1 00:00:01,080 --> 00:00:11,160 Speaker 1: Welcome to Stuff You Should Know fromhouse Stuff Works dot com. Hey, 2 00:00:11,160 --> 00:00:13,640 Speaker 1: and welcome to the podcast. I'm Josh Clark, and there's 3 00:00:13,680 --> 00:00:18,160 Speaker 1: Charles W. Chuck Bryant, and this is stuff you should Know. Yes, 4 00:00:18,239 --> 00:00:22,159 Speaker 1: I think this might complete our brain. I don't know 5 00:00:22,200 --> 00:00:25,119 Speaker 1: about that, because we've done Einstein's brain, You've done difference 6 00:00:25,160 --> 00:00:29,400 Speaker 1: between men and women's brain, and now we're tackling brain size, 7 00:00:30,280 --> 00:00:32,240 Speaker 1: which is sort of gets on both of us a 8 00:00:32,280 --> 00:00:35,919 Speaker 1: little bit. It does, but there's always new findings. So yeah, 9 00:00:35,960 --> 00:00:39,479 Speaker 1: that's what I'm saying. If there's ever an ongoing sweet, 10 00:00:39,720 --> 00:00:42,760 Speaker 1: it's got to be the brain. Man. It's growing all 11 00:00:42,800 --> 00:00:47,920 Speaker 1: the time. It's changing shape, changing size, changing connections. You 12 00:00:47,920 --> 00:00:52,080 Speaker 1: could almost say that sweet is plastic plasticity. Baby. Yeah, 13 00:00:52,120 --> 00:00:55,040 Speaker 1: that's right. Um, you sent me something that I think 14 00:00:55,080 --> 00:00:58,920 Speaker 1: we should talk about first, Chuck. This is kind of like, um, 15 00:00:59,120 --> 00:01:03,560 Speaker 1: this is just like a ad bag hodgepodge of loosely 16 00:01:03,640 --> 00:01:07,040 Speaker 1: related studies that all find that we don't really know 17 00:01:07,120 --> 00:01:11,280 Speaker 1: the answer to the question like does a big brain 18 00:01:11,400 --> 00:01:15,040 Speaker 1: mean a smarter person? Yeah, because there's a lot of 19 00:01:15,120 --> 00:01:20,440 Speaker 1: different conflicting findings. Well, a few million years ago, our 20 00:01:20,480 --> 00:01:23,080 Speaker 1: brains started growing a lot and that kind of timed 21 00:01:23,080 --> 00:01:26,600 Speaker 1: out with becoming smarter and using tools and things. So 22 00:01:26,680 --> 00:01:30,200 Speaker 1: I mean there's a little bit of you call it evidence. Well, yeah, 23 00:01:30,240 --> 00:01:32,920 Speaker 1: there's definitely some plenty of evidence. I think that's what 24 00:01:32,959 --> 00:01:36,559 Speaker 1: the confounding part is that there's plenty of evidence that, yes, 25 00:01:36,600 --> 00:01:41,480 Speaker 1: as a brain grows, it is correlated to intelligence. But 26 00:01:41,560 --> 00:01:44,600 Speaker 1: then that's only holding true up to a point. I 27 00:01:44,680 --> 00:01:48,880 Speaker 1: sounded like a Soviet immigrant. Just then that's only holding 28 00:01:48,880 --> 00:01:53,880 Speaker 1: true up to a certain point. Right. He's in Branson, Missouri, though, 29 00:01:53,920 --> 00:01:55,720 Speaker 1: did you know that. I think he's got like his 30 00:01:55,760 --> 00:01:58,640 Speaker 1: own restaurant or something. Well, he's own theater, and I 31 00:01:58,640 --> 00:02:02,760 Speaker 1: think all the theaters are food buttery. We should go 32 00:02:02,800 --> 00:02:04,480 Speaker 1: to Branson, man that I want to see what that 33 00:02:04,480 --> 00:02:08,280 Speaker 1: place is all about. Okay, you know yeah, I mean 34 00:02:08,280 --> 00:02:12,560 Speaker 1: it's a parade of stars. If it's nineteen seventy three, 35 00:02:12,760 --> 00:02:16,399 Speaker 1: you know. Uh, I bet your boy Ronnie mills Up 36 00:02:16,400 --> 00:02:20,160 Speaker 1: is there. Yeah. If he doesn't have a place there, 37 00:02:20,160 --> 00:02:23,880 Speaker 1: I'll bet he plays Branson fairly regularly. He sub lets 38 00:02:24,120 --> 00:02:29,440 Speaker 1: he would play well there. Um, so Branson, how do 39 00:02:29,600 --> 00:02:34,800 Speaker 1: we even get them? Yeah? So brain size does correlate 40 00:02:34,840 --> 00:02:37,960 Speaker 1: to intelligence to a certain extent, But you can point 41 00:02:37,960 --> 00:02:40,959 Speaker 1: out like, well, sperm whale has a seventeen pound brain. 42 00:02:41,520 --> 00:02:44,320 Speaker 1: Holy cow, it must be the smartest animal on the planet. 43 00:02:44,400 --> 00:02:47,440 Speaker 1: Well it's not. I'm sorry to tell you sperm whale 44 00:02:47,480 --> 00:02:50,520 Speaker 1: fans that it's not the smartest animal on the planet. 45 00:02:50,760 --> 00:02:53,280 Speaker 1: Humans are the smartest animal on the planet, and don't 46 00:02:53,280 --> 00:02:56,280 Speaker 1: you forget it. But we don't have the largest brains, 47 00:02:57,000 --> 00:03:00,640 Speaker 1: so you kind of take that idea of well, if 48 00:03:00,639 --> 00:03:03,320 Speaker 1: it's not brain size, maybe it has to do with 49 00:03:03,400 --> 00:03:06,359 Speaker 1: the size of your brain in relation to your body. 50 00:03:06,560 --> 00:03:09,160 Speaker 1: Then we started to get a little closer to jack pot. 51 00:03:09,320 --> 00:03:11,400 Speaker 1: But even still, I just want to I want to 52 00:03:11,400 --> 00:03:14,280 Speaker 1: spoil it for everybody. There's no definitive answer. Yeah, but 53 00:03:14,480 --> 00:03:17,040 Speaker 1: sometimes those are the best ones because we get to 54 00:03:17,080 --> 00:03:21,000 Speaker 1: explore all this stuff and we can't really get anything 55 00:03:21,000 --> 00:03:25,440 Speaker 1: wrong because nobody knows what's right. Oh I like this, then, yeah, 56 00:03:25,600 --> 00:03:28,840 Speaker 1: I've turned you know these? Yeah, now now I feel 57 00:03:28,840 --> 00:03:32,560 Speaker 1: good about this because I can't be wrong right exactly. Well, 58 00:03:32,600 --> 00:03:35,440 Speaker 1: I guess we should start off with um a little 59 00:03:35,440 --> 00:03:38,400 Speaker 1: bit about what determines what size brain you do have. 60 00:03:39,040 --> 00:03:41,640 Speaker 1: And again they don't know everything about it, but they 61 00:03:41,960 --> 00:03:45,560 Speaker 1: think that genetics plays apart. They know this in part 62 00:03:45,640 --> 00:03:52,680 Speaker 1: by studying twins and identical twins um have, of course 63 00:03:52,920 --> 00:03:56,280 Speaker 1: the same genes. Fraternal twins have about half the same genes, 64 00:03:57,000 --> 00:03:59,320 Speaker 1: and there's a greater correlation in brain size if you're 65 00:03:59,360 --> 00:04:02,840 Speaker 1: identical then fraternal. Yeah, so genetics, you know, looks like 66 00:04:02,880 --> 00:04:04,800 Speaker 1: it probably plays a role. Yeah, And they've done a 67 00:04:04,800 --> 00:04:11,000 Speaker 1: lot of exploration into what genes in particular have to 68 00:04:11,040 --> 00:04:14,720 Speaker 1: do with brain size, and they've isolated a few. Um 69 00:04:14,920 --> 00:04:20,479 Speaker 1: one is called beta catenin. There's a hyphen in there too. 70 00:04:20,960 --> 00:04:24,880 Speaker 1: It's pretty flashy gene not beta carotene, no caten in. 71 00:04:25,440 --> 00:04:28,960 Speaker 1: And who's who's coming up with the naming convention for genes? 