Welcome to the Polyvox Podcast, a podcast where researchers from the NCCR Evolving Language talk about their latest discoveries, their work and their career path! Between linguistics, neurosciences, animal cognition and more topics, you’ll surely find something to your taste!
The episodes, though they can be in English, French or German, will all be transcribed and translated, so you can follow everything! Find all transcripts and translations for the next episodes here!
Célia (Host): Hi and welcome. I’m Célia Lazzarotto, communication officer at the NCCR Evolving Language, and today, I’m welcoming Théophane Piette, researcher at the NCCR Evolving Language, in the lab of Didier Grandjean at the University of Geneva. His speciality is neuroethology.
Théophane (Interviewee) : Hi !
Célia: So, Théophane, what is neuroethology ?
Théophane : Neuroethology, in simpler terms is the neuroscience of animal behaviour. So, we’re trying to explain the behaviour of animals by looking at their brain, trying to understand what their brain is telling us about their behaviour, and how much it influences their behaviours.
Célia: You recently finished your PhD, where you studied animal communication. What’s the link exactly? What interests you in this topic ?
Théophane: So, I got interested in the rhythm of vocalizations and “animal speech”. The idea was that actually this rythm is something very important in the human language. When we look at human brains, when someone is speaking to us, we see that the rhythm of certain brain waves aligns with the rhythm of parts of the speech, like syllables or phonemes. And we asked ourselves if there was such a great importance of rhythm in animals, and if we could link that to mechanisms in their brain.
Célia: And did you start this by chance, what brought you into this field ?
Théophane: Ah, it’s going to be a bit of a long story. I have originally a background in cellular and molecular neurosciences, so I studied the inner mechanisms of cells and neurons a lot. And I ended up in a masters of neurosciences and neurobiology in Grenoble. At the end of my first semester, I did an internship in immunofluorescence, on a project about Alzheimer’s disease. Basically for 3 months, I was locked in a dark room, during the spring and summer, not seeing the light of the sun to look at fluorescing cells, and 80% of the time, it didn’t work. So after 3 months, I told myself, “no I’m gonna become depressed”.
So I took a year off, to figure out what else I wanted to do. I ended up doing a 6-month internship with the professor Adrien Meguerditchian in Marseille, about the development of the behaviour of baby baboons – so Anubis baboons, very small ones which were very cute – and at the same time he also had projects about lateralization of communication in baboons. Baboons have a type of gestual communication where they hit the ground, and he looked at if the baboons were doing it more with their right or left hand. He showed that actually, baboons use their right hand more often, which means the information comes from the left side of the brain. And this is super interesting, because in humans too, things that has to do with language are very centralized on the left. So there’s a sort of evolutionary continuity for this lateralization of communication.
And I found this internship absolutely incredible and said to myself, “ok, I need to do this afterwards”. And I was lucky enough to meet Didier Grandjean, my professor today, who told me, “Come to Geneva, we’re doing great things”. So I came back to university, finished my second year of master’s in Geneva, and then I discovered that the NCCR Evolving Language was getting started. So I contacted a few professors, and that’s how I ended up doing my thesis with Professor Anne-Lise Giraux, who’s now in Paris, on the evolution of rhythm in animal communication.
Célia: During your project, you worked with a lot of animal species I think. Did you study them in real life ? How did you study them ?
Théophane: So yes, actually, the thesis a big project that will be divided into a few smaller projects. And together, they create a bigger project that makes sense. For me, in my thesis, the first project was to evaluate the evolution of rhythm in animal communication. And for this, I studied the vocalizations of around 100 species, from birds – from the small sparrows we have in cities, to ones that are not as well known like hoazins in South America – but also mammals like whales, dolphins, lynxes, deers… and some insects as well as a few fishes (I actually learned during my thesis that fishes can communicate with sounds!). So we studied the evolution of rhythm in all these species. This was our first topic. And afterwards, the second topic was to look at if, as we see in humans during language processing and production, we could see that the rhythm of brain oscillations of animals could match the rhythm of their vocalizations. So see if this mecanism is very huma and to the complex structure of language, or if it was much more common and rather linked to the analysis of sound in general, in the brains of animals. And this, we studied on 2 species, which were dogs and baboons.
