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Let me tell you a story about a man called Dante Autullo. | 0:00:02 | 0:00:04 | |
He lives in Illinois, he's 34 years old, | 0:00:04 | 0:00:06 | |
and a couple of years ago, he was doing some DIY around the house with a nail gun, as you do, | 0:00:06 | 0:00:10 | |
he fired a nail into his own brain. | 0:00:10 | 0:00:12 | |
But he never realised, because the brain has no pain receptors. | 0:00:12 | 0:00:15 | |
He had a nosebleed and the following day he felt a bit nauseous, | 0:00:15 | 0:00:19 | |
and his girlfriend said, "You should get that checked out." | 0:00:19 | 0:00:22 | |
So he went to a doctor and they showed him the X-ray, and he simply didn't believe them. | 0:00:22 | 0:00:25 | |
We know this because he found time to post the X-rays to Facebook | 0:00:25 | 0:00:30 | |
in the ambulance on the way to the hospital. | 0:00:30 | 0:00:32 | |
Ah, the brain! The most mysterious object in the universe, | 0:00:32 | 0:00:35 | |
but it can still make you behave like a bit of an idiot. | 0:00:35 | 0:00:39 | |
I'm Dara O'Briain, welcome to Science Club. | 0:00:39 | 0:00:42 | |
APPLAUSE | 0:01:01 | 0:01:03 | |
So, welcome to our show, which takes one major topic each week | 0:01:05 | 0:01:08 | |
and looks at it from every angle to see what we can learn. | 0:01:08 | 0:01:11 | |
As ever, we have our curious audience and illustrious guests - | 0:01:11 | 0:01:14 | |
this week, neuroscientist and developmental psychologist Uta Frith. Welcome. | 0:01:14 | 0:01:18 | |
Our regular reporters, Alok Jha, Helen Czerski and Tali Sharot. | 0:01:18 | 0:01:22 | |
-Our very special guest - Jessica Hynes. Jessica, how are you? -Very well. -Good stuff. | 0:01:22 | 0:01:25 | |
And Mark Miodownik, as ever, our materials scientist, ready to do some messing around over here. | 0:01:25 | 0:01:30 | |
Now, on the show tonight, we're looking at the human brain, | 0:01:30 | 0:01:33 | |
peering into the mass of grey and white matter | 0:01:33 | 0:01:35 | |
to find out the latest thinking about...thinking. | 0:01:35 | 0:01:37 | |
Through the media of filmed reports and experiments, | 0:01:37 | 0:01:40 | |
we'll endeavour to understand where we're at with this most complex but fundamental organ. | 0:01:40 | 0:01:45 | |
Dr Helen Czerski travels to the US to discover amazing, cutting-edge brain research. | 0:01:47 | 0:01:52 | |
-And so, do you feel that you're one step closer to being able to mind-read? -Yes. | 0:01:52 | 0:01:58 | |
Reporter Alok Jha finds out about smart drugs | 0:01:58 | 0:02:01 | |
which seem to maximise our cleverness, and asks whether we should all be taking them. | 0:02:01 | 0:02:06 | |
I'm really tempted to try one. | 0:02:06 | 0:02:08 | |
And 2012 actor Jessica Hynes undergoes memory testing | 0:02:08 | 0:02:12 | |
and literally sees what's going on in her head. | 0:02:12 | 0:02:15 | |
I'm looking forward to having a picture of my brain! | 0:02:15 | 0:02:18 | |
And later, Prof Mark Miodownik will be putting a brain in a blender. | 0:02:18 | 0:02:22 | |
All in the name of science, of course. | 0:02:22 | 0:02:24 | |
If you want to get involved with the show or follow us on Twitter, | 0:02:24 | 0:02:27 | |
the details are on your screen. | 0:02:27 | 0:02:30 | |
Very good, OK. | 0:02:32 | 0:02:34 | |
But first, let's meet our science guru, | 0:02:34 | 0:02:37 | |
neuroscientist and developmental psychologist, a Fellow of the Royal Society, | 0:02:37 | 0:02:42 | |
Emeritus Professor of Cognitive Psychology at UCL, | 0:02:42 | 0:02:45 | |
please welcome Uta Frith! | 0:02:45 | 0:02:48 | |
CHEERING AND APPLAUSE | 0:02:48 | 0:02:50 | |
-How are you? -Hello. -Nice to have you here. Welcome. | 0:02:52 | 0:02:56 | |
Uta, over the course of your long and distinguished career, | 0:03:00 | 0:03:03 | |
you've changed the direction of the stuff that you've been doing | 0:03:03 | 0:03:07 | |
because what we know about the brain has changed, | 0:03:07 | 0:03:10 | |
and the technology with which we learn about the brain has changed. | 0:03:10 | 0:03:13 | |
-almost unrecognisably, since you started. -You're absolutely right. | 0:03:13 | 0:03:16 | |
When I started being interested in psychology, | 0:03:16 | 0:03:19 | |
and also in how the brain creates the mind, | 0:03:19 | 0:03:22 | |
all we had at the time was really looking at | 0:03:22 | 0:03:26 | |
people who had some kind of brain damage. | 0:03:26 | 0:03:28 | |
Eventually, sort of from the 1990s, | 0:03:28 | 0:03:32 | |
we were able to see the living, thinking, feeling brain. | 0:03:32 | 0:03:38 | |
-So it all came about because of the invention of MRI scans? -Absolutely. | 0:03:38 | 0:03:42 | |
-A fabulous invention. -So, the amount of information you had, because... | 0:03:42 | 0:03:46 | |
Listen, I've seen these textbooks about Phineas Gage, | 0:03:46 | 0:03:49 | |
the man who fell onto a spike and it went through his brain, | 0:03:49 | 0:03:53 | |
was the proof that personality is contained in the brain. | 0:03:53 | 0:03:57 | |
That was important information that we had. | 0:03:57 | 0:04:00 | |
But it was abnormal situations like that were how we knew what happened in the brain. | 0:04:00 | 0:04:04 | |
Exactly. And we are waiting for more technological breakthroughs so that we can see even better. | 0:04:04 | 0:04:10 | |
More exact in what we see. OK, we're going to talk about many of the topics it raised here, | 0:04:10 | 0:04:15 | |
but it's worth taking that historical overview. | 0:04:15 | 0:04:17 | |
For many years, finding out about the brain just involved looking at, | 0:04:17 | 0:04:20 | |
measuring it, trying to make assumptions on that basis, | 0:04:20 | 0:04:23 | |
but since the advent of MRI scanners, we started to understand its innermost secrets. | 0:04:23 | 0:04:28 | |
This is what we used to think. | 0:04:28 | 0:04:30 | |
A long time ago, when the Greeks had money and dressed in sheets, | 0:04:35 | 0:04:38 | |
it was thought that thinking came from a kind of internal self, | 0:04:38 | 0:04:42 | |
what the Romans later called the homunculus, the little man. | 0:04:42 | 0:04:46 | |
No-one suspected that thinking happened in the brain. | 0:04:46 | 0:04:50 | |
It was just so dull. | 0:04:50 | 0:04:52 | |
Instead, it was the more exciting internal organs, like the heart, | 0:04:52 | 0:04:56 | |
the liver and the spleen that were marked out | 0:04:56 | 0:04:59 | |
as the essential parts of thought, reason and emotion. | 0:04:59 | 0:05:03 | |
Complete nonsense, of course, but progress was slow, | 0:05:03 | 0:05:06 | |
because for a long time, dissection was banned by the Church. | 0:05:06 | 0:05:10 | |
Eventually, however, it was noticed that the eyes are connected to | 0:05:10 | 0:05:13 | |
the dull, wobbly parts inside our heads, and that, in turn, | 0:05:13 | 0:05:17 | |
it was connected to the rest of the body | 0:05:17 | 0:05:19 | |
by a stringy network of wiry structures - the nervous system. | 0:05:19 | 0:05:23 | |
By the 18th century, | 0:05:23 | 0:05:25 | |
an Italian called Luigi Galvani | 0:05:25 | 0:05:27 | |
had discovered that the wiry bits carried electricity, | 0:05:27 | 0:05:30 | |
which operated muscles. | 0:05:30 | 0:05:32 | |
This he endlessly demonstrated by attaching frogs' legs to a battery. | 0:05:32 | 0:05:37 | |
It was now clear that the brain actually has an important job to do, | 0:05:37 | 0:05:40 | |
controlling the body with electricity. | 0:05:40 | 0:05:44 | |
Gradually, physicians started paying more attention to the brain. | 0:05:44 | 0:05:48 | |
They noticed that injuries to specific parts of it | 0:05:48 | 0:05:51 | |
would affect specific abilities. | 0:05:51 | 0:05:53 | |
Injuries changed the ability to smell, hear or speak. | 0:05:53 | 0:05:58 | |
Accidents revealed a lot about how the brain worked, | 0:05:58 | 0:06:02 | |
but well-meaning surgeons showed even more. | 0:06:02 | 0:06:05 | |
A severely epileptic American was treated by such a surgeon, | 0:06:06 | 0:06:10 | |
who scooped out the part of his brain called the hippocampus. | 0:06:10 | 0:06:14 | |
The fits stopped, | 0:06:14 | 0:06:15 | |
but so did patient's ability to form new memories. | 0:06:15 | 0:06:19 | |
The brain, it turned out, is responsible for memory. | 0:06:19 | 0:06:22 | |
All of a sudden, scientists were all over the brain, probing it, | 0:06:23 | 0:06:27 | |
recording electrical activity. | 0:06:27 | 0:06:30 | |
One of them, Wilder Penfield, made a map of the brain | 0:06:30 | 0:06:33 | |
by poking about in the brains of conscious patients. | 0:06:33 | 0:06:36 | |
He produced the sensory homunculus, | 0:06:36 | 0:06:39 | |
an image of how the brain senses the body. It was also discovered that our brain | 0:06:39 | 0:06:43 | |
is responsible for us being conscious, or unconscious, | 0:06:43 | 0:06:46 | |
and that it's responsible for us being aware of being conscious, | 0:06:46 | 0:06:50 | |
our consciousness. It was also found that the way the brain works | 0:06:50 | 0:06:55 | |
can be altered using drugs, | 0:06:55 | 0:06:56 | |
and that there's another part of our brain that's running the show - | 0:06:56 | 0:07:00 | |
our subconscious - | 0:07:00 | 0:07:01 | |
and that means that our brain knows what we're going to do before we do. | 0:07:01 | 0:07:06 | |
It's almost as though | 0:07:06 | 0:07:08 | |
we're being controlled by another version of ourselves. | 0:07:08 | 0:07:11 | |
Traditionally, the brain is compared to | 0:07:12 | 0:07:15 | |
the most impressive technology available. | 0:07:15 | 0:07:18 | |
