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#17 - David Owald - Tiny Brain, Big Insights: What a Fruit Fly Can Teach Us About Memory
29 Plays20 days ago
What happens in the brain when we learn new information, and how can understanding fruit fly memory help us unlock the secrets of human cognition?
In this episode, I had an insightful conversation with Prof. Dr. David Owald, an expert in neurobiology, who delves into the complexities of memory storage and learning processes as observed in the humble fruit fly. We explore how these simple organisms can reveal profound insights into the mechanisms of memory and how our brains function.
Key highlights include:
- The role of synaptic plasticity in memory formation and how David studies these processes at the molecular level in fruit flies.
- The fascinating dynamics of the mushroom bodies in the fly brain and their critical role in how flies learn and remember odors.
- An exploration of how sleep affects memory consolidation, emphasizing the surprising parallels between insect and human brains.
- Insights into attention and decision-making, including how flies prioritize information and behavior based on their internal states.
- Discussion on the challenges and triumphs of scientific research, including unexpected findings that can reshape our understanding of memory mechanisms.
If you’re interested in how learning happens at the neural level, the parallels between different species, and the implications for understanding human memory, this episode is packed with valuable insights you won't want to miss!
Recommended
Transcript
Introduction to Memory Research with Dr. David Owald
00:00:00
Speaker
Hey, what's up everyone? This is Sajmal Savary and welcome to another podcast episode. Let me ask you something. What can a tiny fruit fly teach us about how memory works? And what actually goes wrong when we forget?
00:00:12
Speaker
In this episode, I'm joined by Professor Dr. David Owald, a neuroscientist who studies memory using one of the most unexpected but powerful models in science, the fruit fly. We dive into what makes the fly brain so useful, how memories are formed and disrupted, and what this all means for understanding the human mind.
00:00:31
Speaker
It's a deep and surprising conversation that shows just how much we can learn from the smallest brains. Enjoy.
00:00:54
Speaker
Hey everyone, and welcome to another podcast episode. If you're new here, my name's Ajmal. I'm a neuroscientist and entrepreneur. On this podcast, we explore the links between science, technology, business, and the impact they have on all of us.
00:01:09
Speaker
Today we talk to Prof. Dr. David Owald. David leads the Owald lab at Charité in Berlin, where his research explores the neural mechanisms behind learning, memory, and sleep. His team uses Drosophila, the common fruit fly, as a model to uncover how synaptic and circuit-level processes shape behavior.
00:01:27
Speaker
With a strong interdisciplinary approach, the lab combines genetics, electrophysiology and cutting-edge imaging to tackle some of neuroscience most fundamental questions. David is also the recipient of an ERC consolidator grant for his project Simple Minds, which aims to shed light on how we make vital decisions.
00:01:45
Speaker
Alright, enough background. Let's get into it, shall we? Welcome to another podcast episode. David, it's great to have you. I mean, we met at the art documentary film premiere of Gedächtnis setzt aus, Amnesie, wenn das Gehirn plötzlich streikt.
00:02:03
Speaker
And i mean, it was pure coincidence that a friend of mine who was there also invited me to come. Actually, her professor was ah in the documentary, but she couldn't come. So my friend went and she could invite some people and told me, hey, you worked on learning before. Why not?
00:02:19
Speaker
Why not come as well? And that's where we met. And I mean, you were part of the actual documentary showing your lab and answering questions about your fascinating work. It was so fascinating actually that afterwards I think I blocked you for an entire hour just to talk about the work you are doing because I thought was so interesting.
00:02:40
Speaker
um And after the film premiere you entered a panel as well and all guests could ask further questions about memory in general because that's what we're going to talk about today. So let's go all the way from the start, right?
00:02:54
Speaker
And take as much time as you want. You saw the questions. I will most likely jump all over the place um because I can't keep it keep it together. I find this so so interesting.
00:03:05
Speaker
and And most importantly, your answers don't have to be short. and We can edit all of this or make it as concise as we want. Alright, so as most people know, I studied motor learning. So of course, when it comes to learning and memory, I'm biased anyway.
00:03:23
Speaker
um But what I'm curious about is what you will tell us. What interests you about memory so much?
The Importance of Memory in Everyday Life
00:03:31
Speaker
So first of all, thanks for having me and um yeah giving me the opportunity opportunity to talk about our research.
00:03:39
Speaker
And um I think memory is process that basically everybody can relate to, right? I mean, it's... what what shapes our personality, what we make out of our everyday life, what we need to get from one place to the next to navigate. So we need to know where to go, how to cross the streets. All these things are based on prior experience.
00:04:07
Speaker
So everything we actually... have in our biography is based on memory everything we do in a moment will be based on memory i'm talking about conscious conscious um but also some subconscious um tasks we do um obviously you also have reflexes but sure um And ah it also is important to predict the future, right? I mean, it's it's something that is so inherent to our personality and how we live our lives that I think it's just one thing that I really want to understand.
00:04:44
Speaker
And i mean, we're going to probably get into this. I mean, there's so many different forms of memory, but what memory... seems to have in common is plasticity in our brains, right? Right.
00:04:56
Speaker
So meaning changes in our brain. And these changes can persist for different times. Sometimes this is, and but in many cases, we we ah this is this is good for us that these memories persist over time.
00:05:12
Speaker
um Some are very strong. Some are very... Childhood memories, for instance, are very strong. They're triggered by olfactory cues, for instance, by experiences often related to food or pleasurable things.
00:05:26
Speaker
And um other memories basically are shorter. And some things we would rather forget and we should forget, right? and And not take into our repertoire.
00:05:38
Speaker
And all these fine-tuned different... forms of memory and changes will have neural correlates and that's our task, I guess, to understand how this this works.
00:05:49
Speaker
Yeah. And you know, what I thought was very interesting is you're totally right. Everyone can relate to this topic from a personal perspective. It's Deeks, we are our experiences, right? That's what you might that's what what you might as well say.
00:06:07
Speaker
and you often realize how important memory is in moments when it fails you. And, um, and it happens often. I mean, when you study, you try to learn new material, you spend so much time getting it in your head.
00:06:22
Speaker
And then all of a sudden there's the exam and you, you just go blank. Right. And I'm those moments I find, or even, even back then I found super interesting as annoying as they were when it happened or,
00:06:36
Speaker
You try to remember a name, the the tip of the tongue phenomenon. you You know you got it, but it's just not. You try to go through multiple cues to trigger it in some different way to get it out.
00:06:50
Speaker
And then sometimes you just give it a rest, wait five minutes, and it just comes out of nowhere. You know, all of these processes... from a personal experience level, I thought were super interesting.
00:07:03
Speaker
Back then, what brought me to memory were motor memories. I yeah i was always fascinated how can we learn these incredibly... um i mean, of course, what's and interesting as well is how do we remember facts? How do we remember events?
00:07:18
Speaker
But to me, motor memories were something that was so... It's like magic, because if you think of it, I mean, if you look at, you try to teach a robot to walk, it's it's incredibly difficult. yeah Or you you try to learn to play the piano, you can, and and no robot can, unless you pre-program the exact sequence. We have this this beautiful dance of, I think, what you what you alluded to.
00:07:46
Speaker
between the plasticity of learning something very complex and yet at the same time keep a flexibility in the system that allows you if things don't go exactly according to plan to to have some type of buffer.
00:08:02
Speaker
Right. which I thought was always very fascinating. And the more I learned about memory, the more I realized I don't think I understand what is happening at all. And that's why I think it's so so interesting to talk to you.
00:08:16
Speaker
Was there you know something specific that brought you to studying
David's Career Journey and Focus on Drosophila
00:08:20
Speaker
memory? I mean, when you look back at your career, when you started studying, was there something specific where you thought, oh, that's, I think I'll dig into this.
00:08:29
Speaker
um It's actually difficult to pinpoint because I think the general interest in how a brain works... that I can't really tell you when when this happened. I think this was very early in my childhood. I mean, I think also something that some people might relate to is trying to understand not just biology, but also physiology, but also history, right? To understand what actually makes humans human, what makes animals animals.
00:09:00
Speaker
how even have How do plants plants survive, right? I mean, any any kind of... biological process and life to me is super interesting and then life history so what can we learn from our own lives what can we learn from from ancestors what can we learn from history in general and i think something that always then pops out is the brain right so it's really i mean that's sort of where we know how information is stored, right?
00:09:31
Speaker
Right. um so So I think it's it's not that there was this moment where it said, I really wanted to go into memory research. um But so as so often in in in research, there there there were a lot of coincidences, right? So so um I started out working on synaptic plasticity, which is one of the bases probably of memory storage. Mm-hmm.
00:09:53
Speaker
As you can say, see i'm I'm being conservative, I'm saying probably, i mean, it's well established that synaptic plasticity will be involved in memory storage. um and And I started out from a very molecular angle.
00:10:06
Speaker
So understand trying to understand single proteins, how they work, how they change after synaptic contacts, so contacts between two nerve cells ah or a nerve cell and a muscle would change after ah usage, right? So this is something that is classic or that is that is typical for the brain, that that activity will shape future activities.
00:10:31
Speaker
um And this is also something to always keep in mind, I think. Brains are not silent. So even in rest periods, brains are very active. ah Nerve cells are very active. And this activity, that allows for a lot of plasticity and a lot of changes. Every time every time neurons are active, this will leave a leave ah a footprint, basically, a history in the end yeah to to what has happened.
00:10:58
Speaker
um so So going back to your question, so so I started working on a molecular basis and it's also, it was a development. So I started working in the model organism Drosophila. So this is a model organism.
00:11:14
Speaker
You'll know it from the kitchen. It's a fruit fly, right? I mean, yeah um it's actually not a fruit fly, but let's call it fruit fly. And it's it's a vinegar fly. um um And and ah basically these...
