S3 #48 What happens in the brain of your cat? Brain-to-brain with Dr. Sevim Isparta and Prof. Nadja Freund.

Introduction

0:00Hi and welcome to Kaleidoscience. Here you find answers about cognition that you may or may not have asked yourself. This episode is hosted by Imogen Hüsing and Elisa Palme. So sit back, relax and enjoy this week's episode. Growing up with cats and sharing my flat with a cat now, I was always fascinated by the question of what might be happening in their brains. Therefore, I'm super excited about our guests in this episode, Sevim Ispata and Nadja Freund, with whom we will be talking about cat behavior and especially cat brain structure and cognition. Welcome.

Guest Introduction

0:36Sevim Ispata is a doctor of veterinarian medicine and did a PhD at Ankara University and was later on afterwards research assisted at Ruhevind University in Bochum in the area of biopsychology and experimental molecular psychiatry. She then held a postdoctoral position at the University of Bari-Aldo-Muru in the area of animal physiology and behavior and is now about to begin a new postdoctoral position at the domestication lab of the University of Veterinarian Medicine in Vienna, Austria, where she will work on hemispheric asymmetries in canine face perception.

1:18Nadja Freund started her career at the University of Bari-Aldo-Muru in Bochum with a study program in biochemistry and did her PhD in biopsychology at the same university. She has previously been a researcher at institutions such as Harvard Medical School and the Karl Ebertz University in Tübingen and now is holding a professorship for experimental and molecular psychiatry at the LWL University Clinic at the Department of Psychiatry, Psychotherapy and Preventive Medicine.

Get to Know Game

1:52Welcome and we're really excited to have you here. Welcome. Thank you for having us. Yeah, and before we get into the scientific part of today's episode, we want to play our usual get-to-know game with you. So I will give you the beginnings of five sentences and your task is to finish them as spontaneously as possible. And the first sentence is, as a kid, I always wanted to be. Who of us should start?

2:23You are the professor, please. And nurse for children. Nurse for children? Yeah. Nice. I was always very curious about science and used to read science magazines, especially about biology and animals. And I always wanted to do something related to science, but for a while I also wanted to be an anarchologist, but I also lost my interest over time. And at some point I also thought about becoming a police officer to catch bad people or going to the sports academy.

2:58Interesting. The second sentence is, if I was an emoji, I would be happy one. A specific happy one or just?

3:13Well, maybe I'm too old to know all the specific grown ones. But I know for sure that I want to be a happy one. Yeah, for me also happy one, but with the tears nearby the eyes, like really smiling one. And laughing one. Nice. The third sentence is, my favorite thing to do on a day off is? Spend time with my family.

3:46Playing tennis.

3:50Very cool. And the fourth sentence is, right now I'm most fascinated by? Society.

4:03Anything in particular about society?

4:09I feel a bit like, I thought about society a lot after the pandemic and all that changing now. And this, like, before I never had those thoughts. And now I really got into, like, thinking about all the aspects. And, yeah, I guess with all the change that happened in the last couple of years.

4:32Good reply. I should find also something very deep after this reply.

4:40Being spontaneous helps. Yeah, true, true. If you are talking from the science-wise, I will say I'm most fascinated by people's attention or interest to our research, I will say. I feel like cats are a good hook because so many people have connections to cats. So, yeah, easy entrance. All right, and then we come to our last sentence, which is, I know it's time to call it a day when.

5:20Often I don't know.

5:29Yeah. I also don't have concrete reply for this, I think. Seven was a night owl as well, so I think it was the same for the two of us.

5:44Fair. I think it's a hard question, especially when you're in research, because then you're usually like, okay, I still have to get that done. And on some days it's quite late, and other days you can quit earlier. So it's, there's no specific time. I think our most common answer is when I can't focus on this one sentence I'm trying to read.

Scientific Background

6:06And before we start into the topic of today's episode, we also want to talk about your scientific background. So from your perspective, how you ended up in this research project. Well, I can tell you that I ended up in this research project because of seven. So for me, it's kind of like, well, it starts when, like, we met, like, very randomly when she was doing an internship with my former PhD supervisor.

6:48And all I remember is that we had some barbecue event and we needed another barbecue. So I went to my supervisor's, former supervisor's department and asked for barbecue. And somehow, Seven and I ended up going to my lab with the barbecue. And she was really helpful. And I think I even said something, like, to my people, like, oh, I found a new PhD student choking. And then a couple of years later, after that internship, actually, we sat together again, like, with some people from my former PhD supervisor's lab.

