1 00:00:02,040 --> 00:00:07,080 Speaker 1: Welcome to brain stuff from how Stuff Works, Hey, brain stuff, 2 00:00:07,120 --> 00:00:11,879 Speaker 1: Lauren vocabam here. Back in two entomologists Joe Lewis and 3 00:00:11,960 --> 00:00:15,240 Speaker 1: Jim Tomlinson joined in a project that for the first 4 00:00:15,280 --> 00:00:19,200 Speaker 1: time uncovered the ability of an insect to learn through association. 5 00:00:19,960 --> 00:00:22,160 Speaker 1: It was at the time not only novel, it was 6 00:00:22,200 --> 00:00:25,160 Speaker 1: an out and out revelation an insect, in this case, 7 00:00:25,200 --> 00:00:28,520 Speaker 1: the parasitic wasp, which feeds on and eventually kills certain 8 00:00:28,520 --> 00:00:32,479 Speaker 1: agricultural pests, could learn in a most basic way I 9 00:00:32,560 --> 00:00:37,280 Speaker 1: think Pavlov's dogs, except smaller and buzzier. From that study 10 00:00:37,360 --> 00:00:40,479 Speaker 1: and other similar research by for example, DARPA, the U. 11 00:00:40,600 --> 00:00:44,080 Speaker 1: S Department of Defense Advanced Research Projects Agency, we have 12 00:00:44,159 --> 00:00:47,400 Speaker 1: spun forward to the point where honeybees now have successfully 13 00:00:47,400 --> 00:00:51,280 Speaker 1: sniffed out long buried land mines in Croatia. That's a 14 00:00:51,320 --> 00:00:53,479 Speaker 1: long way from some thirty years ago when Lewis and 15 00:00:53,520 --> 00:00:57,160 Speaker 1: Tomlinson released their findings in Nature magazine to the astonishment 16 00:00:57,200 --> 00:01:01,400 Speaker 1: of many. Louis said, you talked at training an insect period, 17 00:01:01,480 --> 00:01:04,040 Speaker 1: and you get the look the I start narrowing. It 18 00:01:04,160 --> 00:01:07,480 Speaker 1: just doesn't make sense. So how did they start making 19 00:01:07,520 --> 00:01:10,880 Speaker 1: sense of it? Let's talk about associate of learning. The 20 00:01:10,880 --> 00:01:13,800 Speaker 1: whole idea behind this is fairly simple, even if no 21 00:01:13,840 --> 00:01:17,000 Speaker 1: one dreamed decades ago that insects could do it. With 22 00:01:17,040 --> 00:01:20,520 Speaker 1: Pavlov's dogs, when an outside stimulus a bell is often cited, 23 00:01:20,680 --> 00:01:24,559 Speaker 1: was associated with food, the dogs salivated. The dogs learned 24 00:01:24,640 --> 00:01:29,120 Speaker 1: intuitively that the bell meant food was coming for the Lewis, tumlins, 25 00:01:29,160 --> 00:01:32,880 Speaker 1: and wasps. Various odors that the wasps didn't normally recognize, 26 00:01:32,920 --> 00:01:35,760 Speaker 1: like vanilla or chocolate, or mixed with something that was 27 00:01:35,800 --> 00:01:39,160 Speaker 1: associated with the pests that these parasitic wasps were trying 28 00:01:39,200 --> 00:01:42,399 Speaker 1: to make their hosts. After a very short time, the 29 00:01:42,440 --> 00:01:46,000 Speaker 1: wasps associated the vanilla or whatever with the insects that 30 00:01:46,040 --> 00:01:49,200 Speaker 1: they wanted to attack, and thus would fly toward the odor. 31 00:01:49,760 --> 00:01:52,600 Speaker 1: It took less than five minutes to train the wasps, which, 32 00:01:52,800 --> 00:01:55,800 Speaker 1: like bees and dogs, have all factory senses thousands of 33 00:01:55,840 --> 00:01:59,560 Speaker 1: times more powerful than a humans. As the studies continued, 34 00:01:59,720 --> 00:02:02,840 Speaker 1: new researchers linked the smell of various chemical compounds and 35 00:02:02,880 --> 00:02:06,920 Speaker 1: explosives to food. Today, honey bee trained for just two 36 00:02:07,000 --> 00:02:10,000 Speaker 1: days could associate the smell of explosives with food and 37 00:02:10,080 --> 00:02:14,480 Speaker 1: seek out that smell too. Big advantages to training insects 38 00:02:14,520 --> 00:02:18,120 Speaker 1: to track odors rather than say a dog. They learn faster, 39 00:02:18,440 --> 00:02:20,800 Speaker 1: and there's a lot more of them to teach. But 40 00:02:20,960 --> 00:02:23,959 Speaker 1: releasing a swarm of wasps or bees onto a battlefield 41 00:02:24,240 --> 00:02:26,880 Speaker 1: or even a now quiet meadow in Croatia that may 42 00:02:26,880 --> 00:02:30,680 Speaker 1: be littered with minds has its challenges. Of course, tracking 43 00:02:30,680 --> 00:02:34,280 Speaker 1: the insects is foremost among them. It's impossible, as timlins 44 00:02:34,320 --> 00:02:36,720 Speaker 1: In points out, to put ships on each of them, 45 00:02:36,919 --> 00:02:40,680 Speaker 1: and you can't, as Louis says, put Alisha on a bee. Still, 46 00:02:40,800 --> 00:02:44,359 Speaker 1: scientists can trace the insects movements in at least small numbers, 47 00:02:44,400 --> 00:02:48,160 Speaker 1: through devices like drones and webcams, and something early researchers 48 00:02:48,200 --> 00:02:51,920 Speaker 1: called a wasp pound. Louis's waspound, about the size of 49 00:02:51,919 --> 00:02:55,720 Speaker 1: a large coin, contains