Tutorial: Basic Neuroscience (46:04)
Date Posted:
August 11, 2018
Date Recorded:
August 11, 2018
CBMM Speaker(s):
Francisco Flores All Captioned Videos Brains, Minds and Machines Summer Course 2018
Description:
Francisco Flores, MIT
Download the tutorial slides (PDF)
Also see the Neuroscience tutorial in the Brains, Minds, and Machines Summer Course on MIT OpenCourseWare.
FRANCISCO J. FLORES: Welcome to the tutorial Neuroscience. I already introduced myself yesterday, so today I will skip. And let's go right into the topic.
So basically, main question will be what is neuroscience? And one of the main books on the topic which is the book written by Kandel, Schwartz, and Jessell says that "neuroscience is the study of the processes by which we perceive, act, learn, and remember." OK? Well this is a nice and catchy definition. To me, it's not really what captures the essence of what neuroscience is.
So I want to make or propose a very simpler definition, that "neuroscience is the study of the nervous system." Basically, that's what it is, and that's the basic. And everything else comes from that. So that's me saying it today.
Now, what is the nervous system? That's the next question. Now, starting from an evolutionary point of view, most living organisms have a sensory surface and a motor surface. So they have some ways to sense what's going on in environment, and some ways to act on what's going on in the environment.
This is true for bacteria, protozoa, animals, plants. And I didn't write all living systems, because I'm not really sure that all of them have it. But I'm pretty sure that most of them have this sensory and motor surfaces.
Now, some multicellular organisms, which we typically call animals, develop a neuron-based link between the sensory and motor surface. And we call this link the nervous system. So basically, the nervous system is a neuron-based system that allows animals to integrate sensory and motor processes in a quick and fast manner, which is basically what I just said before.
Now, let's look at a couple of examples to introduce the topic of sensory-motor integration. This is a unicellular-- not an animal, but it's a proto animal, a protozoa.
And the first video-- and let's see if I don't make the same mistake as the third speaker yesterday. Oh yeah, It works. OK. So maybe you can see there, it has some cilia that allows these guys to swim.
So if we go to the next video-- not that one, but this one. So here, it's coming, it touches an algae, and then it changes direction. So you see? Touches, changes. Touches, changes.
So as you can see, this guy is perfectly capable to perform sensory-motor integration without having any need for a nervous system. So what this guy has is a protein, which is the protein that makes the cilia.
This protein, when it touches something, it bends the confirmation of the protein. That mechanic force gets transmitted to the base of the protein, produces a change in conformation in the base of the protein, which makes the protein rotate on an opposite direction, and the animal change direction.
So sensory-motor integration happens all within a single protein. Really fast, but also really simple. I mean, you can not really get much more complicated than that particular behavior, like avoiding objects. But again I want to emphasize that there's no real-- is not absolutely necessary to have a nervous system in order to have this sensory-motor integration process.
Let's look at something even simpler than the protozoa, a bacteria. So what you see here is a sugar crystal. And then, you will see how the bacteria appear from the periphery are swimming around.
This one has music, forget the music. So the guys are coming. You see it? At the beginning, it's kind of random. But then, at some points, you notice that they start gathering around the sugar crystal.
So now in this case, what these guys have is a protein that senses the sugar gradient that is around the sugar crystal, the sugar that is dissolved in the liquid around the sugar crystal. And that protein, through a metabolic cascade that goes through the bacteria, makes the flagella, or the cilia in this case that is in the back of the bacteria that helps the bacteria swim, move in the direction of the sugar crystal.
Again, sensory-motor integration this time is not happening within a single protein. But there is a protein, there is the whole body of the bacteria that acts as like the integrator. And then, there is the motor surface, that is another protein, that changes the direction of the bacteria towards this food source in this case.
Now, let's move into the animal kingdom. So this, what you see here is a hydra. A hydra is the simplest animal that has a nervous system. Of what we could call a nervous system. It has neurons really, not a nervous system.
So here is hydra under some-- I forget the name of these guys, like crabs. Oh, hydra catches one and brings it to the mouth, and is going to eat it at some point. Now, let's take a closer look at how at hydra looks.
