That Neuroscience Guy - How Does the Brain Actually Work?

Episode Date: October 2, 2022

We've spent a lot of time discussing different brain areas and what they do, but that's not the whole picture. How do these areas communicate and work together to create what we experience as brain function? In today's episode of That Neuroscience Guy, we discuss how our brains actually work. 

Hi, my name is Olof Kregolsen, and I'm a neuroscientist at the University of Victoria. And in my spare time, I'm that neuroscience guy. Welcome to the podcast. We've talked a lot about brain regions on this podcast, to the point that I'm afraid to say the word amygdala again. But one thing that I feel like I've kind of missed is how the brain actually works. I've hinted at it, and I've described bits and pieces of it, but I haven't really gone over the key mechanism.

So on today's podcast, the neuroscience behind how the brain actually works. We've talked a lot about neurons, so let's start there. The brain is made up of about 86 billion neurons. It's an estimate, but it's a pretty good one. And the same number, approximately, again, of non-neuronal cells, mostly glial cells. Of course, there is also arteries and veins to supply blood to the brain and a few other things. The brain weighs about three pounds than the average adult. The brain is about 60% fat. The remaining 40% is a combination of water, protein, carbohydrates

and salts. And the brain is also made up of different types of tissue. If you look at a brain slice, you'll clearly see that it's a combination of what we call both gray and white matter. Gray and white matter are two different regions of the central nervous system. In the brain, gray matter refers to the darker outer portion, while white matter describes the lighter intersection that lies underneath. In the spinal cord, this is actually reversed. The white matter is on the outside and the gray matter sits within. Gray matter is primarily composed of neuron somas, the round central cell body of the neuron, and the white matter is mostly the axons of the neurons,

the long communicative stems that connect neurons to each other, and these are wrapped in myelin, which is the protective coating that facilitates neural transmission. The different composition of neuron parts is why the two appear as different shades on certain types of brain scans. Now before we dive back into neurons let's quickly talk about glial cells. Glial cells are cells which are non-neuronal and they're located within the central and the peripheral nervous system. And basically what they do is they provide physical and metabolic support to neurons. So they help with neuronal insulation and communication, nutrient and waste transport, and they basically help the structure.

They help hold everything in place. Glial cells are a general term for many types of different glial cells. For example, those microglial astrocytes and Schwann cells, and each of these has their own functions within the body. I'll do an episode in the future on glial cells. So each type of glial cell performs specific jobs that help keep the brain functioning. But like I said, primarily glial cells provide support and protection to neurons. They maintain homeostasis, cleaning up debris, and they form myelin. They essentially work to care for the neurons in the environment that they're in. So that's physiology, but how does

the brain actually work? As we've discussed before, the brain sends and receives chemical and electrical signals throughout the body. Different signals control different processes, and your brain interprets each differently. Some make you feel tired, while others might make you feel pain. Some messages are kept within the brain. In fact, the vast majority of neurons in the brain are interneurons, just connected to other neurons. But others send messages out through the spine to the body's muscles to help you move, and others are neurons that bring in information from

the sensory system. So to do this, the central nervous system relies on lots of neurons. 86 billion, as I said earlier. But again, this doesn't really explain how the brain actually works. What you're thinking and feeling and seeing right now, for instance. The best way to explain this is to think of a neuron as a detector. When it receives sufficient input, it fires. So it's detected something. The neuronal firing is representative of, hey, I've seen this type of input. So let's think of a neuron in the primary visual cortex, So let's think of a neuron in the primary visual cortex. The first step in visual processing and interpretation. When a photon of light strikes the back of the eye, it hits a receptor.

The rods and cones we talked about when we discussed vision in season one. The receptor in the rod or cone basically detects that photon impacting it. It's got a little mechanism that when the photon hits it, it starts an electrochemical process. So the photon striking that receptor basically causes that neuron to fire. The receptor generates a very small electrical signal, which is then turned into an action potential. That's the other electrical signal we've talked about. And that travels down the neuron to the terminal, which is where it causes a release of neurotransmitter. We talked about that just a couple of weeks ago, and that in turn may cause the next neuron in the chain to fire. This process continues until our neuron in the primary visual cortex fires. Given the input to this neuron that's come through the visual

system, that neuron is representing that receptor on the eye and literally what's happening out in the world. So imagine you're in a perfectly dark room. I mean completely black. If the only thing that existed was this one photon of light, then all you would see is a single point of light very briefly. Now, that's one photon, but what about the complexity of vision? How does your brain actually do this? Well, we talked about it before, but what about the complexity of vision? How does your brain actually do this? Well, we talked about it before, but let's go back through this. What I want you to do is think of your TV screen or your computer monitor.