In the past, it would have been a kind of complicated steam engine, | 0:07:18 | 0:07:22 | |
an electronic telephone exchange, and a microprocessor. | 0:07:22 | 0:07:25 | |
Today, the brain is presented as being a bit like the internet. | 0:07:25 | 0:07:29 | |
Tomorrow, who knows? | 0:07:29 | 0:07:31 | |
The fact is, no-one actually knows exactly how the brain works, | 0:07:31 | 0:07:35 | |
but at least we now know where to look. | 0:07:35 | 0:07:38 | |
So, in many ways, we've just stepped onto the moon, | 0:07:43 | 0:07:48 | |
we've just started that journey, essentially, | 0:07:48 | 0:07:50 | |
when it comes to finding out what's happening in the brain. | 0:07:50 | 0:07:53 | |
Explain to me the way it's different from other organs. I'm intrigued by this. | 0:07:53 | 0:07:57 | |
The lungs, for example, | 0:07:57 | 0:07:59 | |
it's like a series of corridors that lead to smaller and smaller corridors, | 0:07:59 | 0:08:03 | |
that lead to rooms that perform a discrete job. | 0:08:03 | 0:08:05 | |
The heart has its valves. | 0:08:05 | 0:08:07 | |
The brain seems more like a continuum, like a large hall. | 0:08:07 | 0:08:11 | |
-Like an orchestra. -Is that how it is? | 0:08:11 | 0:08:13 | |
And all of these parts of the brain can adopt functions | 0:08:13 | 0:08:18 | |
-from other parts of the brain? -To some extent. | 0:08:18 | 0:08:20 | |
I think we don't know quite the limits of how they could do absolutely everything. | 0:08:20 | 0:08:24 | |
I think there are some that are very much more specialised than others. | 0:08:24 | 0:08:28 | |
The main job of the brain is, really, to keep us upright, | 0:08:28 | 0:08:33 | |
keep us from falling over, | 0:08:33 | 0:08:35 | |
maintain our breathing, | 0:08:35 | 0:08:39 | |
all sorts of things that we are not at all aware of, | 0:08:39 | 0:08:42 | |
but they are very heavy-duty tasks, jobs, | 0:08:42 | 0:08:45 | |
that you need a brain for. | 0:08:45 | 0:08:48 | |
-In fact, perhaps we should look at the brain. -We have brains here. | 0:08:48 | 0:08:52 | |
-It is so tempting. -I love the way we have essentially put it on a cake stand. | 0:08:52 | 0:08:56 | |
I know! It is absolutely amazing. | 0:08:56 | 0:08:59 | |
I really love holding it, because it is the weight of a... | 0:08:59 | 0:09:04 | |
That, by the way, is not, I presume, a brain. | 0:09:04 | 0:09:07 | |
That's a new type of surgical training device. | 0:09:07 | 0:09:10 | |
Yes, and it feels nice and cool and sort of jellylike, | 0:09:10 | 0:09:15 | |
and that's always how I imagine the brain to be, | 0:09:15 | 0:09:18 | |
except, it is nearly always liquid when you really see it, | 0:09:18 | 0:09:20 | |
and you have to do something to it to make it fixated. | 0:09:20 | 0:09:24 | |
-So the grey mass that we see is something that we have treated? -Yes, it has to be treated, | 0:09:24 | 0:09:29 | |
otherwise it will just sort of liquefy very soon. | 0:09:29 | 0:09:32 | |
But it's a really, really beautiful structure. It's really amazing. | 0:09:32 | 0:09:36 | |
This is, of course, underneath here, is the cerebellum, | 0:09:36 | 0:09:39 | |
which is often hidden from view, | 0:09:39 | 0:09:44 | |
and yet, it's probably a structure of the brain | 0:09:44 | 0:09:47 | |
that's just...active and used in almost everything we do. | 0:09:47 | 0:09:52 | |
Absolutely everything. | 0:09:52 | 0:09:54 | |
It used to be thought it was especially to do with movement, | 0:09:54 | 0:09:57 | |
movement control, but, in fact, | 0:09:57 | 0:09:59 | |
it turns out to be kind of the brain's computer. | 0:09:59 | 0:10:01 | |
The cerebellum is very, very important, and we share this cerebellum. | 0:10:01 | 0:10:05 | |
It's the same structure in other animals. | 0:10:05 | 0:10:07 | |
Now, we're going to keep coming back to that for reference. | 0:10:07 | 0:10:12 | |
Yeah, you're right. It is very pleasant. | 0:10:12 | 0:10:15 | |
I'm getting the calming effect of touching it. | 0:10:15 | 0:10:18 | |
We were saying about how the brain has evolved to do with the environment that we are in, | 0:10:18 | 0:10:22 | |
and at different stages, we have, to a certain extent, | 0:10:22 | 0:10:25 | |
passed on duties to technology that we previously had the brain doing. | 0:10:25 | 0:10:29 | |
We invented writing and printing, and that stops us having to memorise tracts... | 0:10:29 | 0:10:33 | |
That's a perfect example of incredible niche construction, | 0:10:33 | 0:10:38 | |
of this sort of cleverness... | 0:10:38 | 0:10:41 | |
-of the brain, that we can outsource... -We can outsource certain parts of it. | 0:10:41 | 0:10:45 | |
-The obvious example now is mobile telephones, smart computers. -Yes. | 0:10:45 | 0:10:49 | |
To a certain extent, we've freed up other skills because of this. | 0:10:49 | 0:10:53 | |
The example that someone has given us, 20 years ago, | 0:10:53 | 0:10:57 | |
we would all have known the telephone number of our partner's workplace... | 0:10:57 | 0:11:00 | |
-Now we just... One click. -We know it's kept for us... | 0:11:00 | 0:11:05 | |
It's all rubbish that we don't need to bother... | 0:11:05 | 0:11:07 | |
-So we basically passed a job on to technology at different stages. -Yes. | 0:11:07 | 0:11:12 | |
19 million of us own these smartphones, by the way, | 0:11:12 | 0:11:15 | |
but how many of us actually know how they work? | 0:11:15 | 0:11:17 | |
We'll be back to this fabulous beauty in a second. | 0:11:17 | 0:11:19 | |
LAUGHTER | 0:11:19 | 0:11:21 | |
Just in terms of the way we pass these things on, | 0:11:21 | 0:11:24 | |
Mark Miodownik has been taking a smartphone apart. | 0:11:24 | 0:11:27 | |
The invention of the telephone changed the way we're connected to each other, | 0:11:29 | 0:11:34 | |
but it was a physical connection, and so engineers dreamed | 0:11:34 | 0:11:37 | |
of severing that connection, | 0:11:37 | 0:11:39 | |
of creating a phone you could use anywhere, any place, | 0:11:39 | 0:11:43 | |
and the realisation of that dream was this, the mobile phone. | 0:11:43 | 0:11:47 | |
Since it came on the scene some 30 years ago, | 0:11:47 | 0:11:50 | |
it's transformed the way we communicate. | 0:11:50 | 0:11:52 | |
But now it's become so much more | 0:11:52 | 0:11:55 | |
than merely a way to connect to each other. | 0:11:55 | 0:11:58 | |
It's changed the way we entertain ourselves, | 0:11:58 | 0:12:00 | |
the way we read and write, and even how we get up in the morning, | 0:12:00 | 0:12:04 | |
and all in something the size of a cassette tape. | 0:12:04 | 0:12:07 | |
And now there's evidence that it's even affecting the way we use our brains. | 0:12:08 | 0:12:13 | |
The smartphone - you're very likely to have one of these in your pocket. | 0:12:13 | 0:12:17 | |
You may even be watching this on it. | 0:12:17 | 0:12:19 | |
But how does something so small do so much? | 0:12:19 | 0:12:22 | |
Smartphones are masters of miniaturisation, | 0:12:24 | 0:12:28 | |
apart from the battery, which still takes up most of the room. | 0:12:28 | 0:12:31 | |
But packed around it are microphones, speakers, a processor, | 0:12:31 | 0:12:35 | |
a SIM card, and let's not forget the antenna, | 0:12:35 | 0:12:37 | |
which makes it all mobile. | 0:12:37 | 0:12:39 | |
Of course none of this would matter if you couldn't tell when your phone rings, | 0:12:39 | 0:12:43 | |
and it does that using the main speaker, | 0:12:43 | 0:12:46 | |
or by this nifty little gadget. Let me show you. | 0:12:46 | 0:12:50 | |
LOUD BUZZING | 0:12:50 | 0:12:52 | |
Of course, that means you can have your phone on silent. | 0:12:54 | 0:12:57 | |
Because they're so good at connecting us, | 0:12:57 | 0:12:59 | |
smartphones are well on their way to becoming | 0:12:59 | 0:13:01 | |
the fastest-spreading technology in human history. | 0:13:01 | 0:13:04 | |
But, of course, they have one extra thing that makes them truly smart - a logic board. | 0:13:04 | 0:13:09 | |
The heart and soul of the phone. | 0:13:09 | 0:13:12 | |
Because there's a processor to control the digital signals, | 0:13:12 | 0:13:15 | |
that effectively turns the mobile phone into a mini computer, | 0:13:15 | 0:13:18 | |
and once you have a mini computer in your hand, well, | 0:13:18 | 0:13:21 | |
all sorts of things can become possible. | 0:13:21 | 0:13:23 | |
It becomes a music player, a video player and, crucially, | 0:13:23 | 0:13:26 | |
a portal to the internet. | 0:13:26 | 0:13:28 | |
This constant access to information means we're relying less and less on our brains, | 0:13:28 | 0:13:32 | |
and it appears that we're actually outsourcing our memory. | 0:13:32 | 0:13:35 | |
And then all you need is some way to control it. | 0:13:35 | 0:13:38 | |
There's no doubt that the defining feature of the smartphone is the screen. | 0:13:38 | 0:13:43 | |
There's an awful lot packed into just a few millimetres - | 0:13:43 | 0:13:47 | |
light-emitting diodes, transparent electrodes | 0:13:47 | 0:13:49 | |
and liquid crystals that rearrange themselves to control the light - | 0:13:49 | 0:13:54 | |
but the thing that never fails to amaze me is how it responds to your finger. | 0:13:54 | 0:13:58 | |
The touch screen works by monitoring the electric field on its surface, | 0:13:58 | 0:14:01 | |
and this is disrupted by an electrical conductor, | 0:14:01 | 0:14:05 | |
but not ANY electric electrical conductor will work. | 0:14:05 | 0:14:08 | |
It's trained to recognise the characteristic signature of a human finger. | 0:14:08 | 0:14:13 | |
Error-correcting algorithms ignore anything with a different electrical signal. | 0:14:13 | 0:14:17 | |