72 00:04:29,040 --> 00:04:31,960 Speaker 1: They are all over the place, like you can't look 73 00:04:32,000 --> 00:04:33,360 Speaker 1: at the name of a gene and be like, that's 74 00:04:33,360 --> 00:04:36,600 Speaker 1: obviously a gene unless there's like a couple of weird 75 00:04:36,640 --> 00:04:40,080 Speaker 1: consonants and a number and then another consonant. Then you're like, well, 76 00:04:40,080 --> 00:04:44,440 Speaker 1: that's a gene. But you're right, that's a gene. It 77 00:04:44,600 --> 00:04:46,520 Speaker 1: is a gene, and it's a gene that they know 78 00:04:46,680 --> 00:04:49,479 Speaker 1: controls brain growth because they've injected poor mice with this 79 00:04:49,520 --> 00:04:53,320 Speaker 1: stuff until their heads exploded. Exactly their heads they fell 80 00:04:53,400 --> 00:04:55,640 Speaker 1: short of exploding. But a lot of the mice died 81 00:04:55,880 --> 00:04:58,800 Speaker 1: as a result of their heads growing too big. But 82 00:04:58,960 --> 00:05:01,560 Speaker 1: they're they're they're brain means grew big, and as a 83 00:05:01,560 --> 00:05:06,040 Speaker 1: result of their brains growing big, they exhibited um more intelligence, 84 00:05:06,160 --> 00:05:12,919 Speaker 1: higher cognitive function. They injected these things with a gene 85 00:05:12,960 --> 00:05:16,800 Speaker 1: your brain. That yeah, that made them smarter. But that, 86 00:05:16,960 --> 00:05:20,039 Speaker 1: like Molly points out in this article, you can't. That 87 00:05:20,080 --> 00:05:22,000 Speaker 1: doesn't mean we should start doing that because these mines 88 00:05:22,040 --> 00:05:24,640 Speaker 1: are dying, so you can't. Just you can't play god, 89 00:05:24,680 --> 00:05:27,040 Speaker 1: as they say, no, But it does make you wonder, like, Okay, 90 00:05:27,480 --> 00:05:29,960 Speaker 1: you don't want to shoot up beta caton in like 91 00:05:30,000 --> 00:05:31,920 Speaker 1: before the s A T S or anything like that, 92 00:05:32,920 --> 00:05:36,080 Speaker 1: but like, is there a way to kind of tamper 93 00:05:36,360 --> 00:05:40,760 Speaker 1: a little less but still tamper with that gene something 94 00:05:40,800 --> 00:05:43,120 Speaker 1: put under your tongue and let it dissolve. Maybe sure, 95 00:05:43,200 --> 00:05:46,440 Speaker 1: like you know, just epigenetically, just a tad bit. Yeah 96 00:05:47,160 --> 00:05:49,760 Speaker 1: not maybe you know, amplify it just a tad and 97 00:05:49,800 --> 00:05:52,480 Speaker 1: see what happens. But it would cause your brain to 98 00:05:52,520 --> 00:05:56,400 Speaker 1: grow because that gene is partially responsible for the size 99 00:05:56,480 --> 00:05:59,200 Speaker 1: that your brain gets to. That's right, as far as 100 00:05:59,680 --> 00:06:04,719 Speaker 1: large your brains go. Yes, like it makes it larger. Yes, 101 00:06:04,880 --> 00:06:07,640 Speaker 1: if you want to talk smaller brains, there's another gene. 102 00:06:08,400 --> 00:06:10,400 Speaker 1: And boy, you're right. The names are all over the place, 103 00:06:11,120 --> 00:06:13,320 Speaker 1: just convention wise. It's not like they have different names 104 00:06:13,320 --> 00:06:17,679 Speaker 1: that some are numbers and dashes. And to get it together, 105 00:06:18,240 --> 00:06:24,000 Speaker 1: people AESPM. It's an abbreviation for abnormal spindle like, uh, 106 00:06:24,120 --> 00:06:28,359 Speaker 1: micro cephalely associated, that's the name of the gene. Yeah, 107 00:06:28,600 --> 00:06:32,240 Speaker 1: that's it's just shameful. And they say microcephalely associated because 108 00:06:32,279 --> 00:06:35,400 Speaker 1: that is a condition that you've probably seen before when 109 00:06:35,400 --> 00:06:38,000 Speaker 1: you're born with a small head and small brain, which 110 00:06:38,040 --> 00:06:41,479 Speaker 1: probably means you're going to have some cognitive impairment. So 111 00:06:41,640 --> 00:06:47,360 Speaker 1: so right there, smaller brain is is correlated to lesser 112 00:06:47,640 --> 00:06:50,800 Speaker 1: or lower faculty your cognitive function. Yeah, we should look 113 00:06:50,800 --> 00:06:52,960 Speaker 1: into that more for another podcast. So I think it's 114 00:06:53,880 --> 00:06:58,000 Speaker 1: uh from the images I saw, it looks like you 115 00:06:58,160 --> 00:07:02,080 Speaker 1: remember like the movie Freaks. Yes, that that guy. I 116 00:07:02,120 --> 00:07:04,359 Speaker 1: think that's so cute the deal. I think you have 117 00:07:04,520 --> 00:07:07,200 Speaker 1: like normal sized nose and ears and eyes, but your 118 00:07:07,200 --> 00:07:11,840 Speaker 1: actual head and skull and brain or smaller. You don't 119 00:07:11,840 --> 00:07:16,080 Speaker 1: look like the the um the African Safari guy from 120 00:07:16,080 --> 00:07:21,000 Speaker 1: Beetle Chuice not proportionately shrunk, right, it's yeah, how you 121 00:07:21,000 --> 00:07:24,240 Speaker 1: get him down so small? Right? Favorite? What was that 122 00:07:24,280 --> 00:07:29,200 Speaker 1: guy's name from Freaks? I've read about him before. No, 123 00:07:29,400 --> 00:07:32,960 Speaker 1: he had his stage name. It was like Topsy or 124 00:07:33,120 --> 00:07:37,080 Speaker 1: Flopsy or something like that, and he apparently like the 125 00:07:37,160 --> 00:07:41,840 Speaker 1: greatest personality of all time, just so lovable and was 126 00:07:41,880 --> 00:07:45,880 Speaker 1: just exploited basically his whole life until that movie like 127 00:07:46,320 --> 00:07:49,080 Speaker 1: kind of got vengeance for him because he was a 128 00:07:49,160 --> 00:07:54,600 Speaker 1: real life side show performer. Well that's good. Yeah, Topsy. 129 00:07:54,800 --> 00:07:57,720 Speaker 1: It wasn't Topsy that was the elephant that Edison electrocuted, 130 00:07:58,560 --> 00:08:01,520 Speaker 1: but it was something along those lines. Just a fun, 131 00:08:02,080 --> 00:08:06,720 Speaker 1: fun name. Yeah, so check. There's another gene. This is 132 00:08:06,760 --> 00:08:10,520 Speaker 1: a little more genetically sounding e m x two. Yeah 133 00:08:10,560 --> 00:08:16,280 Speaker 1: that sel sounds like a dirt bike or a gene. Yeah, 134 00:08:16,680 --> 00:08:21,080 Speaker 1: it's um Again, we're not We're not saying like, well, 135 00:08:21,120 --> 00:08:23,600 Speaker 1: these are the genes that provide you with your intellect. 