1 00:00:00,000 --> 00:00:05,000 Sound has a kind of magic. 2 00:00:05,000 --> 00:00:15,000 Some creatures see with sound, and so do some blind people. 3 00:00:15,000 --> 00:00:22,000 Sound can be shaped and engineered to enhance beautiful music. 4 00:00:22,000 --> 00:00:27,000 Sound can even change the taste of food. 5 00:00:27,000 --> 00:00:34,000 Sound can burn away tumors and may soon treat Alzheimer's disease. 6 00:00:34,000 --> 00:00:38,000 Sound can levitate solid objects. 7 00:00:38,000 --> 00:00:46,000 The mysteries of sound are coming into focus like never before. 8 00:00:46,000 --> 00:00:50,000 Look at that geometry. Oh my goodness. 9 00:00:58,000 --> 00:01:06,000 When people try to explain what sound is, they often liken it to ripples in a pond, 10 00:01:06,000 --> 00:01:13,000 a series of traveling compression waves radiating outward from the source. 11 00:01:13,000 --> 00:01:20,000 We can make a graph of sound. We can measure the level of sound. 12 00:01:20,000 --> 00:01:25,000 We can record the intensity of sound. 13 00:01:25,000 --> 00:01:30,000 But a real picture of sound is more complex. 14 00:01:56,000 --> 00:02:04,000 Sound effects matter in surprising ways, a mystery that has recently deepened. 15 00:02:04,000 --> 00:02:08,000 Cymatics is the science of visible sound. 16 00:02:08,000 --> 00:02:13,000 So all we have is a metal plate, and we sprinkle on some sand. 17 00:02:13,000 --> 00:02:19,000 What you see here is completely formless. In other words, there's no pattern at all. 18 00:02:19,000 --> 00:02:25,000 Then we take a violin bow, and we're going to play the plate with the violin bow. 19 00:02:28,000 --> 00:02:32,000 You see a beautiful star appears on the plate. 20 00:02:32,000 --> 00:02:39,000 Now, that pattern that forms is basically the sound made visible, and it's kind of magic. 21 00:02:39,000 --> 00:02:46,000 And now watch what happens when we make this plate vibrate from an electronic piano. 22 00:02:49,000 --> 00:02:53,000 Isn't that neat? 23 00:02:53,000 --> 00:03:00,000 John Stuart Reid of Keswick, England is the co-inventor of a new instrument called the... 24 00:03:00,000 --> 00:03:07,000 It converts sound into three-dimensional geometric images in water. 25 00:03:07,000 --> 00:03:13,020 What's happening is the sound is actually coming from the 26 00:03:13,040 --> 00:03:19,040 And actually creating a kind of lensing effect to allow light to bounce off those... 27 00:03:19,040 --> 00:03:23,040 So here you see that there's a pattern forming in the center. 28 00:03:23,040 --> 00:03:27,040 If I put my finger in, you can see what happens. 29 00:03:27,040 --> 00:03:31,040 That it actually disturbs the pattern completely. 30 00:03:31,040 --> 00:03:35,040 The pattern's now gone. It's gone into chaos. 31 00:03:35,040 --> 00:03:39,040 And then you can see the pattern in the center. 32 00:03:39,060 --> 00:03:45,060 If I take my finger out again and leave it for a second or two to re-stabilize, 33 00:03:45,060 --> 00:03:49,060 you can see that the pattern starts to come back again. 34 00:03:49,060 --> 00:03:53,060 So that's really interesting, isn't it? 35 00:03:53,060 --> 00:03:57,060 Here we have the beautiful song of a humpback whale. 36 00:03:57,080 --> 00:04:01,080 Some of this geometry that we're seeing is just exquisitely beautiful. 37 00:04:01,080 --> 00:04:05,080 When we look at some of the other Cymoscope images, 38 00:04:05,080 --> 00:04:11,080 we are seeing so many forms that resemble early life forms in the ocean. 39 00:04:11,080 --> 00:04:17,079 The Cymoscope may someday help us determine whether or not the pattern is real. 40 00:04:17,079 --> 00:04:21,079 We're going to have to look at it in a different light source. 41 00:04:21,099 --> 00:04:24,099 Early life forms in the ocean. 42 00:04:24,099 --> 00:04:27,099 The Cymoscope may someday help us determine 43 00:04:27,099 --> 00:04:30,099 whether this is just a fascinating coincidence 44 00:04:30,099 --> 00:04:34,099 or new evolutionary biology. 45 00:04:36,099 --> 00:04:40,099 Sound has evolved into a primary alarm system 46 00:04:40,099 --> 00:04:44,099 because we can hear danger even before we see it. 47 00:04:45,099 --> 00:04:49,099 Lots of animals use the hearing to avoid being even. 48 00:04:49,120 --> 00:04:52,120 It serves as an omnidirectional monitor 49 00:04:52,120 --> 00:04:55,120 for things that are happening in the environment. 50 00:04:55,120 --> 00:04:58,120 Sound is the sense that never sleeps. 51 00:04:58,120 --> 00:05:02,120 The brain listens even while you dream. 52 00:05:02,120 --> 00:05:06,120 If you're sleeping, you're not going to be awakened by most sounds. 53 00:05:06,120 --> 00:05:10,120 Say suppose you're attuned to the sound of a baby crying. 54 00:05:10,120 --> 00:05:14,120 That will wake you up because your brain has learned 55 00:05:14,120 --> 00:05:16,120 that that's something important for you 56 00:05:16,139 --> 00:05:19,139 to go right through whatever your defenses are 57 00:05:19,139 --> 00:05:22,139 to keep you asleep and you are awake. 58 00:05:22,139 --> 00:05:26,139 But sometimes sound plays tricks on the brain, 59 00:05:26,139 --> 00:05:31,139 bouncing around, causing echoes and turning words to mush. 60 00:05:31,139 --> 00:05:34,139 Solving problems caused by sound 61 00:05:34,139 --> 00:05:38,139 is what acoustic engineer Trevor Cox does for a living. 62 00:05:38,139 --> 00:05:42,139 I did a physics degree and I was always a musician. 63 00:05:42,159 --> 00:05:46,159 It was a way of combining my interest in music and physics together. 64 00:05:46,159 --> 00:05:49,159 Cox records sound in odd spaces 65 00:05:49,159 --> 00:05:53,159 here with a head-like device that mimics human hearing. 66 00:05:53,159 --> 00:05:57,159 I got fascinated in how architecture changes music 67 00:05:57,159 --> 00:06:00,159 and enhances and beautifies it. 68 00:06:02,159 --> 00:06:04,159 Sometimes it's about making music beautiful. 69 00:06:04,159 --> 00:06:08,159 Other times it's about speech, trying to communicate. 