Instant Genius - Inside the mind of a bee, with Prof Lars Chittka

Episode Date: July 31, 2022

How smart can an insect be? Lars Chittka, a professor of sensory and behavioural ecology and Queen Mary, University of London unpacks the incredible depth of intelligence exquisitely packed into the mind of a bee. Once you’ve mastered the basics with Instant Genius, dive deeper with Instant Genius Extra, where you’ll find longer, richer discussions about the most exciting ideas in the world of science and technology. Only available on Apple Podcasts. Hosted on Acast. See acast.com/privacy for more information. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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So you can experience exceptional sound at home. Music just as the artist intended. Visit name audio.com to learn more. From BBC science focus, this is instant genius, a bite-sized masterclass in podcast four. I'm Daniel Bennett, the magazine's editor, and today we're going to reveal what goes on inside the mind. And believe me, this episode will surprise you. I'm joined by Lars Chitka, a professor of sensory and behavioral ecology at Queen Mary University of London. Lars's new book, which is on sale now, is called The Mind of the Bee.

And it unpacks the huge array of intelligence exquisitely packed into the brain of an insect. To start off, here's Lars explaining what exactly he's trying to learn. about the mind of the bee. So I started out as a PhD student 30 years ago or so, aware that bees are aware of simple associative learning, that they can learn the colors of flowers, the scents, patterns of flowers as well, as well as, of course, the location of their hive.

They have to be good at spatial orientation to be able to relocate, their hives after extensive excursions that might take them 10 kilometers away from their native hive, and then they have to reliably find their way back. All of this was known at the time, but if you would have asked anyone at the time whether there is a higher level of intelligence or let alone any form of sentience or consciousness, people would have laughed, and that would have included me, I think, at the time. And we did one study already in the early 90s, which changed my mind a little bit and that of other people. That is, we asked if bees can count.

So we trained them along a series of pyramid-shaped landmarks, where they had to count off three and then land. Of course, bees can also remember distances. And so we then produced contradictions between the memorized number of landmarks, and the memorized distance, so that we put more landmarks over the same distance or fewer. And if we increased the numbers of landmarks over the same distance, the bees would land at an earlier distance, so guided by the number three.

And if we reduced the number of landmarks, they'd overshoot the learned distance and fly again closer to the number of three. And that surprised us, and I think many, many others, in the field and that there seemed to be a little more than basic associative learning. Then over the years, we and other labs ran all kinds of more advanced intelligence tests by the bees. So, for example, a colleague Martin Juerfah did an experiment on concept learning where the bees had to learn that all symmetrical objects are.

associated with rewards, no matter what the actual shape of them was. And another group of beans learned as asymmetrical objects. And what you could then do after the training, you give them completely novel objects that they've never seen before, either symmetrical ones or asymmetrical ones. And the bees would correctly classify these wholly new objects based on a class, a concept of symmetry or asymmetry correctly. We also then later did experiments on object manipulation, where, for example, bees would have to pull a string

to pull out an artificial flower from underneath a glass surface to get access to a reward. And that was historically a kind of animal intelligence test that was used for primates or corvette birds, And I remember initially when I run this idea by colleagues who worked with such animals, they basically laughed and said this ridiculous. But we weren't discouraged, and indeed bees were able to learn this task very well. And we could then, after training just a few individuals, or one in some cases, see the technique spread through a whole population of bees in the laboratory, very much like a social media, a meme that would ultimately spread to all individuals of a colony.

So they were learning this by copying each other. And that a decade ago, I think people would have ridiculed even the idea that an insect might be capable of such performances. And then after decades of this research on intelligence, there emerged the question, well, if they sort of smart, what if maybe they're also sentient? And I can tell you one experiment that nudged my mind in that direction. So about 15 years ago, we did an experiment to explore whether bees could learn about predation threat. And one scenario where bees have to watch out is to our so-called crab spiders that lurk on flowers for unsuspecting pollinators. These are spiders, they're so-called sit and wait predators. So they sit in one spot on a flower and they are able to take on the

color of the flower on which they sit. So very much like a chameleon, they can turn themselves yellow or white, depending on whether the flowers they sit on are yellow or white. And we wanted to take this scenario into the laboratory and find out if bees can learn to avoid flowers that harbor this predation threat. And so, we want to take this. And so, we want to take this scenario into the laboratory and find out if bees can learn to avoid, And so we built what we called robotic crab spiders. These were essentially solenoid-driven arms of a spider with sponge pads. So they were combined with a life-sized model of a spider, and these sponge pads could briefly capture a bee without injuring it at all, so they were very soft, and then releasing it again. And we wanted to know can bees learn to avoid the flowers on which.

