1 00:00:06,000 --> 00:00:10,000 Speaker 1: Happy Halloween everyone. This is my favorite time of year. 2 00:00:10,360 --> 00:00:14,080 Speaker 1: The weather's cool, the leaves are changing color here in Virginia, 3 00:00:14,440 --> 00:00:18,319 Speaker 1: and creepy stuff is in. So this week Daniel and 4 00:00:18,360 --> 00:00:23,079 Speaker 1: I are geeking out about zombies and ghosts. The zombies 5 00:00:23,079 --> 00:00:25,960 Speaker 1: I'm going to be talking about aren't like creatures who 6 00:00:26,000 --> 00:00:29,360 Speaker 1: have been infected by viruses that bring the creatures back 7 00:00:29,360 --> 00:00:32,760 Speaker 1: from the dead in search of delicious brains. But what 8 00:00:32,840 --> 00:00:36,360 Speaker 1: are often called zombies in pop science are creatures that 9 00:00:36,400 --> 00:00:40,800 Speaker 1: are infected by parasites, and then those parasites manipulate their 10 00:00:41,000 --> 00:00:45,440 Speaker 1: living creatures living hosts into acting in weird ways that 11 00:00:45,520 --> 00:00:50,880 Speaker 1: benefit the parasite while often hurting the host. But one 12 00:00:50,880 --> 00:00:55,600 Speaker 1: of the hard things about studying seemingly zombified creatures is 13 00:00:55,640 --> 00:00:59,360 Speaker 1: that behaviors can change when someone is infected for a 14 00:00:59,440 --> 00:01:03,080 Speaker 1: lot of reasons. Just because it sounds like a behavior 15 00:01:03,120 --> 00:01:07,520 Speaker 1: can benefit a parasite, that doesn't necessarily mean that it does. 16 00:01:08,120 --> 00:01:12,760 Speaker 1: In fact, sometimes we've looked into seemingly zombified creatures and 17 00:01:12,800 --> 00:01:15,440 Speaker 1: when we look into them more closely, the story that 18 00:01:15,480 --> 00:01:18,800 Speaker 1: we had been telling ourselves falls apart. Let's think through 19 00:01:18,800 --> 00:01:21,400 Speaker 1: why this can be so tough, all right, So, imagine 20 00:01:21,400 --> 00:01:24,080 Speaker 1: you're a kid who's home with a fever. Who does 21 00:01:24,120 --> 00:01:27,160 Speaker 1: that fever benefit all right, Well, maybe it benefits the 22 00:01:27,200 --> 00:01:30,160 Speaker 1: sick kid. If the high temperature makes it hard for 23 00:01:30,360 --> 00:01:33,160 Speaker 1: the bacteria or something to survive and grow, all right, 24 00:01:33,160 --> 00:01:37,720 Speaker 1: that's option one. Option two, maybe neither benefits. So if 25 00:01:37,720 --> 00:01:40,160 Speaker 1: the fever gets too high, then maybe that's bad for 26 00:01:40,200 --> 00:01:43,360 Speaker 1: the kid and it's bad for the bacteria. Anyone who 27 00:01:43,360 --> 00:01:46,679 Speaker 1: has allergies knows that sometimes immune systems overact and do 28 00:01:46,800 --> 00:01:49,680 Speaker 1: things that are not beneficial. So there are some instances 29 00:01:49,720 --> 00:01:53,200 Speaker 1: where something changes about the infected individual that's really not 30 00:01:53,280 --> 00:01:57,040 Speaker 1: good for the individual or the bacteria. Third option is 31 00:01:57,040 --> 00:02:01,240 Speaker 1: that maybe the change that happens after infection benefits the parasite. 32 00:02:01,880 --> 00:02:04,280 Speaker 1: So say a kid comes home with a fever, some 33 00:02:04,480 --> 00:02:07,680 Speaker 1: parent is definitely going to bend over and give that 34 00:02:07,800 --> 00:02:10,480 Speaker 1: kiddo a kiss on the forehead to see how warm 35 00:02:10,480 --> 00:02:14,120 Speaker 1: their forehead is. And if my experience as a parent 36 00:02:14,240 --> 00:02:17,200 Speaker 1: is any indication that is exactly when the kid is 37 00:02:17,240 --> 00:02:21,040 Speaker 1: going to sneeze directly into your face and often directly 38 00:02:21,080 --> 00:02:24,000 Speaker 1: into your mouth. So you could tell a story about 39 00:02:24,040 --> 00:02:29,040 Speaker 1: a fever being away that parasites are bacterial infections. Transmit 40 00:02:29,160 --> 00:02:32,320 Speaker 1: from kids to their parents. So we've come up with 41 00:02:32,360 --> 00:02:35,560 Speaker 1: a fairly plausible story. And I was just spitballing here, 42 00:02:35,560 --> 00:02:37,480 Speaker 1: but the point is that it's easy to tell a 43 00:02:37,560 --> 00:02:41,240 Speaker 1: story that sounds kind of plausible. So when you see 44 00:02:41,280 --> 00:02:44,400 Speaker 1: a story about a creature responding in some way after 45 00:02:44,480 --> 00:02:47,680 Speaker 1: it gets sick, it's important to consider all the different 46 00:02:47,720 --> 00:02:50,960 Speaker 1: reasons why that could be happening. So today we're going 47 00:02:51,040 --> 00:02:54,880 Speaker 1: to start our Halloween show with the chat about toxoplasma 48 00:02:54,919 --> 00:02:57,800 Speaker 1: GANDHII and how it changes the behavior of the creatures 49 00:02:57,840 --> 00:03:00,640 Speaker 1: it infects, and we're going to evaluate how good the 50 00:03:00,680 --> 00:03:04,920 Speaker 1: evidence for these claims actually are. The disconnect between the 51 00:03:04,960 --> 00:03:09,000 Speaker 1: strength of the claims about toxoplasma gandhi i'm manipulating the 52 00:03:09,040 --> 00:03:12,480 Speaker 1: behavior of the creature and effects and the actual evidence 53 00:03:13,040 --> 00:03:17,440 Speaker 1: is kind of spooky. And parents, we talk a bit 54 00:03:17,480 --> 00:03:19,680 Speaker 1: about the birds and the bees when describing the life 55 00:03:19,720 --> 00:03:23,480 Speaker 1: cycle of this parasite. Nothing too gratuitous or anything. But 56 00:03:23,600 --> 00:03:26,120 Speaker 1: now is your chance to pick a different episode for 57 00:03:26,200 --> 00:03:29,120 Speaker 1: the car ride with your kids if you think that's necessary. 58 00:03:29,800 --> 00:03:36,480 Speaker 1: All right, Welcome to Daniel and Kelly's Extraordinary and spooky universe. 59 00:03:50,440 --> 00:03:53,800 Speaker 2: Hi, I'm Daniel, I'm a particle physicist, and I'm wearing 60 00:03:53,920 --> 00:03:56,160 Speaker 2: a Halloween costume chosen by my daughter. 61 00:03:56,680 --> 00:03:59,440 Speaker 1: I'm Kelly Wiener Smith, and I'm excited because this is 62 00:03:59,480 --> 00:04:02,480 Speaker 1: the best time a year to not be in California, 63 00:04:02,560 --> 00:04:05,040 Speaker 1: because the leaves are changed in color and it's gorgeous 64 00:04:05,080 --> 00:04:07,560 Speaker 1: here in California. Just doesn't have anything on Virginia this 65 00:04:07,600 --> 00:04:10,000 Speaker 1: time of year. Sorry, Daniel. 66 00:04:10,280 --> 00:04:13,400 Speaker 2: Have you been to California in October? The air is 67 00:04:13,520 --> 00:04:17,160 Speaker 2: wonderfully crisp, it still never rains. It's pretty nice. 68 00:04:17,400 --> 00:04:20,200 Speaker 1: I lived there, I've been there in the fall, and 69 00:04:20,240 --> 00:04:21,839 Speaker 1: it's not as good as Virginia. 70 00:04:22,640 --> 00:04:24,400 Speaker 2: All Right, I'm gonna have to come gather some data 71 00:04:24,440 --> 00:04:27,680 Speaker 2: on Virginia so I can make intelligent comments rather than 72 00:04:27,760 --> 00:04:28,919 Speaker 2: just take cheap potshots. 73 00:04:29,000 --> 00:04:31,440 Speaker 1: Sounds good, although you're coming to visit in March, which 74 00:04:31,520 --> 00:04:33,640 Speaker 1: is maybe not the best Virginia month. 75 00:04:33,839 --> 00:04:35,440 Speaker 2: But oh, I see right. 76 00:04:35,680 --> 00:04:37,120 Speaker 1: I'm already hedging my bets. 77 00:04:37,640 --> 00:04:39,320 Speaker 2: You're making excuses for it already. 78 00:04:39,400 --> 00:04:41,400 Speaker 1: Yeah, that's right, that's right. 79 00:04:42,279 --> 00:04:45,760 Speaker 2: Well. I love Halloween also because I usually teach my 80 00:04:45,839 --> 00:04:48,919 Speaker 2: class in costume, and today I give an exam in 81 00:04:48,960 --> 00:04:51,120 Speaker 2: my class, and I told them if they came to 82 00:04:51,160 --> 00:04:53,760 Speaker 2: the exam in full costume. They get extra credit. 83 00:04:54,440 --> 00:04:56,839 Speaker 1: What is the best costume your student has ever worn 84 00:04:56,880 --> 00:04:57,360 Speaker 1: to class? 85 00:04:58,480 --> 00:05:00,279 Speaker 2: Somebody came in one of those huge, bl low up 86 00:05:00,320 --> 00:05:03,920 Speaker 2: dinosaur costumes, took up like three rows of seats and 87 00:05:04,080 --> 00:05:06,160 Speaker 2: took their exam. It's hard to fill out a scanshow 88 00:05:06,200 --> 00:05:08,120 Speaker 2: with the little t rex arms, but they did it. 89 00:05:08,480 --> 00:05:11,640 Speaker 1: That's commitment. That's actually my daughter's Halloween costume this year. 90 00:05:11,920 --> 00:05:13,480 Speaker 1: We got her one of those. I can't wait to 91 00:05:13,480 --> 00:05:15,360 Speaker 1: see how she looks at it. She's gonna have a blast. 92 00:05:15,520 --> 00:05:18,240 Speaker 1: And I am a giant moth because I like insects, 93 00:05:18,279 --> 00:05:20,359 Speaker 1: and so I got a moth onesie so that I 94 00:05:20,360 --> 00:05:22,320 Speaker 1: can still wear it for other things, because I don't 95 00:05:22,320 --> 00:05:24,600 Speaker 1: want to spend fifty dollars on something I'm gonna wear once. 96 00:05:24,880 --> 00:05:26,360 Speaker 1: So yeah, it's gonna be a good Halloween in the 97 00:05:26,360 --> 00:05:27,279 Speaker 1: Wienersmith House. 98 00:05:27,320 --> 00:05:29,320 Speaker 2: So you're just gonna hang out in that onesie the 99 00:05:29,320 --> 00:05:29,920 Speaker 2: rest of the year. 100 00:05:30,000 --> 00:05:33,240 Speaker 1: Also, yeah, no, probably I might decide that I really 101 00:05:33,279 --> 00:05:35,240 Speaker 1: like being a moth and maybe that's all I'm gonna. 102 00:05:35,000 --> 00:05:38,080 Speaker 2: Wear Sunday Moth Day at the Wienersmith Farm. 103 00:05:38,400 --> 00:05:41,919 Speaker 1: Yeah, just one more way I embarrass my children. The 104 00:05:42,000 --> 00:05:42,800 Speaker 1: list is getting long. 105 00:05:43,080 --> 00:05:45,240 Speaker 2: Well, I give my daughter free rain to choose my costume. 106 00:05:45,279 --> 00:05:48,520 Speaker 2: I said, whatever costume you pick, I'm gonna wear, which 107 00:05:48,560 --> 00:05:51,359 Speaker 2: is why I'm now an alien abducting human. 108 00:05:53,279 --> 00:05:56,359 Speaker 1: That's fantastic. How hard was it to make that costume? 109 00:05:57,240 --> 00:06:01,440 Speaker 2: Oh no, she bought it for sure. Oh and I 110 00:06:01,440 --> 00:06:03,560 Speaker 2: don't think she listens to the podcast, but she hears 111 00:06:03,560 --> 00:06:06,480 Speaker 2: me talk about aliens enough to know that the alien 112 00:06:06,520 --> 00:06:07,440 Speaker 2: theme was going to suit me. 113 00:06:07,839 --> 00:06:10,120 Speaker 1: Excellent. It's nice when your kids know you pretty well 114 00:06:10,640 --> 00:06:12,880 Speaker 1: a little bit. I can't get my husband to wear 115 00:06:12,880 --> 00:06:13,600 Speaker 1: a costume at all. 116 00:06:13,800 --> 00:06:14,120 Speaker 2: What. 117 00:06:14,400 --> 00:06:16,440 Speaker 1: No, He's never worn a costume for Halloween as far 118 00:06:16,480 --> 00:06:16,800 Speaker 1: as I know. 119 00:06:17,279 --> 00:06:18,680 Speaker 2: Why is he anti costume? 120 00:06:18,920 --> 00:06:21,600 Speaker 1: He's so creative, he's anti fun. I don't know. 121 00:06:22,120 --> 00:06:26,159 Speaker 2: Come he writes a webcomic. He can't be anti fun. 122 00:06:26,200 --> 00:06:28,679 Speaker 2: He makes people laugh. He can't be anti fun. 123 00:06:29,040 --> 00:06:30,960 Speaker 1: I don't know what to tell you, man, he's anti 124 00:06:31,040 --> 00:06:33,920 Speaker 1: fun on Halloween. I guess I tried to get a 125 00:06:33,960 --> 00:06:36,599 Speaker 1: family costume and he was absolutely no on the family 126 00:06:36,640 --> 00:06:37,240 Speaker 1: costume thing. 127 00:06:37,480 --> 00:06:39,360 Speaker 2: Maybe you should all dress up as him one year, 128 00:06:39,520 --> 00:06:40,560 Speaker 2: then he's in costume. 129 00:06:40,920 --> 00:06:44,240 Speaker 1: I like that, Eric, Thank you. I'm making a note 130 00:06:44,279 --> 00:06:46,880 Speaker 1: in my Google calendar for next year, everybody dresses up 131 00:06:46,920 --> 00:06:47,320 Speaker 1: like Zach. 132 00:06:47,680 --> 00:06:49,920 Speaker 2: But we are not here today just to so discord 133 00:06:49,920 --> 00:06:52,960 Speaker 2: in Kelly's family. We are here to talk about Halloween. 134 00:06:53,080 --> 00:06:55,479 Speaker 2: And because we are science nerds and we'd like to 135 00:06:55,480 --> 00:06:57,960 Speaker 2: dig deep into science of everything, we're here to talk 136 00:06:57,960 --> 00:07:02,599 Speaker 2: about the science of Halloween, specifically zombies and ghosts, the 137 00:07:02,640 --> 00:07:05,000 Speaker 2: biology and physics of Halloween. 138 00:07:05,720 --> 00:07:08,080 Speaker 1: I am so excited about this episode, and I'm also 139 00:07:08,120 --> 00:07:10,080 Speaker 1: exciting because it gives me a chance to talk about 140 00:07:10,320 --> 00:07:14,040 Speaker 1: probably the most famous parasite that manipulates the behavior of 141 00:07:14,080 --> 00:07:17,520 Speaker 1: its host, Toxoplasma gandhi. And as someone who got their 142 00:07:17,560 --> 00:07:21,240 Speaker 1: PhD in this field, I am constantly asked about this parasite, 143 00:07:21,320 --> 00:07:24,320 Speaker 1: and I am constantly frustrated by the disconnect between what 144 00:07:24,480 --> 00:07:27,520 Speaker 1: people think we know and what the evidence actually supports. So, 145 00:07:27,960 --> 00:07:31,640 Speaker 1: just like usual, I am going to throw water on 146 00:07:31,880 --> 00:07:34,800 Speaker 1: everyone's fun. But there's still some cool things to learn 147 00:07:34,840 --> 00:07:36,080 Speaker 1: along the way, so it'll be okay. 148 00:07:36,160 --> 00:07:39,000 Speaker 2: So you're saying it's not just physics that has like nonsense, 149 00:07:39,040 --> 00:07:42,480 Speaker 2: popsy clickbait misinformation, it's also biology. 