7:22And several met others and discussed about her PhD project. That's how she ended up in my lab. And, yeah, and then we did the PhD, like, doing the project, doing her PhD together. And we stayed in contact afterwards. And then at some point she approached me and was like, oh, we have this great idea with CAD and other labs. And I think you would be a great fit. But, yeah, and so that's how it went for me. And then maybe Seven can tell you more about the idea, how it started.

7:56Yeah, but you well described. But also you forget that we went to the dinner all together with Onur and other labs. And we also had some guests from Japan. And we met there. It was, like, a round table. And we were just six people. And I was just, like, the first week of my internship, I also found myself with all the professors and all important people. Yeah, because it was the dinner. And everyone was invited after the talk. And I was very happy to join. And from here, I will say all the people who started their scientific career, they should join all the meetings, all the dinners, and all the social events.

8:38Because it is very important to know people. Because after even some years, you can say, oh, I know X people. I know these people. Because I think it's very important to connect. Yeah, Nadia is totally correct. And I also remember how we carried the barbecue all the way. And it was very fun.

Research Project

9:00Yeah, from the scientific perspective, as you already mentioned, I'm a veterinarian. And I have been always interested in the laterality. And I'm working on the different species, rats, cats, and dogs. And after my PhD was done, and I moved to Bari. And during our all discussions with our other colleagues also, then we thought, because we really wanted to have an idea about the general literature profile of the cats.

9:33Not only because of pole preference, but also the tail positioning, how they communicate people, and also their sleeping positions, like the overall general literature patterns. Because the cats are not that much studied, as compared to dogs. And then we decided to have a big international researcher group, all together from Canada, Italy, Germany, and Turkey.

10:05Then we just started the project, and the interest, maybe Nadia can mention more, because we got the biggest attention from Germany. And we had more than 10,000 participants. And now we are trying to analyze all the videos, all together. Yeah, so you already briefly mentioned that you got video submissions.

Video Analysis

10:31Maybe you can directly start with what type of videos you're analyzing and where you get your videos from. We asked the cat caregivers to record their kids during the different social interactions with their caregivers, and also during some spontaneous behaviors. And they recorded for us, and we also gave them like a short demographical information form. And they are recording the videos, and they are sending us, and now we are analyzing the positioning from the laterality aspect.

11:10And also before we started the citizen science project, we also had like a pilot study with YouTube videos, YouTube cat videos. And since the sleeping position is more observable, and it's easy to observe. And also we had some good hypothesis about it, because the cats are very special for sleeping behavior. And then we started with that project, and we found the population level, leftward population level bias. Then we continue, and we also would like to get into deeper for the sleeping patterns as well.

11:47So now we are analyzing the videos for the, like a paw preference, like determine the paw preference, also the tail positioning, different context, like a different emotional context, how they are using their tails for the communication. And we are also measuring the sleeping patterns of the cats. Maybe for listeners to get an idea of what the cat owners sent in, because I also, my cat is also somewhere in the data set.

12:22Could you maybe, could you maybe just briefly explain what kinds of behaviors or propositions, etc., you were asking for in the videos? So people can get an idea of what type of video material you're analyzing exactly. Because I remember that there were some instructions of, for example, that your cat kind of get into a, not quite toy, but get them, for example, a roll of toilet paper with some treats and film of which paw they're using, etc., like those instructions.

12:54Yeah, so we asked the caregivers to, one thing I remember was, one thing I remember was, they should call their cats and record the cat while they are coming. I, one position was like just recording the cat while the cat is resting. And then we also asked the caregivers to play a little game with their cats, though they should hide like a treat in, in, in, in something small, like for example, like the, the roll of a, of toilet paper.

13:26So like something where like only paw, one paw would fit in, so that the cat would have to use one paw to reach for the treat, and they should record the cat reaching for the toy. So, um, you, uh, on the one hand, you asked for, um, uh, videos of, um, certain behaviors, and, um, uh, on the other hand, you also asked for, um, uh, pictures, uh, of the cat sleeping and, um, a sleep diary.

14:00Exactly, exactly, and we also had some questionnaires, a little bit information about the cats, like, um, sex of the cat, age of the cat, um, things like that. And then also, um, a little bit of the, the, like general behavior, um, of the, of the cat. And I think a little bit also interaction of the, like, caregiver attachment form we gave, caregiver attachment we gave, and we had a cat demographic.

14:30And also for the tail positioning, we asked a different context, like approaching, and, um, resting, I think, and it should be one more.

