1 00:00:03,120 --> 00:00:06,000 Speaker 1: Welcome to Stuff to Blow Your Mind from how Stuff 2 00:00:06,000 --> 00:00:13,560 Speaker 1: Works dot Com. Hey, everybody, wasn't the Stuff to Blow 3 00:00:13,560 --> 00:00:16,160 Speaker 1: Your Mind? My name is Robert Lamb and I'm Julie Douglas. 4 00:00:16,239 --> 00:00:18,960 Speaker 1: It is Halloween weak here at Stuff to Blow Your 5 00:00:18,960 --> 00:00:20,840 Speaker 1: Mind and then the rest of the world really to 6 00:00:20,880 --> 00:00:23,400 Speaker 1: be honest, and so we wanted to roll out a 7 00:00:23,440 --> 00:00:26,239 Speaker 1: couple of our favorite Halloween episodes. So today we are 8 00:00:26,280 --> 00:00:30,520 Speaker 1: resurrecting the science of Uncanny Music, which is one of 9 00:00:30,520 --> 00:00:33,160 Speaker 1: our favorites and one that we've received a lot of 10 00:00:33,159 --> 00:00:36,280 Speaker 1: of praise for from listeners. So we thought, hey, let's 11 00:00:36,280 --> 00:00:38,680 Speaker 1: bring it back. Yeah, if I remember correctly, this, this 12 00:00:38,720 --> 00:00:43,159 Speaker 1: is when we explore the violent streams in Psycho and 13 00:00:43,200 --> 00:00:47,040 Speaker 1: the psychological effect, which is pretty interesting because can you 14 00:00:47,080 --> 00:00:52,479 Speaker 1: imagine a world without Psycho and that? Yeah, yeah, we 15 00:00:52,520 --> 00:00:54,960 Speaker 1: really get to the question, you know, is the is 16 00:00:54,960 --> 00:00:58,040 Speaker 1: the music in Psycho scary in and of itself or 17 00:00:58,080 --> 00:01:01,760 Speaker 1: is it dependent entirely upon the movie that you're watching, 18 00:01:02,160 --> 00:01:04,040 Speaker 1: or is it some shade of gray between the two? 19 00:01:04,440 --> 00:01:11,160 Speaker 1: Find out. Since this is the Halloween season and we're 20 00:01:11,160 --> 00:01:18,039 Speaker 1: talking about creepy, uncanny, scary, frightening sonic experiences, let's kick 21 00:01:18,080 --> 00:01:20,800 Speaker 1: this episode off with just a little bit of the 22 00:01:20,920 --> 00:01:45,319 Speaker 1: uncanny from the Weirding Module. We should talk about this 23 00:01:45,360 --> 00:01:48,560 Speaker 1: weird module. Yes, yeah, just yeah, real quick, this is 24 00:01:48,680 --> 00:01:51,160 Speaker 1: the Weirding Module. This is a solo project from musician 25 00:01:51,240 --> 00:01:54,160 Speaker 1: Christopher Gladwin uh as soon as you may name, is 26 00:01:54,200 --> 00:01:59,360 Speaker 1: one half of Team do Yobi and very accomplished musician 27 00:01:59,400 --> 00:02:01,600 Speaker 1: has his hands in a number of different projects, but 28 00:02:01,680 --> 00:02:05,640 Speaker 1: this one is all about the uncanny, about at times 29 00:02:05,680 --> 00:02:11,040 Speaker 1: the frightening, the unsettling. This particular track was titled Chapter 30 00:02:11,120 --> 00:02:15,359 Speaker 1: one Abysmal Cathedrals Arise from mel flurious ire from some 31 00:02:15,560 --> 00:02:18,960 Speaker 1: less regions. And right there that gives you a clue. Yeah, 32 00:02:18,960 --> 00:02:21,320 Speaker 1: it gives you a clue. And uh and if you 33 00:02:21,320 --> 00:02:25,440 Speaker 1: recognize the tune, and that's because he's utilizing Symphony Fantastic 34 00:02:25,720 --> 00:02:30,359 Speaker 1: from Hector Berlioz. And you may also recognize it because 35 00:02:30,560 --> 00:02:33,359 Speaker 1: Wendy Carlos used it in the theme to The Shining. 36 00:02:34,400 --> 00:02:37,440 Speaker 1: So what we are introducing to you today is this 37 00:02:37,520 --> 00:02:43,160 Speaker 1: idea that a scary movie could perhaps be less scary 38 00:02:43,280 --> 00:02:46,040 Speaker 1: or not even scary without the sort of soundtrack that 39 00:02:46,080 --> 00:02:50,200 Speaker 1: goes along with it, really amping up our experiences while 40 00:02:50,200 --> 00:02:53,400 Speaker 1: we're watching something on the screen, and when you listen 41 00:02:53,480 --> 00:02:56,600 Speaker 1: to something like the Weirding Module, you can already start 42 00:02:56,680 --> 00:02:59,760 Speaker 1: to sense that this ease, that that sort of d 43 00:03:00,080 --> 00:03:02,480 Speaker 1: centering that that music makes you feel with some of 44 00:03:02,520 --> 00:03:05,760 Speaker 1: the chords and some of the ways that it's arranged. Yeah, 45 00:03:05,840 --> 00:03:07,639 Speaker 1: so it it raises the question, and this is the 46 00:03:07,680 --> 00:03:10,240 Speaker 1: question we're gonna explore in this episode to what extent 47 00:03:10,600 --> 00:03:14,720 Speaker 1: is there something just innately creepy, uncanny, scary, frightening about 48 00:03:14,960 --> 00:03:18,720 Speaker 1: music like this or is it all cultural? Is it 49 00:03:18,760 --> 00:03:21,600 Speaker 1: all contextual? So we're gonna unravel that. But but first, 50 00:03:22,600 --> 00:03:24,560 Speaker 1: just to to to rehash, we did an episode of 51 00:03:24,560 --> 00:03:26,440 Speaker 1: a while back called music on the Brain where we 52 00:03:26,440 --> 00:03:29,720 Speaker 1: talked about the various ways that didn't music Uh speaks 53 00:03:29,720 --> 00:03:32,320 Speaker 1: to us on a conscious and subconscious level. Uh, And 54 00:03:32,480 --> 00:03:34,720 Speaker 1: we have to think about music and stuff. What is music? 55 00:03:35,080 --> 00:03:36,720 Speaker 1: You know? It's obviously it's a deep part of our 56 00:03:36,720 --> 00:03:40,880 Speaker 1: cognitive architecture. It changes our mood, it heightens our emotions. Uh. 57 00:03:40,880 --> 00:03:44,000 Speaker 1: And we'd have to find a culture that didn't or 58 00:03:44,120 --> 00:03:47,640 Speaker 1: doesn't have it. And some evidence even suggests that the Neanderthals, 59 00:03:47,920 --> 00:03:50,960 Speaker 1: in absence of language, may have used music as a 60 00:03:51,000 --> 00:03:54,680 Speaker 1: means of communication. Um. Indeed, there are also parts of 61 00:03:54,680 --> 00:03:57,640 Speaker 1: the brain that respond to music. They don't respond to languid, 62 00:03:57,880 --> 00:03:59,920 Speaker 1: separate parts of the brain that respond to the male 63 00:04:00,000 --> 00:04:02,280 Speaker 1: pality of language, different from the parts that respond to 64 00:04:02,280 --> 00:04:06,600 Speaker 1: the melody of music. So music is really kind of 65 00:04:06,640 --> 00:04:09,120 Speaker 1: this uncanny thing in and of itself. Yeah. I like 66 00:04:09,160 --> 00:04:12,280 Speaker 1: to bring up cognitive psychologists and ling with Stephen Pinker 67 00:04:12,360 --> 00:04:15,440 Speaker 1: because he's the guy who he's probably pretty brilliant guy, 68 00:04:15,480 --> 00:04:19,520 Speaker 1: but he did say music is just auditory cheesecake, an 69 00:04:19,560 --> 00:04:23,800 Speaker 1: accident of evolution. But when we look at music a 70 00:04:23,839 --> 00:04:26,520 Speaker 1: little bit deeper than we really begin to see that 71 00:04:26,680 --> 00:04:29,599 Speaker 1: the case that was made in the documentary The Music 72 00:04:29,640 --> 00:04:34,000 Speaker 1: Instinct with Bobby McFerrin, that music actually maybe a precursor 73 00:04:34,080 --> 00:04:37,520 Speaker 1: to languages. You had said, um is there because you 74 00:04:37,520 --> 00:04:40,760 Speaker 1: think about music and there's no one music center in 75 00:04:40,800 --> 00:04:43,680 Speaker 1: our brains. And as you had said, their music used 76 00:04:43,720 --> 00:04:46,600 Speaker 1: a certain parts of our brain that language doesn't. UM. 77 00:04:46,720 --> 00:04:49,640 Speaker 1: One of the parts that music recruits, and I think 78 00:04:49,680 --> 00:04:52,640 Speaker 1: this is so interesting is the visual cortext And it's 79 00:04:52,680 --> 00:04:55,640 Speaker 1: thought that the visual cortex actually maps a visual of 80 00:04:55,680 --> 00:04:59,240 Speaker 1: how the pitch and tone are changing, and in turn, 81 00:04:59,360 --> 00:05:02,720 Speaker 1: music moves us literally moves us. We dance to it 82 00:05:02,760 --> 00:05:06,520 Speaker 1: because we envision the movement in it. So keep that 83 00:05:06,560 --> 00:05:08,680 Speaker 1: in mind as we continue to talk a little bit 84 00:05:08,720 --> 00:05:12,280 Speaker 1: more about music and how it manipulates this um, and 85 00:05:12,440 --> 00:05:15,920 Speaker 1: particularly spooky music, how that might motivate us. The manipulation 86 00:05:16,000 --> 00:05:19,159 Speaker 1: is key here because when when music psychologists talk about 87 00:05:19,360 --> 00:05:23,880 Speaker 1: music and emotion, they often distinguished between emotion perception, which 88 00:05:23,920 --> 00:05:26,880 Speaker 1: refers to the perception of emotions expressed by the music. 