136 00:08:23,760 --> 00:08:27,120 Speaker 1: These are just genes that they are saying these things 137 00:08:27,200 --> 00:08:30,040 Speaker 1: have to do with the size of your brain, and 138 00:08:30,320 --> 00:08:33,200 Speaker 1: they we also have figured out that if you mess 139 00:08:33,280 --> 00:08:38,000 Speaker 1: with these genes, you may also be messing with cognitive function. 140 00:08:38,840 --> 00:08:41,880 Speaker 1: So we're laying the groundwork here, everybody to bear with us. 141 00:08:42,400 --> 00:08:46,240 Speaker 1: The e m x two gene UM apparently has to 142 00:08:46,280 --> 00:08:50,920 Speaker 1: do with the growth of your UM, the functional subdivisions 143 00:08:50,960 --> 00:08:54,400 Speaker 1: of the cortex. You have different cortices, they're responsible for 144 00:08:54,440 --> 00:08:57,640 Speaker 1: different things. So like if in that New York Times 145 00:08:57,720 --> 00:08:59,840 Speaker 1: article you seth me, the guy uses the visual cortex 146 00:09:00,000 --> 00:09:03,480 Speaker 1: as an example, UM, where like you get all your 147 00:09:03,600 --> 00:09:06,640 Speaker 1: visual sensory input and your brain puts it all together. 148 00:09:06,920 --> 00:09:09,600 Speaker 1: That cortex, that region of your brain is responsible for 149 00:09:09,640 --> 00:09:15,320 Speaker 1: a fairly specific but also very um complicated task. Now, 150 00:09:15,480 --> 00:09:19,400 Speaker 1: this one functional cortex that the e m x two 151 00:09:19,440 --> 00:09:24,040 Speaker 1: gene is responsible for UM has to do with basically input, 152 00:09:24,600 --> 00:09:30,440 Speaker 1: sensory input and motor output. So your behavior, Like, um, 153 00:09:30,480 --> 00:09:32,680 Speaker 1: if I came across this desk at you and like 154 00:09:32,880 --> 00:09:35,760 Speaker 1: pinched your cheeks, you'd like jump back, I'd say, what 155 00:09:35,840 --> 00:09:39,280 Speaker 1: is it Wednesday? Right? Yeah, you would make the connection 156 00:09:39,320 --> 00:09:43,800 Speaker 1: that's Wednesday. Your behavior would occur. So, UM, this e 157 00:09:43,960 --> 00:09:47,080 Speaker 1: m x two gene has to do with that cortex 158 00:09:47,480 --> 00:09:50,599 Speaker 1: and its size. What they found is that bigger is 159 00:09:50,640 --> 00:09:55,520 Speaker 1: not necessarily better. If you have a lower expression of 160 00:09:55,520 --> 00:09:58,520 Speaker 1: it and you have a smaller subdivision of that cortex, 161 00:09:59,320 --> 00:10:03,960 Speaker 1: you're not to do very well behaviorally functionally, like you 162 00:10:03,960 --> 00:10:06,720 Speaker 1: won't be able to hit a baseball very well, all right, 163 00:10:07,600 --> 00:10:10,480 Speaker 1: but if it's too big, if that gene over expresses, 164 00:10:10,880 --> 00:10:13,600 Speaker 1: you don't get better at hitting a baseball. With this 165 00:10:13,640 --> 00:10:17,240 Speaker 1: in particular, it seems to be fine tuned. So if 166 00:10:17,240 --> 00:10:19,719 Speaker 1: you're not hitting that sweet spot, you're never going to 167 00:10:19,840 --> 00:10:23,400 Speaker 1: hit a baseball. And there may be myriad other problems, 168 00:10:23,520 --> 00:10:26,120 Speaker 1: but you're definitely not gonna hit that baseball. So that 169 00:10:26,160 --> 00:10:30,760 Speaker 1: means you're born with baseball talent pretty much. Yeah, because 170 00:10:30,760 --> 00:10:33,480 Speaker 1: it's genetic, and there's like there's some people who are 171 00:10:33,559 --> 00:10:36,240 Speaker 1: so close to perfect that like baseball just comes naturally 172 00:10:36,280 --> 00:10:41,079 Speaker 1: to right, right, like Robert Redford exactly. Yeah, he really 173 00:10:41,080 --> 00:10:44,640 Speaker 1: gave those lights a wall. Yeah, he's the natural. So 174 00:10:46,400 --> 00:10:49,880 Speaker 1: that's the genetic basis of it. Chuck. Yeah, and uh, 175 00:10:49,960 --> 00:10:54,040 Speaker 1: I guess we should talk some about size if it's important, 176 00:10:54,400 --> 00:10:57,240 Speaker 1: because this is sort of the debate that keeps going 177 00:10:57,280 --> 00:11:02,240 Speaker 1: on and on. Is brain size corollary to intelligence levels? Uh? 178 00:11:02,280 --> 00:11:05,360 Speaker 1: They did find or they have found links between if 179 00:11:05,400 --> 00:11:08,040 Speaker 1: you have a lot of brain growth, um, if it's 180 00:11:08,080 --> 00:11:12,040 Speaker 1: disproportionate early on, Um, they've linked that then early I 181 00:11:12,040 --> 00:11:15,760 Speaker 1: mean the first twelve months too. They've linked that to autism. 182 00:11:15,840 --> 00:11:19,480 Speaker 1: So super rapid growth may what it may do is 183 00:11:19,679 --> 00:11:24,880 Speaker 1: just prevent those neural connections from happening like they should, right. 184 00:11:25,640 --> 00:11:28,960 Speaker 1: Um And actually, well that's kind of links into that 185 00:11:29,000 --> 00:11:31,160 Speaker 1: tethering thing I sent you too, it does, which we 186 00:11:31,200 --> 00:11:36,560 Speaker 1: will talk about later. Um. In biology, though, is there's 187 00:11:36,640 --> 00:11:40,480 Speaker 1: kind of this consensus that it's it's not the only determinant, 188 00:11:41,040 --> 00:11:43,679 Speaker 1: that it has a lot to do with um environment 189 00:11:43,679 --> 00:11:47,079 Speaker 1: as well, I think kind of as a whole. People 190 00:11:47,080 --> 00:11:51,360 Speaker 1: who investigate correlations between brain size and intelligence have totally 191 00:11:51,360 --> 00:11:57,800 Speaker 1: abandoned the idea that, um, like, your brain is predetermined 192 00:11:58,160 --> 00:12:01,680 Speaker 1: to grow a certain way and then that's the Yeah. Well, 193 00:12:01,720 --> 00:12:04,080 Speaker 1: size wise, they've also found that if you have a 194 00:12:04,160 --> 00:12:06,600 Speaker 1: d h D, if you're an adolescent, your brain might 195 00:12:06,600 --> 00:12:09,880 Speaker 1: be three to four percent smaller than your classmate who 196 00:12:09,880 --> 00:12:12,880 Speaker 1: does not have a d h D. UM, and your 197 00:12:12,920 --> 00:12:16,400 Speaker 1: brain shrinks as you get older, but doesn't necessarily lose 198 00:12:16,440 --> 00:12:20,520 Speaker 1: functionality because of the shrinkage. It's not to say when 199 00:12:20,520 --> 00:12:23,080 Speaker 1: you get older, you don't, you know, loose functionality, but 200 00:12:23,120 --> 00:12:25,959 Speaker 1: it's not due to the size. No. They think that, um, 201 00:12:26,000 --> 00:12:31,720 Speaker 1: it's probably mostly due to really Okay, that you're you're 202 00:12:32,160 --> 00:12:36,240 Speaker 1: synapsies are just kind of built up with gunk remnant 203 00:12:36,240 --> 00:12:39,720 Speaker 1: proteins from years and decades of firings. Then you shake 204 00:12:39,800 --> 00:12:43,880 Speaker 1: that off by continuing to use it. Yes, that's one thing. 