14:46You, uh, dropped a term, um, in your answer, um, and that was a citizen science project. Um, could you briefly explain what, um, citizen science means? Yeah, so in, in, in general, it means that you involve the general public to participate in, in your science. Um, yeah, this can be done in, like, different ways. I've seen projects where they really, like, invite people to come to, to the lab and, like, pipe it things, like we're saying.

15:20Um, yeah, and in our case, this was, like, um, yeah, asking the cat owners, like, to send these videos and pictures and things of their, of their cats. Um, what, um, what, um, benefits, um, do the citizen science project bring? Well, I, I, I gave a good start with my society answer at the beginning, um, and already mentioned that I feel like a lot changed since the pandemic.

15:51And I also have a feeling that, um, with everything suddenly, um, being so strange and, and different from what we had known before, um, the pandemic brought a lot of discussion. And I was a bit scared and, and I'm worried that also a lot of people, like, even in, in my, like, my private life, I realized that, that how hard it is for people to understand science and where they were, like, like, why would we have to close schools? Now we know it wasn't that bad in schools and, and, and, and, like, the people had this feeling that even science would, like, know right away.

16:28And it was, like, uh, uh, this, the science would give a yes or no answer. And, like, I, I had to explain to, like, parents and so, like, like, what's the statistics? And, and, and, and, like, that in science, we don't get a clear answer of yes or no, but we have a, like, a likelihood and, and all those things. And, um, and that really made me aware of, we, we need to, to teach more of what science can tell us and also, like, what science cannot, um, and what does, what does it not mean?

16:59And I feel like with a project like this, I, I really hope that people get involved a little bit more in science and, and learn more what it does. And then at the same time, I, I hope that with the cats, we maybe get, like, kids involved and also get, like, this interest of, of science and maybe even want to become, become a scientist later on. Yeah, so I see there are a lot of benefits. I don't know, Sevin, if you want to add to it. Yeah, the sample size is always higher and I'm also happy with it in general, like, um, because when you do the experiments, of course, um, you can also have a big, um, like a large data set, but when you, when the citizens are involved, of course, you will have a larger data set.

17:48And so this also increase the robustness of the results and then the reliability of the results. Of course, there are also some limitations are, uh, as already Nadia mentioned, some of them, like, it's not always easy to get like a really reliable or valid data points. Um, from the, the, um, um, the people out, outside of the, the science, but in general, when you describe perfectly and when you support them, um, when they are really keen to do, and especially cat owners.

18:20And I always prefer to say actually caregivers, but yes, cat owners, um, are also keen to do it and they really follow the rules and guidelines and they are trying their best to, to provide you the, the most valuable data set. So it is very nice cooperation. And then of course, uh, it is increasing the, the reliability of the study and, uh, the power. And see, I feel now we already had one example to where it is important to, to talk and exchange because, um, by me making this mistake of cat owner, which is just in my vocabulary, um, I wouldn't think about it.

19:00I would always say like cat owners, like, why, why not? But then when seven points it out, it's like, yeah, it makes total sense. It's not, the cat is not owned by someone you should say caregiver. And this is really a process where I learn a lot, where I think about like the role of the caregiver and all that. And I think this was just like a perfect example of my, like talking about science, but like talking to people. And why also, if you exchange like your thoughts and your viewpoints with like the general public is really helpful.

19:30Yeah. Yeah. Even for me, the owner comes first and you already realize because as a veterinarian, especially when you are working at the clinic, you are always calling them like an owner owner. Then it's not easy to even change, um, as a veterinarian, but nowadays we are trying to, to use the most common and most like the better terminology in general. Yeah. And just coming back to the videos, I would also assume that having read videos in the home environment also changes compared to getting cats in the lab because cats especially are usually not used to changing environments.

20:07Then they're stressed and they behave differently. So just the recording at home, I guess, will also give you a more realistic cat, usual cat behavior, um, compared to other measurement methods, which you could, for example, use with human participants. Yeah, exactly. Yeah, exactly. Especially with cats. We really wanted to, um, study at their own environment, um, to avoid any stress related changes or any bias because, uh, as you said, cats don't in general, don't like to change the environment and their routines.

20:43And when you want to, to really investigate the natural behavior of the cats, also it's same for dogs, but, uh, it gets, it's, I think a little bit more important because dogs are in general get used to be with their owners, like their caregivers to go to the clinics or to go to the different environments. Uh, but with cats, exactly. This was one of the other reason that we wanted to do it with, um, um, as a citizen science project.