00:11:27
Speaker
These animals have been studied or the synapses, they have a neuromuscular, so nerve to muscle contact that is very accessible to research.
00:11:37
Speaker
And it's actually quite, in some aspects, similar to so our central brains because it uses glutamate primary neurotransmitter, like most of our excitatory neurons in in our brains and not like for us, acetylcholine. Yeah. so um So it's ah it's a model synapse um and a lot of the molecules are conserved. to what So they they use a lot of the proteins that our neurons also use. And this is also something fascinating when we look into evolution.
00:12:09
Speaker
Obviously, a lot of the machinery shared between many, many animals. It's a very ancient process. And a lot of release factors, I mean, you find them in budding yeast, or right? And you find receptors, neurotransmitter receptors. In the end, these are chemical receptors, right? I mean, you can find them in in and many organisms.
00:12:28
Speaker
um Also it was the plants and so on, right? so so So basically, um the the field had... had developed, so the Drosophila field had developed its analysis of centros of brain functions quite rapidly um in the years when I was working at the molecular level.
00:12:49
Speaker
And the idea of studying behavior, and this is going to be the readout for memory, right? Behavior, something the animal has learned. um This research had been ongoing since the 1970s.
00:13:02
Speaker
So combining genetics and behavior. And when talking about genetics, again, we have to go a bit into history here because genetics, so the model organism Drosophila was actually based on trying to understand the genetic basis of, for instance, body patterning, development, and then was taken in the 1970s to the next level, I would say, obviously biased from my side, and that's behavior, right?
Insights from Fruit Fly Research on Memory
00:13:27
Speaker
Mm-hmm. And so conditioning experiments, pairing a stimulus that has no inherent or little inherent valence or meaning to an animal to something that is meaningful, and then looking whether the...
00:13:43
Speaker
paired previously not meaningful for stimulus would predict something meaningful for the animal or in simpler words the animal would before not care about the stimulus and then suddenly care because it thinks that's this predicting for instance some food yeah um to look into that in the context of genetics right so so to look into if you if you have um specific genetic um genetic variants, where this will predict, for instance, the behaviors.
00:14:15
Speaker
And and this this this is still being done, and this is super interesting, but what really took the whole field a bit further was that it became possible to address single nerve cells in ah in a fly brain or nerve neural circuits, so yeah many a group of nerve cells, and then manipulate their activity. So in a way, remote control these, right?
00:14:39
Speaker
And if you if you can do that, this can give you a lot of information about how brains work and how behaviors are um in the end steered by a brain.
00:14:53
Speaker
Yeah. Wow. i I didn't realize it was, well, in air quotes, only since the 70s that the behavioral experiments in this direction started. I assumed it was already much longer going on, but this is very recent then.
00:15:11
Speaker
I mean, yeah fri was awful very, very recent. Yeah, for Drosophila. Yeah, yeah, yeah. I don't know why I thought this is going on for longer. So it's like the obvious thing to do, but as it As you said, it goes with any field. It just takes, ah most of the time things are built on top of each other. right exactly. So then when one thing happens, then people from a different department think like, hey.
00:15:34
Speaker
Exactly, exactly. We could do something here as well. Yeah, yeah, definitely, yeah. And that's super cool. And as you said, right, it's the the classical conditioning things. I mean, most people know the the um um the Pavlovian conditioning, right? With the dog and the bell and the food.
00:15:51
Speaker
And um but the the bell being the thing that normally doesn't mean anything. right And all of a sudden it's then coupled with with food. So if you then do this often enough and then you ring the bell, the dog knows it's time stand for some food. Yeah, I think we can all relate to that, right? Oh, for sure. For sure. For sure. Especially I was ah i had to take a trip. um last week and i was almost running late for my train but I had a few minutes left so all I had i had to grab some food very very quickly I didn't eat all day so of course what do you do I ran to McDonald's because I thought it would be quick and
00:16:36
Speaker
I thought it was quite interesting because they have, you can hear what's going on in the kitchen and you can hear the machine start to beep when, you know, the fries are ready and everyone can hear it, especially the ones directly waiting for their food.
00:16:51
Speaker
Yeah. So I can relate. Yeah. Yeah. Yeah. For sure. For sure. And I think it's it's something now that you're also ah putting like internal states like hunger into the game. i think I think this is something that is also fascinating in the context of memory because the memory, the recall of our memories, but also the strength of how memories are formed can be influenced, obviously, by our internal state. So it's not just the surrounding. It's not just...
00:17:19
Speaker
um our umwelt one could call it yeah but it's also the the internal yeah representation am i hungry am i sleepy and so on that can influence memory and also behavior a lot yeah yeah definitely oh i have already a million more questions on this But you are now studying Drosophila, so the fruit fly, which I mean, the vinegar fly, as as you have pointed out. eachla Which is quite interesting. I didn't know this. So this is already quite, you can be, a to everyone listening, you can now be a smart ass pointing these things out. and um
00:17:56
Speaker
What is it that we can learn from a fruit fly when it comes to memory? And... Start as simple as possible because I know this we can go very, very deep here. yeah so So let's start with actually sizes of brain in in the context of numbers.
00:18:18
Speaker
so So if we obviously look a, I'm just going to say fruit fly, fruit fly brain, right? yeah yeah We're talking not about, um were we're just talking about 150,000 neurons, roughly, maybe right? yeah And um so so we have to obviously also assume that this low number of neurons, relatively no low number, um is gonna reflect also the capacity of a brain.
00:18:47
Speaker
right um Again, being very conservative here because they're always, I mean, these are very very very clear assumptions, but the simpler system gets, the more complex it it can also get because single neurons might take over multiple roles.
00:19:04
Speaker
right So it's not really, we can't take the linear assumption that low numbers would mean low complexity. But still, I mean, it's something that we might be able to relate to.
00:19:14
Speaker
um so So that's that's ah one of the reasons, the technical practical reason to work with flies. The other technical practical reason is the very advanced genetic access, meaning that we can really use um um a lot of so-called genetic tools.
00:19:33
Speaker
to um monitor brain activity, genetic tools or sensors that are targeted to specific neuronal populations. So these can be populations of, for instance, dopaminergic neurons.
00:19:49
Speaker
We work with reward signaling, so dopaminergic neurons can be targeted. And here you can also see, again, high degree of conservation. so You might know, you certainly know, but also the listeners might know, dopamine um is heavily involved in um reward signaling in our brains in the end, right? Yeah. um And we find a lot of the neurotransmitters, I already mentioned glutamate and A2-choline in flies. So so the the basic components
00:20:22
Speaker
are there that would be in our brains. A lot of other basic components are also there that are in our brains. And um this makes it comparable to a certain extent to our brains.
00:20:35
Speaker
Now, there are also a lot of differences, right? So the general architecture of a brain, of a neuron even, um can be can be different from a million neurons. All the so all the all the the The input sites, the dendrites, the output sites, the axons, and so on, you'll find all of this, but the basic morphology can be different. So the shape of the neuron.
00:20:56
Speaker
right Also how the information is basically processed along the neuron, just also a very simple thing. If you have a small brain, you will have to, pro you can you can transduce information in a different way to a large brain, right?
00:21:12
Speaker
It's a matter of time yeah time and distance. So to me, the interesting things are finding out what similar, but also what is different. Because when we think about biology, there are so many different ways to reach something, but there are also constraints.
00:21:30
Speaker
So anything we can learn on how a biological system can solve a problem... obviously talking about brains here, is valuable, I think, at least to me, but also when we consider what you were saying, robots, right? How how many different, what are the constraints to have a system um perform a certain ah certain task? And now going down to memory again, again, we can't ask the fly,
00:21:57
Speaker
Can you memorize that? Yeah. Do you remember the picture of the dog you saw 10 days ago? Yeah, yeah. Also, another thing before before I go on, flies live for 60, 70 days, right? They don't live for just one day some sometimes. so And they can they can keep memories for a day up to a week even, right? so Really? Yeah, they they can they can memorize things.
00:22:17
Speaker
But obviously, the memories we're looking at need to be simple, right? Right. So this could be... Similar to the Pavlovian dog, this basically we expose the fly to an odor, smell something, and at the same time we provide a sugar reward.
00:22:35
Speaker
right And then we ask the fly, we didn't ask it obviously, but we give the fly a choice between an odor that does predict the sugar reward because it was paired previously, and odor that does not predict the odour the the sugar reward because it hadn't been paired.
00:22:51
Speaker
And then most flies or many flies will choose the odor that predicts the sugar reward. And it's obviously important that the odors previously have as little meaning to the fly as possible.
00:23:06
Speaker
Right? I'm again being conservative here. I can't say no meaning because obviously flies also have experiences that we can control for in in our research settings, but we can we cannot have flies not being exposed to anything. and but they They have to eat to survive, right? So so right food will have odors and so on and so forth.
00:23:27
Speaker
I mean, maybe there strategies, but this would be a whole own research topic by itself. Right, right. I mean, when it comes to the the usage of stimuli, I mean, it's you don't just guess, right? I mean, most research is just, they try out a lot of things and then they, um in in this case, you can quickly see if the fly were to choose on average fifty fifty you can say, okay, this is exactly this is as as as un- ah the biased as a stimulus could be. Exactly. And now we can use this for yeah the the the learning. But one week, I had no idea.
00:24:07
Speaker
Yeah, yeah i mean, that's an extreme case. But 24 hours definitely 24-hour memories. um They can form. And this is also something, again, so, I mean, your question was, but why study memory in the fly, right? Yeah.
00:24:20
Speaker
so So if we look at the hallmarks of memory, So many of the memories formed by fly, even when they're based on these simple associations, you can identify different memory traces.
00:24:33
Speaker
What are memory traces? Memory traces basically are manifestations of memory, so changes in neural circuits um that you can basically either perturb or study, visualize that represent a memory, right?