150 00:07:42,760 --> 00:07:44,960 Speaker 1: Oh my gosh, it's also biology. I mean, we're lucky 151 00:07:44,960 --> 00:07:47,480 Speaker 1: because we have Ed Yong who writes about parasites that 152 00:07:47,480 --> 00:07:51,360 Speaker 1: manipulate host behavior, and he's like, super good about evaluating 153 00:07:51,360 --> 00:07:53,920 Speaker 1: the evidence, but not everybody is quite that careful. And 154 00:07:53,960 --> 00:07:56,600 Speaker 1: it seems to have emerged in the public consciousness that 155 00:07:56,640 --> 00:08:00,800 Speaker 1: Toxoplasma gandhi absolutely makes rodents attract to cats and gets 156 00:08:00,800 --> 00:08:03,200 Speaker 1: the meetn by it and changes human behavior and all 157 00:08:03,240 --> 00:08:04,080 Speaker 1: sorts of weird pays. 158 00:08:04,800 --> 00:08:07,320 Speaker 2: But let's start with the connection of Halloween. Do you 159 00:08:07,400 --> 00:08:11,400 Speaker 2: chose this paraside because it kind of makes things into zombies? 160 00:08:11,560 --> 00:08:15,520 Speaker 2: Is that right? What's the zombie connection between Toxoplasma gandhi 161 00:08:15,640 --> 00:08:16,320 Speaker 2: and Halloween? 162 00:08:16,520 --> 00:08:19,640 Speaker 1: All right, So every field has their like thing that 163 00:08:19,680 --> 00:08:22,000 Speaker 1: everybody fights about and they get upset about, and the 164 00:08:22,120 --> 00:08:25,920 Speaker 1: use of the phrase zombie really divides my field. So 165 00:08:25,960 --> 00:08:28,080 Speaker 1: there are some people who are like, well, if you 166 00:08:28,120 --> 00:08:30,400 Speaker 1: call it a zombie, people are going to think that 167 00:08:30,520 --> 00:08:33,160 Speaker 1: the animal that got infected died and then came back 168 00:08:33,160 --> 00:08:35,640 Speaker 1: from the dead. And I'm like, I just feel like 169 00:08:35,640 --> 00:08:37,880 Speaker 1: you're not giving the general public enough credit, Like, I 170 00:08:37,920 --> 00:08:40,240 Speaker 1: don't think anyone thinks that they're being brought back from 171 00:08:40,240 --> 00:08:42,320 Speaker 1: the dead. What do you think is that fair to say? 172 00:08:42,520 --> 00:08:44,600 Speaker 2: Yeah, that's a great question. I think my first thought 173 00:08:44,600 --> 00:08:47,280 Speaker 2: when I hear, zombie is definitely the walking dead, right, 174 00:08:47,360 --> 00:08:49,600 Speaker 2: like these folks have been killed and now they're like 175 00:08:49,640 --> 00:08:53,040 Speaker 2: shuffling around. But I've seen enough zombie movies and science 176 00:08:53,040 --> 00:08:55,800 Speaker 2: fiction in general to appreciate this like a broadening of 177 00:08:55,800 --> 00:08:58,440 Speaker 2: the category. And you know, people being infected by some 178 00:08:58,480 --> 00:09:00,840 Speaker 2: sort of disease which makes them want to eat brains 179 00:09:00,880 --> 00:09:03,000 Speaker 2: and shuffle around and like are they or not doesn't 180 00:09:03,040 --> 00:09:05,720 Speaker 2: seem to be really crucial to being a zombie. It's 181 00:09:05,760 --> 00:09:08,520 Speaker 2: more like, you know, drooling a lot, shuffling along and 182 00:09:08,559 --> 00:09:11,880 Speaker 2: wanting to eat brains. So it'd be pretty cool if 183 00:09:11,880 --> 00:09:15,120 Speaker 2: there was a real life biological effect that made people 184 00:09:15,200 --> 00:09:17,679 Speaker 2: act like the zombies in the movies we see. I 185 00:09:17,720 --> 00:09:19,599 Speaker 2: think people would accept that as a zombie. 186 00:09:19,760 --> 00:09:23,080 Speaker 1: Okay, well that's not what I'm talking about today. No, 187 00:09:24,240 --> 00:09:26,760 Speaker 1: it's not like that. I still feel like if you 188 00:09:26,840 --> 00:09:29,600 Speaker 1: use the word zombie, then people think like, okay, some 189 00:09:29,720 --> 00:09:33,480 Speaker 1: infectious something that's changing the behavior as high decked the behavior, 190 00:09:33,920 --> 00:09:36,079 Speaker 1: And that's really all we mean today. And so it's 191 00:09:36,120 --> 00:09:38,319 Speaker 1: a way to try to make the topics sort of 192 00:09:38,400 --> 00:09:41,120 Speaker 1: accessible and exciting to a general public. But it has 193 00:09:41,160 --> 00:09:44,080 Speaker 1: its drawbacks because I guess, just like any analogy. It's 194 00:09:44,080 --> 00:09:46,720 Speaker 1: not perfect and it falls flat in some ways, but 195 00:09:46,800 --> 00:09:47,600 Speaker 1: I like it anyway. 196 00:09:47,720 --> 00:09:49,560 Speaker 2: And just to set the context a little bit more like, 197 00:09:49,880 --> 00:09:52,880 Speaker 2: I can be infected by some bug or even some parasite, 198 00:09:53,000 --> 00:09:55,440 Speaker 2: but doesn't change my behavior. I mean, maybe I get sick, 199 00:09:55,440 --> 00:09:57,480 Speaker 2: but it doesn't make me like change what I eat 200 00:09:57,960 --> 00:10:00,440 Speaker 2: or decide I'm gonna study biology instead of physics or 201 00:10:00,640 --> 00:10:04,360 Speaker 2: some crazy mind bending misdecision in life, or live in 202 00:10:04,480 --> 00:10:08,200 Speaker 2: Virginia or something insane. Right, I'm still who I am mentally. 203 00:10:08,440 --> 00:10:11,360 Speaker 2: So you're saying that there's a category of bugs or 204 00:10:11,360 --> 00:10:14,280 Speaker 2: parasites whatever that also change the way your brain works, 205 00:10:14,280 --> 00:10:15,600 Speaker 2: and so the decisions. 206 00:10:15,120 --> 00:10:17,640 Speaker 1: You make, yes, and those decisions that you make are 207 00:10:17,640 --> 00:10:20,160 Speaker 1: decisions that benefit the parasite and may or may not 208 00:10:20,240 --> 00:10:23,280 Speaker 1: benefit you. So you know the eating brains in the 209 00:10:23,360 --> 00:10:25,160 Speaker 1: zombie movies, you know, you take a bite out of 210 00:10:25,160 --> 00:10:28,120 Speaker 1: somebody and that transmits the parasite in the saliva to 211 00:10:28,200 --> 00:10:30,840 Speaker 1: another individual. And maybe the eating brains is a side effect. 212 00:10:30,920 --> 00:10:32,680 Speaker 1: I don't know, but so it's got to benefit the 213 00:10:32,679 --> 00:10:35,000 Speaker 1: parasite in some way, and often at the expense of 214 00:10:35,040 --> 00:10:35,720 Speaker 1: the host. 215 00:10:35,960 --> 00:10:38,480 Speaker 2: Okay, So now I'm mentally imagining, you know, the rat 216 00:10:38,480 --> 00:10:40,480 Speaker 2: and ratitude that sits on the guy's head and pulls 217 00:10:40,480 --> 00:10:43,000 Speaker 2: on his hair and controls him. Basically, you're like being 218 00:10:43,120 --> 00:10:45,640 Speaker 2: driven by this thing. You're not really making your own 219 00:10:45,679 --> 00:10:48,760 Speaker 2: decisions and your own best interest anymore. You're being used 220 00:10:48,840 --> 00:10:51,720 Speaker 2: as a vessel for whatever it is that's infected you, 221 00:10:51,800 --> 00:10:52,600 Speaker 2: and it's controlling you. 222 00:10:53,120 --> 00:10:56,360 Speaker 1: Yes, And it's usually not all or nothing. It's usually 223 00:10:56,440 --> 00:10:59,240 Speaker 1: like a very specific Sometimes it can be a feature 224 00:10:59,240 --> 00:11:01,080 Speaker 1: of the way that you look, or a certain set 225 00:11:01,080 --> 00:11:03,640 Speaker 1: of behaviors that change. It's often when we're talking about 226 00:11:03,720 --> 00:11:06,360 Speaker 1: actual cases where parasites are manipulating the behavior of the 227 00:11:06,400 --> 00:11:09,440 Speaker 1: creature they infected, it's actually kind of targeted as opposed 228 00:11:09,440 --> 00:11:12,720 Speaker 1: to like a wholesale shambling along change in everything that 229 00:11:12,760 --> 00:11:15,600 Speaker 1: you do. But yes, you're essentially to some extent under 230 00:11:15,600 --> 00:11:16,920 Speaker 1: the control of another individual. 231 00:11:17,160 --> 00:11:19,960 Speaker 2: On that topic, one of my favorite Halloween costumes ever 232 00:11:20,360 --> 00:11:22,920 Speaker 2: is the rat from Ratitui sitting on somebody's head, and 233 00:11:22,960 --> 00:11:25,920 Speaker 2: this nerdy engineer actually designed one where the rat is 234 00:11:25,960 --> 00:11:29,040 Speaker 2: like moving and controls the person like a puppet or 235 00:11:29,080 --> 00:11:32,360 Speaker 2: really hilarious. That's awesome, But let's not talk about Ratituvi 236 00:11:32,640 --> 00:11:35,880 Speaker 2: and fictional zombies anymore. Let's talk about the actual science. 237 00:11:36,360 --> 00:11:40,640 Speaker 2: So in what way does Toxoplasma gandhii fulfill this category 238 00:11:40,760 --> 00:11:42,760 Speaker 2: of zombie ish kind of takeovers? 239 00:11:42,960 --> 00:11:45,800 Speaker 1: All right, Well, first let's just talk about some background 240 00:11:45,920 --> 00:11:49,160 Speaker 1: on this organism. It is sometimes called the most successful 241 00:11:49,200 --> 00:11:51,800 Speaker 1: parasite on the planet. It can infect just about any 242 00:11:51,880 --> 00:11:55,800 Speaker 1: warm blooded animal, so beluga whales have it, hyenas have it, 243 00:11:55,880 --> 00:11:59,120 Speaker 1: rodents have it, humans have it, birds have it. It 244 00:11:59,160 --> 00:12:00,000 Speaker 1: infects a lot of stuff. 245 00:12:00,320 --> 00:12:02,080 Speaker 2: But what is it? Is it like a little worm? 246 00:12:02,160 --> 00:12:02,920 Speaker 2: Is it a bug? 247 00:12:03,200 --> 00:12:07,160 Speaker 1: It's like a little protozoan parasite, so it's eukaryotic, but 248 00:12:07,240 --> 00:12:09,199 Speaker 1: it's very small, single cells. 249 00:12:09,120 --> 00:12:12,240 Speaker 2: So it's a single cell, has a nucleus. It's basically 250 00:12:12,320 --> 00:12:13,480 Speaker 2: a tiny little critter. 251 00:12:13,679 --> 00:12:15,840 Speaker 1: It is basically a tiny little critter, that's right. And 252 00:12:15,880 --> 00:12:19,480 Speaker 1: so a really quick jargon distinction which might be helpful 253 00:12:19,600 --> 00:12:22,160 Speaker 1: is that, you know, usually when people talk about pathogens, 254 00:12:22,559 --> 00:12:25,520 Speaker 1: they're talking about bacteria and viruses, things that give you 255 00:12:25,559 --> 00:12:28,280 Speaker 1: like the cold and the flu. When they're talking about parasites, 256 00:12:28,280 --> 00:12:31,040 Speaker 1: we're usually talking about eu carryouts. So organisms with like 257 00:12:31,040 --> 00:12:33,640 Speaker 1: a nucleus and a cell wall and stuff, and so 258 00:12:33,880 --> 00:12:38,880 Speaker 1: Toxoplasma gandhii is a parasite, not a pathogen. Not a pathogen, okay, 259 00:12:39,120 --> 00:12:39,400 Speaker 1: And so. 260 00:12:39,400 --> 00:12:42,600 Speaker 2: It infects a huge number of things worldwide, Like do 261 00:12:42,679 --> 00:12:43,840 Speaker 2: you have it? Do I have it? 262 00:12:43,920 --> 00:12:46,880 Speaker 1: So there's probably like a eleven percent chance that either 263 00:12:46,880 --> 00:12:48,040 Speaker 1: one of us happens to have it. 264 00:12:48,240 --> 00:12:49,360 Speaker 2: What that's very high. 265 00:12:49,480 --> 00:12:52,720 Speaker 1: Yeah, in the US, about one in ten people have it. Worldwide, 266 00:12:52,760 --> 00:12:55,280 Speaker 1: about one in three people have it. And there's a 267 00:12:55,400 --> 00:12:56,960 Speaker 1: bunch of different ways that you can get it. And 268 00:12:56,960 --> 00:12:59,000 Speaker 1: this is what makes the parasite so successful and so 269 00:12:59,120 --> 00:13:01,480 Speaker 1: mind blowing is that those parasites have like one or 270 00:13:01,520 --> 00:13:05,000 Speaker 1: two paths to their next host. Toxoplasma gandhi is like 271 00:13:05,120 --> 00:13:08,720 Speaker 1: amazing in its diversity. So let's start with cats. So 272 00:13:08,840 --> 00:13:11,840 Speaker 1: cats are in any different species of cat is a 273 00:13:11,960 --> 00:13:15,000 Speaker 1: very important kind of host for Toxoplasma gandhi. This is 274 00:13:15,000 --> 00:13:17,760 Speaker 1: where the parasites get together and have sex. So it's 275 00:13:17,800 --> 00:13:19,719 Speaker 1: called the definitive host, and I think of it as 276 00:13:19,760 --> 00:13:22,240 Speaker 1: that's definitely where they're going to be having sex. And 277 00:13:22,240 --> 00:13:25,120 Speaker 1: that's how I remember that. You're welcome everyone, and so 278 00:13:25,480 --> 00:13:27,480 Speaker 1: like we can have a whole episode actually on why 279 00:13:27,520 --> 00:13:30,760 Speaker 1: evolutionary biologists think sex is beneficial in general, But it's 280 00:13:30,800 --> 00:13:33,480 Speaker 1: something about mixing genetic material up so that you can 281 00:13:33,520 --> 00:13:35,880 Speaker 1: have some diversity for dealing with things that might be 282 00:13:35,920 --> 00:13:38,480 Speaker 1: happening in the environment or for battling the host immune system. 283 00:13:38,720 --> 00:13:41,800 Speaker 2: And so these guys can only reproduce inside the guts 284 00:13:41,840 --> 00:13:44,880 Speaker 2: of cats, or there's something about that environment that's better 285 00:13:45,000 --> 00:13:46,480 Speaker 2: and they can do it elsewhere also, or is it 286 00:13:46,520 --> 00:13:49,000 Speaker 2: just really only inside cat guts. 287 00:13:49,160 --> 00:13:52,680 Speaker 1: That is only where sexual reproduction happens. So we're going 288 00:13:52,760 --> 00:13:54,840 Speaker 1: to talk a little bit later about places where they 289 00:13:54,880 --> 00:13:57,439 Speaker 1: can do asexual reproduction where you can essentially just think 290 00:13:57,440 --> 00:14:00,200 Speaker 1: they're like copying and pasting the exact same cop be 291 00:14:00,240 --> 00:14:02,280 Speaker 1: over and over and over again. So this is where 292 00:14:02,280 --> 00:14:05,080 Speaker 1: they get to like swap genetic material to hope to 293 00:14:05,200 --> 00:14:07,800 Speaker 1: like stay ahead of the immune system arms race they're 294 00:14:07,840 --> 00:14:10,040 Speaker 1: going through with the other animals that they're trying to infect. 