But it's the addition of the camera that really brings the screen to life. | 0:14:17 | 0:14:22 | |
Of course, this is not just for taking photos. | 0:14:22 | 0:14:25 | |
It's one of a growing number of sensors that mobile phones are requiring. | 0:14:25 | 0:14:29 | |
As you can see, the phone knows which way is up. That means it knows which way gravity is. | 0:14:32 | 0:14:37 | |
It also knows how fast it's turning. | 0:14:37 | 0:14:39 | |
And that's really quite remarkable, and it's down to two sensors - | 0:14:39 | 0:14:43 | |
a gyroscope and an accelerometer. | 0:14:43 | 0:14:47 | |
They may look just like blobs of plastic, | 0:14:47 | 0:14:50 | |
but inside, they're microelectronic machines with moving parts smaller than the hair on a flea. | 0:14:50 | 0:14:56 | |
These intricate components vibrate and move, | 0:14:56 | 0:14:59 | |
and so can sense motion and the force of gravity, | 0:14:59 | 0:15:03 | |
making the phone, in a sense, aware of itself. | 0:15:03 | 0:15:06 | |
This is mechanical engineering on a phenomenally small scale. | 0:15:08 | 0:15:12 | |
Mobile phones have embedded themselves into every aspect of our lives. | 0:15:12 | 0:15:16 | |
They wake us up in the morning, they tell us where we need to go and how to get there. | 0:15:16 | 0:15:20 | |
They allow us to communicate globally. | 0:15:20 | 0:15:22 | |
They become an intimate expression of who we are. | 0:15:22 | 0:15:25 | |
PHONE RINGS | 0:15:25 | 0:15:27 | |
Yeah, hey! How's it going? | 0:15:29 | 0:15:30 | |
Tell me, firstly, Mark, I think you've voided your warranty | 0:15:36 | 0:15:42 | |
by opening it up. Don't go back to the shop with that one. | 0:15:42 | 0:15:45 | |
We pass on certain duties, certain memory tasks, to it. | 0:15:45 | 0:15:48 | |
Do we fill the space in our brains with something else, then? | 0:15:48 | 0:15:51 | |
I think the brain is very busy all the time. | 0:15:51 | 0:15:54 | |
I don't think we even notice that we don't have to remember these numbers any more. | 0:15:54 | 0:15:58 | |
But we have to remember that there have been technological innovations | 0:15:58 | 0:16:01 | |
all the time, and every time, for example, | 0:16:01 | 0:16:04 | |
when printing came in, there was a huge worry about what that might do to people, | 0:16:04 | 0:16:09 | |
and what, in fact, print might do to memory. | 0:16:09 | 0:16:12 | |
It would atrophy, that was the prediction. | 0:16:12 | 0:16:15 | |
And you could say again, we don't even remember phone numbers any more. | 0:16:15 | 0:16:19 | |
The important thing about memory is that it we know how to get at it, | 0:16:19 | 0:16:22 | |
and that's what these phones and these things like Google are so useful for, | 0:16:22 | 0:16:27 | |
because we can... we know where to look up things, | 0:16:27 | 0:16:31 | |
and that, of course, needs a lot of learning and a lot of practice. | 0:16:31 | 0:16:35 | |
So, now it's a different skill. As an academic, are you finding that | 0:16:35 | 0:16:38 | |
students have different skills now to what we expected? | 0:16:38 | 0:16:41 | |
I think the mobile phone, the internet, | 0:16:41 | 0:16:43 | |
these are things that are going to make us much more rich, intellectually. | 0:16:43 | 0:16:47 | |
-I think it's unarguable, really, and I think they should be welcomed. -OK. | 0:16:47 | 0:16:51 | |
Now, a huge chunk of our brain is taken up with movement. | 0:16:51 | 0:16:54 | |
In fact, massive parts of the brain, | 0:16:54 | 0:16:56 | |
not just in getting the legs moving, modelling the space around us | 0:16:56 | 0:16:59 | |
and making sure we don't fall, and co-ordinating us. | 0:16:59 | 0:17:02 | |
If you're ever wondering about that, next time you're walking, | 0:17:02 | 0:17:05 | |
in the middle of it go, "Where is my left leg going?" | 0:17:05 | 0:17:08 | |
Don't do that on the stairs. You will actually fall. That's bad advice to give. | 0:17:08 | 0:17:11 | |
But there is interesting science around the information coming to our brains from different senses? | 0:17:11 | 0:17:16 | |
Exactly. We thought we'd do an experiment to sort of test that out. | 0:17:16 | 0:17:20 | |
-I've got a hand here. It's an artificial rubber hand. -A mannequin's hand. | 0:17:20 | 0:17:25 | |
There's no way you'd think that's your own hand. | 0:17:25 | 0:17:29 | |
-Of course not. -But maybe there is. | 0:17:29 | 0:17:30 | |
Maybe we could actually fool the brain into thinking that is your own hand | 0:17:30 | 0:17:34 | |
by some very simple mechanical movements. | 0:17:34 | 0:17:38 | |
It's remarkable, how you just obstruct someone's sight | 0:17:38 | 0:17:41 | |
and have a hand that could be yours | 0:17:41 | 0:17:43 | |
and then start doing the same thing to both, how you can start to feel this alien hand. | 0:17:43 | 0:17:48 | |
-So, we need a volunteer for this. It could be you or I... -We know it's a fake hand. | 0:17:48 | 0:17:52 | |
-So, I'm going for that guy there. -OK. | 0:17:52 | 0:17:54 | |
-Conveniently wearing a microphone. -What can I say? -Come here. | 0:17:54 | 0:17:58 | |
Now, our fake hand has got this shirt on, | 0:17:59 | 0:18:01 | |
so do you mind wearing a similar shirt? | 0:18:01 | 0:18:04 | |
-The largest man we found! What's your name? -Luke. | 0:18:04 | 0:18:09 | |
-How are you, Luke? It suits you. -It's nice. | 0:18:09 | 0:18:12 | |
-A good fit. -Could be made for you. | 0:18:12 | 0:18:14 | |
Would you sit down, Luke? As if that is where you'd be sitting, | 0:18:14 | 0:18:16 | |
-with your hand in front. -Yeah. | 0:18:16 | 0:18:19 | |
-That's it -OK, cool. -How does that feel? -Yeah. | 0:18:19 | 0:18:23 | |
No, we also have to put this on, so that it feels like a continuous... | 0:18:23 | 0:18:26 | |
Gotcha, gotcha. Sort of shirt... | 0:18:26 | 0:18:29 | |
Now, you think this is weird? Watch this. | 0:18:29 | 0:18:32 | |
I'm going to get on this box and give you a manicure. | 0:18:32 | 0:18:36 | |
-Have you ever had a manicure? -Not professionally, no. -OK. | 0:18:36 | 0:18:39 | |
Well, this is not going to be a first for you. | 0:18:39 | 0:18:43 | |
It's definitely an unprofessional manicure. | 0:18:43 | 0:18:45 | |
So, you can see that hand and, in a sense, | 0:18:45 | 0:18:47 | |
your brain is thinking, perhaps, "That is my hand," | 0:18:47 | 0:18:50 | |
because it's in the right place, isn't it? | 0:18:50 | 0:18:52 | |
Now, that's just your vision, | 0:18:52 | 0:18:54 | |
but we want to do multi-multi-multimodal perceptions, | 0:18:54 | 0:18:57 | |
so we're going to start adding the sense of touch. | 0:18:57 | 0:19:00 | |
So, if I stroke both fingers at the same time and in the same place | 0:19:00 | 0:19:03 | |
with the same frequency, your brain is thinking, | 0:19:03 | 0:19:05 | |
"Hold on. I can see it's perhaps my hand, | 0:19:05 | 0:19:08 | |
"and I can feel exactly what I should feel." | 0:19:08 | 0:19:11 | |
The back of the hand is very sensitive, like that. | 0:19:11 | 0:19:13 | |
I do feel like I want to move it now. | 0:19:13 | 0:19:15 | |
Really? | 0:19:15 | 0:19:17 | |
LAUGHTER | 0:19:17 | 0:19:20 | |
APPLAUSE | 0:19:20 | 0:19:22 | |
-Did that feel strange? -Yeah, really strange. It felt like... | 0:19:27 | 0:19:31 | |
Yeah. Like I had a really bad dead arm, or something, | 0:19:31 | 0:19:35 | |
-and I was just trying and trying. -Did you...when the hammer came up, | 0:19:35 | 0:19:38 | |
-did you think...? -Yeah. | 0:19:38 | 0:19:39 | |
I thought, "Oh, God, my hand's squished." | 0:19:39 | 0:19:42 | |
-That hand there, does the hand flinch in any way? -I couldn't see... | 0:19:44 | 0:19:47 | |
Yeah, it did. | 0:19:47 | 0:19:49 | |
We have a slow motion, by the way, | 0:19:49 | 0:19:51 | |
of your reaction to the arrival of the hammer. | 0:19:51 | 0:19:54 | |
LAUGHTER | 0:19:54 | 0:19:57 | |
-Cheers. -Well done. Thank you very much indeed. -Thanks a lot. | 0:19:57 | 0:20:00 | |
So, someone with an actual limb, you give them a false limb, you give them the impression | 0:20:05 | 0:20:09 | |
of the false limb, their brain can fill in the gaps. | 0:20:09 | 0:20:11 | |
But the opposite is also true. | 0:20:11 | 0:20:13 | |
Exactly. So, phantom limb syndrome, where someone has lost a limb - | 0:20:13 | 0:20:16 | |
they sometimes feel that their limb is still there. | 0:20:16 | 0:20:19 | |
But sometimes that's even weirder because it is clenched | 0:20:19 | 0:20:21 | |
or they're in great pain. | 0:20:21 | 0:20:23 | |
So in order to get rid of that feeling, | 0:20:23 | 0:20:26 | |
people use a similar technique with a mirror and a box, so one arm | 0:20:26 | 0:20:29 | |
is reflecting the other, so you'd perceive yourself as having two hands, | 0:20:29 | 0:20:33 | |
-and then you can get the other hand to be all flexible and stretch. -Stretch? -Stretch, yeah. | 0:20:33 | 0:20:37 | |
Getting our brains to control things remotely, that are not directly | 0:20:37 | 0:20:41 | |
attached to you, again sounds like the ultimate in science fiction. | 0:20:41 | 0:20:44 | |
But Dr Helen Czerski has uncovered some new research which is starting | 0:20:44 | 0:20:47 | |
to make some startling inroads in that direction. | 0:20:47 | 0:20:51 | |
I'm finding it quite hard to control this robotic arm. | 0:21:00 | 0:21:04 | |
But a few months ago, a woman called Cathy Hutchinson picked up | 0:21:04 | 0:21:07 | |
a coffee cup with a robotic arm. | 0:21:07 | 0:21:09 | |
It was a special event because Cathy is paralysed from the neck down. | 0:21:13 | 0:21:17 | |
She was controlling the robot arm just with her thoughts. | 0:21:20 | 0:21:24 | |