70 00:06:08,180 --> 00:06:11,180 Mary had a little lamb. 71 00:06:11,180 --> 00:06:15,180 It's fleeced with white as snow. 72 00:06:15,180 --> 00:06:19,180 At the town hall in Manchester, England, 73 00:06:19,180 --> 00:06:23,180 Cox explains the hearing problem caused by reverberation. 74 00:06:23,180 --> 00:06:26,180 In a big space like this, 75 00:06:26,180 --> 00:06:30,180 you have to talk slowly to make the speech tangible. 76 00:06:30,180 --> 00:06:32,180 When I talk in a building, 77 00:06:32,180 --> 00:06:35,180 you don't just get the sound straight from my voice, 78 00:06:35,199 --> 00:06:39,199 you get the reflections off the floor, the walls and the ceiling. 79 00:06:43,199 --> 00:06:49,199 And each reflection arrives at the ears at a slightly different time. 80 00:06:49,199 --> 00:06:51,199 That amplifies my voice. 81 00:06:51,199 --> 00:06:55,199 It's one of the reasons it's easy to project your voice in a space like this. 82 00:06:55,199 --> 00:06:57,199 But it's not very good for speech 83 00:06:57,199 --> 00:07:00,199 because the words start running into each other. 84 00:07:00,199 --> 00:07:03,199 The previous word lingers, mingles with the next one. 85 00:07:03,219 --> 00:07:05,219 It's a bit unintelligible. 86 00:07:07,219 --> 00:07:10,219 To hear an extreme example of this, 87 00:07:10,219 --> 00:07:12,219 go to Pisa, Italy, 88 00:07:12,219 --> 00:07:15,219 where there is a second less famous tower 89 00:07:15,219 --> 00:07:18,219 called the Baptistery of St. John. 90 00:07:18,219 --> 00:07:22,219 Here opera singers demonstrate some remarkable acoustics 91 00:07:22,219 --> 00:07:26,219 by singing notes that linger so long in the air 92 00:07:26,219 --> 00:07:30,219 a singer can harmonize with himself. 93 00:07:33,219 --> 00:07:38,219 Ah. 94 00:07:42,219 --> 00:07:47,219 Ah. 95 00:07:49,219 --> 00:07:54,219 Ah. 96 00:07:55,219 --> 00:08:00,219 Ah. 97 00:08:03,219 --> 00:08:08,219 Each note lasts a full nine seconds. 98 00:08:14,219 --> 00:08:18,219 Good acoustics are more than just entertainment. 99 00:08:18,219 --> 00:08:23,219 If the announcements in a train station, for example, are garbled... 100 00:08:23,240 --> 00:08:28,240 Passenger's might miss more than the Orient Express. 101 00:08:28,240 --> 00:08:30,240 You know, it's about life or death situation 102 00:08:30,240 --> 00:08:33,240 if someone's being evacuated because there's a fire or a bomb alert. 103 00:08:33,240 --> 00:08:36,240 It's more than just being able to hear the announcements. 104 00:08:36,240 --> 00:08:40,240 Acoustic engineers in a studio like this in Manchester 105 00:08:40,240 --> 00:08:42,240 can clean up muddy speech 106 00:08:42,240 --> 00:08:45,240 by creating a computer model of the station 107 00:08:45,240 --> 00:08:49,240 and then tweaking the sound system or the background sound 108 00:08:49,259 --> 00:08:51,259 or the buildings acoustics. 109 00:08:51,259 --> 00:08:54,259 But we can use a much more directional loudspeaker 110 00:08:54,259 --> 00:08:56,259 which is aimed at the passengers 111 00:08:56,259 --> 00:08:59,259 and away from all the reflective surfaces in the room. 112 00:08:59,259 --> 00:09:01,259 If we add some sound absorbing treatment, 113 00:09:01,259 --> 00:09:03,259 and in this case it's to the soffit 114 00:09:03,259 --> 00:09:05,259 all along the top of the structure, 115 00:09:05,259 --> 00:09:07,259 hopefully much better intelligibility. 116 00:09:07,259 --> 00:09:12,259 The train approaching platform two is the 946 train to Milan. 117 00:09:12,259 --> 00:09:15,259 Will passengers for the 946 train to Milan... 118 00:09:15,259 --> 00:09:18,259 For a theater opera singer like this 119 00:09:18,279 --> 00:09:20,279 for a theater or concert hall designer 120 00:09:20,279 --> 00:09:23,279 sitting in the sweet spot of this lab 121 00:09:23,279 --> 00:09:26,279 provides the chance to hear what their building will sound like 122 00:09:26,279 --> 00:09:28,279 before it's built 123 00:09:28,279 --> 00:09:32,279 and compare it with some of the best acoustics in the world. 124 00:09:32,279 --> 00:09:36,279 I'm going to take you to the Boston Symphony Hall in the US. 125 00:09:36,279 --> 00:09:39,279 Mary had a little lamb. 126 00:09:39,279 --> 00:09:42,279 His fleece was white as snow. 127 00:09:42,279 --> 00:09:44,279 And everywhere that Mary went... 128 00:09:44,299 --> 00:09:47,299 The secret of Symphony Hall's virtually perfect sound 129 00:09:47,299 --> 00:09:51,299 is in the math, the equation written in the 1890s 130 00:09:51,299 --> 00:09:54,299 by Harvard physicist Wallace Sabine. 131 00:09:57,299 --> 00:10:00,299 Using a pipe organ and a stopwatch, 132 00:10:00,299 --> 00:10:03,299 Sabine made thousands of measurements 133 00:10:03,299 --> 00:10:07,299 to calculate the ideal ratio between room volume 134 00:10:07,299 --> 00:10:09,299 and sound absorbing materials. 135 00:10:09,299 --> 00:10:13,299 With a reverb time of 1.9 seconds, 136 00:10:13,319 --> 00:10:17,319 Symphony Hall is considered one of the top concert halls in the world. 137 00:10:17,319 --> 00:10:21,319 And the Sabine equation underlies the software 138 00:10:21,319 --> 00:10:25,319 that allows acoustic engineers Ping Chen and Gary Mack 139 00:10:25,319 --> 00:10:29,319 to fine tune the sound of a modern performing arts center. 140 00:10:32,319 --> 00:10:35,319 They start by measuring the time it takes 141 00:10:35,319 --> 00:10:38,319 for sound to bounce off the walls and the ceiling, 142 00:10:38,319 --> 00:10:42,319 keeping in mind the ideal times for voice and music. 143 00:10:43,319 --> 00:10:46,319 They create a computer model of the soundscape, 144 00:10:46,319 --> 00:10:49,319 what they call an auralization. 145 00:10:49,319 --> 00:10:52,319 The back walls below the balcony, 146 00:10:52,319 --> 00:10:55,319 that's going to be the longest reflections 147 00:10:55,319 --> 00:10:57,319 that we're trying to control. 148 00:10:57,319 --> 00:11:00,319 Which allows them to customize the way a room sounds 149 00:11:00,319 --> 00:11:02,319 depending on what it's used for. 150 00:11:02,319 --> 00:11:05,319 Those acoustical panels, they're retractable. 