Citizen Science Project

21:11Um, I'm, I just have one question regarding the videos. Um, how do you analyze them? So do you use a video tagging tool where you kind of track your behavior or, because I've also done video research in my bachelor's thesis. And I remember just using timestamps and describing the behavior on the timestamp. I was, it wasn't chimpanzee. So I used gestures and specific codes for that, but how are you analyzing the videos you get? Because if you have such a large dataset, it, it must be quite time intense to get the data out of it.

21:45Yeah. Well, good question. And that's why we cannot talk about results yet, because we really learned that this is very challenging. And, and yeah, Sam already mentioned that like with citizen science project, there's like a great value, but then there's always like a downside of it. And this was something that we realized. Um, yeah. Um, right at the beginning when we looked at the videos that due to the asking, um, people to send videos and not having like a lab setting where everything always stays the same.

22:20Um, using a tool to, um, analyze the videos, um, computerized is not possible. So we have to do it. Um, yeah. By watching the videos and, and this is, we get just figuring out, like dividing the videos between, between all the groups. Like we ask like students, uh, for help and, and we have to figure out if we can maybe like sort them in a way where we, we, they are the same. And then we'll like sorted videos. We can have analyzing tools, but it's not as simple as if we have.

22:52Like a pre. Set setting where we put, like would put the cat in like one corner and would have it do something that it's, it's like with now the tools, it's pretty simple. And it's also nice because you don't have the bias of, of the people watching it. Um, but this is not possible with the videos we got. Okay. Exactly. I totally agree. Yeah. For the poll preferences in, maybe if I give you a little bit more detail for the poll preferences, we, um, we are checking the each manipulation, like a right, left, right, left.

23:27And there are also formulas at the end. You can use either laterality index or Z score to define the, the strength of the laterality and also the directional information you can get from it for the tail. Um, based analysis, as you said, we also use some tracking programs, but it's not there already mentioned. We have to do it manually because when you work with the, for instance, laboratory animals, the environment and the setup are always the same. Even the, the, the color of the animals are always the same.

23:57So you can use some automated tools to, to track analysis, um, video from the videos. But, um, when you record something like we get, you have to do it manually. Therefore it takes longer. But, um, since we are also doing like a different groups, we also need to check the interrate reliability, uh, between the raters. So it's a lot of work, but we are very happy that we have many data points. Yeah, the, um, uh, the project got a lot of attention, especially in Germany, right?

24:32Um, uh, when I was Googling, um, just cat study, like the, but the German term Katzenstudie, um, it directly pointed me to your, uh, study. I didn't even have to add, uh, or anything. Yep. We did not expect that. So this was really, I was really surprised because yeah, we, we, yeah. And it wasn't like really planned, like such a big study or so.

25:02Um, yeah, we, I think we hope like to get like a hundred, uh, registered cat out of each, each country or something like that. And, and, and it was basically by chance. So as several mentioned, we have had a publication before. And so we were in contact with our PR department about that study. And then my student who was involved in the study came to me and said, oh, there's like a homepage of the university where you can post citizen science projects. And I just learned that like the PR department is also responsible for this side.

25:34So do you think it makes sense to contact the person I had previously been in contact about the other study, about the new study? And I was like, oh yeah, great. Sure. And then he later came and said, like, she was, um, um, she was interested and she was like, um, oh, maybe we can even have like a short press release. And he, I, he asked like, oh, I should, I just give my contact information. And I, I think this was like two weeks or three weeks before I left for summer vacation. I was like, oh yeah, perfect. Just give you a phone number. I think this was my biggest mistake because I saw like this one or two people who might call is fine if they call my PhD student.

26:12And I'm kind of like about to prepare for my summer vacation anyways. Um, yeah. And then like the first day, um, when the, the press release got out, like he came to me, to my office, like every five minutes and was like, now, like I, I got a call from like, I think the radio station. And I think there was something with like kids involved, but it was like, could you do this? And then assert saying, um, and then even when I left, um, at night, like he called again saying like there was another call.

26:44So we realized, okay, it might be a bit, a bit bigger. And then in the next morning, when I came to the office, he's like, okay. Uh, someone, um, from like TV will come in like two hours, but I don't feel comfortable when you do it. And then it really exploded. Um, it was really crazy. Like for the two weeks, um, we got, like, I know that there was like, I was doing interviews in my office while he was doing interviews, um, in the other office. And at some point we really had to sit together with all our collaboration partners and decide, okay, what gonna do?

