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Dr. Samantha Meen / Curiosity Weekly Host (7:37)

I was always taught that the ultimate goal of neuroscience was to know exactly what was happening in the brain with any behavior and any disease, but we haven't been able to figure that out yet because the human brain is no simple feat to map the Fact that we can't just do experiments in people aside, the sheer complexity makes it something that's been deemed an impossible task. I mean, picture the tangle of sewing threads in your grandma's cookie tin. Separating those is challenging enough. Now, remember, there are 171 billion cells in the human brain and trillions of connections. Well, a project called Microns created the most detailed mouse brain wiring diagram ever made, revealing how neurons actually communicate in unprecedented detail. We have neuroscientist Dr. Forrest Coleman, an associate director of data and technology at the Allen Institute, here to tell us more. Welcome to Curiosity Forest.

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Dr. Samantha Meen / Curiosity Weekly Host (8:33)

So, machine intelligence from cortical networks. It's this big project, right? It produced the most detailed map showing not just brain cells, but also the connections and activity all in one. And it was covering an area of the mouse brain just about the size of a grain of rice. Can you tell us more about what was actually mapped in that area?

Capital One Terms Announcer (8:52)

Yeah. So there were two really important phases of the experiment. The first was an experiment that was done at Baylor where they recorded the activ of every, almost every neuron in this millimeter grain of sand, grain of rice scale, part of a mouse brain. And to do that, they used a microscope that makes every neuron kind of flash when it's active. And so there are these movies from this microscope where you can see the neurons flashing as the animal is watching a movie, basically watching a bunch of YouTube clips, so you can see which neurons are responding to which parts of the different movies. And then that animal was actually shipped to the Allen Institute here in Seattle, where we took its brain and then we took a chunk of it and we reconstructed it in extraordinary detail to be able to image it with a fleet of what are called electron microscopes. These are microscopes that use, rather than using light, they use electrons to take pictures. And that's because you can take really higher resolution pictures with electrons than you can with light. And with these high resolution pictures, you can start to trace all of the individual threads, as you put it, or axons, as we talk about them in neuroscience, to see where one neuron goes and wires through this very complicated intertangled web of brain tissue and then talks to other neurons. And so when you put these two things together, we have a picture of how the neuron, what is the neuron's activity, and then which of the other neurons are those neurons talking to to try to get a better picture, to understand how brain processes information through these complex networks.

Dr. Samantha Meen / Curiosity Weekly Host (10:34)

So you see the physical Neurons, you see their structures, but you also can overlay that with a map of their activity in response to these animals watching something, right?

Capital One Terms Announcer (10:45)

That's right. My colleague, Nunu Dacosta, has this metaphor that I really love, so I'm going to reuse it here. It's like we're trying to understand the dynamics of a complicated party. Right? Where the party has the neurons are the people in the party.

Dr. Samantha Meen / Curiosity Weekly Host (10:59)

And.

Capital One Terms Announcer (10:59)

And you might imagine, like, I could tell you something about the party and be like, all right, I'm going to tell. I'm going to give you a list of everything everybody said at the party, but I'm not going to tell you who they talked to. And then on the other hand, I could also give you a list of who everyone talked to, who was talking to who, but not anything about what was said. And you might imagine it's pretty difficult to understand what's going on at the party if you only have one of those things. But in this experiment, we actually have both of those things. We have, you know, when were the neurons that are active. That's basically saying when they were talking. And then we have who they were talking to in the structural data. And we're hoping, you know, by putting those two pieces of things together, we can have a better understanding of how information gets processed in the brain.

Dr. Samantha Meen / Curiosity Weekly Host (11:42)

That's amazing. The analogy of a party really captures the chaos of activity in the brain, because you really do have no idea. Okay, so you said a lot of cool things, but what I must follow up on is that mice were being shown YouTube videos. Yeah, I'm sorry, I need to ask more.

Capital One Terms Announcer (12:00)

