Deborah Gordon: What ants teach us about the brain, cancer and the Internet

78,446 views

2014-05-13 ・ TED


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Deborah Gordon: What ants teach us about the brain, cancer and the Internet

78,446 views ・ 2014-05-13

TED


Please double-click on the English subtitles below to play the video.

00:13
I study ants
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in the desert, in the tropical forest
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and in my kitchen,
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and in the hills around Silicon Valley where I live.
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I've recently realized that ants
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are using interactions differently
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in different environments,
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and that got me thinking that we could learn from this
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about other systems,
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like brains and data networks that we engineer,
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and even cancer.
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So what all these systems have in common
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is that there's no central control.
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An ant colony consists of sterile female workers --
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those are the ants you see walking around —
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and then one or more reproductive females
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who just lay the eggs.
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They don't give any instructions.
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Even though they're called queens,
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they don't tell anybody what to do.
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So in an ant colony, there's no one in charge,
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and all systems like this without central control
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are regulated using very simple interactions.
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Ants interact using smell.
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They smell with their antennae,
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and they interact with their antennae,
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so when one ant touches another with its antennae,
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it can tell, for example, if the other ant
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is a nestmate
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and what task that other ant has been doing.
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So here you see a lot of ants moving around
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and interacting in a lab arena
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that's connected by tubes to two other arenas.
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So when one ant meets another,
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it doesn't matter which ant it meets,
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and they're actually not transmitting
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any kind of complicated signal or message.
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All that matters to the ant is the rate
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at which it meets other ants.
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And all of these interactions, taken together,
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produce a network.
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So this is the network of the ants
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that you just saw moving around in the arena,
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and it's this constantly shifting network
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that produces the behavior of the colony,
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like whether all the ants are hiding inside the nest,
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or how many are going out to forage.
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A brain actually works in the same way,
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but what's great about ants is
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that you can see the whole network as it happens.
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There are more than 12,000 species of ants,
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in every conceivable environment,
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and they're using interactions differently
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to meet different environmental challenges.
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So one important environmental challenge
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that every system has to deal with
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is operating costs, just what it takes
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to run the system.
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And another environmental challenge is resources,
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finding them and collecting them.
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In the desert, operating costs are high
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because water is scarce,
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and the seed-eating ants that I study in the desert
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have to spend water to get water.
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So an ant outside foraging,
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searching for seeds in the hot sun,
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just loses water into the air.
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But the colony gets its water
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by metabolizing the fats out of the seeds
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that they eat.
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So in this environment, interactions are used
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to activate foraging.
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An outgoing forager doesn't go out unless
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it gets enough interactions with returning foragers,
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and what you see are the returning foragers
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going into the tunnel, into the nest,
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and meeting outgoing foragers on their way out.
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This makes sense for the ant colony,
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because the more food there is out there,
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the more quickly the foragers find it,
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the faster they come back,
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and the more foragers they send out.
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The system works to stay stopped,
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unless something positive happens.
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So interactions function to activate foragers.
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And we've been studying the evolution of this system.
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First of all, there's variation.
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It turns out that colonies are different.
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On dry days, some colonies forage less,
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so colonies are different in how
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they manage this trade-off
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between spending water to search for seeds
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and getting water back in the form of seeds.
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And we're trying to understand why
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some colonies forage less than others
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by thinking about ants as neurons,
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using models from neuroscience.
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So just as a neuron adds up its stimulation
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from other neurons to decide whether to fire,
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an ant adds up its stimulation from other ants
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to decide whether to forage.
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And what we're looking for is whether there might be
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small differences among colonies
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in how many interactions each ant needs
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before it's willing to go out and forage,
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because a colony like that would forage less.
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And this raises an analogous question about brains.
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We talk about the brain,
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but of course every brain is slightly different,
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and maybe there are some individuals
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or some conditions
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in which the electrical properties of neurons are such
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that they require more stimulus to fire,
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and that would lead to differences in brain function.
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So in order to ask evolutionary questions,
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we need to know about reproductive success.
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This is a map of the study site
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where I have been tracking this population
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of harvester ant colonies for 28 years,
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which is about as long as a colony lives.
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Each symbol is a colony,
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and the size of the symbol is how many offspring it had,
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because we were able to use genetic variation
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to match up parent and offspring colonies,
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that is, to figure out which colonies
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were founded by a daughter queen
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produced by which parent colony.
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And this was amazing for me, after all these years,
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to find out, for example, that colony 154,
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whom I've known well for many years,
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is a great-grandmother.
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Here's her daughter colony,
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here's her granddaughter colony,
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and these are her great-granddaughter colonies.
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And by doing this, I was able to learn
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that offspring colonies resemble parent colonies
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in their decisions about which days are so hot
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that they don't forage,
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and the offspring of parent colonies
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live so far from each other that the ants never meet,
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so the ants of the offspring colony
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can't be learning this from the parent colony.
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And so our next step is to look
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for the genetic variation underlying this resemblance.
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So then I was able to ask, okay, who's doing better?
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Over the time of the study,
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and especially in the past 10 years,
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there's been a very severe and deepening drought
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in the Southwestern U.S.,
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and it turns out that the colonies that conserve water,
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that stay in when it's really hot outside,
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and thus sacrifice getting as much food as possible,
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are the ones more likely to have offspring colonies.
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So all this time, I thought that colony 154
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was a loser, because on really dry days,
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there'd be just this trickle of foraging,
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while the other colonies were out
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foraging, getting lots of food,
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but in fact, colony 154 is a huge success.
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She's a matriarch.
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She's one of the rare great-grandmothers on the site.
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To my knowledge, this is the first time
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that we've been able to track
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the ongoing evolution of collective behavior
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in a natural population of animals
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and find out what's actually working best.
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Now, the Internet uses an algorithm
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to regulate the flow of data
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that's very similar to the one
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that the harvester ants are using to regulate
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the flow of foragers.
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And guess what we call this analogy?