151 00:11:05,319 --> 00:11:08,319 So for speech, we're going to have them in place. 152 00:11:08,319 --> 00:11:11,319 But for music, we're going to retract them 153 00:11:11,340 --> 00:11:14,340 to have the lateral reflections for music. 154 00:11:14,340 --> 00:11:18,340 So these reflectors should probably be a little bit lower. 155 00:11:18,340 --> 00:11:22,340 A series of mobile panels converts this theater stage 156 00:11:22,340 --> 00:11:26,340 to a music venue in a matter of minutes. 157 00:11:41,320 --> 00:11:45,340 We make the space sound like it's supposed to sound. 158 00:12:11,340 --> 00:12:15,340 People respond to sound in varying ways. 159 00:12:18,340 --> 00:12:22,340 Much depends on who's listening and what's making the sound. 160 00:12:23,340 --> 00:12:27,340 Usually the sounds of nature, even when loud, 161 00:12:27,340 --> 00:12:31,340 tend to be less annoying than the sounds of modern life. 162 00:12:34,340 --> 00:12:37,340 But how much is too much? 163 00:12:37,340 --> 00:12:40,340 A decibel meter measures the length of the sound 164 00:12:40,360 --> 00:12:43,360 and a decibel meter measures the level of sound pressure. 165 00:12:43,360 --> 00:12:46,360 Normal conversation is roughly 60. 166 00:12:46,360 --> 00:12:49,360 Because the scale is logarithmic, 167 00:12:49,360 --> 00:12:52,360 70 decibels is twice as loud. 168 00:12:54,360 --> 00:12:58,360 Hearing protection is recommended at 85. 169 00:12:59,360 --> 00:13:02,360 Above 90, sound is damaging. 170 00:13:03,360 --> 00:13:06,360 Prolonged exposure to noise at this level 171 00:13:06,360 --> 00:13:09,360 causes hearing loss. 172 00:13:10,360 --> 00:13:13,360 Pain begins at 125. 173 00:13:15,360 --> 00:13:19,360 Loud sound produces a fight or flight response. 174 00:13:19,360 --> 00:13:22,360 Stress, anxiety, increased heart rate, 175 00:13:22,360 --> 00:13:25,360 loss of sleep, fatigue, and social conflict 176 00:13:25,360 --> 00:13:29,360 have all been linked to louder environments. 177 00:13:34,360 --> 00:13:38,360 Psychologist Alan Poliakoff of the University of Manchester 178 00:13:38,379 --> 00:13:42,379 has studied how sound even affects the taste of food. 179 00:13:43,379 --> 00:13:46,379 For this experiment, we wanted to target 180 00:13:46,379 --> 00:13:49,379 salty-flavoured foods and sweet foods. 181 00:13:49,379 --> 00:13:53,379 We asked participants to wear the headphones. 182 00:13:53,379 --> 00:13:56,379 There was one condition where there was no noise at all, 183 00:13:56,379 --> 00:14:00,379 one where it was quiet, so this was 45 to 55 decibels. 184 00:14:03,379 --> 00:14:07,379 Or louder noise, which was the 75 to 85 decibels. 185 00:14:07,399 --> 00:14:10,399 The participant would close their eyes, 186 00:14:10,399 --> 00:14:13,399 so they didn't know which of the foods was coming 187 00:14:13,399 --> 00:14:16,399 and they would reach out and then they would eat it. 188 00:14:16,399 --> 00:14:19,399 People found that they rated the food less sweet 189 00:14:19,399 --> 00:14:23,399 and less salty in the presence of the background noise. 190 00:14:23,399 --> 00:14:27,399 This may explain why airline food often tastes bland. 191 00:14:27,399 --> 00:14:30,399 One theory is that high background noise 192 00:14:30,399 --> 00:14:34,399 prevents the brain from following the sound. 193 00:14:34,419 --> 00:14:38,419 Prevents the brain from fully processing other sensory input. 194 00:14:38,419 --> 00:14:41,419 The white noise actually distracts you 195 00:14:41,419 --> 00:14:44,419 from processing the taste as much as you might 196 00:14:44,419 --> 00:14:47,419 otherwise do so, so it appears less strong to you 197 00:14:47,419 --> 00:14:49,419 because you're distracted. 198 00:14:58,419 --> 00:15:01,419 The volume of sound in cities everywhere 199 00:15:01,439 --> 00:15:03,439 is constantly changing. 200 00:15:08,439 --> 00:15:11,439 Sounds that used to be strong and clear 201 00:15:14,439 --> 00:15:18,439 are getting lost in the din of urban noise. 202 00:15:20,439 --> 00:15:22,439 So isn't that a great sound? 203 00:15:22,439 --> 00:15:24,439 Right in the centre of Vancouver. 204 00:15:24,439 --> 00:15:26,439 Barry Truax is an emeritus professor 205 00:15:26,439 --> 00:15:29,439 of acoustic communication at Simon & Schuster 206 00:15:29,460 --> 00:15:30,460 University. 207 00:15:30,460 --> 00:15:34,460 Truax believes that preservation of iconic sounds 208 00:15:34,460 --> 00:15:37,460 or sonic landmarks is just as important 209 00:15:37,460 --> 00:15:40,460 as preserving a city's visual landmarks. 210 00:15:40,460 --> 00:15:43,460 He and a team of researchers set out to measure 211 00:15:43,460 --> 00:15:46,460 how far away they can hear the bells 212 00:15:46,460 --> 00:15:48,460 of Holy Rosary Cathedral. 213 00:15:48,460 --> 00:15:51,460 His concern is that the roar of the street 214 00:15:51,460 --> 00:15:55,460 is drowning out the city's historic sounds. 215 00:15:55,480 --> 00:15:57,480 It really began in the early 1970s 216 00:15:57,480 --> 00:15:59,480 with a much more ambitious title, 217 00:15:59,480 --> 00:16:01,480 the World Soundscape Project. 218 00:16:01,480 --> 00:16:03,480 The Canadian composer R. Murray Schaeffer 219 00:16:03,480 --> 00:16:05,480 who taught at Simon Fraser University 220 00:16:05,480 --> 00:16:08,480 decided that instead of being just anti-noise 221 00:16:08,480 --> 00:16:10,480 that it would be much more positive 222 00:16:10,480 --> 00:16:13,480 to create a soundscape approach. 223 00:16:17,480 --> 00:16:21,480 Which is sound marks as oral landmarks 224 00:16:21,500 --> 00:16:23,500 and so first of all it gets everybody thinking 225 00:16:23,500 --> 00:16:25,500 well what is so special? 226 00:16:33,500 --> 00:16:35,500 And there you have it, one of arguably 227 00:16:35,500 --> 00:16:38,500 the most unique sound mark in Canada. 228 00:16:38,500 --> 00:16:40,500 First four notes of the national anthem 229 00:16:40,500 --> 00:16:42,500 for almost 50 years now that sound has become 230 00:16:42,500 --> 00:16:44,500 a part of the Vancouver soundscape 231 00:16:44,500 --> 00:16:46,500 and probably is the most recognisable one 232 00:16:46,500 --> 00:16:47,500 out there. 