These are very unique times for brain research. The aperitif for the course will thus highlight the present “brain-excitements” worldwide. You will then become intimately acquainted with the operational principles of neuronal “life-ware” (synapses, neurons and the networks that they form) and consequently, on how neurons behave as computational microchips and how they plastically and constantly change - a process that underlies learning and memory. Recent heroic attempts to realistically simulate large cortical networks in the computer will be highlighted (e.g., “the Blue Brain Project”) and processes related to perception, cognition and emotions in the brain will be discussed. For dessert we will deliberate on the future of brain research, including the questions of “brain and art”, consciousness and free will. For more information see the course promo below and read “About the course.”
The Brain Learns
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Do curso por Hebrew University of Jerusalem
Sinapses, Neurônios e Cérebros
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Neurons as Plastic/Dynamic Devices
This module discusses "Neurons as plastic/changing devices". Probably the most unique aspect of the nervous tissue is its amazing capability to constantly and adaptively change in response to a challenging environment; this capability enables us to learn and to store memories. We start by a short discussion about the notion of learning in the brain and then highlight various mechanisms that support learning and memory – introducing the term ‘neuronal plasticity”. In particular “functional plasticity”, whereby the efficacy of existing synapses is changed as well as “structural plasticity”, whereby learning/memory processes are associated with anatomical changes - the formation of new synaptic connections and with neurogenesis – the birth of new nerve cells (yes, also in the adult brain). A mathematical model that captures some aspects of functional plasticity will also be introduced together with several new exciting experimental finding related to “neuronal plasticity”.
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Idan SegevProfessor
Computational Neuroscience
Okay, so welcome to the fifth lesson which
is actually trying to integrate data that you learned in last two lessons.
So you learned about the mechanism of the brain, about spikes, action potentials,
about synaptic potentials, about neurons, about anatomy, and today I would like to
connect with what you've learned to a very fascinating phenomenon.
Maybe the most fascinating phenomenon about the brain.
The fact that you learn, that you change.
Hopefully, during my talk, you will be different at the end of the talk.
What makes us change?
We call it plasticity of the brain.
So we are going to focus on neurons.
Particularly about neurons is plastic and changing devices of serving memory and
learning in the brain.
So I will start with some fast examples just to convince us all,
what we already are convinced with, is that we are a learning machine.
I'll give some fast examples.
I will try to discuss a little bit the purpose of learning, and in particular
I want to highlight a concept that is called the action perception loop.
I then will discuss plasticity in two aspects, what we call the functional
plasticity whereby there are no big changes,
anatomical changes, but still the nervous system does change functionally,
and so you can learn without anatomical changes.
And then we discuss structural plasticity, which really implies that there
are structural changes associated with learning and plasticity in the brain.
And I will end with some kind of a discussion, controversies,
interesting aspects about the brain, about memory.
For example, can we embed new memories in the brain?
Can we copy?
Can we read out memories like a disc and key?
Is it reliable?
Can I trust memory?
So this will be the ending.
But before going into the memory aspect of the brain,
I would like to highlight to show you something that happened last week.
And so my role is also to introduce to you fascinating aspects of the brain.
And so I want to
show you a new technology that was just published last week in Nature.
The technology is called the Clarity Method.
It's a very beautiful method,
developed in the lab of Karl Deisseroth, in Stanford, and his team.
And the idea is to develop methods to make the whole brain,
of a rat, of a mouse, hopefully of human, completely transparent,
which will enable us to look into the brain in a very new kind of way.
So here is this movie from Nature.
>> We're heading into the center of a mouse's brain, into the hippocampus,
where memories are formed.
>> Look how beautiful the brain becomes when it's transparent.
>> Looking up, you can see neurons projecting to the surface of the brain.
>> So this is going up, so to speak, to this first surface of the brain.
>> This is the work of Karl Deisseroth and his team at Stanford University.
By making the entire brain transparent,
they were able to image it using a light microscope.
They call the new technique Clarity.