Célia: And what are the results of this ? Is there a meaning behind these oscillations ?
Théophane: So, what we showed in our first study was that there was a sort of common rhythm in animal communication, that was conserved in all species, around 3 hertz, so 3 sounds per second. We really noticed that in the majority of species, from the whale to the cricket, and the sparrow, that communicate at this approximate rhythm. It is really conserved in the various species. So this was already incredible.
Celia: And were there variations depending on the size of the animals, or depending on the species, for example, if mammals were closer together or not ?
Théophane: So actually, this was a surprising result : we didn’t find anything that could influence the rhythm directly.What needs to be taken into consideration is that I’m not saying that the environment can’t have an impact on the specific rhythm of a species, or that within a family of species, the weight of an individual compared to another won’t influence its rhythm. What I am saying, is that at a much bigger scale, what we call macro-evolutionary scales, these factors don’t influence the rhythm. We have a conservation of this rhythm, no matter the size, the environment, the social complexity of the individual… All this is conserved in the evolution of the different species.
Célia: Your second project with baboons and dogs, what was the finality of it ?
Théophane: So, it’s still going on a bit. On dogs, it was a study that I joined, that was led by Dr. Eloïse Déaux, in Anne-Lise Giraud’s lab. The idea was to ask how dogs, that are used to being with humans – we know that they understand many words and things we tell them – how do they process language? So I said that the rhythm was important in the human language. Notably, we know that the rhythm of syllables comes in range of rhythm that we call theta range (4-8 syllables per second for most languages of the world). And we see that the cerebral oscillations that we call theta waves between 4-8 Hz, they come and match their rhythm to that of syllables when we listen to someone talk. And what Eloïse’s study on dogs showed, was that dogs will rather use slower waves, which we call delta waves. So this time, it corresponds to the common rhythm we found in animals. So they’re going to process language at this slower rhythm, and not with theta waves like humans do.
Célia: And afterwards, we humans adapt to this rhythm.
Théophane: That’s it ! And this is why when we talk to our dog, we go a bit gaga. We talk slower, with a high-pitched voice, like we do often with babies. It’s a parallel. Probably because we adapt to the rhythm that they use, more than the opposite. We adapt more to them than they adapt to us when we speak, though it’s already incredible that another species can understand words we say, we are adapting a bit to the constraints.
Célia: Okay. And with baboons, have you tried to do the same thing, or did you have another approach?
Théophane: So, with baboons, we asked a bit of a different question: we asked how they analyze their own vocalization. So rather than making them listen only to human speech, we also made them listen to baboon vocalizations, to see if there was a difference in the way their brain were analyzing human vocalizations vs language vs noise with a rhythm that resembled vocalizations.
Célia: And then, what were the results of this ?
Théophane: It’s still ongoing, so very preliminary. But what we seem to see is that contrary to dogs, which will analyse language and their own vocalizations probably in a slow rhythm, the baboon will be able to do both! The vocalizations of baboons are around 3 Hz, like other animals, and humans around 5 Hz. When they hear sounds from baboons, they will track these sounds with their delta cerebral zone (slow). And when they hear human speech, they’re rather going to track it with the theta cerebral waves (faster), just like a human listening to language. So, it’s a bit like there was an evolution, slowly, withing primates that developed a more rapid rhythm, that may have enabled the development of language, that allows to send more information per second than the other animals. But this is very preliminary, I’m not saying that it is the absolute truth.
Célia: So, in its entirety, what do all these small studies assembled tell us, in the end ?
