Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin
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0:08 - 0:12OK, so it's time
to let your trousers down. -
0:12 - 0:15Let's face it, we all have
a couple of secrets, yeah? -
0:16 - 0:17Everyone has a secret,
-
0:17 - 0:22and I'd like to invite you to participate
in a simple experiment right now. -
0:22 - 0:24I'd like you to think one of your secrets.
-
0:24 - 0:28Just think it by conjuring up
the image in your mind. -
0:28 - 0:32We tend to think these secrets are secret;
nobody knows about them. -
0:32 - 0:34You would think because it's in your mind
-
0:34 - 0:37it doesn't mean
your neighbor sitting next you -
0:37 - 0:39can understand
or know about your secret. -
0:39 - 0:41That's why I want to challenge here.
-
0:41 - 0:45I want to ask you about
whether your privacy is real, -
0:45 - 0:47the way you feel it.
-
0:47 - 0:50Now your secret might
be something mundane. -
0:50 - 0:53It might be something simple such as,
for example, the PIN of your credit card. -
0:53 - 0:56It could be something embarrassing
you don't want people to know, -
0:56 - 1:01for example, it could be you enjoy
watching funny cat movies on the Internet, -
1:01 - 1:03something like that.
-
1:03 - 1:05So, is it possible
to read out these thoughts? -
1:07 - 1:12In fact, we can tell about the person's
mental state to some degree -
1:12 - 1:15about their feelings
from their body language, -
1:15 - 1:18from the expressions on their faces.
-
1:18 - 1:21If you look at these
famous Ekman faces here, -
1:21 - 1:25you can see that our facial expressions
give away what we feel, -
1:25 - 1:28but this is still severely limited.
-
1:28 - 1:32If you look at the person on the left,
obviously she is surprised. -
1:32 - 1:35But what is she surprised about?
What is she looking at? -
1:35 - 1:38What is she hearing?
What is surprising her? We don't know. -
1:38 - 1:41We can't tell this
from the surface of the body, -
1:41 - 1:45from the body language or from face;
we somehow need to go deeper. -
1:45 - 1:48And deeper here means
that we need to go into that part -
1:48 - 1:52of the body that encodes
and stores your thoughts, -
1:52 - 1:54and that is the human brain.
-
1:54 - 1:58Now, I am a brain scientist,
and for many years brain scientists -
1:58 - 2:01have established fact after fact
about the brain. -
2:01 - 2:02One thing that's always shown up
-
2:02 - 2:07is that our thoughts are intimately
related to the brain processes. -
2:07 - 2:11So, it should in theory be possible -
if I put someone in a brain scanner - -
2:11 - 2:13to find out what they are thinking.
-
2:13 - 2:18The question though is: How do I know
to interpret the language of the brain? -
2:18 - 2:22I somehow need to translate it
when I want to read it out. -
2:22 - 2:25I need some understanding
of the way information is stored. -
2:25 - 2:29So, a simple analogy can help us here.
-
2:29 - 2:31We could think of the way
in which information is stored -
2:31 - 2:34on the surface of a CD.
How does this work? -
2:34 - 2:39It's the pattern of pits on the surface
of a CD that codes a piece of information, -
2:39 - 2:41say, for example, about a piece of music:
-
2:41 - 2:44One piece of music,
one pattern of surface; -
2:44 - 2:48a different piece of music,
a different pattern of surface. -
2:48 - 2:51This is very similar to the way
your brain stores information. -
2:51 - 2:56It stores your thoughts
in spatial patterns of the brain activity. -
2:56 - 2:58So, how can we read these out?
-
2:58 - 3:01How do we know what the spatial patterns
of the brain activity are? -
3:01 - 3:04For this we use so-called brain scanners.
-
3:04 - 3:08It's a technology known as MRI,
Magnetic Resonance Imaging, -
3:08 - 3:11and basically involves
very strong magnetic fields. -
3:11 - 3:13It doesn't do you any harm,
-
3:13 - 3:17but it gives you a quite well resolved map
of your brain activity. -
3:17 - 3:18So, that's what we do.