89 00:05:26,960 --> 00:05:31,360 Speaker 1: Like oh um, the sprint the boss is singing about 90 00:05:31,400 --> 00:05:34,520 Speaker 1: some sort of sad working class story and run in 91 00:05:34,600 --> 00:05:37,320 Speaker 1: with the law. That's a sad story. The song is sad. 92 00:05:37,600 --> 00:05:39,839 Speaker 1: I'm interpreting the sadness of it. Can you say the 93 00:05:39,839 --> 00:05:42,800 Speaker 1: boss you're talking about? Of course, of course he's still 94 00:05:42,800 --> 00:05:44,400 Speaker 1: the boss. I don't I don't think he's that that 95 00:05:44,440 --> 00:05:47,480 Speaker 1: position has has not been vacated yet. Uh. And then 96 00:05:47,480 --> 00:05:50,440 Speaker 1: there But then there's emotion induction, and this refers to 97 00:05:50,520 --> 00:05:53,680 Speaker 1: the listeners effective response to the music. But I think 98 00:05:53,720 --> 00:05:56,560 Speaker 1: it's interesting about this. It's not just the emotional arousal. 99 00:05:56,720 --> 00:06:00,520 Speaker 1: It's that we actually will show a physical demonstration of emotion. 100 00:06:01,240 --> 00:06:03,640 Speaker 1: And there's a two thousand and nine study of twenty 101 00:06:03,680 --> 00:06:07,600 Speaker 1: six people who it turns out for a strong correlation 102 00:06:07,680 --> 00:06:12,160 Speaker 1: between subjective emotional response and objective physical response to music. 103 00:06:12,240 --> 00:06:15,880 Speaker 1: The paper is called the Rewarding Aspects of music listening 104 00:06:15,880 --> 00:06:18,440 Speaker 1: are related to a degree of emissional arousal, and it 105 00:06:18,480 --> 00:06:22,320 Speaker 1: details the chills that someone can feel when they're listening 106 00:06:22,360 --> 00:06:25,960 Speaker 1: to something flesh, whatever you want to call it, and 107 00:06:26,200 --> 00:06:28,479 Speaker 1: have you you yourself experience this when you listen to 108 00:06:28,520 --> 00:06:32,280 Speaker 1: any music. Um, I think the one that comes to 109 00:06:32,400 --> 00:06:37,440 Speaker 1: mind is um Centerman by Nana Simone, and I'm talking 110 00:06:37,480 --> 00:06:40,080 Speaker 1: about the live version. It's like a ten minute long song. 111 00:06:40,279 --> 00:06:45,279 Speaker 1: It is Actually you don't want me to do that, 112 00:06:45,320 --> 00:06:47,440 Speaker 1: because I would do that for ten minutes gonna be insane. 113 00:06:47,720 --> 00:06:50,560 Speaker 1: But if you listen to that piece of music, it's 114 00:06:50,560 --> 00:06:54,119 Speaker 1: a rollicking right of emotions and the piano just gets 115 00:06:54,160 --> 00:06:57,360 Speaker 1: crazy at some points, and it's a it's a very 116 00:06:57,400 --> 00:07:01,440 Speaker 1: emotional song and there's um a lot of syncopated rhythm 117 00:07:01,520 --> 00:07:03,719 Speaker 1: with the clapping which is a stand in for the 118 00:07:03,720 --> 00:07:06,640 Speaker 1: percussion in it. Very nice. Well, well, I was trying 119 00:07:06,640 --> 00:07:08,800 Speaker 1: to think of songs that have the similar effect on me, 120 00:07:09,160 --> 00:07:12,559 Speaker 1: and for my own part, radioheads everything in its right place. 121 00:07:12,960 --> 00:07:15,480 Speaker 1: Every time I listened to that, particularly just the first 122 00:07:15,880 --> 00:07:19,960 Speaker 1: few seconds of it, when with this kind of cascade 123 00:07:20,000 --> 00:07:23,800 Speaker 1: of notes, sort of finding synchronicity like that always gives 124 00:07:23,800 --> 00:07:26,200 Speaker 1: me chill bumps. Again, I think if you stay cascading 125 00:07:26,200 --> 00:07:28,840 Speaker 1: and there's that movement, yeah, it's definitely the movement of 126 00:07:28,840 --> 00:07:31,320 Speaker 1: the music, and and my body moves with it. I 127 00:07:31,360 --> 00:07:33,679 Speaker 1: just get to get the chills every time. These twenty 128 00:07:33,720 --> 00:07:37,640 Speaker 1: six people who underwent this experiment, well machines measured their 129 00:07:37,720 --> 00:07:41,680 Speaker 1: heart rate, respiration rate, body temperature, and galvanic skin response. 130 00:07:41,760 --> 00:07:44,320 Speaker 1: This is how much basically they were sweating in response 131 00:07:44,360 --> 00:07:48,320 Speaker 1: to the music and their blood volume pulse and uh. 132 00:07:48,880 --> 00:07:52,080 Speaker 1: They were asked to click a button every time that 133 00:07:52,120 --> 00:07:56,680 Speaker 1: they felt really aroused. And so number four, they're four 134 00:07:56,680 --> 00:08:00,360 Speaker 1: clicking button was the button that correlated with chills. And 135 00:08:00,400 --> 00:08:03,200 Speaker 1: so they found that the chills occurred at the highest 136 00:08:03,200 --> 00:08:06,560 Speaker 1: moment of pleasure reported I think that's interesting that it's 137 00:08:06,600 --> 00:08:09,760 Speaker 1: a pleasurable response and yet chills is the expression of 138 00:08:09,800 --> 00:08:12,920 Speaker 1: the body. Yeah, you're you're intensely satisfied by the music, 139 00:08:12,960 --> 00:08:16,160 Speaker 1: but it's giving giving you chills. Um. And there's another 140 00:08:16,160 --> 00:08:17,960 Speaker 1: study we looked at here from You're All just Jack 141 00:08:18,040 --> 00:08:21,520 Speaker 1: Panckship of Bowling Green State University. This one's interesting because 142 00:08:21,520 --> 00:08:24,280 Speaker 1: he found that people listening to music often experienced goose 143 00:08:24,320 --> 00:08:27,480 Speaker 1: bumps because of sad feelings more so than happy or 144 00:08:27,520 --> 00:08:30,000 Speaker 1: excited emotions. But a lot of this came down to 145 00:08:30,360 --> 00:08:35,240 Speaker 1: um melancholy associations with the past, which which is kind 146 00:08:35,280 --> 00:08:37,680 Speaker 1: of like, you know, getting into the context issue of 147 00:08:37,720 --> 00:08:40,320 Speaker 1: all of this. For instance, that song that you listen 148 00:08:40,400 --> 00:08:42,760 Speaker 1: to a hundred times in a row during a breakup, 149 00:08:43,120 --> 00:08:46,320 Speaker 1: you listen to it ten years later. You don't care 150 00:08:46,600 --> 00:08:49,320 Speaker 1: the least bit about that individual, but that music can 151 00:08:49,360 --> 00:08:51,360 Speaker 1: still stir something and there's a bit of nostalgi in 152 00:08:51,360 --> 00:08:53,480 Speaker 1: that as well. You know, it sort of sucks you 153 00:08:53,520 --> 00:08:56,559 Speaker 1: back a little bit into that emotional state. It wasn't. 154 00:08:56,600 --> 00:08:59,760 Speaker 1: The idea behind that is that the listener is filling 155 00:08:59,840 --> 00:09:03,679 Speaker 1: us logic or sad because they and having these bumps 156 00:09:03,720 --> 00:09:07,840 Speaker 1: as a response because they physically are missing the warmth 157 00:09:07,840 --> 00:09:10,760 Speaker 1: of that person. Yes, the researcher argues that music and 158 00:09:10,800 --> 00:09:13,640 Speaker 1: news chills are tied into the chemicals released in our 159 00:09:13,640 --> 00:09:16,960 Speaker 1: brain to deal with social loss. So the idea is 160 00:09:17,040 --> 00:09:20,040 Speaker 1: that our ancient ancestors might have experienced as if they 161 00:09:20,040 --> 00:09:22,720 Speaker 1: are separated from a family member all right, you you 162 00:09:22,760 --> 00:09:25,520 Speaker 1: wander off, and then the cries you hear in the 163 00:09:25,520 --> 00:09:28,880 Speaker 1: air of of of of the lost family members that 164 00:09:28,880 --> 00:09:31,520 Speaker 1: that will call it cause a chill inside you and 165 00:09:31,559 --> 00:09:33,760 Speaker 1: cause you to have this desire to reach out to 166 00:09:33,800 --> 00:09:36,320 Speaker 1: the warmth of others. And I thought it was interesting 167 00:09:36,360 --> 00:09:39,520 Speaker 1: that this was the response, that these chill bumps, even 168 00:09:40,040 --> 00:09:42,640 Speaker 1: for someone who would be singing or listening to the 169 00:09:42,640 --> 00:09:46,000 Speaker 1: Star Spangled Banner. And I thought, Okay, that's a little 170 00:09:46,040 --> 00:09:48,600 Speaker 1: bit odd. But when you a little cheesy, no, it's fine, 171 00:09:48,640 --> 00:09:51,960 Speaker 1: it's fine, it's nice, it's nice. But if you peel 172 00:09:52,040 --> 00:09:54,400 Speaker 1: that back a little bit, and then you can say, okay, 173 00:09:54,440 --> 00:09:58,120 Speaker 1: well what is it to be to be moved by 174 00:09:58,200 --> 00:10:02,120 Speaker 1: that song? You feel united with your countrymen and country women. 