v Speaker 1>can then observe spikes in the activity of certain neurons.

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<v Speaker 1>And as they observe these of the course of several studies,

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<v Speaker 1>they began to figure out what patterns of spikes corresponded

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<v Speaker 1>with certain our motions, and over time the researchers figure

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<v Speaker 1>about how to teach the monkeys to control a robotic arm,

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<v Speaker 1>you know, just using their brain signals. And of course

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<v Speaker 1>the next step was then to figure out how to

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<v Speaker 1>do this, you know, for people. Yeah, so I actually

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<v Speaker 1>read a good bit about this, especially as it related

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<v Speaker 1>to helping those dealing with paralysis, and I think the

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<v Speaker 1>first person to use a brain implant to both use

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<v Speaker 1>certain functions on a computer screen and to gain some

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<v Speaker 1>functionality from a prosthetic hand was this guy named Matthew

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<v Speaker 1>Nagle back in two thousand four. So he was paralyzed

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<v Speaker 1>from the neck down. So this was a big step,

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<v Speaker 1>and though with the brain being such a complicated organ,

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<v Speaker 1>there's clearly a long way to go. So researchers are

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<v Speaker 1>still working on ways to improve this technology, and as

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<v Speaker 1>of now, patients still have to be connected to a

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<v Speaker 1>computer for it to work. But it's still pretty remarkable

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<v Speaker 1>what's happened in efforts to help those fighting paralysis. Yeah,

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<v Speaker 1>we were talking about some of these yesterday, and I

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<v Speaker 1>actually think it would be helpful if you would just

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<v Speaker 1>walk us through some of the most recent progress in

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<v Speaker 1>this area. Sure, well, several things have happened in the

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<v Speaker 1>past year or two. On the communications front. We've placed

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<v Speaker 1>electrodes inside the brain of woman with a LS, allowing

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<v Speaker 1>her to communicate simply by using her thoughts. Basically, she

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<v Speaker 1>uses an eye tracker to spell words on a screen.

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<v Speaker 1>But at some point, like many people with a LS,

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<v Speaker 1>she may lose that ability as well. So she's participating

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<v Speaker 1>in this other study where they've implanted an electrode system

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<v Speaker 1>over the region of the brain that affects hand movement,

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<v Speaker 1>and after a bit of training, just by imagining moving

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<v Speaker 1>her hand, she was actually able to make selections on

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<v Speaker 1>a screen, And she's apparently gotten this down to accuracy,

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<v Speaker 1>which is just unbelieved. I just have a hard time

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<v Speaker 1>wrapping my head around how this is even possible. Yeah,

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<v Speaker 1>it's really is amazing. So in recent years we've also

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<v Speaker 1>seen some major leaps in terms of motion and touch.

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<v Speaker 1>So last year, this partially paralyzed man was able to

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<v Speaker 1>pour liquid from a bottle, and even more impressively, he

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<v Speaker 1>was able to play guitar hero because they had an

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<v Speaker 1>electrode sleeve that was connected to the motor cortex in

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<v Speaker 1>his brain. And in another study, scientists helped this quadriplegic

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<v Speaker 1>man feel as though he was touching certain objects through

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<v Speaker 1>a robotic arm, like he could actually yield objects all

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<v Speaker 1>by tapping into a somatosensory cortex. I mean, I can

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<v Speaker 1>only imagine how strange and guessing overwhelming that was to

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<v Speaker 1>regain this sense of touch. Definitely, it all just seems

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<v Speaker 1>so unreal. And there's also this electrode cap that's actually

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<v Speaker 1>helped some paralyzed people begin walking again. It's a little

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<v Speaker 1>different than the others because the cap is connected to

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<v Speaker 1>this exoskeleton which is on the person's legs, and as

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<v Speaker 1>signals get sent from the cap to the exoskeleton, it

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<v Speaker 1>allows the legs to move, which is awesome. But there's

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<v Speaker 1>actually been some cases that paralyzed people learning to walk

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<v Speaker 1>without the exoskeleton in recent years. Like the cap sends

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<v Speaker 1>signals to electrodes implanted into the person's own legs, that's

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<v Speaker 1>so cool. A Alright, so we've talked about input devices

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<v Speaker 1>and output devices, and you might be wondering what the

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<v Speaker 1>next step in the evolution is, and it's something called

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<v Speaker 1>bidirectional interfaces, and these combined the input and the output

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<v Speaker 1>and they could be huge and helping those deal with

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<v Speaker 1>damaged nervous systems. So, well, let's say somebody had a

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<v Speaker 1>stroke and as a result of that, there are parts

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<v Speaker 1>of their nervous system that are not really communicating or

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<v Speaker 1>appropriately connected anymore. And so through the use of a

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<v Speaker 1>bidirectional implant, you might be able to re establish this

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<v Speaker 1>connection and give them the ability to use a body

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<v Speaker 1>part that had effectively been paralyzed due to the stroke.

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<v Speaker 1>But what's even more fascinating is that there's a developing

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<v Speaker 1>area that's still very very early days. So what's that. Well,

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<v Speaker 1>it involves playing with memories, and apparently we might be

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<v Speaker 1>able to restore memories by using an implant to replace

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<v Speaker 1>the input and output flow from the hippo campus. And

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<v Speaker 1>and this is the area of the brain that's responsible

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<v Speaker 1>for memory formation. Well, let's talk a little bit more

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<v Speaker 1>about memory and some of that research you mentioned at

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<v Speaker 1>the very top of the show. I mean, the idea

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<v Speaker 1>that scientists could basically transplant the memories of a bunch

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<v Speaker 1>of rats into a single rats brain and then watch

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<v Speaker 1>it behave as though it learned certain things through experience,

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<v Speaker 1>even though it hadn't. I mean, that's just so crazy

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<v Speaker 1>to me and also just so hard to believe. And

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<v Speaker 1>that's pretty much what Deadweiler said about the science community's

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<v Speaker 1>response to his five findings at first. I mean, he said,

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<v Speaker 1>no one's going to believe this until I do a

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<v Speaker 1>hundred control experiments. But play this out for me a

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<v Speaker 1>little like what does all of this mean for people, Well,

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<v Speaker 1>there's obviously a long way to go to apply this

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<v Speaker 1>to the same type of neural and plant and humans,

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<v Speaker 1>but you know, the thinking is that something like this

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<v Speaker 1>could play a very real role in helping somebody with

0:11:19.520 --> 0:11:22.520
<v Speaker 1>Alzheimer's or someone who out of stroke, you know, get

0:11:22.559 --> 0:11:25.440
<v Speaker 1>some of their brain function back. I mean, the problem

0:11:25.440 --> 0:11:27.920
<v Speaker 1>of memory losses that it often results in damage in

0:11:27.960 --> 0:11:31.640
<v Speaker 1>the brain that prevents the flow of information between two locations.