Théophane: This is an interesting question because indeed, the goal of a theses is indeed to create a coherent story with all our small results. So, if we take our results, we have : 1) a conservation of animal communication at a certain rhythm, around 3 sounds per seconds, 2) and we have baboons, that can follow both slow sounds when it’s their own species, and rapid sounds, when it’s human’s, 3) and we can compare this to dogs, which seem to only follow slower sounds, and humans, that are more interested in rapid sounds. Let’s say it like that.
And in fact, this allows us to develop a theory about the evolution of communication and the basis of its analysis by the brain; how closely these are probably linked to sound analysis in general. To understand this, we need to imagine a small animal arriving in the world, in its environment, and unable to hear any sound. And suddenly, it develops this ability, a kind of ear, something, and it can hear its surroundings. So now it faces two challenges. The first challenge is that he must be able to detect sounds as soon as they occur. Because if you detect a sound too late, let’s say it’s a predator approaching, chances are you’ll die a little too quickly. But you also have to be able to identify one sound from another. We are not supposed to react the same way to a river flowing beside us or a friend approaching us as we do to a predator approaching us.
And so, what we think is that in order to do this, animals need to analyze sound at two different frequencies. And in fact, this is based on a physical phenomenon used in sound analysis called Fourier transform. But in fact, what this Fourier transform tells us is that if we use a long analysis window, i.e., at a slow rate, we will be able to differentiate between the different frequencies, but not really know when they occur. Conversely, if we use a fairly short window, i.e., a fast rate, we will be able to detect very well when the sound arrives, but we will not be able to detect what is inside it. So, in fact, we believe that animals need to analyze sound at two speeds, slow and fast, in order to do both. And in fact, we think that communication has adapted to this organization of sound analysis that already existed in the brains of animals, that it is not something that was created specifically for communication, but that it is something much older that comes from constraints that already existed in the basic analysis of sound.
Célia: Super interesting, and all this research, that’s actually quite theoretical, how do you see it helping society, or bettering something for people in their daily lives?
Théophane: So first we must separate the different studies, from the big global results of everything. If we take the study with dogs, there is a simple consequence : talk to your dog slowly if you want it to understand. And then from the results on animal vocalisations, well you can play a fun game that consists in listening to the animal species outside, and suddenly you’ll realize that all are in this common rhythm, quite slow. Personnaly, I can’t get over this information. Anytime I hear it, it’s terrible. Also, we see a lot of system that are developing typically on the automatic recognition of animal vocalizations, extracting the vocalizations of animals from the environment to be able to identify them, for example to count the animals, or detect the presence of certain species. We can imagine that this information could be used for example to better the detection of certain vocalizations. So it seems very theoretical like that, but actually there can be more direct implications.
Célia: It’s also important to know how they work to be able to take care of them, i picture ?
Théophane: It’s always important yes. The more we understand how animals function, the more we can take care of them. And when we go on the topic of evolution, of language and of brain waves in animals and humans, it’s way more theoretical. We are trying to understand how language could evolve to be such a complex communication system. And even if now I don’t see the implications, that doesn’t mean that there won’t be any in the future. For example in the field of auditory aid, for people. Understanding how the language was built and on which basis it functions, it allows us to understand how to give it back to people that don’t have it anymore, for example.
Célia: You finished your PhD a few months ago, so what are you doing now that this big slice of your life is over?
Théophane: It’s going to seem a bit depressive at first, but I promise it ends well. So, it’s a question we are asked very often “you just finished your thesis, what are you going to do now?”. The classic scenario would be to do post-doctoral contracts – for people that don’t know, it’s small research contracts, typically lasting 2-3 years, which we often go to another university to do, it’s often asked for. And then we can apply to become professor… So here is the academic path, the goal is to become a professor somewhere.