27:19Where do we say like, no, this is like, oh, our capacities. Or with some even like, where do we feel comfortable with, or where would we say like, maybe this is not a good decision. And yeah, I would not have thought that this gets so big. And even now, like, so as with you, so of course it's not as crazy, um, as it was in summer, but still like every month we get one or two. Um, yeah, like contact where they ask for like, like a podcast or, um, I think the other day, my student taught me that they, they, they, um, recording like a general kids TV show about cats.

28:00But he was asked to, um, read the script and, and edit. If, if he thinks something, um, should be added and things like that. So it's really nice. Yeah. It certainly was on Italian TV a couple of weeks ago. Yeah. It was about our cat sleeping paper. Yes. It was an interesting experience.

Media Attention

28:19And if you are a scientist, you can find yourself suddenly on a, like a national TV. Yeah. But we are very happy because I think it's really connect people to science because especially for kids, not only for kids, but especially for kids, it's very nice that they see the results of the scientific projects in an interesting way. But of course we didn't do it to get that much attention, but it was also somehow consequences. And we were also all, um, surprised.

28:51But then I realized that if you are doing something with cats, it is like really the cat owners really wants to know a lot about their cats. And they're very keen to participate the studies, which is very good. And it is very cooperative way for us, but also it's another clue. I think for the people who wants to do citizen science, maybe now they can confirm this observation. And that's not at least how I feel. I think you found a very good moment to share the press release because it was a summer time and it was a holiday and people were really checking the TV and other, um, or social media.

29:29Then people had the time to do it because for instance, when we released the press in Turkey, uh, it was a very chaotic moment for like a different political reasons. And like all the news were talking about this and at that time it didn't get that much attention for instance. So I think it's also very important to choose the time when you want to announce the study. Absolutely. And also didn't realize, I think it was like the press release was like 10 days or two weeks before the international cat day.

30:03It was quite funny because I also had heard of the project and I think three of my podcasts of this podcast I'm listening to. And then one of them, it was like at the end of the episode, they were like, okay, that was the bad news of the, of yesterday or today. Here's the good news. They are doing a cat study.

30:33Yeah, because there are many topics under explored with cats because cats are living with us for thousands of years, but we still don't really know how they perceive the world, how they think, because it's always the mystery with cats, right? They are very sometimes independent and they're like a queens or kings at home. And they're also acting like our owners sometimes. So, of course, it gets a lot of attention and also people wants to know, we are all also curious about it.

Cat Behavior Focus

31:03You may be getting back to cat behavior here. What could you maybe just tell us what cat behaviors you're focusing on in your research? So you've already touched on sleep, pause. Is there anything else you are focusing on? In our city science project, we are also interested in the tail positioning because tail is very important for the communication, both in intraspecies and interspecies. So, for instance, with dogs, we know a little bit about the tail wagging when, depending on the emotional context, you can see sometimes they wag their tails on the right more or the left more.

31:47But with cats, it's just underexplored at all. And we don't know that much. And also not only for the tail positioning, but also tip of the tail, sometimes directing, especially when they are approaching people or when they are interacting people or when they are tense, you can easily see from their tails. Or for instance, I'm sure that all of you had this experience when you are cuddling your kids when they are not super happy or when they get bored, you can see that their tails started to move like, hey, I'm already annoyed, please leave me alone.

32:21So the tail is very, very important component of their body language. Therefore, we also want to see from the laterality approach, because laterality approach also can give us more understanding about how their brain works, like a brain working principle. You've already mentioned laterality once or twice. Could you, for our listeners who are not into neuroscience, just really briefly explain what that means? The laterality. As maybe you already know, the brain is divided into two hemispheres as right and left, and they are specialized for different functions.

33:00And we can also see this, when we look at the behavior, we can also see, because the observational manifestation of the brain asymmetries, for instance, handedness in humans. But in humans are a little bit different than the cats, because in humans, 90% of the population use their right hand as dominant hand. But in cats, we don't have this kind of population bias for pole preference, but rather they have individual preferences being either left pole or right pole.

33:32So like us, they also prefer to use one hand, one pole more dominantly. So basically, we can explain laterality like this, but laterality is also the main principle of how brain works, because it's from sensory, motor and cognitive functions. It's like not only for the motor behavior, but we also see from different aspects of the cognition and sensory information, like how the brain works.

34:04So in cats, the distribution of right or left partness is roughly like, is equal proportion. So around 50, 50, or almost like a 54. We also did a meta analysis about it, and they're almost same, like a 54 percentage of like left and right. But it also brings some advantage. So to have because we also showed that when they are lateralized, they are better at problem solving tests.