205 00:12:43,960 --> 00:12:47,920 Speaker 1: But also they've recently found that, um, while you sleep, 206 00:12:48,120 --> 00:12:51,280 Speaker 1: they think now the function of sleep. They didn't notice 207 00:12:51,280 --> 00:12:53,920 Speaker 1: it before until I don't know what kind of new 208 00:12:54,360 --> 00:12:57,000 Speaker 1: imaging technology they used, but they found out that there's 209 00:12:57,000 --> 00:13:02,400 Speaker 1: this whole channel of like basically a sewage system that 210 00:13:02,559 --> 00:13:05,440 Speaker 1: just clears out all the gunk from your brain while 211 00:13:05,440 --> 00:13:10,000 Speaker 1: you're sleeping at night. And it's just that's why you 212 00:13:10,080 --> 00:13:13,360 Speaker 1: are cognitively refreshed. That makes sense from sleep. And we've 213 00:13:13,400 --> 00:13:16,400 Speaker 1: done we did one on why sleep is important, right, Yes, 214 00:13:16,520 --> 00:13:18,160 Speaker 1: I think that was in there. We've done a bunch. 215 00:13:18,280 --> 00:13:21,240 Speaker 1: There's a whole sleep suite too, alright. So one of 216 00:13:21,280 --> 00:13:25,319 Speaker 1: the reasons why uh people are still debating whether or 217 00:13:25,360 --> 00:13:29,000 Speaker 1: not brain size equals more intelligence or less intelligence is 218 00:13:29,040 --> 00:13:31,760 Speaker 1: because when there are a lot of different ways to 219 00:13:31,800 --> 00:13:36,080 Speaker 1: measure the brain, um, you know, like do you take 220 00:13:36,120 --> 00:13:38,640 Speaker 1: a tape measure and go around it or do you 221 00:13:38,679 --> 00:13:41,320 Speaker 1: go from the middle out or do you do it 222 00:13:41,400 --> 00:13:45,360 Speaker 1: proportioned to your body size, which is a real measurement 223 00:13:45,360 --> 00:13:49,400 Speaker 1: called insephalation quotient. And if they're talking about your body size, 224 00:13:49,400 --> 00:13:53,439 Speaker 1: what if you're super fat? Like, there are all these 225 00:13:53,480 --> 00:13:55,640 Speaker 1: different ways and no one I don't think has ever 226 00:13:55,679 --> 00:13:57,679 Speaker 1: come to a consensus on the best way to actually 227 00:13:57,679 --> 00:13:59,680 Speaker 1: do the measurement in the first place. No. And there's 228 00:13:59,679 --> 00:14:02,840 Speaker 1: another a really big outstanding question is how do you 229 00:14:03,000 --> 00:14:08,840 Speaker 1: measure intelligence? Like our i Q tests actually legitimate. Yeah, 230 00:14:08,840 --> 00:14:12,800 Speaker 1: So when you have two parts of your equation that 231 00:14:12,840 --> 00:14:17,120 Speaker 1: are both hinky, how can you come up with an answer? Well, 232 00:14:17,200 --> 00:14:21,200 Speaker 1: it depends, like if you're comparing species to species, that 233 00:14:21,280 --> 00:14:25,320 Speaker 1: in cephilization quotiation actually has been proven to be pretty effective. 234 00:14:25,960 --> 00:14:31,240 Speaker 1: So like the proportion of your brain to your body 235 00:14:31,320 --> 00:14:34,960 Speaker 1: size is a pretty decent predictor of your e Q 236 00:14:35,320 --> 00:14:38,560 Speaker 1: is what it's called as a mammal. Yes, as as 237 00:14:38,600 --> 00:14:40,800 Speaker 1: a mammal. When you go outside of mammals, it gets 238 00:14:40,880 --> 00:14:45,360 Speaker 1: less and less effective. Um. But with humans, for example, 239 00:14:45,960 --> 00:14:50,560 Speaker 1: we our our brain is like two point seven pounds 240 00:14:50,560 --> 00:14:53,600 Speaker 1: on average, it's something like around two to three. I've 241 00:14:53,600 --> 00:14:55,360 Speaker 1: seen as much as five, but I think it's about 242 00:14:55,440 --> 00:14:59,680 Speaker 1: three percent of our body weight. Um. But it uses 243 00:14:59,720 --> 00:15:03,200 Speaker 1: up a about of the energy, which is another measure 244 00:15:04,320 --> 00:15:07,200 Speaker 1: like how much energy is your brain require? The more 245 00:15:07,360 --> 00:15:11,440 Speaker 1: energy your brain requires. In addition to things like eq, 246 00:15:12,480 --> 00:15:14,520 Speaker 1: you can get a pretty good idea of like how 247 00:15:14,560 --> 00:15:18,320 Speaker 1: intelligent that being is. Well, Einstein's brain remembers this was 248 00:15:18,360 --> 00:15:21,000 Speaker 1: the same size, but different parts were bigger than others. Right, 249 00:15:21,200 --> 00:15:25,040 Speaker 1: so supposedly let's come under fire lately. Yeah, somebody was like, 250 00:15:25,880 --> 00:15:29,240 Speaker 1: these studies are terrible, Like, you can't make these huge 251 00:15:30,000 --> 00:15:34,480 Speaker 1: leaps and bounds and um in conclusions just from a 252 00:15:34,520 --> 00:15:40,200 Speaker 1: couple of strips of brain tissue. But apparently most studies have. 253 00:15:41,000 --> 00:15:42,960 Speaker 1: Well I think that's sort of like a juicy thing 254 00:15:43,080 --> 00:15:45,880 Speaker 1: that people like to talk about Einstein's brain. Yeah, you know, 255 00:15:45,920 --> 00:15:47,840 Speaker 1: I could see people making that leap, right, and the 256 00:15:47,920 --> 00:15:50,320 Speaker 1: idea that like, oh, well, Einstein's brain is just like 257 00:15:50,360 --> 00:15:53,800 Speaker 1: anybody else's, Well, that means that anybody could be a genius. 258 00:15:53,840 --> 00:15:56,640 Speaker 1: You know. It really argues in favor of the nurture 259 00:15:56,760 --> 00:16:00,280 Speaker 1: side of things. But if his brain is structurally different, well, 260 00:16:00,320 --> 00:16:04,080 Speaker 1: the genius is an inborn natural thing. It's just nature 261 00:16:04,160 --> 00:16:08,160 Speaker 1: versus nurture played out on pout. Einstein sliced up brain. Yeah, 262 00:16:08,320 --> 00:16:11,360 Speaker 1: that lived in a garage for many years, like everyone's brain. 