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.”
Neuron Type
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來自 Hebrew University of Jerusalem 的課程
突触，神经元和大脑
700 個評分
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從本節課中
The Materialistic Mind - Your Brain's Ingredients
This module's purpose is to acquaint you with "The materialistic mind – your brain’s ingredients". You will become intimately acquainted with the beauty and variety of neurons – the elementary building block/microchips of the brain. We will highlight a big controversy between two great anatomists (Ramon y Cajal and Camillo Golgi) who both received the Nobel Prize in 1906. They asked whether the neuron is a separate “independent” unit (like other cells in other tissues) or whether it is part of a continuum? We will next discuss the neuron as an input-output device and highlight a key property of the nervous system, namely that neurons connect to each other via a wonderful devise called “synapse”.
與講師見面
Idan SegevProfessor
Computational Neuroscience
Okay, so, I spoke about a neuron, I spoke about the dendrites.
I already mentioned two general types of neuron, the spiny and the smooth.
I already spoke about two different types of neurons when I spoke about
functionality. Because I spoke about excitatory neurons.
And I spoke about inhibitor in neurons. So there are many ways to classify
neurons. And speaking about neuron types.
But maybe before going into the neuron types.
Let me just mention, something that I should have mentioned before.
That of course in our brain there are so many neurons, so many neurons.
And the last counting of how many neurons you have in your brain is very, very
close to 100 billion, or 100 million. Meaning 10 to the power of 11.
Huge number, huge number of cells. In very many regions.
Some more dense, some less dense. But you know that your brain is built
from so many, many, many elements. 100 billion of cells.
And so, can we speak about each cell as a separate, individual, different not in
terms of not being connected, but type. Or can we speak about classes of cell
types? Like, when you go to the jungle, you say,
this is one class of tree. This is another class of tree.
So we can often do the same thing in terms of types, or classes of neurons.
We can classify neurons by anatomical features.
As I said, you can use the anatomy of the dendrites.
The shape of the dendrite, to classify neurons and say this is cerebellar
Purkinje cell. This is parameter cell from layer 5 of
the neocortex. This is parameter cell C, from CA1 of the
hippocampus, and so on. So, this is anatomical features using
anatomical features to classify different cell types.
We can also classify neurons in terms of functionality, as I said.
I can, this neuron is excitatory, because it sends excitation.
It wants to activate the post synaptic cell or this cell is inhibitory.
This is another type of functional classification.
And this is actually the broadest classification, functional
classification. I can say about the brain.
That the brain consists of two type of cell, in terms of function.
One type tries to inhibit the brain, to control activity, reduce activity.
And another type, the excitatory, tries to excite the brain.
And it is indeed the balance between the two, in your brain.
The balance between excitation and inhibition is really what makes the brain
functional. You don't want too much excitation.
It may cause epilepsy. You don't want too much inhibition
becasue the brain then is not active, it doesn't function.
You all the time seek for a balance. Not a very interesting puzzle, the
balance between excitation and inhibition.
But this is the two general types, excitation, inhibition.
I can also classify neurons by their electrical characterization, or
characteristics. Some as you will see.
Some cells like to fire more spikes. Some cells like to fire less spike.
And also with the different patterns of activity.
So you can classify neurons by electrical types.
Morphological anatomical types electrical types.
Functional types. I can also classify neurons by their
chemical, characteristics. What chemicals consist of a particular
cell type? And because today we can use chemicals,
stain chemicals. We can see that this cell consists of
this type of chemical. And another cell of this, another type of
cell eh, chemical, and so on. So, chemical characterization, and of
course you can also use the gene expression.
Which genes are expressed? In what type of cell?
So I can ask the general question, how many cell types we have in the brain?
Is each cell a different type or can I say this is pyramidal cell?
And all of the pyramidal cell in layer five are the same.
This cell, is layer two, three[INAUDIBLE] cell , this cell is layer, one, and so
on. Can I use this or can I speak about each
cell separately. This is an interesting work.
It's not final. We think that our cortex for example,
depending on which criteria now, you're using for typing the cells.
For classifying the cell, probably have several thousand cell types.