-
3:18 - 3:22My job is people come to my lab,
at the Charité here in Berlin, -
3:22 - 3:24and we put people in brain scanners,
-
3:24 - 3:27we read out the brain activity patterns,
-
3:27 - 3:31and now we get something
that looks like this. -
3:31 - 3:33A brain image.
-
3:33 - 3:35Don't confuse these brain images
with photographs. -
3:35 - 3:37They are not photographs.
-
3:37 - 3:42They are not like accurate, perfect
depictions of some spatial events. -
3:42 - 3:46What they show is a spatial map
of probability -
3:46 - 3:50that tells you most likely
this part of the brain is involved -
3:50 - 3:52in some kinds of thought.
-
3:52 - 3:56You can see some regions
are hot colored, red or orange; -
3:56 - 3:59they are the regions that become
more active than usual -
3:59 - 4:00when you engage in a specific thought.
-
4:00 - 4:06The cold areas, blue areas are
where the activity is lower than normal. -
4:06 - 4:10But what does this specific pattern
of the brain activity mean? -
4:10 - 4:13Does anyone know what this person
is currently thinking about? -
4:13 - 4:14What do you think?
-
4:14 - 4:16It's difficult.
-
4:16 - 4:19It doesn't say on there
this person is thinking -
4:19 - 4:22about the Brandenburg Gate
or something like that. -
4:22 - 4:24It's not written in there.
-
4:24 - 4:27Instead it's an abstract code
that the brain uses. -
4:27 - 4:30This is something
that's quite familiar to us. -
4:30 - 4:31We know this.
-
4:31 - 4:34People faced this problem
over 200 years ago; -
4:34 - 4:37in fact, when they
encountered the hieroglyphs. -
4:37 - 4:39People 200 years ago
were puzzled by hieroglyphs; -
4:39 - 4:42they didn't know what hieroglyphs mean.
-
4:42 - 4:43They saw this on the pyramids.
-
4:43 - 4:46Some people must have said,
"That must be like a pretty wallpaper. -
4:46 - 4:50But instead, others might have said,
"I think it actually means something." -
4:50 - 4:52But what does it mean?
-
4:52 - 4:55What do you think this means?
It's a very similar problem. -
4:55 - 4:58What does this mean?
Like the brain image, you can't know. -
4:58 - 5:03I can tell you this one here means
the brain as you might have guessed. -
5:03 - 5:05But how do you know this?
-
5:05 - 5:09I don't have any ancient Egyptians
in my family. How do I know this? -
5:09 - 5:12It's because people
stumbled on the translation. -
5:12 - 5:17In 1799, someone found the translation,
the famous Rosetta Stone, -
5:17 - 5:20that you can see
in the British Museum in London. -
5:20 - 5:26This famous Rosetta Stone
contains a text in hieroglyphs -
5:26 - 5:29and a text in ancient Greek --
and Demotic as well, -
5:29 - 5:32that wasn't quite so much of interest.
-
5:32 - 5:36So this allowed us to translate
hieroglyphs into ancient Greek, -
5:36 - 5:39a language that people
did know to understand. -
5:39 - 5:42This now makes the task very simple.
-
5:42 - 5:46All we need to do is to find
the "Rosetta Stone" for the brain, right? -
5:46 - 5:47It sounds easy.
-
5:47 - 5:49Where is it? Where do we
have to go and dig? -
5:49 - 5:53Do we have to go and dig
in North Africa or Southeast Asia? -
5:53 - 5:55Where is the "Rosetta Stone"
for the brain going to be? -
5:55 - 6:00Nobody so far unfortunately has found
the "Rosetta Stone" for the brain. -
6:00 - 6:05The reason is it is very very complicated,
much more complicated than hieroglyphs. -
6:05 - 6:10We need to use something different,
something called codebreaking. -
6:10 - 6:16Now, in the Second World War, the Germans
thought they were particularly clever -
6:16 - 6:19by encrypting their messages
on this famous Enigma machine. -
6:19 - 6:22They took a military text,
they put it through the machine, -
6:22 - 6:26and out came some scrambled version
that nobody could understand. -
6:26 - 6:30Then in the U-boats they
would find a scrambled text, -
6:30 - 6:33and they put it through the machine,
out they'd get the real message. -
6:33 - 6:36This is what you can do
if you know the code. -
6:36 - 6:40The British were trying to decipher it,
but they didn't know the code. -
6:40 - 6:43It was said they invented
brute force, statistical techniques -
6:43 - 6:47that allowed them to translate
this hidden code, -
6:47 - 6:50and that's what we do today
with brain images. -
6:50 - 6:53We try to understand
what the thoughts are a person has. -
6:53 - 6:55How does this work in detail?