263 00:16:11,760 --> 00:16:15,200 Speaker 1: So here's the most controversial thing, Like when you're comparing 264 00:16:15,280 --> 00:16:20,200 Speaker 1: species to species, like you said, especially among mammals, chuck. Um, 265 00:16:20,240 --> 00:16:24,440 Speaker 1: it's easier to say like, yes, this EQ thing works, 266 00:16:24,480 --> 00:16:27,320 Speaker 1: but within a single species that when things starting to 267 00:16:27,360 --> 00:16:33,000 Speaker 1: fall apart, for instance, specifically among humans. Um, men tend 268 00:16:33,040 --> 00:16:36,920 Speaker 1: to have about a hundred grahams more mass to their 269 00:16:36,960 --> 00:16:41,680 Speaker 1: brain than women. But if a bigger brain means that 270 00:16:41,760 --> 00:16:45,480 Speaker 1: you are more intelligent, then does that mean that men 271 00:16:45,520 --> 00:16:47,720 Speaker 1: are more intelligent than women? I think we all know 272 00:16:47,800 --> 00:16:50,160 Speaker 1: that women are more intelligent than men. Okay, so then 273 00:16:50,280 --> 00:16:54,040 Speaker 1: brain size really has nothing to do with it, at 274 00:16:54,080 --> 00:16:58,760 Speaker 1: least intra species, That's what I'm saying. But um, there 275 00:16:58,800 --> 00:17:00,520 Speaker 1: have been plenty of studies that I'm sure got a 276 00:17:00,560 --> 00:17:05,280 Speaker 1: lot of people's hackles up. Um. One guy named Michael McDaniel, 277 00:17:05,320 --> 00:17:11,000 Speaker 1: who's a psychologist, basically entered the news cycle bursting onto 278 00:17:11,000 --> 00:17:13,960 Speaker 1: the scene in two thousand five, which is always a 279 00:17:14,000 --> 00:17:17,159 Speaker 1: little bit like yeah's this guy right, Yeah, But he 280 00:17:17,200 --> 00:17:21,360 Speaker 1: came up with a study that was ready made for CNN. Yeah. 281 00:17:21,400 --> 00:17:24,640 Speaker 1: I mean he said flat out that bigger brains means 282 00:17:24,680 --> 00:17:28,960 Speaker 1: you're smarter and that I E or e G. Which 283 00:17:28,960 --> 00:17:33,240 Speaker 1: one is it? Uh? I EVE in this case, men 284 00:17:33,280 --> 00:17:36,760 Speaker 1: are smarter than women. Yeah, yeah, that's what he was saying. Yeah, 285 00:17:37,119 --> 00:17:41,080 Speaker 1: because he basically put brain imaging tests and i Q 286 00:17:41,320 --> 00:17:46,879 Speaker 1: tests together and said, well, there's a direct correlation between 287 00:17:46,920 --> 00:17:50,800 Speaker 1: the two. And again with these tests they did, uh, 288 00:17:50,960 --> 00:17:54,480 Speaker 1: they compared, Um, they converted s A T scores of 289 00:17:54,480 --> 00:17:57,320 Speaker 1: a hundred thousand seventeen and eighteen year old to an 290 00:17:57,320 --> 00:18:00,080 Speaker 1: ice Q score And I don't see why they and 291 00:18:00,119 --> 00:18:02,320 Speaker 1: had to do that, and they found that males average 292 00:18:02,359 --> 00:18:06,240 Speaker 1: three point six three IQ points higher. But um, I 293 00:18:06,240 --> 00:18:09,000 Speaker 1: don't know. It just seems really hinky because first of all, 294 00:18:09,040 --> 00:18:11,800 Speaker 1: they used ten thousand more females and males, so that's 295 00:18:11,800 --> 00:18:15,560 Speaker 1: gonna excuw things. And then it's an s A T R. 296 00:18:16,119 --> 00:18:18,520 Speaker 1: What does that even mean? Yeah, it has been proven 297 00:18:18,600 --> 00:18:20,520 Speaker 1: time and time again to be biased. Yeah, and then 298 00:18:20,520 --> 00:18:22,760 Speaker 1: they converted that to an i Q source with some 299 00:18:23,040 --> 00:18:25,600 Speaker 1: like I guess machine, seems like some things would be 300 00:18:25,680 --> 00:18:27,920 Speaker 1: lost in translation. Yeah, I think it's a bunch of bunks. 301 00:18:28,119 --> 00:18:30,359 Speaker 1: So yeah, I think you're not alone in the idea 302 00:18:30,400 --> 00:18:32,080 Speaker 1: that it's a bunch of bunks. So a lot of 303 00:18:32,280 --> 00:18:36,479 Speaker 1: um scientists have said, Okay, all right, this whole brain 304 00:18:37,320 --> 00:18:43,720 Speaker 1: size correlating to intelligence stinks of phrenology when you're talking 305 00:18:43,760 --> 00:18:46,560 Speaker 1: about looking at it just in the human species, right, 306 00:18:47,359 --> 00:18:49,880 Speaker 1: So what is it though? I mean, surely there's got 307 00:18:49,880 --> 00:18:55,119 Speaker 1: to be some biological part or aspect of the brain 308 00:18:55,720 --> 00:19:01,320 Speaker 1: that correlates to intelligence. If it's not size in maybe 309 00:19:01,359 --> 00:19:04,919 Speaker 1: it's the number of neurons that you have, Yeah, neural connections. 310 00:19:04,960 --> 00:19:07,400 Speaker 1: A lot of people have thought that that was kind 311 00:19:07,440 --> 00:19:11,639 Speaker 1: of the second to most recent wave in thinking about 312 00:19:12,400 --> 00:19:17,080 Speaker 1: what brain structure correlates to intelligence. Yeah, this um was 313 00:19:17,119 --> 00:19:19,280 Speaker 1: this the New York Times one about the tether hypothesis. 314 00:19:19,840 --> 00:19:22,840 Speaker 1: This is just December of last year, so it's pretty recent. 315 00:19:23,359 --> 00:19:26,840 Speaker 1: And a couple of neuroscientists from HAVID so you know 316 00:19:26,920 --> 00:19:32,399 Speaker 1: they're right. Um, they had a pretty simple explanation. Um, 317 00:19:32,480 --> 00:19:34,840 Speaker 1: when back in the day when tooktok had a little 318 00:19:34,880 --> 00:19:38,520 Speaker 1: bitty tiny brain. Uh. Their argument is that the neurons 319 00:19:38,600 --> 00:19:43,800 Speaker 1: were tightly tethered in a pretty simple connection pattern, and 320 00:19:43,880 --> 00:19:46,520 Speaker 1: that when our brains started getting bigger, those tethers were 321 00:19:46,560 --> 00:19:49,960 Speaker 1: torn apart and it formed h It enabled us, We 322 00:19:50,000 --> 00:19:52,520 Speaker 1: formed new neurons and new neural pathways and new circuits. 323 00:19:53,200 --> 00:19:55,000 Speaker 1: That that makes a lot of sense to me. Yeah, 324 00:19:55,040 --> 00:19:57,480 Speaker 1: it's like the brain size might have been about the same, 325 00:19:57,520 --> 00:20:00,760 Speaker 1: and it was, but the neuro connections were still following 326 00:20:00,840 --> 00:20:06,880 Speaker 1: the primal animal connectivity, where it's like they they connect 327 00:20:06,880 --> 00:20:11,960 Speaker 1: in a predictable way, whereas with this untethered idea, they 328 00:20:12,040 --> 00:20:16,359 Speaker 1: just blossomed out. And do you know the idea of um, 329 00:20:16,440 --> 00:20:19,159 Speaker 1: like like what neuro connections look like today, rather than 330 00:20:19,200 --> 00:20:22,000 Speaker 1: following like straight predictable lines, they were all over the place. 