On my part, I decided not to pursue this path, not because I don’t like research, I absolutely loved all I did, my PhD… Right now I still have a small research contracts with Didier Grandjean. So really, I love the concept of research, and I love trying to better understand animals, and how their brains work. But I’m facing a contradiction, which is, and that’s when it gets a bit depressive, we are aware of the problem that there is a decline in diversity, with global warming, human activities, and others… So we are losing a lot of species every year. So I came to the conclusion that I had a hard time being interested in understanding animals at the same time that their very existence is threatened. So I decided to focus my time and energy on protecting and defending biodiversity rather than understanding it. There’s no guarantee that one day things won’t get better, and I’ll say to myself, “Great, I can go back to understanding it.” But for now, I’ve decided to concentrate on protecting it. I hope it works.
Célia: Yes, and outside this, you’ll still work a bit at the NCCR.
Théophane: Indeed, I managed to get a part-time lecturer position at the University of Geneva to help master’s students write their theses on affective psychology.
Célia: So, as a result, the auditors will soon find you again as a host for this podcast, in the next episodes.
Théophane: Indeed, i’ll be on the other side of the mic !
Célia: So there you have it. Thank you, Théophane, for telling us about your research. We’ll see you soon for new episodes and to discover the research of other scientists and researchers from the NCCR Evolving Language.
Théophane: Good bye and see you soon !
Célia (Host): Hello, I’m Célia Lazzarotto, Communication Officer of the NCCR Evolving Language, and I’d like to welcome researcher Giuachin Kreiliger to today’s Polyvox podcast. Hi, Giuachin!
Giuachin (Interviewee): Hi Célia, thanks for inviting me.
Célia: You’re now a PhD student working with Sabine Stoll at the University of Zurich. What is your research topic?
Giuachin: In our research group, we are very interested in how children learn language. Children learn language effortlessly and at an extremely early age. Some children can’t even walk yet, and they are already speaking – or at least beginning to speak – which is truly amazing. It also has a lot to do with the evolution of language, because every language must be learnable. No matter how complex or difficult it is, if a young child cannot learn a language, then the language will not survive. That’s why Sabine has her research group, with which she studies how children learn such languages. We’re particularly interested in the child’s environment and the influence that environment has. There is this, this so-called baby talk (or “child directed speech” that parents use when speaking to their babies. They don’t speak the way we do in this podcast, but rather with exaggerated intonation and long vowels. We ask ourselves: How important is this baby talk for language learning? My research focuses on the repetitions in baby talk – for example, when we say to an infant: “Look at the tiger! Yes, the tiger!”
Célia: So, a lot of repetition.
Giuachin: Yes, exactly.
Célia: What motivated you to do research on this topic?
Giuachin: I’m actually a statistician, and what’s kind of funny is that you could say babies are a bit like statisticians, too. They learn language without any prior knowledge. They don’t have a grammar book to consult, and the only thing they can do is listen and pay attention. There’s a really nice experiment by Jenny Safran in which she simply played an extremely simple speech sequence for the children, e.g., “Baduki buda buki di baduki.” After the children heard it, they started breaking this sequence down into words on their own. The answer to how they did this lies in statistics. They simply tried out which combinations sounded good, and that became their word. I find this very fascinating because they don’t have a statistics program or make a table somewhere while listening. They did this on their own, using their brains.
Célia: How do you go about answering your research questions?
Giuachin: That’s a very good question. It is difficult to know, for example, how important a repetition is for a child. Of course, you could conduct an experiment to see if a child learns a word while reducing the number of repetitions in the experiment. I am researching such variations in repetition, but this is obviously not the same as in a real-world setting or the same as for a child. A child does a lot of things and hears a lot of language. I first built a statistical model for my research question and am now simply collecting a lot of data. We’ve compiled a large dataset of conversations between children and adults, totaling about 400,000 words. I will then run this entire dataset through my program and see what the results show.
Célia: Where exactly does this data come from?
Giuachin: The data is based on video footage and was transcribed by a large number of patient students. As far as I know, the footage was filmed in Manchester, England. For over a year, they visited parents with their children and filmed them. Then, students were paid to transcribe everything that was said from hundreds of hours of video footage.
Célia: So, is the dataset written in English, or is it also available in other languages?