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The anternet is coming.
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(Applause)
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So data doesn't leave the source computer
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unless it gets a signal that there's enough bandwidth
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for it to travel on.
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In the early days of the Internet,
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when operating costs were really high
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and it was really important not to lose any data,
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then the system was set up for interactions
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to activate the flow of data.
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It's interesting that the ants are using an algorithm
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that's so similar to the one that we recently invented,
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but this is only one of a handful of ant algorithms
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that we know about,
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and ants have had 130 million years
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to evolve a lot of good ones,
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and I think it's very likely
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that some of the other 12,000 species
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are going to have interesting algorithms
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for data networks
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that we haven't even thought of yet.
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So what happens when operating costs are low?
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Operating costs are low in the tropics,
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because it's very humid, and it's easy for the ants
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to be outside walking around.
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But the ants are so abundant
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and diverse in the tropics
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that there's a lot of competition.
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Whatever resource one species is using,
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another species is likely to be using that
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at the same time.
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So in this environment, interactions are used
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in the opposite way.
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The system keeps going
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unless something negative happens,
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and one species that I study makes circuits
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in the trees of foraging ants
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going from the nest to a food source and back,
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just round and round,
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unless something negative happens,
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like an interaction
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with ants of another species.
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So here's an example of ant security.
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In the middle, there's an ant
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plugging the nest entrance with its head
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in response to interactions with another species.
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Those are the little ones running around
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with their abdomens up in the air.
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But as soon as the threat is passed,
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the entrance is open again,
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and maybe there are situations
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in computer security
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where operating costs are low enough
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that we could just block access temporarily
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in response to an immediate threat,
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and then open it again,
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instead of trying to build
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a permanent firewall or fortress.
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So another environmental challenge
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that all systems have to deal with
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is resources, finding and collecting them.
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And to do this, ants solve the problem
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of collective search,
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and this is a problem that's of great interest
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right now in robotics,
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because we've understood that,
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rather than sending a single,
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sophisticated, expensive robot out
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to explore another planet
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or to search a burning building,
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that instead, it may be more effective
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to get a group of cheaper robots
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exchanging only minimal information,
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and that's the way that ants do it.
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So the invasive Argentine ant
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makes expandable search networks.
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They're good at dealing with the main problem
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of collective search,
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which is the trade-off between
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searching very thoroughly
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and covering a lot of ground.
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And what they do is,
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when there are many ants in a small space,
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then each one can search very thoroughly
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because there will be another ant nearby
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searching over there,
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but when there are a few ants
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in a large space,
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then they need to stretch out their paths
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to cover more ground.
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I think they use interactions to assess density,
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so when they're really crowded,
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they meet more often,
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and they search more thoroughly.
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Different ant species must use different algorithms,
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because they've evolved to deal with
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different resources,
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and it could be really useful to know about this,
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and so we recently asked ants
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to solve the collective search problem
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in the extreme environment
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of microgravity
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in the International Space Station.
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When I first saw this picture, I thought,
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Oh no, they've mounted the habitat vertically,
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but then I realized that, of course, it doesn't matter.
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So the idea here is that the ants
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are working so hard to hang on
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to the wall or the floor or whatever you call it
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that they're less likely to interact,
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and so the relationship between
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how crowded they are and how often they meet
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would be messed up.
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We're still analyzing the data.
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I don't have the results yet.
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But it would be interesting to know
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how other species solve this problem
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in different environments on Earth,
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and so we're setting up a program
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to encourage kids around the world
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to try this experiment with different species.
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It's very simple.
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It can be done with cheap materials.
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And that way, we could make a global map
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of ant collective search algorithms.
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And I think it's pretty likely that the invasive species,
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the ones that come into our buildings,
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are going to be really good at this,
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because they're in your kitchen
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because they're really good at finding food and water.
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So the most familiar resource for ants
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is a picnic,
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and this is a clustered resource.
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When there's one piece of fruit,
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there's likely to be another piece of fruit nearby,
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and the ants that specialize on clustered resources
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use interactions for recruitment.
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So when one ant meets another,
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or when it meets a chemical deposited
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on the ground by another,
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then it changes direction to follow
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in the direction of the interaction,
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and that's how you get the trail of ants
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sharing your picnic.
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Now this is a place where I think we might be able
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to learn something from ants about cancer.
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I mean, first, it's obvious that we could do a lot
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to prevent cancer
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by not allowing people to spread around
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or sell the toxins that promote
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the evolution of cancer in our bodies,
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but I don't think the ants can help us much with this
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because ants never poison their own colonies.
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But we might be able to learn something from ants
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about treating cancer.
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There are many different kinds of cancer.
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Each one originates in a particular part of the body,
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and then some kinds of cancer will spread
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or metastasize to particular other tissues
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where they must be getting resources that they need.
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So if you think from the perspective
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of early metastatic cancer cells
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as they're out searching around
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for the resources that they need,
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if those resources are clustered,
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they're likely to use interactions for recruitment,
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and if we can figure out how cancer cells are recruiting,
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then maybe we could set traps
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to catch them before they become established.
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So ants are using interactions in different ways
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in a huge variety of environments,
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and we could learn from this
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about other systems that operate
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without central control.
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Using only simple interactions,
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ant colonies have been performing
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amazing feats for more than 130 million years.
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We have a lot to learn from them.
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Thank you.
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(Applause)
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