>> Clarity, the brain becomes clear.
>> [MUSIC]
>> Existing techniques for studying the brain's wiring are often limited to
looking at small volumes of brain.
>> So usually you can look at very, very small region.
>> Of interest.
>> Now you can look at the whole brain.
>> You can label lots of molecules in whole brains.
>> In Clarity, you can label lots of molecules in the whole brain.
[MUSIC]
So, how do you make a brain transparent?
>> That's the new technique, how to make it transparent.
>> The thing that obscures the view is fat.
Lipid layers surround each cell.
To remove them without destructing the cell structure, the team
used a hydrogel to create a mesh to hold the rest of the components in place.
Then they can clear away the fat.
This is a mouse brain before, and after.
>> That's before.
That's after.
Completely transparent. >> The brain is now transparent to light,
but it's also permeable to molecules,
which means scientists can add molecular markers to highlight specific features.
>> Quite amazing.
You can continue marking the brain, staining the brain with different stains
so you can see red cells and blue cells, regions.
>> In this one millimeter block of hippocampus, excitatory neurons are green,
inhibitory neurons are red, and cells called astrocytes are blue.
>> So, we already know what inhibition excitation is.
So here are the excitatory and inhibitory cells.
Red and green.
[MUSIC]
The technique works in human brains, too.
This is a chunk of the frontal lobe of a 7 year-old boy who had Autism.
It's possible- >> This is of course, a dead tissue.
>> Nerve projection through a forest of the cells.
[MUSIC]
>> We can see these unusual structures here.
>> When the team looked closely in one layer of the cortex.
>> Here.
>> They noticed ladder like patterns when neurons collected back to themselves and
to other neurons.
>> This is very unusual in the regular brain.
Maybe it is connected to Autism.
>> Animals with Autism-like behaviors.
Being able to analyze brain structures like this, and
match them up with molecular information,
could help neuroscientists uncover how changes to the brain underlie disease.
[MUSIC]
And it's- >> Very beautiful.
Very beautiful.
So it's a new technique.
As I said, it's developing very fast in the whole field, the Clarity Technique.
So, let's go back to what I want to focus about today, memory and
learning in the brain, and let's start with Aristotle who already, long time ago,
2500 years ago or so, already said the following.
We have in the next place, he says, to treat of memory and remembering,
considering its nature, its cause, and the part of the soul, we
shall say the brain today, the part of the soul to which this experience as well,
it's recollecting, recollection belongs.
So we struggle, although we realize that one of the magical things about the brain
is really its capability to modify itself, to adapt itself,
to learn constantly, all the time new things, also forgetting certain things.
We've discussed also forgetting.
It's part of the brain.
It's a very unique kind of machinery that tends to change constantly while, for
example, now, you listen to me.
So of course, the underlying question, the big question,
is what changes in your brain when you learn?
What changes in your brain that enables it to be so fascinating
in its capabilities to learn and perform so well, gymnastics, physics,
football, and every other learning that we are capable of doing.
For example, the following example.
So I show you a picture and immediately, automatically,
I'm sure that you see a tree.
It's a tree.
How do you know that it's a tree?
You know it's the tree because you remember, since you were very young,
that your parents told you that this is a tree.
A tree looks like this, there is the stem, there are the leaves, and so forth,
it's a tree.
But now I'm teaching you something else.
I'm showing you that it can be also interpreted.
The same picture, the same image can be also viewed as a face.
So, here is the eye.
Here is the nose.
Here is the mouth.
And you can see a ear here.
I hope you can see, that you can see this same image.
Once, automatically, as a tree.
And once, after I'm teaching you,
that you can really interpret the same thing as a face.
You can see suddenly a nose, and a mouth, and an ear.
A face looking this direction.
Now you see it, hopefully, and you cannot get rid of it anymore.
You cannot get rid of it.
So I was your teacher,
I taught you that you can interpret the same image differently.
From now on, your brain has changed, and
it now embeds this image as a face also in addition to a tree.