such predation threat is existent. And it turned out that they can do that very well. The bees can learn to avoid individual flowers as well as artificial flower species with predation threat. But there was something else that was really remarkable. And that was that the bees' whole demeanor changed. They became overall much more hesitant to land on flowers. They would inspect everything.

every flower extensively and scan it before landing, even days after such a simulated predation attack. The most remarkable phenomenon were what were so-called false alarms. That is, the bees scanned a flower and then rejected it even if it was perfectly safe. And this sort of behaved essentially as if they were seeing ghosts, inspects. a flower that had no crab spider and then flew away rejecting it, apparently thinking, ooh, this doesn't look quite right. So this is a kind of phenomenon that's almost reminiscent of post-traumatic stress disorder where you're actually responding to threats that are not actually in existence just because your mind is so highly sensitized to the possibility that

there might be something scary. It feels like an imaginative act, like that. Exactly. They're imagining a perceived threat. Indeed. Yeah. So this was a chance discovery. We hadn't set out investigating this phenomenon of false alarms, but it was a clearly recognizable phenomenon that we could statistically quantify.

And that looked to us at least like something, like a negative emotion-like state. And we then, in later years, we and other labs, again, explored such states in a more former manner using environmental paradigms that have been developed, for example, for farm animals to find out if sheep or goats are kept in an environment that is conducive to keeping them psychologically happy or whether the converse might be the case. And the approach is basically one that

is related to the proverbial, is your glass half full or half empty question? That is, you present, in this case the human subject, with an ambiguous stimulus, a glass that's filled with 50% of a liquid. And if they're optimistic, then they will judge that as being a more positive state of the world. The glass is basically full. Or if you're a pessimist, you might judge that as, it's already run down, class. to empty, even though it's the same stimulus. And this experimental approach is used in various adaptations to the animal world.

And the way we did that was that we trained bees that, for example, one color is associated with sugar reward. So that's how, by the way, we train our bees. Typically, if they get something right, they always get a droplet of sugar water. And that's their natural reward. That's what they find in flowers, and that's how they learn. rewarding flowers and learn their colors and so on. So in this case, we trained bees that one color was rewarding.

Let's say blue was rewarding and another green was not. And so this is what the bees knew. Of course, we always do another, train another group of bees with the reverse paradigm so we can then compare how they respond. But let's keep it simple. So let's say one group of bees learned that blue is rewarding, green is not. There was only ever one color present, and the bees that saw blue during a test would fly right away to that target. The ones that saw only green would wait quite a long while before trying it because they knew there's never anything there.

So they would hesitate to approach that color. And now comes our ambiguous stimulus, our 50% filled glass. That's a new one. Let's say it's turquoise in the middle between blue and green. And we then ask, well, how do you judge that? Does that look to you like it's more likely rewarding or not, as the case may be? And it turns out that the response to such ambiguous stimuli depends to what has happened to the B before she enters the setup. If we give a B a little surprise reward that she doesn't expect before she's even coming to our experiment,

a little tiny droplet of sugar water, then she will more likely accept such an ambiguous stimulus. as rewarding than if she hasn't been surprised with a little extra reward. And another team by Geraldine Wright at Oxford University did the inverse of that experiments, that is that they subjected the bees before they were being tested to a surprise predator kind of attack. They briefly vibrated the bee as if it was captured. And in that case, the bees respond in the opposite way to the ambiguous stimulus. So by the same criteria as we're diagnosing or other people are diagnosing positive or negative emotion-like states or an optimism or pessimism-like response in domestic mammals,

by the same criteria the bees also qualify. Now, this is just a psychological test, and of course what you want to do is complement such tests with physiological ones about hormone levels and neurophysiological. states to make sure that you have a number of robust approaches that each complement each other to make sure that you're not straying into simple anthropomorphism. But using a battery of such tests, we can be at least reasonably confident that an animal has indeed emotional-like states. So that is how you would interpret that, you know, with the caveat of further testing that the bees appear to display something akin to what we would call mood.

You know, you're in a positive, but optimistic mood because you found a penny on the floor, and so you're more likely to take a risk and, you know, or do something with the expectation of a good outcome compared to someone who's maybe tripped over, picking up a penny. They might then be in a bad mood and they might not be so likely to take a risk. And so it's akin to our moods, perhaps. Is that overstepping it? Or is that a kind of interpretation? No, that is exactly the kind of interpretation that we use.