So this is hydra. Basically this is the body, these are the tentacles. This is the hypostomes, which is basically the entry hole and the exit hole at the same time. And this here is a cross-section of the gastric region of the hydra, the body of the hydra.
There is an external epithelial, an internal epithelial, and here are the neurons. So basically, here you have a neuron which is a sensory neuron, that as you can see is directly connected to the muscle of the hydra. So here, you have a single neuron doing the sensing part and affecting the motor action of the hydra.
There are other neurons that sense how these muscles move, connect to the neurons that are responsible for contracting the other muscles that are in the inner part of epithelium. And this is how, basically, hydra make all of the movements that is has.
But it has these very rudimentary motor nervous system, that sometimes, only a single neuron is doing the whole integration. But there's also a couple other neurons, so maybe you have two neurons, or maybe as much as three neurons doing the whole integration of the sensory-motor process.
This is basically just a close-up of the same idea. Sensory neurons contract the muscles, affect movement. These neurons sense the movement of the muscles, sends that information to the other neurons that are in the inner part of the hydra. And the muscles can move in a concerted manner, and hydra can have these behaviors, like catching the prey and eating it.
And also digesting it. Because remember that this is the gut of the hydra. Just like us have neurons in the gut that actually do the same behavior. Hydra is basically the same.
Now, let's take a closer look to this particular cell that we call the neuron. So here is the neuron in a schematic. Neuron, typically we can divide it anatomically in several parts.
The first one from this point of view will be the dendrites, which are projections that come out of the body of the neuron. Then you have this soma, which is the-- will be like the cell part of the neuron. All cells have a soma. And of course, has a nucleus inside.
Then the neuron has what is called an axon, which is like a cable that the neuron has, that allows the neuron to send signals to other neurons. And then we have the terminals, the axonic terminals of the neuron, which are the ones that are going to affect the communication on the next neuron. Or in the muscle, depending on what kind of neuron this one is.
Now, we can also have neurons that have what is called Ranvier nodes, which are cells that wrap around the axon and provide some insulation, electrical insulation. So that makes that it is possible that the neuron can send electrical signals in a faster way than if you didn't have this Ranvier nodes.
Now this is how a real neuron looks. This is from cortex of a mouse. The neuron is stained with GFP, so you can see this fluorescent green. And it has the same components. These are the dendrites, here you can see the soma. And here is the axon, like very-- how to say, thin, compared to the dendrites which are typical way thicker.
Now other than the anatomical view of the neuron, we can also have a functional view of the neuron. Which in this case is the sensory part of the neuron, which are the dendrites of this. And the soma, which sense what signals are coming from other neurons or from environment.
You have an integrative part, which is the part of the neuron that decides whether a signal is going to be transmitted to the next neuron through the axon. You have the conductive part, which is basically the cable that the neuron uses to send signals to the neurons or to the muscles.
And then finally, you have the motor part of the neuron, which is where these vesicles are mobilized and excreted. And that basically goes to build that chemical signal for the other neurons.
So you can see, the neuron itself is affecting these sensory-motor, just like bacteria did and protozoa. If you can imagine, you have heat sensing, then there is some integration process here. A signal is sent, and then there is a motor action. Which is basically at-- well, mobilization of vesicles that contain chemicals that signal to other neurons.
This is the most typical view of a neuron like the one that I showed before in the mouse, but there are great diversity of possible neuron shapes. Typically, here you only see somas. For example the one in the mouse, here is the soma, and these are than dendrites. You typically don't see the axons because those are thin and way more difficult to stain and to visualize in slides.
But there is a great diversity. For example, this one is particularly beautiful, the Purkinje cell in the cerebellum. Here is there soma, and this is all the dendritic arbor of this particular neuron.
But they all basically do the same. They receive some stimulus, they decide whether or not to transmit that signal. And then if they do, they will send a chemical signal to the next neuron.
Now, what makes the neuron special among all the other cells that animals have? Let's take a look at it. So first, let's take a look at the membrane potential.
So if we take a little piece of the soma of the neuron, what we will get a membrane, which is just like all other eukaryotic membranes. It's a bi-lipid layer, which you probably saw in biology class in even elementary school.