0:11:32.160 --> 0:11:33.920
<v Speaker 1>And so if you could essentially create a way to

0:11:34.000 --> 0:11:37.040
<v Speaker 1>bypass the damaged areas, you might be able to create

0:11:37.080 --> 0:11:40.520
<v Speaker 1>both new memories and hopefully regain the ability to access

0:11:40.559 --> 0:11:44.360
<v Speaker 1>old ones, which is a fascinating idea. Though obviously memories

0:11:44.440 --> 0:11:47.640
<v Speaker 1>this super complicated thing, right, I mean, while the hippocampus

0:11:47.679 --> 0:11:50.040
<v Speaker 1>is where long term memories are formed, you still have

0:11:50.080 --> 0:11:52.199
<v Speaker 1>to consider all these other areas of the brain that

0:11:52.280 --> 0:11:54.520
<v Speaker 1>are working together. And that's true, so it's it's a

0:11:54.640 --> 0:11:57.840
<v Speaker 1>very difficult task. But there are many researchers that believe

0:11:57.880 --> 0:11:59.920
<v Speaker 1>at some point it might be possible to put in

0:12:00.080 --> 0:12:02.640
<v Speaker 1>implant in the hippo campus and actually be able to

0:12:02.679 --> 0:12:05.800
<v Speaker 1>record memories as they come together. Of course, they then

0:12:05.880 --> 0:12:08.040
<v Speaker 1>have to figure out that you know, the neural signals

0:12:08.120 --> 0:12:11.720
<v Speaker 1>or the codes that are the indicators of certain memories. Yeah,

0:12:11.760 --> 0:12:13.160
<v Speaker 1>and and of course no one's saying this will be

0:12:13.160 --> 0:12:15.880
<v Speaker 1>an easy task, but I was reading about some researchers

0:12:15.920 --> 0:12:17.840
<v Speaker 1>that are working to try and figure out how to

0:12:17.880 --> 0:12:21.000
<v Speaker 1>crack the code around certain memories and understand this has

0:12:21.040 --> 0:12:24.080
<v Speaker 1>to happen among the millions and millions of neurons firing.

0:12:24.440 --> 0:12:27.320
<v Speaker 1>But scientists like Theodore Burger at the University of Southern

0:12:27.360 --> 0:12:31.200
<v Speaker 1>California are actually making real progress towards this. Yeah. And

0:12:31.240 --> 0:12:33.160
<v Speaker 1>actually Burger was one of them that teamed up with

0:12:33.240 --> 0:12:36.120
<v Speaker 1>dead Wilder and Hampson on some of their rats studies,

0:12:36.440 --> 0:12:39.160
<v Speaker 1>so specifically in studies where they drugged rats to mimic

0:12:39.200 --> 0:12:41.760
<v Speaker 1>amnesia so they wouldn't be able to remember the whole

0:12:41.960 --> 0:12:45.800
<v Speaker 1>lever pushing thing. But then after using electrodes to stimulate

0:12:45.840 --> 0:12:49.040
<v Speaker 1>the same neural pattern, the rats were able to remember

0:12:49.080 --> 0:12:51.600
<v Speaker 1>what to do. Yeah. So, uh, I don't know about

0:12:51.640 --> 0:12:55.079
<v Speaker 1>roofy rats, but the potential applications of this are truly staggering.

0:12:55.400 --> 0:12:57.559
<v Speaker 1>But but I guess one question I have is whether

0:12:57.559 --> 0:13:00.320
<v Speaker 1>there's a neural code that applies to everyone, or whether

0:13:00.360 --> 0:13:02.920
<v Speaker 1>everyone's is different. That's a very good point that they're

0:13:02.920 --> 0:13:05.200
<v Speaker 1>still trying to figure out all the specifics of this.

0:13:05.360 --> 0:13:07.720
<v Speaker 1>But I have to be honest, I can't wait to

0:13:07.720 --> 0:13:09.600
<v Speaker 1>get our guests on the line to get his thoughts

0:13:09.640 --> 0:13:12.800
<v Speaker 1>on some even more mind blowing possibilities of this brain

0:13:12.880 --> 0:13:23.320
<v Speaker 1>machine connection. Yeah, let's do it. So our guest today

0:13:23.360 --> 0:13:26.960
<v Speaker 1>is a neuroscientist and professor at Johns Hopkins. He's also

0:13:27.040 --> 0:13:30.000
<v Speaker 1>the founder and director of the Brain Learning, Animation and

0:13:30.040 --> 0:13:33.319
<v Speaker 1>Movement Laboratory or BLAM as mango and I love to say,

0:13:33.760 --> 0:13:36.520
<v Speaker 1>and his work in helping treat stroke patients is just

0:13:36.840 --> 0:13:40.160
<v Speaker 1>fascinating and we're thrilled to have him on today. John Krakauer,

0:13:40.280 --> 0:13:44.360
<v Speaker 1>welcome to part time Genius. Thank you. I certainly I'm

0:13:44.400 --> 0:13:47.880
<v Speaker 1>only a part time genius. So you're joining us from

0:13:47.880 --> 0:13:51.280
<v Speaker 1>a cafe in Lisbon, Portugal, Is that right? Yeah? I

0:13:51.280 --> 0:13:55.120
<v Speaker 1>mean Portugal. I spend a month and you know too,

0:13:55.800 --> 0:13:59.679
<v Speaker 1>usually a month and a half every year. Yeah. So