And of course, I would have to add a few words of caution. Let's say a roboticist might say, well, I can program a machine, a robot, a computer to respond in exactly the same kind of way. They would be right. It's correct that you can get a robot to display such responses, as well as to program it to solve many of the tasks that I've just described as intelligence tasks. So you can build a robot that would be able to count or pull strings for reward and so on. So formally, all of these things could be done by a machine.

but that's because you've programmed your machine to do exactly these things. So today we could build a robot that could pretty much deliver every one of the performances that I've just described to you, but the robot would probably fail at what bees will be discovered to do next year. And that's the key difference. So you can make a machine that mimics any kind of animal. more behavior. That's correct.

And that machine might demonstrably not have a mind or sentience or emotions and so on. But number one, nature does not have room for such profligacy to just pretend as if it delivered certain kinds of psychological phenomena that just look like an animal is enjoying something or suffering from something just to fool us scientists. And number two, the flexibility that comes with a real animal mind, we would so far fail to see in any kind of machine. So if you had built, let's say, a robot that could do everything, a bee was known to be doing 10 years ago,

that machine would not have been able to pull strings for food or to copy another machine's technique to get access to rewards and so on. So machines work because you've made them work to do certain things, but to get the kind of flexibility that we're already seeing in our bees, I'm not aware that this is yet possible to have a machine that displays that sort of level of flexible intelligence. that adaptability and ability to generalise and learn new things to that extent. And so I suppose it's important to note that as you do in the book,

this is all, of course, driven by their lifestyle. So the way that they eat, the way they live together. Could you just explain how the sort of demands of their life have sort of driven the need for this kind of brain? Of course. So a bee's natural lifestyle means that first of all, it needs to be a super navigator. It needs to be very good at memorizing where its native home is. It's hive if you're a social bee. Because if you fail, if you fly out for an excursion that might take you two hours to visit flowers and collect nectar and pollen,

you fail relocating your hive, all your efforts are wasted for the colony, and you yourself might also die. There are some species of bees that would be able to survive on their own honeybees cannot. So it's game over, basically, if your memory for spatial locations isn't very precise. And that applies even more to the many species of bees that are solitary. So many of us will be familiar with the honeybee and bumble bees. These are social species, but fewer people are aware that there are thousands of species of bees that are solitary. These are all single mothers. It's invariably the female bees that do all the work. And these solitary bees construct a nest on their own. They provision their larvae and seal the nest and so on once the provisioning is finished.

and if these bees fail to find their way home, it's a disaster. They lose all their offspring and they will starve to death. So even in these solitary, these less familiar species of bees that live by themselves, the need for having a highly precise spatial memory is great. And that distinguishes bees from most other insects which might more aimlessly drift across the landscape because they don't have a home. Another aspect of bees' lifestyle is, of course, that they must be careful shoppers in the flower supermarket. So in any bees' home range, there might be two dozen or more different plant species that are in flower,

and all of these differ in their accessibility. Some flowers are difficult to manipulate, such as snapdragons, others are easier to access. they differ in the nectar and pollen offerings, in the concentration of nectar as well as the amount, and of course in their advertisement. So the colors of flowers, their patterns, the scents are what I call advertisement in analogy to how you recognize a product in the supermarket.

And so bees have to be very good economists when it comes to comparing the e-enomeness. efforts they have to get into, invest into accessing the rewards in relation to the rewards that they're actually getting. And for that, they have to be able to learn the advertisements of the flowers, the color signals, as well as their position in space, to be efficient foragers and to out-compete other bees and other bee colonies that might also operate in the same area. So it's a biological market in which bees have to be good learners and good navigators. That's their natural lifestyle, and that explains why they're good at learning colors and

sense and so on. It does not necessarily explain why they're also good at solving tasks that no bee in its evolutionary history would ever have encountered. So we deliberately choose some tasks which are not natural for bees just because we want to put them on the spot and ask, well, how far can we actually push their micro brains in terms of cognitive performance? And for that, we have to use tasks that are outside the natural range of things that they would have to solve. And this includes the kinds of counting tasks or string pulling tasks that I mentioned earlier. we've also used a task that where bees have to roll a little ball over a horizontal surface to a goal area

and get access to a reward in that kind of way. Again, that's not in that form a task a bee has ever solved before, so they're not naturally evolved to learn that kind of task, as they are with flower colors, for example. But, of course, these kinds of intelligence, and problem-solving skills come handy for some tasks that are less common. So, for example, after we published this string-pulling study, a member of the public sent to me a video link to a little YouTube video