Nothing have changed on your image on your brain, so
it's the same image goes into your brain.
It's just interpretation of the image
now was made differently because I was your teacher for this example.
Or, a very classical example, I don't know if you can immediately see it.
Some people see it, some not.
Some people see it as a cow, some not.
So, let me teach you that there is a cow here.
So, this cow looks at you.
This is the right eye, this is the left eye.
This is the nose of the cow.
This is the right ear.
This is this part.
So, can you see a cow?
So suddenly I taught you that this very vague kind of image, very obscure kind of
image, can be interpreted using your memory if you know what cows are.
Because if you don't know what cows are, of course, it means nothing to you.
But since you have a memory of cows, this can be interpreted now, as a cow.
So I'm using your memory, I'm igniting your memory just by showing you a very,
very sparse image.
Which could be something maybe different, but now because you know cows and
I'm telling that you can see it as a cow, you see a cow.
I'm using your memory.
I'm teaching you.
From now on, for many, many years, you will see this image in books or
in movies, you will remember that this is a cow.
So, within a few seconds, I was a teacher for cows.
You became well acquainted with this figure from now on.
So what has changed in your brain now?
Something must have changed.
Otherwise you would not remember it is a cow.
Now or in the future.
I want to also show you a fascinating example of using memory for the blind.
So this is Professor Amir Amedi of the Hebrew University.
And he's interested in a very fascinating aspect of brain
research which is called sensory substitution.
You are all well acquainted with the fact that blind people can learn to
use another sense, touch, touching,
somatosensory sense, in order to develop the capability to read Braille.
So this is the substitution of the normal visual capability to see
letters, to see writings, with touch.
But can we use another sense, that's the question of Amir Amedi.
Can we use hearing to replace, to substitute for blindness?
So the idea here was to project, into whatever you want to see,
a signal that will eventually come back to your ears.
And for each aspect of the word, there will be different sound.
So, here is the idea.
The idea is really to teach, using our capability to learn,
to teach the blind person that this line has a particular sound.
This other line with this orientation has a particular sound.
A combination of them has a particular sound, so
you can reconstruct the auditory word, the visual word using audition.
Just for an example, so this line, this line has this sound.
You can associate this particular sound with [SOUND].
Another line, another direction, another orientation.
[SOUND] Has a different sound.
[SOUND] So very fast, the blind person learns to associate,
to learn that a particular angle is associated with
a particular sound, or a combination of them.
So for example, [SOUND].
Okay, so you can now associate this [SOUND] to a line,
to perpendicular line plus a circle.
So you can construct the word, you can construct faces with lines and
with circles, or anything else.
You can reconstruct it from basic features.
That's what the blind is learning to do.
And I want to show you a movie, short movie, about the blind person,
a blind woman, who is trying to read the word, Aba, in Hebrew.
So this is A-B-A, Aba.
You see, this is the blind person, there is a scanning, and she hears something.
>> [FOREIGN] >> She found, she saw, she saw, she saw.
The word Aba through her ears.
This is a sensory substitution, but not only a word, she can go in her
room now with this new system, very new system, and she can detect,
just by listening to sounds, she can detect her shoes.
Because shoes are built from circles, the opening of the shoe,
from line, so she can reconstruct the word, sensory substitution.
This is learning.
Very fast, the blind person learns to see through his or her ears.
So learning is so fundamental, learning is so important.
Learning is so basic, but
let me give you a few remarks before going into the mechanism of learning.
Mark number one is that one of the major,
if not the main purpose of the brain,
purpose of learning, is to be able to predict what is coming.
So, you learn, you learn, you learn.
You are able to predict what should be the next move, for example.
Or you can predict, in this case, what should be the next
physical move when you are Nureyev who dances so well.
After so
many years of learning, he becomes such an amazing, genius expect in dancing.
He can predict what out will be the outcome of a particular gesture,
of a particular movement.