233 00:16:47,500 --> 00:16:49,500 And it's a very special one. 234 00:16:49,519 --> 00:16:51,519 It really is the most recognisable one 235 00:16:51,519 --> 00:16:53,519 outside of Vancouver. 236 00:17:00,519 --> 00:17:02,519 What Murray Schaeffer created 237 00:17:02,519 --> 00:17:04,519 with the World Soundscape Project 238 00:17:04,519 --> 00:17:06,519 was a whole new field of study 239 00:17:06,519 --> 00:17:08,519 called acoustic ecology. 240 00:17:08,519 --> 00:17:10,519 It's essentially an oral ethnography 241 00:17:10,519 --> 00:17:13,519 that you actually understand society 242 00:17:13,519 --> 00:17:15,519 like an anthropologist would 243 00:17:15,519 --> 00:17:18,519 but using your ears and not just your eyes. 244 00:17:19,519 --> 00:17:22,519 These bells used to be heard all over town. 245 00:17:22,519 --> 00:17:25,519 Now, even if you listen carefully 246 00:17:25,519 --> 00:17:28,519 even if you can still see the bell tower 247 00:17:30,519 --> 00:17:33,519 the sound is lost after a few city blocks. 248 00:17:33,519 --> 00:17:35,519 SIRENS 249 00:17:39,519 --> 00:17:41,519 So there you go, there's the difference 250 00:17:41,519 --> 00:17:44,519 between the acoustic world and the mechanical world. 251 00:17:46,519 --> 00:17:47,519 Half a block. 252 00:17:47,539 --> 00:17:49,539 A hundred years ago they could talk about 253 00:17:49,539 --> 00:17:51,539 listening to the beautiful chimes 254 00:17:51,539 --> 00:17:53,539 of the Holy Rosary Cathedral 255 00:17:53,539 --> 00:17:55,539 in the Hillcrest area and also South Vancouver. 256 00:17:55,539 --> 00:17:57,539 You know how many miles away that is. 257 00:17:59,539 --> 00:18:01,539 A hundred years ago, Holy Rosary 258 00:18:01,539 --> 00:18:04,539 was one of the tallest buildings in the city. 259 00:18:04,539 --> 00:18:07,539 Today, it's lost in a concrete forest. 260 00:18:10,539 --> 00:18:13,539 If the ringing could be heard in Hillcrest 261 00:18:14,539 --> 00:18:16,539 nearly 40 blocks away 262 00:18:16,559 --> 00:18:19,559 then the acoustic profile of the bells 263 00:18:19,559 --> 00:18:23,559 has shrunk to less than a tenth of what it was. 264 00:18:24,559 --> 00:18:26,559 But this is only part of the story. 265 00:18:26,559 --> 00:18:29,559 The sound of city streets in Vancouver 266 00:18:29,559 --> 00:18:32,559 was entirely different a century ago. 267 00:18:32,559 --> 00:18:34,559 The only moving pictures from those days 268 00:18:34,559 --> 00:18:37,559 shot from the front of a streetcar are silent. 269 00:18:37,559 --> 00:18:39,559 But with the same technology 270 00:18:39,559 --> 00:18:42,559 used to create movie soundtracks 271 00:18:42,559 --> 00:18:44,559 it is possible to experience 272 00:18:44,579 --> 00:18:47,579 what the city sounded like in 1906 273 00:18:47,579 --> 00:18:49,579 when the bells were new. 274 00:18:49,579 --> 00:18:52,579 I'm trying to make people jump into the scene 275 00:18:52,579 --> 00:18:54,579 and live the scene. 276 00:18:54,579 --> 00:18:56,579 So I thought, well, maybe what we'll do 277 00:18:56,579 --> 00:18:58,579 is we will play a bit of the scene, 278 00:18:58,579 --> 00:19:00,579 look around us and see what we hear. 279 00:19:04,579 --> 00:19:07,579 This is only two blocks away from the Holy Rosary bells, 280 00:19:07,579 --> 00:19:09,579 so have you tried putting those in? 281 00:19:09,579 --> 00:19:11,579 Oh, for sure. 282 00:19:14,579 --> 00:19:16,579 Mm-hmm, right. 283 00:19:21,579 --> 00:19:24,579 Notice how they're really audible over everything else. 284 00:19:25,579 --> 00:19:28,579 That kind of traffic didn't dominate like it does now. 285 00:19:28,579 --> 00:19:31,579 I mean, this is all on a very human scale. 286 00:19:31,579 --> 00:19:34,579 Watching all those people racing across the street 287 00:19:34,579 --> 00:19:36,579 it looks actually positively dangerous. 288 00:19:36,579 --> 00:19:39,579 So they obviously are relying on their ears 289 00:19:39,579 --> 00:19:42,579 as well as their eyes to tell them what was happening. 290 00:19:42,599 --> 00:19:44,599 The sounds are clear and distinct, 291 00:19:44,599 --> 00:19:46,599 and it isn't dominated by just one sound, 292 00:19:46,599 --> 00:19:48,599 such as traffic would be today. 293 00:19:48,599 --> 00:19:50,599 The point, according to Truax, 294 00:19:50,599 --> 00:19:53,599 is that cities have always been loud. 295 00:19:53,599 --> 00:19:57,599 But back in the day, it was a loud you could live with. 296 00:20:00,599 --> 00:20:02,599 Take a tour of Venice, 297 00:20:02,599 --> 00:20:04,599 and you'll hear what cities sounded like 298 00:20:04,599 --> 00:20:07,599 before the Industrial Revolution. 299 00:20:07,599 --> 00:20:09,599 Once you get out of the city, 300 00:20:09,619 --> 00:20:11,619 you'll hear what the world sounded like 301 00:20:11,619 --> 00:20:14,619 before the Industrial Revolution. 302 00:20:14,619 --> 00:20:17,619 Once you get away from the Vaporetto transit boats 303 00:20:17,619 --> 00:20:21,619 and slide into the narrow little canals called Rios, 304 00:20:21,619 --> 00:20:23,619 you hear what the world sounded like 305 00:20:23,619 --> 00:20:26,619 before internal combustion. 306 00:20:26,619 --> 00:20:29,619 Instead of gasoline and diesel engines, 307 00:20:29,619 --> 00:20:32,619 you hear voices and footsteps. 308 00:20:32,639 --> 00:20:37,639 But even here, sound has long had an uncanny power 309 00:20:37,639 --> 00:20:39,639 over people's lives. 310 00:20:39,639 --> 00:20:41,639 And as it turns out, 311 00:20:41,639 --> 00:20:44,639 people were constantly listening to their city, 312 00:20:44,639 --> 00:20:46,639 and this came as a huge surprise. 313 00:20:46,639 --> 00:20:48,639 They were listening to their buildings, 314 00:20:48,639 --> 00:20:50,639 they were listening to the way 315 00:20:50,639 --> 00:20:53,639 in which the city talked to them in various ways. 316 00:20:53,639 --> 00:20:56,639 Art historian Neil Atkinson is fascinated 317 00:20:56,639 --> 00:20:59,639 with the way sound organized the workday. 