Yeah, well, I mean, you know, everything about, you know, our experience and activity in the brain is really complicated. You know, there are so many visual stimuli. The space of different kinds of things that can hit our eyes is really unbounded. And so one of the challenges in trying to map the brain is trying to get a sense of, for how functionally how neurons respond to the full host of diversity of different kinds of visual stimuli that they might exist. And so in this experiment, the strategy was just to try to give the most diverse, like, most different kinds of stimuli that you could. And, you know, so we showed. The experiment, showed the mice just a lot of different clips of a lot of different kinds of stimuli. And so one of the best sources of that is YouTube. Just like, um, yeah, so lots of different movie clips taken from a range of different from. From different things, along with a few other stimuli that are sort of more classic stimuli that you might Expect a scientist to use like a bunch of drifting gratings of bars that just like go to the left like this, right, like kind of boring, boring things. And so, yeah, so those are the kinds of stimuli that we're using. And the, and the, the, the team at Baylor tried to actually use advancements in machine learning to take all of the videos. And so for each neuron they have basically, okay, this video, this video, this video and the neuron's activity. And they tried to build a model that could, based upon just the activity, just the movie that was being shown, could they predict exactly whether this neuron was going to respond or not respond to that movie? Basically, does this neuron like this movie or not like this movie is one way of talking about it. And remarkably for many neurons, some neurons just don't respond to visual stimuli. Even in the part of this brain that's the visual cortex, which is interesting. But for ones that do, they could build a model that was pretty good and they can test it by holding out some movies from their training and then showing those held out movies and showing that their model is able to predict how that neuron is going to respond to some YouTube video that the model's never seen before.

Dr. Samantha Meen / Curiosity Weekly Host (14:09)

It's not the first time we hear about a new map of the brain, right. And we've had all of these big papers publishing like new circuit map, new activity map, new highest resolution map of neurons in this part of the brain. So what sets the map that you all created as part of the Microns project apart from those things we might have heard of already?

Capital One Terms Announcer (14:30)

Yeah, I mean first off, it's very true. There's been a tremendous amount of progress made in this general field over the last few years. People may have heard about mapping the full time a full fly brain was mapped just happened, just happened last year there. People may have heard that we've a similar map was made in a chunk of human brain. And I expect this is going to continue because really there's been a revolution in technology and machine artificial intelligence are really driving this field forward and we're making a lot of progress right now. So that's definitely a meta story that's behind this so broadly. This field is called connectomics. It's the idea that you want to measure all of the connections between all of the neurons in a portion of brain. And this experiment is called functional connectomics in the sense that you have the, the way the activity of neurons, the function of neurons and their structure in the same experiment. So this is the largest Functional connect. It's the largest connectomics experiment, but it's also the largest functional connectomics experiment that's ever been done. A goal for the next decade is to try to figure out how do we scale up this effort to be able to make the first map of a mammalian brain? Which is, which is a goal that we're working on and many others around the country. There's an NIH Brain Initiative kind of consortium called BrainConnects that is trying to work through all the technical problems that would be required to make this first full mammalian mouse brain map at this synaptic resolution possible.

Dr. Samantha Meen / Curiosity Weekly Host (16:00)

I want to dig deeper into the scale of what you did with the Microns project. So the map reflects only 1 cubic millimeter of brain tissue. But that really is a huge feat considering all that's cataloged with the imaging technique that you described, electron microscopy. So can you put into perspective for us just how high of resolution we're talking when it comes to imaging with electron microscopy?

Capital One Terms Announcer (16:23)

Yeah, let's see. So one of the pictures, this data set, like I said, has around 100 million pictures in it. Each picture is a photograph that's like, there are different size cameras used, but there's something like 5,000 by 5,000 pixels. And one of those pixels was 4 nanometers by 4 nanometers. A nanometer is 1 1000th of a micron. And you know, a human hair is something on the order of 10 microns, 25, 2500 or so pixels just in the, just to the diameter of a hair. Like that's a, that's a pretty high resolution picture. People think about light like, you think about a light ray, like a, like a, a laser, for example. You know, the smallest a light ray is, it's a wave that goes through, through space. And the, and the size of that wave is about 500 nanometers. And we're talking about 4 nanometers. So we're really talking about things that are, that are smaller than light, which is, which is kind of incredible. We cut these sections. In order to do this, we have to cut the sections with a diamond knife when we were cutting them at about 40 nanometers. So that's 1/10, 1/10 a wavelength of light that we're shaving off the brain. Section after section for 25,000 sections. We had to collect across this thing without missing many in a row. So it's like, you know, it took, it took the whole team working round the clock as a team over several weeks, a couple weeks to do this carefully In a way that was. Yeah, didn't lose any sections, have them crumple up too much, and so on and so forth.

Dr. Samantha Meen / Curiosity Weekly Host (17:55)

And what we're really talking about here is this, like, junction between two cells. Like this, the connections between two cells in the brain that underlie, like, everything that we think we do, we see, we feel our memories, all has to do with those connections between cel. The exchange of molecules at this synapse. So you're telling me that that's at the nanometer level. If we want to really know what's going on to make us laugh or make us remember something at the end of the day, we need to look at all of those tiny, tiny synapses. Right?