175 00:10:02,559 --> 00:10:06,040 Speaker 1: So in a sense, there there's that community based longing. Well, 176 00:10:06,080 --> 00:10:08,600 Speaker 1: it's like with with with so many issues we've discussed. 177 00:10:08,720 --> 00:10:11,360 Speaker 1: You can find the sort of core of like ancestral 178 00:10:11,400 --> 00:10:14,760 Speaker 1: animal organism sense to what happens, but then you pile 179 00:10:14,920 --> 00:10:19,160 Speaker 1: enough layers of human complexity and human cognition and it 180 00:10:19,280 --> 00:10:21,640 Speaker 1: just turns it into a maze. Yeah, And just to 181 00:10:21,760 --> 00:10:23,920 Speaker 1: further compound that the maze too, of course, we're going 182 00:10:24,000 --> 00:10:25,959 Speaker 1: to have to look back at the brain because I 183 00:10:26,000 --> 00:10:28,400 Speaker 1: want to look at the amygdala for a moment, in 184 00:10:28,440 --> 00:10:32,840 Speaker 1: particular when we talk about scary music, because the amygdala, 185 00:10:32,880 --> 00:10:37,079 Speaker 1: as we know, processes emotion, memory, fear, and to test 186 00:10:37,120 --> 00:10:39,760 Speaker 1: out the theory that certain strains of music can ramp 187 00:10:39,840 --> 00:10:43,480 Speaker 1: up or dial down the fear response, researchers in Oxford, 188 00:10:43,520 --> 00:10:47,160 Speaker 1: England played different kinds of music for people's who who'se 189 00:10:47,240 --> 00:10:51,160 Speaker 1: amygdala's had been removed because of an illness or an accident, 190 00:10:51,760 --> 00:10:53,800 Speaker 1: and then people without this part of the brain the 191 00:10:53,840 --> 00:10:58,040 Speaker 1: actually had trouble recognizing scary music, whereas people with their 192 00:10:58,040 --> 00:11:03,760 Speaker 1: amygdala's intact had a definite response when scary music was played, 193 00:11:03,880 --> 00:11:06,920 Speaker 1: as shown by the brain scanners. So again there's an 194 00:11:07,000 --> 00:11:09,120 Speaker 1: idea that there's so many different parts from your brain 195 00:11:09,200 --> 00:11:12,520 Speaker 1: that are weighing in on the notes that you hear. Now, 196 00:11:12,559 --> 00:11:14,520 Speaker 1: I know what in a reviewer probably wondering to what 197 00:11:14,559 --> 00:11:18,160 Speaker 1: extent is it contextual? Is it cultural? Um For instance, 198 00:11:18,280 --> 00:11:20,120 Speaker 1: the music we heard at the top of the the 199 00:11:20,240 --> 00:11:23,400 Speaker 1: program um A, it's by an act known as the 200 00:11:23,440 --> 00:11:25,559 Speaker 1: weirding modul So some of you would if you hear 201 00:11:25,640 --> 00:11:29,240 Speaker 1: that you interpret this kind of strange sounding name you're 202 00:11:29,280 --> 00:11:32,320 Speaker 1: bringing that into the game, or you're recognizing the piece 203 00:11:32,360 --> 00:11:35,360 Speaker 1: of music sample in the work as a as being 204 00:11:35,360 --> 00:11:37,640 Speaker 1: familiar to something in the shining. We're bringing all this context, 205 00:11:37,679 --> 00:11:39,680 Speaker 1: we're bringing all this culture, and so of course we 206 00:11:39,720 --> 00:11:43,080 Speaker 1: interpret it as creepy. So if you were to play 207 00:11:43,280 --> 00:11:46,360 Speaker 1: creepy music for someone who had zero experience with any 208 00:11:46,360 --> 00:11:49,000 Speaker 1: of that, would they still find it scary. You're talking 209 00:11:49,000 --> 00:11:52,280 Speaker 1: about the study of the MafA people in Cameroon who 210 00:11:52,320 --> 00:11:57,120 Speaker 1: had never ever heard any sort of strains of Western music, 211 00:11:57,600 --> 00:12:01,280 Speaker 1: and they were introduced to three Western musical clips. One 212 00:12:01,520 --> 00:12:05,040 Speaker 1: that is typically thought to be sad, one that's happy, 213 00:12:05,120 --> 00:12:08,199 Speaker 1: and one that's spooky. All three examples. By the way, 214 00:12:08,200 --> 00:12:11,280 Speaker 1: it sounds like something that would play during like a um, 215 00:12:11,400 --> 00:12:13,600 Speaker 1: an old silent film that would be played on the piano, 216 00:12:13,679 --> 00:12:17,120 Speaker 1: you know, trying somebody to the railroad tracks kind of 217 00:12:17,120 --> 00:12:20,679 Speaker 1: a thing right in the music speeds up, um all right. 218 00:12:20,800 --> 00:12:26,440 Speaker 1: These Cameroonians were also shown something called Ekman faces, and 219 00:12:26,440 --> 00:12:30,680 Speaker 1: these Ekman faces are photos of standardized expressions of emotions. 220 00:12:30,760 --> 00:12:33,960 Speaker 1: So in this case, they had a happy, sad, and 221 00:12:34,440 --> 00:12:37,480 Speaker 1: scared face to look at while they listened to the music. 222 00:12:37,880 --> 00:12:41,680 Speaker 1: And just like Westerners the Cameroonians correlated the music type 223 00:12:41,679 --> 00:12:45,400 Speaker 1: with the same facial expressions. So that would tell you 224 00:12:45,440 --> 00:12:48,760 Speaker 1: that there's some universality to it. Now that's not There 225 00:12:48,760 --> 00:12:51,880 Speaker 1: are other studies that say, no, that's there. You know, 226 00:12:51,920 --> 00:12:54,400 Speaker 1: some that negate this because there are other cultures that 227 00:12:54,520 --> 00:12:58,360 Speaker 1: might hear certain notes in interpret in different ways. Yeah, 228 00:12:58,360 --> 00:13:00,520 Speaker 1: when you get in deep into saity of difference between 229 00:13:00,559 --> 00:13:04,840 Speaker 1: Eastern and Western music trends in Middle Eastern music versus 230 00:13:04,880 --> 00:13:07,800 Speaker 1: Western music, then things get a little more complicated. Well, 231 00:13:07,840 --> 00:13:11,720 Speaker 1: I was just thinking about Chinese opera, which the tones 232 00:13:12,160 --> 00:13:16,000 Speaker 1: in a Chinese opera might sound very um, harsh or 233 00:13:16,080 --> 00:13:21,040 Speaker 1: dissonant to the Western year, but very pleasant to Eastern year. Yeah, 234 00:13:21,040 --> 00:13:23,200 Speaker 1: there's a fabulous I think in ther piece in the 235 00:13:23,200 --> 00:13:26,720 Speaker 1: past year about Western and Western musician a Western opera 236 00:13:26,760 --> 00:13:30,520 Speaker 1: singer traveling to China and engaging in Chinese opera and 237 00:13:30,559 --> 00:13:33,320 Speaker 1: sort of dealing with the the the contrast between Western 238 00:13:33,320 --> 00:13:35,640 Speaker 1: opera and Chinese opera, I mean, some of the overlap 239 00:13:35,679 --> 00:13:38,480 Speaker 1: of the performers, and it's it's interesting because they are 240 00:13:39,480 --> 00:13:44,040 Speaker 1: such different animals well and even in language. And Alison 241 00:13:44,040 --> 00:13:45,839 Speaker 1: and I had kind of talked about this a little bit. 242 00:13:45,840 --> 00:13:48,880 Speaker 1: There's a musicality to language, and if you look at 243 00:13:48,920 --> 00:13:53,720 Speaker 1: something like Vietnamese, one word can be said in five 244 00:13:53,760 --> 00:13:57,880 Speaker 1: different tones, I mean five entirely different things. So similar 245 00:13:57,920 --> 00:14:00,640 Speaker 1: thing in Mandarin. Yeah, yeah, so it's much more nuanced 246 00:14:00,880 --> 00:14:04,440 Speaker 1: and it has to be taken into account. But Christopher Gladwin, 247 00:14:04,840 --> 00:14:08,080 Speaker 1: the man behind the Weirding module, had some very interesting 248 00:14:08,559 --> 00:14:12,240 Speaker 1: thoughts on this universality. Yeah. It was exchanged some emails 249 00:14:12,360 --> 00:14:14,520 Speaker 1: UH with Chris and he had a lot of great 250 00:14:14,559 --> 00:14:17,560 Speaker 1: in photo to share and sadly between the two of us, 251 00:14:17,559 --> 00:14:19,800 Speaker 1: we didn't have time to do an audio interview, but 252 00:14:19,840 --> 00:14:22,320 Speaker 1: I'll hopefully be sharing some stuff on the blog from 253 00:14:22,360 --> 00:14:24,800 Speaker 1: him in the weeks they had. He said, quote, there 254 00:14:24,800 --> 00:14:27,560 Speaker 1: are sounds which almost universally caused revulsion or fight or 255 00:14:27,560 --> 00:14:29,960 Speaker 1: flight responses. The sound of vomiting came out is the 256 00:14:29,960 --> 00:14:34,160 Speaker 1: most obnoxious auditory experience in a worldwide Internet survey conducted 257 00:14:34,200 --> 00:14:37,400 Speaker 1: by Professor Trevor Cox. The reason for this, UH is 258 00:14:37,440 --> 00:14:40,640 Speaker 1: that we're it's hardware to our biology avoid those that 259 00:14:40,680 --> 00:14:43,400 Speaker 1: are disgorging the contents of their stomachs unless you want 260 00:14:43,440 --> 00:14:45,880 Speaker 1: the same to happen to you. Other sounds that came 261 00:14:45,960 --> 00:14:49,040 Speaker 1: out on top where babies crying and nails down at blackboard. 