that someone had posted of a solitary bee that nested, some of these solitary bees nest in natural holes in rocks, for example, and this bee had built its nest in a brick, with a hole in it. And someone had pushed a small nail into the entrance of that nest. I've seen the video, yes. And the remarkable thing was that this little bee, rather than robotically, as you might expect,

trying to push its way past the nail into the hole, actually in a sense must have understood that the only way to remove this obstacle is to pull it. And so she was a little clumsy. She tried various ways by, for example, standing on the nail and wearing her little wings backwards. But in the end, she managed to get the nail out of the way. And that, in a sense, is similar to our string pulling task in that you had to pull on an object in order to get to a reward, which in our case was shrugger. And in the solitary bees case, the access to her nest and presumably her off-stop.

spring. Now this would have been a new task for that be, but one that with the right level of behavioral flexibility and a form of understanding of the nature of the task is solvable. So it's a kind of general intelligence and flexibility that allows you to solve such tasks. I'd mentioned the ball rolling task, and again, after we published that, someone emailed me seeing that they had seen a bumblebee. Bumblebees are often ground nests. They nest in abandoned mouse burrows. But someone had seen a bumblebee worker removing a slug

that had crawled straight accidentally, perhaps, into the nest entrance, that the worker bumblebee had rolled the ball, had basically rolled the snail into the slug into a little ball and rolled it exactly in the same manner as they were rolling ball. backwards as an ORIS study with the ballroom. And that is the kind of the adaptive significance,

the beauty of having a kind of more general intelligence beyond just being prepared to learn colors and so on to solve unexpected tasks, to solve tasks that are not common in your environment because you can deploy that sort of general intelligence for almost an unlimited number of potential challenges. So just to help people make sense of this, because these are all remarkable feats for something.

So I suppose insignificant in a way, not in use, but in just sheer size. Where does this put bees in the kind of, I mean, we like to rank things, but what is it comparable to in terms of intelligence? We're talking about the kind of tests that usually we put towards apes. Is that right? Indeed, it is.

I mean, I would hesitate to make direct comparisons of this nature. I mean, they're fun, but I'm not sure about the extent to which they're meaningful. I mean, there are some remarkable performances of bees that, to my knowledge, have not been solved by other animals at all. So a team of friends of mine, Adrian Dyer and colleagues recently tested bees to recognize odd or even numbers, irrespective of the actual number of dots in a display, the bees were able to apparently class. the targets as to whether they had two, four, six or eight, even numbers or in another class of objects whether they had odd numbers. And to my knowledge, other animals have not solved that kind of task. There are undoubtedly many things that primates can do that, at least from my

vantage point today, I doubt whether bees would be competent at that. And that's, for example, understanding other minds, metacognition, knowing what other individuals know. And so this kind of mental perspective taking on your own knowledge, assessing how sure I am of certain knowledge, or knowing what other animals in your environment know, there might be glimpses of that in bees, but the evidence still would need collecting. and it might very well be that bees fail some of these tasks. So because different animals are differently good at different things, and that, of course, is in part at least explained by their social environments,

by the kinds of tasks, at least to some extent that they naturally solve, I would hesitate to put animals on a rank order like that. There are also other insects that deliver some intelligent behaviors that bees lack. So there are certain species of wasps which display individual recognition. So these are wasps that live in relatively small colonies, where each individual differs in their facial markings. So they have highly individually variable faces, and it turns out that in these species of polysthes wasps,

every individual recognizes the other individuals in their nest. And not only that they actually store bits of information about the other individuals, so they know each other's fighting abilities, they live in a kind of linear hierarchy by which there is one alpha female at the top of the hierarchy and she gets to lay all the eggs. But that position has to be determined

by winning lots of fights with other individuals. And these fights are costly. You might lose a leg or sometimes individuals get killed, but that happens more rarely. But it's best not to repeat a fight against an individual that you already know is superior. And so they store information about each other. there's fighting ability. They can even by watching from a distance, other individuals fight between

each other, judge where they would themselves come in the sort of fighting ability hierarchy, just by watching other wasps fighting. So there's a level of social intelligence that I am fairly confident does not exist in bees, but it does in some other insects. Does that mean the bees then, as far as we know, socially don't, when they, when they, the species that live in colonies don't recognize one another. They don't have, they don't recognize each other when they meet, when they cross parts. I suspect not, and part of the reason why I'm saying this is that there is very little variation between individuals. At least there is not the kind of variation that we're seeing in these wasps.