Capital One Terms Announcer (18:28)

Yeah. That's our best hypothesis about where all of the richness of our experience and our memories gets encoded in the brain certainly involves not only, but is definitely involves exactly which neurons are talking to which other neurons. Because those connections, the synapses, some of them are, Some of them form, some of them are eliminated. And that's the way in which our brain stores information on a very long timescale.

Dr. Samantha Meen / Curiosity Weekly Host (18:52)

Now, this level of detail, of course, I think you've convinced me. It's very necessary. Right. But it comes at a cost. You mentioned nearly 2 petabytes of data for a cubic millimeter of brain tissue. First of all, what is a petabyte?

Capital One Terms Announcer (19:08)

Yeah, so a petabyte, hopefully. Maybe people have heard of a terabyte. So usually on your hard drive, like your hard drive on your computer, you know, they're different sizes, but they're on order a terabyte. And so a petabyte is 1024 terabytes. So it's kind of like you had 1000 computers worth of data, is in order to store all of the really raw data that went into this experiment.

Dr. Samantha Meen / Curiosity Weekly Host (19:32)

Sheesh. Are there certain technological advancements that have made that level of data capture and processing? Because that's a lot of data to process like, possible today that we maybe couldn't have done this even five, ten years ago.

Capital One Terms Announcer (19:45)

Yeah, absolutely. I mean, the first. The first has to do with cameras. The way in which we were able to acquire this data was by kind of taking really kind of old microscopes, microscopes from the 1970s, and retrofitting them with really modern electronic cameras and all of the. All of the things that have happened with cell phones and with, you know, microcircuits in general. So the fact that we have these bigger cameras is one of the important. One of the important things driving this technology. And then Obviously you mentioned data processing. You know, there were many stages. You know, I have to take all the individual pictures and you have to stitch them together, find exactly where they line up and, and go from a bunch of individual tiles, both put them in 2D and then also into, into three dimensions because you got these different sections and you have to line them up. And then trying to train a computer to trace all the individual axons and dendrites through this very large volume to create, to help trace out all the axons and find the synapses and so on and so forth, was all really kind of a very large scale AI application, which I think even when the project started, it was not clear that artificial intelligence was going to be good enough to make this possible. And as, as has been a continuing theme across many areas of society, AI is continuing to exceed our expectations about what it is possible to do. And I think drove a lot of this progress forward and will continue to do so in this field for some time.

Dr. Samantha Meen / Curiosity Weekly Host (21:21)

So now that it exists, what can researchers do with these maps? What have they, or even you all already done?

Capital One Terms Announcer (21:29)

We've had a lot of unexpected people utilize this data. For example, the, the folks who study the way in which our blood system interacts with their brains, the sort of neurovascular interaction community, has discovered a lot of things that we didn't even intend this data set for. So they're discovering different cells and how the cells interact with the vasculature. They're seeing how the axons wrap around the blood vessels in ways that were unexpected. People are studying the non neurons, the glial cells that are also there, have made fundamental discoveries about that. And all basically in these, you can see absolutely everything which lets people discover this kind of stuff. What we were very interested in doing was mapping what are the different kinds of cells that exist in the brain and what are the pathways that exist, what are the kinds of neurons that talk to other neurons? And we've written one very extensive paper about how there are these different kinds of inhibitory cells and different kinds of excitatory cells. And we found kind of new patterns of specificity in the connections between the inhibitory neurons. These are neurons that when they're active, they make who they're talking to less active, as opposed to excitatory neurons, which when they are active, the ones they're talking to, it makes them more likely to be active. And so this inhibition is really important for controlling activity in the brain. So that was one of the major insights, was really finding these specific inhibitory pathways in this chunk of brain. This experiment and many other experiments that are happening in, in neuroscience is really giving us a new appreciation for how diverse the neurons in our brains are. There are just really a lot of different kinds of neurons, and each kind of neuron has a different shape. It sort of has a different set of proteins or parts within it. And, and, and they're remarkably conserved from mouse to primates to humans. We have very many of. We have lots of these kinds, like, you know, 5,000, you know, different kinds of neurons in your brain, and they're very similar across these species. But we don't have a really clear idea about why we have so many kinds of neurons and exactly which kind of neuron is responsible for what we're. We're trying to build an understanding of exactly what are they? What are they for?

Dr. Samantha Meen / Curiosity Weekly Host (23:52)

Last quick thing I want to ask is people may be wondering, okay, this is cool for you neuroscience nerds to understand the anatomy and function of the brain, but can this relate to understanding any diseases or disorders of the brain as well? And are there any inklings of where that may go so far?