This remarkable moment was the result of five years' intense | 0:21:30 | 0:21:33 | |
collaboration between Cathy and a team of over 40 scientists. | 0:21:33 | 0:21:37 | |
Our brains are buzzing with electrical activity, | 0:21:40 | 0:21:43 | |
signals whizzing around all the time. | 0:21:43 | 0:21:46 | |
They listened in on those signals, | 0:21:46 | 0:21:49 | |
isolated the ones that are just associated with moving one hand, | 0:21:49 | 0:21:54 | |
and then used those signals to control an external device. | 0:21:54 | 0:21:57 | |
'Leigh Hochberg, who led the research, is going to show me how it all works, | 0:21:59 | 0:22:03 | |
'starting with a brain on loan from the medical school.' | 0:22:03 | 0:22:07 | |
-Oh, it's got stuff at the bottom! -It does. | 0:22:07 | 0:22:09 | |
This stuff would be the spinal cord. | 0:22:09 | 0:22:11 | |
'If you have a stroke, it can disrupt the connections between your | 0:22:12 | 0:22:15 | |
'motor cortex and your spinal cord, leaving you paralysed.' | 0:22:15 | 0:22:20 | |
'But remarkably, when we imagine moving, we still generate | 0:22:20 | 0:22:24 | |
'signals in our motor cortex that can be detected with electrodes.' | 0:22:24 | 0:22:28 | |
So, tell me what this is. | 0:22:28 | 0:22:30 | |
This is the BrainGate implant that we've been | 0:22:30 | 0:22:32 | |
using in our clinical trials. | 0:22:32 | 0:22:34 | |
If you squint your eyes, there's 100 tiny electrodes, | 0:22:34 | 0:22:38 | |
each of which is a millimetre or 1.5 millimetres long. | 0:22:38 | 0:22:41 | |
It would be placed essentially right on the motor cortex, | 0:22:41 | 0:22:44 | |
right about there, and then the cells of interest are somewhere | 0:22:44 | 0:22:47 | |
between a millimetre and 1.5 millilitres deep inside the brain. | 0:22:47 | 0:22:52 | |
Soon after the implant was placed in Cathy's brain, | 0:22:52 | 0:22:55 | |
Leigh's team recorded this signal from a single neuron. | 0:22:55 | 0:22:59 | |
CRACKLING | 0:22:59 | 0:23:01 | |
It is the sound Cathy's thoughts as she imagines moving her hand. | 0:23:04 | 0:23:08 | |
Open your hand. | 0:23:08 | 0:23:09 | |
Relax. | 0:23:13 | 0:23:14 | |
-You can hear it firing away, that rat-tat-tat-tat. -That crackling. | 0:23:14 | 0:23:17 | |
That staccato crackling, like an old AM radio. | 0:23:17 | 0:23:20 | |
That's the language of the nervous system. | 0:23:21 | 0:23:24 | |
It's how neurons talk to neurons, | 0:23:24 | 0:23:26 | |
it's how neurons talk to muscle, | 0:23:26 | 0:23:27 | |
and that's the language that we're trying to decode. | 0:23:27 | 0:23:31 | |
'It took a long time, but gradually the team learned to recognise Cathy's | 0:23:31 | 0:23:35 | |
'different brain signals as she imagined moving her hand in different directions... | 0:23:35 | 0:23:41 | |
'until they were finally able to use them to drive the robotic arm.' | 0:23:41 | 0:23:45 | |
-How did you feel when that happened? -It was an amazing moment for her, | 0:23:45 | 0:23:48 | |
it was an amazing moment for all of us on the research team, | 0:23:48 | 0:23:51 | |
and it suggested that we're on our way towards developing | 0:23:51 | 0:23:54 | |
a technology that would allow somebody with paralysis | 0:23:54 | 0:23:58 | |
to regain some of that mobility and independence that they'd lost. | 0:23:58 | 0:24:01 | |
'While Leigh and his team are decoding the brain | 0:24:01 | 0:24:04 | |
'signals from the motor cortex, another group of scientists | 0:24:04 | 0:24:07 | |
'are beginning to tune into the very heart of human consciousness. | 0:24:07 | 0:24:12 | |
'They are trying to isolate the brain signals of speech and thought. | 0:24:12 | 0:24:17 | |
'But tuning into our brain's language centres isn't easy.' | 0:24:17 | 0:24:21 | |
If you're squeamish, | 0:24:21 | 0:24:22 | |
it might be a good idea to look away for the next few moments. | 0:24:22 | 0:24:26 | |
This is footage of an epileptic patient having life-saving surgery. | 0:24:27 | 0:24:31 | |
'You can see a sheet of electrodes being placed over the surface of their brain.' | 0:24:31 | 0:24:36 | |
The surgeons use these electrodes to locate the source of epileptic | 0:24:39 | 0:24:43 | |
seizures, but this unusual access to the brain also is an enormous | 0:24:43 | 0:24:48 | |
window of opportunity for research. | 0:24:48 | 0:24:51 | |
Because it brings the otherwise inaccessible language centres | 0:24:51 | 0:24:54 | |
of the brain within our reach. | 0:24:54 | 0:24:56 | |
Here in St Louis, Missouri, brain surgeon Eric Leuthardt has been using | 0:24:57 | 0:25:02 | |
this system to tune into the most basic building blocks of language - phonemes. | 0:25:02 | 0:25:07 | |
A phoneme is a unit of spoken sound like "ah" or "ooh". | 0:25:07 | 0:25:11 | |
Eric asks the participants in the trial to speak those sounds | 0:25:11 | 0:25:16 | |
out loud so that he could monitor which areas of the brain were active when they were spoken. | 0:25:16 | 0:25:21 | |
He also asked them to imagine the sounds, | 0:25:21 | 0:25:23 | |
and what he found was really interesting. | 0:25:23 | 0:25:27 | |
Thinking of words before you speak | 0:25:28 | 0:25:30 | |
happens in a different part of the brain than actually speaking them out loud. | 0:25:30 | 0:25:34 | |
Eric and his colleagues managed to isolate signals from both areas. | 0:25:35 | 0:25:39 | |
It was the first time anyone has ever tuned into our unspoken, inner voice. | 0:25:39 | 0:25:44 | |
To demonstrate it, he taught his computers to recognise | 0:25:45 | 0:25:47 | |
the brain signals and use them to move a cursor. | 0:25:47 | 0:25:51 | |
Here is a video of the patient, | 0:25:51 | 0:25:53 | |
who has her electrodes implanted over the surface of her brain. | 0:25:53 | 0:25:57 | |
Now, what she's doing is, she's saying, "Ooh, ooh, ooh," | 0:25:57 | 0:26:01 | |
or, "Ah, ah, ah." | 0:26:01 | 0:26:03 | |
Essentially, each time she says, "Ooh," | 0:26:03 | 0:26:05 | |
it moves the cursor in one direction, just a little bit. | 0:26:05 | 0:26:09 | |
And each time she says, "Ah," it moves in the opposite direction. | 0:26:09 | 0:26:12 | |
So she really has to use her speech intention to get the cursor | 0:26:12 | 0:26:15 | |
to go to the target. | 0:26:15 | 0:26:18 | |
Here you can see she's imagining "ooh" and "ah" to control the cursor. | 0:26:18 | 0:26:22 | |
-So no sound is coming out of her mouth? -She's not saying anything. | 0:26:22 | 0:26:26 | |
This is purely based on her inner voice. | 0:26:26 | 0:26:29 | |
'The computer is effectively reading her thoughts.' | 0:26:31 | 0:26:35 | |
So do you feel that you're one step closer to being able to mind-read? | 0:26:37 | 0:26:42 | |
Well, yes. | 0:26:42 | 0:26:44 | |
I think that again, as a scientist, | 0:26:44 | 0:26:46 | |
you always have to be cautious about what you can promise. | 0:26:46 | 0:26:49 | |
But it does provide some of the early demonstration that | 0:26:49 | 0:26:52 | |
we can start to capture some things that more closely approximate | 0:26:52 | 0:26:56 | |
what it is to make up human thoughts. | 0:26:56 | 0:26:59 | |
-That's incredible stuff. -Just astonishing. | 0:27:06 | 0:27:08 | |
It's astonishing. | 0:27:08 | 0:27:09 | |
Whatever about seeing the brain's reaction of being able to | 0:27:09 | 0:27:13 | |
measure as they actually said it, even thinking about saying | 0:27:13 | 0:27:16 | |
"ah" and "ooh" is enough to create the same reaction in the brain? | 0:27:16 | 0:27:20 | |
Yeah, so, what they did was very clever. | 0:27:20 | 0:27:22 | |
They showed her an arm moving | 0:27:22 | 0:27:24 | |
and made her imagine that she was doing it and then | 0:27:24 | 0:27:27 | |
they looked at the signals and then gradually they gave her the control. | 0:27:27 | 0:27:30 | |
So they learned from her and she learned to control the arm. | 0:27:30 | 0:27:34 | |
I am completely amazed at this film. | 0:27:34 | 0:27:36 | |
I think it's really, really interesting, particularly | 0:27:36 | 0:27:40 | |
that it's not just about having a specific movement | 0:27:40 | 0:27:45 | |
or a specific sound that is made, | 0:27:45 | 0:27:47 | |
but imagining the movement, imagining the sound. | 0:27:47 | 0:27:50 | |
What kind of conditions is this going to help you with? | 0:27:50 | 0:27:52 | |
Amputees, people with locked-in syndrome, people with strokes? | 0:27:52 | 0:27:55 | |
So the first thought is obviously people who've been injured in some way, | 0:27:55 | 0:27:59 | |
and the most serious injuries come to mind, first, | 0:27:59 | 0:28:02 | |
so locked-in syndrome is one, amputees, paralysis, lots of things. | 0:28:02 | 0:28:06 | |
But then Eric, certainly the second brain surgeon, is completely | 0:28:06 | 0:28:10 | |
convinced that this will become normal for healthy people, | 0:28:10 | 0:28:14 | |
because machines can do a lot of things we can't. | 0:28:14 | 0:28:16 | |
They can go to places that are colder or have conditions that | 0:28:16 | 0:28:20 | |
we can't go to, or they're on other planets. | 0:28:20 | 0:28:24 | |
But we have... Humans are amazing at pattern recognition and | 0:28:24 | 0:28:27 | |
at solving problems, but if you have direct control, we could go there. | 0:28:27 | 0:28:32 | |
-We could use this for space exploration or for mining or for surgery? -Anything. -Anything at all. | 0:28:32 | 0:28:37 | |
That's fantastic. Still to come - Jessica Hynes goes on a journey | 0:28:37 | 0:28:41 | |
into her own brain, and Alok Jha asks if we should be using smart drugs. | 0:28:41 | 0:28:45 | |
You can get more information | 0:28:45 | 0:28:46 | |