00:24:47
Speaker
So you have several parallel memory traces that can last different times, like minutes, hours, 24 hours, let's say 24 hours. many of these 24-hour memories, not all, but many require the flight to sleep.
00:25:00
Speaker
and um many of these twenty four hour memories not all but many require the flight to sleep right So something that is very inherent to our memories, right to to building like at least for fact memories, is that we need sleep to consolidate memories. It doesn't mean that you can't memorize things if you don't sleep. It's just the efficiency and there is very low. right i mean and um so So basically, these things these these very fundamental things and requirements um in memory processing that make me quite optimistic that the things that we learn in the fly, um to a certain degree at least, will um help us to understand our brains eventually.
00:25:44
Speaker
Right, right. And i think I really like what you said about...
Neural Mechanisms and Behavior Flexibility
00:25:50
Speaker
it's Of course, it's important to to figure out what is similar, but also what is different.
00:25:56
Speaker
And I always liked the most what is neuronally different, but behaviorally similar. yeah That is like, wait a minute, because that that shows us you can reach...
00:26:10
Speaker
the same goal or in this case, behavioral pattern yeah um or or skill in ah very different way of implementing it. um And that can tell you a lot about, well, maybe this was evolutionary, just a different you know branch off and then it happened this way. Or, well, this doesn't have to happen with acetylcholine, but can happen with glutamate.
00:26:34
Speaker
um does It does tell you a lot about all the individual knobs, I shall say, right? I mean, you have the neuron, you have the axon, you have the dendrites. How does the morphology influence things? How does it maybe not influence things?
00:26:51
Speaker
Which patterns might be, which behavioral patterns might be agnostic when it comes to um morphological changes, so which are not. And I think that's also when it comes to, well, hopefully later down the line, the more we understand, the more we know, maybe from a morphological perspective, when it comes to perturbations in human brains, where we may be in an, and now i'm I'm speaking very crudely, so all researchers out there, forgive me, but from ah let's say you have an MRI scan, which of course not the same as
00:27:24
Speaker
neuronal ah direct measurements but you find morphological anatomical abnormalities but behaviorally everything's okay i mean this is i shall say a curious case but we can that's also how we learn from um from these abnormalities in on the human side right that's a lot of famous cases have been done this way as well yeah and they taught us a lot. yeah And I think this is ah this is definitely interesting on the from the fly perspective.
00:28:00
Speaker
And yeah, I think it was super interesting what you said about all the different levels of memory. right We have the short-term memory, they can remember things shortly. Then we have consolidation.
00:28:13
Speaker
of People say moving, um well, consolidating the memory, but make making sure it stays with us and doesn't just vanish after a day.
00:28:24
Speaker
That sleep is super, super interesting and important. um Fly sleep? Fly sleep. They sleep, well, but up and to up up to 16 hours a day. So that they're they're very active in the morning. 16? 16, yeah. Then they have a nap in the afternoon, sort of like. They're very active in the morning, have a nap.
00:28:46
Speaker
And then in the evening, basically, they're active again and then they go to sleep. and It's like. They have little bouts of activity between, right? They don't necessarily sleep the whole night, but we don't either, right? We just don't remember waking up often, right? right yeah um um And in in general, um sleep is a very, very conserved feature in the animal kingdom again, right? and it's Right.
00:29:08
Speaker
Also, ah but I mean, there many, many ideas what we need sleep for. We know we need sleep to survive, right? And we know that we need sleep to stay alert, to to perform many, many tasks.
00:29:21
Speaker
um Besides memory, we also know that we know need sleep to consolidate, so to... make the memory permanent, to it in simple terms in the end. um But it's still unclear how or why this is so, so conserved throughout kingdom or the animal kingdom.
00:29:38
Speaker
It probably is quite important, I would say, yeah. And you mentioned these simple experimental paradigm. Well, let me say it sounds simple, but I mean, the way you measure things and what you manipulate in the background is is insanely complicated.
00:29:56
Speaker
um you You said, okay, we do that the classical conditioning, the pairing of an odor with a reward, and then exposing them to maybe maybe you want this odor or this odor, and then you see what's going to happen.
00:30:12
Speaker
But your manipulation, as you mentioned at the beginning, is on the genetic level. Yes. How do you do that? So first of all, I mean, just um to be to be, yeah, ah so so we didn't develop these assays, right? Right. So basically these assays are used all over the world. There's many, many research groups all over the world using these assays, developing these assays.
00:30:39
Speaker
And there's tremendous... speed in developing sensors to use geneticists. I'll get to your question. Right, right. No, no, no. That's fine. Take your time. So so so to to use the sensors I'm going to talk about in a sec yeah and so on.
00:30:55
Speaker
um And um yeah, it's it's it's it's basically um really... a classical example for science developing over decades um that allows to do that. And independently for different questions, things were developed.
00:31:15
Speaker
One thing that was developed at at one point was to introduce new genes to the fly genomes, genetic information. And the fly actually is a system that, or the fly system allows to do that for for many reasons. Other systems, um other animals are not so easily manipulated. Is it is it maybe, be it sorry for interrupting, is it because it is simple that it's?
00:31:42
Speaker
Yeah. um So if we if we go into the chromosome architecture. Yeah. So we have um a very small two larger ones and a third sex chromosome. Right. so So in the end, it's an overseable repertoire of chromosomes. We still have many, many genes on there. Right. I mean.
00:32:03
Speaker
um a lot of genes that are conserved to our system. Right, right. um and And without going into too much technical detail here, This has allowed researchers to map genes um with certain ease yeah because it definitely was not easy in the past.
00:32:26
Speaker
um And this also allowed for the Drosophila genome to be entangled pretty pretty timely in compar comparison to to other genomes, which allows for comparison between between genomes. And it's it's it's all this development in science with really many parallel research questions.
00:32:46
Speaker
So the initial questions were not on neuroscience, I guess, at least, right? I can't say. and I also doubt it. But then these things, like introducing so-called transgenes, allowed further developments and then to bring in transgenes that report neural activity, for instance. So if you're interested in understanding transgenes are dopaminergic neurons involved in reward signaling in the fly, you can introduce specifically to using using promoter elements.
00:33:18
Speaker
So basically genetic elements that are upstream of your gene of interest. So let's say dopaminergic neurons would express a dopamine um dopamine transporter, for instance, right? Right. So as an example, maybe you can take this dopamine transporter genetic information. So the promoter, this where the transcription factor binds. Again, let's not go into too much detail, I guess. We will later. Okay, we will. so so so so So basically you can use a specific sequence, yeah clone this.
00:33:50
Speaker
So molecularly clone this in front of your reported gene. and then bring this back to the, or bring this, or introduce this to the fly genome. That, again, through some other tricks, you in the future can basically express this indicator specifically in these neurons.
00:34:08
Speaker
And then when you provide the reward to the fly, monitor whether this these neurons are active. And this then allows really to visualize um at a very precise level neural activity.
00:34:20
Speaker
And this is basically, this is based on genetics. It's an incredibly precise level. yeah It doesn't get more precise than that, I guess. Or you can always get more precise. How do you get more precise than you? can You can get to the synaptic level, right? i mean Yeah, okay. and And there are attempts and there's also some success to do this do that, but it's it's I think there's no... The the precision can always improve. and And I mean, in the end, I mean...
00:34:48
Speaker
Ideally, we'll get to a understanding how things function live at the um atomic scale. i mean, that's that's in the end what we yeah maybe at some point would head towards. Yeah, yeah. eyes ah yeah Let's hope we got time, i guess.
00:35:07
Speaker
i don't I don't see it in the at least my foreseeable future that we will get there. Well, ah me neither. But, you know, ah with many things, it's it's things can you need one finding, yeah one development, one technology that can change a lot.
00:35:22
Speaker
sir So so i I think it's also one thing about being... Yeah, being in science is that to be optimistic. yeah Yeah, yeah, yeah. Stay curious. I think that's that's that's the that's the thing, right? it's ah it's a And that's why I find the exchange of ideas always so interesting, as you said at the beginning.
00:35:43
Speaker
mapping out the genome of the fly, the goal was not to then later on use this for neuroscience, it just happened. It was it was there. it They built fundamental knowledge that that can then be used in various areas of biology, which I think is insane.
00:36:06
Speaker
ah since and Also with the human genome that came afterwards, it's just insane. yeah And and how fast how fast they were able to do it only because they started with a fly.
00:36:16
Speaker
um Developing the tools and infrastructure and techniques. I'm still very impressed by this. I remember when I was a kid and it was announced on the news and I thought, Okay, I have no idea what they're doing and I don't know why it needs so many people to do this. Why does this cost so much money? But, well, we all grow up and then understand understand why this is so expensive.
00:36:40
Speaker
Well, I think it's, I mean, this expense is one thing, but I also think that... um it is I do have to explain a lot why we would work on flies and why this is interesting and why why won't why should i why yeah why do we do why right? yeah yeah and And it's it's it's basically... um The answer is very simple. it's It's something where we have a chance to progress our understanding.
00:37:10
Speaker
And I'm not saying that other avenues working, ah trying to understand brains and other animals and so on. Of course, we need that, right? yeah I mean, yeah. um But again, mean, this is something that is really interesting, or to me is really interesting, is exactly knowing the diversity, how, what we were talking about before, how can different brain architectures solve similar problems? Yeah, yeah.
00:37:37
Speaker
And we only understand this from from understanding how different brains work. um And one one thing to also put into, I mean, I personally am also just interested in enough how fly brain works, to be honest, right? i mean Right, right.
00:37:51
Speaker
um But it's also interesting when we talk about biodiversity and other insects that we basically need in, well, we need for our environment to upkeep our environment.
00:38:04
Speaker
um Obviously, um understanding how these brains just of the honeybee or something would work, which a honeybee obviously has to more to us visible at least complex behaviors than the fruit fly.