five wasps, a tiny camera, and 50 00:02:55,760 --> 00:02:58,520 Speaker 1: a computer fan that pulls air through a small hole 51 00:02:58,639 --> 00:03:01,519 Speaker 1: in the bottom of the device. When the hound comes 52 00:03:01,560 --> 00:03:05,280 Speaker 1: near the target, smell the wasps, Lewis says, cluster around 53 00:03:05,360 --> 00:03:09,080 Speaker 1: that little hole, like pigs to a trough. Another problem 54 00:03:09,080 --> 00:03:12,560 Speaker 1: researchers face is scale. Training one wasp or one b 55 00:03:12,680 --> 00:03:15,840 Speaker 1: at a time can be laborious. Scientists have come up 56 00:03:15,840 --> 00:03:19,079 Speaker 1: with methods to train more than that, but insects, like people, 57 00:03:19,400 --> 00:03:22,840 Speaker 1: learn at different rates, so mass learning is not as accurate. 58 00:03:23,520 --> 00:03:27,000 Speaker 1: In addition, bad weather or anything that disrupts the insexibility 59 00:03:27,040 --> 00:03:32,239 Speaker 1: to smell can cause difficulties. Research is continuing. Tomlinson and 60 00:03:32,320 --> 00:03:36,240 Speaker 1: Lewis never envisioned be signiffiicg out bombs. Tomlinson is a 61 00:03:36,240 --> 00:03:39,520 Speaker 1: professor of entomology at Penn State and Lewis a retired 62 00:03:39,560 --> 00:03:42,360 Speaker 1: professor and a research entomologist with the U S Department 63 00:03:42,360 --> 00:03:45,680 Speaker 1: of Agriculture in Tifton, Georgia. They were looking for ways 64 00:03:45,680 --> 00:03:49,640 Speaker 1: to control pests biologically rather than with pesticides, and in 65 00:03:49,720 --> 00:03:52,920 Speaker 1: fact they were very successful at it. Along with UK 66 00:03:53,040 --> 00:03:56,520 Speaker 1: scientist John Pickett, Lewis and Tomlinson one the two thousand 67 00:03:56,600 --> 00:03:59,840 Speaker 1: eight Wolf Prize for Agriculture, considered by many as a 68 00:04:00,000 --> 00:04:02,800 Speaker 1: type of Nobel Prize in the field. From the official 69 00:04:02,800 --> 00:04:05,840 Speaker 1: announcement on the Wolf Foundation website, they were awarded the 70 00:04:05,880 --> 00:04:09,680 Speaker 1: prize quote for their remarkable discoveries of mechanisms governing plant 71 00:04:09,720 --> 00:04:14,320 Speaker 1: insect and plant plant interactions. Their scientific contributions on chemical 72 00:04:14,320 --> 00:04:17,919 Speaker 1: ecology have fostered the development of integrated pest management and 73 00:04:18,000 --> 00:04:23,440 Speaker 1: significantly advanced agricultural sustainability. Whether their work eventually will help 74 00:04:23,520 --> 00:04:26,400 Speaker 1: form the basis of a widespread practical use of bees 75 00:04:26,400 --> 00:04:29,359 Speaker 1: and wasps in sniffing out bombs or drugs remains to 76 00:04:29,400 --> 00:04:33,640 Speaker 1: be seen. Even they have some doubts. Tomlinson said, you 77 00:04:33,680 --> 00:04:36,760 Speaker 1: can train insects to find a mine, that's not a problem. 78 00:04:36,800 --> 00:04:38,800 Speaker 1: But then you release them into the field to find 79 00:04:38,839 --> 00:04:42,159 Speaker 1: a mine. How do you track them unless someone comes 80 00:04:42,240 --> 00:04:43,880 Speaker 1: up with a small chip so that you can track 81 00:04:43,920 --> 00:04:46,599 Speaker 1: them with some electronic means. I don't see how in 82 00:04:46,640 --> 00:04:49,800 Speaker 1: the world you can use them, and says Lewis, to 83 00:04:49,880 --> 00:04:52,000 Speaker 1: move it from the lab to the actual field. You 84 00:04:52,080 --> 00:04:54,479 Speaker 1: have to scale it up and refine it. But we 85 00:04:54,560 --> 00:04:57,200 Speaker 1: clearly can see that it can be practical in development. 86 00:04:57,440 --> 00:05:00,359 Speaker 1: It's technically feasible. It's all on valid sign it's the 87 00:05:00,400 --> 00:05:03,320 Speaker 1: ability is there. It's about the demand for it and 88 00:05:03,400 --> 00:05:07,320 Speaker 1: putting the infrastructure in place for that. Scientists have been 89 00:05:07,360 --> 00:05:09,880 Speaker 1: trying to find ways to harness the remarkable power of 90 00:05:09,960 --> 00:05:14,000 Speaker 1: smell for years. Bees, some believe, have such strong abilities 91 00:05:14,000 --> 00:05:17,239 Speaker 1: that they can smell out illnesses, even cancer. A Spanish 92 00:05:17,279 --> 00:05:20,840 Speaker 1: designer went so far as developing a prototype bowl complete 93 00:05:20,839 --> 00:05:23,360 Speaker 1: with honey bees that you can breathe into to see 94 00:05:23,360 --> 00:05:26,160 Speaker 1: how the bees react as a sort of proto diagnosis, 95 00:05:26,680 --> 00:05:29,360 Speaker 1: and tests are being done in California with cancer detecting 96 00:05:29,400 --> 00:05:37,520 Speaker 1: dogs too. Today's episode was written by John Donovan and 97 00:05:37,560 --> 00:05:40,560 Speaker 1: produced by Tyler Clang. Brain Stuff has merch now. 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