by going to the website or following us. | 0:28:46 | 0:28:48 | |
Details are on your screen now. | 0:28:48 | 0:28:50 | |
OK, but first, our brains are also responsible for our personalities. | 0:28:54 | 0:28:58 | |
That's the location of our personality. | 0:28:58 | 0:29:00 | |
I want to bring in our resident neuroscientist, Tali Sharot. | 0:29:00 | 0:29:03 | |
Tali, thank you very much. | 0:29:03 | 0:29:04 | |
Tali, you're currently in your own research investigating | 0:29:09 | 0:29:13 | |
one aspect of personality. Which is that? | 0:29:13 | 0:29:16 | |
Well, one thing that we're looking at is optimism. | 0:29:16 | 0:29:19 | |
So that's our tendency to expect positive events in the future. | 0:29:19 | 0:29:24 | |
But what's really interesting is that most of us | 0:29:24 | 0:29:26 | |
have what is known as an optimism bias, or unrealistic optimism, | 0:29:26 | 0:29:31 | |
which means that we tend to overestimate | 0:29:31 | 0:29:33 | |
the likelihood of experiencing good events in our lives, | 0:29:33 | 0:29:36 | |
such as longevity or professional success, and we underestimate | 0:29:36 | 0:29:40 | |
the likelihood of experiencing negative events in our lives. | 0:29:40 | 0:29:43 | |
A lot of people will say, "I'm a realist, I'm a little bit of a pessimist." | 0:29:43 | 0:29:47 | |
So we're not aware of our own optimism. | 0:29:47 | 0:29:49 | |
It is a bit of a trick that our brain plays on us. | 0:29:49 | 0:29:52 | |
Are there any sample questions we can ask? | 0:29:52 | 0:29:54 | |
We can try it here. Let's see. | 0:29:54 | 0:29:56 | |
OK, so, who here believes that if and when they get married, | 0:29:56 | 0:30:00 | |
they will get divorced? Just put your hands up. | 0:30:00 | 0:30:03 | |
-OK. -And the divorce rate is? | 0:30:05 | 0:30:07 | |
Divorce rate in the Western world is between 40% and 50%. | 0:30:07 | 0:30:10 | |
I would say, what, 5% of our audience. | 0:30:10 | 0:30:14 | |
Very few people get married going, "Ah, I'll probably give this five years." | 0:30:14 | 0:30:17 | |
Exactly. People who get married... There was a survey... | 0:30:17 | 0:30:21 | |
Newlyweds estimate their own likelihood of divorce at 0%. | 0:30:21 | 0:30:24 | |
LAUGHTER | 0:30:24 | 0:30:26 | |
Even people who should know better, like divorce lawyers, | 0:30:26 | 0:30:28 | |
they estimate their own divorce rates as about 0% as well. | 0:30:28 | 0:30:31 | |
Let's do another one. | 0:30:31 | 0:30:33 | |
This time, think about how well you get along with other people, OK, relative to the population. | 0:30:33 | 0:30:39 | |
So, who believes they're at the bottom 25% of getting | 0:30:39 | 0:30:42 | |
along well with others? | 0:30:42 | 0:30:44 | |
Bottom 25. So we have one person, two, maybe three people. | 0:30:44 | 0:30:48 | |
Bottom 50%? | 0:30:48 | 0:30:49 | |
Not many. Top 50% for getting along well with others? | 0:30:50 | 0:30:54 | |
Right, that's about 90% of the population. | 0:30:54 | 0:30:56 | |
So 90% of the population think they're in the top 50% of the population? | 0:30:56 | 0:31:00 | |
Well, actually, in an actual survey, they found | 0:31:00 | 0:31:03 | |
that 25% of the population believe they are at the top 1% | 0:31:03 | 0:31:08 | |
That's known as a superiority illusion, | 0:31:08 | 0:31:10 | |
which means that we tend to think that we're better than most | 0:31:10 | 0:31:13 | |
other people and we're better than what we actually are. | 0:31:13 | 0:31:16 | |
Now, you've been studying this for a number of years, I know, | 0:31:16 | 0:31:19 | |
and you set tests for this, | 0:31:19 | 0:31:20 | |
not only on our studio audience, but on the team here as well. | 0:31:20 | 0:31:23 | |
Yeah, so we put together an experiment | 0:31:23 | 0:31:25 | |
and I think we're going to show you the results in a little bit. | 0:31:25 | 0:31:28 | |
Fantastic. Now, we've also talked, by the way, about memory. | 0:31:28 | 0:31:30 | |
We've touched on memory a couple of times. | 0:31:30 | 0:31:32 | |
Memory's very interesting as well because it's not like there's | 0:31:32 | 0:31:35 | |
one store for memory, essentially, is there? | 0:31:35 | 0:31:38 | |
Well, there are many different kinds of memory. | 0:31:38 | 0:31:41 | |
The memory that you will call on when I ask you what you | 0:31:41 | 0:31:46 | |
had for breakfast this morning is completely different from | 0:31:46 | 0:31:50 | |
the memory that's where, for example, | 0:31:50 | 0:31:53 | |
when I ask you, "What is the capital of Mongolia?" | 0:31:53 | 0:31:56 | |
We have spatial memory, which is very different, visual memory, | 0:31:56 | 0:32:01 | |
auditory memory - all sorts of memories. | 0:32:01 | 0:32:03 | |
Long-term memory, short-term memory... | 0:32:03 | 0:32:05 | |
Should people be really insulted by the fact that I can't remember their names? | 0:32:05 | 0:32:09 | |
-Because I really am bad with names. -Some people can't remember faces. | 0:32:09 | 0:32:12 | |
I'm also bad with faces. | 0:32:12 | 0:32:14 | |
I'm sure you have ways of glossing over this. | 0:32:14 | 0:32:17 | |
-I do, I do. I am tremendously charming. -We all do. | 0:32:17 | 0:32:20 | |
This is why people, in order to remember, | 0:32:20 | 0:32:24 | |
recommend a special method, which is quite interesting. | 0:32:24 | 0:32:29 | |
It's like wandering through a space, through a house. | 0:32:29 | 0:32:31 | |
You walk through a house you are familiar with. | 0:32:31 | 0:32:34 | |
Yeah, and that seems to work. | 0:32:34 | 0:32:36 | |
-That's a trick that will increase all your memory. -Very good, OK. | 0:32:36 | 0:32:41 | |
Actors obviously use their memory constantly, | 0:32:41 | 0:32:44 | |
with new scripts for show after show. | 0:32:44 | 0:32:45 | |
We send Twenty Twelve actor Jessica Hynes to find out | 0:32:45 | 0:32:48 | |
what effect this was having on her brain. | 0:32:48 | 0:32:51 | |
I'm on my way to a cognition and brain sciences unit, | 0:32:52 | 0:32:55 | |
where I'm going to meet some scientists who study the brain. | 0:32:55 | 0:32:59 | |
They do this by actually looking inside the brain | 0:32:59 | 0:33:02 | |
and then studying the brain's responses to controlled stimuli. | 0:33:02 | 0:33:08 | |
I can't think of a better way to spend an afternoon. | 0:33:08 | 0:33:11 | |
Scientists here are trying to measure how effectively humans | 0:33:13 | 0:33:17 | |
can control their consciousness. | 0:33:17 | 0:33:19 | |
Michael Anderson and Roland Benoit plan to use MRI scanning | 0:33:21 | 0:33:25 | |
to watch how effectively I can do that in a memory test. | 0:33:25 | 0:33:29 | |
But first, they say they need to train me. | 0:33:29 | 0:33:32 | |
No press ups involved, I hope. | 0:33:32 | 0:33:34 | |
Vice. | 0:33:36 | 0:33:38 | |
Hero. | 0:33:38 | 0:33:40 | |
In the very beginning, she's provided with a set of word pairs, | 0:33:40 | 0:33:43 | |
and she's trained to provide the second of the two words | 0:33:43 | 0:33:46 | |
on the right-hand side | 0:33:46 | 0:33:47 | |
whenever she's given the word on the left-hand side. | 0:33:47 | 0:33:50 | |
So if I see the word "vault", I have to think of the word "gold". | 0:33:50 | 0:33:54 | |
Hexagon. | 0:33:54 | 0:33:56 | |
Parent. | 0:33:56 | 0:33:58 | |
And she's drilled until she knows these pairs really well. | 0:33:58 | 0:34:01 | |
I'm really looking forward to having a picture of my brain. | 0:34:01 | 0:34:04 | |
'Michael and Roland also want a picture of my brain, | 0:34:04 | 0:34:07 | |
'using their MRI scanner.' | 0:34:07 | 0:34:09 | |
But this is no mere memory test. | 0:34:13 | 0:34:16 | |
First, they'll watch what parts of my brain are active | 0:34:16 | 0:34:19 | |
when I remember a word pair. | 0:34:19 | 0:34:21 | |
But then they'll look for a difference | 0:34:21 | 0:34:23 | |
when I'm instructed not to think of a pair. | 0:34:23 | 0:34:26 | |
When a reminder pops up in green, | 0:34:26 | 0:34:29 | |
like it's happening right now, | 0:34:29 | 0:34:31 | |
that's her instruction, "Go," | 0:34:31 | 0:34:33 | |
to think about a memory that goes with that. | 0:34:33 | 0:34:36 | |
However, when a reminder appears in red, such as this one, | 0:34:36 | 0:34:39 | |
that's her instruction to stop, | 0:34:39 | 0:34:42 | |
to prevent the associated memory from entering consciousness, even for a second. | 0:34:42 | 0:34:45 | |
Good on the first red, and then, just as it went off the screen, | 0:34:45 | 0:34:49 | |
the associated word just popped into my head. | 0:34:49 | 0:34:52 | |
Please do your very best, yeah, OK? | 0:34:52 | 0:34:55 | |
When Jessica is trying to keep something out of consciousness, | 0:34:55 | 0:34:58 | |
whatever part of the brain it is that is doing that will have | 0:34:58 | 0:35:01 | |
to work harder. | 0:35:01 | 0:35:03 | |
When it's working harder, the blood flow increases | 0:35:03 | 0:35:06 | |
and that's what we can see. | 0:35:06 | 0:35:08 | |
As the experiment progresses, | 0:35:08 | 0:35:10 | |
you just work out ways of blocking it out. | 0:35:10 | 0:35:12 | |
And the more you think about the red word, | 0:35:12 | 0:35:14 | |
the easier it is to actively forget the associated word. | 0:35:14 | 0:35:18 | |
What we're looking at here is a slightly creepy | 0:35:18 | 0:35:21 | |
three-dimensional rendering of your actual skull. | 0:35:21 | 0:35:25 | |
I like the wood look. | 0:35:25 | 0:35:26 | |
Yes, this would be what it would look like | 0:35:26 | 0:35:28 | |
if you had a wood sculpture of your head. | 0:35:28 | 0:35:31 | |
-A wooden head. -Yes. | 0:35:31 | 0:35:33 | |
On the periphery here, it's slightly darker grey. | 0:35:33 | 0:35:37 | |