-
6:55 - 6:57l'll just give you a simple example.
-
6:57 - 7:00What you can see here
are three images on the left -
7:00 - 7:03the person was looking at
inside the brain scanner: -
7:03 - 7:06the Brandenburg Gate, a bouquet
of flowers and a German shepherd dog. -
7:06 - 7:10On the right are the corresponding
patterns of the brain activity. -
7:10 - 7:12As you can see they are very different.
-
7:12 - 7:17Every thought you have has its own
unique signature pattern of activity -
7:17 - 7:18in your brain.
-
7:18 - 7:21You think one thing,
you get one pattern of activity; -
7:21 - 7:24you think something else,
you get a different pattern of activity. -
7:24 - 7:26Now what we do is we train computers
-
7:26 - 7:29to recognize these patterns
of brain activity. -
7:29 - 7:32If I know to recognize
the pattern of activity in the top right, -
7:32 - 7:36I can tell that the person is thinking
about the Brandenburg Gate, -
7:36 - 7:40similar to recognizing an individual
based on their fingerprints. -
7:40 - 7:43If I find their fingerprints,
and I have them in a database, -
7:43 - 7:46I can use the software to detect
the fingerprints out of our database. -
7:46 - 7:47That's what we do.
-
7:47 - 7:50We train the computers;
we train them to recognize -
7:50 - 7:52these brain activity patterns,
-
7:52 - 7:55and then the computer has to prove
that it's worth the money, -
7:55 - 7:58or if the program we write
is worth its money, -
7:58 - 8:00that it can decipher
what you are thinking about, -
8:00 - 8:03and then you give the computer
some pattern of brain activity; -
8:03 - 8:05you might not know what it is,
-
8:05 - 8:10and the proof is if the computer can
correctly tell what you're thinking about. -
8:10 - 8:13This works remarkably well.
-
8:13 - 8:18If you do this simple game,
you get accuracy of up to 100%. -
8:18 - 8:20You get it right almost every time.
-
8:20 - 8:24So this is for people in brain scanners
looking at visual images. -
8:24 - 8:26But you could say,
-
8:26 - 8:28"If someone's in a brain scanner
looking at an image, -
8:28 - 8:31I just have to look at the image
they're looking at -
8:31 - 8:33and I'll know what
they're thinking about." -
8:33 - 8:35So, we need to go one step further.
-
8:35 - 8:38The next step is we just
have to imagine an image. -
8:38 - 8:42Put them in a brain scanner,
we get them to imagine various things, -
8:42 - 8:46for example, watches, hands,
faces, all sorts of stuff, -
8:46 - 8:49we measure the brain activity patterns,
and we can decode -
8:49 - 8:52what they're thinking about
based on pure imagination. -
8:52 - 8:55It's just in their mind,
there's nothing in their environment -
8:55 - 8:59or on the computer screen to give it away,
they're just thinking about it. -
8:59 - 9:02This works incredibly well, as well.
-
9:02 - 9:03But you could say,
-
9:03 - 9:08"This is still rather academic. Let's look
for something even more interesting. -
9:08 - 9:10What about people's behavior,
their decisions, -
9:10 - 9:11things that are relevant?"
-
9:11 - 9:14So we went ahead
and did a number of studies -
9:14 - 9:16where we tried to look
at people's decisions. -
9:16 - 9:18These are the decisions,
very simple decisions -
9:18 - 9:22among a few alternatives
for things either completely irrelevant, -
9:22 - 9:23such as, for example:
-
9:23 - 9:26"Do you want to press
left or right button?", -
9:26 - 9:28or things that are a bit
more relevant, for example: -
9:28 - 9:31"Do you like this car?