Now, let's make a thought experiment now here. So let's assume that we can have this bi lipid layer, in the middle. Let's assume that with some kind of magic, we are able to have only negative-charged ions on one side, which we will call the intracellular side, and only positive-charged ions on the other side, which we will call the extracellular side. OK?
Because this bi-lipid layer is very-- how to say, tightly packed and also highly phobic, especially in the middle, there's no way that these ions, which are like bigger typically, can cross through the membrane so they will be separated.
And basically, if you try to measure the difference in potential across the membrane, what you will get-- just like if it was a battery because basically that's what it is, you will get that the signal is zero, because there's no current flow. So you'll remember, by ohm's law, V equals I times R. In this case, I is zero because the ions cannot flow. So basically, V is zero, too.
Now, let's do some other magic trick and add a couple of very special, how to say, channels or ports. That one of these channels had the property that can only allow the negative ions cross through it. But it will not allow the positive ions cross to the other side. And then, another one of these channels has the property that will allow only the positive channels goes through it, but not the negative channels.
So if you do this and let time go by, you will see that one guy will cross here and then and other guys will cross here, just because of the electrostatic charges. So you see negative will try to go to the positive side, and positive will try to go to the negative side. So this is the electrical driving force behind it.
There is another force which I'm not really going to mention now, but that you should be aware, which is the chemical force. So basically, if you have a higher concentration of ions in this side, those ions will tend to go to the flow of lower concentration. But let's just focus on the electrical part for today.
Now you can imagine if you let this process be, at some point you will get into an equilibrium. With the number of negative charges here will equal the number of positive charges, and the same way will be true on the other side. And although there may be current flow, that current flow will be at equilibrium, so there will be no change or difference in the distribution of charges across the neuron.
So that also would be boring. The process will end there, and then nothing more will happen. So now you have to add another bit of magic, which is a pump.
Now this pump works against the electrochemical gradient. So what it's going to do, it's going to pick these positive guys, and going to bring them, the positive guys, here. And going to bring them back, where there is more positive charges. So basically, what they shouldn't be. And the same is going to be true for the negative ions.
And basically, when you have this combination of charge or ion-selective channels and pumps that work against the electrochemical gradient, you can establish a charge difference because you will always have more positive guys here and more negative guys here. And basically, if you measure the potential across the membrane, you will get, which is typical in a neuron, -65 millivolts. So this is what is called the membrane potential.
So all neurons, the potential across the membrane, if you measure it, is going to be around this number. Some might be lower, some might be higher. But this is the average number.
Now for this example, I have lied to you. It's not really how it works. And this is more of like the reality of the situation.
There's never any movement in the rest-- at least in the resting situation, there's never any movement of negative charge. There's only movement of positive charge. So basically, positive-- sorry, potassium positive ions tends to go out. And sodium positive ions tends to come in.
And the magic is done by the pump. So the pump moves three sodiums out, and two patassiums in. So it's always going to give this ever so slightly imbalance between the ions that across the membrane. So there will be a little tendency to have a slightly negative charge inside, in the intracellular space, and a slightly more positive charge in the extracellular space.
And this is basically how neurons keep the membrane potential across their membranes. The pump, of course because it works against the laws of thermodynamics, it needs fuel. And that fuel is obviously coming from ATP.
Now if we look at this point of view from how this works in time. So in this particular graphic, here they have amplitude, which is measured in millivolts, and this is just time. And this is going to represent some stimulus, idealized by current changes across the membrane potential of the neuron.
So if I do nothing then nothing happens, and the neuron stays at the resting membrane potential which is about -60 millivolts. Now if I introduce some positive current, the neuron it's going to de-polarize. which means that it's going to move towards more positive potentials.
We'll still be within the realm of negative millivolts, but it's moving towards positive potential. and that process is called the depolarization of the membrane. Or of the neuron, if you want. And we will introduce later the concept of an EPSP.
Now, when I stop my stimulus, the neuron re-polarizes, which basically means that it's coming back to the resting membrane potential. If I do the opposite and deliver negative current, the neuron will hyper-polarize. So basically, it will move away from the more positive potentials. And then as soon as I stop the stimulus, the neuron will re polarize again. And again, we'll go into where this could be called an IPSP a little bit later.