318 00:20:59,660 --> 00:21:02,660 Long before radio, TV, and the Internet, 319 00:21:02,660 --> 00:21:05,660 and even Holy Rosary in Vancouver, 320 00:21:05,660 --> 00:21:08,660 bells were a primary means of communication. 321 00:21:10,660 --> 00:21:12,660 Before people had watches, 322 00:21:12,660 --> 00:21:16,660 the sound of bells controlled their every waking moment, 323 00:21:16,660 --> 00:21:19,660 and it wasn't just the church that rang them. 324 00:21:19,660 --> 00:21:22,660 The big mountain gona that rings in that tower 325 00:21:22,660 --> 00:21:24,660 that signifies that the dock workers 326 00:21:24,660 --> 00:21:26,660 have to be in the arsenal, 327 00:21:26,680 --> 00:21:28,680 or during the day, bells will ring 328 00:21:28,680 --> 00:21:31,680 to make sure that magistrates are in their council halls, 329 00:21:31,680 --> 00:21:34,680 that lawyers and jurists are in the courts. 330 00:21:34,680 --> 00:21:37,680 By the time that the bells finish, 331 00:21:37,680 --> 00:21:39,680 everyone has to be in place. 332 00:21:39,680 --> 00:21:42,680 So there's this kind of acoustic organization 333 00:21:42,680 --> 00:21:46,680 or choreography to the daily rhythms of the city. 334 00:21:47,680 --> 00:21:50,680 The same was true in other Renaissance cities 335 00:21:50,680 --> 00:21:52,680 such as Florence. 336 00:21:52,680 --> 00:21:54,680 Here, the city's first town hall 337 00:21:54,700 --> 00:21:57,700 had its own bell tower to rival the ringing 338 00:21:57,700 --> 00:22:00,700 from the church's main cathedral. 339 00:22:01,700 --> 00:22:04,700 The government's bell had to be the biggest and the loudest, 340 00:22:04,700 --> 00:22:07,700 big enough and loud enough, from a tower high enough 341 00:22:07,700 --> 00:22:09,700 in order to establish their legitimacy 342 00:22:09,700 --> 00:22:11,700 and authority over the city. 343 00:22:11,700 --> 00:22:13,700 So what the regime was doing was acoustically 344 00:22:13,700 --> 00:22:15,700 trying to insert itself into the sounds 345 00:22:15,700 --> 00:22:18,700 that the Christian church had been making for centuries. 346 00:22:18,720 --> 00:22:21,720 But it wasn't just city hall and the church 347 00:22:21,720 --> 00:22:24,720 that wanted to control sound. 348 00:22:24,720 --> 00:22:29,720 In 1378, wool workers who toiled at looms like these, 349 00:22:29,720 --> 00:22:31,720 who had no voice in government, 350 00:22:31,720 --> 00:22:36,720 launched a revolution by seizing control of the bells. 351 00:22:36,720 --> 00:22:39,720 Within a few minutes, eight bells were ringing 352 00:22:39,720 --> 00:22:41,720 and the bell would ring. 353 00:22:41,720 --> 00:22:43,720 The bell was ringing, 354 00:22:43,720 --> 00:22:45,720 and the bell would ring, 355 00:22:45,740 --> 00:22:47,740 and the bell would ring. 356 00:22:47,740 --> 00:22:49,740 Within a few minutes, eight bell towers 357 00:22:49,740 --> 00:22:51,740 around the periphery of Florence were ringing 358 00:22:51,740 --> 00:22:53,740 to signal and coordinate what turned out to be 359 00:22:53,740 --> 00:22:55,740 one of the first, if not the first, 360 00:22:55,740 --> 00:22:58,740 successful worker revolution in Europe. 361 00:22:58,740 --> 00:23:00,740 Having hijacked the bells, 362 00:23:00,740 --> 00:23:04,740 as many as 10,000 workers swarmed into the public square 363 00:23:04,740 --> 00:23:08,740 outside city hall to voice their demands. 364 00:23:08,740 --> 00:23:12,740 And this is exactly what happened in Tahrir Square in 2011 365 00:23:12,740 --> 00:23:14,740 when Egyptians gathered in the square 366 00:23:14,759 --> 00:23:17,759 who wouldn't stop making noise, who would not leave. 367 00:23:17,759 --> 00:23:20,759 The bells were the twitter of their day. 368 00:23:22,759 --> 00:23:25,759 The sound of the crowd penetrated the walls of the palace, 369 00:23:25,759 --> 00:23:28,759 so much so that the government gave up. 370 00:23:28,759 --> 00:23:31,759 They came down, they handed the keys to the palace, 371 00:23:31,759 --> 00:23:33,759 and they literally went home. 372 00:23:33,759 --> 00:23:35,759 The people had finally won. 373 00:23:40,759 --> 00:23:43,759 Noise is a natural byproduct of human activity. 374 00:23:44,759 --> 00:23:50,759 So silence, or the use of quieter technology, 375 00:23:50,759 --> 00:23:54,759 has become a valuable commodity in our loud cities. 376 00:23:56,759 --> 00:23:58,759 From a distance, you can't hear us at all. 377 00:23:58,759 --> 00:24:00,759 You can't smell us either. 378 00:24:00,759 --> 00:24:03,759 Sheldon Wright, out of Vancouver, 379 00:24:03,759 --> 00:24:05,759 has created a landscaping company 380 00:24:05,759 --> 00:24:09,759 that works entirely without gasoline-powered tools. 381 00:24:09,759 --> 00:24:11,759 Back in the bad old days, 382 00:24:11,759 --> 00:24:13,759 we used to be covered in two-stroke, 383 00:24:13,779 --> 00:24:16,779 and you're in a wall of sound all the time and covered in dust. 384 00:24:16,779 --> 00:24:18,779 Now you're just covered in dust. 385 00:24:19,779 --> 00:24:23,779 At first, Wright Out's new company did everything by hand. 386 00:24:23,779 --> 00:24:26,779 Then technology changed. 387 00:24:28,779 --> 00:24:31,779 The electric equipment we have is all lithium battery powered, 388 00:24:31,779 --> 00:24:34,779 so we've almost got the Teslas of lawnmower equipment. 389 00:24:35,779 --> 00:24:37,779 This equipment does make noise, 390 00:24:37,779 --> 00:24:41,779 but only half as much as internal combustion engines. 391 00:24:41,799 --> 00:24:43,799 What I heard on a regular basis was, 392 00:24:43,799 --> 00:24:45,799 we're so tired of the noise. 393 00:24:45,799 --> 00:24:46,799 We're tired of the smell. 394 00:24:46,799 --> 00:24:49,799 We're tired of our entire day being interrupted 395 00:24:49,799 --> 00:24:51,799 when a landscaping company shows up. 396 00:24:53,799 --> 00:24:55,799 You're not going to get away from noise, 397 00:24:55,799 --> 00:24:58,799 but anything that can be done to reduce it, 398 00:24:58,799 --> 00:25:00,799 it helps with stress levels. 