295 00:14:10,440 --> 00:14:13,319 Speaker 2: And what is it about cat guts that's so especially romantic? 296 00:14:13,520 --> 00:14:16,160 Speaker 1: Mm? Wow, that's a great question. 297 00:14:16,440 --> 00:14:18,839 Speaker 2: I mean, it's not hard to imagine you find yourself 298 00:14:18,920 --> 00:14:21,600 Speaker 2: inside a catgut with somebody else that's a dot. One 299 00:14:21,600 --> 00:14:22,480 Speaker 2: thing leads to another. 300 00:14:24,320 --> 00:14:26,840 Speaker 1: So this is a kind of parasite that's called trophically transmitted, 301 00:14:26,840 --> 00:14:29,760 Speaker 1: which means a host that's infected gets eaten by a predator, 302 00:14:29,760 --> 00:14:31,720 Speaker 1: and that's how the parasite makes it to the next host. 303 00:14:32,360 --> 00:14:36,560 Speaker 1: And in different systems, like in trematodes and nematodes and tapeworms, 304 00:14:36,600 --> 00:14:39,440 Speaker 1: like lots of different kinds of parasites have this system, 305 00:14:40,000 --> 00:14:42,800 Speaker 1: and there's usually one species out of all of them 306 00:14:42,800 --> 00:14:45,280 Speaker 1: in there where sexual reproduction happens, and then in the 307 00:14:45,360 --> 00:14:48,880 Speaker 1: other hosts they just kind of replicate asexually. And to 308 00:14:48,880 --> 00:14:51,160 Speaker 1: be honest, I don't know why they're not able to 309 00:14:51,280 --> 00:14:56,120 Speaker 1: flexibly reproduce sexually in all of those hosts. Maybe I'll 310 00:14:56,120 --> 00:14:57,680 Speaker 1: look that up and we'll do a different show on it. 311 00:14:57,760 --> 00:14:59,600 Speaker 1: I don't know why it's just cats. It seems like 312 00:14:59,600 --> 00:15:01,160 Speaker 1: it would be to be able to do it everywhere. 313 00:15:01,200 --> 00:15:04,040 Speaker 1: But the other thing about these cats is after they 314 00:15:04,200 --> 00:15:07,600 Speaker 1: reproduce sexually, they produce a stage called oocysts, which I'm 315 00:15:07,600 --> 00:15:10,080 Speaker 1: just going to call eggs for the rest of the 316 00:15:10,200 --> 00:15:11,880 Speaker 1: conversation because it just makes it easier. 317 00:15:12,080 --> 00:15:13,720 Speaker 2: Please do I didn't want to pronounce that word. 318 00:15:14,000 --> 00:15:16,800 Speaker 1: Yeah, maybe I'm saying it wrong. Who cares. But they 319 00:15:16,840 --> 00:15:19,080 Speaker 1: get pooped out into the environment when the cat poops, 320 00:15:19,600 --> 00:15:21,680 Speaker 1: and that's how the parasite gets back out into the 321 00:15:21,760 --> 00:15:23,720 Speaker 1: environment to infect a bunch of other organisms. 322 00:15:23,800 --> 00:15:25,840 Speaker 2: So don't eat cat poop is the lesson here. 323 00:15:26,040 --> 00:15:28,480 Speaker 1: Well, it's not that simple, right, because cat poop looks 324 00:15:28,520 --> 00:15:30,920 Speaker 1: like cat poop at first, right, that's pretty obvious. But 325 00:15:31,000 --> 00:15:33,600 Speaker 1: over time, cat poop gets like worked into the soil 326 00:15:33,640 --> 00:15:35,920 Speaker 1: and you might not know there's cat poop, and these 327 00:15:36,000 --> 00:15:39,000 Speaker 1: eggs can stay in the environment for a really long time. 328 00:15:39,400 --> 00:15:42,119 Speaker 2: This episode is going to make me like cats less, Kelly. 329 00:15:41,920 --> 00:15:46,880 Speaker 1: Unfortunately, yes, it will outdoor cats in particular less. So 330 00:15:46,960 --> 00:15:50,440 Speaker 1: like if you have a garden and a outdoor cat 331 00:15:50,560 --> 00:15:52,280 Speaker 1: comes by and poops in your garden and you don't 332 00:15:52,320 --> 00:15:54,440 Speaker 1: realize it, and it gets mixed in with the soil, 333 00:15:54,720 --> 00:15:57,120 Speaker 1: then maybe one day you'll pull a vegetable not rinse 334 00:15:57,160 --> 00:15:59,960 Speaker 1: it sufficiently, and then you'll get infected. Or you'll be 335 00:16:00,080 --> 00:16:02,520 Speaker 1: gardening and you get the eggs on your hands and 336 00:16:02,520 --> 00:16:05,200 Speaker 1: you don't realize it. They're like microscopic, and then you 337 00:16:05,240 --> 00:16:07,440 Speaker 1: go to eat something else before washing your hands, and 338 00:16:07,480 --> 00:16:10,560 Speaker 1: you get infected. And this is also how like birds 339 00:16:10,600 --> 00:16:13,760 Speaker 1: and rodents and stuff like that get infected. Once you 340 00:16:13,800 --> 00:16:16,560 Speaker 1: get infected, they get ingested and then they move out 341 00:16:16,600 --> 00:16:18,240 Speaker 1: into your muscles and into your brain. 342 00:16:18,800 --> 00:16:21,240 Speaker 2: What about the blood brain barrier I hear all about. 343 00:16:21,400 --> 00:16:24,200 Speaker 2: Isn't that my vaunted protection for my brain cell. 344 00:16:24,120 --> 00:16:26,560 Speaker 1: Matter doesn't work for this parasite. In fact, the parasite 345 00:16:26,560 --> 00:16:29,800 Speaker 1: goes into your neurons, and that's what makes it actually 346 00:16:29,880 --> 00:16:32,200 Speaker 1: impossible to get rid of once you're infected. If you're 347 00:16:32,200 --> 00:16:34,080 Speaker 1: get infected with this parasite, you're gonna have it. 348 00:16:34,040 --> 00:16:36,400 Speaker 2: Forever, forever. There's no way to get rid of it. 349 00:16:36,560 --> 00:16:39,320 Speaker 1: No, no, because we can't get medication like into your neurons. 350 00:16:39,480 --> 00:16:42,239 Speaker 2: Oh wow, Yeah, this thing is pretty clever and insidious. 351 00:16:42,320 --> 00:16:43,160 Speaker 2: I'm terrified now. 352 00:16:43,320 --> 00:16:45,040 Speaker 1: Most successful parasite on the planet. 353 00:16:45,240 --> 00:16:46,640 Speaker 2: This is appropriate for Halloween. 354 00:16:46,760 --> 00:16:50,960 Speaker 1: Yes, it's some spooky stuff. So when it first gets 355 00:16:51,000 --> 00:16:53,720 Speaker 1: in there, it starts copying and pasting itself like crazy, 356 00:16:54,040 --> 00:16:55,960 Speaker 1: and you feel kind of like you have the flu. 357 00:16:56,040 --> 00:16:57,760 Speaker 1: Some people feel worse than others, Like I have a 358 00:16:57,760 --> 00:17:00,720 Speaker 1: friend who found out he got infected by toxoplusmos by 359 00:17:00,720 --> 00:17:03,800 Speaker 1: bringing in two feral kittens into his house. And when 360 00:17:03,800 --> 00:17:05,560 Speaker 1: he was changing the litter box, he must not have 361 00:17:05,600 --> 00:17:07,600 Speaker 1: like washed his hands well enough, or maybe they like 362 00:17:07,640 --> 00:17:09,920 Speaker 1: you know, scratched around in the litter box and then 363 00:17:10,000 --> 00:17:12,439 Speaker 1: walked on the kitchen table or something like that. And 364 00:17:12,480 --> 00:17:14,480 Speaker 1: so he got infected. His lymph nodes swelled up, and 365 00:17:14,520 --> 00:17:16,359 Speaker 1: he called me and he was like, what's gonna happen 366 00:17:16,359 --> 00:17:16,920 Speaker 1: to me? Now? 367 00:17:18,400 --> 00:17:21,040 Speaker 2: You're a zombie. Forget it. That's why life is over. 368 00:17:23,800 --> 00:17:25,359 Speaker 1: So you feel kind of crummy for a while. 369 00:17:25,800 --> 00:17:28,200 Speaker 2: Wait, but how are these things reproducing in your brain? 370 00:17:28,280 --> 00:17:30,399 Speaker 2: Does that mean they're eating your neurons? Like where are 371 00:17:30,400 --> 00:17:33,520 Speaker 2: they getting raw materials and energy? Like what are they gobbling? 372 00:17:33,880 --> 00:17:37,480 Speaker 1: They are gobbling some nutrients. A lot of parasites at 373 00:17:37,480 --> 00:17:41,600 Speaker 1: this stage are pretty energy efficient, So if they were 374 00:17:41,680 --> 00:17:44,800 Speaker 1: to straight up kill a host while replicating in their brain, 375 00:17:45,200 --> 00:17:47,760 Speaker 1: they probably would not have matured to the stage where 376 00:17:47,800 --> 00:17:51,480 Speaker 1: they can survive transmitting to the next host. So often 377 00:17:51,480 --> 00:17:54,639 Speaker 1: there's like this stage in between when you first infect 378 00:17:54,640 --> 00:17:57,120 Speaker 1: a host and when you can survive if that host 379 00:17:57,160 --> 00:17:59,639 Speaker 1: gets eaten to live in the next host, and so 380 00:17:59,840 --> 00:18:04,320 Speaker 1: you usually parasites are like pretty careful about energy usage, 381 00:18:04,320 --> 00:18:06,439 Speaker 1: so they don't like totally kill the host or like 382 00:18:06,520 --> 00:18:08,119 Speaker 1: cause it to I don't know, fall off a bridge 383 00:18:08,160 --> 00:18:11,840 Speaker 1: or something. But so, yeah, they're being pretty energy efficient, 384 00:18:11,960 --> 00:18:14,240 Speaker 1: but they are replicating. You're feeling kind of grummy. 385 00:18:14,160 --> 00:18:16,080 Speaker 2: And they're active in your brain. Is this how they're 386 00:18:16,160 --> 00:18:17,439 Speaker 2: changing your behavior somehow? 387 00:18:17,600 --> 00:18:20,320 Speaker 1: We don't know, So it does seem like behavioral changes 388 00:18:20,400 --> 00:18:24,560 Speaker 1: have something to do with either changes in dopaminergic activity. 389 00:18:24,680 --> 00:18:27,040 Speaker 1: So dopamine is a neurotransmitter you have in your brain. 390 00:18:27,600 --> 00:18:31,920 Speaker 1: The parasite has genes for I think it's called tyrosine hydroxylase, 391 00:18:32,600 --> 00:18:35,879 Speaker 1: and that's the limiting factor in the production of dopamine. 392 00:18:35,920 --> 00:18:38,320 Speaker 1: So all the other stuff that you need to make 393 00:18:38,359 --> 00:18:41,199 Speaker 1: dopamine is present on the inside of a neuron, but 394 00:18:41,280 --> 00:18:44,240 Speaker 1: when you dump tirosine hydroxylase in there, the rest of 395 00:18:44,240 --> 00:18:46,320 Speaker 1: the reaction just happens and you get dopamine. 396 00:18:46,440 --> 00:18:48,920 Speaker 2: Isn't dopamine good? Don't you want dopamine? Dopamine makes you 397 00:18:48,960 --> 00:18:49,760 Speaker 2: feel good, right. 398 00:18:49,880 --> 00:18:51,600 Speaker 1: I mean, dopamine is good. It makes you feel good, 399 00:18:51,600 --> 00:18:54,040 Speaker 1: but it also controls a bunch of other sorts of behavior. 400 00:18:55,040 --> 00:18:57,679 Speaker 1: Presumably our brains are making something like the right amount, 401 00:18:58,040 --> 00:19:00,720 Speaker 1: and then the parasite is notching the us up, so 402 00:19:00,760 --> 00:19:02,480 Speaker 1: you're making more of it than you would have wanted. 403 00:19:03,040 --> 00:19:05,920 Speaker 2: Now I'm imagining happy zombies, all these people walking around 404 00:19:06,000 --> 00:19:09,480 Speaker 2: mind the grinning. Oh well, they're all infected. Look at them. 405 00:19:09,640 --> 00:19:11,600 Speaker 1: Life is better with tuxo. 406 00:19:13,640 --> 00:19:16,240 Speaker 2: If you meet somebody who's grumpy, you know they're not infected. See, 407 00:19:16,240 --> 00:19:17,040 Speaker 2: And that's the what to tell. 408 00:19:17,359 --> 00:19:20,440 Speaker 1: Yeah, And there have been some experiments where they've given 409 00:19:20,520 --> 00:19:26,840 Speaker 1: rodents drugs for people who have sort of dopaminergic imbalances 410 00:19:26,920 --> 00:19:29,040 Speaker 1: or imbalances of dopamine in their brain, and a lot 411 00:19:29,080 --> 00:19:32,000 Speaker 1: of the weird behaviors that the rodents do sort of 412 00:19:32,080 --> 00:19:34,840 Speaker 1: either get tamped down or go away. So it does 413 00:19:34,880 --> 00:19:38,000 Speaker 1: seem like dopamine has something to do with it. But 414 00:19:38,640 --> 00:19:40,439 Speaker 1: one of the things we've discovered in this field is 415 00:19:40,440 --> 00:19:42,800 Speaker 1: that nothing is ever straightforward, and I mean the field 416 00:19:42,800 --> 00:19:45,680 Speaker 1: of how parasites change the behavior of the creatures that 417 00:19:45,720 --> 00:19:48,840 Speaker 1: they infect, It almost always involves lots of different things. 418 00:19:49,280 --> 00:19:51,520 Speaker 1: And so there's also some evidence that it's just like 419 00:19:51,920 --> 00:19:54,960 Speaker 1: the whole brain has inflammation when the parasites are in there, 420 00:19:54,960 --> 00:19:58,280 Speaker 1: and it might be that generalized inflammation causes things. The 421 00:19:58,320 --> 00:20:01,000 Speaker 1: parasites might also be localizing in certain parts of the 422 00:20:01,000 --> 00:20:04,160 Speaker 1: brain and making behaviors weird. It might also have something 423 00:20:04,160 --> 00:20:06,359 Speaker 1: to do with argentine vasa pressin or something to do 424 00:20:06,400 --> 00:20:10,240 Speaker 1: with testosterone, So you might notice that in the outline 425 00:20:10,440 --> 00:20:12,960 Speaker 1: I hadn't put anything about mechanisms because it's just like 426 00:20:13,320 --> 00:20:15,840 Speaker 1: such a mess right now. There's a lot of different 427 00:20:15,840 --> 00:20:16,399 Speaker 1: things it could be. 428 00:20:16,800 --> 00:20:20,680 Speaker 2: So it's active in the brain. It probably changes brain chemistry. 429 00:20:20,920 --> 00:20:24,080 Speaker 2: We don't understand completely the mechanism for how it's doing that. 430 00:20:24,560 --> 00:20:27,439 Speaker 2: Are there behaviors though in people that we can identify 431 00:20:28,040 --> 00:20:30,560 Speaker 2: as due to this impact, even if we don't have 432 00:20:30,680 --> 00:20:33,640 Speaker 2: all these little pieces that connect the dots. Are there 433 00:20:33,800 --> 00:20:37,040 Speaker 2: characteristic ways that it changes people's behavior? Or is it 434 00:20:37,080 --> 00:20:40,040 Speaker 2: mostly in cats that we notice the change in behaviors? 