34:38So there are some cats who I have not preferred. Do all cats have a favorite pole or do some cats use both poles equally? You can see both poles, but also it's like a contextual, depending on the context. But in general, they prefer to use one pole more, especially for the foot reaching tests. But of course, it's like the brain plasticity and also environmental factors can change the asymmetries. In cats, we don't know that much how they change with the different environments.

35:13But we know, for instance, better with dogs, when they are exposed to the acute or chronic stress, you can see that their lateral strength is reducing. And there are more tendency to have ambilaterality rather than being right or left. Sevim, you mentioned that having a preference for pole shows better problem solving abilities.

35:43Do you have any inkling on how the partners and the problem solving abilities are connected? Yeah, 2020, we actually studied this question. We wanted to see the link between the cognitive abilities, like a problem solving ability with the pole-ness. Since we already know in different species like a parrot, chickens, having like a lateralized brain and having like a strong pole preference or behavioral asymmetries brings some advantage in cognition.

36:19And we wanted to check this also with cats because cats are using their poles very manipulatively for both like during the play and during play. And anything they do, they always use their clothes like a poles very manipulatively. And therefore, we had like a two different problem solving tests. They need to open the lid to reach the foot inside. And we tested 41 cats.

36:49And we saw that when they are more lateralized, they have like the individuals who show stronger lateralization were more successful for opening and reaching the foot. So it was the main finding of the results. And we also found that the kids, which one used first their head to interact with the apparatus, testing apparatus were less successful than the ones started manipulation with their poles.

37:22It was very interesting from the evolutionary perspective because we thought nowadays kids doesn't, I mean, they are still, of course, they don't, they are getting the food by their caregivers directly in a bowl and they need to go and sniff and eat it. They don't need to use their poles to reach the food or get the food. Of course, the breed differences are very important, but we thought maybe during the domestication and afterwards,

37:52the ones which they don't use their poles that much and start with the head, they are less successful. So that was the second interesting finding of our study. But we found the strong link between pole preference and problem solving ability. Is it that they are more trained in kind of doing tasks with a certain pole or is it general problem solving abilities? It was a general problem solving.

38:22It was a very good question because we avoid to train them for any task to observe their natural pole preferences. We gave them to the task apparatus and we directly record them until they use 50 pole preferences. And yeah, they didn't receive any training during or before, or they even didn't get any positive reinforcement during the, I mean, from human, they didn't get any positive reinforcement, but of course they got it from the task.

38:54When they opened the lead, they got a positive reinforcement while reaching the food. Interesting. You already published a paper on laterality and sleep behavior, right?

Laterality and Sleep

39:10Yes. And if I remember correctly, there was a finding about the head position. Could you maybe briefly go into what you looked at there and what you found out? Yeah. Yeah. For the cat sleeping behavior, we checked their not head position, but they are like all body position, like how they sleep on. Especially if we had like a different reference points, like the shoulders, because you can,

39:45it's kind of easy, but at the same time, it's very difficult to analyze the videos. But we use the YouTube as a source because as we already said, the cat owners really like to record the videos of their kids and they like to upload and you can publicly can find many videos. And we also go through more than 600 videos in general. Most of them were not useful at all because when you use the keywords for cat sleeping, sometimes it doesn't appear really sleeping positions.

40:18But then we had like a different inclusion and exclusion criteria. And we had the three different raters. And then we had, for instance, 10 seconds sleeping duration. And even if they wake up by their owners or other reasons, if they continue to sleep or stand in the same position, we marked them as a valid point. And we found that all 65 percentage of the cats prefer to sleep on their left side.

40:53Yeah, that was the results. But maybe we can talk more about what does this exactly means? Yes, please. Because I've also skipped the video. I think it was, you assume that it's something about how fast they can react when danger comes, or can you maybe go into that a bit? Yeah, because if you go back to the literality perspective, as I told you, the brain hemisphere is specialized for different things. And we know that the right hemisphere is more specialized for the threat processing and threat detection,

41:24and for the unusual things in general. And what is really special for cats, cats are sleeping 12 to 16 hours per day. And it is a very important cycle of their life. And like, not only cats, but in general, like when we or the cats are sleeping there at the vulnerable situation. And cats also really like to sleep on like elevated places to check the surroundings and the control the environment,

41:55what's going on either for their predators or their prey, because they are also both predator and prey. And then we thought, because the population-level asymmetries in general needs to give you some advantage, why there are this kind of bias. And what we also thought, not during the sleeping, but when they wake up, they really need to see the environment clearly.