331 00:20:22,240 --> 00:20:25,680 Speaker 1: And from these new connections, new associations arose, and that 332 00:20:26,440 --> 00:20:30,360 Speaker 1: gave rise to intellect. According to this, it's pretty simple smart. Yeah, 333 00:20:30,400 --> 00:20:33,640 Speaker 1: I like, I think sometimes the simplest hypotheses might be 334 00:20:33,720 --> 00:20:36,359 Speaker 1: on target with acam's razor my friend, or maybe they 335 00:20:36,359 --> 00:20:43,720 Speaker 1: just speak to me because I'm a dummy other ball um. 336 00:20:43,760 --> 00:20:48,159 Speaker 1: So that's that is a competing explanation. Another one that 337 00:20:48,240 --> 00:20:53,000 Speaker 1: I've seen, uh says that it's not not the neurons, 338 00:20:53,000 --> 00:20:55,320 Speaker 1: not the number of neurons, not even the number of 339 00:20:55,359 --> 00:20:59,359 Speaker 1: neural connections. It's the chemistry and the complexity of the 340 00:20:59,400 --> 00:21:03,200 Speaker 1: neuro train sbmitters that are being conducted between these neurons, 341 00:21:04,560 --> 00:21:07,120 Speaker 1: and from this has kind of come this new idea 342 00:21:07,240 --> 00:21:11,840 Speaker 1: that it's folly to even say, well, humans are obviously 343 00:21:11,880 --> 00:21:14,880 Speaker 1: smarter than a bottle knows dolphins, even though they're smart, 344 00:21:15,280 --> 00:21:23,560 Speaker 1: because the bottle knows dolphins. Um experience understanding of life 345 00:21:24,800 --> 00:21:27,439 Speaker 1: is so radically different from humans. Yeah, you can't. You 346 00:21:27,480 --> 00:21:30,480 Speaker 1: can't compare intellect to intellect. Yeah you can't say, well, 347 00:21:30,520 --> 00:21:32,720 Speaker 1: a dolphin can't, you know, talk and speak, but I 348 00:21:32,760 --> 00:21:35,679 Speaker 1: can't do things a dolphin can do. Or maybe dolphins 349 00:21:35,760 --> 00:21:38,480 Speaker 1: are speaking, I mean, to one another, just not to us. 350 00:21:38,880 --> 00:21:41,200 Speaker 1: That doesn't make them less intelligent. So long, and thanks 351 00:21:41,200 --> 00:21:42,840 Speaker 1: for all the fish and we're not Yeah, that's a 352 00:21:42,840 --> 00:21:46,440 Speaker 1: good one, and we're not like anthropomorphizing here. Basically, there's 353 00:21:46,600 --> 00:21:52,840 Speaker 1: there is very little um point I guess. Yeah, I 354 00:21:52,880 --> 00:21:56,399 Speaker 1: don't get it to comparing the two. There's tremendous point 355 00:21:56,480 --> 00:22:00,920 Speaker 1: to getting to cracking this code and understanding dolphin intellect 356 00:22:01,280 --> 00:22:05,919 Speaker 1: or bird intellect, degreed octopus intellect and human intellect. But 357 00:22:06,400 --> 00:22:09,880 Speaker 1: to compare them is it's an exercise and futility. There's 358 00:22:09,920 --> 00:22:12,400 Speaker 1: no point to it. I don't get it. Yeah, I mean, 359 00:22:12,480 --> 00:22:16,000 Speaker 1: compared dolphin A to dolphin B one, maybe smarter one 360 00:22:16,040 --> 00:22:18,679 Speaker 1: might have a little patchy mustache and hang out at 361 00:22:18,720 --> 00:22:22,600 Speaker 1: the gas station a lot. And that's not the smart one. Yeah. 362 00:22:22,600 --> 00:22:24,880 Speaker 1: I think people do this to either. I think they're 363 00:22:24,880 --> 00:22:28,240 Speaker 1: trying to claim some either superiority of animals over humans 364 00:22:28,320 --> 00:22:30,600 Speaker 1: or humans over animals, right, And that's kind of that's 365 00:22:30,600 --> 00:22:32,720 Speaker 1: a big issue of these days, Like there there are 366 00:22:32,800 --> 00:22:36,000 Speaker 1: groups um animal rights groups that are trying to further 367 00:22:36,359 --> 00:22:42,160 Speaker 1: animal rights by getting them inalienable rights like humans have right, 368 00:22:42,280 --> 00:22:46,480 Speaker 1: which would really screw up the zoos system. Yeah, you 369 00:22:46,520 --> 00:22:48,840 Speaker 1: can look for a podcast on that too. We did. Yeah, 370 00:22:48,880 --> 00:22:51,399 Speaker 1: that was a good one. I think we landed pretty 371 00:22:51,400 --> 00:22:57,040 Speaker 1: heavily against zoos. Yeah, we did. But to each their own. 372 00:22:58,400 --> 00:23:01,720 Speaker 1: But I haven't been to a zoo since then. What 373 00:23:01,840 --> 00:23:03,960 Speaker 1: is this Project Enigma? I thought that was pretty interesting. 374 00:23:04,440 --> 00:23:07,600 Speaker 1: It was another genetic thing, this um it was. It 375 00:23:07,680 --> 00:23:11,120 Speaker 1: was neat though in that like this Australian researchers said, Hey, 376 00:23:11,160 --> 00:23:13,359 Speaker 1: we have something called internet and m r I S 377 00:23:14,160 --> 00:23:19,200 Speaker 1: and willing participants, so everybody starts sending in your brain scans. 378 00:23:19,400 --> 00:23:21,720 Speaker 1: Is that who proved that the complexity of the neural 379 00:23:21,760 --> 00:23:25,320 Speaker 1: activity was the most important thing? Was that project? No, 380 00:23:25,440 --> 00:23:28,040 Speaker 1: that was a different one. That was there was a 381 00:23:28,119 --> 00:23:34,040 Speaker 1: New Scientist or no Scientific American article that um that 382 00:23:34,240 --> 00:23:39,399 Speaker 1: explored that idea as the the synaptic proteins that create 383 00:23:39,520 --> 00:23:44,439 Speaker 1: intellect or intelligence. But the Project Enigma basically found that 384 00:23:44,480 --> 00:23:50,160 Speaker 1: there is a single mutation on a specific gene where 385 00:23:50,200 --> 00:23:53,640 Speaker 1: if you have a C instead of T, I think 386 00:23:54,480 --> 00:23:57,439 Speaker 1: you um have a bigger brain. And they correlated that 387 00:23:57,520 --> 00:24:02,320 Speaker 1: to more intelligence. Yeah, but again using the i Q test. Well, 388 00:24:02,359 --> 00:24:05,960 Speaker 1: what I'm tired of are the studies that throw out 389 00:24:06,160 --> 00:24:11,120 Speaker 1: the results that don't make a fun headline, you know. Right, 390 00:24:11,240 --> 00:24:14,440 Speaker 1: There was this one um from Smithsonian magazine from December 391 00:24:14,440 --> 00:24:17,560 Speaker 1: of last year that uh, well they it wasn't from them, 392 00:24:17,640 --> 00:24:21,040 Speaker 1: was from the Proceedings of the Royal Society b and 393 00:24:21,119 --> 00:24:24,399 Speaker 1: Smithsonian reported on it. But it was a study of 394 00:24:25,040 --> 00:24:28,480 Speaker 1: country mice and city mice. Well a bunch of animals. 