435 00:20:40,600 --> 00:20:44,680 Speaker 1: So cats don't usually show behavioral changes, So the parasites 436 00:20:44,720 --> 00:20:47,840 Speaker 1: replicating in the gut, we haven't associated any behavioral changes 437 00:20:48,000 --> 00:20:50,840 Speaker 1: with that. Humans are interesting. So we're jumping ahead a 438 00:20:50,880 --> 00:20:52,879 Speaker 1: little and that's okay. But so usually what happens with 439 00:20:53,000 --> 00:20:55,600 Speaker 1: like a rodent that gets infected is you see some 440 00:20:55,680 --> 00:20:58,600 Speaker 1: behavioral changes, and then when the cat eats the muscles 441 00:20:58,600 --> 00:21:00,800 Speaker 1: of that rodent, the parasite gets back to the cat. 442 00:21:01,359 --> 00:21:05,840 Speaker 1: So usually manipulation is supposed to help with some transmission 443 00:21:05,880 --> 00:21:08,639 Speaker 1: goal for the parasite. So when you're in a rodent, 444 00:21:08,800 --> 00:21:10,320 Speaker 1: the goal is to get it eaten by a cat, 445 00:21:10,720 --> 00:21:14,480 Speaker 1: but with humans, we don't usually get eaten by cats. 446 00:21:14,960 --> 00:21:16,600 Speaker 2: Sometimes we do big cats. 447 00:21:16,680 --> 00:21:20,439 Speaker 1: Yeah, yeah, sometimes big cats, but like it's pretty rare 448 00:21:20,640 --> 00:21:23,800 Speaker 1: and so we are kind of a dead end from 449 00:21:23,800 --> 00:21:26,679 Speaker 1: the perspective of getting back to cats. There are some 450 00:21:26,760 --> 00:21:29,120 Speaker 1: other ways that we can pass it. For example, men 451 00:21:29,160 --> 00:21:31,760 Speaker 1: can pass it to women during intercourse. We think when 452 00:21:31,760 --> 00:21:33,359 Speaker 1: I think about that, I'm like, ah, I'm so glad 453 00:21:33,400 --> 00:21:37,960 Speaker 1: I'm not dating anymore anyway, sorry everyone. Moms can pass 454 00:21:38,000 --> 00:21:41,159 Speaker 1: it to their children. It's called trans placental, so it 455 00:21:41,280 --> 00:21:43,480 Speaker 1: goes from the mom to the baby. So if mom 456 00:21:43,520 --> 00:21:45,800 Speaker 1: gets infected for the first time ever when she's pregnant, 457 00:21:45,840 --> 00:21:48,280 Speaker 1: it can pass into the fetus. Or if mom gets 458 00:21:48,320 --> 00:21:51,159 Speaker 1: infected for the first time when she's breastfeeding, I can 459 00:21:51,200 --> 00:21:54,199 Speaker 1: do trans mammory transmission, which means it goes across the 460 00:21:54,240 --> 00:21:57,240 Speaker 1: memory lands during breastfeeding into the baby. It still has 461 00:21:57,280 --> 00:21:59,479 Speaker 1: some options to get from host to host, but we're 462 00:21:59,520 --> 00:22:03,280 Speaker 1: probably not back to cats. But it is associated with 463 00:22:03,359 --> 00:22:06,960 Speaker 1: behavioral changes in humans. In humans, right after that stage 464 00:22:06,960 --> 00:22:09,200 Speaker 1: where it's replicating like crazy, it kind of slows down. 465 00:22:09,280 --> 00:22:12,800 Speaker 1: It slows its replication. But there's still some evidence that 466 00:22:12,840 --> 00:22:15,520 Speaker 1: it changes human behaviors. And the interesting thing about like 467 00:22:15,560 --> 00:22:18,440 Speaker 1: the study of this is there's this guy named Yaroslav Flager. 468 00:22:19,119 --> 00:22:23,000 Speaker 1: He's a Czech scientist, and apparently he was like, you know, 469 00:22:24,000 --> 00:22:25,919 Speaker 1: I do a lot of behaviors that really aren't in 470 00:22:25,960 --> 00:22:28,919 Speaker 1: my own interest, and I just kind of do a 471 00:22:28,920 --> 00:22:31,240 Speaker 1: bunch of weird stuff. I wonder if that, like brain 472 00:22:31,280 --> 00:22:35,399 Speaker 1: infecting parasite is to blame. Always makes me wonder like 473 00:22:35,480 --> 00:22:37,840 Speaker 1: is he just looking for excuses for like, well, I'm 474 00:22:37,840 --> 00:22:40,320 Speaker 1: a jerk, but it's not my fault I'm infected by 475 00:22:40,359 --> 00:22:41,280 Speaker 1: this parasite. 476 00:22:41,520 --> 00:22:43,200 Speaker 2: All right, I want to hear a lot more about 477 00:22:43,280 --> 00:22:47,119 Speaker 2: Yaroslav and his zombie research and how he wrote zombies 478 00:22:47,160 --> 00:22:49,960 Speaker 2: into his proposals to get big money from science foundations. 479 00:22:50,280 --> 00:22:52,800 Speaker 2: But first we have to take a quick break. So 480 00:22:52,920 --> 00:22:55,200 Speaker 2: go clean up your cat litterbox to keep your family 481 00:22:55,240 --> 00:23:14,080 Speaker 2: safe and come right back. All right, we're back, and 482 00:23:14,119 --> 00:23:18,359 Speaker 2: we're talking about the science of Halloween, more specifically zombies. 483 00:23:18,680 --> 00:23:21,720 Speaker 2: What are they in biology? Are they really like zombie behaviors? 484 00:23:22,080 --> 00:23:25,720 Speaker 2: And is toxoplasma GANDHII All it's been cracked up to 485 00:23:25,760 --> 00:23:28,320 Speaker 2: be in the popular science literature. And you were telling 486 00:23:28,400 --> 00:23:31,199 Speaker 2: us about a guy who's been doing research into the 487 00:23:31,280 --> 00:23:34,960 Speaker 2: impact on humans of this little bug. Tell us what 488 00:23:35,000 --> 00:23:36,080 Speaker 2: he did and what he learned. 489 00:23:36,480 --> 00:23:38,800 Speaker 1: Well, so what he was doing was he would draw 490 00:23:38,920 --> 00:23:41,200 Speaker 1: blood from a group of people. And when you look 491 00:23:41,240 --> 00:23:44,480 Speaker 1: at people's blood, if you've been infected by this parasite, 492 00:23:44,760 --> 00:23:48,240 Speaker 1: which you'll have forever, your immune system mounts a response 493 00:23:48,280 --> 00:23:51,040 Speaker 1: to it, and you always will have that signature of 494 00:23:51,040 --> 00:23:54,520 Speaker 1: the immune system response in your blood Forevermore So, if 495 00:23:54,560 --> 00:23:57,000 Speaker 1: you draw blood, you can look at the blood and say, Okay, 496 00:23:57,080 --> 00:24:00,399 Speaker 1: this person was definitely infected by the parasite at some point. 497 00:24:00,600 --> 00:24:01,960 Speaker 1: You don't know when, but you know that at some 498 00:24:02,000 --> 00:24:04,119 Speaker 1: point they were infected, and the parasite is probably just 499 00:24:04,200 --> 00:24:05,280 Speaker 1: chilling out in the brain. 500 00:24:05,080 --> 00:24:07,719 Speaker 2: Now, okay, Because if you have it, you have it forever, right, 501 00:24:07,760 --> 00:24:10,320 Speaker 2: So you're infected at some point, you're still infected, that's right. 502 00:24:10,480 --> 00:24:12,000 Speaker 2: This is just a way to tell who's got it 503 00:24:12,040 --> 00:24:12,920 Speaker 2: and who doesn't have it. 504 00:24:13,160 --> 00:24:15,439 Speaker 1: Yep, right, So by drawing blood, you don't need to 505 00:24:15,520 --> 00:24:18,359 Speaker 1: like invasively dissect someone's brain to know if they've got it. 506 00:24:18,400 --> 00:24:20,359 Speaker 1: You can just draw blood, and that way you know 507 00:24:20,359 --> 00:24:22,879 Speaker 1: who's got it and who doesn't, and then you can 508 00:24:22,920 --> 00:24:26,200 Speaker 1: give people personality tests, and you can look for correlations 509 00:24:26,240 --> 00:24:29,200 Speaker 1: between the answers that they give on those personality tests 510 00:24:29,560 --> 00:24:32,160 Speaker 1: and their infection status. Does that make sense? 511 00:24:32,600 --> 00:24:35,439 Speaker 2: It does, But these correlational studies are really hard to interpret, right, 512 00:24:35,560 --> 00:24:38,320 Speaker 2: Like you might just be selecting for cat people versus 513 00:24:38,359 --> 00:24:41,800 Speaker 2: dog people, and there's a whole lot of potential confounding 514 00:24:41,840 --> 00:24:42,680 Speaker 2: variables there, right. 515 00:24:43,160 --> 00:24:46,120 Speaker 1: Amen, So we have reached the first of my main 516 00:24:46,280 --> 00:24:49,399 Speaker 1: problems with this field. It could be that there's some 517 00:24:49,560 --> 00:24:54,320 Speaker 1: third behavior that predisposes people to getting infected, and then 518 00:24:54,320 --> 00:24:57,000 Speaker 1: when you give them this personality test which you're really measuring, 519 00:24:57,119 --> 00:24:58,720 Speaker 1: is that they have this behavior to begin with, and 520 00:24:58,720 --> 00:25:01,760 Speaker 1: that's what got them infected necessarily that the parasite gave 521 00:25:01,800 --> 00:25:02,520 Speaker 1: them the behavior. 522 00:25:02,880 --> 00:25:05,440 Speaker 2: So what you really need is some good control where 523 00:25:05,480 --> 00:25:08,040 Speaker 2: you take a person, you clone them, then you infect them, 524 00:25:08,400 --> 00:25:11,680 Speaker 2: then you create a perfectly identical world for them to experience, 525 00:25:12,119 --> 00:25:14,160 Speaker 2: and then you see their changes in behavior. Why don't 526 00:25:14,160 --> 00:25:17,120 Speaker 2: people just do that experiment? Kelly? Biology is so easy, that. 527 00:25:17,160 --> 00:25:20,480 Speaker 1: Sounds so ethical, it does, But maybe that's why we 528 00:25:20,560 --> 00:25:21,040 Speaker 1: have it yet. 529 00:25:22,560 --> 00:25:25,760 Speaker 2: See, I just don't have those scientific bones. Because particles 530 00:25:26,000 --> 00:25:29,119 Speaker 2: don't have consent forms, they don't have rights. We annihilate 531 00:25:29,160 --> 00:25:31,439 Speaker 2: them all the time. No big deal. They don't have 532 00:25:31,440 --> 00:25:31,960 Speaker 2: a union. 533 00:25:32,160 --> 00:25:35,800 Speaker 1: It's great, no IRB committees. I'm jealous. I mean, there 534 00:25:35,840 --> 00:25:37,359 Speaker 1: are some ways to get at this, Like if you 535 00:25:37,400 --> 00:25:40,760 Speaker 1: do cohort studies where you follow individuals from the beginning 536 00:25:40,800 --> 00:25:43,439 Speaker 1: of their lives and you regularly measure their behavior and 537 00:25:43,480 --> 00:25:46,400 Speaker 1: you regularly measure their infection status, then maybe you can 538 00:25:46,480 --> 00:25:51,640 Speaker 1: start to disentangle what parasites changed after infection. And these 539 00:25:51,640 --> 00:25:55,359 Speaker 1: cohort studies are really expensive, really time consuming. But without 540 00:25:55,359 --> 00:25:58,160 Speaker 1: doing controlled infections, that's probably the best we can do. 541 00:25:58,640 --> 00:26:00,800 Speaker 1: But there's not a lot of studies that have done all. 542 00:26:00,920 --> 00:26:03,800 Speaker 2: Right, so we've qualified this already by saying we don't 543 00:26:03,800 --> 00:26:05,960 Speaker 2: know what we can learn from these studies. But tell 544 00:26:06,040 --> 00:26:07,600 Speaker 2: us what do the studies reveal? 545 00:26:07,920 --> 00:26:10,440 Speaker 1: Okay, So here is the stuff that's sort of exciting 546 00:26:10,440 --> 00:26:13,359 Speaker 1: to talk about over tea or over beer or something. Okay. 547 00:26:13,440 --> 00:26:16,760 Speaker 1: So people who are infected tend to seek novelty less, 548 00:26:16,760 --> 00:26:18,399 Speaker 1: so they're less likely to want to go out and 549 00:26:18,440 --> 00:26:21,439 Speaker 1: try new things. Don't know why. There's a lot of 550 00:26:21,640 --> 00:26:24,639 Speaker 1: sex specific differences. So women who are infected tend to 551 00:26:24,640 --> 00:26:27,720 Speaker 1: be less suspicious, and men who are infected tend to 552 00:26:27,720 --> 00:26:30,000 Speaker 1: be more suspicious. 553 00:26:29,680 --> 00:26:31,800 Speaker 2: And are men who are infected less likely to wear 554 00:26:31,800 --> 00:26:32,760 Speaker 2: Halloween costumes? 555 00:26:33,160 --> 00:26:37,159 Speaker 1: Oh, it depends on how novel those costumes are. You know, 556 00:26:37,960 --> 00:26:39,760 Speaker 1: if they're comfortable with it, maybe they're. 557 00:26:39,600 --> 00:26:43,080 Speaker 2: Fine, non novel, non suspicious costumes. That's your pitch to 558 00:26:43,160 --> 00:26:43,880 Speaker 2: zact next time. 559 00:26:44,040 --> 00:26:45,640 Speaker 1: Well, I don't know if he's infected or not. It's 560 00:26:45,640 --> 00:26:47,360 Speaker 1: hard to say. He does work in the garden a lot. 561 00:26:47,640 --> 00:26:50,360 Speaker 2: There you go. See, I'm starting to ask questions. 562 00:26:49,920 --> 00:26:54,240 Speaker 1: Here you should. And then women who are infected tend 563 00:26:54,280 --> 00:26:57,440 Speaker 1: to be more warm and like caring, and men tend 564 00:26:57,480 --> 00:27:01,720 Speaker 1: to be either less warm or unchanged by the parasite. 565 00:27:01,920 --> 00:27:02,440 Speaker 2: Interesting. 566 00:27:02,920 --> 00:27:04,760 Speaker 1: I get a lot of questions about like does this 567 00:27:04,800 --> 00:27:09,000 Speaker 1: parasite turn people into crazy cat ladies? But actually the 568 00:27:09,119 --> 00:27:12,160 Speaker 1: evidence is that women who are infected tend to think 569 00:27:12,200 --> 00:27:14,480 Speaker 1: cat urine smells less good. They're like, oh, this is 570 00:27:14,480 --> 00:27:15,520 Speaker 1: an unpleasant smell. 571 00:27:15,880 --> 00:27:18,240 Speaker 2: Cat Urine already smells zero good. How can you be 572 00:27:18,320 --> 00:27:19,680 Speaker 2: hit less good than zero? 573 00:27:20,040 --> 00:27:24,040 Speaker 1: See, there's various levels of repulsion, okay, and infected women 574 00:27:24,119 --> 00:27:28,920 Speaker 1: are more repulsed, but infected men relative to uninfected men, 575 00:27:29,160 --> 00:27:32,520 Speaker 1: rate the smell of cat urine as being more pleasant. 576 00:27:32,880 --> 00:27:37,920 Speaker 1: What so maybe crazy cat men. I don't know. There 577 00:27:37,920 --> 00:27:41,320 Speaker 1: are some quantifiable effects at the country level. Also, a 578 00:27:41,359 --> 00:27:45,280 Speaker 1: friend of mine looked at personality aggregate scores by countries 579 00:27:45,320 --> 00:27:47,400 Speaker 1: and also the percent of people in a country who 580 00:27:47,400 --> 00:27:49,640 Speaker 1: are infected, and we tend to have like pretty good 581 00:27:49,680 --> 00:27:52,600 Speaker 1: data on percents because often when women are pregnant, they'll 582 00:27:52,600 --> 00:27:54,600 Speaker 1: get a test to see if they have the parasite. 