262 00:14:49,080 --> 00:14:52,360 Speaker 1: Both of these sounds have relatively complex, high frequency tones 263 00:14:52,400 --> 00:14:55,680 Speaker 1: that we are evolutionarily designed to respond to. Having a 264 00:14:55,760 --> 00:14:59,040 Speaker 1: year old daughter, I can appreciate this. Many industrial bands 265 00:14:59,040 --> 00:15:02,360 Speaker 1: have used such a casual tactics robbing gristle and their 266 00:15:02,440 --> 00:15:05,960 Speaker 1: use of recordings of dogs attappicking a dummy, etcetera. And 267 00:15:06,240 --> 00:15:09,360 Speaker 1: he goes on to UH to discuss this in further depth, 268 00:15:09,560 --> 00:15:12,560 Speaker 1: and I will hopefully share that with everyone later on. 269 00:15:12,640 --> 00:15:15,680 Speaker 1: But but yeah, there's certain things that just as an organism, 270 00:15:15,720 --> 00:15:19,960 Speaker 1: we feel this either discussed with or this aversion to, 271 00:15:20,200 --> 00:15:22,120 Speaker 1: or it just sets up all our alarms. I mean, 272 00:15:22,120 --> 00:15:25,240 Speaker 1: the baby crying. I I too am experiencing that one 273 00:15:25,280 --> 00:15:28,760 Speaker 1: with the toddler that time my wife and I have 274 00:15:28,760 --> 00:15:31,960 Speaker 1: have adopted and he will he'll start, you know, crying 275 00:15:32,040 --> 00:15:33,360 Speaker 1: or tuning up a little bit in the middle of 276 00:15:33,360 --> 00:15:36,760 Speaker 1: the night, and it just has this intense effect on me, 277 00:15:37,080 --> 00:15:39,720 Speaker 1: uh to where even after I've I've put him back 278 00:15:39,760 --> 00:15:42,320 Speaker 1: to sleep, my heart is just still beating like crazy, 279 00:15:42,400 --> 00:15:45,320 Speaker 1: like it's just it's reaching behind my brain and uh 280 00:15:45,680 --> 00:15:48,600 Speaker 1: and you know, grabbing hold of the reptilian portion there 281 00:15:48,760 --> 00:15:52,760 Speaker 1: right now, is your camp biscuit mimicking the cries of 282 00:15:52,840 --> 00:15:55,400 Speaker 1: a newborn? Yeah, well, you know there's that argument that 283 00:15:55,400 --> 00:15:58,320 Speaker 1: that's what cats are doing anyway, and they're they're perverse 284 00:15:58,440 --> 00:16:01,760 Speaker 1: means of manipulating a humans, And so yeah, we'll have 285 00:16:01,800 --> 00:16:05,080 Speaker 1: they'll be situations where the child is authentically crying and 286 00:16:05,120 --> 00:16:08,320 Speaker 1: then the cat is also crying and it's mock human voice, 287 00:16:08,760 --> 00:16:11,800 Speaker 1: and it's it's you know what this is like, it's frustrating. 288 00:16:11,920 --> 00:16:15,800 Speaker 1: It becomes a loud household at three am. Yes, yeah, um. 289 00:16:15,920 --> 00:16:18,360 Speaker 1: Christopher Gladwin also mentions there was a sound that he 290 00:16:18,360 --> 00:16:21,080 Speaker 1: found difficult to describe. Michael Geret of the Swans, he said, 291 00:16:21,080 --> 00:16:24,240 Speaker 1: put it best that sex death sound that comes from 292 00:16:24,240 --> 00:16:27,920 Speaker 1: somewhere deep inside. There are some experiences of sound that 293 00:16:28,040 --> 00:16:31,440 Speaker 1: you just get that right. You tried to spot off. 294 00:16:32,920 --> 00:16:35,400 Speaker 1: That's the best I can do. Feeling from and some 295 00:16:35,480 --> 00:16:38,560 Speaker 1: sort of possession occurs. I believe that this connects with 296 00:16:38,640 --> 00:16:43,120 Speaker 1: some subterranean evolutionary memory, something in our ancestral reptilian fish brain. 297 00:16:43,480 --> 00:16:46,640 Speaker 1: We still have this the sigil fish ears, you know, 298 00:16:47,160 --> 00:16:49,680 Speaker 1: and I thought, you know what that sound? Let me 299 00:16:49,680 --> 00:16:51,800 Speaker 1: tell you this and I'm gonna give you the context 300 00:16:51,880 --> 00:16:54,120 Speaker 1: it was not a sexual context, so you don't have 301 00:16:54,200 --> 00:16:56,480 Speaker 1: to put your hands up to your ears and say no, 302 00:16:56,480 --> 00:16:59,400 Speaker 1: no, no no no. I did something called the seven minute workout. 303 00:16:59,760 --> 00:17:03,080 Speaker 1: Do know about this? It's awful. It is like this 304 00:17:03,720 --> 00:17:07,520 Speaker 1: ramped up, high density crazy workout you do for seven minutes, 305 00:17:07,960 --> 00:17:11,720 Speaker 1: just the best and highest rate that you can. Okay, 306 00:17:11,840 --> 00:17:15,760 Speaker 1: And I heard these noises coming out of myself that 307 00:17:15,880 --> 00:17:19,800 Speaker 1: I was a little bit ashamed of. I felt a 308 00:17:19,840 --> 00:17:22,680 Speaker 1: little bit like freaked out that they were actually coming out. 309 00:17:22,680 --> 00:17:24,959 Speaker 1: But I understand what he's saying. There's a guttural like, 310 00:17:25,040 --> 00:17:28,160 Speaker 1: oh my god, I'm dying inside noise that I had 311 00:17:28,280 --> 00:17:31,840 Speaker 1: never heard come out of myself before. And so there 312 00:17:31,920 --> 00:17:35,840 Speaker 1: is something to that, this evolutionary like, oh there's something wrong. Yeah. 313 00:17:36,320 --> 00:17:40,080 Speaker 1: An example of that, I was driving my child around 314 00:17:40,280 --> 00:17:41,640 Speaker 1: in the middle of the night, trying to get him 315 00:17:41,640 --> 00:17:44,400 Speaker 1: to sleep immediately after returning home, and his super jet 316 00:17:44,440 --> 00:17:46,880 Speaker 1: lagged now his jet lag, And so I was listening 317 00:17:46,920 --> 00:17:49,800 Speaker 1: to Radio Lab catching up in some Radio Lavish episodes, 318 00:17:49,840 --> 00:17:52,000 Speaker 1: and there's an excellent one they did recently on rabies. 319 00:17:52,720 --> 00:17:56,080 Speaker 1: And in that episode they play some audio of humans 320 00:17:56,320 --> 00:17:59,840 Speaker 1: who have rabies and are experiencing that rage and that 321 00:18:00,080 --> 00:18:03,520 Speaker 1: just you know, the mindless rage that is associated with 322 00:18:03,560 --> 00:18:06,760 Speaker 1: the later stages of Rabies. And it was extremely unsettling 323 00:18:06,800 --> 00:18:09,000 Speaker 1: to hear those sounds like and it's and I wonder 324 00:18:09,080 --> 00:18:10,800 Speaker 1: to what extent that's kind of cross somebody, that this 325 00:18:10,920 --> 00:18:13,400 Speaker 1: this idea, that that that is on some level human, 326 00:18:13,440 --> 00:18:16,680 Speaker 1: but it must be bodily possessioned by some outside force 327 00:18:16,760 --> 00:18:19,080 Speaker 1: that is making that kind of noise. And you're right, 328 00:18:19,200 --> 00:18:22,440 Speaker 1: that bodily possession, as if you are outside of yourself 329 00:18:22,560 --> 00:18:25,680 Speaker 1: or something was outside of itself. All right, we should 330 00:18:25,680 --> 00:18:28,200 Speaker 1: probably take a quick break, and when we get back, 331 00:18:28,400 --> 00:18:31,920 Speaker 1: we you and I Robert Lamb are going to actually 332 00:18:32,000 --> 00:18:35,880 Speaker 1: sing some of the strains of music classics, not because 333 00:18:35,920 --> 00:18:38,600 Speaker 1: we necessarily want to do that to your ears, but 334 00:18:38,640 --> 00:18:46,720 Speaker 1: because we have no budget, correct, right, So stand by 335 00:18:48,040 --> 00:18:52,000 Speaker 1: all right, we're back, Robert. Did you know that in 336 00:18:52,119 --> 00:18:56,480 Speaker 1: the original cut of Psycho that Hitchcock did not want 337 00:18:57,040 --> 00:19:02,400 Speaker 1: those high pitched violin screens to accompany the shower scene 338 00:19:02,680 --> 00:19:09,760 Speaker 1: fa iconomy. He sorry about that. Again, we have no budgets, 339 00:19:09,760 --> 00:19:12,000 Speaker 1: so that's which you guys are getting. Um. It was 340 00:19:12,000 --> 00:19:16,119 Speaker 1: actually his wife, Alma Revel, who was a script writer 341 00:19:16,520 --> 00:19:20,480 Speaker 1: and actually a director of her own right, and an 342 00:19:20,600 --> 00:19:22,600 Speaker 1: editor who said, no, no, no, you need to check 343 00:19:22,640 --> 00:19:26,919 Speaker 1: out Bernard Herman's score that he's created for this. It's amazing. 