395 00:24:28,800 --> 00:24:32,280 Speaker 1: But they found that city mice and vol I don't 396 00:24:32,280 --> 00:24:34,639 Speaker 1: even know what that is, v l E. Prairie vols? 397 00:24:35,040 --> 00:24:39,400 Speaker 1: What is that? Like? They're very sweet. They they are 398 00:24:39,800 --> 00:24:43,359 Speaker 1: monogamous like a bowl eevil, No, that's a bug. A 399 00:24:43,440 --> 00:24:46,600 Speaker 1: bowl is like a like a prairie dog. You should 400 00:24:46,600 --> 00:24:48,560 Speaker 1: look up prairie balls. Very cute and the idea that 401 00:24:48,600 --> 00:24:52,040 Speaker 1: they're very sweetest, even better. You wouldn't like shoot one 402 00:24:52,080 --> 00:24:54,680 Speaker 1: for being on your property. No, I mean some people would, 403 00:24:54,760 --> 00:24:58,960 Speaker 1: but not good people. I know someone who does that 404 00:24:59,040 --> 00:25:02,240 Speaker 1: kind of thing, shoots at voles, not bowls, but woodchucks 405 00:25:03,320 --> 00:25:07,200 Speaker 1: with with the air rifles. That's not nice. He knows 406 00:25:07,200 --> 00:25:12,199 Speaker 1: who he is. Boom. But this study basically said that 407 00:25:12,560 --> 00:25:17,920 Speaker 1: city mice and city bowls had larger brains than country mice. 408 00:25:18,440 --> 00:25:20,560 Speaker 1: And of course that makes a big headline because people 409 00:25:21,040 --> 00:25:22,800 Speaker 1: are going to try and make the point that, you know, 410 00:25:22,840 --> 00:25:25,040 Speaker 1: people that live in urban environments are smarter and the 411 00:25:25,240 --> 00:25:28,880 Speaker 1: hillbillies out in the country are dumber. They study ten animals, 412 00:25:28,920 --> 00:25:30,640 Speaker 1: only two of them showed that, and some of them 413 00:25:30,640 --> 00:25:35,480 Speaker 1: showed the opposite that the I think bats and shrew's 414 00:25:35,680 --> 00:25:39,160 Speaker 1: actually the country versions had larger brains. So they don't 415 00:25:39,160 --> 00:25:40,800 Speaker 1: say any of that in the study because they just 416 00:25:40,840 --> 00:25:43,199 Speaker 1: want a headline that says, you know, if you live 417 00:25:43,200 --> 00:25:45,440 Speaker 1: in a city, you're smarter. Yeah, and we I mean 418 00:25:45,480 --> 00:25:49,480 Speaker 1: we've been addressing this lately, like there is like a 419 00:25:49,560 --> 00:25:55,359 Speaker 1: symbiotic collusion between bad science and bad science reporting, you know, 420 00:25:55,480 --> 00:25:58,200 Speaker 1: yeah that results and stuff like that, where it's just like, 421 00:25:59,320 --> 00:26:02,840 Speaker 1: you know, city city people are smarter than country people. 422 00:26:03,560 --> 00:26:07,520 Speaker 1: Says this one study that where the data was massaged. Well, 423 00:26:07,520 --> 00:26:10,240 Speaker 1: can you city person, can you go make butter with 424 00:26:10,280 --> 00:26:14,000 Speaker 1: your hands? I have to say, can you farm land? No? 425 00:26:14,359 --> 00:26:19,719 Speaker 1: Of course not um, but there it is possible that 426 00:26:19,760 --> 00:26:25,320 Speaker 1: there's a basis to this. Whereas city people are, their 427 00:26:25,359 --> 00:26:29,399 Speaker 1: brains are more stimulated than country folk perhaps, and so 428 00:26:29,560 --> 00:26:33,240 Speaker 1: more neural connections, more plasticity takes place. I don't I 429 00:26:33,280 --> 00:26:35,520 Speaker 1: don't think that's true. I think there's just as much 430 00:26:35,520 --> 00:26:38,920 Speaker 1: stimulation in nature as there is in a city full 431 00:26:38,960 --> 00:26:41,919 Speaker 1: of people. Spends once you're stimulated by I look at 432 00:26:42,000 --> 00:26:44,480 Speaker 1: Dar when he spent his entire life living in the country. Yeah, 433 00:26:44,520 --> 00:26:47,320 Speaker 1: for sure, But I mean like we're also we also 434 00:26:47,359 --> 00:26:51,480 Speaker 1: have hundreds of thousands of years of latent inhibition built 435 00:26:51,520 --> 00:26:53,680 Speaker 1: up against a lot of the stuff in nature, whereas 436 00:26:53,760 --> 00:26:57,160 Speaker 1: the stuff in Times Square is relatively new, so our 437 00:26:57,160 --> 00:27:00,920 Speaker 1: brain isn't doesn't defend against it quite as easily. So 438 00:27:01,400 --> 00:27:04,159 Speaker 1: hence we're possibly more stimulated. I think it depends on 439 00:27:04,240 --> 00:27:06,760 Speaker 1: what you're doing with your time. Sure, if you're out 440 00:27:06,800 --> 00:27:10,520 Speaker 1: the country sitting around watching reality TV. If you're in 441 00:27:11,920 --> 00:27:15,320 Speaker 1: your apartment watching reality TV. I found this other study 442 00:27:15,320 --> 00:27:19,679 Speaker 1: today to um from Germany about pornography may reduce your 443 00:27:19,680 --> 00:27:24,920 Speaker 1: brain size. Another kind of sexy headline, right and um 444 00:27:25,160 --> 00:27:29,320 Speaker 1: sample size at three And it's always self reported to 445 00:27:29,480 --> 00:27:32,399 Speaker 1: and when you're dealing with porn and self reporting, do 446 00:27:32,520 --> 00:27:35,320 Speaker 1: you look at check the box? Do you think your 447 00:27:35,359 --> 00:27:39,479 Speaker 1: brain is small? Check the boom? Yeah? How smart are you? 448 00:27:39,680 --> 00:27:42,920 Speaker 1: Somebody called the Uh they cannot say that watching porn 449 00:27:42,960 --> 00:27:45,800 Speaker 1: caused a decrease in brain matter, but they did say 450 00:27:45,800 --> 00:27:49,480 Speaker 1: they found that the volume of striatom, a brain region 451 00:27:49,480 --> 00:27:53,920 Speaker 1: that's been associated with reward processing and motivated behavior, was 452 00:27:54,080 --> 00:27:59,280 Speaker 1: smaller the more pornography you consumed. And basically where they're 453 00:27:59,320 --> 00:28:02,439 Speaker 1: at is we don't know whether it's causing this or 454 00:28:02,480 --> 00:28:05,879 Speaker 1: if people did. Oh yeah, they gets struck dumb and 455 00:28:05,920 --> 00:28:09,200 Speaker 1: they're like, yeah, they're just end up watching porn more 456 00:28:10,320 --> 00:28:14,840 Speaker 1: like in Idiocracy again that movie. There's probably been no 457 00:28:14,960 --> 00:28:18,120 Speaker 1: other movie that's made more of a legitimate appearance in 458 00:28:18,160 --> 00:28:23,080 Speaker 1: our episodes than that MOVIECCY, Yeah, yeah, I think you're right. Yeah, 459 00:28:23,119 --> 00:28:26,359 Speaker 1: my judge, he's onto something. Do you watch Silicon Valley? 460 00:28:26,600 --> 00:28:30,800 Speaker 1: I haven't I know. Uh, Kamal nan Giani's in it. Yeah, 461 00:28:30,840 --> 00:28:33,560 Speaker 1: he's funny. Does he do well? Yeah, Martin Starr, it's 462 00:28:33,680 --> 00:28:36,280 Speaker 1: uh yeah, it's a good show. Nice, it's I think 463 00:28:36,280 --> 00:28:38,000 Speaker 1: it was high time that someone took on the tech 464 00:28:38,040 --> 00:28:41,240 Speaker 1: industry and like a comedy like that. Yeah, leave it 465 00:28:41,280 --> 00:28:45,560 Speaker 1: to Mike Judge. I know if there's any crusader crusader 466 00:28:45,640 --> 00:28:51,480 Speaker 1: people feeling good about, right, Yeah, it's Judge. Uh. If 467 00:28:51,600 --> 00:28:55,920 Speaker 1: you want to know more about brain size in relation 468 00:28:56,000 --> 00:28:59,920 Speaker 1: to whatever, just type in brain in the search part house. 