00:38:20
Speaker
That's true. Being conservative. Yeah. So it has honeybees have very, very, very interesting and and complex behaviors. Very complex. um And again, honeybees need to learn.
00:38:32
Speaker
Honeybees need to sleep. And so a lot of factors that can perturb these things right so understanding how the brains work of an insect or obviously honeybee brain will be different from a fly brain again sure the general
Comparing Fruit Fly and Honeybee Brains
00:38:48
Speaker
principles may also help to understand how we can um be better at preserving the habitats of these animals yeah yeah i think that's now that you bring in the the honeybee as an example i mean it's its brain is also more complex yeah than the the um the fly brain. I mean, in this case, the fruit fly brain.
00:39:11
Speaker
um Because I have not, maybe maybe I'm agnostic to it, I don't know. I have not seen that type of communication between fruit flies about, hey, yeah some food's over there.
00:39:26
Speaker
i've i' Because that means, if you if you think about this, this means that they can um not only encode spatial information, which I mean, you don't only have factual memory or let's say memory in the sense of, you know, coupled with a...
00:39:45
Speaker
um with a um olfactory stimulus and knowing it's a reward. Now you also encode spatial location with reward yeahp based on some reference frame, exactly which is quite complex. yeah And then you are also able to communicate it yeah in a specific way to...
00:40:12
Speaker
other bees. yeah Which is, i mean i mean, if we think about this, if I'm lost in a city and I ask for directions, some people know where it is, but they already fail at communicating the directions. No, little but navigation is a very interesting and important thing. And and flights can navigate. so i mean, they can they can really navigate and they're not bad in navigation, definitely. Right. and it's It's something very, very interesting. I think in the community, a lot of people are interested in how navigation works in the fly ah brain at the moment. so
00:40:48
Speaker
um And yeah, it's it's it's something that um is also inherent like memories inherent to to animals, right? animals need to, most animals at least, need to find food sources, right? Need to find, um find, made for reproduction, right? um So, so there's a lot of things we need to find, animals need to find. And again, there are things that are very, very,
00:41:14
Speaker
clearly conserved on the behavior level. And that's not just navigation or hunger or sleep, right? But then also memories. And and these these things are really the fundamental things that I think we can do we can we can study well in a system like Rosofield.
00:41:28
Speaker
Right. You know, one thing I found on um your website, it said, um it's a quote and it says, we aim at understanding the relevant computations at exactly those sites in the fly brain that are needed to express memory.
00:41:46
Speaker
Can you tell us a bit about those those sites? So, i mean, the the general assumption is that synaptic plasticity between very specific and well specific connections, so changes in synaptic strengths, changes in strength of communication will underlie memory, right?
00:42:07
Speaker
And um the advantage of the simple system, numerical simple system of the flies, and I'm going to jump into a brain structure called the mushroom bodies, right um which basically gets olfactory or factory it gets input from different layers so that you have the olfactory receptor neurons.
00:42:25
Speaker
They transduce the information via synapses to the to the next level. And these then so-called projection neurons transduce these olfactory informations to the mushroom bodies. And inherent to the mushroom bodies are so-called Kenyan cells.
00:42:42
Speaker
You have about, well let's say, two and a half thousand per hemisphere, so about 5,000 of these. um And these code for different odors or also a combination of odors, right?
00:42:56
Speaker
So this is a classical yeah a coding principle that we know from structures like the cerebellum and and others, where basically you have...
00:43:07
Speaker
I didn't say the number before, 150 projection neurons that would then give information to 2,500 Kenyan cells. So the information is diverging. yeah yeah um And this allows for combinations.
00:43:19
Speaker
This allows for representation of combinations of information. um And these Kenyan cells then get sparsely activated. So let's say 5%, an odor would activate 5% of the total number of Kenyan cells.
00:43:34
Speaker
And these Kenyan cells then synapse onto something 40 plus so-called mushroom body output neurons. So here we have a strong convergence, right? So basically the information is transduced to only a few cells and these few cells in the end would bias an animal. The activity would bias the animal to choose one or the other option. So if it's a reward and the animal's learned this sugar predicts something nice, sorry, this odor predicts something nice like a sugar,
00:44:07
Speaker
um then basically the synaptic strength of the Kenyan cell that is active through the odor exposure during the training process, um this ah this will then transduce information to these output neurons.
00:44:22
Speaker
And if we give us sugar at the same time, dopaminergic neurons that are overlap with the synapse between Kenyan cell and mushroom body output neuron would also get active.
00:44:33
Speaker
And when Kenyan cells and dopaminergic neurons get active at the same time, something at the connection Kenyan cell to mushroom body output neuron changes. And this is basically the synaptic, well, plasticity that we're looking for, right?
00:44:47
Speaker
And it has to be specific to these synapses because if you just change everything, so if you just change every Kenyan cell to muscle body output in your room, no information, right? There's no information that is stored because basically, yeah, it's just everything's changed. You need contrast.
00:45:03
Speaker
You need some specific connections to be changed. And when we want to pinpoint what happens, we need to identify the connections, meaning Kenyan cell the motion body output neuron connection, which we've done to a certain extent, and then really look into what really changes at the synapses. Readouts can be physiological readouts, meaning activity. yeah This can be measured by calcium, a second messenger, or voltage changes, um or um molecular changes.
00:45:32
Speaker
So I've already mentioned that receptor Receptor types for neurotransmitters are very conserved. um The machinery for output is conserved.
00:45:42
Speaker
And here's another very big difference between fly brain and our brains. So I was saying that flies use glutamate at the neuromuscular junction. We use glutamate in our central brains.
00:45:54
Speaker
We use S2-choline at our neuromuscular junctions. Flies use S2-choline mostly as excitatory transmitter in their brains. right So the Kenyan cell to mushroom body output neuron synapse is cholinergic. Now, you might say, who this we can't compare the whole thing now.
00:46:11
Speaker
yeah yeah But it turns out that the principles, meaning presynaptic release machinery of neurotransmitter, receptor principles in the post-synapse are remarkably conserved, even when the molecular identity on the post-synapse can be different, like glutamate or S2-choline receptors. Molecularly, they're very different, right? yeah But the the principles of needing one receptor type to induce plasticity and changes then of the receptor composition that will change the efficacy of the synapse, the principle is very conserved.
00:46:45
Speaker
so So again, finding these differences and similarities is is very rewarding because it's it's basically giving us a sense for for for the yeah all the options there are to design a brain that works. right Yeah, right. so but Okay, to get back to your question. So what we really want to do is want to see at a synapse,
00:47:10
Speaker
how it changes, how the molecular composite changes, how the functional parameter changes at exactly a synapse while an animal is learning. And to a certain extent, we are getting there, um but it's obviously a a long road and and it's... it's It's basically where research is leading to. We have pinpointed sites. That's basically the synapses, right?
00:47:36
Speaker
But what we're working on now is what exactly happens at the moment. How are the molecular components changed? Yeah. who Okay, that was a lot.
00:47:47
Speaker
um Sorry. No, no, don't be sorry. This is nice. This is really good. i just... I don't know where to start because I want to know more. m So when you say, so the so olfactory neurons go to the mushroom body, yeah there you have to the um the Kenyan cells that get activated.
00:48:10
Speaker
and So you have a divergence. yeah And then there is a convergence happening afterwards at the output neuron level.
00:48:18
Speaker
And the output changes as soon as you start, let's say the the learning process with the olfactory coupling olfactory of the information so the Kenyan cells get activated together with the... Dopaminergic.
00:48:38
Speaker
Dopaminergic. Thank you. With the dopaminergic neurons. And then the the pattern of the output activity changes. Yes. Which then correlates with the behavioral change. Yes, exactly. So, so um okay, we have to go into a bit more detail. That's fine. That's fine. That's fine. um So when we talk about the 40 plus output neurons, we can...
00:49:02
Speaker
For simplicity, imagine that we have two populations, right? Obviously not just two populations, but there's two populations. When you activate them, so use genetics to activate them, for instance, through light. So if you express light sensitive channels,
00:49:17
Speaker
in these neurons, when you activate them, you will bias a fly to run away from something or towards something. And let's just assume we have half of the population that would, when when stru being strongly active, bias a fly to run away and the other to approach something.
00:49:34
Speaker
And all of these cells get input from a Kenyan cell. Again, for simplicity, we're just going to talk about one Kenyan cell, which is not correct, but one Kenyan cell that is activated by an odor.
00:49:44
Speaker
Yeah. So odor A, we expose a fly to odor A. Odor A gives input to 40 Kenyan cells, 40 mushroom body output neurons. The Kenyan cell activated by odor A gives in input to 40 mushroom body output neurons, half of them when activated will advise the fly to run away and half of them to approach.
00:50:03
Speaker
What's the outcome? it's not going approach or run away. This is a naive, if the fly doesn't care about it. The fly doesn't care about the odor in the end.
00:50:16
Speaker
Now, let's take the scenario where we pair dopamine, so reward, to um to the odor. And the dopaminergic neurons now would change the strength of the connectivity between um between the ketnion cell and mushroom body output neurons, but not for all 40, but for only 20 of them.
00:50:41
Speaker
yeah So only for the ones, for instance, that tell the fly to run away. So we would weaken those connections in that case. Right. Long-term depression in the end. um And what would be the outcome? The next time Oda A activates the Kenyan cells, the synapses to the runaway neurons are weakened, and the ones to the approach neurons are strengthened.
00:51:04
Speaker
So if these are integrated downstream, this would bias the animal to... um display approach behavior. And this is a very simple way how a brain or plasticity in a brain system can influence behavior based on learned information.
00:51:22
Speaker
And have you, i don't even know if this is possible, have you tried to
00:51:31
Speaker
to stimulate only the mushroom body output neurons to see if, and in to stay with your example, without any learning, let's say that the fly was not exposed to any learning, but you have roughly, maybe you have an idea of which 20 neurons yeah would would lead to which type of approach or avoidance behavior.