So now, this is what is called the passive properties of the neuron. So basically, the membrane potential is sitting at -55. And if things happen, it can move around the number, either de-polarizing or hyper-polarizing. But really, not much more than that.
So now, this is when it comes more interesting. The action potential, how does the neuron generate the action potential? The trick for the action potential is the existence of this voltage-gated ion channels.
So the ion channels that I mentioned before are all passive. There are just there and they let ions go through, depending on the characteristics of the particular ions and the particular channel. But still they are just holes, right?
Now these guys, the voltage-gated ion channels-- for example here, we have a schematic of the sodium voltage-gated channel. These are like voltage-sensors. So whenever they sense a particular change in the voltage across the membrane of the neuron, they are going to open, and they're going to let sodium come inside the neuron.
At some point when the voltage gets at a certain level, this channel will deactivate by this ball-and-chain mechanism. There is actually a ball-and-chain protein hanging from the channel, which is also a protein, that will block the channel. So basically, it will inactivate the channel.
And after some point as the voltage comes back to the resting potential, the channel will go back to the original state. Which was here in one, which is just closed channel.
So there are sodium voltage-gated ion channels and there are also potassium voltage-gated ion channels. And these are the guys that actually make possible the production, and the active production, of action potentials.
So let's take a look using more or less the same diagram as before. So here, we have amplitude in millivolts. This is the time. And here is some stimulus using current as an example.
I'm at zero, and then nothing happens. The neuron is at its resting potential. If I introduce a little bit of current, the neuron will depolarize, as we saw before. And if I do nothing else, the neuron will re-polarize again, and then we're back to the resting potential. Again, nothing much happens.
But if whenever I'm finishing the first stimulus, I deliver another stimulus on top of that which is larger, then the neuron will depolarize and depolarize again. And it's going to reach what is called the threshold, which is the voltage at which the ion channels open, the voltage-gated sodium channels open.
And at that time, a huge influx of sodium channels is going to come into the neuron. And the neuron is going to be really depolarized, and it's even going to-- see? On this one, it's going to go to positive potentials.
Now at this time, is when the channel, the sodium channel is going to be inactivated, you remember, by this ball-and-chain mechanism. And this is also the time when the sodium and the potassium voltage-gated channels are going to open, and there will be a potassium influx. And then, the neuron is going to be re-polarized again.
And after, it not only re-polarized, but it will also be an overshoot. It will be like an undershoot in this case, where it'll be hyper-polarized for a little period of time. And this is what is called the refractory period of the neuron.
So this time when the neuron is hyper-polarized, even if I deliver a stimulus it's going to be much more difficult to bring it to the threshold. So this is why typically, neurons cannot really fire on action potential immediately after they fire an action potential. There is a hard limit of one millisecond that they have to wait before fighting the next action potential. It's exactly because of this part here.
It also might vary across neurons. There is the absolute refractory period, which is about one millisecond, and there is the relative refractory period. So for example in this part here, it might be a little bit more difficult to find an action potential, but not impossible. So things can be a little bit more probabilistic there. But at least, this part is completely absolute.
And basically, this is how everything happens. This is how the action potential is produced, just in virtue of current changes, or a stimulus coming, or some light coming into the photoreceptors of the eye for example, and action potentials being produced.
If we go back to our schematic of the neuron-- and we said that the sensory part was here where the dendrites have been, the integrative part. Which, is where the neurons decides whether it's going to produce an action potential or not is here, which is called the axon hillock, at the very part where the axon starts and the soma ends really.
So this part here is really, really high-density of sodium voltage-gated channels. So this is what allows to integrate all the little changes in the membrane potential of the neuron. And if these changes at some point are high enough in order to activate these guys, this is just a massive response.
And the action potential is produced, and this will travel through the axon, up to the end of the axon and that axonic terminals. We'll go over what happens here in the couple next slides.
Now these was all really beautiful drawings, but this is how things look in reality. So these are three neurons that were simultaneously recorded, membrane potentials and action potentials in the cortex of an awake mouse. And you can see that things are way more noisier than what I was drawing before.
So here there are EPSPs IPSPs, everything is being mixed up. It's difficult to tell what is-- but for example, if you look at these three different neurons. Even though this guy was much more de-polarized here and maybe reaching -50, it didn't fire an action potential. But this guy actually did. So the threshold is also not an absolute number, it can change. And even can change across the same neuron, depending on the conditions there are at the particular time.