344 00:19:27,000 --> 00:19:29,360 Speaker 1: It's going to do its thing. And they actually tested 345 00:19:29,400 --> 00:19:32,840 Speaker 1: two versions, one with the with the violins and one without, 346 00:19:33,480 --> 00:19:37,280 Speaker 1: and apparently when they showed the audience when without, they 347 00:19:37,320 --> 00:19:39,720 Speaker 1: were a little like, okay, so this this one is 348 00:19:39,720 --> 00:19:42,600 Speaker 1: getting hacked enough in a shower. But when they accompanied 349 00:19:42,640 --> 00:19:46,920 Speaker 1: the violence strains of Bernard Herman, people freaked out. It's 350 00:19:47,119 --> 00:19:50,920 Speaker 1: interesting to think of having not scene the scene without 351 00:19:51,480 --> 00:19:54,159 Speaker 1: the music, and it's hard to imagine because such an 352 00:19:54,240 --> 00:19:57,840 Speaker 1: iconic scene and you go together so well, and when 353 00:19:57,840 --> 00:19:59,600 Speaker 1: I imagine the scene in my mind, and I think 354 00:19:59,640 --> 00:20:02,400 Speaker 1: that's a really horrific scene. You know, even even though 355 00:20:02,440 --> 00:20:06,240 Speaker 1: it it doesn't show as much um in way in 356 00:20:06,280 --> 00:20:09,200 Speaker 1: the way of nudity or bloodshed that you might. You 357 00:20:09,240 --> 00:20:11,639 Speaker 1: know that I'm sure you can get away with today. Uh. 358 00:20:11,680 --> 00:20:15,920 Speaker 1: It's so effective and so disturbing, and yet the music 359 00:20:16,760 --> 00:20:19,919 Speaker 1: is what seems to make it so effective, like in 360 00:20:19,920 --> 00:20:22,280 Speaker 1: in a sense we can't feel or even imagine what 361 00:20:22,400 --> 00:20:25,719 Speaker 1: those the stabs feel like physically, because most of us 362 00:20:25,760 --> 00:20:28,359 Speaker 1: have not been brutally stabbed with a butcher knife before, 363 00:20:28,960 --> 00:20:32,480 Speaker 1: but the music kind of fills that place. It's interesting 364 00:20:32,480 --> 00:20:35,359 Speaker 1: that you say that it's it's not that much nudity 365 00:20:35,400 --> 00:20:38,440 Speaker 1: and it's not that much violence, because then what you thought, 366 00:20:38,520 --> 00:20:40,920 Speaker 1: because a lot of people when they when they ask people, 367 00:20:41,160 --> 00:20:44,040 Speaker 1: you know, about that scene, they tend to envision much 368 00:20:44,080 --> 00:20:46,320 Speaker 1: more violence and nudity than there actually is because of 369 00:20:46,359 --> 00:20:50,320 Speaker 1: that heightened emotionality there. I think, Um, and of course 370 00:20:50,480 --> 00:20:52,720 Speaker 1: it's that high pitch sound, and we'll get a little 371 00:20:52,720 --> 00:20:55,919 Speaker 1: bit more into that in terms of the animal world. Um, 372 00:20:56,000 --> 00:20:58,240 Speaker 1: but I wanted to mention that in terms of pitch. 373 00:20:58,440 --> 00:21:03,119 Speaker 1: Daniel Blumstein uh He scrutinized on two films and found 374 00:21:03,160 --> 00:21:06,679 Speaker 1: that horror films had a higher than expected number of 375 00:21:06,760 --> 00:21:09,960 Speaker 1: abrupt shifts up and down and pitch, which he reported 376 00:21:10,000 --> 00:21:14,439 Speaker 1: in the Royal Society Journal Biology Letters. So already you 377 00:21:14,440 --> 00:21:17,879 Speaker 1: can see that they are very different ways that UM 378 00:21:18,240 --> 00:21:23,800 Speaker 1: filmmakers and musical composers can manipulate the brain. In terms 379 00:21:23,800 --> 00:21:27,480 Speaker 1: of psycho that was just something that they didn't necessarily know, like, hey, 380 00:21:27,520 --> 00:21:29,879 Speaker 1: we've got all these neuroscientists saying like the amygdala is 381 00:21:29,920 --> 00:21:32,080 Speaker 1: going crazy. It was just sort of a hunch that 382 00:21:32,160 --> 00:21:34,680 Speaker 1: this music would heighten the effect. Yeah. So, like you said, 383 00:21:34,680 --> 00:21:38,240 Speaker 1: they didn't have the neuroscientists, but they did have musical tradition. Obviously, 384 00:21:38,440 --> 00:21:41,399 Speaker 1: run Herman knew what worked because when you look at 385 00:21:41,400 --> 00:21:43,439 Speaker 1: stuff like Peter and the Wolf, you know, that's a 386 00:21:43,480 --> 00:21:45,879 Speaker 1: classic one that we always learned in like elementary music class, 387 00:21:45,880 --> 00:21:48,000 Speaker 1: where every character has kind of their own little jaunty 388 00:21:48,359 --> 00:21:51,360 Speaker 1: number and you you're you're told by your music teacher, oh, 389 00:21:51,400 --> 00:21:53,520 Speaker 1: well this this music is behaving like this, because this 390 00:21:53,640 --> 00:21:57,080 Speaker 1: is what's happening in the story. Um. Some of the 391 00:21:57,080 --> 00:22:03,280 Speaker 1: basics though, cord tempo in amplitude. Okay, So with chords, 392 00:22:03,320 --> 00:22:06,680 Speaker 1: we have minor and major chords, and in a very 393 00:22:07,280 --> 00:22:12,160 Speaker 1: very broad sense, minor chords evoke sad feelings. Major chords 394 00:22:12,240 --> 00:22:15,520 Speaker 1: are happy. Um, at least again in Western music. Um, 395 00:22:15,760 --> 00:22:17,680 Speaker 1: you tay. And the interesting thing is if you take 396 00:22:17,760 --> 00:22:20,720 Speaker 1: something in a major key and you translate it into 397 00:22:20,800 --> 00:22:24,280 Speaker 1: a minor key, you go from happy too sad. As 398 00:22:24,359 --> 00:22:27,040 Speaker 1: a as an engineer, a musician by the name of 399 00:22:27,040 --> 00:22:31,119 Speaker 1: Oleg Berg has demonstrated he's a from the Ukraine and 400 00:22:31,200 --> 00:22:34,000 Speaker 1: he has a YouTube account. Takes a number of songs 401 00:22:34,080 --> 00:22:37,200 Speaker 1: such as the rhythmic sweet dreams are made of these 402 00:22:37,320 --> 00:22:41,200 Speaker 1: minor key transforms. It tweaks, it makes it a major 403 00:22:41,320 --> 00:22:45,080 Speaker 1: key song, and it's suddenly a different entire emotional experience. 404 00:22:45,119 --> 00:22:48,160 Speaker 1: Suddenly it's upbeat and not kind of dark and uh 405 00:22:48,200 --> 00:22:50,280 Speaker 1: and you know foreboding. Uh. That's the same thing with 406 00:22:50,400 --> 00:22:52,679 Speaker 1: losing my religion. Instead of it being this kind of 407 00:22:52,720 --> 00:22:55,560 Speaker 1: you know, down song about oh I've lost my religion, 408 00:22:55,560 --> 00:22:57,200 Speaker 1: I've kind of lost my way, it's more like I've 409 00:22:57,240 --> 00:22:59,479 Speaker 1: lost my religion, I'm free, I'm happy, and Michael Stipes 410 00:22:59,560 --> 00:23:03,320 Speaker 1: is sansing around. It's more in keeping with you know, 411 00:23:03,520 --> 00:23:04,920 Speaker 1: it's the end of the world as I know it, 412 00:23:04,960 --> 00:23:07,680 Speaker 1: as opposed to what we we have come to expect 413 00:23:08,000 --> 00:23:11,880 Speaker 1: from losing my religion. Now. He also took the song 414 00:23:12,000 --> 00:23:15,000 Speaker 1: don't Worry Be Happy, recorded by Bobby mcfarren. Are you 415 00:23:15,000 --> 00:23:18,959 Speaker 1: familiar with that? Yeah, don't worry as long I wrote, 416 00:23:19,160 --> 00:23:22,720 Speaker 1: I mean just relentlessly upbeat, right, And he put that 417 00:23:22,720 --> 00:23:26,240 Speaker 1: in a minor key and I don't know, it's it 418 00:23:26,280 --> 00:23:28,840 Speaker 1: sounds like the beginnings of a mental breakdown. Yeah, it's 419 00:23:29,080 --> 00:23:33,119 Speaker 1: like it brings to mind the happy bobbing Farren reduced 420 00:23:33,440 --> 00:23:37,560 Speaker 1: to hopping on a box car somewhere like shivering. Yeah, 421 00:23:37,640 --> 00:23:39,439 Speaker 1: you're like, there's there's gonna be problems ahead. I know 422 00:23:39,520 --> 00:23:42,080 Speaker 1: you're saying don't worry, be happy, but it