00:51:56
Speaker
that you stimulate only those 20 neurons and you can see the behavior of the flight change? Or does it mean the entire um mechanism of learning needs to be in place specifically with the signaling of the dopaminergic neurons?
00:52:14
Speaker
Yeah. um So I think i think an experiment that addresses this um in a way would be the opposite, inhibiting um the output of mushroom body output neurons. So basically during a training process.
00:52:29
Speaker
Yes. Oh, sorry. No, sorry. Not during a training process. You can also do that, but um in a naive animal, right? Yeah. So let's imagine we take a naive animal. Again, no these animals aren't naive, right? Yeah, yeah, yeah. It's basically... ah Yeah, oversimplification. So basically an animal that we believe will not have a preference to odor, let's put this way. An animal that wasn't in the boot camp yet. Exactly.
00:52:57
Speaker
So this would be normally would be indifferent, right? So yeah would not... so so um to know But it's also not quite true. So if you give a fly the choice between air and most odors, not all odors, but at certain kind concentrations, the fly will avoid the odor and run towards the air. So it's probably a bit, doesn't know what's really going on. Yeah.
00:53:19
Speaker
Interesting. So it's balanced between two odors, but it would run away from many odors. And if we take one of these odors, it would initially run away from, right? And in this experiment block,
00:53:31
Speaker
and mushroom body output neuron that would be biasing towards avoidance, we would actually predict that we would get a result similar to when a fly has learned.
00:53:42
Speaker
Because the output or the input to the output neuron, meaning then the output of the output will be reduced, right? and yeah And this is exactly what we observed. And this was one of the experiments um that that led us towards formulating the functional model. And again, when I say us, then it's been a big research group that I was part of and also others in the world who worked on this in parallel.
00:54:07
Speaker
um um when we When we basically look into, um it do such an experiment, right we can actually change the avoidance behavior to an approachive behavior, just as if the fly had learned that this odor would predict a reward. That's crazy. So this, yeah, this this makes us pretty confident that that this is how it works in the end, yeah.
00:54:30
Speaker
Wow. Wow. I mean, it's... It's like flipping a switch. It is, isn't it? is It is amazing. But it's not a robot. and Of course not. of course i mean this is I mean, this is something that one could be tempted to think yes in in that moment. yeah it's It's not a robot. And it's it's really... These are extreme cases. Obviously, if we take this out.
00:54:52
Speaker
yes um And there's there's a lot of modulation. So so just... I mean, again, it's it's it's easy to underestimate a fly. But a fly, when you train a fly and ask it to...
00:55:03
Speaker
choose between the odours, one predicting the sugar and one not predicting the sugar. The fly needs to be hungry to actually recall the memory. Oh, basically, maybe it recalls the memory otherwise, but it doesn't care. It doesn't care, maybe. So there needs to be a sort of motivation for the fly to actually find this.
00:55:21
Speaker
And all this system, it's it's yeah it's definitely not like... it's I know what you mean with a switch. Yes, yes. But I understand what you're saying. yeah yeah it's ah It needs to be in a certain, let's say, state of...
00:55:35
Speaker
Wow. Okay. I would like to say arousal, but that's also not correct. It's a me more in a state that biases a certain type of behavior. Exactly. Or let's say necessitates it more. Exactly. That's a better phrase. yeah goza and and And then we can go into really, really interesting questions like attention, for instance. Yeah. Motivation, attention, all these things that are so important to us, right? Obviously, I mean, our life, when we talk about memories. Yes.
00:56:01
Speaker
How is our life shaped in an everyday fashion? Attention, right? To things. yeah How do we influence memories? yeah Attention. Attention. And I think and there's many factors like motivation, and we can maybe liken hunger to something like motivation, right? and Obviously, you're more motivated to find food at the station. Sure, yeah. and I'm pretty good at ignore McDonald's normally.
00:56:30
Speaker
It's those moments of weakness. Yeah. Yeah, exactly. And it's a I think it's important that you bring in attention because i but a lot of people around me, you know, they they sometimes say, oh, I'm really bad at memorizing at memorizing things.
00:56:46
Speaker
And I try to tell them, you are actually not bad at memorizing things. It's in the moments when you want to memorize things is that you immediately ah disrupt the process by...
00:57:01
Speaker
you know bombarding yourself with something else. right with With lots of different stimuli, your attention is scattered and the memory didn't have a chance to get formed in the first place.
00:57:12
Speaker
right And if you would not do that, everything would be fine. So it's not that you're inherently... There's something wrong with your memory system. It's just... you you're making it very difficult.
00:57:26
Speaker
Yeah, yeah, sure, sure. I mean, definitely, but yeah, I mean, this is just getting us to the next question again, right? Because obviously we are different between, there are differences between individuals, right ah even in flies again, right?
00:57:39
Speaker
Yeah. um so So you will always have a certain amount of flies who, so so we typically test flies or ask them whether they've memorized flies the odor, asking meaning giving choice, right? yeah um And you always get flies that take the other option.
00:57:59
Speaker
ah so so so Maybe they're not hungry enough. I don't know. It's possible. It's possible. um But you can find this and in in in many behaviors yeah for the fly.
00:58:11
Speaker
there's that But it also makes sense, right? There must be individual differences that allows also species to explore new things, right? And and I think this is something something that we also i mean you're totally right about the attention right i mean that is that's that's but but that's also i mean i think i think also the way we can focus our attention and so on is different between individuals for sure and and yeah this is super interesting for sure i think it's it speaks again to what you uh what you mentioned about that it's not a light switch and i think it's really important now to to to uh bring home it's
00:58:53
Speaker
any biological system is inherently not necessarily deterministic. So so it's there's always noise. and And to work with noise, you have to work then with probabilities and thresholds. And in biological systems, you also don't have you press something and something immediately happens. There's some lag, which introduces some more noise and all of these things. And the...
00:59:22
Speaker
The higher up um the higher up you go from molecular to neuronal, then to neuronal signaling, yeah synaptic transmission, and then classes of neurons being active or not active. it's Yeah, that's definitely not... um like a light switch, it's always involved with with probability. Right, right. Definitely, definitely.
00:59:48
Speaker
But it's great that you point out all these layers, yeah right?
Levels of Memory Study: From Molecular to Behavioral
00:59:52
Speaker
Because this is exactly what we try to do, right? We try to identify the network, the neuron, the synaptic connection, the molecules, and then we zoom out again. Yeah. Right. Then we go, okay, when we perturb this molecule, what is the effect on the neuron, on the network, on the behavior?
01:00:10
Speaker
And so I think the zooming in and out, this is this is the important thing. So identifying places where changes happen in the brain, getting a as good as possible um overview of what happens there yeah at as many levels as possible. as possible And then taking this information to then look in the big picture again, right?
01:00:32
Speaker
And then go and start again and start again, right? It's it's kind of like, yeah. rolling the stone, but still, we're kind of getting some information. yeah And um I think this is something that I find very important to not be not ignore layers that are molecular or behavior and so on and so forth, but to try and combine all of these. Yeah, for sure. as best As good as one can. Yeah, yeah yeah definitely.
01:01:01
Speaker
i think that's super, super important. um
01:01:07
Speaker
So thank you for mentioning ah how the neuronal connectivity in the system roughly works. And you mentioned, okay, you you have And I mean this as respectful as possible. simple The simple, the super simple system, which of course it isn't, but it's fine. I'm not a fly. It's a simpler system of neurons, which make it much, much easier to track what's happening, even though, of course, it's not.
01:01:37
Speaker
There's still a lot of data. I think most people don't realize how much data this still is. um
01:01:44
Speaker
You talked about the importance of sleep at the beginning, right? What happens, and and may I don't know if you looked into this or studied this, based on the neuronal um mechanisms that you mentioned, you know the the um the mushroom body, the input, the the the Kenyan cells,
01:02:05
Speaker
You have a pattern of activity during training, right? And and then recall, right? Just seeing what the behavior will do. Do you see changes in this activity when sleep is brought into play?
01:02:21
Speaker
Right, right. so that's a very interesting question. And and so when we look at neuronal activity related to sleep, I can tell you for the moment, we don't know. Okay. Right.
01:02:32
Speaker
um What we know from work of others is that sleep is required for a lot of memory. Consolidation, right? yeah But this is something we're trying to understand. yeah um But what we're getting more and more insight on is what actually happens on a physiological level when a fly goes to sleep, right? And what we think is happening is that we've studied this for a visual pathway now.
01:03:00
Speaker
Not olfactory pathway, but a visual pathway. and we Which is very complex. which is complex to a certain extent. So it's definitely complex in the eye, but it's downstream. um So this is a later path.
01:03:14
Speaker
And here you have um some relayed neurons. I'm just going to call them relayed neurons. yeah um So neurons that get input from cells that process visual information um and then transduces to a navigational circuit.
01:03:31
Speaker
So the navigational circuit requires the visual information for navigation, right? Mm-hmm. um And what happens is that during the day, we have two networks, feed-forward networks, that are permeable.
01:03:47
Speaker
So they transduce the information. And this is a mostly inhibitory network, GABAergic, so it inhibits downstream targets, and most at least mostly excitatory cholinergic network.
01:04:01
Speaker
um And these neurons start to oscillate meaning start to go into states of neuroactivity and non-activity over the time of day, meaning that in the morning when the flight doesn't have a high sleep drive,
01:04:19
Speaker
You won't observe this, but in the evening you do. And the more tired the fly gets, if it stays up all night even, um they get stronger and stronger, these oscillations. Right?
01:04:29
Speaker
Right. And these oscillations, yeah, kind of what we think is happening is that through these oscillations, you have... I'm going to call them down and up states in this case.
01:04:41
Speaker
In the down state, hyperpolarized, you will not transduce information that is basically brought to the animal by the visual system. But in the up states, you will. Okay. And in contrast to the daytime where all the information can go through all the time, right? So you're reducing the amount of information transduced downstream.