0:13:59.840 --> 0:14:02.959
<v Speaker 1>that a visiting exhibition of a fantastic place. It's talking

0:14:02.960 --> 0:14:09.400
<v Speaker 1>about names. It's called the Shampolo mo Center for the Unknown. So, John,

0:14:09.440 --> 0:14:12.000
<v Speaker 1>knowing that stroke is the leading cause of disability in

0:14:12.040 --> 0:14:15.400
<v Speaker 1>the US and often causes complete arm and or leg

0:14:15.520 --> 0:14:19.320
<v Speaker 1>paralysis and people. This is obviously very important work to

0:14:19.760 --> 0:14:22.600
<v Speaker 1>many many people. Yeah, but you've explained that one of

0:14:22.640 --> 0:14:25.240
<v Speaker 1>the things we failed to understand for so long was

0:14:25.600 --> 0:14:28.200
<v Speaker 1>just how critical it is to begin rehab as quickly

0:14:28.240 --> 0:14:30.880
<v Speaker 1>as possible. So can you talk a little bit about

0:14:30.920 --> 0:14:35.120
<v Speaker 1>this and the studies that led to this realization. Yeah, so, Um,

0:14:35.680 --> 0:14:38.320
<v Speaker 1>it's a it's a long story really. In other words,

0:14:38.600 --> 0:14:41.920
<v Speaker 1>Strokes has been really interesting to neurologists over a century,

0:14:42.120 --> 0:14:47.600
<v Speaker 1>and they were very much interested in studying animals, particularly

0:14:49.240 --> 0:14:53.960
<v Speaker 1>primate non even primates sort of guests some of the

0:14:54.000 --> 0:14:58.040
<v Speaker 1>mechanisms of the deficit office Strokes. And it's ironic that

0:14:58.120 --> 0:15:00.480
<v Speaker 1>if you look at the very early study in the

0:15:00.520 --> 0:15:04.200
<v Speaker 1>early twentieth century, there was evidence that the animals had

0:15:04.200 --> 0:15:07.960
<v Speaker 1>the potential to get better early on after the lesions

0:15:08.000 --> 0:15:11.160
<v Speaker 1>were into and especially if you encourage them with training.

0:15:12.000 --> 0:15:16.920
<v Speaker 1>So it was there in the early literature, um, and

0:15:16.960 --> 0:15:22.360
<v Speaker 1>then it's not clear that ever sort of got through

0:15:22.440 --> 0:15:26.760
<v Speaker 1>to the clinicians and the therapists, and a certain nihilism

0:15:26.800 --> 0:15:34.800
<v Speaker 1>and a certain pessimism seconds um, and the general impetus

0:15:34.920 --> 0:15:39.720
<v Speaker 1>was to try to make people better early but not

0:15:39.840 --> 0:15:43.240
<v Speaker 1>with very high doses or to help people cope with

0:15:43.360 --> 0:15:46.280
<v Speaker 1>what they had left. So, John, your team developed a

0:15:46.280 --> 0:15:51.080
<v Speaker 1>system of therapy. They're involved in exo skeleton, robotics, brain stimulation,

0:15:51.360 --> 0:15:53.960
<v Speaker 1>and a game where you control a dolphin. Can Can

0:15:53.960 --> 0:15:55.320
<v Speaker 1>you tell us a little bit about the game you

0:15:55.400 --> 0:15:58.120
<v Speaker 1>developed and how things are going in you're testing well,

0:15:58.160 --> 0:16:00.280
<v Speaker 1>I should stay stay right from the beginning, it's been

0:16:00.320 --> 0:16:04.400
<v Speaker 1>a painful, low process. We are hoping to be able

0:16:04.440 --> 0:16:06.880
<v Speaker 1>to look at the data by the end of the year.

0:16:07.040 --> 0:16:10.760
<v Speaker 1>I cannot tell you any results. I don't know that yet.

0:16:11.160 --> 0:16:17.640
<v Speaker 1>Um Now, in terms of why, it's actually a bit

0:16:17.680 --> 0:16:20.720
<v Speaker 1>of a bit of a story, the major answers, how

0:16:20.760 --> 0:16:23.280
<v Speaker 1>do you get people to make hundreds, if not thousands,

0:16:23.280 --> 0:16:26.440
<v Speaker 1>of continuous movements day in day out. In other words,

0:16:26.440 --> 0:16:30.760
<v Speaker 1>the animal egg suggestive you needed thousands of movements of

0:16:30.960 --> 0:16:33.920
<v Speaker 1>titrated difficult movements. You know, you're not going to get

0:16:33.960 --> 0:16:36.400
<v Speaker 1>somebody to pick up a glass of water five hundred

0:16:36.480 --> 0:16:38.960
<v Speaker 1>times in a row. You're not going to get someone

0:16:39.000 --> 0:16:42.280
<v Speaker 1>to use in life and fork, you know, thousands of repetitions,

0:16:42.320 --> 0:16:45.400
<v Speaker 1>so it's not a trivial thing. How do you get

0:16:45.400 --> 0:16:48.680
<v Speaker 1>people into a context where they're going to be making

0:16:49.040 --> 0:16:50.880
<v Speaker 1>the kinds of movements you want them to use in

0:16:50.960 --> 0:16:53.360
<v Speaker 1>everyday life, but in a way you trick them into

0:16:53.360 --> 0:16:55.840
<v Speaker 1>making them in the under conditions. But there's so much

0:16:55.880 --> 0:16:58.720
<v Speaker 1>fun they don't realize they're practicing one. I mean, I

0:16:58.760 --> 0:17:00.720
<v Speaker 1>don't know if any of you've ever had the abilitation

0:17:00.800 --> 0:17:05.159
<v Speaker 1>for anything, you know, elbow surgery, shoulder surgery, and I have,

0:17:06.000 --> 0:17:09.000
<v Speaker 1>and it's so boring that I was a terrible patience.

0:17:09.200 --> 0:17:11.600
<v Speaker 1>I didn't even do the ten minutes quite a day

0:17:11.640 --> 0:17:13.640
<v Speaker 1>that I was meant to do. It was so dull.