doesn't sound 423 00:23:42,119 --> 00:23:44,639 Speaker 1: like you really mean it. So it's amazing that just 424 00:23:44,760 --> 00:23:48,080 Speaker 1: that shift can create that sense of dread and doom. 425 00:23:48,520 --> 00:23:50,479 Speaker 1: Now it's interesting with pop music, is pointed out by 426 00:23:50,520 --> 00:23:53,480 Speaker 1: Glenn Shellenberg of the University of Toronto. If you look 427 00:23:53,520 --> 00:23:57,080 Speaker 1: at through the nine eighties and the nineties, UH, there's 428 00:23:57,240 --> 00:23:59,960 Speaker 1: definitely a dominance of the major key in the top forties, 429 00:24:00,160 --> 00:24:02,760 Speaker 1: but it begins to shift slowly at first and then 430 00:24:02,880 --> 00:24:05,840 Speaker 1: really radically, and by two thousand nine only eighteen out 431 00:24:05,880 --> 00:24:08,560 Speaker 1: of the top forty songs are in the major key. 432 00:24:08,640 --> 00:24:12,680 Speaker 1: So there various explanations for this. And partially, people get 433 00:24:12,760 --> 00:24:17,399 Speaker 1: kind of used to the major key UH preference in 434 00:24:17,440 --> 00:24:20,560 Speaker 1: pop music and it becomes more and more cliche. So 435 00:24:20,880 --> 00:24:23,960 Speaker 1: avoiding cliches, the trend moves towards the minor key. But 436 00:24:24,080 --> 00:24:27,720 Speaker 1: also there's the the idea that people were coming around 437 00:24:27,760 --> 00:24:30,760 Speaker 1: more to the idea that life is not so happy, 438 00:24:30,800 --> 00:24:32,879 Speaker 1: that life is maybe a little more nuanced and a 439 00:24:32,920 --> 00:24:36,560 Speaker 1: little more ambiguous, and then their sadness uh at least 440 00:24:36,600 --> 00:24:39,960 Speaker 1: around the corner from any happiness, if not meshed in 441 00:24:40,040 --> 00:24:43,320 Speaker 1: it to begin with. So even something that is more 442 00:24:43,400 --> 00:24:47,960 Speaker 1: or less universal, you start applying enough cultural influence to it, 443 00:24:47,960 --> 00:24:51,880 Speaker 1: it can begin to shift. It's interesting that that's, Um, 444 00:24:51,920 --> 00:24:53,840 Speaker 1: that that's something that's happening, because I was just thinking 445 00:24:53,840 --> 00:24:56,840 Speaker 1: about the Halloween music that the are you familiar with 446 00:24:56,880 --> 00:25:01,240 Speaker 1: that one? The John Carper John you are, yeah, John Carpenter, 447 00:25:01,320 --> 00:25:06,680 Speaker 1: Alan Howorth both both I mean John Carpenter excellent director, fighter, etcetera, 448 00:25:06,680 --> 00:25:09,000 Speaker 1: but also an accomplished musician, and his work with Allan 449 00:25:09,040 --> 00:25:11,040 Speaker 1: Howorth is is some of my favorite stuff. But that 450 00:25:11,119 --> 00:25:15,200 Speaker 1: music has been sampled in pop music. And yeah, and 451 00:25:15,800 --> 00:25:20,280 Speaker 1: that actually is a really good example of tempo in 452 00:25:20,640 --> 00:25:23,360 Speaker 1: an odd meter. And we talk about tempo, we're talking 453 00:25:23,440 --> 00:25:31,640 Speaker 1: about how how fast or slow the intent intent intent entent. Again, 454 00:25:31,720 --> 00:25:33,800 Speaker 1: you feel the motion in that music, right, Yeah, Like 455 00:25:33,840 --> 00:25:35,840 Speaker 1: even as you were you were doing that, you were 456 00:25:35,880 --> 00:25:38,200 Speaker 1: bopping back and forth as if you were running right. 457 00:25:38,280 --> 00:25:41,280 Speaker 1: And Um, the thing about that is that most music 458 00:25:41,520 --> 00:25:45,080 Speaker 1: uses beat counts divisible by two, but the Halloween score 459 00:25:45,160 --> 00:25:48,200 Speaker 1: uses an odd meter of five four. That sort of 460 00:25:48,240 --> 00:25:51,800 Speaker 1: creates that weird like catch up feeling to do like 461 00:25:51,800 --> 00:25:54,080 Speaker 1: you just can't really quite get there. Yeah, Like you're 462 00:25:54,119 --> 00:25:56,840 Speaker 1: just you're trying to stay one step ahead of the 463 00:25:56,880 --> 00:25:59,440 Speaker 1: mass killer. You're trying to get to the car before 464 00:25:59,440 --> 00:26:01,240 Speaker 1: the mass kill that gets you, but you're not quite 465 00:26:01,280 --> 00:26:04,080 Speaker 1: there exactly. And now think about your visual cortex trying 466 00:26:04,119 --> 00:26:06,800 Speaker 1: to map that and all while you're watching Jamie Lee 467 00:26:06,800 --> 00:26:11,560 Speaker 1: Curtis do that. It works perfectly. Yeah, yeah, girl, you 468 00:26:11,680 --> 00:26:15,360 Speaker 1: in danger. Yeah, all of that is happening. And according 469 00:26:15,400 --> 00:26:17,679 Speaker 1: to Neil Learner, he is a professor of music at 470 00:26:17,760 --> 00:26:20,680 Speaker 1: Davidson College and Davidson, North Carolina and an expert in 471 00:26:20,800 --> 00:26:24,720 Speaker 1: horror film music, one that music technique is messing with 472 00:26:24,760 --> 00:26:28,200 Speaker 1: that tempo to suggest that chase, and he says that 473 00:26:28,320 --> 00:26:31,040 Speaker 1: musical music typically speeds up and grows louder as the 474 00:26:31,160 --> 00:26:33,879 Speaker 1: danger closes in. And he says, my hunch is that 475 00:26:33,920 --> 00:26:36,520 Speaker 1: our brains here that music in terms of being hunted, 476 00:26:36,600 --> 00:26:39,040 Speaker 1: Our instincts tell us a creature is upon us and 477 00:26:39,080 --> 00:26:44,320 Speaker 1: we need to run away or just turn and fight it. Well, 478 00:26:44,320 --> 00:26:48,000 Speaker 1: there's obviously one great example of that that everyone's already 479 00:26:48,000 --> 00:26:57,040 Speaker 1: thinking of. Boom boom boom, bum boom boom boom, pumomum pomummmmmm, 480 00:26:59,200 --> 00:27:03,320 Speaker 1: pump pump, bump, bump, and then the shark attacks Jaws. 481 00:27:03,359 --> 00:27:07,360 Speaker 1: Of course, of course, yes, classic John Williams score, iconic 482 00:27:07,680 --> 00:27:11,359 Speaker 1: John Williams score been sampled all over the place, but 483 00:27:11,400 --> 00:27:15,359 Speaker 1: not here because we can't afford it, so that you 484 00:27:15,400 --> 00:27:17,240 Speaker 1: know that I'll have to do. But yeah, you've got 485 00:27:17,240 --> 00:27:21,080 Speaker 1: those Christian doing minor chords that again slicing in. And 486 00:27:21,119 --> 00:27:23,840 Speaker 1: obviously you can't run from a shark. Um. I mean 487 00:27:23,840 --> 00:27:25,680 Speaker 1: you can't. But if you're running from the shark, you're 488 00:27:25,680 --> 00:27:28,480 Speaker 1: really okay, you don't run land, Yeah, you're good. But 489 00:27:28,480 --> 00:27:31,360 Speaker 1: but it does bring this ideas like I'm stepping, I'm stepping, 490 00:27:31,359 --> 00:27:34,480 Speaker 1: I'm walking a little faster, and then I'm running. Uh 491 00:27:34,520 --> 00:27:37,840 Speaker 1: and and it just grabs us right uh, you know, 492 00:27:37,920 --> 00:27:40,400 Speaker 1: right right at the root of our reptilian brain. Yeah. 493 00:27:40,440 --> 00:27:41,840 Speaker 1: And then in the middle of that you have a 494 00:27:41,920 --> 00:27:44,720 Speaker 1: high pitched noises in in terms of the whistle, right, 495 00:27:44,720 --> 00:27:47,120 Speaker 1: you've got the lifeguard on the beach blowing the whistle. 496 00:27:47,400 --> 00:27:50,840 Speaker 1: And then when Jaws finally gets victim, you've got the 497 00:27:51,280 --> 00:27:56,280 Speaker 1: big note pulling the person under corresponding with it. I'm 498 00:27:56,320 --> 00:27:58,199 Speaker 1: telling you right now, if I had some sort of 499 00:27:58,240 --> 00:28:02,600 Speaker 1: galvanic skin response that was looking at my like how 500 00:28:02,680 --> 00:28:04,480 Speaker 1: much I was sweating? They would feel it right now. 501 00:28:04,640 --> 00:28:08,159 Speaker 1: Just in talking about it now. To return to Daniel Bloomstein, 502 00:28:08,600 --> 00:28:11,840 Speaker 1: he also pointed out that when he looked at a 503 00:28:11,880 --> 00:28:13,880 Speaker 1: hundred and two different film scores, he found it, among 504 00:28:13,880 --> 00:28:16,600 Speaker 1: other things, the screams of animals were used in several 505 00:28:16,640 --> 00:28:20,040 Speaker 1: key scenes in horror films, including such iconic films as 506 00:28:20,080 --> 00:28:23,119 Speaker 1: The Exorcist and The Shining Um. And and this is 507 00:28:23,280 --> 00:28:26,320 Speaker 1: this is a is very interesting because in a sense, 508 00:28:26,359 --> 00:28:29,159 Speaker 1: it's very straightforward. The cries of animals are going to 509 00:28:29,200 --> 00:28:31,280 Speaker 1: resonate with us in the same way the cries of 510 00:28:31,280 --> 00:28:33,399 Speaker 1: of humans are going to resonate with us. Yeah, and 511 00:28:33,400 --> 00:28:36,879 Speaker 1: didn't he get this idea of of really looking at 512 00:28:36,880 --> 00:28:40,560 Speaker 1: these film scores for animal cries because he was working 513 00:28:40,560 --> 00:28:44,640 Speaker 1: with actually yellow bellied marmots and he notices that when 514 00:28:44,640 --> 00:28:47,120 Speaker 1: the research went to go and grab the marmots that 515 00:28:47,160 --> 00:28:50,880 Speaker 1: they would have these high pitched screams. And he thought, wow, 516 00:28:50,960 --> 00:28:54,240 Speaker 1: I wonder you know what that's doing to our brains. 