Giuachin: Yes, it’s also available in other languages. We have a few very rare languages in our dataset. Perhaps the best known is the Xintang language. It’s quite well known because the verb conjugation in Xintang sounds impossible for us to learn. This language is so complicated. For example, there are up to 3,000 different verb endings. In German, there are about 30. Try to imagine what it’s like when there are 3,000 endings that you have to learn.
Célia: I heard that, in addition to humans, you also want to work with other animal species, right?
Giuachin: Yes, that’s correct. And it’s actually very important to us because humans are the only ones who possess both this specific baby talk and a highly developed language. This could mean that these two aspects are connected. If other animals also had baby talk, even though they lack our linguistic diversity and development, then there is strong evidence to suggest that such sound patterns have a different origin or purpose than human language. Precisely because our language is so highly developed and functional, it would be remarkable if similar patterns emerged in animals—and it would suggest that baby talk is not simply a byproduct of language, but something distinct in its own. So, in our research group, we are convinced that baby talk is very important for children. There are many studies here that show the following: the more a child hears, and the more they hear this baby talk, the better they learn to speak and the faster they develop. We are convinced that baby talk serves an important function, even if we don’t yet know exactly what it is. If we were to find another animal species that uses baby talk, with lots of repetitions, this could help us better understand what baby talk was originally intended for.
Célia: What animal species do you work with?
Giuachin: We’d like to work with marmosets, and are currently studying a few marmoset babies at the University of Zurich in Judith Burkhardt’s group. PhD student Elena Belli from Judith Burkhardt’s group is filming them, and we’re eager to see what we find.
Célia: Are there so far no other animal species known to have a baby language?
Giuachin: Yes, there are other animal species that also have a kind of baby talk. They use a higher pitch when talking to their young, just like we do. If I recall correctly, there are references in an article about gorillas describing how adult gorillas repeat gestures multiple times if the gorilla infant doesn’t understand them. But there’s still very little research on this. Regarding vocalizations, a research group from the NCCR showed in an article last year that great apes (chimpanzees, orangutans, and bonobos) rarely communicate verbally with their young. Humans, on the other hand, do this constantly. We see this difference not only between European cultures and great apes. In the indigenous Shipibo-Konibo community, which Johanna Schick from the NCCR studied, adults also talk much more to their children.
Célia: So, do you already have results from your study, or is it too early to say anything?
Giuachin: I have some preliminary results, but of course we still need to discuss them. Even before my study, we knew that we use a lot of repetition in baby talk. Now we’ve found that while we do repeat things more often, we do so over a shorter period of time than in conversations with adults. We naturally asked ourselves why that is. We suspect that in a conversation between adults, there’s often a topic where a word is repeatedly brought up. With a child, there usually isn’t a specific topic, for example a movie, that you could delve into for half an hour.
Célia: What are the next phases of your study?
Giuachin: Of course, we now want to observe what these little marmosets do. But the young animals are still growing up, and we have to be patient until we can see how they react to repetition. With human children, we see that at some point they start to join in on a topic. They begin to say a word that’s been repeated over and over. If the mother keeps saying “book,” for example, the child will eventually respond with the word “book.” That doesn’t happen at first; the child does something else.
Célia: I’d like to bring up another topic. You’ve had a unique career so far, marked by many changes and diverse experiences. What’s the reason for that, and does it help you in your work as a doctoral student at the NCCR Evolving Language?
Giuachin: I started two degrees first political science and chemistry, then I went on to study and complete degrees in biology and data science. Through this, I’ve had a variety of experiences, and I think it’s helpful to be curious and open to other fields of research. For me, it’s obviously great that this now allows me to conduct biological studies. But of course, it’s also very good and important to be an expert in a specific field. For me, both diversity and expertise have their advantages. It’s also great to be an expert and know that something works.
Célia: Don’t you feel like an expert in your field of study?
Giuachin: I feel comfortable with programming, and that’s very important. But I’m learning an enormous amount right now, also because I have to learn. I’ve learned a lot in linguistics and now also in behavioral biology. But the whole thing is also very demanding.