Again depending on the typing of the cell.
An example, I take a network in the cortex, just examples of several cell
types. Immediately you see this big beautiful.
Layer five pyramidal cell dendrites with the blue axons that may go out, they do
go out from this region to other regions. And you can see all this local neurons
with a dendritic tree red and the axonal tree locally.
So this is indeed, another general characterization of cell types.
Usually, we say that this big excitatory pyramidal cells.
And other excitatory cells, where they have this axonal projection, out of this
local region. We call them projection, or principal
neurons. Because they are principal in the sense
that, they send from local processing outside to other regions through long
Axons. And we call other neurons like this one,
for example, or this one, Interneurons. Usually, inhibitory neurons enter neurons
because there are inter, they are inside the region.
And the[UNKNOWN] tree only talks locally. So here is another characterization.
Usually the excitatory cells in the cortex are principle projecting cells
outside of this region. And the inhibitory population, this one,
and this one, and this one, are local, are inter neurons.
So principals versus interneurons. It's an important classification to try
to understand the system of this local inhibitory control.
And more globally sending information to other regions.
Excitatory information. And if you zoom in, just recently, there
was an attempt to classify inhibitor in neurons into classes, into types.
A very recent work from 2013, by Javier DeFelipe, the great Spaniard anatomist.
I sometimes call him the grandson of[UNKNOWN] although he's not a real
grandson, but intellectually. And they, a group of people sitting
trying to decide, based on morphology. How many neuron, inter-neuron types?
How many inhibitory types you have? You can see that they are using
the[UNKNOWN] tree as, as a signature for time.
So you will call this beautiful[UNKNOWN] tree a chandelier cell.
'Cuz it looks like a chandelier, like a chandelier.
And you will call this cell basket, because it generate basket, like a basket
connection through the axon, in this case.
Or in this case, they use the[INAUDIBLE] structure that is en-, en-, engulfing the
post-synaptic cell like this, like baskets.
The horse tail. This is this is another, another cell
type and so forth, the Martinotti, so you can see that you can start to make some
order. It's not a complete jungle in the sense
of types, for some reason that is not completely clear, absolutely not yet, why
do we have the different types? Why don't we have just one inhibitory
type, one excitatory type, and finish with it.
Why do we need all these little characters?
Each one with different shapes. Each one makes contacts to different
direction, and with different post-synaptic cells.
It's not a jungle. It's an orderly system that is doing
function. Speaking, talking, feeling.
So these are the basic elements in the inhibitory system.
We can do the same for the excitatory group of cells.
One is called pyramidal cell layer five. Another one is called[INAUDIBLE] layer
four. So I'm not going to elaborate on that.
So this is more for logical characterization.
Or classification. Using morphology as a parameter for
classification. But I can also use as I said before,
electrical based classification, so based on this spiking part of the neurons.
So for example, if you record from one neuron.
The spikes of one neuron, you see that one neuron is doing[SOUND] very
intensely. If you recall from another neuron it, it,
it fires spikes but in a sparse kind of way.
We call it stutterer because it stutters,[SOUND] a stutterer.
Another stutterer. So, there are different types based on
the electrical activity. And each one of these cells has
electrical character. This type of cell wants to do[SOUND] and
then accommodates slower and slower. So, very fast at the beginning, and then
slower here. This is a regular firer.
It fires very regularly. Fires spike after spike with very regular
intervals. So we'll call it a regular firer and so
on. And so, so this characterization which is
independent of the morphology ju-, the morphological character, is just based on
how you speak electrically. I like to speak very strongly fast.
I like to speak more regularly. I'm a solid, i'm a solid person.
This one starts very fast and then becomes tire a little bit and then it
finds less. This one is completely started it doesn't
succeed to speak continuously so it spies like this .
And there's must be some functional meaning to all that.
Which again we don't completely understand.
But it's important to see that inside this spiking mechanisms which again, we
should speak a lot about this spiking mechanism of cells there are different
types of spiking mechanism. This 1, this 1 and this 1.
So it can categorize the cells as they did here through this blue brain data
base. We can see different types of sales.