-Is that a problem? -No! It's perfectly normal. | 0:35:37 | 0:35:41 | |
-Good. I was just asking. -That is your grey matter. | 0:35:41 | 0:35:45 | |
On the inside is the white matter, literally, fat. | 0:35:45 | 0:35:50 | |
So it takes £1 million-worth of Cambridge's finest scanning | 0:35:50 | 0:35:53 | |
equipment to tell me that I have a wooden head filled with fat. | 0:35:53 | 0:35:57 | |
I'll give Michael a while longer to process my results. | 0:35:57 | 0:36:00 | |
In the meantime, his colleague James Rowe can show me | 0:36:00 | 0:36:03 | |
where memories are in the human brain. | 0:36:03 | 0:36:06 | |
This is about the right size and weight of a human brain. | 0:36:06 | 0:36:09 | |
It's not a human brain. It's made from wood, but it's about the right size and shape. | 0:36:09 | 0:36:13 | |
Even I could have told you that... | 0:36:13 | 0:36:15 | |
'Wood effect is obviously very popular.' | 0:36:15 | 0:36:18 | |
If we look here at this model, this is a plastic model of the brain. | 0:36:18 | 0:36:21 | |
It's slightly larger than a real brain. | 0:36:21 | 0:36:22 | |
But it's inside here, we see where the hippocampus lies, | 0:36:22 | 0:36:26 | |
which is critical for those long-term memories. | 0:36:26 | 0:36:28 | |
But it is in constant communication, or conversation, | 0:36:28 | 0:36:31 | |
between the hippocampus and the frontal lobe. | 0:36:31 | 0:36:33 | |
And the retrieval which comes with this conversation | 0:36:33 | 0:36:36 | |
between different memory areas is very precisely tuned. | 0:36:36 | 0:36:38 | |
It's very exact in what you want to call in mind and when you want it. | 0:36:38 | 0:36:42 | |
-And it doesn't take much to make that inefficient. -About four pints? | 0:36:42 | 0:36:46 | |
Less than four pints, in my case. You may be better trained than I am. | 0:36:46 | 0:36:51 | |
So, what about me? | 0:36:51 | 0:36:53 | |
Could I control what I chose to remember and what I chose to forget? | 0:36:53 | 0:36:57 | |
So this is the proportion of the words that you recalled correctly | 0:36:59 | 0:37:02 | |
in the controlled condition, which you did fantastically well, by the way. | 0:37:02 | 0:37:06 | |
95% correct. Very good memory. | 0:37:06 | 0:37:08 | |
Nice tie. | 0:37:08 | 0:37:10 | |
Thanks! | 0:37:10 | 0:37:12 | |
The ones that you tried to keep out of consciousness, | 0:37:12 | 0:37:16 | |
you were successful at blocking out some of the memories. | 0:37:16 | 0:37:19 | |
In fact, I would say you're better than average. | 0:37:19 | 0:37:22 | |
That was such an interesting day. | 0:37:24 | 0:37:26 | |
I'm going to go and now spend a bit of attention on my basal ganglia | 0:37:26 | 0:37:30 | |
and my ventral striatum. | 0:37:30 | 0:37:33 | |
Ladies and gentlemen, Jessica Hynes. | 0:37:34 | 0:37:38 | |
Hi, very nice to meet you. | 0:37:38 | 0:37:40 | |
How are you? | 0:37:40 | 0:37:41 | |
You looked quite sheepish there, but you did way better than average. | 0:37:43 | 0:37:47 | |
He said that I was about 16% effective, | 0:37:47 | 0:37:51 | |
and he said the average person is about 8% effective. | 0:37:51 | 0:37:55 | |
So I was about twice as effective as the average person. | 0:37:55 | 0:37:58 | |
-Why, do you think? -It was interesting. | 0:37:58 | 0:38:00 | |
He asked me and I sort of was going to say, | 0:38:00 | 0:38:03 | |
"Maybe you could tell me. I don't know. You're the scientist." | 0:38:03 | 0:38:06 | |
The only thing I could think of was whether there was a relationship | 0:38:06 | 0:38:09 | |
between the type of work you mentioned, you know, learning lines. | 0:38:09 | 0:38:12 | |
But I think it's beyond learning lines | 0:38:12 | 0:38:14 | |
in terms of actually memory recall. | 0:38:14 | 0:38:16 | |
I think there's a part of performance and creativity | 0:38:16 | 0:38:19 | |
which is as much about suppression as it is about remembering. | 0:38:19 | 0:38:22 | |
If you're trying to create a reality with another actor, | 0:38:22 | 0:38:26 | |
very effectively and powerfully, | 0:38:26 | 0:38:28 | |
what you want to do is suppress the real reality. | 0:38:28 | 0:38:31 | |
-Who they actually are. -And who you are as well. | 0:38:31 | 0:38:34 | |
So I did wonder whether there was some connection there. | 0:38:34 | 0:38:38 | |
-Does that make sense? -Yes, it does. Absolutely. | 0:38:38 | 0:38:41 | |
An act of creative doublethink, | 0:38:41 | 0:38:42 | |
that you can keep both realities compartmentalised? | 0:38:42 | 0:38:46 | |
Yes, that, certainly. But there has to be this huge control... | 0:38:46 | 0:38:50 | |
And they did talk about control, | 0:38:50 | 0:38:52 | |
and a large part of the human brain is exactly about control, | 0:38:52 | 0:38:56 | |
you know, switching on, switching off, doing very subtle things. | 0:38:56 | 0:39:00 | |
This bit can be trained. | 0:39:00 | 0:39:03 | |
The idea of suppressing memories would be useful | 0:39:03 | 0:39:06 | |
to post-traumatic stress cases? | 0:39:06 | 0:39:08 | |
I think the idea of wiping out certain memories is fascinating. | 0:39:08 | 0:39:12 | |
But I think there might be more bad effects than good effects. | 0:39:12 | 0:39:16 | |
Surely if we could just wipe out... | 0:39:16 | 0:39:18 | |
I have facts about Kim Kardashian in my head that are no use to me... | 0:39:18 | 0:39:23 | |
-Images. -Images, all of this. | 0:39:23 | 0:39:26 | |
I have a dossier about this woman in my head. | 0:39:26 | 0:39:30 | |
You never know how this will come in useful. | 0:39:30 | 0:39:33 | |
The stuff of the brain is similar in all animals. | 0:39:33 | 0:39:36 | |
But the ratio of different sections differ | 0:39:36 | 0:39:39 | |
depending on the environment they have adapted to. | 0:39:39 | 0:39:41 | |
For example, human brains put a lot of effort into understanding and using language, | 0:39:41 | 0:39:45 | |
but it is not the same for all animals. Here is some data. | 0:39:45 | 0:39:48 | |
You live inside your brain, 77% of which is water, | 0:39:48 | 0:39:52 | |
8% protein and 12% fat. The rest is a mixture of carbohydrates, | 0:39:52 | 0:39:57 | |
soluble organics and salts. | 0:39:57 | 0:39:59 | |
What is it that makes us so smart? Is it the size? | 0:39:59 | 0:40:04 | |
The biggest brain on the planet belongs to the sperm whale, at 7kg. | 0:40:04 | 0:40:08 | |
But a dolphin's weighs in at 1.6kg. | 0:40:08 | 0:40:11 | |
The elephant's brain averages 4.7. The average human's weighs about 1.4. | 0:40:11 | 0:40:16 | |
Interestingly, Einstein was a lightweight. | 0:40:16 | 0:40:20 | |
His brain weighed only 1.2kg. | 0:40:20 | 0:40:24 | |
Clearly, size isn't everything. | 0:40:24 | 0:40:26 | |
Scientists have compared an animal's weight to the size of their brains. | 0:40:26 | 0:40:32 | |
This is what is called the EQ. A rabbit has an EQ of 0.4. | 0:40:32 | 0:40:35 | |
A cat has an EQ of 1. A dog, 1.2. The elephant has an EQ of 2. | 0:40:35 | 0:40:41 | |
A dolphin of 4.1. | 0:40:41 | 0:40:44 | |
Our kissing cousins, the Neanderthals, come in with 4.7. | 0:40:44 | 0:40:49 | |
And we humans have an EQ of a whopping 7. | 0:40:49 | 0:40:52 | |
However, this overlooks how much of the brain is actually used for thinking. | 0:40:52 | 0:40:56 | |
More recently, scientists have begun to count neurons. | 0:40:56 | 0:41:01 | |
A leech has about 10,000. A cockroach, 1 million. | 0:41:01 | 0:41:06 | |
A cat has 1 billion. A chimp has close to 7 billion brain cells. | 0:41:06 | 0:41:13 | |
And you? Most recently, it has been calculated that we humans | 0:41:13 | 0:41:16 | |
have 86 billion neurons firing in concert. | 0:41:16 | 0:41:20 | |
This is the brain. | 0:41:20 | 0:41:23 | |
It uses 20% of the oxygen in our bodies and yet accounts for only | 0:41:23 | 0:41:26 | |
2% of our weight, which is something worth thinking about. | 0:41:26 | 0:41:30 | |
Anyway... Right, we have a number of brains here. | 0:41:34 | 0:41:38 | |
We are presuming that they are from adult animals. There are similarities. | 0:41:38 | 0:41:43 | |
There are many similarities. | 0:41:43 | 0:41:45 | |
They all have these two hemispheres | 0:41:45 | 0:41:47 | |
and they have this folded sheet. | 0:41:47 | 0:41:52 | |
Yes, why? | 0:41:52 | 0:41:53 | |
We have a sheet here to fold. Actually the human brain, if you stretched it out flat, the cortex... | 0:41:53 | 0:42:00 | |
-This is the outer bit. -The outer bit, yes. | 0:42:00 | 0:42:02 | |
It would be about that big. | 0:42:02 | 0:42:05 | |
All these folds would be that large. The volume of the human brain, if you took the surface | 0:42:05 | 0:42:11 | |
-and it was smooth, would be that big. -That's right. -But because it is all folded... | 0:42:11 | 0:42:15 | |
All folded in valleys and ridges | 0:42:15 | 0:42:19 | |
and it sort of goes altogether, like this. | 0:42:19 | 0:42:22 | |
It is a great evolutionary trait because that allows you to have more activity into a small area. | 0:42:22 | 0:42:27 | |
Absolutely. | 0:42:27 | 0:42:29 | |
The increase of abilities is often associated with these structures. | 0:42:29 | 0:42:34 | |
That means that this limited area of contact with the core is | 0:42:34 | 0:42:39 | |
suddenly magnified. | 0:42:39 | 0:42:40 | |
It is a brilliant way of getting around the fact that you | 0:42:40 | 0:42:43 | |
cannot really get a massive head, or it's not so great to have a massive head. | 0:42:43 | 0:42:46 | |
We do have a picture - I think we have used me for this - of what I look like | 0:42:46 | 0:42:51 | |
and what I would look like if we had to have the same volume. | 0:42:51 | 0:42:54 | |
-What is that? -That is a fresh calf's brain. | 0:42:56 | 0:43:01 | |