Do you want to buy it?", -
9:31 - 9:33or "Do you like this car?
Do you want to buy it?" -
9:33 - 9:37So we read the brain activity
out of their brains. -
9:37 - 9:40In the first case, we looked
after they've made up their mind. -
9:40 - 9:43So people make up their mind,
we read their brain activity, -
9:43 - 9:46we try to decipher
until which choice they've made. -
9:46 - 9:49So everyone of you make a choice,
-
9:49 - 9:53say, for example, between wanting
a BMW or a Mercedes. -
9:53 - 9:54You make your choice.
-
9:54 - 9:56Can we read this
out of your brain activity? -
9:56 - 10:00The answer is yes,
with pretty decent accuracy. -
10:00 - 10:05The next question is, however,
what about the choice itself? -
10:05 - 10:08You're more or less free to choose
between one or the other. -
10:08 - 10:11What made you go one or the other way?
-
10:11 - 10:15So we look backwards in time
before the decision. -
10:15 - 10:18And what we found was
that you could, to some degree, -
10:18 - 10:21predict a person's decision --
a free decision, -
10:21 - 10:23they can choose either alternative --
-
10:23 - 10:27before they actually feel
that they're making up their mind, -
10:27 - 10:31up to 7 seconds before they think
they're making up their mind. -
10:31 - 10:35So you think you're deciding now,
but your brain has at least started -
10:35 - 10:39preparing this decision 7 seconds before.
-
10:39 - 10:40How is that possible?
-
10:40 - 10:44Well, it raises an important riddle.
-
10:44 - 10:46That is, we normally think
-
10:46 - 10:48of the sequence of events
when we make choices, -
10:48 - 10:52we decide in our mind,
we don't tell anyone, we just decide, -
10:52 - 10:55and then we use our brain
to put our body into motion, -
10:55 - 10:58for example, to tell people
what we're thinking about. -
10:58 - 11:00But this says it's quite different.
-
11:00 - 11:04This says the brain
starts preparing the decision, -
11:04 - 11:07and then your mind comes
in a few seconds later, -
11:07 - 11:10and then you start moving
and doing things. -
11:10 - 11:15This is quite different, and it raises
lots of interesting questions. -
11:15 - 11:20The most important one is:
Who's responsible for the action? -
11:20 - 11:23If your conscious mind comes
after the decision, -
11:23 - 11:25that presumably has already been made,
-
11:25 - 11:28how can you be held responsible
for the action? -
11:28 - 11:31If you commit a crime,
it was my unconscious brain activity -
11:31 - 11:34that happened before I made up my mind,
-
11:34 - 11:37it's not my fault
that I committed this crime, -
11:37 - 11:38you could say.
-
11:38 - 11:42So you can see there are lots
of interesting questions raised here -
11:42 - 11:44with respect to free will.
-
11:44 - 11:47I'm going to leave that as an open teaser.
-
11:47 - 11:49I'm going to focus
on a different question. -
11:49 - 11:52If you're interested in that,
go to our website. -
11:52 - 11:54I'm going to ask
a different question, and that is: -
11:54 - 11:58Can we read people's minds
in a technology -
11:58 - 12:02that is similar now to these stage acts
that people did in the 19th century? -
12:02 - 12:05What you can see here
is a depiction of a stage act, -
12:05 - 12:08a magician draws a person
from the audience, -
12:08 - 12:11they come on the stage and are blindfolded
and think about something, -
12:11 - 12:14say, for example, a shape or a person,
-
12:14 - 12:16and the magician can
magically read their mind -
12:16 - 12:20and draw their thought on the board here.
-
12:20 - 12:23Can we now replace this stage act
with something new? -
12:23 - 12:25Can we put a brain scanner on the stage?
-
12:25 - 12:28And then the famous brain scanner,
you put people in it, -
12:28 - 12:31and it shows you on a board
what they're thinking about. -
12:31 - 12:33Is this possible?
-
12:33 - 12:37The answer is: to some degree,
but not that well. -
12:37 - 12:39I'll explain to you why.