You cannot resist looking at it for a second, the Swan Lake by Rudolf Nureyev.
This is all heavy learning, very, very heavy learning.
And eventually you become an expert through changes in your brain that enables
you not only to perform so well but
also to predict what would be the outcome of a particular movement.
Will you fall like this, will you jump like this?
And all of us are doing it all the time.
We are not dancers like Nureyev but
we are doing other things all the time and we learn all the time.
Okay.
We also need learning to categorize the word.
During learning, you know that the word after learning is built from faces, and
from cows, and from trees, and so forth.
So to categorize the word is very important for us, and
then we create consensus between us.
We generate some kind of consensus that this is a face.
And this is a tree, so when I'm saying tree, we wanna teach you something we
agree between us among us all, 40,000 students that may listen
to the course just now, that this a face and this is a dance and this is chess.
This is all a result of learning.
So this is comment number one.
I want also to show you something that influenced myself a lot very much so
when I was a student because when I was a student,
suddenly I learned something very new.
I hope you learned something very new just now because of this very simple
experiment by Held and Hein from '63.
A very classical, very influential, very simple, but very dramatic experiment.
So here is the experiment showing basically that to see,
in order to learn to see, you have to act.
Okay, this is what's called action perception.
You have to act, there is an action and
then you are capable to see, to interpret perception correctly.
So this is a simple experiment.
Here are two cats, kittens that were born recently.
From the day they are born, they are put in this kind of machinery.
One cat, we call it the passive cat,
is incapable of putting his legs outside of this little basket.
The other cat, we call it the active cat, is identical twin to this cat,
but he can put his legs, so to speak, outside of the basket, and so he can walk.
And, then, the whole structure is now revolving due to the activity of this cat.
So, this is the active cat.
This is the passive cat.
For a few hours every day, they experience the visual world in this system.
He is moving, and he is being passively moved due to this activity.
But eventually they, so to speak, experience the same environment.
This is in light, and then they go in dark to play, to sleep, to eat.
So this is the only part where you have vision.
The amazing thing, I was very amazed by the outcome of this simple result.
The amazing thing is when you take them after two weeks or
three weeks out of these baskets.
Enable them just to walk freely in a regular room or
environment, this cat behaves like a completely blind cat.
He behaves as if he doesn't see.
He goes into the wall.
He falls on stairs.
He is a functionally blind cat.
Although nothing is wrong with his brain,
he is actively, functionally blind.
The other cat behaves normally, completely normally, he sees the world.
This is quite shocking, isn't it?
Because the two cats are originally identical, they are the same genetically.
They are fine.
We could have replaced the two cats, and
this one would become a seeing cat, and one cat would become a passive cat.
So this means, here, that the fact that this cat was moving physically and
this cat was not moving physically, was passive during the visual experience,
eventually somehow the brain of this cat cannot interpret
the visual world and behave like a blind cat.
And this cat, because he was moving,
because the movement itself generates changes in the world.
And he was the one, the cat, it was the one who by moving,
changes also the visual experience.
So there was a correlation between the fact that this cat moved forward and
backward, to the side, to the other side.
And so his visual system, correlated with the fact that he moved,
together enabled him to generate a correct, so to speak,
perception of the world.
This cat was just passively moved.
There was no correlation between its own activity and the visual world movement.
It could not integrate movement and
visual input to form a coherent image of the world.
It could not.
And the amazing thing also is that this cat remained blind all his life.
It could not relearn, because there is a critical period, apparently,
in the case of cats whereby you have to both move and see.
Or both move, and experience vision.
When vision and action goes together, like in the case of this cat, then you see.
So, seeing is not passive.
We are not things in the world.
We are not a camera.
We are active machine that learns to interpret the world.
And this interpretation becomes correct interpretation only if you
move at an early age.
Of course I don't need to move now, or you don't need to move now to see me.
But you should've been moving then in order to see me now.
This cat never sees anymore.
So, seeing depends on learning, like any other action.
[FOREIGN]
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