517 00:28:54,480 --> 00:28:56,720 Speaker 1: And then he examined those film scores and then found 518 00:28:56,720 --> 00:29:00,120 Speaker 1: those the animal screess I thought was really interesting. So he, 519 00:29:00,480 --> 00:29:04,840 Speaker 1: along with film composer Michael Kay, created a study here, 520 00:29:05,360 --> 00:29:09,120 Speaker 1: of course pattern on these screaming marmots, and they had 521 00:29:09,160 --> 00:29:12,280 Speaker 1: a neutral music clip as well as music segments with 522 00:29:12,440 --> 00:29:18,440 Speaker 1: nonlinear sounds, so that Mormot was creating a discordant nonlinear sound. Yeah, 523 00:29:18,480 --> 00:29:22,080 Speaker 1: and that's something that the Christopher Gladwin brought up as well. 524 00:29:22,480 --> 00:29:24,880 Speaker 1: That Discordia, of course is big. And the music you 525 00:29:24,920 --> 00:29:27,880 Speaker 1: think of all the shrieking, clanging noises, the one that 526 00:29:27,920 --> 00:29:31,320 Speaker 1: comes instantly to mind Texas Chainsaw Masca has a highly 527 00:29:31,360 --> 00:29:34,120 Speaker 1: effective score and it's another film that isn't nearly as 528 00:29:34,200 --> 00:29:37,040 Speaker 1: violent or bloody as some people think it is. That 529 00:29:37,120 --> 00:29:40,080 Speaker 1: it's just everything just fell together perfectly in that film. 530 00:29:40,320 --> 00:29:43,040 Speaker 1: So you have Discordia and then you have you have 531 00:29:43,200 --> 00:29:46,920 Speaker 1: these these animal sounds popping up and uh. And another 532 00:29:46,920 --> 00:29:51,080 Speaker 1: thing Gladwin mentioned is the taking of animal sounds or 533 00:29:51,120 --> 00:29:53,920 Speaker 1: other sounds that are natural, tweaking them into an unnatural 534 00:29:53,960 --> 00:29:56,040 Speaker 1: area and then they hit us in a way wherever 535 00:29:56,160 --> 00:29:57,479 Speaker 1: like what is that? I don't know what that is? 536 00:29:57,520 --> 00:30:00,280 Speaker 1: And the fear of the unknown is summoned. Yeah. I 537 00:30:00,280 --> 00:30:03,400 Speaker 1: noticed this when we visited nether World last year. In 538 00:30:03,880 --> 00:30:07,120 Speaker 1: the hunting house in the background, there were these sort 539 00:30:07,160 --> 00:30:09,920 Speaker 1: of clinging elements that were going on. Now this was 540 00:30:10,000 --> 00:30:14,719 Speaker 1: just the house music before they have actual music though, no, right, 541 00:30:14,800 --> 00:30:19,000 Speaker 1: there was no like um, but you know, is this 542 00:30:19,040 --> 00:30:20,960 Speaker 1: way of kind of setting the scene and making people 543 00:30:21,000 --> 00:30:23,160 Speaker 1: feel a little bit uncertain about it because you're going 544 00:30:23,200 --> 00:30:25,400 Speaker 1: to do what's it? What sound is coming next? You know, 545 00:30:25,480 --> 00:30:28,920 Speaker 1: our pattern recognition craving brains don't know what to make 546 00:30:28,920 --> 00:30:30,560 Speaker 1: of it. So we're on edge where we don't know 547 00:30:30,600 --> 00:30:33,440 Speaker 1: what's happening next. Yeah, someone please play that chasing music 548 00:30:33,480 --> 00:30:37,480 Speaker 1: so I know to run alright. So in this experiment 549 00:30:37,600 --> 00:30:40,200 Speaker 1: that that k and Plumstein created, uh, they found that 550 00:30:40,240 --> 00:30:44,280 Speaker 1: participants were far more stimulated by the nonlinear music segments. 551 00:30:44,400 --> 00:30:46,920 Speaker 1: In addition, this is so interesting to me. If the 552 00:30:47,000 --> 00:30:51,000 Speaker 1: nonlinear melodies became higher, the emotional reaction was more pronounced, 553 00:30:51,360 --> 00:30:54,320 Speaker 1: much like a mother tuning into the tensed vocal cord 554 00:30:54,400 --> 00:30:57,480 Speaker 1: screams of the baby mormot. And so what he's saying 555 00:30:57,600 --> 00:31:02,240 Speaker 1: is that um that these vocal cords straining sounds are 556 00:31:02,400 --> 00:31:05,680 Speaker 1: unbluffable signs of fear in the animal world, and of 557 00:31:05,720 --> 00:31:08,520 Speaker 1: course they would be in in the human world as well. 558 00:31:08,560 --> 00:31:11,000 Speaker 1: And it made me think back to those high pitched, 559 00:31:11,440 --> 00:31:17,240 Speaker 1: strangled um pitches of the violin during the Psycho shower scene. 560 00:31:16,960 --> 00:31:20,080 Speaker 1: In fact, let's listen to a marmot screen because we 561 00:31:20,080 --> 00:31:29,000 Speaker 1: have a little clip, all right, so you can kind 562 00:31:29,000 --> 00:31:32,440 Speaker 1: of hear that there's there's that element. And how did 563 00:31:32,440 --> 00:31:34,000 Speaker 1: they get the scream out of the marmot? Do we 564 00:31:34,040 --> 00:31:38,320 Speaker 1: want to know? I think that they continually advanced upon 565 00:31:38,400 --> 00:31:40,560 Speaker 1: the mormot until they were like, you're you're in my 566 00:31:40,680 --> 00:31:44,280 Speaker 1: zone here feeling uncomfortable. Okay, as long as no marmots 567 00:31:44,280 --> 00:31:47,280 Speaker 1: were harmed. Okay. So we've talked a lot about the 568 00:31:47,280 --> 00:31:51,600 Speaker 1: way that that's scary music, on settling music, on canny music, 569 00:31:51,720 --> 00:31:55,120 Speaker 1: how it will enhance some the visuals of a horror 570 00:31:55,160 --> 00:31:57,600 Speaker 1: movie or what have you. But what happens when we 571 00:31:57,720 --> 00:32:02,520 Speaker 1: take take away the visual text from the music, Well, 572 00:32:02,640 --> 00:32:05,440 Speaker 1: it turns out that it can do a couple of 573 00:32:05,480 --> 00:32:08,080 Speaker 1: different things. If you if you take away from the context, 574 00:32:08,160 --> 00:32:11,880 Speaker 1: you can actually water down the effect. Because Bloomstein had 575 00:32:11,920 --> 00:32:15,960 Speaker 1: a second stage of his study and participants were asked 576 00:32:15,960 --> 00:32:20,000 Speaker 1: to watch objectively boring videos we're talking about drinking coffee 577 00:32:20,440 --> 00:32:24,760 Speaker 1: or reading a book, which was paired with nonlinear music. Okay, 578 00:32:24,800 --> 00:32:28,040 Speaker 1: So they found that the same disort of music was 579 00:32:28,240 --> 00:32:32,360 Speaker 1: much less emotionally stimulating and much less scary when it 580 00:32:32,440 --> 00:32:35,120 Speaker 1: went along with something that was just kind of wrote. 