Those people wondering whether the brain is hardware or software, | 0:43:01 | 0:43:06 | |
let me tell you it is soft. | 0:43:06 | 0:43:08 | |
It is kind of amazing to hold in your hand. | 0:43:08 | 0:43:11 | |
There's 12% fat in it | 0:43:11 | 0:43:12 | |
and actually, if you take out the water, it's more than 50% of the matter. | 0:43:12 | 0:43:16 | |
The important thing is that when you put a brain in a blender... | 0:43:16 | 0:43:19 | |
You are not really going to do this, are you? | 0:43:19 | 0:43:23 | |
-You are not really going to do this? -You can discover where that fat is. | 0:43:23 | 0:43:26 | |
I don't want to know. Oh! | 0:43:26 | 0:43:28 | |
Oh! Oh! | 0:43:36 | 0:43:39 | |
Now we have moulded the blood and the fat and protein, you might | 0:43:44 | 0:43:50 | |
-think that would be a delicious thing to eat now. -I would not. | 0:43:50 | 0:43:54 | |
We can look at what the constituents of this thing are. That is what it is. | 0:43:54 | 0:44:00 | |
If we add one of our other favourite... | 0:44:00 | 0:44:02 | |
Our favourite. | 0:44:02 | 0:44:03 | |
It is almost neat alcohol. This is a very strong vodka. | 0:44:03 | 0:44:07 | |
-We use this for everything. -And then we mix this up. | 0:44:08 | 0:44:12 | |
The fat is going to start dissolving in that alcohol. | 0:44:12 | 0:44:16 | |
It will leave behind things like the protein mass and the other constituents in there. | 0:44:16 | 0:44:21 | |
You can see it kind of changing. I am mixing it around. | 0:44:21 | 0:44:25 | |
It is difficult to get this kind of technique going. | 0:44:25 | 0:44:27 | |
It looks easy. | 0:44:27 | 0:44:29 | |
If I gave this spoon to you, Dara... | 0:44:29 | 0:44:32 | |
With my lack of training, yeah! | 0:44:32 | 0:44:34 | |
Now, if we are right, the fat should have | 0:44:34 | 0:44:37 | |
dissolved into this alcohol layer. | 0:44:37 | 0:44:39 | |
We can separate that off by putting it through a filter. | 0:44:39 | 0:44:42 | |
-We are taking all the protein out. -That has all been left in there. | 0:44:45 | 0:44:49 | |
What we should be left with is a solution which is mostly alcohol | 0:44:49 | 0:44:53 | |
with some dissolved fats in it and a few other things. | 0:44:53 | 0:44:56 | |
-How do we show that? It looks clear. -I know it looks like that. | 0:44:56 | 0:44:59 | |
You could take my word for it, or we can get the fat to come out of solution by adding water. | 0:44:59 | 0:45:04 | |
Fat doesn't dissolve very well in water, it sort of floats. | 0:45:04 | 0:45:07 | |
This should go cloudy. There it goes. | 0:45:07 | 0:45:11 | |
That is a little emulsion of fat globules from that brain. | 0:45:11 | 0:45:16 | |
In case you were wondering where all the fat is - there it is. | 0:45:17 | 0:45:22 | |
It is the so-called white matter in the brain. It is white because of the fat. | 0:45:22 | 0:45:26 | |
But it's sheath around nerve fibres | 0:45:26 | 0:45:29 | |
and the more of these sheaths you have, the better the conduction is | 0:45:29 | 0:45:33 | |
of the speed of the signals. | 0:45:33 | 0:45:36 | |
This is the fat that sheaths the neurons, allows you to think fast | 0:45:36 | 0:45:40 | |
and watch this television programme. | 0:45:40 | 0:45:42 | |
Thank you very, very much. | 0:45:42 | 0:45:45 | |
We are covering a mind-boggling range of topics on tonight's show. | 0:45:49 | 0:45:52 | |
If you have any questions about the brain, | 0:45:52 | 0:45:54 | |
we have our after-hours Science Club starting at the end of the show | 0:45:54 | 0:45:57 | |
where a top neuroscientist will be waiting for your questions. | 0:45:57 | 0:46:01 | |
We are at our Hall of Fame. Is there anything you want to add to this? | 0:46:05 | 0:46:09 | |
Yes. My hero is Hermann von Helmholtz. | 0:46:09 | 0:46:13 | |
-Here he is. -He was a physicist. He was involved in thermodynamics. | 0:46:13 | 0:46:16 | |
He was an incredibly well-known physicist in the 19th century. | 0:46:16 | 0:46:21 | |
He was a polymath. | 0:46:21 | 0:46:23 | |
What is less well known is that he was also a neuroscientist. | 0:46:23 | 0:46:27 | |
And he made some stunning discoveries. | 0:46:27 | 0:46:31 | |
So he was actually able to measure the speed of conduction in a nerve. | 0:46:31 | 0:46:37 | |
The other thing I like about his neuroscience is that he | 0:46:37 | 0:46:43 | |
discovered, he invented the idea, of unconscious influences. | 0:46:43 | 0:46:47 | |
He actually invented the deep cognitive unconscious | 0:46:47 | 0:46:53 | |
well before Freud. | 0:46:53 | 0:46:55 | |
-Wow, that's very good. -That is why I want him to be recognised. | 0:46:55 | 0:46:58 | |
I'm going to add a few people to this. | 0:46:58 | 0:47:00 | |
Every week, I jokingly mention people who have made silly contributions to it, | 0:47:00 | 0:47:06 | |
but there are people constantly on Twitter, Facebook and the website, | 0:47:06 | 0:47:09 | |
about people who they think should join the canon, as it were. | 0:47:09 | 0:47:13 | |
Ernest Rutherford gets a lot of votes from people - | 0:47:13 | 0:47:16 | |
the father of nuclear physics, in the Cavendish lab in Cambridge, | 0:47:16 | 0:47:21 | |
discovered the enormous amount of space within it. | 0:47:21 | 0:47:23 | |
Nikola Tesla, because they think that Edison did him down. | 0:47:23 | 0:47:28 | |
He invented alternating current. Edison invented direct current, | 0:47:28 | 0:47:31 | |
and Edison had 1,000 patents to his 100 patents. | 0:47:31 | 0:47:34 | |
He is some sort of geek nerd hero. | 0:47:34 | 0:47:37 | |
And a woman who doesn't... Rosalind Franklin. | 0:47:38 | 0:47:42 | |
CHEERING | 0:47:42 | 0:47:44 | |
Great. | 0:47:44 | 0:47:46 | |
Who published a paper on the structure of DNA in | 0:47:46 | 0:47:48 | |
the same edition of Nature as Watson and Crick, and a lot of people feel | 0:47:48 | 0:47:52 | |
she does not get the credit she deserves for her part in that. | 0:47:52 | 0:47:57 | |
It is also a lot about this sort of non-visibility of female scientists. | 0:47:57 | 0:48:02 | |
It is important. | 0:48:02 | 0:48:03 | |
The human brain has approximately 86 billion neurons | 0:48:03 | 0:48:07 | |
but are yours working to full capacity? | 0:48:07 | 0:48:10 | |
So-called smart drugs and medicines were developed for the treatment | 0:48:10 | 0:48:13 | |
of mental health conditions, | 0:48:13 | 0:48:14 | |
but now they are available to buy on the internet. | 0:48:14 | 0:48:16 | |
Alok Jha reports on what could become a modern dilemma. | 0:48:16 | 0:48:19 | |
If you look on the internet, you will find loads of examples | 0:48:42 | 0:48:46 | |
of people who take smart drugs, writing about their experiences. | 0:48:46 | 0:48:50 | |
I have got some of them here. "I went from a C average student to an A plus. | 0:48:50 | 0:48:54 | |
"I wrote 2,000 words in an hour and a half." "My senses are sharper. | 0:48:54 | 0:48:58 | |
"My work is much faster." | 0:48:58 | 0:49:00 | |
I am always putting things off, dreading the big pieces of work that I have to do. | 0:49:00 | 0:49:06 | |
If these drugs could help me out on that, I mean, | 0:49:06 | 0:49:08 | |
I am really tempted to try one. | 0:49:08 | 0:49:10 | |
So-called smart drugs cover a variety of prescription medicines | 0:49:18 | 0:49:22 | |
originally developed to treat a range of brain disorders. | 0:49:22 | 0:49:25 | |
Neuro-psychologist Mitul Mehta | 0:49:28 | 0:49:30 | |
studies the different effects they have on the brain. | 0:49:30 | 0:49:33 | |
If you think about cognitive enhancers, neurotrophics or psychostimulants, | 0:49:35 | 0:49:38 | |
these are all terms that you might hear in relation to smart drugs. | 0:49:38 | 0:49:43 | |
But they really refer to drugs that are designed to treat people | 0:49:43 | 0:49:47 | |
with cognitive impairments such as Alzheimer's disease, | 0:49:47 | 0:49:50 | |
patients with schizophrenia, patients with attention deficit disorder, | 0:49:50 | 0:49:54 | |
traumatic brain injury. | 0:49:54 | 0:49:56 | |
What are these drugs doing in the brains of people who are healthy? | 0:49:56 | 0:49:59 | |
It might enhance information flow in certain brain systems, | 0:49:59 | 0:50:03 | |
stabilising neutral activity, and this is one way | 0:50:03 | 0:50:06 | |
we think psychostimulants might work in the frontal lobes of the brain. | 0:50:06 | 0:50:10 | |
Another way they might work is by enhancing the signal-to-noise ratio, | 0:50:10 | 0:50:15 | |
so making the signals a bit clearer in the brain. | 0:50:15 | 0:50:18 | |
I did not realise it, but the use of smart drugs is allegedly quite widespread in the world of academia. | 0:50:22 | 0:50:28 | |
Anders Sandberg is a philosopher who studies smart drugs. | 0:50:30 | 0:50:35 | |
-Often under their influence. -My main cognitive enhancer is caffeine. | 0:50:35 | 0:50:40 | |
But I do use modafinil, a prescription drug | 0:50:40 | 0:50:44 | |
originally intended for narcolepsy, | 0:50:44 | 0:50:47 | |
but I am using it for alertness and sharpening in my thinking. | 0:50:47 | 0:50:51 | |
What should people be wary of before taking something like that? | 0:50:51 | 0:50:54 | |
The cognitive enhancer, many of them are stimulants, | 0:50:54 | 0:50:56 | |
and of course stimulants tend to raise your blood pressure, | 0:50:56 | 0:50:59 | |
improve metabolism and exhaust you. | 0:50:59 | 0:51:01 | |
But also, you can think about memory enhancers. | 0:51:01 | 0:51:04 | |
They affect memory systems. You might learn a little bit too much. | 0:51:04 | 0:51:07 | |
You can go a little bit obsessive. There are always trade-offs. | 0:51:07 | 0:51:11 | |