583 00:27:54,880 --> 00:27:58,080 Speaker 1: Because if you have the parasite already, your immune system 584 00:27:58,160 --> 00:27:59,920 Speaker 1: probably has it in check and it's not going to 585 00:28:00,040 --> 00:28:03,040 Speaker 1: transmit to your fetus. But if you get infected, well 586 00:28:03,080 --> 00:28:06,920 Speaker 1: you're pregnant, it can transmit. So if you are pregnant 587 00:28:06,920 --> 00:28:09,040 Speaker 1: and you're not already infected, then you're often told like, 588 00:28:09,119 --> 00:28:11,720 Speaker 1: don't change any litter boxes. Have your partner do that. 589 00:28:12,040 --> 00:28:14,560 Speaker 1: But anyway, so we've got these country level scores and 590 00:28:14,720 --> 00:28:18,000 Speaker 1: countries with more toxoplasma gandhi I tend to be more neurotic. 591 00:28:18,240 --> 00:28:19,800 Speaker 2: Which countries are more neurotic? 592 00:28:19,880 --> 00:28:22,520 Speaker 1: Come on, oh all right, let's look up Lafferty's paper 593 00:28:22,560 --> 00:28:22,960 Speaker 1: real quick. 594 00:28:25,119 --> 00:28:27,840 Speaker 2: I want to slander some nations here. I'm gonna guess 595 00:28:28,359 --> 00:28:32,320 Speaker 2: more Pacific, more tropical, more equatorial, is more laid back. 596 00:28:32,760 --> 00:28:35,360 Speaker 2: And more northern colder, it's going to be more neurotic. 597 00:28:35,400 --> 00:28:38,440 Speaker 2: That's going to be my totally uninformed Basian prior on 598 00:28:38,480 --> 00:28:38,959 Speaker 2: this one. 599 00:28:39,160 --> 00:28:41,840 Speaker 1: So this paper was some two thousand and six, so 600 00:28:41,920 --> 00:28:46,040 Speaker 1: it looks like Yugoslavia, according to this study, had sixty 601 00:28:46,080 --> 00:28:50,760 Speaker 1: seven percent prevalence, and then Hungary had fifty nine percent. 602 00:28:50,840 --> 00:28:54,760 Speaker 1: Brazil was it sixty seven percent. So those are some 603 00:28:54,840 --> 00:28:57,440 Speaker 1: of the top countries. That doesn't necessarily mean that the 604 00:28:57,480 --> 00:29:00,520 Speaker 1: most neurotic. It's like an association, there's some move along 605 00:29:00,520 --> 00:29:02,800 Speaker 1: that correlation line, but those are some of the more 606 00:29:02,800 --> 00:29:05,680 Speaker 1: neurotic countries, some of the countries with the higher prevalence 607 00:29:05,680 --> 00:29:09,720 Speaker 1: of the parasite countries with the lowest prevalence. I'm seeing 608 00:29:09,880 --> 00:29:15,240 Speaker 1: Finland is at like sixteen percent, so is Israel. Norway 609 00:29:15,320 --> 00:29:18,000 Speaker 1: is at nine percent. South Korea is only at four percent. 610 00:29:18,440 --> 00:29:21,120 Speaker 2: That's basically the opposite of what I predicted. I predicted 611 00:29:21,200 --> 00:29:23,840 Speaker 2: like Norway and Finland would be very neurotic and Brazil 612 00:29:23,840 --> 00:29:24,680 Speaker 2: would be very chill. 613 00:29:24,800 --> 00:29:27,479 Speaker 1: So why would nor would be very neurotic? They were 614 00:29:27,520 --> 00:29:29,760 Speaker 1: pretty laid back when I was there. They take weekends 615 00:29:29,760 --> 00:29:32,040 Speaker 1: off in Norway, they were serious about that. They take 616 00:29:32,080 --> 00:29:33,080 Speaker 1: August off Man. 617 00:29:33,280 --> 00:29:35,640 Speaker 2: Yeah, they are like the richest nation on earth because 618 00:29:35,680 --> 00:29:38,560 Speaker 2: of their oil wealth, so maybe that helps. Maybe their 619 00:29:38,560 --> 00:29:41,440 Speaker 2: toxoplasma GANDHII infected them and told them where the oil 620 00:29:41,520 --> 00:29:43,480 Speaker 2: was going to be. Oh wait, no, you're saying they're 621 00:29:43,520 --> 00:29:45,400 Speaker 2: less infected, they're more infected. I'm confused. 622 00:29:45,520 --> 00:29:50,320 Speaker 1: They're less infected, so probably statistically they would be expected 623 00:29:50,320 --> 00:29:51,200 Speaker 1: to be less neurotic. 624 00:29:51,360 --> 00:29:53,400 Speaker 2: All right, So most of the zombies on Earth you're 625 00:29:53,400 --> 00:29:56,520 Speaker 2: saying are in Brazil, Hungary and the former Yugoslavia. 626 00:29:57,160 --> 00:30:00,360 Speaker 1: Yes, that's probably the right conclusion. 627 00:30:00,000 --> 00:30:04,280 Speaker 2: And maybe apology to all of our listeners in those countries. 628 00:30:04,560 --> 00:30:07,320 Speaker 1: That's right. So there's also a bunch of other correlations. 629 00:30:07,320 --> 00:30:09,600 Speaker 1: We probably don't want to spend too long on this 630 00:30:09,680 --> 00:30:11,560 Speaker 1: because I'd also like to get to the rodents real 631 00:30:11,640 --> 00:30:13,720 Speaker 1: quick and still leave you some time to talk about ghosts. 632 00:30:13,800 --> 00:30:17,880 Speaker 1: But there are some worrying things. There's like association with suicides, 633 00:30:17,960 --> 00:30:21,200 Speaker 1: association with schizophrenia, association with being more likely to be 634 00:30:21,240 --> 00:30:24,000 Speaker 1: in a traffic accident, which we think is maybe because 635 00:30:24,000 --> 00:30:26,960 Speaker 1: of a bit of a delay in reaction times. So 636 00:30:27,240 --> 00:30:29,720 Speaker 1: it's not like they're driving from one side of the 637 00:30:29,800 --> 00:30:32,040 Speaker 1: road to another like crazy people. Acting like they're drunk. 638 00:30:32,080 --> 00:30:33,560 Speaker 1: It's just that if they're in a moment where they 639 00:30:33,560 --> 00:30:35,800 Speaker 1: need to make a split decision, they're a little slower 640 00:30:35,840 --> 00:30:38,280 Speaker 1: to respond. And we don't know for sure that that's 641 00:30:38,280 --> 00:30:40,200 Speaker 1: what it is, but that's one of the working hypotheses 642 00:30:40,280 --> 00:30:40,640 Speaker 1: right now. 643 00:30:40,760 --> 00:30:44,400 Speaker 2: All right, So we see these correlations between infection and behavior. 644 00:30:44,440 --> 00:30:46,680 Speaker 2: We don't know the calls of mechanism. We don't really 645 00:30:46,760 --> 00:30:50,280 Speaker 2: understand how it works from like a micro biochemical point 646 00:30:50,320 --> 00:30:53,680 Speaker 2: of view. Do we understand things better in other creatures 647 00:30:53,720 --> 00:30:56,720 Speaker 2: where we can actually do experiments like cats and rodents 648 00:30:56,760 --> 00:30:58,800 Speaker 2: that life cycle, like, does it change the behavior of 649 00:30:58,840 --> 00:31:02,120 Speaker 2: cats and rodents in some way that benefits the parasite? 650 00:31:02,360 --> 00:31:06,120 Speaker 1: Well, for both humans and rodents, there are studies that 651 00:31:06,160 --> 00:31:08,120 Speaker 1: don't always say the same thing. So you collect to 652 00:31:08,120 --> 00:31:10,320 Speaker 1: the same data in two different studies and sometimes you 653 00:31:10,360 --> 00:31:12,800 Speaker 1: find an effect and sometimes you don't. That's complicating. 654 00:31:12,960 --> 00:31:13,760 Speaker 2: Science is hard. 655 00:31:13,960 --> 00:31:16,680 Speaker 1: Science is so hard. But at least with rodents you 656 00:31:16,720 --> 00:31:19,360 Speaker 1: can do the controlled infections that you can't do in humans, 657 00:31:19,640 --> 00:31:22,120 Speaker 1: so you can look at how behavior changes following infection. 658 00:31:22,440 --> 00:31:25,160 Speaker 1: And one of the most exciting things about rodents studies 659 00:31:25,360 --> 00:31:28,960 Speaker 1: is this thing that's become called fatal feline attraction. 660 00:31:29,600 --> 00:31:31,360 Speaker 2: I want to see that movie. That sounds great. 661 00:31:31,760 --> 00:31:33,880 Speaker 1: It is, Yeah, it's such an interesting idea. So the 662 00:31:33,920 --> 00:31:37,280 Speaker 1: idea is that rodents, when they're not infected, they smell 663 00:31:37,320 --> 00:31:39,640 Speaker 1: cat urine, they freak out. They avoid the area because 664 00:31:39,640 --> 00:31:41,640 Speaker 1: that's the smell of a predator. They don't want to 665 00:31:41,640 --> 00:31:43,760 Speaker 1: get eaten. So if they can smell that a cat 666 00:31:43,800 --> 00:31:45,680 Speaker 1: has been around, they don't want to be in that area. 667 00:31:46,160 --> 00:31:51,040 Speaker 1: Makes sense, whereas rodents that are infected tend to spend 668 00:31:51,120 --> 00:31:54,040 Speaker 1: more time in those areas, almost as though they're attracted 669 00:31:54,080 --> 00:31:57,200 Speaker 1: to those areas. And there were some studies done that 670 00:31:57,240 --> 00:31:59,680 Speaker 1: show that, like you know, when you have an uninfected rodent, 671 00:31:59,720 --> 00:32:02,120 Speaker 1: the part their brain associated with fear kind of lights 672 00:32:02,200 --> 00:32:05,320 Speaker 1: up when they smell cat urine, But when you have 673 00:32:05,600 --> 00:32:09,520 Speaker 1: infected animals, the part of their brain associated with getting 674 00:32:09,560 --> 00:32:12,320 Speaker 1: excited about a potential partner lights up. So it's almost 675 00:32:12,360 --> 00:32:16,440 Speaker 1: like the parasite is changing this response to this chemical 676 00:32:16,480 --> 00:32:20,440 Speaker 1: cue from absolutely petrifying to like something that's maybe kind 677 00:32:20,440 --> 00:32:26,080 Speaker 1: of sexy. But two problems here. One, you don't always 678 00:32:26,080 --> 00:32:29,479 Speaker 1: see this effect. Sometimes you do the controlled infections and 679 00:32:29,600 --> 00:32:32,040 Speaker 1: you don't see this attraction to the smell of cat urine, 680 00:32:32,320 --> 00:32:34,880 Speaker 1: and it looks like maybe it differs depending on like, 681 00:32:34,920 --> 00:32:37,680 Speaker 1: are you using an inbred rodent strain that's been living 682 00:32:37,720 --> 00:32:39,680 Speaker 1: in the lab for a really long time. Are you 683 00:32:39,720 --> 00:32:42,880 Speaker 1: looking at males or females? How long has the rodent 684 00:32:42,920 --> 00:32:47,200 Speaker 1: been infected? What strain of Toxoplasma gandhi are you using? 685 00:32:47,360 --> 00:32:50,480 Speaker 1: And so if you read the popular literature, they're like, oh, man, 686 00:32:50,600 --> 00:32:54,280 Speaker 1: rodents who are infected, they're attracted to cat urine. But 687 00:32:54,360 --> 00:32:55,720 Speaker 1: at the end of the day, the answer is much 688 00:32:55,760 --> 00:32:58,520 Speaker 1: more complicated. Sometimes we see the effects, sometimes we don't. 689 00:32:58,960 --> 00:33:00,720 Speaker 1: At the moment, we don't really understand why. 690 00:33:00,960 --> 00:33:03,600 Speaker 2: And even if the story we're true, the explanation would 691 00:33:03,600 --> 00:33:06,640 Speaker 2: be that the parasite wants the rat to get eaten 692 00:33:06,680 --> 00:33:09,040 Speaker 2: by a cat because it wants to get back into 693 00:33:09,080 --> 00:33:11,760 Speaker 2: the cat's gut for more reproductive. 694 00:33:11,240 --> 00:33:15,520 Speaker 1: Sexy time exactly. And then here's another problem. So I 695 00:33:15,640 --> 00:33:17,840 Speaker 1: was talking to one of the people who did the 696 00:33:17,840 --> 00:33:21,840 Speaker 1: original fatal feline attraction study, and I asked, when are 697 00:33:21,880 --> 00:33:24,920 Speaker 1: we going to see a study where rodents get infected, 698 00:33:25,520 --> 00:33:27,760 Speaker 1: we confirm that they're now more attracted to the smell 699 00:33:27,800 --> 00:33:30,520 Speaker 1: of cat urine, and then we release them into an 700 00:33:30,600 --> 00:33:33,040 Speaker 1: environment with cats and we see if that actually gets 701 00:33:33,040 --> 00:33:35,080 Speaker 1: them eaten, because right now we've got this story that 702 00:33:35,160 --> 00:33:37,960 Speaker 1: sounds super convincing, but we haven't actually shown it gets 703 00:33:37,960 --> 00:33:41,640 Speaker 1: them eaten. And her response was like, look, I would 704 00:33:41,640 --> 00:33:44,480 Speaker 1: never feel comfortable doing that to rodents. That's mean to 705 00:33:44,520 --> 00:33:47,680 Speaker 1: the rodents. We don't want to be infecting cats. I 706 00:33:47,720 --> 00:33:49,520 Speaker 1: don't want to have anything to do with that study. 707 00:33:50,080 --> 00:33:51,720 Speaker 1: And I think it would be hard to get past 708 00:33:51,960 --> 00:33:55,200 Speaker 1: an institutional Animal Care and Use Committee, which is the 709 00:33:55,320 --> 00:33:57,480 Speaker 1: organization that has to approve all of the experiments that 710 00:33:57,480 --> 00:34:01,200 Speaker 1: people at universities do. And so we don't actually have 711 00:34:01,920 --> 00:34:04,920 Speaker 1: that study. We don't actually have that connection. And you 712 00:34:04,920 --> 00:34:07,760 Speaker 1: can imagine that, you know, rodents who spend a lot 713 00:34:07,800 --> 00:34:10,480 Speaker 1: of time really examining an area where there's a cue 714 00:34:10,520 --> 00:34:13,440 Speaker 1: about a predator get a really good sense for like, Okay, 715 00:34:13,680 --> 00:34:15,759 Speaker 1: here's where the predator seems to go. Here are the 716 00:34:15,840 --> 00:34:19,399 Speaker 1: hiding places in the area. Maybe they're just like really 717 00:34:19,480 --> 00:34:22,279 Speaker 1: understanding the area, and when a cat shows up, they 718 00:34:22,320 --> 00:34:24,000 Speaker 1: know how to get out of there better then another 719 00:34:24,080 --> 00:34:26,040 Speaker 1: rodent who happens to be passing through. And I don't know, 720 00:34:26,080 --> 00:34:27,879 Speaker 1: I'm just making up stories now too, but The point 721 00:34:27,920 --> 00:34:29,200 Speaker 1: is we're all just making up stories. 