but there is a kind of social badge in that bees are very good at guarding their nest entrances against intruders from other colonies even of the same species. So we are accustomed to thinking of bees as very peaceful and harmonious organisms, but there is competition, of course, between colonies, and that includes sometimes raiding each. other's food stores. So the extent that perhaps, especially in autumn, it becomes more difficult to find nectar yielding or pollen yielding flowers, than one alternative is you just steal it from a neighboring hive. And bees naturally do that, but there is also a countermeasure, and that's that they position guard bees at the entrance that smell other bees using their antenna to see whether they have the hive-specific smell or whether more likely this bee is actually an intruder

from another colony. They will attack such intruders and drive them away or even kill them. So there is a colony level recognition in bees that is based on scent. But to my knowledge, no evidence, nor indeed the likelihood of individual recognition by recognizing individuals by their color mark

or their visual appearance, basically. So, you know, colloquially, we think, you know, big brains are good and useful and small, you know, call people pea-brained, perhaps meanly. And the bee has a brain, if I'm quite, the size of a poppy seed. So what does this mean for our general understanding of minds and that, the, that, the, that, the, that, all these functions can be performed with such a sort of efficiently small piece of biological equipment? That's a very good question. So first of all, it's important to realize that in brains, everything can be scaled up and scaled down depending on body size. So there are, of course, animals that have much bigger brains than we do, and these are typically bigger animals.

such as blue whales or elephants, for example, have bigger brains without necessarily having more intelligence. And smaller animals, on average, have smaller brains. And so the best predictor across the animal kingdom of brain size is simply body size. Now, what, of course, becomes interesting is if you scale brains with body size, is to look at animals that have larger brains than expected for their body size. So if they have larger brains than is expected for a particular body size, then that might at least reflect higher levels of intelligence, although you will have to ask, of course,

what these added brain structures are for. They might not necessarily be the equivalent of a better processor, if you want to use an analogy from computer science, but they could just be a bigger hard drive, more memory storage and so on, without higher levels of intelligence. So the reason why bigger animals need bigger brains is not necessarily intuitive from computer science

because you could in principle use, if you again use the analogy from computing, man-made computing systems, you could fly a jumbo jet or a small two-seater plane using the same size of computational equipment. You don't need a bigger computer for a larger plane. And so what happens in nervous systems is that because you're using neurons, nerve cells rather than electrical cables of, made from metal is that to conduct a signal over a larger distance, you need bigger nerve cells. So the bigger the animal, the more you have to scale up its nerve cells to still have

efficient conduction of nerve impulses over larger distance. So bigger animals need bigger nerve cells to compute efficiently. And so what you're seeing in bees and other smaller animals is that everything is elegantly miniaturized, but not necessarily less complex. So as you say, a bee brain is small. It's about the size of a pinhead, a cubic millimeter, and in it there are about only a million nerve cells. Now, that's very small compared to a human brain, which is perhaps about 85 billion. But each of these bee brain cells might have the structure of, in some cases, you know, of fully grown oak tree, an extremely finely branched network of protrusions that in some cases

extend through the entire brain. And each of each individual nerve cell might have 10,000 connections with other nerve cells. And each of these connections, these synapses, as they're called, might to some extent be plastic and modifiable and might change its efficiency. in conducting signals from one cell to another with experience. And so even that tiny brain of an insect with perhaps just a million neurons is still out of reach in terms of our quest to understand it comprehensively. We were closer perhaps than a human brain, that's a distant dream to understand the human brain function comprehensively, but we're still a long way from even fully understanding an insect brain.

So in terms of the complexity that I've mentioned, just in the visual system of a fly and that extends also to bees, there are over a hundred different types of nerve cells. There are only about 80 different types of nerve cells in the human retina. So there's a higher degree of complexity in insect brains, at least in the visual system, for example, than you would find in a human retina. So everything is remarkably miniaturized in an insect brain, but not necessarily less complex. That was Professor Lars Chitka there, explaining the incredible circuitry inside a bee's head. If you'd like to dig a little deeper into the mind's eye of a bee and find out whether there really is such a thing as a hive mind,

tune in to Instant Genius Extra, a bonus podcast available via subscription on Apple's podcast app. Alternatively, do pick up a copy of Lars's book, The Mind of a Bee. It's on so now and is published by Princeton University Press. Thank you for listening. The Instant Genius podcast is brought to you by the team behind BBC Science Focus magazine, which you can find on sale now in supermarkets and newsagents as well as on your preferred app store. Alternatively, do come find us online at sciencefocus.com.

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