Célia: The interdisciplinary approach is, after all, a key focus of the NCCR Evolving Language. Your career really reflects this approach, and in addition to your studies, you also have experience in radio and podcasting, right?
Giuachin: I also worked in radio for two years, but only behind the scenes and not on the microphone, like I am now. I’ve listened to a lot of radio and really enjoy it. I’m a big fan. Ironically, I’m happy that in my new job I now get to do a little bit of radio myself.
Célia: I’m excited that you’ll be hosting the next German episodes and also looking forward to meeting you again with other guests. Thank you.
Giuachin: Thank you.
Célia (Host): Hello everyone, welcome to the NCCR Evolving Language Polyvox Podcast. I’m here today with PhD student, Jovana Maksic. She’ll talk about her PhD, which she started pretty recently. How are you, Jovana?
Jovana (Guest): Hi, I’m good. Thanks for having me.
Célia: You’re doing a PhD. What’s the topic of your PhD?
Jovana: I just started my second year, but the topic of my PhD is looking at the neural signatures of technological complexity in stone toolmaking. More broadly, what that means is I’m trying to understand what kind of neurocognitive pressures the activities of producing stone tools might have placed on the brains of our hominin ancestors. Of course, we know that hominin minds, just minds in general, do not fossilize. And therefore, what I do, on a sort of day-to-day is I study modern day stone toolmakers. These people are also called flintknappers. The methodology that I use for the brain imaging, it’s called functional near-infrared spectroscopy. It’s easier to call it fNIRS. This device measures cortical activity by tracking blood oxygenation levels. So in principle, it works very similar to an MRI. But of course, it’s quite different from an MRI because it allows you to move around. Rather than laying still in a scanner, with FNIRs, you can do all sorts of naturalistic tasks like dancing, sports.
Célia: And toolmaking.
Jovana: And tool making, of course! Besides looking at the brain activity while they produce these tools, I’m also interested in the behavioral structure of the action of producing the stone tools. And what I do is look at the video of where they actually produce these tools and try to understand micro-actions involved.
Célia: And so the key question is, how did our ancestors make those tools and how do we do it now?
Jovana: We know from the archaeological record that our ancestors were pretty much consistently making different kinds of stone tools throughout the Paleolithic. And actually the lithic record is one of the best-preserved continuous records of hominin behavior.
Célia: When you say lithic, what’s the…?
Jovana: So the Paleolithic refers to lithics. So it’s really just stones. Yeah, exactly. And this gives us a very broad evolutionary timeline.
So we know that the earliest stone tools date around 3.3 million years ago. And this was called the Lomekwian technology. And then we also have stone tools ranging up to 10,000 years ago. And this is more like upper Paleolithic technologies. Over this very broad time span of evolution, we know that several different hominin species were making these stone tools.
And just to say a little bit more about the nature of the stone tools, some of the earliest stone tools, they’re called the Oldowan technologies, they date around 2.6 million years ago. And if you imagine how these tools look like, what they were used for, they are relatively simple, so that means that you just take a flintstone and you remove a couple of flakes. And if you have a nice edge that is sharp enough, then you can use it for things like cutting meat, processing plants, or even breaking bone to access the bone marrow, which was of course very important for our ancestors. And later you see a very interesting change happening at around 1.7 million years ago, which is the advent of something called the Acheulean tradition. And here you start seeing more symmetrical tools and standardized forms. So things like hand axes, they are quite complex compared to just relatively simple Oldowan tools.
And this suggests not only that there were changes in the cognitive capacities of our ancestors, but also this suggests that there were some important changes in social and cultural transmission. There were even some theories out there that some of these tools were so large, like the hand axes, that they might have not even been so practical for use, like butchering and killing, but rather they were like the artistic expression of the toolmaker. These stone tools were not just about sustenance, or maybe they were at the beginning, but clearly they become much more over the span of the Paleolithic, and they become important cultural signatures as well.