So another important part is how do the action potential propagates across the axon or through the axon? Now if this is an axon segment, just like the axon hillock, the axon itself is full of these sodium voltage-gated channels and potassium voltage-gated channels.
So what happens is at the very beginning, the sodium channels open. You see, the sodium comes in, temporarily changes the charge balance of the neuron. So now, the inside is more positive than the outside, which becomes more negative. And this is what you see, the initial part, the rise of the action potential.
Now here in the boundary of this, the voltage-gated ion channels, the sodium voltage-gated ion channels that are just sitting here, they start being activated just because they are getting the very tail of the massive influx of sodium into this area. So now, they continue with the propagation of the action potential.
And by the time that these guys had acted in the area that was acted before, now the potassium voltage-gated channels had acted. So basically, they are polarizing and even hyper-polarizing the neuron. And if you keep them going, that's how you keep them moving, the action potential across the axon.
This is also why the action potential cannot propagate backwards. Because always, when there is the rising phase of the action potential here, the refractory period is going to be behind it in space. So it cannot just go back.
Even though here, there is still sodium channels that might respond to this part, the potassium channels win at this point. So there cannot be another action potential regenerated here, even though they're very close to this depolarized zone. And that is called the orthodromic direction, which is like the normal direction of action potential movement.
Of course, if I fool the neuron and I inject current here in the middle, then I'm going to have action potentials being propagated in both directions. But in normal physiological conditions, that doesn't happen.
If I'm, by experimental means, I'm able to stimulate the axons in a way that will send action potentials backwards, that's called the antidromic direction of action potential movement. But again, it doesn't happen in physiological conditions, it only can happen experimentally. And it's typically very useful to identify neuron tracks or fiber tracks, or-- I can stimulate here and record here, and see more or less where I am regarding the anatomy of the brain.
Now, enough for single neurons. And let's make things more interesting, and lets get to neurons connected. So that's called a synapse. So when the axon terminals of one neuron, the place where they connect with the dendrites on soma of the following neuron, is called the synapse. And basically, we can see it here in this area. So the axon terminals can be actually contacting the dendrites or the soma of the neuron that is postsynaptic.
And there are mainly two types of synapses. One is the simplest one, is the electrical synapse, which is nothing more than when the neurons touch each other, there are proteins that are typically called connections, that allow the influx of ions across them. So it's basically, the action potential just goes through. This is just like a standard electrical connection.
Now these here have not been very well studied, especially in the mammals. Let's say in electric fish these are real, like really prevalent and very important. But in mammals, although they are present in several areas, typically the mutants for these electrical synapses don't show any obvious problem. So it's not like right now we are thinking that they are so important. But I imagine that there will be some function. It's just a matter of discovery.
Now the one that has been heavily studied and the one that typically we see in most textbooks or like the classical image is the chemical synapse. Which is where the action potential comes through the axon, reaches the axonic terminal, and it induces some, how to say, transduction cascade, that it results in the mobilization of vesicles the contain chemicals that are released in the very tight space between the membrane of the presynaptic neuron and the membrane of the postsynaptic neuron.
Now these chemicals are called neurotransmitters. And there's basically-- there's many types of these synapses, but there is two main ones. One is the excitatory synapse, where basically what you have is activation of other proteins which are sensitive to these particular neurotransmitters.
And they will produce a de-polarization of the membrane potential of the neuron which we also call an EPSP, for excitatory postsynaptic potential. So whenever it causes a depolarization it will be called excitatory, because it has the chance of producing an action potential down the line.
So basically, yeah. Just trying to recapitulate, it's more or less like if it was doing here. So whenever a chemical synapse release, in this case glutamate for example which is a classical excitatory neurotransmitter into the space, you will get a little depolarization of the membrane potential.
Now there is also inhibitory synapses. And these inhibitory synapses, it's the same idea, except that these are different neurotransmitters being released into the synaptic space, and different kind of protein being activated.