42:25And when they use their left visual field, because they are sleeping on the left, and can you imagine them when they open their eyes, they can use directly their left visual field. It means they can react to the environment faster. So then we thought it could be a survival advantage, like it increased their survival ability, rather than just like a random left sleeping bias. I'm trying to visualize my cat sleeping right now.

42:58My cat is loafing. She's on the couch and it's just a loaf. But usually when she's sleeping really deep, she's always curled up on her left shoulder. Usually, mostly. I'm not sure if always, but at least when she's sleeping deep enough to wake up meowing, because she had the dream or something, I guess, that she was dreaming. Then she was always sleeping on her left. Yeah. Because she had that yesterday that she woke up and was just... Good point for us.

43:28Yeah. Yeah, I'm also like imagining my cat sleeping, I also see him laying like this like folded paws and then the head tilted to the left. Yeah. Did you... Well, I don't know if you can answer this, but like sometimes my cat has as Imogen just described her head on her paws, but sometimes also curled underneath her paws. Did you also focus on that or investigate that?

43:59Or did you not do anything on kind of having the, for example, eyes covered? Yeah, it's actually a good question because the sleep position, not only for the directional, but at the beginning of our analysis, we wanted to also do separate analysis for C-shaped sleeping or like a lying down, but lying down on the left, it's more like also the resting. And therefore we had a 10 second inclusion criteria to at least make sure that they are really sleeping.

44:31So since we didn't have enough data set for the different positioning, because cats are also changing so often, we couldn't investigate the differences. But of course it would be very interesting, not only the directional, but how they can react faster while they are sleeping. But even sometimes when they sleep deeply, they are just neutral position and they don't care at all. But also don't forget they are not in that much danger anymore in our houses.

45:01But it's still, if evolutionary conserved, they might still use their right hemisphere more for this kind of situation like instinctively. But it doesn't mean that they really use nowadays because which kind of predator can come from down at home. But the sample size is a good point. That's now that we had like more than 10,000 cats participating in the citizen science project,

45:32we maybe should have asked for more information on the sleeping position. But it was like aiming for like 100 cats per country. If then you divide that up by sex, maybe even age is an influence. And then a sample size would have been too short if we would have evaluated more than just the left and right sleeping position. Do you know if there is a difference between cats who are just in home and outside, so in house and outside?

46:08No, it's also a very good point. We also wanted to mark them as outside sleeping and inside sleeping, but it was not possible from the videos. Because sometimes the environment looks like outside, but it is just balcony or it is inside outside. And as Nadia said, we didn't have enough sample, at least from YouTube videos. But it would be also very nice to check when like when they sleep outside, how they are sleeping. Most probably they are more cautious or more careful.

46:40And when they sleep at home is like a safest place for them. And this is exactly our reasoning for the for the citizen science project that we liked what we could do with the YouTube videos. But we also learned that there is some restriction that we have with the YouTube videos as we don't know anything about the cats. And that's why we then started the citizen science project to get more information about the cats and be able to ask questions like the exact one that you asked.

47:14One question that came to my mind, since you talked about YouTube, do you or how did you handle AI videos? Because I know, especially on Instagram, AI videos of cats are just flooding Instagram. And sometimes like I would consider myself as quite OK in spotting them, but they just get better and better. And I often struggle as well in noticing, OK, is that a real cat or is that an AI cat? How did you handle that issue? A very good question.

47:45And we had like tons of discussions about that, especially now with follow up projects. I feel when we did the sleeping YouTube videos, it wasn't as much of a topic as it is now. And I well, I can summarize our discussion that we had like about follow up projects where we said like we cannot make sure like we cannot for 100% sure say that there are no AI videos.

48:17We have and we I think we even discussed about like tools where you can filter or where the tool will tell you, but it wasn't just as reliable that we would say we can make sure. So we for now follow up projects. We and I think this wasn't the case in the in the published study when there sometimes are the logos of the AI that of course we know and we can exclude. But if there are no logos, we cannot 100% sure say there are no.

48:52So what we said is if we for sure see or have evidence that is AI generated, of course, we will delete it. But if we don't, we have to assume that it's it's a real video, but it's a very good point. Yeah, and also we were very careful with the public. And it's not a publication time, but when it was updated uploaded to the YouTube, because nowadays we are also super careful and we are like, oh, this might be maybe AI.

49:24Then when you look at the uploaded time in 2012, it cannot be right because at the moment the tools are really developed. And if you see them from the 2024, 2025, then you should be more careful. Therefore, we also for the follow up study, we also divided them as a separate files. And we all check for the logos as Nadia mentioned. But we also use Gemini additionally for writing the script to ask also some possibilities because for 95 percentage it with the confidence it can give you like because it can reach the content content of the videos because of the YouTube and Gemini are from comes from the same.