You need to figure out the right drug for the right task. | 0:51:11 | 0:51:14 | |
In sports performance, enhancing drugs are banned | 0:51:16 | 0:51:19 | |
as we want athletes to compete au naturel. | 0:51:19 | 0:51:23 | |
It is the same with exams. | 0:51:23 | 0:51:25 | |
Schools and universities want to test your natural ability | 0:51:25 | 0:51:30 | |
so, in that context, taking any smart drugs is cheating. | 0:51:30 | 0:51:34 | |
At Cambridge University, Barbara Sahakian | 0:51:38 | 0:51:41 | |
is looking at the wider social issues surrounding smart drugs. | 0:51:41 | 0:51:45 | |
I have discussed it with student groups and some of them | 0:51:47 | 0:51:49 | |
feel they are being coerced into using them. | 0:51:49 | 0:51:52 | |
They know that other students are using them to get an advantage. | 0:51:52 | 0:51:55 | |
But outside of competitive cleverness... | 0:51:55 | 0:51:58 | |
Do you think that these drugs could help us have a better and more productive society? | 0:51:58 | 0:52:02 | |
First of all, we obviously need to have the safety information, | 0:52:02 | 0:52:06 | |
long-term safety information. | 0:52:06 | 0:52:08 | |
But when you consider that we do have an ageing population | 0:52:08 | 0:52:11 | |
and people want to stay at work better, | 0:52:11 | 0:52:13 | |
want to function in their own homes for longer | 0:52:13 | 0:52:15 | |
and not go into institutionalised care, | 0:52:15 | 0:52:18 | |
we may well find that this is very good. | 0:52:18 | 0:52:20 | |
We may also find that people are making faster discoveries and inventions. | 0:52:20 | 0:52:25 | |
So smart drugs could help us be mentally sharper, | 0:52:28 | 0:52:31 | |
boost concentration and stay focused. | 0:52:31 | 0:52:35 | |
If we were all taking them, | 0:52:35 | 0:52:37 | |
then society as a whole might even benefit, | 0:52:37 | 0:52:39 | |
and as we are all living longer, | 0:52:39 | 0:52:41 | |
smart drugs could help keep us mentally competitive in old age. | 0:52:41 | 0:52:45 | |
So would I take them? | 0:52:48 | 0:52:49 | |
I have got a lot of work on and lots of deadlines to meet, | 0:52:49 | 0:52:52 | |
so I think anything that could help me along with that, | 0:52:52 | 0:52:55 | |
I would be well up for it. | 0:52:55 | 0:52:57 | |
-Are you on drugs right now? -Before you say that... No, I'm not. | 0:53:06 | 0:53:10 | |
Why are you not on drugs right now? | 0:53:10 | 0:53:12 | |
I did mean that at the end, that I am tempted by it, | 0:53:12 | 0:53:14 | |
because Barbara Sahakian, who you saw there, has published something recently where | 0:53:14 | 0:53:19 | |
she has indicated that one of the drugs we talked about, modafinil, a drug for narcolepsy, | 0:53:19 | 0:53:24 | |
it's been tested for that, it's safe for that, but that drug | 0:53:24 | 0:53:27 | |
can make you focus on something you might not find too interesting. | 0:53:27 | 0:53:31 | |
You can focus on it for several hours, get the job out of the way. | 0:53:31 | 0:53:34 | |
There are loads of things where you just want to get something out of the way. You procrastinate. | 0:53:34 | 0:53:39 | |
There is something important to be said about all this. | 0:53:39 | 0:53:42 | |
These drugs are not illegal, but we do not know how safe they are. | 0:53:42 | 0:53:46 | |
You have to be quite careful when thinking about what to do in terms of taking them. | 0:53:46 | 0:53:50 | |
You can't just jump in and take them yourself. | 0:53:50 | 0:53:53 | |
Fine. I can understand the ethical debate about, we don't want some students | 0:53:53 | 0:53:58 | |
who are on smart drugs to be competing with those who are not. | 0:53:58 | 0:54:02 | |
-But in everyday life, I wouldn't mind my air-traffic controller being... -On drugs? | 0:54:02 | 0:54:09 | |
On drugs. On the drugs that will make them | 0:54:09 | 0:54:12 | |
better at that kind of shape recognition. | 0:54:12 | 0:54:14 | |
A surgeon or whatever... | 0:54:14 | 0:54:15 | |
It sounds great until they are forced to do that, | 0:54:15 | 0:54:18 | |
so what if you have a situation where lots of surgeons are doing it and | 0:54:18 | 0:54:22 | |
then the hospital says, "If you want to be a surgeon, | 0:54:22 | 0:54:25 | |
"you have to take these drugs?" That is more dodgy. | 0:54:25 | 0:54:29 | |
There is the question of exams. | 0:54:29 | 0:54:31 | |
You may want to keep everyone on the same level. It is fairer that way | 0:54:31 | 0:54:34 | |
because what if, in the future, | 0:54:34 | 0:54:36 | |
this stuff is available and only the rich people can afford it | 0:54:36 | 0:54:39 | |
so they become cleverer or whatever else? | 0:54:39 | 0:54:41 | |
But what would you have? | 0:54:41 | 0:54:42 | |
Would you have a drug-testing lab at the start of every exam? | 0:54:42 | 0:54:45 | |
-A little fingerprinting pinprick or something like that. -Everyone has to pee into a cup before they... | 0:54:45 | 0:54:52 | |
That is the future. A little pinprick to see whether you're on... | 0:54:52 | 0:54:56 | |
Depending on how many buckets they have taken from the exam room. | 0:54:56 | 0:55:01 | |
There are so many enhancing things that you can do | 0:55:01 | 0:55:04 | |
that cost nothing at all. | 0:55:04 | 0:55:05 | |
For example, exercise is really good for the brain. | 0:55:05 | 0:55:08 | |
For example, sleeping is very good for the brain. | 0:55:08 | 0:55:11 | |
You're doing all these things... and fairly and easier. | 0:55:11 | 0:55:14 | |
Banging on about exercise. | 0:55:14 | 0:55:16 | |
-Like that's the answer to anything. -..You have a very good diet. | 0:55:16 | 0:55:20 | |
Stop it. We are not dealing in science fiction here(!) | 0:55:20 | 0:55:25 | |
Diet, exercise and sleep(!) | 0:55:25 | 0:55:28 | |
We're going to scan across the room. | 0:55:28 | 0:55:30 | |
How many of you would take smart drugs? | 0:55:30 | 0:55:33 | |
About 60% of the room. | 0:55:37 | 0:55:39 | |
How many would approve of other people taking smart drugs? | 0:55:39 | 0:55:43 | |
That's interesting. Different people raised their hands there. | 0:55:45 | 0:55:48 | |
Earlier, Tali told us about her work on optimism. | 0:55:48 | 0:55:51 | |
We're going to bring her back in. Tell us about the results. | 0:55:51 | 0:55:55 | |
It is assessing a predetermined bias towards optimism in people. | 0:56:01 | 0:56:07 | |
The puzzle was, how do we maintain these positive expectations, | 0:56:07 | 0:56:11 | |
because we get information that is discouraging all the time? | 0:56:11 | 0:56:16 | |
Our process was that | 0:56:16 | 0:56:17 | |
we must learn more from good news than from bad news. | 0:56:17 | 0:56:21 | |
So we go throughout life learning more from positive information than | 0:56:21 | 0:56:24 | |
negative information, that will create this biased view of the world. | 0:56:24 | 0:56:29 | |
-So we put together a study. -You tested all of our reporters. | 0:56:29 | 0:56:32 | |
Helen, Mark and Alok are there. All three of them did this. | 0:56:32 | 0:56:37 | |
-Were the results normal? -Two of them look normal. | 0:56:37 | 0:56:41 | |
We can show it on screen now. | 0:56:41 | 0:56:43 | |
We have two normal individuals on the left. I say normal, you know! | 0:56:43 | 0:56:47 | |
They act like normal individuals, learn more from good than bad. | 0:56:47 | 0:56:52 | |
The candidate for the magnetic hat is M3. | 0:56:52 | 0:56:57 | |
This doesn't mean anything. | 0:56:59 | 0:57:02 | |
80% of the people show the effect, 20% don't. Not all 20% are depressed. | 0:57:02 | 0:57:06 | |
There's not anything wrong with them. | 0:57:06 | 0:57:09 | |
If I had to choose which one of the three | 0:57:09 | 0:57:11 | |
was most likely for the bad news, | 0:57:11 | 0:57:13 | |
would it be the happy smiling one who has done the experiments, | 0:57:13 | 0:57:17 | |
the one who has been all round the world | 0:57:17 | 0:57:19 | |
looking at different treatments, or the one who wanted pandas to die? | 0:57:19 | 0:57:23 | |
-And who's sat here. -I know. Is that Alok? | 0:57:24 | 0:57:28 | |
I thought the same thing when I saw it. | 0:57:28 | 0:57:31 | |
Maybe it was a panda dying. | 0:57:33 | 0:57:35 | |
In fact, it was the guy who blended a dog's brain a few minutes ago. | 0:57:35 | 0:57:40 | |
-With the flowery shirts and the cheery demeanour? -Yeah. -That is Mark. | 0:57:40 | 0:57:45 | |
Are you OK? You are not feeling down about things? | 0:57:45 | 0:57:47 | |
I'm an emotionally scarred individual, that's clear, as you can see. | 0:57:47 | 0:57:50 | |
I don't think your flowery shirts are hiding anything any more. | 0:57:50 | 0:57:54 | |
We want to thank all our guests. As ever, our reporters - | 0:57:54 | 0:57:57 | |
Alok Jha, Tali Sharot and Mark Miodownik and Helen Czerski, | 0:57:57 | 0:58:03 | |
our special guest Jessica Hynes, | 0:58:03 | 0:58:06 | |
and our science guru Uta Frith, ladies and gentlemen. | 0:58:06 | 0:58:09 | |
There is so much we have learned. | 0:58:12 | 0:58:15 | |
We have learned how to move things with our minds, that you can | 0:58:15 | 0:58:20 | |
disguise a fair amount of depression | 0:58:20 | 0:58:22 | |
using only a flowery shirt and some Polish vodka, | 0:58:22 | 0:58:24 | |
and we've learned that Alok Jha is on smart drugs. | 0:58:24 | 0:58:27 | |
But I am naturally optimistic and I think he is going to beat it. | 0:58:27 | 0:58:30 | |
That is all from us tonight on Science Club. We will see you again. Good night. | 0:58:30 | 0:58:34 | |
MUSIC: "Crazy" by Gnarls Barkley | 0:58:36 | 0:58:39 | |
Subtitles by Red Bee Media Ltd | 0:58:55 | 0:58:58 |