722 00:34:29,719 --> 00:34:32,080 Speaker 2: The point is you're saying it's not so simple as 723 00:34:32,200 --> 00:34:34,640 Speaker 2: just rats who are attracted to cat here and get 724 00:34:34,640 --> 00:34:37,239 Speaker 2: eaten more. You're saying you could plausibly come up with 725 00:34:37,280 --> 00:34:40,160 Speaker 2: a scenario where it actually prevents them from getting eaten more, 726 00:34:40,160 --> 00:34:42,279 Speaker 2: and we actually need to go out and measure this 727 00:34:42,600 --> 00:34:44,879 Speaker 2: in the world. I think that's a huge lesson, right, 728 00:34:44,920 --> 00:34:47,600 Speaker 2: Like we're always attracted to these simple stories and science 729 00:34:47,600 --> 00:34:50,640 Speaker 2: and all of our science are stories. But just because 730 00:34:50,640 --> 00:34:52,520 Speaker 2: the story makes sense to us, doesn't mean it's the 731 00:34:52,560 --> 00:34:54,520 Speaker 2: way the world works. Right. We have to always go 732 00:34:54,560 --> 00:34:57,880 Speaker 2: out and do experiments and make measurements because the universe 733 00:34:57,960 --> 00:35:01,359 Speaker 2: is filled with surprises. Usually it's the kind of stuff 734 00:35:01,360 --> 00:35:03,760 Speaker 2: we're so certain about that turns out to be wrong. 735 00:35:03,840 --> 00:35:05,560 Speaker 1: And there have been some examples where we had this 736 00:35:05,640 --> 00:35:07,759 Speaker 1: great story and we thought it made sense, and then 737 00:35:07,800 --> 00:35:09,840 Speaker 1: when we did dig in a little bit more, it 738 00:35:09,920 --> 00:35:12,520 Speaker 1: fell apart. The behavior was not benefiting the parasite in 739 00:35:12,560 --> 00:35:14,920 Speaker 1: any way. So you do have to test these stories. 740 00:35:14,920 --> 00:35:16,399 Speaker 1: And I just want to tell you about one more 741 00:35:16,440 --> 00:35:19,160 Speaker 1: study that I think is the closest we've gotten so 742 00:35:19,360 --> 00:35:22,279 Speaker 1: far to trying to provide support for this, and this 743 00:35:22,320 --> 00:35:25,080 Speaker 1: is an indirect study that was done in Switzerland. So essentially, 744 00:35:25,200 --> 00:35:28,040 Speaker 1: there was this survey where people were asked like, okay, 745 00:35:28,400 --> 00:35:30,919 Speaker 1: when your cat catches something and they bring it home 746 00:35:30,920 --> 00:35:32,560 Speaker 1: to you, and they like, put it on your doorstep, 747 00:35:32,880 --> 00:35:35,359 Speaker 1: put it in a plastic bag, and bring it to us. 748 00:35:35,840 --> 00:35:38,600 Speaker 1: So they got this big collection of rodents that had 749 00:35:38,640 --> 00:35:42,560 Speaker 1: been killed by cats, and then they took blood from 750 00:35:42,600 --> 00:35:44,239 Speaker 1: all of these rodents and they looked to see what 751 00:35:44,400 --> 00:35:47,440 Speaker 1: percent of them were infected by the parasite, Okay, and 752 00:35:47,480 --> 00:35:51,720 Speaker 1: what they found was that for European water bowls, eleven 753 00:35:51,760 --> 00:35:54,439 Speaker 1: percent of them were infected by the parasite. So let's 754 00:35:54,480 --> 00:35:56,719 Speaker 1: walk through a really quick thought experiment to decide if 755 00:35:56,719 --> 00:35:59,560 Speaker 1: we're impressed by that or not. If one percent of 756 00:35:59,600 --> 00:36:03,320 Speaker 1: the poppylation of European water voles is infected and eleven 757 00:36:03,360 --> 00:36:05,319 Speaker 1: percent of the European water boles that are caught by 758 00:36:05,360 --> 00:36:08,239 Speaker 1: cats are infected, then that suggests that at least the 759 00:36:08,320 --> 00:36:11,600 Speaker 1: infected water bowls are selectively more likely to be killed 760 00:36:11,600 --> 00:36:15,160 Speaker 1: by cats. If eleven percent of the water bowls are 761 00:36:15,160 --> 00:36:18,000 Speaker 1: infected and eleven percent are being killed by cats, that's 762 00:36:18,040 --> 00:36:20,080 Speaker 1: just kind of random. You'd expect that from a random 763 00:36:20,120 --> 00:36:23,120 Speaker 1: draw of the population, So possibly the parasite isn't changing 764 00:36:23,160 --> 00:36:23,759 Speaker 1: behavior at all. 765 00:36:23,920 --> 00:36:27,440 Speaker 2: You're saying, if bowls are caught by cats more often 766 00:36:27,480 --> 00:36:30,279 Speaker 2: than their prevalence in the natural population, that suggests that 767 00:36:30,280 --> 00:36:32,359 Speaker 2: there's something making it easier for them to be. 768 00:36:32,320 --> 00:36:36,040 Speaker 1: Caught exactly, And that doesn't necessarily have to mean that 769 00:36:36,080 --> 00:36:38,000 Speaker 1: it's because the rodents are attracted to the smell of 770 00:36:38,040 --> 00:36:40,840 Speaker 1: cat urine. It could be because when you've got cysts 771 00:36:40,840 --> 00:36:43,239 Speaker 1: in your brain, you run into trees or something like that, 772 00:36:43,280 --> 00:36:47,080 Speaker 1: so totally different. But they looked at water voles in 773 00:36:47,160 --> 00:36:50,279 Speaker 1: another population and they put out traps and they found 774 00:36:50,320 --> 00:36:53,280 Speaker 1: that the percent of those water bowls that were infected 775 00:36:53,320 --> 00:36:57,080 Speaker 1: by the parasite was zero. So if you assume that 776 00:36:57,280 --> 00:37:00,080 Speaker 1: just about throughout all of Switzerland, most of the voles 777 00:37:00,120 --> 00:37:03,680 Speaker 1: are not infected by Toxoplasma gandhiy, but eleven percent of 778 00:37:03,719 --> 00:37:06,600 Speaker 1: them coming home in the mouth of a cat are, 779 00:37:07,280 --> 00:37:09,799 Speaker 1: then that does suggest that they're more likely than you 780 00:37:09,800 --> 00:37:13,959 Speaker 1: would expect to be getting caught by a cat after 781 00:37:14,000 --> 00:37:14,640 Speaker 1: they're infected. 782 00:37:15,200 --> 00:37:17,440 Speaker 2: So the cats are catching the ones that are infected 783 00:37:17,840 --> 00:37:19,960 Speaker 2: more than they're catching the ones that are not infected. 784 00:37:20,160 --> 00:37:25,760 Speaker 1: They're still bringing home more uninfected individuals because there's probably 785 00:37:25,800 --> 00:37:28,800 Speaker 1: still not loads of individuals who are infected by the 786 00:37:28,840 --> 00:37:32,000 Speaker 1: parasite in the environment. But of the population of les 787 00:37:32,040 --> 00:37:33,839 Speaker 1: that are out there, the ones that are infected are 788 00:37:33,840 --> 00:37:35,680 Speaker 1: more likely to get caught by cats than the ones 789 00:37:35,719 --> 00:37:36,520 Speaker 1: that are uninfected. 790 00:37:37,080 --> 00:37:39,760 Speaker 2: But these are water voles, like swimming around in lakes. 791 00:37:40,280 --> 00:37:42,200 Speaker 1: They don't spend all their time in the water. I 792 00:37:42,200 --> 00:37:45,080 Speaker 1: think they tend to be like associated with aquatic habitats. 793 00:37:45,440 --> 00:37:47,680 Speaker 2: I imagine like Brazilian voles, or like on the beach 794 00:37:47,719 --> 00:37:49,560 Speaker 2: all the time or something. I want to make a 795 00:37:49,600 --> 00:37:52,239 Speaker 2: connection to the human studies. But you know, that's just 796 00:37:52,239 --> 00:37:53,640 Speaker 2: me trying to tell a science story. 797 00:37:54,880 --> 00:37:57,160 Speaker 1: Yeah, I'm not sure that's supported by fact, but yeah, so, 798 00:37:57,200 --> 00:38:00,560 Speaker 1: I mean that's intriguing at least evidence. But I still 799 00:38:00,560 --> 00:38:02,560 Speaker 1: feel like that's not a slam dunk. So that's where 800 00:38:02,560 --> 00:38:05,040 Speaker 1: we are right now. We've got this cool story about zombies. 801 00:38:05,440 --> 00:38:08,680 Speaker 1: The evidence suggests that there's something happening. We know it's 802 00:38:08,680 --> 00:38:11,520 Speaker 1: in the brain that's enticing too, but we haven't really 803 00:38:11,560 --> 00:38:13,680 Speaker 1: locked up a bunch of loose ends that we have 804 00:38:13,760 --> 00:38:16,239 Speaker 1: to you know, slam dunk. Say this is definitely the 805 00:38:16,239 --> 00:38:19,600 Speaker 1: parasite manipulating rodent behavior to its own benefit. So there's 806 00:38:19,600 --> 00:38:21,319 Speaker 1: a lot of work left to do, all right. 807 00:38:21,400 --> 00:38:22,960 Speaker 2: So we know that this thing is out there, we 808 00:38:22,960 --> 00:38:25,520 Speaker 2: know it's infecting a lot of rats and other rodents. 809 00:38:25,760 --> 00:38:28,040 Speaker 2: We understand that it might be changing behavior, and it 810 00:38:28,120 --> 00:38:30,239 Speaker 2: might be changing the behavior of rudents in such a 811 00:38:30,280 --> 00:38:32,799 Speaker 2: way that gets them caught by cats more often, does 812 00:38:32,840 --> 00:38:35,200 Speaker 2: it also change the behavior of the cats or the 813 00:38:35,239 --> 00:38:37,080 Speaker 2: cats just the host for reproduction? 814 00:38:37,520 --> 00:38:40,040 Speaker 1: The cats are just the host for reproduction, and in general, 815 00:38:40,360 --> 00:38:43,879 Speaker 1: the hosts where the sexual reproduction is happening, we don't 816 00:38:43,920 --> 00:38:46,480 Speaker 1: often see a lot of behavior changes in those hosts. 817 00:38:46,920 --> 00:38:49,600 Speaker 1: We usually see behavioral changes in the hosts that need 818 00:38:49,680 --> 00:38:53,520 Speaker 1: to get eaten by those predators where the sexual reproduction 819 00:38:53,600 --> 00:38:54,200 Speaker 1: tends to happen. 820 00:38:54,560 --> 00:38:57,160 Speaker 2: And so tell me how this story then became so 821 00:38:57,239 --> 00:39:00,440 Speaker 2: prevalent in the popular media. There's a very simple story 822 00:39:00,440 --> 00:39:02,840 Speaker 2: about how this affects you and changes your behavior and 823 00:39:02,880 --> 00:39:05,719 Speaker 2: doctor thought you're a zombie. The science is much more 824 00:39:05,719 --> 00:39:08,960 Speaker 2: complicated and fuzzy, as it is always was there like 825 00:39:08,960 --> 00:39:12,080 Speaker 2: a seminal paper that overstated its claims, or like one 826 00:39:12,120 --> 00:39:15,600 Speaker 2: particular news coverage that misunderstood this or how did this 827 00:39:15,640 --> 00:39:19,160 Speaker 2: get centered in the popular mind is like the zombie parasite. 828 00:39:19,400 --> 00:39:22,320 Speaker 1: So there was a seminal paper. It was a Burdoi 829 00:39:22,400 --> 00:39:24,680 Speaker 1: at all two thousand, I think, and they were the 830 00:39:24,680 --> 00:39:29,680 Speaker 1: ones who identified fatal feline attraction. And it was a 831 00:39:29,680 --> 00:39:32,520 Speaker 1: good paper. The science was good. Sometimes you do find 832 00:39:32,520 --> 00:39:34,880 Speaker 1: this effect, sometimes you don't. They found it, and I 833 00:39:34,920 --> 00:39:38,160 Speaker 1: think that kind of blew up. And then Yaroslav Flager's 834 00:39:38,200 --> 00:39:41,359 Speaker 1: work suggesting that maybe it impacts human behavior too, came out, 835 00:39:41,600 --> 00:39:44,120 Speaker 1: and I think a bunch of people got excited. And 836 00:39:44,360 --> 00:39:46,480 Speaker 1: it could just be random chance that the first couple 837 00:39:46,680 --> 00:39:49,760 Speaker 1: papers that were looking for an effect hit on something, 838 00:39:50,280 --> 00:39:52,880 Speaker 1: and that's the story that made it out into the wild. 839 00:39:53,000 --> 00:39:55,440 Speaker 1: And in general, you know, the first study that finds 840 00:39:55,440 --> 00:39:57,640 Speaker 1: a cool effect is going to get a lot of press. 841 00:39:57,960 --> 00:40:00,000 Speaker 1: The second study that says they didn't find an effect 842 00:40:00,320 --> 00:40:02,680 Speaker 1: people don't usually want to talk about that. I did 843 00:40:02,680 --> 00:40:05,719 Speaker 1: work in another system that found that the effect of 844 00:40:05,760 --> 00:40:09,400 Speaker 1: a brain infecting parasite of fish on the fish's behavior 845 00:40:09,480 --> 00:40:12,320 Speaker 1: is like way less than we had previously thought. No 846 00:40:12,440 --> 00:40:15,160 Speaker 1: one cites my paper. They cite the first paper where 847 00:40:15,160 --> 00:40:16,200 Speaker 1: the effect was huge. 848 00:40:16,360 --> 00:40:19,040 Speaker 2: So even as a scientist. You're throwing cold water on theories, 849 00:40:19,760 --> 00:40:21,680 Speaker 2: not just in your popular science communication. 850 00:40:22,040 --> 00:40:24,000 Speaker 1: I didn't think this was going to be my niche. 851 00:40:24,000 --> 00:40:26,160 Speaker 1: I didn't want it to be my ditch. But yes, 852 00:40:26,280 --> 00:40:28,080 Speaker 1: that is the person that I am. So you know, 853 00:40:28,320 --> 00:40:30,000 Speaker 1: call me up and invite me to your parties if 854 00:40:30,000 --> 00:40:32,240 Speaker 1: you want to make sure they don't get too rowdy. 855 00:40:32,360 --> 00:40:34,840 Speaker 2: Well, you know, maybe the journalists that covered those papers 856 00:40:34,920 --> 00:40:38,040 Speaker 2: they were infected by the parasite, and the parasite influenced 857 00:40:38,080 --> 00:40:40,920 Speaker 2: them to write like hyperbolic statements about it because it 858 00:40:41,040 --> 00:40:42,000 Speaker 2: just wanted to be famous. 859 00:40:42,239 --> 00:40:44,360 Speaker 1: And that is the fun thing about talking about this system. 860 00:40:44,400 --> 00:40:49,239 Speaker 1: You always get new hypotheses and fun conversations. And yeah, 861 00:40:49,239 --> 00:40:50,920 Speaker 1: it's just exciting to think about. But you know what 862 00:40:51,000 --> 00:40:52,800 Speaker 1: else is exciting to think about? 863 00:40:52,880 --> 00:40:53,200 Speaker 2: What's that? 864 00:40:53,840 --> 00:41:01,640 Speaker 1: Ghosts? Oooooooo, it's as spooky as not having a enough dude. 865 00:41:03,040 --> 00:41:05,240 Speaker 1: Let's take a break and come back and talk about 866 00:41:05,520 --> 00:41:27,480 Speaker 1: the physics behind ghost busting. And we're back, and now 867 00:41:27,520 --> 00:41:32,000 Speaker 1: it's Daniel's turn to tackle ghosts. All right, Daniel, tell 868 00:41:32,040 --> 00:41:35,799 Speaker 1: me about the science behind ghost busting, and don't disappoint 869 00:41:35,800 --> 00:41:38,480 Speaker 1: me because when you first mentioned this topic, I'm like, 870 00:41:38,760 --> 00:41:40,680 Speaker 1: oh man, every once while you have a conversation with 871 00:41:40,719 --> 00:41:44,640 Speaker 1: someone and you're like, ah, I thought I understood you, 872 00:41:45,360 --> 00:41:48,160 Speaker 1: But you believe in ghosts, and that's fine, but that's 873 00:41:48,160 --> 00:41:49,200 Speaker 1: not what I would have predicted. 