In the past, people in this field, which is sort of affectionately called neuroarchaeology, have been very interested in the transition between the Oldowan and the Acheulean, which I’ve mentioned. And the reason is that purely by looking at the brain size of hominins during this period, we know that something interesting begins happening with brains at the advent of the early Acheulean. So brains begin expanding exponentially in size. And there’s probably many reasons to this, but why it’s interesting to look at stone tool making is trying to figure out, okay, maybe there was something about making hand axes that might have placed additional cognitive pressures on our minds and therefore the brain.
Célia: Now more about the actual making of the tool, like in the archaeological records you have the finalized tool or maybe some intermediate forms, but then how do you study how exactly people make it?
Jovana: I really wanted to get to this because it’s pretty much the core of my PhD. The field of cognitive and experimental archaeology pretty much deals with this approach, where rather than only looking at the finished product from the archaeological record, you actually try to mimic the behaviors that might have been involved in creating these tools. If you try to imagine how a tool or anything else in the Paleolithic was made, you really need to begin by imagining every step that went into that process. So in the case of stone tools, we need to imagine a hominin firstly going out to find the right kind of stone and the right kind of material to make that tool and then working on the tool and then maybe using it a little bit and then going back working again on it. This is a sort of like process-oriented thinking. In contemporary experimental and cognitive archaeology, people try to really mimic these processes in the lab and then try to look at the behaviors that you get by mimicking these things. In my case, I record very detailed videos of these flintknappers who make the tools – different kinds of tools that I instruct them to do. And then I really look at how this production takes place, what kinds of motor behaviors or changes in hand grip are happening…
Célia: And then within this experiment, where does the NIRS come into place?
Jovana: Well, we actually want to have the participant wear the cap while they are reproducing the tools from specific periods that we are interested in. And what we know so far is that the Oldowan, which if you remember, was this very relatively simple tool that mostly requires you to just remove a couple of flakes and get a sharp edge and the Acheulean, which is this nice symmetrical hand axe, the Oldowan seems to be based in mostly sensory motor and visual areas. So that reflects kind of immediate processing: working with the stone, rotating it, understanding its properties and kind of coordinating your hand accordingly. And while in the Acheulean, these scientists have found an additional activation mostly in the prefrontal regions. And this has been linked to different things, one of them being an increase in working memory, for example. So there seems to be something interesting that we can get at with fNIRS. And now what I want to do is take a closer look at the individual production steps of these technologies rather than just using categories like Oldowan or Acheulian.
Célia: So all these processes, what do they teach us about human evolution?
Jovana: I think we can probably dissect it into several different segments. So for example, if we are trying to understand cognition, this gives us a very nice continuous record of, not just how hominins were interacting with the tools and their environment, but also how
the cognition and brains were changing at the same time. So for example, we can look at how these trends that we see in the lithic record compare to trends in fossil endocasts – so basically just looking at the size and the properties of brains in parallel.
And then on the other hand, we can also try to understand how the hand morphology might have developed in parallel with toolmaking. There were some changes in hand dexterity throughout our evolution. There was a very famous case of bonobo called Kanzi, which I think the NCCR is more than familiar with. And over the last several decades, anthropologists actually wanted to train Kanzi to make stone tools. What turned out to be the case is that Kanzi actually did get relatively okay at removing flakes and he understood the concept of “I need to get a sharp flake because that flake will let me cut – let’s say- a rope that connects to a box and in the box I get some food”. But what Kanzi was not able to do is really get this level of dexterity that is necessary to shape the tool in a finer way. So in a sense, this was something that seems to be very important in our evolution, this continued hand dexterity. And of course, this also has implications for our brains. So we know that throughout evolution, some additional brain areas appeared that seemed to be involved in this very fine control of fingers and grip and things like that. So that’s also another thing we can learn.