-
12:39 - 12:43First of all, there's severe limitation
with the resolution of brain scanners. -
12:43 - 12:45They have a resolution
of a few millimeters, -
12:45 - 12:49so that means in every one of these
small measurement volumes we have, -
12:49 - 12:51we have up to a million nerve cells.
-
12:51 - 12:55That's a lot of nerve cells
in one measurement pixel. -
12:55 - 13:00So basically we need to increase
the resolution of these brain scanners, -
13:00 - 13:03so we can get down
to the activity of single cells, -
13:03 - 13:06if you really want
to read out the full details, -
13:06 - 13:09but there are even worse issues
in this than just the resolution. -
13:09 - 13:14One big problem is that everyone of you
has that own signature brain language -
13:14 - 13:16that stores information.
-
13:16 - 13:18You can see here 4 brain activity patterns
-
13:18 - 13:21for the same thought
in 4 different individuals. -
13:21 - 13:22They're all different.
-
13:22 - 13:25Everyone stores information differently,
-
13:25 - 13:29which explains why we have
such a hard time understanding each other, -
13:29 - 13:32if our brain activity patterns
are so different. -
13:32 - 13:34So this is a severe challenge.
-
13:34 - 13:36So we can't train our machine
on one person -
13:36 - 13:38and use it for another person.
-
13:38 - 13:42It doesn't work that well
on the second person. -
13:42 - 13:44Another problem is:
-
13:44 - 13:47The preferences and thoughts
change on the brain language -
13:47 - 13:50presumably changes
well across the lifespan. -
13:50 - 13:53When you're young
your favorite movie might be Lassie, -
13:53 - 13:56your favorite food might be a hamburger,
-
13:56 - 13:58and your favorite music
might have been heavy metal. -
13:58 - 14:03Come on, we're talking about secrets here.
That's your secret, my secret. -
14:03 - 14:08When you're older, things might change,
now you like schmaltzy Austrian movies, -
14:08 - 14:11you like salad or at least pretend
to yourself that you like salad -
14:11 - 14:13and Bavarian brass music.
-
14:13 - 14:15Come one, admit it.
-
14:15 - 14:18So the problem is
that the brain activity patterns -
14:18 - 14:22causing this kind of information
change across a lifespan, -
14:22 - 14:24and we got no way of dealing with this.
-
14:24 - 14:29But now the biggest problem is that we
can think so many different things. -
14:29 - 14:31One of my favorite sentences
is from Monty Python, -
14:31 - 14:34it's called, "My hovercraft
is full of eels." -
14:34 - 14:38Who would've ever thought that
someone was going to think this today? -
14:38 - 14:40If you're to program
the computer to predict -
14:40 - 14:42what you might be thinking about today,
-
14:42 - 14:44I'm pretty sure
"My hovercraft is full of eels" -
14:44 - 14:47would've been very low on that list.
-
14:47 - 14:51So we need to be able to account
for these situations as well. -
14:51 - 14:53We can think so many different things.
-
14:53 - 14:56We could take a whole dictionary
full of different things. -
14:56 - 14:59So, we need a dictionary to translate
thoughts into brain activity patterns, -
14:59 - 15:01and we don't have this dictionary.
-
15:01 - 15:04So, what could this look like?
-
15:04 - 15:06Do we get a subject to come,
we pay them very well, -
15:06 - 15:09they come for 20 years
to the brain scanner. -
15:09 - 15:11The first day we start
reading the dictionary. -
15:11 - 15:16We begin with apple, and we continue,
and after 20 years we've finally done, -
15:16 - 15:19but with zed, we'd start
reading zebra and etc. -
15:19 - 15:21Is that how we measure
the brain activity patterns -
15:21 - 15:24for all these thoughts they might have?
-
15:24 - 15:27Well, luckily we can take a shortcut.
-
15:27 - 15:31The shortcut is that the brain’s
arranged information in a way -
15:31 - 15:34that is easier for us to understand.
-
15:34 - 15:37And that is it uses
principles of similarity, -
15:37 - 15:40and I explain to you how this works.