581 00:32:35,560 --> 00:32:38,480 Speaker 1: So watching a guy press his pants while a music 582 00:32:38,600 --> 00:32:41,960 Speaker 1: box track plays is just pretty ho hum, right, yeah, 583 00:32:42,000 --> 00:32:45,080 Speaker 1: And you know there's no room for interpretation in these 584 00:32:45,080 --> 00:32:48,880 Speaker 1: examples either. It's not like, say, imagine like a film 585 00:32:48,880 --> 00:32:51,920 Speaker 1: of a of a mother approaching a cradle, where it 586 00:32:51,920 --> 00:32:53,960 Speaker 1: seems like that's asitution at which and where if you 587 00:32:54,000 --> 00:32:57,960 Speaker 1: played happy music, you know, sad music or or scary music, 588 00:32:58,240 --> 00:33:00,680 Speaker 1: you could really force us to to to make the 589 00:33:00,720 --> 00:33:02,480 Speaker 1: story in our own head. It's like, oh my, you know, 590 00:33:02,480 --> 00:33:04,280 Speaker 1: oh my goodness, what's in that cradle? What's not in 591 00:33:04,320 --> 00:33:08,160 Speaker 1: that cradle but a guy ironing his shorts. You know, 592 00:33:08,360 --> 00:33:09,880 Speaker 1: that's probably not going to be a pitch for a 593 00:33:09,880 --> 00:33:12,960 Speaker 1: horror movie anytime soon, unless those tinny strains of a 594 00:33:13,040 --> 00:33:15,440 Speaker 1: music box are playing and then they pan to like 595 00:33:15,520 --> 00:33:19,040 Speaker 1: a Portla indulve batting her eyes and you hear door creek. Yeah, 596 00:33:19,080 --> 00:33:22,760 Speaker 1: and then you have a student film, Yes, how did 597 00:33:22,840 --> 00:33:27,920 Speaker 1: you know that was my fil And then here's another 598 00:33:27,960 --> 00:33:31,720 Speaker 1: aspect of this, of the visual context is that when 599 00:33:31,800 --> 00:33:36,160 Speaker 1: you shut your eyes, you change the emotional landscape. And 600 00:33:36,240 --> 00:33:37,800 Speaker 1: I want you guys to guess out there, would it 601 00:33:37,880 --> 00:33:42,880 Speaker 1: be more horrific or less horrific. I would have guessed 602 00:33:43,280 --> 00:33:47,600 Speaker 1: less horrifically yes before this, simply because it's something that 603 00:33:47,640 --> 00:33:49,360 Speaker 1: I do when I don't, you know, I think that 604 00:33:49,400 --> 00:33:52,960 Speaker 1: I'm lessening the experience. And I'm watching watching some scary 605 00:33:53,000 --> 00:33:54,920 Speaker 1: and then you close your eyes and it's like my 606 00:33:54,920 --> 00:33:57,960 Speaker 1: my friend Dave will blur his eyes out during scary 607 00:33:57,960 --> 00:34:00,200 Speaker 1: parts in the movie to accomplish the same thing, like 608 00:34:00,320 --> 00:34:03,440 Speaker 1: to sort of stare at nothing. Um. I guess it 609 00:34:03,440 --> 00:34:06,000 Speaker 1: didn't surprise me because I listened to enough creepy music 610 00:34:06,560 --> 00:34:09,840 Speaker 1: that I do find that, like I'm listening to weirding 611 00:34:09,880 --> 00:34:12,960 Speaker 1: module where I'm listening to like Throbbing Gristle or or 612 00:34:13,000 --> 00:34:16,480 Speaker 1: what have you, Chris Carter, and it's uh, if I'm 613 00:34:16,520 --> 00:34:19,279 Speaker 1: if I'm zoning out or I'm closing my eyes, it 614 00:34:19,400 --> 00:34:23,160 Speaker 1: really takes on a richer, darker form in my mind. 615 00:34:23,960 --> 00:34:26,840 Speaker 1: I'm still stuck on Throbbing Gristle. Oh, They're one of 616 00:34:26,520 --> 00:34:29,760 Speaker 1: the mainstays. It's just the combination. One of the creepiest 617 00:34:29,800 --> 00:34:32,200 Speaker 1: tracks of all time. Hamburger lady, look it up if 618 00:34:32,200 --> 00:34:36,879 Speaker 1: you want to feel terrified. Okay, throbbing gristle, hamburger lady. 619 00:34:36,920 --> 00:34:39,680 Speaker 1: All right, and research published in the Public Library of 620 00:34:39,719 --> 00:34:43,640 Speaker 1: Science one by Tel Aviv University researchers found that the 621 00:34:43,680 --> 00:34:46,319 Speaker 1: premise of squinting your eyes shut during a freaky scene 622 00:34:46,360 --> 00:34:50,160 Speaker 1: may actually heightened your fear responses. We've just said. Volunteers 623 00:34:50,200 --> 00:34:53,600 Speaker 1: listened to Hitchcock style music twice, once with their eyes 624 00:34:53,600 --> 00:34:56,399 Speaker 1: open and once with their eyes shut, and with their 625 00:34:56,440 --> 00:35:00,000 Speaker 1: eyes closed, their migdalas were far more active, and volunteer 626 00:35:00,239 --> 00:35:03,279 Speaker 1: said that they also felt the emotional effects being much 627 00:35:03,320 --> 00:35:06,640 Speaker 1: more pronounced when when they were completely in the dark 628 00:35:06,719 --> 00:35:09,200 Speaker 1: listening to this. So it seemed to wire together a 629 00:35:09,280 --> 00:35:12,560 Speaker 1: direct connection to the regions of our brain that process emotions. 630 00:35:12,600 --> 00:35:15,719 Speaker 1: And it's not merely subjective. They're using a functional m 631 00:35:15,920 --> 00:35:17,680 Speaker 1: r I and I can see the distinct changes in 632 00:35:17,719 --> 00:35:20,239 Speaker 1: the brains were more pronounced in the person's eyes were 633 00:35:20,280 --> 00:35:22,520 Speaker 1: not being used. Yeah, so the idea is that you're 634 00:35:22,600 --> 00:35:26,560 Speaker 1: actually better able to focus on your fear response. Yeah, 635 00:35:26,880 --> 00:35:30,000 Speaker 1: which is you know, climbing to this fMRI machine listened 636 00:35:30,000 --> 00:35:33,000 Speaker 1: to some really unsettling music and want to see what happens. Yeah, 637 00:35:33,040 --> 00:35:35,279 Speaker 1: that's cool, right, So I mean those are a couple 638 00:35:35,280 --> 00:35:39,040 Speaker 1: of ways that that music can actually game our response. 639 00:35:39,040 --> 00:35:41,760 Speaker 1: And I was thinking about this in terms of political ads. 640 00:35:42,239 --> 00:35:46,279 Speaker 1: Oh yeah, you know those sort of dot notes that 641 00:35:46,320 --> 00:35:49,359 Speaker 1: are played sometimes to cast one of the politicians really 642 00:35:49,400 --> 00:35:57,200 Speaker 1: does know what's best for America. Don't, don't, but she really. Yeah. 643 00:35:57,640 --> 00:36:00,680 Speaker 1: Another great example of this in terms of changing the 644 00:36:00,760 --> 00:36:03,239 Speaker 1: music changing the tone of something. If you've ever seen 645 00:36:03,280 --> 00:36:06,959 Speaker 1: the trailer for Shining um so available on YouTube, where 646 00:36:07,000 --> 00:36:10,400 Speaker 1: someone took the trailer for the Shining Kubrick's adaptation to 647 00:36:10,440 --> 00:36:12,719 Speaker 1: Stephen King's novel How that we've been talking about here, 648 00:36:13,160 --> 00:36:16,719 Speaker 1: took that recut, it added some happy music and and 649 00:36:16,760 --> 00:36:19,640 Speaker 1: I think through in one little Jack Nicholson quote from 650 00:36:19,640 --> 00:36:23,960 Speaker 1: another movie about fatherhood, and made the film look like 651 00:36:24,000 --> 00:36:26,960 Speaker 1: a romantic comedy that maybe involved ghosts a little bit, 652 00:36:27,080 --> 00:36:30,000 Speaker 1: as opposed to a horrific journey into horror. It is 653 00:36:30,120 --> 00:36:33,440 Speaker 1: hilarious because it looks like this inspirational tale of fatherhood 654 00:36:33,520 --> 00:36:36,479 Speaker 1: and being a writer as well. Yeah, and Shelley Davall 655 00:36:36,520 --> 00:36:40,640 Speaker 1: actually looks perky in those clips. So there you have it. 656 00:36:41,120 --> 00:36:43,560 Speaker 1: To quote Christopher Glad when one last time. He said, 657 00:36:43,600 --> 00:36:45,680 Speaker 1: it is my belief that our reaction to music we 658 00:36:45,760 --> 00:36:49,440 Speaker 1: find unsettling is triggered by a combination of inherited biological 659 00:36:49,480 --> 00:36:53,520 Speaker 1: responses modified by culturally acquired behavior. See. I think that 660 00:36:53,520 --> 00:36:55,200 Speaker 1: pretty much sums it up right there. So as we 661 00:36:55,239 --> 00:36:57,239 Speaker 1: close out the podcast here, let's just listen to one 662 00:36:57,360 --> 00:37:00,560 Speaker 1: last clip from the Weirding module of this the fourth 663 00:37:00,600 --> 00:37:23,439 Speaker 1: track from No Lifus I Corps from some Lost Regions. Yes, 664 00:37:35,480 --> 00:37:37,440 Speaker 1: all right, So there you have it, the science of 665 00:37:37,560 --> 00:37:40,880 Speaker 1: Uncanny music. And uh and hey, if you enjoyed the 666 00:37:40,920 --> 00:37:44,759 Speaker 1: Weirding Module, go look him up. He has I'm sure 667 00:37:44,760 --> 00:37:47,080 Speaker 1: he's putting out at a mix for Halloween this year, 668 00:37:47,160 --> 00:37:49,200 Speaker 1: and I think he has a new release coming out 669 00:37:49,280 --> 00:37:51,799 Speaker 1: in the new year, so uh so, definitely definitely check 670 00:37:51,840 --> 00:37:55,320 Speaker 1: him out. He's one of my favorites. And Sundays even 671 00:37:55,440 --> 00:37:58,480 Speaker 1: your memories of your most frightening movies as a child 672 00:37:58,560 --> 00:38:00,279 Speaker 1: and how the music affected you, And you can do 673 00:38:00,360 --> 00:38:03,200 Speaker 1: that by sending us an email to blow the mind 674 00:38:03,320 --> 00:38:10,480 Speaker 1: at how staff works dot com. For more on this 675 00:38:10,640 --> 00:38:27,920 Speaker 1: and thousands of other topics, visit how staff works dot com.