0:17:14.240 --> 0:17:17.560
<v Speaker 1>Now imagine that in the conditions of strokes. So one

0:17:17.560 --> 0:17:20.920
<v Speaker 1>thing we know is having an illness, being brain damaged

0:17:21.240 --> 0:17:24.240
<v Speaker 1>business in it of itself an incentive to go to

0:17:24.280 --> 0:17:26.680
<v Speaker 1>the gym or the equivalent. So we had to find

0:17:26.720 --> 0:17:30.240
<v Speaker 1>a way to make people do stuff that was fun,

0:17:31.200 --> 0:17:34.200
<v Speaker 1>and we also wanted to do something that the movements

0:17:34.240 --> 0:17:38.000
<v Speaker 1>they made were general, they were useful for everyday life.

0:17:38.000 --> 0:17:39.960
<v Speaker 1>Because there's something, you know, the learning that's called the

0:17:40.000 --> 0:17:43.879
<v Speaker 1>curse of charte specificity. But if you practice task A,

0:17:44.680 --> 0:17:47.479
<v Speaker 1>you only get good at tak A, and it doesn't

0:17:47.600 --> 0:17:49.879
<v Speaker 1>make you any better at task B, two or D.

0:17:50.680 --> 0:17:53.640
<v Speaker 1>And how do you guys, come up with a dolphin concept. Well, okay,

0:17:53.720 --> 0:17:55.879
<v Speaker 1>so there's a lot of data to show you if

0:17:55.880 --> 0:17:59.080
<v Speaker 1>you put wraps after brain injury into enriched environment and

0:17:59.160 --> 0:18:01.240
<v Speaker 1>as you put them in a little cage full of

0:18:01.680 --> 0:18:06.320
<v Speaker 1>ramps and spinning wheels and balls and friends, they do

0:18:06.480 --> 0:18:08.480
<v Speaker 1>much better even if you don't train them on the

0:18:08.520 --> 0:18:11.199
<v Speaker 1>top to test him on. So that was the final

0:18:11.520 --> 0:18:15.120
<v Speaker 1>sort of clue it needs to be in an emotional, immersive,

0:18:15.640 --> 0:18:21.159
<v Speaker 1>motivated environments. And then I met these remarkable to people

0:18:21.359 --> 0:18:26.040
<v Speaker 1>to meet Roy and o'barmage who were both graduate students,

0:18:26.119 --> 0:18:29.879
<v Speaker 1>well they've both been undergrad and grad ad Hopkins and

0:18:30.080 --> 0:18:34.360
<v Speaker 1>they were doing beautiful gaming um where they were simulating

0:18:34.480 --> 0:18:37.880
<v Speaker 1>animal movements. And I had gone to the Hopkins campus

0:18:37.880 --> 0:18:43.680
<v Speaker 1>looking for young gamers and I found them, introduced to them,

0:18:43.720 --> 0:18:45.879
<v Speaker 1>and they showed me what they had done, and I

0:18:45.960 --> 0:18:48.800
<v Speaker 1>realized that I wanted to go a step further and

0:18:48.880 --> 0:18:54.720
<v Speaker 1>not to have people watch beautiful movement on a game,

0:18:54.960 --> 0:18:59.000
<v Speaker 1>but the to take the execlusive step of controlling it

0:19:00.040 --> 0:19:03.120
<v Speaker 1>if you became the character in the game. So basically

0:19:03.160 --> 0:19:09.679
<v Speaker 1>imagine gaming meats Pixar meets new controlling the characters using

0:19:10.640 --> 0:19:13.080
<v Speaker 1>into the idea that if you had a dolphin, which

0:19:13.119 --> 0:19:16.280
<v Speaker 1>is a beautiful animal that we love to watch moves.

0:19:16.320 --> 0:19:19.560
<v Speaker 1>That's why we love dolph, which you love their acrobatics

0:19:19.600 --> 0:19:22.240
<v Speaker 1>and they love continuously in the water and there's no

0:19:22.359 --> 0:19:25.280
<v Speaker 1>stopping is starting. I mean you can be moving your

0:19:25.400 --> 0:19:28.840
<v Speaker 1>arms around continuously without starting and stopping because eused to

0:19:28.920 --> 0:19:32.240
<v Speaker 1>you stop moving your arm, the animal will continue to

0:19:32.280 --> 0:19:37.080
<v Speaker 1>move through the water. Bribesmen, So we thought that we

0:19:37.160 --> 0:19:43.119
<v Speaker 1>could make patients babble like children do, moving in this

0:19:43.320 --> 0:19:45.720
<v Speaker 1>cloud of everyday life. We'll tell us what else you

0:19:45.720 --> 0:19:48.719
<v Speaker 1>guys are focused on it blam right now. So you

0:19:48.760 --> 0:19:51.480
<v Speaker 1>can actually take somebody who's locked their hands through an

0:19:51.480 --> 0:19:55.399
<v Speaker 1>actiment soldier for example, so they can have just a

0:19:55.480 --> 0:20:02.600
<v Speaker 1>stump where their hand was and the using prospect for years.

0:20:03.160 --> 0:20:06.800
<v Speaker 1>And you can take the towns of someone who died

0:20:09.080 --> 0:20:14.479
<v Speaker 1>and basically reconnected to someone else's body, so you can

0:20:14.560 --> 0:20:20.320
<v Speaker 1>basically have someone else's hand. There are many many ways

0:20:20.359 --> 0:20:24.440
<v Speaker 1>that you could basically expand the the repertoires in the

0:20:24.520 --> 0:20:28.840
<v Speaker 1>movement by actually having more than just your hands. In

0:20:28.880 --> 0:20:31.760
<v Speaker 1>other words, the irony right on the one hand, you

0:20:31.800 --> 0:20:34.199
<v Speaker 1>want to use this app to training just to have

0:20:34.280 --> 0:20:38.040
<v Speaker 1>a hand like everybody else it is healthy people. You

0:20:38.080 --> 0:20:40.600
<v Speaker 1>could go beyond the hand. Yeah, that was one of

0:20:40.600 --> 0:20:42.480
<v Speaker 1>the things that Will and I were both fascinated by

0:20:42.480 --> 0:20:45.080
<v Speaker 1>in that article, the idea that we could almost like

0:20:45.280 --> 0:20:48.359
<v Speaker 1>upgrade our boring old hands. We don't know what the

0:20:48.400 --> 0:20:51.600
<v Speaker 1>upper limit times. What if you what if somebody was

0:20:51.640 --> 0:20:54.960
<v Speaker 1>to be born in eight homes? Because in the minute,

0:20:56.600 --> 0:21:01.639
<v Speaker 1>each of your muscle fibers might be the admit you

0:21:01.680 --> 0:21:04.400
<v Speaker 1>see many many, many many muffles make up your arm.

