Name: How Close Are We to Controlling Machines With Our Minds?
Uploaded: 2020-04-04T06:12:22.000Z
Duration: 9 min 7 s
Description: Thousands of YouTube videos with English-Chinese subtitles! Now you can learn to understand native speakers, expand your vocabulary, and improve your pronunciation...

We've said it before, and we'll say it again – brains 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,

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

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

How close are we to controlling machines with

It's been said that humans have something

of a communication “bandwidth 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

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

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

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

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

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

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

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

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

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

Dr. Thomas Reardon and his team have an idea

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

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

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.

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

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

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

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, Anna,  wanted

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

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

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.

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How Close Are We to Controlling Machines With Our Minds?

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