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  • We've said it before, and we'll say it againbrains are amazing.

  • And we've put some the best of them to work devising incredible machines that can beat

  • us at our own games, bring virtual worlds to life, perform quantum calculations, and

  • exponentially expand what we're capable of as a species.

  • But when we interact with those machines,

  • sometimes it still looks like this.

  • But imagine: it's date night, and you project

  • a silent command across the room to turn on some mood music.

  • Or, imagine you're a paralyzed genius, but you can communicate effortlessly through a

  • computer.

  • Imagine you can write volumes, without ever learning to type.

  • How close are we to controlling machines with

  • our minds?

  • It's been said that humans have something

  • of a communicationbandwidth problem.”

  • You're always seeing things, you're smelling

  • things, you're feeling things, you're hearing things, and all of that's a lot of information

  • that you're collecting in real time.

  • We call that a high-bandwidth, and by bandwidth we just mean the rate of information that

  • can flow over a particular time scale.

  • The information coming into you is Niagara Falls.

  • The information coming out of you is like a drop from a dropper.

  • If you think about how you generate your interactions with the machine, your brain is capable of

  • so much more.

  • A more direct connection between brain and machine could be the key to unlocking that

  • potential.

  • And this idea goes by many names, because it's a vast and complex field.

  • So you can think of brain-computer interfaces as being used for rehabilitative purposes,

  • for assessment purposes, and for enhancement purposes.

  • Thought-controlled wheelchairs or prosthetic limbs, or communication solutions for patients

  • with ALS or Locked-In Syndrome are just a few examples of how this tech can help with

  • rehabilitation.

  • But, the field of neural interfaces is just being born.

  • And what we have so far can be sorted into invasive and non-invasive approaches.

  • One example of an invasive BCI is called Deep Brain Stimulation, or DBS for short.

  • These are tiny implanted electrodes which can both send signals and record signals from

  • deep within the brain.

  • There's also what's called electrocorticography, and those can read signals from the surface

  • of the brain.

  • This is pretty effective, but still requires cracking open the skull.

  • And unless you suffer debilitating seizures, you might not be up for that.

  • I think it's sort of the holy grail of this emerging field to be able to get to all of

  • the information we could get if we drilled into your brain, without drilling into your

  • brain.

  • The challenge is, non-invasive brain imaging is super noisy, and only captures signals

  • from outside the skull.

  • That's like trying to listen to an epic symphony through a brick wall.

  • Dr. Thomas Reardon and his team have an idea

  • about how to overcome this problem.

  • It starts with re-thinking what the brain actually is –– and it's more than just

  • the cortex.

  • It's also the primitive part of the brain,

  • the reptilian part of the brain, the basal ganglia, and all the way through the brain

  • stem.

  • And most importantly, the spinal cord, that long, thin extension of the brain that connects

  • the forebrain out to the rest of the body.

  • But you've got neurons all the way down into the spinal cord, and they work collaboratively,

  • in this unbelievable symphony of neural music, to get your body to do stuff.

  • And when you form an intention to 'do stuff,' your motor neuron cells –– the largest

  • cells in your body –– start to transmit that signal from your brain to your muscles.

  • When it releases neurotransmitter, the muscle responds with a little electrical spark.

  • And that causes the muscle to contract.

  • That's the evolved natural output place.

  • We don't have to hack into it, your brain evolved to output it.

  • And that's the signal that we record.

  • Turns out, recording that signal is actually

  • pretty easy, using a technique called differential surface EMG, which these neuroscientists and

  • engineers have funneled into a nifty wristband.

  • The bigger challenge is decoding what the signal means to you.

  • The way those neurons go into your muscle, what we'll call the motor map, is totally

  • different than me.

  • In fact, it's so different, it's different than your twin.

  • We have a bunch of deep algorithmic work we've done to take that electrical signal and map

  • that to the chatter of the neurons in your spine.

  • It sits here, right above your wrist, which happens to be the most densely-innervated

  • part of your whole body.

  • And what it's going to start doing is streaming neural signals to a computer, maybe my phone,

  • which is going to digest those and turn that into a control signal.

  • So rather than the signal being, "hey, move my hand," it becomes, "hey, move that cursor."

  • Your typical computer mouse requires you to

  • coordinate fourteen muscles with up to 20,000 neurons.

  • This device just learns to listen to you, down to the level of a single neuron.

  • And from there, the options are limitless.

  • So, obviously our producer, Annawanted

  • to try this thing out.

  • - So we can look at your raw EMG, which is also kind of cool.

  • - Cool.

  • - So the band has 16 channels here.

  • So if you just rest, if you just drop your hand here on the table, your brain is sending

  • no signals to move your hand because you're resting.

  • If you just slowly bring your wrist up like

  • that, you can see the pattern is that there's some movement there, and you just slowly extend

  • your wrist even more, and then max it out.

  • You can see that now we're getting a lot more signal, and so we're activating thousands

  • of motor units.

  • - Wow.

  • This is what's called the recruitment curve.

  • And this program is learning what Anna's looks like as she tries to accomplish a specific

  • task –– in this case, tracing a ball around a circle.

  • You actually spent the first year of your life doing all this stuff.

  • We call it motor babbling.

  • Your brain was trying to figure out your body

  • "If i send this command, oh, I got it, that's the fingers, got it."

  • What we're trying to do is compress that down into an hour, or minutes.

  • To then do new things you'd never be able to do with just your body.

  • Mapping your hand to a virtual hand or a cursor is just the beginning.

  • With enough Jedi training, you could eventually play Fortnite with your mind.

  • - All the control schemes that basically humanity has ever created rely on physical movement.

  • Even voice controls rely on the movement of my vocal chords.

  • But here, because we can recognize an individual motor unit that's not sufficient to create

  • physical movement, but is sufficient to act as a digital button, we can control a digital

  • environment.

  • You can just play the game.

  • This is just one approach to blurring the

  • line between brain and machine.

  • The military is very interested.

  • Some of their ideas are improving the function of soldiers, allowing them to communicate

  • silently across the battlefield, for example.

  • Other applications, like hacking into a soldier's capacity for empathy, or attempting to decode

  • private thoughts, present major ethical questions.

  • So you can imagine these devices in various ways will change different elements of you,

  • and some will be more core to who you are.

  • Careful thought and regulation will be essential in ensuring our safety as we merge mind with

  • machine.

  • But one thing's for sure: that future is coming.

  • So, how close are we to controlling machines with our minds?

  • I can imagine that in a decade from now we have brain-computer interfaces that can help

  • us do really simple tasks in the world, like turning the lights on and off, or changing

  • the channel on the television.

  • Right now, the technology is absolutely appropriate

  • for people to start developing new things with.

  • Whether it's how to control a surgical robot while your hands are doing other things, or

  • you're an astronaut and you need to do high-complexity things on the space stationit's time to

  • move past the old models, and really open up new human experiences.

  • For more episodes ofHow Close Are We?”, check out this one here.

  • Don't forget to subscribe, and come back to Seeker for more episodes.

  • Thanks for watching.

We've said it before, and we'll say it againbrains are amazing.

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私たちの頭で機械を制御するには、どのくらいの距離があるのでしょうか? (How Close Are We to Controlling Machines With Our Minds?)

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    林宜悉 に公開 2021 年 01 月 14 日
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