0:21:04.720 --> 0:21:08.159
<v Speaker 1>And we talk about just controlling, but you're actually controlling

0:21:08.280 --> 0:21:12.000
<v Speaker 1>much the d of your muscles in your heart. So

0:21:13.040 --> 0:21:16.760
<v Speaker 1>you can you start thinking the way I'm laying out now,

0:21:17.600 --> 0:21:21.119
<v Speaker 1>imagine what the range of its impacting, the words you

0:21:21.160 --> 0:21:25.240
<v Speaker 1>could have if you were to st combinatory slow in

0:21:25.280 --> 0:21:28.240
<v Speaker 1>that way. Yeah, it's so crazy to think where your

0:21:28.240 --> 0:21:32.679
<v Speaker 1>brain might max out. Yeah, instead of we could have

0:21:33.080 --> 0:21:38.159
<v Speaker 1>a New Yorker cartoon where the the conductor, instead of

0:21:38.160 --> 0:21:43.080
<v Speaker 1>having all the musicians in the orchestra is all the musicians.

0:21:44.560 --> 0:21:47.919
<v Speaker 1>That's pretty incredible. Well, John, we we really appreciate the

0:21:47.920 --> 0:21:51.280
<v Speaker 1>work you're doing. It's both fascinating and obviously, you know,

0:21:51.359 --> 0:21:53.480
<v Speaker 1>life changing for a lot of people. So thank you

0:21:53.520 --> 0:21:55.360
<v Speaker 1>for that work and thank you for joining us today

0:21:55.400 --> 0:21:57.919
<v Speaker 1>on Part Time Genius. It was an athlete pleasure and

0:21:58.440 --> 0:22:14.920
<v Speaker 1>you guys are wonderful. A pat to welcome back to

0:22:14.960 --> 0:22:17.360
<v Speaker 1>Part Time Genius, no Ango. Before the break, we were

0:22:17.359 --> 0:22:20.440
<v Speaker 1>talking about the possibilities of using devices in our brains

0:22:20.480 --> 0:22:22.840
<v Speaker 1>to assist with memory. Yeah, and there are actually a

0:22:22.920 --> 0:22:24.680
<v Speaker 1>few other things related to this field that I wanted

0:22:24.720 --> 0:22:26.840
<v Speaker 1>to talk about before we move on. All right, we'll

0:22:26.880 --> 0:22:28.720
<v Speaker 1>go for it. Well. The first is something I was

0:22:28.760 --> 0:22:31.680
<v Speaker 1>reading about a new scientist, and this is the possibility

0:22:31.760 --> 0:22:33.359
<v Speaker 1>that we could one day and plan a chip in

0:22:33.440 --> 0:22:36.359
<v Speaker 1>people who had suffered some sort of brain damage, and

0:22:36.480 --> 0:22:38.800
<v Speaker 1>this chip would include code that would help these people

0:22:38.800 --> 0:22:41.479
<v Speaker 1>accomplish some of the basic things lost after a stroke

0:22:41.640 --> 0:22:44.360
<v Speaker 1>or some other form of damage. There's a quote from

0:22:44.400 --> 0:22:47.639
<v Speaker 1>Justin Sanchez, who works in neuroprosthetics at the University of

0:22:47.680 --> 0:22:51.440
<v Speaker 1>Miami and Florida, and it goes, before we can get

0:22:51.520 --> 0:22:53.919
<v Speaker 1>someone with brain damage back to work, we want to

0:22:53.920 --> 0:22:58.000
<v Speaker 1>return their capability to form those fundamental declarative memories. Yeah.

0:22:58.080 --> 0:23:00.720
<v Speaker 1>It's fascinating to think of that being a possibility, and

0:23:00.760 --> 0:23:02.800
<v Speaker 1>I can't even imagine how life changing it would be

0:23:02.840 --> 0:23:05.480
<v Speaker 1>for people struggling to tackle some of the basic life

0:23:05.480 --> 0:23:08.080
<v Speaker 1>skills they may have once had. Sure, and and then

0:23:08.080 --> 0:23:10.280
<v Speaker 1>you take it a step further right, because Sanchez also

0:23:10.359 --> 0:23:13.120
<v Speaker 1>told new scientists, think of the guy coming back from

0:23:13.160 --> 0:23:16.919
<v Speaker 1>war who can't remember his wife's face. And that's heartbreaking

0:23:16.960 --> 0:23:19.479
<v Speaker 1>to think about. But the science behind it and how

0:23:19.520 --> 0:23:23.160
<v Speaker 1>they're approaching the science, that's fascinating. And we can actually

0:23:23.200 --> 0:23:25.640
<v Speaker 1>come back to more studies from dead Wilder and Hampson

0:23:25.720 --> 0:23:28.920
<v Speaker 1>on this sod did you read about their studies on maccas, Yeah,

0:23:29.200 --> 0:23:31.840
<v Speaker 1>I did so for the listeners. This is a study

0:23:31.880 --> 0:23:34.480
<v Speaker 1>where they showed the maccas and image on the screen

0:23:34.560 --> 0:23:36.320
<v Speaker 1>and and then have them pick out that image once

0:23:36.320 --> 0:23:38.400
<v Speaker 1>it was part of a much bigger collection of images.