50:10So I hope that it's not a problem to share the names of the programs, but if you already share the YouTube, I think Gemini shouldn't be problem as well. Then you can also, we also try to do as a double check. So we did our best for not having AI generated or when we have any doubts like the image or videos, then we went to the user name and check all the descriptions and the comments. Then if there are any certain evidence, then we excluded them.

50:48Yeah, that is a very good point. And these are all the things that you have to consider in your studies, like where does your data set come from? What does this all mean? And so I feel like it was still like YouTube was still a great tool and it's fantastic to find out things like that. But at the same time, you have to consider where does your video come from? Like what obstacles could there be? And I would assume also if kind of a person posts videos of one cat over five years, then you can be quite sure that that's a real cat.

51:24But if a person posts videos of a thousand cats each day, then it's more likely that there are quite a lot of accounts, not person, but an account that there are a certain percentage of videos included there as well. That's true. That's true. But these were exactly the discussions Sabim and I had. Like, how can you like if you assume that this is an AI video because this person has posted a lot of videos, I felt it's wrong to exclude it because we don't know for sure.

52:00And those were all the discussions. So how do we handle it? And I felt the more that we thought about possibilities, the more not reliable they did get, because if then you say, oh, I feel that this is an AI video. Like, yeah, but then like our studies should always be reproducible. And if we have the feeling or if we think this might be an AI video, this shouldn't be a valid criterion. And therefore we we said we'd rather have.

52:32AI videos in it, but we are open about it and everybody knows this was the reasons how we excluded it and without having this like I have a feeling or this looks like or something like that. So this did bring us like to a lot of challenges and yeah, considering like what what is science, like how are we going to publish? And it's like, yeah, as long as we share what we don't know, it's fine also to don't know everything. Did the citizen science aspect give you more certainty about the realness of your data?

53:11Like, did you encounter videos where you thought, OK, they might have been AI or is the fact that you probably get multiple videos of the same cat reassuring? Well, I think so. So we did not yet. But as I said, we weren't able to really check all the videos with so far. We didn't encounter anything where we thought like this is really AI and here I trust in people that they won't like make up like a name and like demographics of the cat.

53:45And then just create create an AI cat cat. So I think it's more reliable than YouTube. But again, like for sure, like we don't know for sure that all this is like real. And then it's like then we would really need to to bring them to the lab. And that's exactly the discussion about like what is the best approach or how I think the best approach if you really combine everything. I think it's just interesting how science is also changing.

54:15Like we do have more possibilities due to AI also or due to technical advantages than we had like 20, 30 years ago. But also, since everyone has access to certain tools, they can mess it up quite easily if at least get some data points into data set which mess up the whole analysis in the end. Yep. If someone has listened to this episode, is there one, maybe one or two sentence take home message what they should remember about either cat cognition or citizen science or the whole, well, the whole bouquet of topics we talked about?

54:57Well, I hope that a lot of people maybe also not working as scientists listen and for them like join citizen science projects. So it's very interesting. You learn a lot, but it's also very, very helpful for us scientists, as you've seen with our our cats. Yeah. And then with the cats, maybe, yeah, I learned because like this is not my main research with the cats. I learned a lot about cats and new things.

55:29And I hope the people who listened also could learn new things about cats in general, or even like when looking at their cats. Um, notice things that we talk about it. Yeah. Since we started, um, out or since we started as going to science podcast. Um, we always ask our guests in the end of what role cognition plays in their research. Could you maybe, um, give us a short answer on that? Cognition is a very important component because brain asymmetries are one of the, the core features of cognition.

56:06In my research, I would also like to go deeper into cognition, especially social cognition. Therefore, we include different animal species in our research. For example, in my new project, we compare face perception in wolves and dogs to understand the effect of domestication on social cognition. Thank you so much for your time. Thank you so much. Uh, it was really interesting and a real pleasure. Thanks a lot. I had a lot of fun too. This was Kaleidoscience.

56:39We hope that you enjoyed this episode and we would love to have your feedback. You can rate our podcast and give us feedback on our Instagram account. Have a great week and you'll hear from us again in two weeks. This episode was hosted by Imogen Hüsing and Elisa Palmer. Produced by Imogen Hüsing, Clara Kühne, Sophie Kühne, Sönke Lülf and Elisa Palmer. The music is from Jan-Lukas Schröder and the logo is from Annika Richter. The music is from JaniceExpress.