399 00:25:02,799 --> 00:25:04,799 What we're talking about affects everyone. 400 00:25:04,799 --> 00:25:06,799 Whether you say, oh, I can get used to it, 401 00:25:06,799 --> 00:25:08,799 it doesn't bother me, or something like that, 402 00:25:08,799 --> 00:25:10,799 but it always has an effect. 403 00:25:11,799 --> 00:25:13,799 Both physiologically, psychologically, 404 00:25:13,799 --> 00:25:15,799 and in terms of communication. 405 00:25:15,799 --> 00:25:18,799 It's, in many cases, the soundscape 406 00:25:18,799 --> 00:25:20,799 that gives you a quality of life. 407 00:25:21,799 --> 00:25:25,799 What if sound were your primary means of finding food? 408 00:25:27,799 --> 00:25:29,799 Your main method of survival? 409 00:25:31,799 --> 00:25:34,799 That's how it is for big brown bats. 410 00:25:35,799 --> 00:25:37,799 Bats are really neat animals, 411 00:25:37,799 --> 00:25:39,799 and they have to be able to do everything 412 00:25:39,819 --> 00:25:41,819 without relying on vision. 413 00:25:41,819 --> 00:25:44,819 James Simmons, a professor of biology 414 00:25:44,819 --> 00:25:47,819 at Brown University in Providence, Rhode Island, 415 00:25:47,819 --> 00:25:50,819 is setting up a maze of plastic chains. 416 00:25:50,819 --> 00:25:55,819 He and postdoc Kelsey Hom are testing the ability 417 00:25:55,819 --> 00:25:57,819 of bats to navigate with sound, 418 00:25:57,819 --> 00:26:01,819 to help improve sonar navigation by humans. 419 00:26:02,819 --> 00:26:05,819 Bats are very comfortable flying through the branches 420 00:26:05,819 --> 00:26:06,819 and leaves of vegetation. 421 00:26:06,819 --> 00:26:07,819 And while they're doing this, 422 00:26:07,819 --> 00:26:08,819 they're looking for insects. 423 00:26:08,839 --> 00:26:10,839 And they're flying several meters per second. 424 00:26:11,839 --> 00:26:14,839 So the experiment uses a slow-motion camera 425 00:26:14,839 --> 00:26:17,839 and simulates the bat's natural environment. 426 00:26:19,839 --> 00:26:21,839 So the way we thought to do this 427 00:26:21,839 --> 00:26:23,839 is to replace the vegetation 428 00:26:23,839 --> 00:26:26,839 with these black plastic hanging chains. 429 00:26:26,839 --> 00:26:29,839 You get something acoustically very similar 430 00:26:29,839 --> 00:26:31,839 to a whole field of vegetation. 431 00:26:33,839 --> 00:26:35,839 Because the sound a bat makes 432 00:26:35,839 --> 00:26:37,839 is beyond the range of human hearing, 433 00:26:37,859 --> 00:26:39,859 Simmons uses an ultrasound detector 434 00:26:39,859 --> 00:26:43,859 to convert the signals to a frequency we can hear. 435 00:26:47,859 --> 00:26:49,859 Simmons is particularly interested 436 00:26:49,859 --> 00:26:53,859 in how a bat's brain is able to process sound signals 437 00:26:53,859 --> 00:26:57,859 and perform complex mathematics at extremely high speeds. 438 00:26:59,859 --> 00:27:01,859 So the bats emit sounds 439 00:27:01,859 --> 00:27:04,859 and do lots of fast computations in the brain 440 00:27:04,879 --> 00:27:06,879 about the arrival time of the echoes 441 00:27:06,879 --> 00:27:08,879 coming from different distances. 442 00:27:08,879 --> 00:27:10,879 And the trick of sonar 443 00:27:10,879 --> 00:27:12,879 is to be able to do these computations quickly enough 444 00:27:12,879 --> 00:27:16,879 that you can see the scene before you emit the next sound. 445 00:27:16,879 --> 00:27:19,879 We can't do that with our digital computers 446 00:27:19,879 --> 00:27:21,879 because they're not fast enough. 447 00:27:21,879 --> 00:27:25,879 The fascinating discovery is that bats actually 448 00:27:25,879 --> 00:27:29,879 form 3-D images based on sonar echoes. 449 00:27:30,879 --> 00:27:32,879 When we see something with vision 450 00:27:32,900 --> 00:27:35,900 we see color and we see texture and lots of things like that, 451 00:27:35,900 --> 00:27:38,900 the sonar image that a bat gets of an insect 452 00:27:38,900 --> 00:27:42,900 is stripped down to only three or four body parts. 453 00:27:42,900 --> 00:27:45,900 The bat will aim its sound at the insect 454 00:27:45,900 --> 00:27:48,900 and get a bunch of echoes from the different parts of the target. 455 00:27:48,900 --> 00:27:50,900 But when it's chasing the insect, 456 00:27:50,900 --> 00:27:52,900 it doesn't go straight toward it. 457 00:27:52,900 --> 00:27:56,900 It follows a curved path so that each time it emits the sound, 458 00:27:56,900 --> 00:27:59,900 it's getting a slightly different angular view of the target. 459 00:27:59,900 --> 00:28:01,900 And by rotating this way, 460 00:28:01,920 --> 00:28:03,920 the bat gets to see the parts of the object 461 00:28:03,920 --> 00:28:06,920 in their real three-dimensional locations. 462 00:28:06,920 --> 00:28:09,920 Bats actually see with sound. 463 00:28:11,920 --> 00:28:13,920 Perhaps even more astonishing 464 00:28:13,920 --> 00:28:17,920 is the fact that some humans are able to do the same thing. 465 00:28:17,920 --> 00:28:19,920 So we've got a tree here. 466 00:28:21,920 --> 00:28:23,920 I'll turn here. 467 00:28:23,920 --> 00:28:25,920 By 13 months of age, 468 00:28:25,920 --> 00:28:27,920 Daniel Kish had lost both eyes 469 00:28:27,920 --> 00:28:30,920 to a cancer called retinoblastoma. 470 00:28:30,940 --> 00:28:33,940 Instinctively, he soon began to make clicking sounds 471 00:28:33,940 --> 00:28:37,940 and started to echo-locate just like bats do. 472 00:28:37,940 --> 00:28:40,940 Those clicks you hear are from his mouth, 473 00:28:40,940 --> 00:28:42,940 not the tapping of his cane. 474 00:28:42,940 --> 00:28:48,940 Big open area, but we're approaching a structure. 475 00:28:48,940 --> 00:28:50,940 He calls this flash sonar. 476 00:28:52,940 --> 00:28:56,940 Flash sonar has become Kish's primary means of navigation. 477 00:28:56,960 --> 00:28:59,960 So in my case, it wasn't something I was really aware of. 478 00:28:59,960 --> 00:29:03,960 It just happened as a consequence of my childhood experiences. 479 00:29:05,960 --> 00:29:11,960 I get an image that occurs in a 360-degree field. 480 00:29:12,960 --> 00:29:18,960 The roof structure we're under isn't totally solid somehow. 