0:23:38.720 --> 0:23:41.480
<v Speaker 1>This happened a minute or so later, and and during

0:23:41.520 --> 0:23:44.480
<v Speaker 1>this the researchers were martyring their brains and observing the

0:23:44.480 --> 0:23:48.040
<v Speaker 1>signals involved in this process. And then they added drugs

0:23:48.240 --> 0:23:50.399
<v Speaker 1>and these were to prevent the macaques from turning this

0:23:50.440 --> 0:23:53.480
<v Speaker 1>event into a long term memory. It effectively made them

0:23:53.520 --> 0:23:56.399
<v Speaker 1>forget it happened. But then the scientists had them performed

0:23:56.400 --> 0:23:59.080
<v Speaker 1>the task again, and when they did, they hit the

0:23:59.080 --> 0:24:02.040
<v Speaker 1>neurons with the same pattern of signals they observed earlier,

0:24:02.240 --> 0:24:04.880
<v Speaker 1>and the macaques seem to know exactly what to look for.

0:24:05.560 --> 0:24:07.399
<v Speaker 1>You know, there are a couple of pieces of us

0:24:07.400 --> 0:24:10.080
<v Speaker 1>that are just super interesting to me. So one is

0:24:10.119 --> 0:24:13.120
<v Speaker 1>what Deadwiler and Hampson and other researchers believe about how

0:24:13.160 --> 0:24:15.880
<v Speaker 1>memory works, and and that is that the brain patterns

0:24:15.880 --> 0:24:19.520
<v Speaker 1>they observe aren't necessarily attached to an exact image. It's

0:24:19.520 --> 0:24:21.800
<v Speaker 1>really more that our brains tend to break things down

0:24:21.800 --> 0:24:24.840
<v Speaker 1>into features, so you know, like by shape or color

0:24:25.080 --> 0:24:28.680
<v Speaker 1>or size, and then this collection of information, when that's

0:24:28.720 --> 0:24:31.440
<v Speaker 1>piece together, that's what helps us recall an object or

0:24:31.440 --> 0:24:33.960
<v Speaker 1>a person specifically. That's crazy, like I never would have

0:24:34.000 --> 0:24:36.000
<v Speaker 1>thought about that. Well, and the other thing that's so

0:24:36.080 --> 0:24:39.080
<v Speaker 1>interesting is our brains plasticity and its ability to learn

0:24:39.119 --> 0:24:41.760
<v Speaker 1>to work with these devices. So so let's go back

0:24:41.760 --> 0:24:43.840
<v Speaker 1>for a minute to the neural implants used to control

0:24:43.880 --> 0:24:46.639
<v Speaker 1>a robotic arm. The interesting thing is the way that

0:24:46.680 --> 0:24:49.640
<v Speaker 1>the neurons are working to control the robotic arm, that

0:24:49.640 --> 0:24:51.720
<v Speaker 1>that they're not identical to the way it would move

0:24:51.800 --> 0:24:55.400
<v Speaker 1>a typical arm. But our brains adapt and they observe

0:24:55.560 --> 0:24:59.040
<v Speaker 1>and they learn, and then because of this neurofeedback, they

0:24:59.200 --> 0:25:01.800
<v Speaker 1>master attack ask, even if it means doing that task

0:25:01.800 --> 0:25:04.800
<v Speaker 1>in a slightly different way. Yeah, and the same thing

0:25:04.880 --> 0:25:07.800
<v Speaker 1>happens with the stimulation used to assist with memory, Like

0:25:07.840 --> 0:25:10.840
<v Speaker 1>our our brain's plasticity helps us work with these devices

0:25:10.880 --> 0:25:13.280
<v Speaker 1>to learn. And now DARK was getting more and more

0:25:13.280 --> 0:25:16.000
<v Speaker 1>interested in this type of research, and I always forget

0:25:16.000 --> 0:25:17.959
<v Speaker 1>what it stands for US. I wrote down, that's the

0:25:18.040 --> 0:25:21.760
<v Speaker 1>US Defense Advanced Research Projects Agency, and they have something

0:25:21.760 --> 0:25:25.960
<v Speaker 1>they're calling the Restoring Active Memory Project. They're basically investing

0:25:26.080 --> 0:25:28.960
<v Speaker 1>significant sums to try and develop technology that could be

0:25:29.000 --> 0:25:32.200
<v Speaker 1>implanted to help a range of people dealing with brain injury.

0:25:32.400 --> 0:25:35.240
<v Speaker 1>So that means like the soldiers were turning home with injury,

0:25:35.280 --> 0:25:38.520
<v Speaker 1>to to those battling Alzheimer's, to those who suffered strokes.

0:25:39.119 --> 0:25:42.560
<v Speaker 1>You know. And while the applications are truly incredible, I

0:25:42.640 --> 0:25:44.399
<v Speaker 1>do think we have to at least note some of

0:25:44.400 --> 0:25:47.040
<v Speaker 1>the ethical concerns and risk involved in all of this.

0:25:47.640 --> 0:25:49.640
<v Speaker 1>I mean, think about what it means to be able

0:25:49.680 --> 0:25:53.640
<v Speaker 1>to implant memories, especially memories that might not be our own.

0:25:54.000 --> 0:25:56.320
<v Speaker 1>I mean, some would argue that our collection of memories

0:25:56.400 --> 0:25:58.520
<v Speaker 1>is really at the core of who we are, and

0:25:58.880 --> 0:26:01.040
<v Speaker 1>if our memories at some point, are are more of

0:26:01.080 --> 0:26:03.720
<v Speaker 1>a computer algorithm than you know then something our own

0:26:03.760 --> 0:26:07.639
<v Speaker 1>brains are producing. Are we still us? I mean that's

0:26:07.680 --> 0:26:09.199
<v Speaker 1>kind of deep to me, Mano, I don't know how

0:26:09.240 --> 0:26:11.479
<v Speaker 1>you feel about it. Well, I had to drop out

0:26:11.520 --> 0:26:15.639
<v Speaker 1>of a philosophy course for too deep. Another concern is

0:26:15.680 --> 0:26:18.679
<v Speaker 1>just the possibility of certain flaws or downsides to the

0:26:18.680 --> 0:26:20.719
<v Speaker 1>way the chips work. So let's say they don't just

0:26:20.800 --> 0:26:23.399
<v Speaker 1>bring up things we want to remember, but things we

0:26:23.480 --> 0:26:26.720
<v Speaker 1>really don't and have moved on from. I'm not saying

0:26:26.720 --> 0:26:28.880
<v Speaker 1>it's not worth doing this for the people who we've

0:26:28.880 --> 0:26:31.199
<v Speaker 1>talked about. I mean, I think we absolutely should, but

0:26:31.560 --> 0:26:34.760
<v Speaker 1>they're definitely gonna be some hurdles ahead. Well, there's there's

0:26:34.800 --> 0:26:36.960
<v Speaker 1>one other weird thought about this. So so let's say

0:26:37.000 --> 0:26:40.600
<v Speaker 1>we're using these devices and because of regained access to memories,

0:26:40.640 --> 0:26:43.720
<v Speaker 1>we might behave a little bit differently for better or worse.