Now these proteins are more or less what the cartoon sample I was giving before. These proteins, when they sense the presence of this chemical, they open and the allow chloride ions to go into the neuron. So making the inside more negative, which basically means hyper-polarizing the inside of the neuron. And this is what we call an IPSP, for inhibitory postsynaptic potential.
And basically, it's equivalent of what I showed before, a hyper-polarization of the memorable potential. So these guys basically are going to make more difficult or going to prevent the integration of EPSPs in order to fire an actual potential. And this is the main mechanisms of controls that the neurons has when it has to decide whether to fire or not an action potential.
Now let's take a look at how these two basic principles of putting neurons together, and having these excitatory or inhibitory synapse can work in real life. So these are some examples of real neural networks. The green typically means an excitatory interaction, and the red, inhibitory interaction.
The most simple one is you have feedforward excitation. So when excitatory neuron connects onto another excitatory neuron, and they basically propagate excitation. Another, a little bit more interesting, is feedforward inhibition. So an excitatory neuron conducts onto an inhibitory neuron, which in turn inhibits the next excitatory neuron. More interesting, you have convergence/divergence. So several neurons activate one single neuron, which in turn activates other several neurons.
Lateral inhibition, this one is very important for the visual system or for what we will see later as an example of sensory systems. So one neuron is activated, but it activates the inhibitory neurons that are around them-- it around it, which in turn inhibit all the other excitatory neurons that surround this excitatory neuron. Like making it possible to make a fine-tuning of the response of this particular neuron.
So this neuron makes sure that-- in Spanish, neurons are feminine so I say she. This neuron makes make sure that she's inhibiting all the other neurons that are around her, and so that she can fire at that particular time.
This is feedback recurrent/inhibition. So here, we can start seeing something that I'm going to talk more about it. Like, this idea of loops being present within the nervous system. So here, there is there is an excitatory neuron which excites another neuron, but which in turn sends a signal to an inhibitory neuron, which inhibits the neuron that was previously exciting the other neurons. So providing some sort of a stopping mechanism for the excitation coming in.
This one, these networks of inhibitory neurons. One might say, what it this good for? This guy inhibit guy, which inhibit this guy, which inhibit this guy. This is how the classical gamma oscillation is produced, by networks of inhibitory neurons that are activating each other.
There are some more complicated mechanisms that go into this, but this is the basic layout. And a gamma is the classical oscillation of cognition and attention, and so many other phenomena.
Feedback/recurrent excitation, this is a recipe for epilepsy, really. So you can actually find it as having a role in normal physiological processes. So a neuron excites another neuron, which in turn excites the other neurons. So producing a infinite loop of excitation.
And here, there is a similar phenomenon as this one. Feedback/recurrent excitation, where you have networks of neurons forming a loop, which in turn can-- oh, this one is interesting. This is what some people call an autapse. So it's a neuron synapted on itself. So this neuron fires, excites other neurons, but it's also able to excite itself.
Now you can also have inhibitory auto-synapses, where basically the neuron fires. And at the same time, it's able to inhibit itself from firing more. So I'm sure there is many more other possibilities of how to arrange these excitatory and inhibitory neurons, but these are some sort of basic, well-known mechanisms in real brains that have well-known functions.
AUDIENCE: Just a question about that last one. Is that like a gaining method, where this boosts the signal? Is there a--
FRANCISCO J. FLORES: It could be that. But it's also what happens during sleep. This is the way that the slow oscillations signaling sleep are reproducing. So just like gamma is produced by neighbors of inhibitory neurons working together, the slow oscillation is networks of excitatory neurons working together.
Again, yeah. Just from this simple diagram, it's difficult to see how it will happen. But there are some other voltage-gated channels that the neurons have that prevent this thing just going into a crazy loop, and then the neuron dying at the end for lack of glucose or ATP.
You can also imagine, just like these autapse, the auto-synapse here, you can just take a neuron and bend it on itself. And you can have the neuron working just like an infinite loop. Provided that you give enough ATP to the neuron, it should work all the time.
Now, let's see what we can do, like a little bit more interesting with these neurons. So let's take a look at-- a basic look at some basic functioning for the sensory system. Fred, who's giving the second part of the tutorial, is going to go more into detail about the higher cognitive abilities.
AUDIENCE: [INAUDIBLE]
FRANCISCO J. FLORES: Huh?