469 00:29:00,000 --> 00:29:02,959 Speaker 1: So first dot com and it's get lost. That's what 470 00:29:03,000 --> 00:29:06,360 Speaker 1: I say. Type in brain and just go on a trip. Man. 471 00:29:07,040 --> 00:29:11,160 Speaker 1: All right, that's right. Journey. I think that's the slogan 472 00:29:11,280 --> 00:29:14,840 Speaker 1: for how stuff works. That's right, um answers, I said, 473 00:29:14,840 --> 00:29:17,760 Speaker 1: search far as the time for what? Listener mail? Yes, okay, 474 00:29:19,200 --> 00:29:22,600 Speaker 1: I'm gonna call this help for a fan in need. 475 00:29:23,120 --> 00:29:25,360 Speaker 1: It's hey, guys, I want some help please. My wife 476 00:29:25,360 --> 00:29:27,400 Speaker 1: and I are expecting our first kid this summer, and 477 00:29:27,480 --> 00:29:29,760 Speaker 1: thirteen days ago we also found out that my wife 478 00:29:29,760 --> 00:29:33,160 Speaker 1: has staged four breast cancer. So we are spending our 479 00:29:33,160 --> 00:29:37,040 Speaker 1: third trimester getting chemo. My goodness, I know, Uh, We're 480 00:29:37,040 --> 00:29:38,800 Speaker 1: gonna kick cancer in the butt, we have no doubt, 481 00:29:38,880 --> 00:29:42,440 Speaker 1: but we're scared and overwhelmed. Obviously, we're doing chemo now. 482 00:29:42,560 --> 00:29:45,560 Speaker 1: Then we'll have the baby get more chemo than bilateral 483 00:29:45,720 --> 00:29:49,000 Speaker 1: mastectomy than radiation. We have great doctors and great fins 484 00:29:49,040 --> 00:29:51,080 Speaker 1: and families. So even in the face of this, we 485 00:29:51,120 --> 00:29:53,920 Speaker 1: feel very lucky. Uh. And by the way, I gotta 486 00:29:53,960 --> 00:29:59,160 Speaker 1: follow up more recently. That says, uh, there is no 487 00:29:59,320 --> 00:30:02,720 Speaker 1: gestational ibtes and the cancer is already shrinking. Oh, it's great. 488 00:30:02,800 --> 00:30:04,840 Speaker 1: So thanks are going great so far. Thanks for keeping 489 00:30:04,920 --> 00:30:06,840 Speaker 1: us in suspense. I know I was gonna wait till 490 00:30:06,840 --> 00:30:09,120 Speaker 1: the end. Uh. And he asked for a couple of favors. 491 00:30:09,120 --> 00:30:10,680 Speaker 1: He said, First of all, if you want to follow 492 00:30:10,720 --> 00:30:13,560 Speaker 1: and promote my tumbler, uh to keep people updated, it 493 00:30:13,680 --> 00:30:18,040 Speaker 1: is um h T t P colon slash slash gala 494 00:30:18,120 --> 00:30:23,080 Speaker 1: freaki diky g A l l i U f r 495 00:30:23,120 --> 00:30:25,760 Speaker 1: e k y d e e k y dot tumbler 496 00:30:25,800 --> 00:30:29,560 Speaker 1: dot com. He says, we're huge nerds and doctor who fans. 497 00:30:29,560 --> 00:30:32,360 Speaker 1: So that was lost on me some doctor who reference, 498 00:30:32,400 --> 00:30:34,280 Speaker 1: I guess apparently, so does that have to do with 499 00:30:34,320 --> 00:30:36,760 Speaker 1: the phone booth. Maybe that's the only thing you know 500 00:30:36,760 --> 00:30:40,920 Speaker 1: about same here. Um. Secondly, I'm biking a hundred and 501 00:30:40,920 --> 00:30:44,360 Speaker 1: fifty miles to raise money, and could you plug that? 502 00:30:44,480 --> 00:30:46,960 Speaker 1: And you can go to g O O dot g 503 00:30:47,280 --> 00:30:52,800 Speaker 1: L slash two w j z x Q. People don't 504 00:30:52,800 --> 00:30:55,080 Speaker 1: like normal words, well that's one of those shortened U 505 00:30:55,160 --> 00:30:58,960 Speaker 1: R l oh. I see it's a google. Uh. And 506 00:30:58,960 --> 00:31:00,680 Speaker 1: then third, how about a shout out. I think that's 507 00:31:00,680 --> 00:31:02,800 Speaker 1: what we're doing here. My wife is a little shy, 508 00:31:02,880 --> 00:31:08,560 Speaker 1: so just use her nickname the mayor. That's hilarious. Whereas 509 00:31:08,560 --> 00:31:11,520 Speaker 1: a sash during chemo and childbirth. I guess, so, I mean, 510 00:31:11,560 --> 00:31:13,960 Speaker 1: I call Emily the boss, so I guess it's the mayor. 511 00:31:15,080 --> 00:31:17,600 Speaker 1: But the mayor is like the boss of several bosses, 512 00:31:17,600 --> 00:31:19,880 Speaker 1: I would guess. Yeah. We used to call my friend 513 00:31:19,920 --> 00:31:22,440 Speaker 1: Justin who you know, the mayor of Atlanta, because everywhere 514 00:31:22,440 --> 00:31:25,720 Speaker 1: he went nobody knew him. He's a fellow. But now 515 00:31:25,720 --> 00:31:28,040 Speaker 1: we just call him the manager of Atlanta because everywhere 516 00:31:28,080 --> 00:31:30,760 Speaker 1: you go he has some improvement to that place, like 517 00:31:30,800 --> 00:31:32,560 Speaker 1: the lighting is not quite right, or the door should 518 00:31:32,560 --> 00:31:38,280 Speaker 1: be over there, the kitchen is not located properly Brits Yeah. Uh. 519 00:31:38,320 --> 00:31:40,920 Speaker 1: And then forth, my wife works in public policy, specifically 520 00:31:40,920 --> 00:31:43,720 Speaker 1: helping women and families get themselves out of poverty and 521 00:31:43,760 --> 00:31:47,000 Speaker 1: advocating for low income workers. So there you have it. 522 00:31:47,040 --> 00:31:49,880 Speaker 1: An awesome an incredible woman who dedicates her considerable talents 523 00:31:50,160 --> 00:31:53,239 Speaker 1: helping others. He's pregnant and his breast cancer. Kind of 524 00:31:53,240 --> 00:31:55,520 Speaker 1: hard to say no, right, I'm not above guilt tripping. 525 00:31:56,360 --> 00:32:01,040 Speaker 1: So Bob from Swithmore, Pennsylvania. UM, there you go. People 526 00:32:01,040 --> 00:32:02,840 Speaker 1: should go and check out that stuff and support your 527 00:32:02,880 --> 00:32:05,720 Speaker 1: bike ride. And I hope things have continued to progress 528 00:32:05,760 --> 00:32:09,800 Speaker 1: well for your wife and child and keep us updated. Yeah, 529 00:32:09,960 --> 00:32:12,680 Speaker 1: and you keep me updated at the very least. If 530 00:32:12,680 --> 00:32:16,600 Speaker 1: not everybody listening, I will. Okay, thanks a lot, Bob 531 00:32:16,800 --> 00:32:20,760 Speaker 1: and the mayor, good luck to you both. And um, 532 00:32:20,840 --> 00:32:22,520 Speaker 1: let's see if you want to get in touch with us, 533 00:32:23,000 --> 00:32:28,000 Speaker 1: whether you're a mayor a provincial governor who knows, you 534 00:32:28,040 --> 00:32:30,600 Speaker 1: can get in touch with us on Twitter at s 535 00:32:30,720 --> 00:32:33,760 Speaker 1: Y s K podcast. You can join us on Facebook 536 00:32:33,800 --> 00:32:36,120 Speaker 1: dot com slash stuff you Should Know. You can send 537 00:32:36,160 --> 00:32:39,320 Speaker 1: us an email to Stuff Podcast at how stuff Works 538 00:32:39,360 --> 00:32:42,280 Speaker 1: dot com and join us at our home on the web, 539 00:32:42,760 --> 00:32:49,800 Speaker 1: Stuff you Should Know dot com. For more on this 540 00:32:49,960 --> 00:32:52,480 Speaker 1: and thousands of other topics. Is it how stuff Works 541 00:32:52,480 --> 00:33:00,000 Speaker 1: dot com