01:05:02
Speaker
Okay. and Now, remember I told you we have excitatory and inhibitory networks and they have the same target, the navigational cells. and it Now gets really interesting because this target, the dendrites of the navigation cells or head direction cells, signal the head direction of the fly,
01:05:18
Speaker
the synapses of the excitatory and inhibitory neuron are neighboring on these dendrites. Okay? So the connections are neighboring. And now just imagine we have a typical normal day and information is transduced via both, right? So you will get sometimes inhibitory input, sometimes excitatory, but the excitatory will be transduced and can be computed, right?
01:05:41
Speaker
Now just imagine we have a coherent activity through these oscillations between the two networks. yeah So the excitatory and inhibitory network are active and inactive at the same time.
01:05:53
Speaker
Again, this is what we observe. So this happens at night. So first, the individual cells of the inhibitory, mostly inhibitory network, I should say, they're mixed. They synchronize, then they synchronize the excitatory network.
01:06:06
Speaker
And this synchronization then allows, again, for very biased or for for temporal... unified input times to the next level.
01:06:17
Speaker
And this allows again for only partial information transduction and filtering out a lot of the visual information. And this is what we think happens when the fly goes to sleep, right? So the fly is basically going to sleep by filtering out sensory information.
01:06:35
Speaker
However, the filter cannot be absolute. right So if you just, again, if we have a switch, if we just yeah close it and something important happens, right some some strong stimulus comes, the fly wouldn't wake up. yeah right So we need some something that allows for some partial information for the animal to be able to wake up.
01:06:57
Speaker
and and And this is what we think is happening through such network interactions. And again, this is an example of a network computational principle that we then don't necessarily say is the same and in humans or mammals or whatever, right?
01:07:14
Speaker
But it's a strategy how the brain can achieve this. But if we zoom out again, i mean, if we look into our brains, mean, i mean We have structures like the thalamus, that is a feedforward area that is involved in creating oscillatory activity of networks. Right. can be with different principles, but the core idea of using such oscillatory activity is found in both brains. Again, can be different principles. Yeah.
01:07:41
Speaker
Could also be similar. We don't know yet. That would have been my next question. Are there delta waves in the fly brain? But it's... it's the the The answer is yes. yeah and we did discover these.
01:07:53
Speaker
And we also called them delta band activities because it is they are in the in the frequency range that is considered delta band activity in an EEG g in a human, right? Yeah.
01:08:07
Speaker
um I sometimes wish we hadn't caught them down. Because it it kind of, I mean, it's I think it's not wrong, but it does imply is wrong.
01:08:19
Speaker
is maybe the same kind of source as an human. I understand what you mean. I mean, there could be a real principle that we don't understand yet why it's at 1 hertz or 1.5 or 2 hertz or whatever, right? Right, right.
01:08:32
Speaker
So this means like one open peak in per second in the end, right, um of the filter. Yeah. Could be, but again, these are different network structures, different brains.
01:08:44
Speaker
It would be dangerous to say these are the same as delta waves in humans, which is very, very... tempting. Yeah, it's very tempting. Because it is basically the marker for deep sleep, slow wave sleep right in humans EEG g recordings, right? Right. And we know that these slow wave activities that we see in flies that fall into the delta band, right?
01:09:06
Speaker
um That they correlate to the deepest, so the highest strength of the oscillatory activity is correlated to the deepest sleep in the fly. So when the fly...
01:09:18
Speaker
is has the phase of most uninterrupted sleep in the night, we can see a maximum in in in network delta activity, right? Wow. So there are reasons to believe that, um well, fun on a functional level, there are definitely similarities.
01:09:36
Speaker
However, again, the the ways we measure this is different from an EEG in in humans. And yeah, I wouldn't go as far as say it's it's the same principle. It could be, right? Again, could be. um But the brain uses similar temporal frequency bands to achieve something that is comparable. This is something I think you can say yeah Yeah, yeah, and I think it's important that to that you say, um we met you i and say we you measure it in different ways. i mean, one electrode of an EEG is bigger than a fruit fly. yeah That to start with the simple hardware differences here. um
01:10:17
Speaker
And also um the EEG g is, ah it's it's it's on the scalp. Yes. And and that's... that much less precise and many, many different more sensors that you need for this. But but again, i mean, sorry, no problems talking about technology, that is still a very powerful it is measurement. Of course, right of course. Especially temporary resolution. is really so So I think it's always a question of what what you want to achieve, right? So sorry. yeah No, no, no, you're right. You're right. Definitely, you're right. I don't want to bash EEG too much. I normally bash and MRI more.
01:10:53
Speaker
ah Because I mean, for motor stuff, right it's it temporally ah very important. yeah and And of course, then you need high temporal resolution. route And sure, i then might not perfectly know where it's done, but do some maybe beamforming. and yeah Well, ah getting into them the technical details maybe later.
01:11:13
Speaker
um I think this is super interesting. And you are right. Calling it delta waves. might be a bit misleading, um or at least you need to form another memory that, hey, this is not exactly the same and we're only talking about the frequency band exclusively.
01:11:32
Speaker
um which is Which is very important, right? Because it's the the fly does not necessarily have the same, the fruit fly does not necessarily have the same structures. Exactly, exactly.
01:11:46
Speaker
And I thought what super interesting is that, yeah, you're right, deep sleep um and the delta waves in the human, it has been shown that by disrupting that, right, the deep sleep measured by then the delta waves,
01:12:03
Speaker
it does mess with your memory. Oh, yeah. Yeah. Like a lot. Yeah. Yeah. Can you tell us a bit about that? i mean, um in the end, I mean, we but oh but recognize that we need sleep, yeah deep sleep yeah for consolidation of at least some factual memories, right?
01:12:25
Speaker
um um so So I think that's that's not disputed. How exactly this works is... matter of research. Yeah. right And same for the fly.
01:12:35
Speaker
Same for the Same for the fly. I mean, we we know that, again, not for all memory forms, but for many memory forms, deep, so well, sleep at least is needed.
01:12:46
Speaker
There are studies that have uncovered forms of deep sleep in the fly. They're also fairly recent. So actually staging different sleep stages or analyzing them in the fly is is a very, very timely topic. um But they exist.
01:13:05
Speaker
Because i' i'm ah I would be wondering, but mean, talk talking about the human comparison again, we have the deep sleep, we have REM sleep, right and I mean, that the the fly oculomotor system, that I mean, they're there is that The fly isn't really moving the eye the same way we do. No, but it does move the eye, actually. Really? We don't know about sleep, but there's a study that um actually she shows that flies do have... um do can move their eyes, yeah. yeah really I did not know that. Yeah, it's it's amazing, yeah.
01:13:41
Speaker
But it's not our work, right? Right, right. but this But this would mean that... Wait, let me think. This would mean...
01:13:50
Speaker
the way they process visual information. So I mean, it's it's insane anyways, I mean, to start with. um And adding a layer of
01:14:06
Speaker
um reference frame transformation on top of it on a... Yeah. It leaves me a bit speechless, I must admit.
01:14:17
Speaker
Yeah, yeah. I mean, it's... Just from a computational perspective, that is... yeah that is a lot of computations that have to Oh yeah, yeah i guess so. And then you on top of that, you can navigate 3D because you can fly.
01:14:29
Speaker
That's something we can't do, yeah. yeah I mean, we can't with planes. Sure, yeah. and and and And a lot of technosensory assistance. Yes, exactly.
01:14:39
Speaker
No, it's it's amazing. I mean, the the whole whole thing is is is... I mean, the more we learn about the system of this very simple animal, the more we understand it's not that simple. Yeah, it's not that simple. um And it's it really also... yeah it's... Which is great. Yeah, it's great. I think that's great. I agree. I mean, um it's it's... I think...
01:15:03
Speaker
Brains, are yeah, is it's it's fascinating what brains can do. And visual systems, sorry, not just visual, but bright sensory systems. Yeah. and And it's this interplay of sensory information. mean, getting back to the beginning, right? I mean, just and everyday life, what happens?
01:15:23
Speaker
um We take on take take in information. We filter out irrelevant information. We integrate it into what we know, right?
01:15:35
Speaker
We predict what this means and what the outcome will be. Yeah. and And this is basically how we are, right? And and the fly probably, I mean, the fly does the same kind of thing, right?
01:15:47
Speaker
Yeah. Yeah. Yeah. and' so I mean, we just added a lot of oh yeah yeah societal complications. Oh, no, no. We added a, I'm not saying we're flies. No, no. But I understand what you mean. I mean, in essence, it is.
01:16:01
Speaker
the basic things that we want to do as an organism are yeah the same. yeah We don't do it the same way. We we want different things, but in principle, yeah we also want we also have to sleep, we also have to eat, yeah and we are, um say, autonomous agents in our environment. right right And that's basically it. and And we want to reproduce. And we're not flies. which we Yes, and we're not flies. And of course, we also do that in a different ways.
01:16:32
Speaker
Okay, I had no idea the fly can move there. Wow. um One thing I thought was very interesting that you when you when you talked about the the research on sleep and the activity um that you mentioned, the um the down and up states, and forgive me if I get this wrong, the head direction cells.
01:16:59
Speaker
Right. are very close to that to the um yeah to the other ones. Yes.
01:17:08
Speaker
I'm wondering if there is potentially some type of um orientation and coding then happening as well at the same time. During sleep?
01:17:19
Speaker
Yeah, yeah, yeah. Because it's ah you you you mentioned you have this filter. You mean dreaming? Not necessarily drinking. No, not necessarily drinking. I mean, yeah I wouldn't know. i don't know I don't know. I wouldn't know.
01:17:31
Speaker
But in a sense of, I mean, you you mentioned it a few times and it's it's one of the basic things, right? What what what what for fires together, that that wires together, not necessarily always, but it's, and if it fired together once, the likelihood it will fire together again is very high.