0:26:44.160 --> 0:26:46.400
<v Speaker 1>Let's say in this case it's for worse, and then

0:26:46.400 --> 0:26:49.679
<v Speaker 1>there are consequences for that behavior. Could you then have

0:26:49.720 --> 0:26:52.560
<v Speaker 1>somebody that would argue that the memories that lead to

0:26:52.600 --> 0:26:55.359
<v Speaker 1>that said behavior were you know, not really their own,

0:26:55.440 --> 0:26:59.000
<v Speaker 1>and therefore shouldn't be the ones facing the consequences. Yeah,

0:26:59.080 --> 0:27:00.760
<v Speaker 1>I mean, the legal stuff is gonna be this other

0:27:00.800 --> 0:27:03.199
<v Speaker 1>patch of problems. But I'm going to choose to be

0:27:03.240 --> 0:27:05.560
<v Speaker 1>optimistic here and especially in the way it will help

0:27:05.600 --> 0:27:08.480
<v Speaker 1>those dealing with brain injury and disease. And I just

0:27:08.520 --> 0:27:11.399
<v Speaker 1>think it's going to be fascinating to watch. Well, you

0:27:11.440 --> 0:27:13.560
<v Speaker 1>don't have to wait decades to be fascinated, because guess

0:27:13.640 --> 0:27:21.919
<v Speaker 1>what time it is? Time for the PGG fact off. Yeah,

0:27:26.280 --> 0:27:28.880
<v Speaker 1>it's I'm gonna kick this off here. It turns out

0:27:28.960 --> 0:27:32.040
<v Speaker 1>researchers are better at understanding why after a night of drinking,

0:27:32.280 --> 0:27:35.000
<v Speaker 1>despite all those recent self promises you've made to eat

0:27:35.040 --> 0:27:37.720
<v Speaker 1>better and lose a few pounds, your hungry brain goes

0:27:37.720 --> 0:27:39.960
<v Speaker 1>into overdrive and you find yourself running for the border

0:27:40.000 --> 0:27:43.719
<v Speaker 1>to down a handful of Darrito's tacos. In a study

0:27:43.840 --> 0:27:47.000
<v Speaker 1>of mice, of course, they booze them up and martyred

0:27:47.040 --> 0:27:50.520
<v Speaker 1>their brain activity, and when the mice were completely pickled,

0:27:50.800 --> 0:27:52.960
<v Speaker 1>they noticed a spike in activity in a group of

0:27:52.960 --> 0:27:55.720
<v Speaker 1>neurons called a g r P and these are the

0:27:55.720 --> 0:27:58.600
<v Speaker 1>ones that are activated when our bodies are actually facing starvation,

0:27:59.000 --> 0:28:02.240
<v Speaker 1>and as a result, the mice ate more. But when

0:28:02.280 --> 0:28:04.440
<v Speaker 1>the scientists got them drunk again and block the A

0:28:04.520 --> 0:28:07.520
<v Speaker 1>g RP neurons. With medication, the mice didn't eat as much.

0:28:07.920 --> 0:28:10.160
<v Speaker 1>And the thinking is these same neurons are the ones

0:28:10.200 --> 0:28:13.040
<v Speaker 1>responsible for our post drunken feast. You know, I feel

0:28:13.040 --> 0:28:15.080
<v Speaker 1>like we've talked about drunk mice a couple of times

0:28:15.119 --> 0:28:17.760
<v Speaker 1>in this episode. All right, where do I want to start.

0:28:17.840 --> 0:28:20.280
<v Speaker 1>Let's see. Um. Well, as we've learned more about how

0:28:20.280 --> 0:28:23.480
<v Speaker 1>the brain works, I find those little tricks or shortcuts

0:28:23.480 --> 0:28:26.919
<v Speaker 1>that our brains used for making memories so interesting. And

0:28:26.960 --> 0:28:29.240
<v Speaker 1>there's some other ways our brains take shortcuts that that

0:28:29.320 --> 0:28:31.760
<v Speaker 1>I also find pretty interesting to look at. And one

0:28:31.760 --> 0:28:34.560
<v Speaker 1>of these deals with peripheral vision. So, according to a

0:28:34.600 --> 0:28:38.120
<v Speaker 1>study in the journal Psychological Science, researchers found that our

0:28:38.120 --> 0:28:40.920
<v Speaker 1>brains often make up things in our peripheral vision that

0:28:41.040 --> 0:28:43.920
<v Speaker 1>that aren't actually there. And this is because our brains

0:28:43.960 --> 0:28:47.520
<v Speaker 1>focus on our central vision intend to just make educated

0:28:47.560 --> 0:28:51.640
<v Speaker 1>guesses about our peripheral vision. I love that. So, despite

0:28:51.680 --> 0:28:53.680
<v Speaker 1>what your mother may have told you, it's a myth

0:28:53.760 --> 0:28:56.200
<v Speaker 1>that we're born with all our brain cells will ever have.