AUDIENCE: [INAUDIBLE]
FRANCISCO J. FLORES: Yes. Cool, cool, cool. So, yeah. So this is the classical-- all you know from this from kindergarten. You know there is an eye, there is the retina, there is the receptors in the back of the eye. These get activated, sends signal to the brain.
These signals at some point get crossed, so basically in your left visual cortex is what is in the right visual field, and your right visual cortex is what is in the left visual field. So basically, the way that your brain is sensing the world is like the opposite.
And this is the classical experiment that show how the brain neurons in primary visual cortex work. And there is a cat that here it seems awake, but it was anesthetized. These are recording electrodes in the primary visual area. And there is a stimulus that's going to be presented in a screen in front of them.
The idea for these experiments-- what the people, Hubel and Wiesel who actually did the experiments, noticed that some war veterans that had lesions in the occipital area, they were actually blind. So they wondered whether this particular area of the brain could have some role vision, and performed these experiments.
I hope this works. If it doesn't, you can watch this video in YouTube. Yes. So here, we are going to see more or less how they did the experiments. So what you're looking at is the screen just like the cat was looking at. And that's the stimulus.
AUDIENCE: [INAUDIBLE]
FRANCISCO J. FLORES: Yeah. And you can hear the neurons firing. You see? Stimulus firing. So then, they mark the area where they hear the neuron firing with exes.
Now when the stimulus presented on the side, nothing happens. But when you move into the other area, neurons fire. You move away from that area, and neurons don't fire anymore.
The neurons are also answer to the edge of the stimulus, if you notice. So they're gong to mark of the area where the neurons are not firing with somewhat-triangles. And again, they find another area where the neuron doesn't fire when the stimulus is present.
Now it's interesting, if you use a different orientation, the neuron also doesn't fire. But if you get closer to the optimal orientation, the neuron fires a bit. And now, the neuron is firing. So this is a Nobel Prize-winning experiment.
So, I'm going to make it shorter then. This is a depiction or a modern experiment of how these things look. So this is what is called the on area of the receptive field. So the receptive field is the area of space where the neuron responds optimally for a particular stimulus that the neural likes.
In this case, it's bars of light. And of a particular orientation. So, this is where the idea comes up. These neurons act like edge detectors. And also of course, orientation detectors.
And now Hubel and Wiesel, I assume they went back in the visual system and to the thalamus, which is located here. So you have from the retina, the next synapse is in the thalamus. And then you go to the primary visual cortex.
And in the thalamus, what you find is neurons that respond to like rings of light. Basically, more like circles of light. The neurons here respond when the signal is presented in the center on, and this roundness of. Or, of the opposite. When you present a donut around the center-- oh.
TECH SUPPORT: You got very quiet. There you go.
FRANCISCO J. FLORES: Oh, thank you. When you present a donut around the center and they don't respond when you present something in the center. So these are center off and surround.
And what they figured out-- and this is actually the Nobel Prize-winning, is that if you combine several of those cells, you can actually make one of the other cells. So this is basically how all of these hierarchy of different receptive fields and neuron responses can build up towards generating more complex perceptions. And this is what Fred is going to talk, basically, how from the primary visual cortex you can go towards more complex perceptions.
Now let's not forget, also there is action related to this. So this is a face, that you can just look at it. But if you were able to look at the eye movements that you're performing while looking at this face, what you will see is something like this. Where there are five fixations, points with your eyes stay still, and then there are saccades, which have these lines that you can see.
So basically, we're never really perceiving the whole space. Just like us, we think we do. We're just getting little samples, and then the brain just fills the rest with whatever previous knowledge you have on how spaces should be.
So this idea that action and perception are inextricably linked is it has been ephemera for some long time, but now it's gaining more traction again. And people is trying-- is striving to do no more experiments in anesthetized animal. But actually, doing experiments in animals that are actively exploiting, and moving, and sensing the environment.
Short look at the auditory system. Very similar, the primary auditory system has neurons that are attune for sounds. So there are bands of neurons that responds to 500, 2,000 hertz, 4,000 hertz, so different frequencies.
Similar as the primary visual cortex neurons were tuned to the orientations of these light bars, the neurons in the auditory system, the primary auditory system, are tuned for like different frequencies of sound. Basically, they're doing that for auditory composition, if you wish.