01:17:53
Speaker
So there must be some some some type of... i'm I'm just thinking out loud. I'm wondering what could be the potential relationship between those two things.
01:18:05
Speaker
No, it's interesting. I think the way... i mean, again, there's there's many options and there's interesting thoughts. But I think the the thing that ties the neuronal circuits together...
01:18:21
Speaker
um is is really choosing or helping the animal's brain to choose what to do. So this was basically a big question or has been a big question in the field. So we knew before that these neurons work from other groups discovered this also, that these neurons transducing the information to the head direction cells are involved in sleep regulation, right?
01:18:50
Speaker
And it was unclear how this fits together, similar to what you just asked. How does it fit together providing sensory input to to head direction cells and regulating sleep? And what we think is happening is basically these up and down states or the oscillations um Slow wave activity um basically allows this filtering process to allow for behaviors like sleep.
01:19:19
Speaker
but It's not necessarily a sleep switch, oh but basically i would i would assume that a lot of programs in the fly brain compete for what the animal is going to do next.
01:19:31
Speaker
And we're basically biasing through this filtering mechanism, biasing the whole process in a way of saying, okay, we're taking out world related things to a certain extent.
01:19:44
Speaker
And then we can take programs that are more relevant for self related things. And It's actually what we see. So if we use genetic tricks again to manipulate the activity of the neurons in a way similar to what we observe, so having the mentioned networks oscillate in this one hertz frame, then basically we don't just see flies going to sleep on ah and and on a pardon minute timescale, but we also see flies that start to groom.
01:20:22
Speaker
yeah So they start... Really? What we say, brushing their teeth. Yeah. So they they start programs that are independent of the external world to a certain extent.
01:20:33
Speaker
Right. And this is sort of what we think is happening, that the internal programs now can get or get a... get a get an advantage. yeah They compete. So sleep versus grooming and so on. And there are factors that we don't understand for the moment that would bias one or the other.
01:20:52
Speaker
um and and And that's what we think how it works. Yeah. Well, okay. That is, I think it's super fascinating.
01:21:03
Speaker
I mean, having these... um that you mentioned these competing programs it reminds me when i was in still at the university ah and studying and then they were showing us experimental paradigms of very simple you know arm reaching movements right and then they showed this in ah in a very elegant design and an mri study that both arm reaching program plans were active at the same time.
01:21:34
Speaker
and um of course, one of them won based on the manipulation you biased it towards, but it still meant both were active at the same time, which to me was insane because I always thought, well, why would I do that? yeah To me, it always seems like,
01:21:52
Speaker
I do one thing. Right, right. ah But that's just, yeah I guess, the f the information that I'm told afterwards. Well, no, no. I find this also very fascinating. Very fascinating. And it's, um I think, finding out what biases... I mean, we had this example with the mushroom bodies, right? I mean, again, we have this integrated activity.
01:22:14
Speaker
So the two arms run away or approach are active at the same time. Just one is more active than the other. Right, yes. And... It will be integrated at some point to then get to get the information Yannapur needs, right? and Right.
01:22:27
Speaker
so So having parallel streams of activity to bias a behavior, I think, yeah, to me makes total sense. and We just need to understand how how this works in the end.
01:22:38
Speaker
I mean, i'd like I'd like to think about the whole process and really having having these filter mechanisms throughout the brain to bias one thing over the other by excluding, the again, now the attention. maybe Maybe we can even talk about attention in this Yeah, let's do that.
01:22:54
Speaker
um So the attention towards a stimulus. So basically filtering out the visual stimulus means it's a partial filter, so it's semi-permeable.
01:23:05
Speaker
So um it's still information that goes through. right um and And this basically allows for flexibility again.
01:23:17
Speaker
right Flexibility if it's something important, strong to wake up or do or put the outside world on the map again if a predator comes, for instance, right? um Or not. And um yeah, this is we can find this on on on on different scales also. So the collaboration with a group in Birmingham ah basically just helped a little bit um um for this for this work.
01:23:45
Speaker
Basically, they found in in ah in a mating scheme um that when a male um was courting a female um and ah i know potentially a
01:23:57
Speaker
something, something, um a predator would come up. Right. So not a predator, but something that... During court. During courtship. During courtship. So basically what happens is ah when the when the male fly has progressed for a certain time, it will not abandon...
01:24:15
Speaker
mating, ah but carry on, right? When the thread comes in, right? like a sun-coast bias almost. And basically what what what um what the team found was that ah there's also a filtering mechanism, this time via dopaminergic neurons, different set of dopaminergic neurons, that would basically um gradually um shut down visual information processing again um in a different area of the brain. yeah
01:24:46
Speaker
um And then bias the animal to ignore basically the threat, the potential threat. right so So again, prioritization of information through guided changes in permeability of information, meaning activity of neurons to the downstream targets could be a common principle.
01:25:08
Speaker
That is very interesting. I mean,
01:25:15
Speaker
You would, I don't know how I would put it. you
01:25:20
Speaker
In simplistic terms, I would assume if the highest priority were to be to reproduce, that it doesn't matter when during courtship a predator comes in, you yeah you you leave in order to make sure let's try ah you that you're able to try again to reproduce. i I agree, but maybe it's also how many yeah chances do you get. Yeah, yeah yeah exactly. i mean i I think, I mean, the bias ah is is, I mean, towards, I mean,
01:26:00
Speaker
If you're close to reproduction, maybe you will ignore the threats right more. right And then it's a numbers game. It's a numbers game, yeah. in the end right And it's a gradual process over time. So, yeah, I think it can make sense. I think it makes sense.
01:26:18
Speaker
Trying to put this into human terms. Yeah, I think we shouldn't. We shouldn't. I'm just saying, well, if a predator comes along, i'm yeah. i i think i think I think this is just something that I think what we can take home for for for our discussion is really this prioritization of information flow. right But that is for the you mentioned that's for the male behavior. That's for the male behavior. Yeah.
01:26:41
Speaker
What does the female do? Don't know yet. Oh, don't know yet. Don't know yet. Okay. Okay. Still in progress. Okay. I'm curious. and Please let me know when something comes up. I said, I said, this This is the latest the latest research. this is ah I find this very interesting.
01:26:57
Speaker
but But also led by by sure different group. Sure. Yeah. But I'm sure you'll hear about it before I... and You know, another thing that I find interesting, now we we talked about sleep, we talked about consolidation, I mean, all of these effects on to memory itself.
01:27:15
Speaker
We talked about um the structural changes, the synaptic ones, um how neuronal activity based on learning and memory can can shape behavior.
01:27:28
Speaker
um We talked about attention. One thing that I'm super interested in is one hallmark of learning and memory being, of course, central part of it is if you learn one thing once and you want to learn something else that is very similar, you don't have to start from scratch.
01:27:52
Speaker
There is some type of generalization. We we all yes know that when you learn how learned how to say, ride simple city bike, you are able to ride road bike. yeah It's not, it's, you don't have to start from scratch. I would even go as far as you could even survive for a little bit on a motorcycle. Yeah. ah Is, is,
01:28:18
Speaker
are there um Is there research in this direction in the fly?
Learning Processes and Sensory Integration in Flies
01:28:23
Speaker
There is. And how would you do that? There's a lot. No, I think it's it's basically, ah one is context, for instance, right? Known context that can facilitate learning processes, memory performance.
01:28:35
Speaker
which is um being actively researched, right? um Multisensory experiences. um Flies can bind different experiences, different sensory modalities together, right?
01:28:48
Speaker
So then then things like conditioning, like how long can can a fly... um use traces of information. um So i think I think there's maybe, I mean, the the experiment that you you'd be hoping for, right, would be... Whichever one it is. Because, I mean, I really have no idea about experimental designs in the fly. Yeah. I mean, i'm um you tell me. No, I think i think there's there's many, many ways to approach it. It would stay at this simple...
01:29:20
Speaker
olfactory environment, you could basically um do um um secondary conditioning. So use an odor after you've conditioned it to something else, to something else, put it in a specific context. And things like this have been done, right? Yeah. And and the fly can do it.
01:29:37
Speaker
The fly can do it. The fly can do it, yeah. But if we if we really want to go into can a fly have ah very complex thing of really generalizing riding a motorbike to bike.
01:29:50
Speaker
i i know I think it's it's a reasonable question. I mean, it's not motorbike to bike. to bike yeah yeah yeah But I think it's a reasonable question. And I think that there are ways to to look into how a fly can actually and so instrumentalize knowledge to to perform new tasks.
01:30:08
Speaker
yeah And um I think the development is going exactly in that direction that people are trying to um produce information more and more complex behavioral paradigms. Right, exactly.
01:30:19
Speaker
um To study how can a fly do operant learning, instrumentalization-like learning, or transfer of information, right? Navigation. Navigation. um um and And this is exactly where the field is going. So it started in ah in a way with very classical conditioning. It's also still a big research topic.
01:30:43
Speaker
But yeah, I think this is something that people are actively working on, including us, yeah to really work on on the complexity of the behavior and then look into how the brain solves that, right? So this is a natural progression from going from...
01:30:58
Speaker
A very simple kind of memory, right? I mean, this's something everybody can relate to very i mean, it's it's an associative memory in the end, right? and Like any memory, will be an association in a way, right? Yes. So from an associative memory towards more complex tasks. yeah And let's see what we can do.
01:31:18
Speaker
Yeah, well yeah, yeah, definitely. i will I will write you often, I think, because um I find this a very fascinating topic. Cool. um memory in general but also it's we often think so much in you know fact-based memory right so it seems like you have this one snippet that is completely unrelated to something else that you try to remember but that's not how it goes and how to and and also from a information processing and storage perspective that is not how you would design any system it would be
01:31:53
Speaker
very wasteful. um Also not how the anatomical way the brain is structured is also not the same way. That's why I think generalization is so fascinating. It's almost like, um I shouldn't say the key to understanding memory, but an essential part understanding understand it because it is so essential to yeah the feature of memory that we have. But you know, this is also something that touches, again, these parallel memory traces. Yeah. yes Yes. So the importance of, again, having parallel streams, not just sensory, but also memory streams in the brain.