0:28:56.640 --> 0:28:58.760
<v Speaker 1>This study out of Sweden in the late nineties help

0:28:58.800 --> 0:29:02.360
<v Speaker 1>scientists prove that the hipocampus forms new neurons pretty much

0:29:02.400 --> 0:29:05.680
<v Speaker 1>our entire lives. And in this other study, also out

0:29:05.720 --> 0:29:08.000
<v Speaker 1>of Sweden, Wow, Sweden is really doing it. Yeah, they're

0:29:08.040 --> 0:29:11.080
<v Speaker 1>killing it. A team of researchers show that new brain

0:29:11.120 --> 0:29:13.920
<v Speaker 1>cells are formed in the striatum. It's a part of

0:29:13.920 --> 0:29:16.520
<v Speaker 1>the brain involved in motor control and decision making, among

0:29:16.560 --> 0:29:19.440
<v Speaker 1>other things. All right, well here's another one. I think

0:29:19.480 --> 0:29:21.720
<v Speaker 1>we've all heard that exercise is good for the brain.

0:29:22.160 --> 0:29:24.680
<v Speaker 1>In fact, studies have shown that taking half hour walks

0:29:24.720 --> 0:29:27.680
<v Speaker 1>a few times a week helps our abstract reasoning skills

0:29:27.920 --> 0:29:29.880
<v Speaker 1>and even helps with the growth of new cells and

0:29:29.920 --> 0:29:32.120
<v Speaker 1>the hippocampus. Kind Of like you were just talking about,

0:29:32.560 --> 0:29:34.880
<v Speaker 1>but I didn't realize that the effect can happen in

0:29:34.920 --> 0:29:38.479
<v Speaker 1>the reverse direction as well, That is, mental exercise can

0:29:38.480 --> 0:29:41.719
<v Speaker 1>be good for your physique. To one, study done at

0:29:41.720 --> 0:29:44.320
<v Speaker 1>the Cleveland Clinics show that those who spent fifteen minutes

0:29:44.320 --> 0:29:48.000
<v Speaker 1>a day thinking about exercising their biceps actually increase the

0:29:48.080 --> 0:29:52.479
<v Speaker 1>strength of their biceps by over a three month period.

0:29:52.720 --> 0:29:55.960
<v Speaker 1>I'm gonna start thinking so hard about my biceps. Yeah

0:29:56.000 --> 0:29:59.480
<v Speaker 1>that's awesome. Uh so, do you know a bigger brain

0:29:59.600 --> 0:30:03.160
<v Speaker 1>doesn't necessarily mean a smarter brain. Uh, the average human

0:30:03.160 --> 0:30:06.160
<v Speaker 1>brain is three pounds and Einstein's was only two point

0:30:06.240 --> 0:30:09.160
<v Speaker 1>seven pounds, And I think that's pretty solid proof. Yeah,

0:30:09.160 --> 0:30:11.959
<v Speaker 1>I would agree with that. Well, your brain generates twenty

0:30:12.040 --> 0:30:14.520
<v Speaker 1>watts of power, which is actually enough to run a

0:30:14.560 --> 0:30:18.440
<v Speaker 1>regular sized LED bulb. You know how we talk about

0:30:18.480 --> 0:30:21.600
<v Speaker 1>people being auditory or visual learners. Yeah, well, well, while

0:30:21.600 --> 0:30:23.520
<v Speaker 1>it may be true that we all have our preferences

0:30:23.520 --> 0:30:25.880
<v Speaker 1>and how we learn, like you might prefer to read

0:30:25.960 --> 0:30:28.800
<v Speaker 1>something instead of hearing it in lecture form, there really

0:30:28.800 --> 0:30:31.480
<v Speaker 1>aren't studies to back up this idea. I mean, when

0:30:31.560 --> 0:30:34.800
<v Speaker 1>tested students tended to perform similarly regardless of whether they

0:30:34.800 --> 0:30:37.040
<v Speaker 1>were taught in their preferred method or some other method.

0:30:37.400 --> 0:30:40.440
<v Speaker 1>That is surprising. Yeah, I've always just assumed that we

0:30:40.440 --> 0:30:43.000
<v Speaker 1>were either one or the other. So I think I'm

0:30:43.040 --> 0:30:45.640
<v Speaker 1>going to give you this week's fact Off trophy. Congratulations,

0:30:46.000 --> 0:30:48.080
<v Speaker 1>and if there any brain facts you feel we should know,

0:30:48.160 --> 0:30:50.120
<v Speaker 1>hit us up at part time genius at how stuff

0:30:50.160 --> 0:30:52.760
<v Speaker 1>works dot com. You can also find us on Facebook

0:30:52.840 --> 0:30:55.560
<v Speaker 1>or Twitter, or as always called our fact hot Line

0:30:55.960 --> 0:30:59.240
<v Speaker 1>one eight four four pt genius. It's it's still seven

0:30:59.240 --> 0:31:02.000
<v Speaker 1>fact hot Line. I think it's still all right. So

0:31:02.120 --> 0:31:18.000
<v Speaker 1>call us there. Thanks so much for listening. Thanks again

0:31:18.040 --> 0:31:20.240
<v Speaker 1>for listening. Part Time Genius is a production of how

0:31:20.280 --> 0:31:23.120
<v Speaker 1>stuff works, and wouldn't be possible without several brilliant people

0:31:23.120 --> 0:31:26.040
<v Speaker 1>who do the important things we couldn't even begin to understand.

0:31:26.160 --> 0:31:28.960
<v Speaker 1>Tristan McNeil does the editing thing. Noel Brown made the

0:31:28.960 --> 0:31:31.640
<v Speaker 1>theme song and does the mixy mixy sound thing. Jerry

0:31:31.760 --> 0:31:34.680
<v Speaker 1>Rowland does the exact producer thing. Gay Bluesier is our

0:31:34.760 --> 0:31:38.080
<v Speaker 1>lead researcher, with support from the Research Army including Austin Thompson,

0:31:38.160 --> 0:31:40.640
<v Speaker 1>Nolan Brown and Lucas Adams and Eve Jeff Cook gets

0:31:40.640 --> 0:31:42.800
<v Speaker 1>the show to your ears. Good job, Eves. If you

0:31:42.880 --> 0:31:44.760
<v Speaker 1>like what you heard, we hope you'll subscribe, And if

0:31:44.760 --> 0:31:46.640
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0:31:46.720 --> 0:31:48.600
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0:31:48.600 --> 0:32:00.280
<v Speaker 1>forget Jason Jason who