It's basically made up of lots and lots of pixels, little tiny squares. And when you color those squares, you have an image. And if you zoom in on an image in Photoshop or any kind of visual program, as you zoom in further and further, you'll actually see the pixels. Now, as computer graphics have gotten better, you don't see individual pixels really, unless you zoom right in. But those of us that are older will remember 8-bit graphics and when you could only represent a small or a relatively small number of pixels on a screen. And that's what's happening in

the primary visual cortex. All of the photons hit rods and cones, and the receptive field in the brain perceives this as an image. So this is how your brain represents an image. It is a pattern of neural firing in the primary visual cortex that is then recognized, if you will, by the other visual areas of the brain. And again, you could go back to season one for that process. Now, the same is true for sensory information, as we've discussed in the past as well. A single neuron firing in the somatosensory cortex might represent a muscle spindle in the biceps. And when that neuron fires, it means the biceps muscle is being contracted. Just as a different neuron firing might represent a pain receptor in your ankle. But in some, the firing of all of the

receptors in your skin, muscles, and joints is a pattern of activity, which is the representation of the current state of the body. For instance, standing up doing a biceps curl with a weight while your right ankle is bothering you a little bit. And again, this is also true for motor output. The firing of a single neuron in the primary motor cortex might lead to the contraction of a muscle spindle in the biceps, but whole movements are just a pattern of neural activity reflecting the firing of all the muscles needed to hit a golf ball, for instance. And the key idea here, and where we're going with this, is how the brain

actually works are these patterns of neural activity. And that's all there is to it. Now, it's important to note that you have to think of this statistically. To hit a golf ball successfully, you do not need to fire every neuron that is needed. You just need to fire most of them. You could think of firing all of them perfectly as the perfect golf swing, but you do not need to hit the perfect golf shot every time to be a good golfer. And this is also true of visual recognition. When your brain is presented with a pattern of neural activity, some of the pixels might be missing, some might not be working for whatever reason,

but as long as enough of the information is there, your brain can recognize the person you're seeing as your best friend or your mom or your dad. And you might have even seen when you're fooled by this. So if you see someone from behind and you think you know them, it's because that pattern is close enough to the person you know,

and there's just not enough information there that your brain goes, hey, that might be my friend. And then they turn around and you go, oh, well, wow, they are clearly not my friend. But what about more complex processes like learning and decision-making? It's the same thing, patterns of neural activity that reflect different things. Let's think about what you want to eat for dinner. Basically, let's say you're deciding like I am right now about whether I want to have a piece of salmon for dinner or a piece of chicken. I have a value representation for these things,

as we discussed when we talked about learning decision-making. But what is that value representation literally? It's a pattern of neural activity. And when I go to make the decision, there is a pattern of neural activity that represents the value I have for chicken. And there's a pattern of neural activity that represents the value I have for fish. And then the brain evaluating this again is just another pattern of neural activity. It's a bunch of neurons firing. Kind of like the way a computer can represent a 2 with a pattern of electrical activity

and a 1 with a pattern of electrical activity. And by applying some logic, it can add these numbers and come up with the fact that 3 is the answer. And these patterns, this even holds true for things like love. The love you have for your parents or a significant other. It's a unique pattern of neural activity. And that is how the brain actually works. The firing of 86 billion neurons and the trillions of interconnections allows for extremely complex patterns, which is why our brains are capable of all the things that they are. And this is why other mammals are not as sophisticated.

They literally have less neurons and far less internet connections, so they cannot have the same complexity of thoughts that we humans have. So right now, as you listen to this, realize your ability to understand what I'm saying. Your feelings about whether or not you like this episode and your thoughts about what you're going to do next are just complex patterns of neural activity. A bunch of neurons that are either firing or not firing, that are either on or off. And that's all it really is. There's no black box in there. There's no secret mechanism. It's just 86 billion neurons and all their interconnections creating complex patterns of neural activity. Okay, I hope you enjoyed this episode. If you do, please subscribe to the podcast. We're still looking for ideas to wrap up season four, so you can follow me on Twitter at ThatNeuroscienceGuy, and you can DM me ideas. We're processing them right now, and we've already done some bits and

pieces in season four and are planning more based on your feedback and your ideas. You can email us at thatneuroscienceguy at gmail.com. The website's up, of course, thatneuroscienceguy.com. There's links to our Etsy store there where we sell some T-shirts. Thanks to those of you that are buying them. We're going to come up with some new ideas. And like I said, the money from that just goes to support graduate students in the Kregolson Lab. And that goes for Patreon too.

A couple of people are supporting us with donations every month. It just takes a dollar or two. And all of you that are listening, we're almost at 200,000 downloads. That would pay for graduate students for like the next 20 years of my career. So if you can support the graduate students in my lab, that'd be great. I don't take any of the money myself. I've got a great job and I don't need it. And of course, like I said at the outset, thanks for listening to the podcast.

We appreciate you so, so, so much. My name is Olof Kregolsen and I'm that neuroscience guy. Have a great week and I'll see you on Wednesday with another Neuroscience Bite.