481 00:29:18,960 --> 00:29:22,960 It's got openings in it, as if it were slatted or... 482 00:29:22,980 --> 00:29:25,980 I describe them as fuzzy geometry, 483 00:29:25,980 --> 00:29:29,980 moving, dynamic figures. 484 00:29:29,980 --> 00:29:32,980 They have depth and contour and character 485 00:29:32,980 --> 00:29:37,980 and they provide me with information about location, density. 486 00:29:37,980 --> 00:29:40,980 And you can also kind of hear things around corners 487 00:29:40,980 --> 00:29:42,980 and you can hear things through objects. 488 00:29:42,980 --> 00:29:46,980 So it almost has this kind of omnipresence about it. 489 00:29:47,000 --> 00:29:53,000 As a kid, I was raised to think of myself as pretty unremarkable. 490 00:29:55,000 --> 00:29:59,000 My parents, their emphasis, their regard for me 491 00:29:59,000 --> 00:30:03,000 was, you're a kid like any other kid. 492 00:30:03,000 --> 00:30:06,000 He got his first bicycle, 493 00:30:06,000 --> 00:30:10,000 and he was a kid who was always looking at his parents 494 00:30:10,000 --> 00:30:14,000 and thinking, you know, you're a kid like any other kid. 495 00:30:14,019 --> 00:30:18,019 He got his first bicycle at the age of six. 496 00:30:20,019 --> 00:30:23,019 I learned. I learned to click like a maniac 497 00:30:23,019 --> 00:30:26,019 and I learned to ride around the neighbourhood. 498 00:30:26,019 --> 00:30:29,019 And if I ran into a pole, 499 00:30:29,019 --> 00:30:32,019 my parents just didn't make a big deal out of it. 500 00:30:32,019 --> 00:30:35,019 Running into a pole is a drag. 501 00:30:35,019 --> 00:30:41,019 But never being allowed to run into a pole is a disaster. 502 00:30:44,019 --> 00:30:48,019 Riding a bike blind has become a kind of stunt he does 503 00:30:48,019 --> 00:30:52,019 to raise awareness that the brain can adapt 504 00:30:52,019 --> 00:30:56,019 and that people can do far more than they realise. 505 00:31:05,019 --> 00:31:08,019 15 years ago, it was just unheard of. 506 00:31:08,019 --> 00:31:12,019 So if you'd all close your eyes for just a moment, 507 00:31:12,039 --> 00:31:15,039 you're going to see a little bit of the light, 508 00:31:15,039 --> 00:31:18,039 and you're going to learn a bit of flash sonar. 509 00:31:18,039 --> 00:31:21,039 Now you have scientists studying it, 510 00:31:21,039 --> 00:31:23,039 you have instructors wanting to learn it, 511 00:31:23,039 --> 00:31:25,039 you have instructors wanting to teach it, 512 00:31:25,039 --> 00:31:28,039 you have blind people wanting to learn it. 513 00:31:28,039 --> 00:31:32,039 Being able to navigate comfortably in any environment 514 00:31:32,039 --> 00:31:36,039 under any circumstances, nothing can be more fundamental 515 00:31:36,039 --> 00:31:39,039 to freedom than being able to do that. 516 00:31:39,059 --> 00:31:43,059 He was asked to draw a picture to recreate from memory 517 00:31:43,059 --> 00:31:47,059 the image he got from nothing more than the sound of clicks. 518 00:31:47,059 --> 00:31:50,059 I'll just do a little dash line here. 519 00:31:50,059 --> 00:31:53,059 And remember, he had never set foot 520 00:31:53,059 --> 00:31:55,059 in this pavilion before today. 521 00:31:55,059 --> 00:32:00,059 And then we had another column kind of across the way here. 522 00:32:00,059 --> 00:32:04,059 Definitely taxing my artistic merits here. 523 00:32:04,059 --> 00:32:07,059 Should I say ta-da? Ta-da! 524 00:32:07,079 --> 00:32:10,079 The accuracy of the image is uncanny. 525 00:32:10,079 --> 00:32:15,079 It shows that there's an actual imaging process taking place. 526 00:32:15,079 --> 00:32:20,079 You're using sound instead of light to create a picture. 527 00:32:22,079 --> 00:32:26,079 Okay. Well, I was right about the roof. 528 00:32:26,079 --> 00:32:31,079 So humans can see with sound just like bats. 529 00:32:31,079 --> 00:32:33,079 But bats have an advantage. 530 00:32:33,079 --> 00:32:36,079 They aren't affected by noise. 531 00:32:36,099 --> 00:32:38,099 Back at Brown University in Providence, 532 00:32:38,099 --> 00:32:42,099 Professor Simmons explains that bats normally live 533 00:32:42,099 --> 00:32:44,099 in a very loud world. 534 00:32:44,099 --> 00:32:46,099 The sonar sounds of many bats 535 00:32:46,099 --> 00:32:50,099 are 120 to 130 decibels of sound. 536 00:32:50,099 --> 00:32:54,099 You have 50 bats all flying around in the same small space. 537 00:32:54,099 --> 00:32:57,099 All the bats in that space are exposing themselves 538 00:32:57,099 --> 00:33:00,099 to this intense sound. 539 00:33:00,099 --> 00:33:04,099 And they appear not to suffer the noise-induced hearing loss 540 00:33:04,119 --> 00:33:07,119 that follows that, something that we would normally suffer. 541 00:33:07,119 --> 00:33:09,119 And we need to find out what it is they're doing 542 00:33:09,119 --> 00:33:11,119 to protect themselves. 543 00:33:16,119 --> 00:33:18,119 In the course of a human lifetime, 544 00:33:18,119 --> 00:33:23,119 loud sounds cause physical damage to the inner ear. 545 00:33:23,119 --> 00:33:27,119 Tiny hair cells in the cochlea convert sound waves 546 00:33:27,119 --> 00:33:31,119 to electrical signals that go to the brain. 547 00:33:31,139 --> 00:33:34,139 The cells most prone to noise-induced damage 548 00:33:34,139 --> 00:33:39,139 are the ones that act like an amplifier for soft sounds. 549 00:33:39,139 --> 00:33:43,139 With hearing loss, people who have cochlear damage, 550 00:33:43,139 --> 00:33:45,139 those outer hair cells get damaged. 551 00:33:45,139 --> 00:33:46,139 So you lose the amplifier. 552 00:33:46,139 --> 00:33:48,139 Basically, you lose the knob 553 00:33:48,139 --> 00:33:51,139 for turning it up on your stereo system. 554 00:33:51,139 --> 00:33:56,139 But noise-induced hearing loss is only part of the problem. 555 00:33:56,139 --> 00:33:59,139 As we age, the brain's processing of audio signals 556 00:33:59,160 --> 00:34:04,160 slows down, making speech harder to understand. 557 00:34:04,160 --> 00:34:09,160 So it's not just the question of turning up the volume. 