-
15:40 - 15:43You can see in the top right
a hypothetical brain activity pattern -
15:43 - 15:47while the person is thinking about a car,
and the bottom right, -
15:47 - 15:51a hypothetical brain activity pattern
while they're thinking about a bike. -
15:51 - 15:54But now we've measured,
with a brain scanner, a different pattern. -
15:54 - 15:58It looks like a mixture for the pattern
of a car and the pattern of a bike. -
15:58 - 16:01What could that be?
What do you think? -
16:01 - 16:04Well, it's a motorbike.
-
16:04 - 16:07So you can exploit
these principles of similarity. -
16:07 - 16:11You don't need to know
what every thought looks like in the brain -
16:11 - 16:14and you can still read out
a large number of thoughts. -
16:14 - 16:18Now there are a number
of technical issues ensuing from this. -
16:18 - 16:22For example, potential lie detectors
or brain marketing, -
16:22 - 16:25lots of people are interested
in commercial applications -
16:25 - 16:27or forensic applications
of this technology, -
16:27 - 16:32and medical applications allowing people
who can't move their bodies -
16:32 - 16:35to suddenly move and control computers
and do things like that. -
16:35 - 16:37Now there's a big debate necessary
-
16:37 - 16:43about what of these technologies we want
and what we think is ethically feasible. -
16:43 - 16:46But one important question
people are always interested in is: -
16:46 - 16:50Does that mean now
you open to manipulation? -
16:50 - 16:54Well, don't worry about that too much
because first of all, it would mean -
16:54 - 16:57that you could have to put someone
inside a brain scanner. -
16:57 - 16:59So to some degree,
your thoughts are private. -
16:59 - 17:01If you're just walking through the world,
-
17:01 - 17:04nobody has a mobile brain scanner
that works remotely. -
17:04 - 17:06You can think about your PIN
of your credit card, -
17:06 - 17:10nobody is going to be able to read it out.
Don't worry about that. -
17:10 - 17:13Now, one thing that people
are still quite interested in -
17:13 - 17:18is whether you can be manipulated,
"manipulated" here means: -
17:18 - 17:21Is it possible to write thoughts
into a person's brain -
17:21 - 17:22to make them think certain things
-
17:22 - 17:25as you can see
in some science fiction movies -
17:25 - 17:27like in "Strange Days,"
or "Inception," and etc.? -
17:27 - 17:32The answer is today this is not possible.
-
17:32 - 17:36And the reason is that the way
our thoughts are coded in our brain -
17:36 - 17:40is in very intricate fine grain patterns
of brain activity, -
17:40 - 17:46there's really lots of detail
in these brain activity patterns. -
17:46 - 17:49Today, there are techniques
for stimulating the brain, -
17:49 - 17:52but they're very diffuse;
-
17:52 - 17:55there's no technique available
that would allow us to write -
17:55 - 17:59these very detailed patterns
of activity into the brain. -
17:59 - 18:04So, brain scanners can be used to read out
a person's thoughts to some degree. -
18:04 - 18:07Don't worry about the technology,
-
18:07 - 18:10and especially you don't have to worry
about people programming thoughts -
18:10 - 18:12into your brains.
-
18:12 - 18:13Thanks very much.
-
18:13 - 18:15(Applause)
- Title:
- Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin
- Description:
-
This talk was given at a local TEDx event, produced independently of the TED Conferences.
The research of John-Dylan Haynes focuses on the neural mechanisms underlying human cognitive processes. His special interests are technical and ethical foundations of mental state decoding, as well as the neuroscience of consciousness, intentions and free will. He talks about mind reading with brain scanners.
- Video Language:
- English
- Team:
closed TED
- Project:
- TEDxTalks
- Duration:
- 18:22
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Leonardo Silva edited English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin | |
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Leonardo Silva edited English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin | |
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Leonardo Silva approved English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin | |
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Leonardo Silva accepted English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin | |
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Leonardo Silva edited English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin | |
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Leonardo Silva edited English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin | |
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Leonardo Silva edited English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin | |
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Leonardo Silva declined English subtitles for Mind reading with brain scanners | John-Dylan Hayes | TEDxBerlin |