01:32:32
Speaker
Because if you learn something new, right, about something you learned before, right and that differs, and you'd overwrite that. Yes. Yeah, would be too much gain, right? Not much gain. so So having the opportunity of sorting things into consider already, yeah, in a framework, basically, um and allowing for exceptions in the end, right? Allowing for gaining new angles of information, I think is key. And yeah, I've...
01:33:00
Speaker
I think this is also going to be a trait that we will find in many animals. yeah Right. bill ya Yeah. And in the um human side of memory research, they talk a lot about ah pattern separation, pattern completion and things that, which I think are in essence the same yeah and the same thing you just mentioned. It's um the memory trace and how much information do you need for a memory trace to be reactivated um Or how much information do you need for it to be separate yeah from a different one, from from one you might already have that you want to keep. yeah
01:33:35
Speaker
hence it's very interesting. yeah And again, annete now we're going to imprecision of memory, right? Yes. I mean, this is also a very common thing that memories can be imprecise, wrong.
01:33:45
Speaker
We memorize things, we get prompted to memorize things. We think we remember things that we actually don't remember. Yes. um But again, this whole system is so plastic and has so many facets that maybe this is needed for also abstraction in the end, right?
01:34:03
Speaker
For sure. Yeah, for sure. um I have only a few questions left for you. Maybe maybe those are the most interesting ones. Okay.
The Thrill of Scientific Discovery and Collaboration
01:34:12
Speaker
Now, during all your time as a researcher, what was one of the findings that really surprised and excited you?
01:34:21
Speaker
Can be your own, doesn't have to be your own, but what was something like that? but that's super difficult question. It is. No, because I would have to select. I mean, to me, the most...
01:34:34
Speaker
Yeah, the best moments are when exactly the opposite result came out of the experiment and anticipated. Yeah. And this happens more often than i would have thought before entering my life as a researcher. um So so it's it's basically often predictions.
01:34:56
Speaker
um or just experiments that had been designed for different things that basically reveal what the idea is, what what the what the whole mechanism would be. And um I mean, there's there's really...
01:35:10
Speaker
um Yeah, been been many, many moments. And I think that's a good thing about being a researcher, right? yeah Research can be tough, as we both of us know, I guess.
01:35:22
Speaker
um And it can be very frustrating because it is basically we are constantly trying to understand something that was not understood before. which means it likely, I mean, we have to push boundary the boundaries constantly, right? Which means a lot of attempts fail.
01:35:40
Speaker
It's just how it is. Most of them fail. Most fail. And sometimes these failures turn out to be the most revealing things because they tell you something different. right And i think I think this is something that that shapes the life and then the reward is very high.
01:35:57
Speaker
And then you can totally live with frustration beforehand. So i i i honestly don't want to point a single finding I'm sorry. Don't be. Don't be. Because I feel that this would not be correct. Yeah. No, I understand. I can tell you, understanding the logic between how the mushroom body codes, I mean, this was a fantastic moment for instance, right? I believe you. um This was definitely fantastic.
01:36:25
Speaker
but Also, our discovery, um um um the our team's discovery then that Aztucolide was the or at least a main neurotransmitter of the mushroom bodies. Right.
01:36:36
Speaker
This was not known for decades. And this was also excluded by many researchers for technical reasons. Right. I mean, they they they were totally right to exclude it. Yeah.
01:36:47
Speaker
Based on the information they had. Sure. But the information, the new information, I mean, this is then just revealing when you're like, okay, nobody's ever seen this and now we've found the solution, right? Yeah. These kind of things are fantastic. Yeah. as it Which is an amazing feeling. Yeah.
01:37:02
Speaker
Also, I mean, more recent, the discovery of these this oscillatory filter. Yeah. This is fantastic. It's amazing. Post-synaptic plasticity mechanisms in fly memory storage.
01:37:17
Speaker
Great. I mean, these are that you know I wouldn't know what to select from. i sure I mean, you don't have to. it's ah it's not I'm not saying we did so many great things. i just so to I'm just saying, look that I think anything that is new and really also to certain degree surprising is rewarding.
01:37:36
Speaker
Yeah. And I think what's also great is, mean, I by by by far didn't have as many of those experiences as you. It's always teams, right? Sure, sure.
01:37:47
Speaker
But what I really enjoyed is when it happened, I could not wait to tell all my colleagues about it. It's like, look. what we found it's amazing look what this could mean for your work and this and this and this it felt like yeah it didn't feel like this was mine it felt like exactly yeah the whole this was for everyone exactly that's I think that's how it is right because I mean in the end science is a massive collaboration yeah international collaboration right and obviously there's always going to be some kind of competition also right that's natural to you
01:38:26
Speaker
unfortunately natural to humans. It is. um Or animal behavior. Yes. um But it is, in the end, a massive collaborative undertaking over generations. Yes. Generation spanning.
01:38:40
Speaker
um Things that we develop now will help future generations. I've pointed, I think I've pointed a few cases where things that were developed in the past have massively facilitated i'll work and I just want to mention this um once because I told you that these synapses um onto the head direction neurons are neighboring, right? This information, um the initial information came from a massive effort over the last years, not not done by us, but many, many labs in the world. We weren't part of this, but many fly labs and technical developments involved in that.
01:39:17
Speaker
um to solve the conic term of a fly brain, right? So basically the conic term means every single connection, nearly at least, right, of of neurons. So understanding, and you can use this as an open source, you can use the tool, go online and then click on your neuron and say, what is this connected to and where and so on. And it's fantastic. That's amazing. It's, it's, these things are revolutionizing things.
01:39:41
Speaker
And these, and and the beauty of this is is really, again, international collaborations, many working as a team. And I think, yeah, this hopefully will continue in the future. Yeah. Yeah.
01:39:55
Speaker
I hope so too. I'm pretty sure it will, but yeah we gotta, we gotta make sure it will. So it won't just go on by itself. Yeah. Well,
Resources for Further Exploration in Neurobiology
01:40:05
Speaker
okay. This brings me to the, I think this this nicely flows into the next question, which is, you know, what pressing questions in your field still need to be investigated? You mentioned things will, things are looking into the generalization part, the filters and things like this. yeah what are What are some other things that where you think, okay, this is
01:40:28
Speaker
No, I think i think ah eventually understanding how the different parts work together, I think that's the thing, right? I mean, we're zooming out again. yeah Exactly. I mean, it's a zooming in. I mean, obviously, we're not done with the zooming in. We need to understand a lot of the of the this of the circuits, of the networks, of the computations.
01:40:48
Speaker
um But in the end, we want to know how all this is integrated. And i mean, it's it's still a long path towards that. so So I think these kind of things um we need to understand. But what we also need to understand is, ah and I think it's science is going to move in that direction, we just don't just want to know how the insect Drosophila's brain works. We don't just want to know how, I don't know,
01:41:16
Speaker
how a mouse brain works. um um We need to understand how
01:41:23
Speaker
how different brain works, right? And I think this is something where um I would hope people will invest in and um to to get more diverse understanding of brain function.
01:41:38
Speaker
Meaning, yeah, what are what are the options? And this can mean working looking into closely related species or distantly related species. Yeah, I think both are very valuable. Exactly. um We can definitely learn something from that. Yeah.
01:41:53
Speaker
You know, for for the listeners who might want to learn more, are there any books or resources that you can recommend, either on the flybrain or fly memory or memory in general? so So I think anybody who's a little bit um who's interested in how brains look like...
01:42:11
Speaker
You can find the fly brain connectome online. I think this is something to play around with if you're interested in these kind of things. But otherwise, i mean, there's a lot of um ah literature also on the basis of fly-in neurobiology that is open source that I...
01:42:28
Speaker
You can just Google um basically, um but there's there's there's quite some resources. um And I think just, yeah, I mean, there's, i wouldn't know what to pinpoint now, but there's there's great ah literature on on on new developments and and and brain science. So I think there's a lot of to offer on the net. And I think ah there's, yeah, I think I can't pinpoint anything. No, no, nos no. It's all good. I just thought maybe there's yeah maybe you have some favorite book where a lot of friends that are not scientists might have asked you.
Conclusion and Further Engagement
01:43:05
Speaker
um
01:43:06
Speaker
But you don't have to pinpoint anything because all of those resources that you just mentioned, I'll find those and I'll put them into the show notes on the website anyways. Perfect. Also linked to your website so that people can...
01:43:18
Speaker
find papers that you did and and other labs what they are working on and the connectome as well so that they can find that immediately David, I don't know what to say. I think we can go on for a long time. I have, I think I have so many more questions for you, but we've been already talking for quite some time.
01:43:35
Speaker
and know you're super busy. i want to thank you very much for this conversation. Thank you for your time. Thank you. And um I'll link everything in the show notes also where people can find you if they want to reach out or other researchers that hear now for the first time about the work you're doing and maybe want to collaborate.
01:43:54
Speaker
Thanks a lot. And well, to all the listeners, have a great day. And thank you for having me. And also, bye and have a great day. Hey everyone, just one more thing before you go.
01:44:07
Speaker
I hope you enjoyed the show and to stay up to date with future episodes and extra content, you can sign up to the blog and you'll get an email every Friday that provides some fun before you head off for the weekend.
01:44:19
Speaker
Don't worry, it'll be a short email where I share cool things that I have found or what I've been up to. If you want to receive that, just go to ajmal.com, A-D-J-M-A-L.com and you can sign up right there.
01:44:33
Speaker
I hope you enjoy. it