Now the visual system and auditory systems are nice, because the stimulus can be easily parameterized. So for example, for the frequency, I know the frequency, I can measure it, I can synthesize it.
Now, things are complicated with the olfactory system. Because imagine that this is a lemon odor, a citrus odor, and a cinnamon odor, then how do you parameterize odors? And this is why the olfactory system is not as well studied, just because it's a nightmare.
And basically, to give you the idea, here is also some action or something going on, which is basically your breathing. So you inspire, and you get a sample of the air around you. And your neurons-- and this is in the olfactory bulb, will respond with different firing patterns to it.
So this is the baseline. You inspire, all the neurons do the same. Now, when the odor is presented, what the neurons do-- if you look at two neurons in this case, is they change their temporal pattern in which they're firing.
So now, not only the amount of action potentials matter, but also matters the timing of these action potentials. And the timing, not only from the same neuron, but also in relationship to other neurons that are around this. And this what is called a temporal code as opposed to the array code, which is just looking at the amount of action potentials.
Now to look at the motor part very quickly. The motor systems-- here is a coronal section of the human brain. It's located in this part, and there is a neuron that goes all the way down to the spinal cord. And this neuron is the one that is able to instruct the muscles in order to effect a movement.
These neurons also have some tuning properties. So if I move my hand, like in this direction or this direction or this direction, some of these neurons are going to respond more when I do this, and some of the neurons are going to respond more when I do this. And you can see that there's a whole array of neurons responding to all of the possible directions of movement. So they also have that tuning for a particular property.
And let's go to the sensory-motor integration. So basically, what we have is our capacity to sense things from the environment, and then a capacity to move and act on the environment. And just like hydra has these sensory neurons which connects into the muscles and/or the neurons that send other information to the muscles.
What we have, still very similar to the hydra for example, is the reflex arc. Which is basically, you have a sensory neuron, that when there is a noxious stimulus like a flame, send a very fast signal to the spinal cord that makes a synapse on another neuron, which they call the integration neuron, which signals into the motor neuron, that instruct the muscle to move away from the noxious stimulus.
So you see, there's only three synapses there. So very fast, no need to think about it. You can think about it if you want, but typically you wouldn't.
And something that is typically not depicted here, is that there is a loop, there are other neurons that sense that this muscle has been contracted, and that send that information back. And that at some point, instruct to release the tension in the muscles. Otherwise, you will stay perpetually in a state of tetanus.
And now, you can have the same idea with more complex system. So basically, you see a glass of water, and then it goes through your brain. Your brain says, oh, yeah, I am kind of thirsty. And then you decide to pick the glass of water and drink it. And then, when you don't feel first anymore, you can put the glass of water back.
And then again, that requires some closed loops that the nervous system has. Just like I showed before in the like basic neural circuits. So they will have the reflex arc, which is rapid and involuntary typically. And then, more complicated decision-making processes that involve the brain.
So basically, the nervous system is, one can say, functionally closed in itself. So it only response to what's going on within itself, although it can sense the environment and it can act on the environment. And to me, the most beautiful proof that the nervous system is closed and can just work basically by itself-- basically if you don't have any sensory surface, or motor surface, or sensory stimuli or motor action coming out, it's sleep.
So when you're asleep, your brain is not really shut down. But it's just intrinsic, autonomous, workings of the nervous system. Which typically, if you look at the non-REM sleep, which is the classical non-dreaming sleep, you will see this activity. So these sleep spindles, k-complexes.
And then for more deep sleep, you have the delta waves, and the slow oscillations which are produced by these networks of recurrent excitatory neurons. And of course, you all know that you can have here more complex phenomena, just like dreaming during sleep.
And basically, with that I would like to finish, and just leave you with a couple of final remarks. Neuroscience is the study of the nervous system, that's what it is, basically. The nervous system provides a fast and sophisticated link for sensory-motor integration. Learning, memory, attention, and everything emerge from the nervous system within the process of sensory-motor integration. This is why I said that it's sophisticated.
And now, I get way to Fred, which is going to talk about all the sophisticated parts that the little system does. Thank you.
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LEARNING