Capital One Terms Announcer (24:10)

Yeah. Well, I think when you think about neurological disease broadly, there are some examples where we have a very clear understanding of what is going wrong. Why. Why is this brain broken? And in many of those cases, what it comes down to is that we know there's a specific kind of cell that is dying or is somehow, somehow being being affected. But there are many diseases that we actually don't really understand what is broken. And so this is a kind of research that we call foundational research, where we're trying to make a basic map about what are all the pieces and how they all talk to each other. And, and once you understand how something is constructed and how it works, it actually provides a framework that you can start to look at how it was broken. So it's this framework of being able to understand what are the parts which lays the foundation for understanding how things might get broken.

Dr. Samantha Meen / Curiosity Weekly Host (25:07)

Absolutely. I mean, we need someone to keep doing foundational research. So that is a good enough thing to say for me. Dr. Forrest Coleman is an associate director of Data and Technology at the Allen Institute. You can learn more about the Allen the Microns project@allen institute.org thank you so much, Forest, for nerding out with us about this fascinating project. It was so much fun.

Capital One Terms Announcer (25:29)

Oh, yeah, me too. Thank you so much for the time. And I, and I, I love nerding out anytime.

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Sure thing. Barbecue sauce.

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Dr. Samantha Meen / Curiosity Weekly Host (27:00)

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Dr. Samantha Meen / Curiosity Weekly Host (27:06)

Got pre qualified for a Carvana auto loan, entered my terms and shop from thousands of great car options all within my budget. That's cool that financing through Carvana was so easy. Financed, done. And I get to pick up my car from their Carvana vending machine tomorrow. Financed, right? That's what I said. You can spend time trying to pronounce financing or you can actually finance and buy your car today on Carvana financing, subject to credit approval. Additional terms and conditions may apply. We all live in the same world, but your version of that reality is different than mine. What's real is subjective. So good news and bad news. Good news, you're the main character in your own story thanks to your good old trusty brain. But bad news? That brain ain't so trusty after all. It starts right at the level of our senses. Seeing is believing, as if each eye has a blind spot where the optic nerve plugs into the retina like a TV plug stuck in the middle of the screen. We don't notice it because the brain fills in the blanks. And then sometimes we just don't pay attention. Have you ever seen that video where you're asked to count how many times people pass a basketball, and in doing that, you completely miss the gorilla walking by? If you haven't, I spoiled some of it. But there's more. It's called the Monkey Business Illusion by cognitive psychologist Dr. Daniel J. Simons. Look it up. The point is, if we aren't paying attention, there's a lot to miss about our surroundings. Like what do the clouds look like in the sky today? Now our perceptions get muddled too. In studies with amputees, they report feeling movement in a missing limb after watching a mirror reflection of their intact limb where their lost one was. The brain is overriding what it actually feels for the sake of a cohesive story. But even if we did sense and perceive things properly, then there's the problem of our memories. I mean, what did you wear last Tuesday? Did you lock your front door? I'm 0 for 2 on remembering both of those. And as the true crime girlies know, this can have bigger consequences for things like eyewitness testimonies. The first study to really popularize this idea asked people who watched a car crash how fast the cars were going when they smashed versus when they merely hit each other. Those who heard smashed not only guessed higher speeds, but later swore they remembered seeing broken glass even though there wasn't any at the scene. Now, for most people, our memories aren't a recording. They're like drafts of stories we keep editing. In fact, every time you recall a memory, it gets reconsolidated, meaning there's opportunities for more edits. And yes, memories can get distorted, but most memories are actually quite accurate. Studies show that around 90 to 95% of verifiable details that someone recalls are typically correct under normal, non stressful conditions. And details aside, people tend to remember the gist or the meaning of events quite well, even if some of the details fade. Ultimately, our brains craft a practical and ever updating narrative of reality, even if it isn't quite perfect. Before you go, we love hearing from you about what science topics piqued your curiosity. Rate and review us on Apple Podcasts or Spotify and let us know what you're into. Or you can and we may just feature your idea on an upcoming episode for Warner Bros. Discovery Curiosity Weekly is produced by the team at Wheelhouse DNA. The senior producer and editorial correspondent is Teresa Carey, our producer is Chiara Noni, our audio engineer is Nick Kharisimi, and head of Production for Wheelhouse DNA is Cassie Berman and I'm Dr. Samantha Yuin. Thanks for listening. I am but a plastic spoon at this point. Forget the Forget the worm in my brain. I'm but a spoon.

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Same. They're so light and so comfy and if it's not comfortable, I'm not wearing it.

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And the bras? Soft, supportive and actually breathable.

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