874 00:41:49,680 --> 00:41:52,680 Speaker 2: I've had that experience, I know, yeah, and I never 875 00:41:52,760 --> 00:41:55,080 Speaker 2: quite know how to approach that. I'm like, wow, okay, 876 00:41:55,480 --> 00:41:57,160 Speaker 2: how do you hold this in your mind? What is 877 00:41:57,200 --> 00:41:59,279 Speaker 2: it you believe or is this in some sort of 878 00:41:59,400 --> 00:42:01,520 Speaker 2: portion of your where you don't apply the same sort 879 00:42:01,560 --> 00:42:04,800 Speaker 2: of like rational careful thinking that I know you apply 880 00:42:04,840 --> 00:42:06,520 Speaker 2: in the rest of your life. I try to always 881 00:42:06,560 --> 00:42:08,400 Speaker 2: approach you sort of generally and carefully to keep the 882 00:42:08,440 --> 00:42:09,720 Speaker 2: lines of communication open. 883 00:42:09,960 --> 00:42:13,000 Speaker 1: Yes, you know, I usually just transition to my listening 884 00:42:13,040 --> 00:42:15,960 Speaker 1: face and I stop asking questions, and I'm like, I 885 00:42:16,040 --> 00:42:19,680 Speaker 1: am listening. There are some questions science can't tackle, and 886 00:42:19,800 --> 00:42:21,960 Speaker 1: I will just listen to you now. But okay, tell 887 00:42:22,000 --> 00:42:24,960 Speaker 1: me about how have people attempted to use scientific techniques 888 00:42:25,440 --> 00:42:27,560 Speaker 1: to answer questions about whether or not there's ghosts? 889 00:42:27,880 --> 00:42:30,480 Speaker 2: Mm hmm. Well, first of all, I want to applaud folks, 890 00:42:30,560 --> 00:42:33,719 Speaker 2: because while there's a lot of stories about ghosts out there, 891 00:42:33,760 --> 00:42:36,000 Speaker 2: there are people out there who are trying to sort 892 00:42:36,040 --> 00:42:38,239 Speaker 2: of nail this down from a scientific point of view, 893 00:42:38,800 --> 00:42:41,200 Speaker 2: just the same way like you can talk about esp 894 00:42:41,560 --> 00:42:44,520 Speaker 2: and you know, pircognition and whatever, and the right thing 895 00:42:44,560 --> 00:42:46,840 Speaker 2: to do there is to do experiments like can people 896 00:42:46,840 --> 00:42:49,520 Speaker 2: predict what card you're holding in your hand? Can people 897 00:42:49,520 --> 00:42:52,080 Speaker 2: predict the future? Like, as we were saying earlier, you 898 00:42:52,120 --> 00:42:54,319 Speaker 2: got to keep an open mind because the universe is 899 00:42:54,400 --> 00:42:57,560 Speaker 2: crazy and it will surprise you, and you can't hold 900 00:42:57,600 --> 00:42:59,680 Speaker 2: on to pre existing narratives. You've got to be open 901 00:42:59,680 --> 00:43:02,480 Speaker 2: to it. But the way to learn about the universe 902 00:43:02,600 --> 00:43:04,920 Speaker 2: is not to just tell crazy stories that some parasite 903 00:43:04,920 --> 00:43:06,839 Speaker 2: in your brain is telling you, but to go out 904 00:43:06,840 --> 00:43:09,120 Speaker 2: there and do experiments. So while there's a lot of 905 00:43:09,200 --> 00:43:11,759 Speaker 2: like spooky silliness out there about ghosts, there are also 906 00:43:11,800 --> 00:43:14,440 Speaker 2: folks out there who try to see is there something 907 00:43:14,480 --> 00:43:17,839 Speaker 2: we can detect scientifically? Are there sensors we can use 908 00:43:18,239 --> 00:43:20,840 Speaker 2: to discover the physics of ghosts? If they are real, 909 00:43:20,880 --> 00:43:23,000 Speaker 2: If they're out there, you know, that means they're part 910 00:43:23,000 --> 00:43:25,279 Speaker 2: of the universe, which means they're physical, which means we 911 00:43:25,280 --> 00:43:27,759 Speaker 2: should be able to detect them. And predominantly from my 912 00:43:27,840 --> 00:43:31,399 Speaker 2: research by watching ghost hunting television shows, which I did 913 00:43:31,400 --> 00:43:36,880 Speaker 2: for this podcast, people use basically electromagnetic field meters, Like 914 00:43:36,960 --> 00:43:41,600 Speaker 2: they have these EMF meters that measure electromagnetic radiation, So 915 00:43:41,719 --> 00:43:44,000 Speaker 2: you can use this if you're curious, like how much 916 00:43:44,040 --> 00:43:46,960 Speaker 2: cell signal am I getting my house or whatever. Electromagnetic 917 00:43:47,040 --> 00:43:49,840 Speaker 2: Radiation is just like a kind of light. You know, 918 00:43:49,960 --> 00:43:52,719 Speaker 2: light is a wiggle in the electromagnetic field. Light is 919 00:43:52,760 --> 00:43:56,520 Speaker 2: electromagnetic radiation. It's a very broad spectrum, all the way 920 00:43:56,600 --> 00:43:59,879 Speaker 2: from radio waves with very long frequency up to extra 921 00:44:00,120 --> 00:44:03,000 Speaker 2: rays and gamma rays. This are not weird and spooky 922 00:44:03,000 --> 00:44:05,880 Speaker 2: in any way, Like we know what electromagnetic radiation is, 923 00:44:06,480 --> 00:44:11,080 Speaker 2: but there's the thought that maybe ghosts create electromagnetic radiation 924 00:44:11,960 --> 00:44:15,680 Speaker 2: or are themselves ripples in the electromagnetic field, because you know, 925 00:44:15,719 --> 00:44:18,359 Speaker 2: the electromagnetic field is important to life. You and I 926 00:44:18,440 --> 00:44:21,920 Speaker 2: both have a lot of electrochemistry going on, and so 927 00:44:21,920 --> 00:44:24,640 Speaker 2: that's one way people try to like use science to 928 00:44:24,640 --> 00:44:26,960 Speaker 2: see is there anything actually out there going on? 929 00:44:27,800 --> 00:44:30,400 Speaker 1: Is there an explanation for why we think that the 930 00:44:30,440 --> 00:44:35,080 Speaker 1: electromagnetic field, which we know living organisms give off, why 931 00:44:35,080 --> 00:44:38,319 Speaker 1: would we expect the dead to also be doing that? 932 00:44:38,400 --> 00:44:40,160 Speaker 1: Like why is that the thing that we're looking for? 933 00:44:40,840 --> 00:44:43,000 Speaker 2: M hm, I don't have an answer, But I do 934 00:44:43,040 --> 00:44:45,319 Speaker 2: have a hypothesis. Okay, First of all, we don't know 935 00:44:45,360 --> 00:44:47,440 Speaker 2: what ghosts are, right, So in order to predict that 936 00:44:47,480 --> 00:44:49,000 Speaker 2: they're making some physical impact, you have to have a 937 00:44:49,040 --> 00:44:51,839 Speaker 2: physical model. You say, ghosts are this or ghost are 938 00:44:51,880 --> 00:44:53,759 Speaker 2: that here? You have to sort of work backwards and 939 00:44:53,800 --> 00:44:56,480 Speaker 2: try to say, well, if how could ghosts create this 940 00:44:56,560 --> 00:44:58,839 Speaker 2: kind of signal? And I don't have an answer for you. 941 00:44:59,120 --> 00:45:02,360 Speaker 2: It's true that the doctromagnetic field is capable of carrying information, 942 00:45:03,040 --> 00:45:07,040 Speaker 2: and that information is massless, right, photons have no mass, 943 00:45:07,680 --> 00:45:10,320 Speaker 2: And so imagine like I took Kelly, and I broke 944 00:45:10,320 --> 00:45:13,719 Speaker 2: her down into her constituent bits and extracted all the 945 00:45:13,800 --> 00:45:17,360 Speaker 2: useful Kelly information, the pieces that made Kelly Kelly, and 946 00:45:17,440 --> 00:45:20,000 Speaker 2: not like the details of your toenails, but just like 947 00:45:20,080 --> 00:45:22,880 Speaker 2: your mind and your thoughts. You can imagine making that 948 00:45:22,960 --> 00:45:25,239 Speaker 2: digital the way people imagine you could like upload your 949 00:45:25,239 --> 00:45:29,719 Speaker 2: consciousness into a computer and you could encode that in photons. 950 00:45:30,160 --> 00:45:32,480 Speaker 2: So you know, I could take Kelly, tear you apart 951 00:45:32,520 --> 00:45:36,040 Speaker 2: into your information, convert you into photons, beam you through space. 952 00:45:36,600 --> 00:45:40,040 Speaker 2: Would that be ghost Kelly? I don't know. Maybe could 953 00:45:40,080 --> 00:45:44,120 Speaker 2: somehow you know people's thoughts and ideas which we don't 954 00:45:44,120 --> 00:45:47,840 Speaker 2: fully understand, of course, be transmitted into the electromagnetic field. 955 00:45:48,080 --> 00:45:50,520 Speaker 2: I don't know that's sort of the direction people are going. 956 00:45:51,000 --> 00:45:53,239 Speaker 2: I think what's really happening here is that people are 957 00:45:53,600 --> 00:45:56,360 Speaker 2: trying to be creative about ways we could identify ghosts, 958 00:45:56,680 --> 00:45:58,800 Speaker 2: and they're looking for the sensors we have at hand. 959 00:45:59,280 --> 00:46:02,080 Speaker 2: And it's easy to get an EMF meter, like they're cheap, 960 00:46:02,440 --> 00:46:07,480 Speaker 2: they're reactive. And here's my hypothesis is that old houses 961 00:46:08,160 --> 00:46:12,360 Speaker 2: have bad wiring, and when you're in an old spooky house, 962 00:46:12,680 --> 00:46:16,759 Speaker 2: you're gonna measure em fields or fluctuations in the electricity 963 00:46:16,920 --> 00:46:18,719 Speaker 2: and you're gonna go, oh my god, look we just 964 00:46:18,760 --> 00:46:23,400 Speaker 2: saw something. I have no data to support this, but 965 00:46:23,640 --> 00:46:24,560 Speaker 2: that's my hunch. 966 00:46:25,160 --> 00:46:29,319 Speaker 1: If someone said, Okay, Daniel, we're giving your lab five 967 00:46:29,400 --> 00:46:32,600 Speaker 1: million dollars to do the best study you can think 968 00:46:32,640 --> 00:46:35,640 Speaker 1: of to look for the existence of ghosts, what would 969 00:46:35,680 --> 00:46:39,240 Speaker 1: you measure or who the heck knows? 970 00:46:39,680 --> 00:46:44,799 Speaker 2: That's a great question which I'm shockingly unprepared for. I 971 00:46:44,800 --> 00:46:46,960 Speaker 2: think if you gave me that money, I would try 972 00:46:47,000 --> 00:46:50,200 Speaker 2: to find some location where people are reporting sort of 973 00:46:50,239 --> 00:46:53,759 Speaker 2: paranormal activity that we couldn't explain and then take as 974 00:46:53,960 --> 00:46:57,080 Speaker 2: broad data as we could so yeah, including ef meters 975 00:46:57,160 --> 00:46:59,279 Speaker 2: and other kinds of things, to see if we can 976 00:46:59,280 --> 00:47:03,520 Speaker 2: make some coral between the data we're collecting and people's experience, 977 00:47:04,040 --> 00:47:05,720 Speaker 2: and that way we could start to get a handle 978 00:47:05,760 --> 00:47:08,640 Speaker 2: on the physical phenomena. If there are indeed any that 979 00:47:08,719 --> 00:47:12,600 Speaker 2: are connected to people's personal experience. I don't know. We 980 00:47:12,680 --> 00:47:15,759 Speaker 2: do know that there's some connections between electromagnetic fields and 981 00:47:15,800 --> 00:47:20,840 Speaker 2: people's experience. You know, there are these crazy studies where 982 00:47:20,960 --> 00:47:24,760 Speaker 2: a psychologist created what he called the God helmet, where 983 00:47:25,080 --> 00:47:28,320 Speaker 2: he created his helmet and he put very strong electromagnetic 984 00:47:28,360 --> 00:47:31,080 Speaker 2: field emitting coils in the helmet and he put this 985 00:47:31,120 --> 00:47:33,440 Speaker 2: on people and he turns it on. So basically he 986 00:47:33,520 --> 00:47:37,200 Speaker 2: immersed your brain in a strong electromagnetic field. And he 987 00:47:37,320 --> 00:47:40,759 Speaker 2: reported that once the helmet was activated, the wearer's temporal 988 00:47:40,800 --> 00:47:44,319 Speaker 2: lobes their brain were pounded with these fields, and eighty 989 00:47:44,360 --> 00:47:47,000 Speaker 2: percent of the people who wore this helmet reported feeling 990 00:47:47,080 --> 00:47:49,640 Speaker 2: quote a presence of some kind in the room with them, 991 00:47:49,800 --> 00:47:53,680 Speaker 2: including on some occasions visions of God. So you know, 992 00:47:54,200 --> 00:47:56,960 Speaker 2: we know the brain is made of neurons, and neurons 993 00:47:57,000 --> 00:47:59,840 Speaker 2: are electromagnetic. They send little pulses of signals, and so 994 00:48:00,280 --> 00:48:03,160 Speaker 2: it's not crazy to imagine that if your brain is 995 00:48:03,200 --> 00:48:05,319 Speaker 2: immersed in a strong field, it might change the way 996 00:48:05,400 --> 00:48:08,560 Speaker 2: that it behaves. So now we're talking physics zombies, right, 997 00:48:10,360 --> 00:48:12,840 Speaker 2: and it changes the way people feel, what they experience 998 00:48:12,880 --> 00:48:15,640 Speaker 2: and what they see. So it could be that if 999 00:48:15,640 --> 00:48:18,640 Speaker 2: you're in a crazy old house with strong electromagnetic fields, 1000 00:48:18,960 --> 00:48:22,439 Speaker 2: those things change the way your brain behaves. Plus you're 1001 00:48:22,480 --> 00:48:25,160 Speaker 2: expecting to see something sort of weird. There's a lot 1002 00:48:25,160 --> 00:48:27,960 Speaker 2: of psychology and physics going on here, So it could 1003 00:48:27,960 --> 00:48:30,360 Speaker 2: be that that's a physical phenomena that could connect people's 1004 00:48:30,400 --> 00:48:33,160 Speaker 2: experience and like readings on an EMF meter. 1005 00:48:33,840 --> 00:48:36,319 Speaker 1: And so I assume that this guy set out to 1006 00:48:36,440 --> 00:48:40,120 Speaker 1: disprove that there are ghosts and just showing that you 1007 00:48:40,160 --> 00:48:43,000 Speaker 1: can create this with EMFs, not to show that EMFs 1008 00:48:43,000 --> 00:48:45,600 Speaker 1: are the way that we communicate with the undead. 