And then of course, the really big question, that we want to get to here is language, which is the whole reason why this project is in the NCCR. It’s a very interesting link and there’s several ways to look at it. One of the most prominent sort of hypotheses is called the technological hypothesis of language, which claims that it was the toolmaking context that actually prompted the development of language. Of course, there’s different variations in how this hypothesis is manifested. So some people emphasize the cognitive requirements and demands of toolmaking and that essentially it was very important to already have skills like sequential behavior, chunking actions together, structuring a toolmaking sequence into smaller units, which as we know has many parallels to how a linguistic processing works. Also, in tool making you also get these nested steps and hierarchies,
which sort of mimics how things like tree structures and syntactic processing works. So, that line of reason really focuses on what is the cognitive overlap of toolmaking and language. And maybe some of these skills were already there in place, especially in the brain. And then language and broader language might have piggybacked on these existing neural circuits that were there. And then the other flavor of the technological hypothesis actually focuses on technological pedagogy. It really focuses on the more interactional side of toolmaking because, as we talked about, at some point it becomes clear that these kinds of stone tools like hand axe or especially later technologies like Levallois and these more complicated Upper Paleolithic tools, they couldn’t be innovated by a single individual. They required some kind of teaching, some kind of transmission, social and cultural. So, this whole idea of technological
pedagogy claims that at some point we went from having a gestural language to speech because the necessity of transmitting increasingly complex stone tool technologies actually placed pressures on the communicative system.
Célia: So now you’re a year into your PhD project. How far have you come into the getting results or have you started the experiments?
Jovana: Now roughly a year in, I have mostly worked on planning my experimental design. I have to say finding the right neuroimaging approach for this kind of experiment has been probably the biggest challenge. Of course, it’s not magic. Just because we have a scanner on someone’s head while they make stone tools doesn’t mean that we can just extract everything that’s happening. So we really need to think about: How do we time these experiments? What are we looking to find? What are some constraints of resolution that this signal can actually provide?
Also, I have been working on collecting and analyzing a lot of videos of flintknapping. I even visited some expert flintknappers in their home, which was a very interesting experience. In the process, I also began learning how to make some very basic stone tools, which I have to say, it’s very difficult. But once you get a hang of just the movement of removing a flake, it becomes quite addictive. So I can definitely understand our ancestors. I now have collected a lot of videos and I started coding these videos myself. What I have been doing is basically just trying to look at every second that happens of the production process. And I got some preliminary results. They’re very preliminary, but there’s still more work to be done.
And at the same time, I’ve been working on a project with the UZH data science team with Lars Malstrom. who is really fantastic, he’s a machine learning expert and we’ve been working on developing a machine decoder that actually can automatically detect these archaeological steps as we define them from the videos.
Célia: And so what are your next steps now?
Jovana: Actually, I just started my first pilot experiments. In the lab, I wanted to first just see if we do these very intense movements, how does that impact the brain signal. Because you can imagine that,
yeah, there might be a lot of vigorous movement when you remove a flake. So we need to make sure that what we are measuring is really the brain signal and not just motion artifact.
And then another thing that I’m actually going to do next week is I’m visiting an international flintknapping symposium, which is very exciting. It’s going to take place in Dordogne in France at a very important historical site, actually. So I’m going there not just for fun and to see some cool cave paintings, but also to record a lot more videos, hopefully of more complicated Upper Paleolithic technologies. And in addition, I want to do my subject recruitment there.
Célia: Yeah, I hope you’ll find people that are interested in your project, I’m sure. And then otherwise you can do it yourself now that you’re a flintknapper, a baby flint knapper.
Jovana: I think I can only recreate the lower Paleolithic somewhat, but beyond that, I’m not…
Célia: In a non-human style.
Jovana: I can do it like Kanzi pretty much. Just like bang the rock together, get some flakes.
Célia: Thank you so much for being here, Jovana. It was super nice to hear from your research. We’re super excited to hear more in the future.
Jovana: Thank you for having me. This was very, very nice and I really enjoyed chatting with you. And yeah, hopefully chat more in a few years when there’s much more to show. And yeah, thanks again. Bye.