1009 00:48:45,440 --> 00:48:47,839 Speaker 2: Right, Yeah, exactly. I don't think he was saying that 1010 00:48:47,920 --> 00:48:51,600 Speaker 2: God is electromagnetic. No, he was saying that our perception 1011 00:48:51,640 --> 00:48:55,640 Speaker 2: of reality is influenced by electromagnetic fields in a way 1012 00:48:55,680 --> 00:48:58,520 Speaker 2: that it could make you feel like spooky or haunted. 1013 00:48:58,880 --> 00:49:01,439 Speaker 2: And so you see a lot of EMF meters on 1014 00:49:01,520 --> 00:49:03,920 Speaker 2: TV with ghost hunters, and I'll say that this is 1015 00:49:04,000 --> 00:49:06,759 Speaker 2: TV show called the ghost Hunters, and they're always showing 1016 00:49:06,880 --> 00:49:09,680 Speaker 2: up at these spooky houses looking and they never see anything. 1017 00:49:10,239 --> 00:49:13,240 Speaker 2: There's never any readings on the meters that are useful 1018 00:49:13,320 --> 00:49:15,920 Speaker 2: or interesting or conclusive, you know, which is probably why 1019 00:49:15,960 --> 00:49:18,160 Speaker 2: the show keeps going because if they found ghosts, they 1020 00:49:18,160 --> 00:49:20,399 Speaker 2: would be done, Oh yeah, we found it, show over, 1021 00:49:20,719 --> 00:49:21,920 Speaker 2: so it would ruin the drama. 1022 00:49:22,000 --> 00:49:25,080 Speaker 1: So I think in those shows they also say something like, oh, 1023 00:49:25,200 --> 00:49:28,600 Speaker 1: the temperature drops suddenly, what do we know about that? 1024 00:49:29,040 --> 00:49:32,640 Speaker 2: Yeah. Another popular technique is just like gathered data about 1025 00:49:32,680 --> 00:49:34,960 Speaker 2: the temperature. So there are these meters you can buy. 1026 00:49:35,000 --> 00:49:38,440 Speaker 2: They're called kestrel meters. Again, they're cheap, they're effective, so 1027 00:49:38,480 --> 00:49:40,160 Speaker 2: a lot of people have them, and they can do 1028 00:49:40,239 --> 00:49:44,080 Speaker 2: things like detect change in airflow or temperature or barometric pressure. 1029 00:49:44,360 --> 00:49:46,440 Speaker 2: They're very useful for understanding weather and like it's a 1030 00:49:46,440 --> 00:49:49,719 Speaker 2: tornado coming. And some ghost hunters believe that like a 1031 00:49:49,760 --> 00:49:53,040 Speaker 2: sudden drop in temperature is a sign of paranormal activity. 1032 00:49:53,360 --> 00:49:56,680 Speaker 2: There's no actual data to support that. Nobody's actually found 1033 00:49:56,719 --> 00:50:01,440 Speaker 2: a correlation between people's reports of paranormal activity and temperature dropping. 1034 00:50:01,800 --> 00:50:03,720 Speaker 2: But you know, it's another thing we can detect about 1035 00:50:03,719 --> 00:50:07,200 Speaker 2: our environment, and it's the kind of study I totally support, Like, 1036 00:50:07,280 --> 00:50:08,839 Speaker 2: let's keep an up in mind, let's go out there, 1037 00:50:08,920 --> 00:50:12,520 Speaker 2: let's take physical data rather than just say I saw 1038 00:50:12,560 --> 00:50:15,720 Speaker 2: a ghost in the corner. Yeah, because even if people 1039 00:50:15,719 --> 00:50:18,879 Speaker 2: believe stuff, eyewitness reports are very very hard to use 1040 00:50:18,920 --> 00:50:21,960 Speaker 2: scientifically because, as we know, they're influenced by memory and 1041 00:50:22,000 --> 00:50:23,520 Speaker 2: emotion and all sorts of stuff. 1042 00:50:23,719 --> 00:50:26,000 Speaker 1: Okay, So I have been dying for us to get 1043 00:50:26,040 --> 00:50:27,919 Speaker 1: to the point where we get to talk about Ghostbusters 1044 00:50:28,080 --> 00:50:31,360 Speaker 1: because when I was a kid, I was obsessed with Ghostbusters. 1045 00:50:31,680 --> 00:50:36,680 Speaker 1: It's possible that my first crush was on Egon Nice, 1046 00:50:36,880 --> 00:50:41,000 Speaker 1: the character in the cartoon. So how good is the 1047 00:50:41,040 --> 00:50:43,719 Speaker 1: science there. They've got those proton packs, they can like 1048 00:50:44,280 --> 00:50:46,719 Speaker 1: catch them in that box and store them in that container. 1049 00:50:47,120 --> 00:50:48,200 Speaker 1: What is the science there? 1050 00:50:50,320 --> 00:50:53,960 Speaker 2: Yees? So I love Ghostbusters and it's not hard science fiction, 1051 00:50:54,520 --> 00:50:56,279 Speaker 2: but I do like that they dress it up a 1052 00:50:56,280 --> 00:50:58,960 Speaker 2: little bit sciencey, you know, and the scientists are kind 1053 00:50:59,000 --> 00:51:02,759 Speaker 2: of heroes in that story. They're creating technology, they're understanding it. 1054 00:51:03,000 --> 00:51:04,440 Speaker 2: They're not just running around. 1055 00:51:04,200 --> 00:51:06,200 Speaker 1: And being woo woo very handsome too. 1056 00:51:06,719 --> 00:51:10,680 Speaker 2: Yeah, exactly, they're good looking, they're charismatic. So what's going 1057 00:51:10,719 --> 00:51:14,200 Speaker 2: on with the science Ghostbusters? While they have these PKE meters, 1058 00:51:14,239 --> 00:51:18,920 Speaker 2: you know, which detect psychic activity. pKa stands for psychokinetic energy, 1059 00:51:19,480 --> 00:51:21,800 Speaker 2: and I think this is just like a fancy version 1060 00:51:21,840 --> 00:51:24,560 Speaker 2: of an EMF meter. They invent this device, they don't 1061 00:51:24,560 --> 00:51:26,960 Speaker 2: go into the details, like what exactly is it measuring? 1062 00:51:27,040 --> 00:51:30,200 Speaker 2: How is it detecting psychic energy? I think it's basically 1063 00:51:30,400 --> 00:51:34,040 Speaker 2: inspired by real life EMF meters like measure fluctuations in 1064 00:51:34,040 --> 00:51:35,280 Speaker 2: the electromagnetic field. 1065 00:51:35,440 --> 00:51:38,000 Speaker 1: So there is no actual such thing as a pKa meter. 1066 00:51:38,480 --> 00:51:41,520 Speaker 2: No, it's just a prop you know, it doesn't actually 1067 00:51:41,560 --> 00:51:44,560 Speaker 2: do anything. There is no psychic kinetic energy as a 1068 00:51:44,600 --> 00:51:48,080 Speaker 2: physical concept. That would be awesome. Wow, somebody could invent 1069 00:51:48,160 --> 00:51:51,280 Speaker 2: that that detected this new field of energy, like huge, 1070 00:51:51,560 --> 00:51:54,360 Speaker 2: huge discovery about the nature of the universe. 1071 00:51:54,800 --> 00:51:55,800 Speaker 1: That would be incredible. 1072 00:51:56,040 --> 00:51:59,080 Speaker 2: But my favorite part about Ghostbuster science are the proton packs. 1073 00:52:00,080 --> 00:52:02,520 Speaker 1: Well, all right, but clearly those would work, right. 1074 00:52:02,840 --> 00:52:05,120 Speaker 2: Those would work in some sense, Like what is a 1075 00:52:05,120 --> 00:52:08,400 Speaker 2: proton pack? If you look at the picture on their backs, 1076 00:52:08,400 --> 00:52:10,520 Speaker 2: they have these circles on them, and what they're really 1077 00:52:10,560 --> 00:52:13,600 Speaker 2: doing there is they're creating a little particle accelerator. Like 1078 00:52:13,640 --> 00:52:15,240 Speaker 2: what do we do with the Large had Drunk Collider. 1079 00:52:15,320 --> 00:52:17,880 Speaker 2: We take protons, we speed them up, We bend them 1080 00:52:17,880 --> 00:52:19,680 Speaker 2: around in a circle so we can keep speeding them 1081 00:52:19,760 --> 00:52:22,400 Speaker 2: up many many times, and then we smash them into stuff. 1082 00:52:22,560 --> 00:52:25,800 Speaker 2: That's what a proton pack is. Takes protons, it spins 1083 00:52:25,840 --> 00:52:28,120 Speaker 2: them around, it shoots them out. It's basically a proton 1084 00:52:28,200 --> 00:52:31,040 Speaker 2: beam generator. And the science of that is pretty solid. 1085 00:52:31,080 --> 00:52:33,160 Speaker 2: Like we build those things, we have those things in 1086 00:52:33,200 --> 00:52:35,720 Speaker 2: real life. I have some comments about like the size 1087 00:52:35,719 --> 00:52:38,080 Speaker 2: of those things on their backs, but like those are details. 1088 00:52:38,160 --> 00:52:40,359 Speaker 1: Do you think one day we could shrink them down 1089 00:52:40,440 --> 00:52:41,960 Speaker 1: enough that you could actually fit them on your back. 1090 00:52:42,200 --> 00:52:44,840 Speaker 2: You could definitely have a proton pack small enough to 1091 00:52:44,920 --> 00:52:47,000 Speaker 2: put on your back. The question is could it have 1092 00:52:47,080 --> 00:52:49,640 Speaker 2: enough energy. The reason the Large had Drunk Collider is 1093 00:52:49,680 --> 00:52:52,239 Speaker 2: so large is that when protons are going really really 1094 00:52:52,239 --> 00:52:54,720 Speaker 2: fast and they have so much energy, it gets harder 1095 00:52:54,760 --> 00:52:57,319 Speaker 2: to bend them. So you need super powerful magnets. At 1096 00:52:57,320 --> 00:53:00,000 Speaker 2: the Large had Drunk Collider, we have like amazing souper 1097 00:53:00,160 --> 00:53:02,840 Speaker 2: conducting magnets that are really awesome, and they can just 1098 00:53:02,880 --> 00:53:05,560 Speaker 2: barely bend those protons around in a circle that's like 1099 00:53:05,600 --> 00:53:09,120 Speaker 2: thirty three kilometers, So to get them within like half 1100 00:53:09,160 --> 00:53:13,480 Speaker 2: a meter at very very high energy would require incredible magnets, 1101 00:53:13,719 --> 00:53:15,799 Speaker 2: which would also be pretty dangerous, like you'd be walking 1102 00:53:15,840 --> 00:53:17,759 Speaker 2: through the streets in New York and like everybody's keys 1103 00:53:17,760 --> 00:53:20,920 Speaker 2: would be flying out of their pockets and like killing people. 1104 00:53:21,520 --> 00:53:24,400 Speaker 2: So very small would require very high magnets. So that 1105 00:53:24,480 --> 00:53:27,520 Speaker 2: part I'm a little skeptical of. The real question is 1106 00:53:27,600 --> 00:53:31,200 Speaker 2: could you use a proton beam to somehow capture ghosts? 1107 00:53:32,560 --> 00:53:34,040 Speaker 1: Okay, so how would that work? What would that have 1108 00:53:34,040 --> 00:53:35,480 Speaker 1: to say about the ghosts in order for this to 1109 00:53:35,520 --> 00:53:36,080 Speaker 1: all work out? 1110 00:53:36,560 --> 00:53:39,279 Speaker 2: Yeah, exactly, Well, protons are positive, so you're shooting a 1111 00:53:39,280 --> 00:53:42,920 Speaker 2: beam of positive charges and you're somehow hemming the ghosts 1112 00:53:42,920 --> 00:53:45,160 Speaker 2: in with that. I mean, in the show, the beam 1113 00:53:45,200 --> 00:53:47,920 Speaker 2: doesn't move perfectly straight. It's sort of like a whip, 1114 00:53:48,400 --> 00:53:51,400 Speaker 2: more like Wonder Woman's lasso or something, which is definitely 1115 00:53:51,440 --> 00:53:53,520 Speaker 2: not scientific, like the protons would move in a straight 1116 00:53:53,560 --> 00:53:56,280 Speaker 2: line or be bent by a magnet. But I guess 1117 00:53:56,440 --> 00:54:00,200 Speaker 2: if ghosts were like negatively charged, you know, some know, 1118 00:54:00,560 --> 00:54:03,239 Speaker 2: then they would get attracted to the beam and you 1119 00:54:03,280 --> 00:54:05,480 Speaker 2: could like stick the beam to them and even pull 1120 00:54:05,520 --> 00:54:08,799 Speaker 2: them around with the beam. So yeah, if ghosts are 1121 00:54:08,920 --> 00:54:11,600 Speaker 2: for some reason negatively charged, then protons are the right 1122 00:54:11,640 --> 00:54:12,719 Speaker 2: way to hem them in. 1123 00:54:13,239 --> 00:54:15,799 Speaker 1: So next year at this time, we'll be reviewing the 1124 00:54:15,880 --> 00:54:18,439 Speaker 1: science about whether or not ghosts or negatively charged, because 1125 00:54:18,480 --> 00:54:20,640 Speaker 1: people will probably follow up on your work here. 1126 00:54:21,280 --> 00:54:23,520 Speaker 2: Well, if ghosts were positively charged, you could just use 1127 00:54:23,520 --> 00:54:25,640 Speaker 2: an electron beam to capture them, but then you got 1128 00:54:25,680 --> 00:54:27,760 Speaker 2: to know the charge of the ghost before you shoot 1129 00:54:27,800 --> 00:54:29,840 Speaker 2: the beam at them, right, So you could do it 1130 00:54:29,840 --> 00:54:32,160 Speaker 2: either way positive or negative, and new restriction there. 1131 00:54:32,320 --> 00:54:35,200 Speaker 1: Gets very complicated, So let us know if you have 1132 00:54:35,280 --> 00:54:37,759 Speaker 1: any data on this question. But actually, Barry Rich wrote 1133 00:54:37,800 --> 00:54:40,040 Speaker 1: a really great book where she interacted with the community 1134 00:54:40,040 --> 00:54:42,480 Speaker 1: of people who ask questions about this kind of stuff, 1135 00:54:42,719 --> 00:54:45,480 Speaker 1: and I highly recommend every book ever written by Mary Roach. 1136 00:54:45,840 --> 00:54:46,520 Speaker 2: She's excellent. 1137 00:54:46,800 --> 00:54:49,799 Speaker 1: Yeah, okay, everybody, Happy Halloween. We hope you have an 1138 00:54:49,840 --> 00:54:52,680 Speaker 1: amazing spooky day, and if you want to send us 1139 00:54:52,719 --> 00:54:56,000 Speaker 1: any questions or suggestions for future shows, drop us a 1140 00:54:56,040 --> 00:54:58,399 Speaker 1: line at Questions at Daniel and Kelly dot org. 1141 00:54:58,800 --> 00:55:01,239 Speaker 2: Happy Halloween, everyone, and this episode goes to show you 1142 00:55:01,320 --> 00:55:04,680 Speaker 2: there's science in everything, in me and you and even 1143 00:55:04,719 --> 00:55:05,680 Speaker 2: in Halloween. 1144 00:55:06,080 --> 00:55:18,440 Speaker 1: W Daniel and Kelly's Extraordinary Universe is produced by iHeartRadio. 1145 00:55:18,640 --> 00:55:21,200 Speaker 1: We would love to hear from you, We really would. 1146 00:55:21,360 --> 00:55:24,080 Speaker 2: We want to know what questions you have about this 1147 00:55:24,320 --> 00:55:25,960 Speaker 2: Extraordinary Universe. 1148 00:55:26,080 --> 00:55:29,040 Speaker 1: We want to know your thoughts on recent shows, suggestions 1149 00:55:29,040 --> 00:55:32,080 Speaker 1: for future shows. 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