558 00:34:09,160 --> 00:34:12,160 Our auditory system is able to pick up 559 00:34:12,160 --> 00:34:14,160 little small gaps in speech. 560 00:34:14,160 --> 00:34:19,160 A common example is the word say versus stay. 561 00:34:19,160 --> 00:34:22,160 The difference between say and stay 562 00:34:22,160 --> 00:34:26,160 is actually a little pause right when the T happens. 563 00:34:26,160 --> 00:34:28,160 These are actually scalp recordings 564 00:34:28,159 --> 00:34:30,159 that we record through EEG. 565 00:34:30,159 --> 00:34:33,159 On the right here, we have a 16-millisecond gap, 566 00:34:33,159 --> 00:34:37,159 and it would be akin to trying to process the sound stay. 567 00:34:37,159 --> 00:34:40,159 There's a little gap when the T happens. 568 00:34:40,159 --> 00:34:42,159 With age-related hearing loss, 569 00:34:42,159 --> 00:34:45,159 these gaps are harder to detect, 570 00:34:45,159 --> 00:34:49,159 so T's and other consonants become muddy. 571 00:34:49,159 --> 00:34:53,159 So you can hear, you know, A-E-I-O-U, 572 00:34:53,159 --> 00:34:56,159 but you're having trouble with the consonants 573 00:34:56,159 --> 00:34:59,159 that surround those vowels. 574 00:34:59,159 --> 00:35:02,159 At the University of South Florida in Tampa, 575 00:35:02,159 --> 00:35:06,159 scientists are testing a new drug that might help. 576 00:35:06,159 --> 00:35:09,159 In a study that began with mice, 577 00:35:09,159 --> 00:35:12,159 they learned that the drug can improve sound perception 578 00:35:12,159 --> 00:35:16,159 by stimulating nerve channels in the brain. 579 00:35:16,159 --> 00:35:20,159 There are little channels that process potassium. 580 00:35:20,159 --> 00:35:25,159 Nerve cells rely on the proper concentration of potassium. 581 00:35:26,159 --> 00:35:31,159 The new drug adds potassium to these sound-processing channels. 582 00:35:31,159 --> 00:35:36,159 As you age, the number of these channels declines. 583 00:35:36,159 --> 00:35:40,159 The drug will increase the activity 584 00:35:40,159 --> 00:35:44,159 or the effectiveness of the remaining channels. 585 00:35:44,159 --> 00:35:47,159 We are ready to do some EEG testing. 586 00:35:47,159 --> 00:35:49,159 This is where we're going to... 587 00:35:49,159 --> 00:35:52,159 After the Florida team successfully tested the drug on mice, 588 00:35:52,159 --> 00:35:55,159 the U.S. Food and Drug Administration 589 00:35:55,159 --> 00:35:59,159 has approved a phase two clinical trial on humans. 590 00:35:59,159 --> 00:36:02,159 What we're going to do is put this electrode cap on. 591 00:36:02,159 --> 00:36:04,159 He's going to listen to some sound sources, 592 00:36:04,159 --> 00:36:06,159 and what we really want to see 593 00:36:06,159 --> 00:36:09,159 is changes in the central auditory processing. 594 00:36:09,159 --> 00:36:12,159 As they screen potential patients for the drug trial, 595 00:36:12,159 --> 00:36:15,159 they're looking for people who have a hard time 596 00:36:15,159 --> 00:36:17,159 detecting those sound gaps, 597 00:36:17,159 --> 00:36:21,159 who have a hard time hearing consonants and understanding words, 598 00:36:21,159 --> 00:36:24,159 especially in a noisy background. 599 00:36:24,159 --> 00:36:27,159 Whenever you hear that rare, high-pitched beep, 600 00:36:27,159 --> 00:36:30,159 I just want you to hit the space bar for me, okay? 601 00:36:30,159 --> 00:36:32,159 Beep. 602 00:36:32,159 --> 00:36:37,159 Because the drug is designed to make speech clearer, not louder. 603 00:36:37,159 --> 00:36:38,159 Beep. 604 00:36:38,159 --> 00:36:41,159 That would be the home run for this study, 605 00:36:41,159 --> 00:36:44,159 if it actually improved their ability to hear speech 606 00:36:44,159 --> 00:36:47,159 and understand speech and background noise. 607 00:36:49,159 --> 00:36:53,159 In the future, a pill may repair hearing loss. 608 00:36:55,159 --> 00:36:58,159 The future of sound even looks like magic. 609 00:36:58,159 --> 00:37:03,159 Sound waves from a bank of speakers can levitate solid objects. 610 00:37:03,159 --> 00:37:06,159 By focusing sound from opposite directions, 611 00:37:06,159 --> 00:37:10,159 researchers have created what are known as standing waves 612 00:37:10,159 --> 00:37:14,159 that can actually suspend objects in midair. 613 00:37:15,159 --> 00:37:20,159 Floating 3D graphics, microgravity, and drug research 614 00:37:20,159 --> 00:37:23,159 are some of the possible future applications. 615 00:37:25,159 --> 00:37:29,159 Sound has already transformed medical science 616 00:37:29,159 --> 00:37:33,159 when researchers at Brigham and Women's Hospital in Boston 617 00:37:33,159 --> 00:37:37,159 married an MRI scanner to an ultrasound device. 618 00:37:38,159 --> 00:37:43,159 Everyone knows ultrasound as the imaging tool for expecting couples. 619 00:37:44,159 --> 00:37:48,159 This team is using sound to burn away tumors, 620 00:37:48,159 --> 00:37:53,159 a form of surgery without a cut or a single drop of blood. 621 00:37:53,159 --> 00:37:56,159 So we're about to start the procedure. 622 00:37:56,159 --> 00:37:58,159 We're going to treat your urine fibroid. 623 00:37:58,159 --> 00:38:01,159 By focusing the ultrasound beam into tissue 624 00:38:01,159 --> 00:38:06,159 somewhat akin to the way we would do with a lens and the sunlight, 625 00:38:06,159 --> 00:38:11,159 sound waves will cause a local vibration of the molecules in the tissue. 626 00:38:11,159 --> 00:38:14,159 That motion causes local heating, 627 00:38:14,159 --> 00:38:17,159 and that heating therefore can kill the cells in that area. 628 00:38:17,159 --> 00:38:22,159 So the thermometry is the really key part that the MRI brings to this procedure, 629 00:38:22,159 --> 00:38:25,159 that no other imaging tool can do. 630 00:38:25,159 --> 00:38:28,159 We're seeing in real time the signal intensity changes. 631 00:38:28,159 --> 00:38:30,159 You see how this area has become white, 632 00:38:30,159 --> 00:38:34,159 but that shows me that that's exactly where the energy is being deposited, 633 00:38:34,159 --> 00:38:35,159 inside her fibroid. 634 00:38:35,159 --> 00:38:40,159 Once we get above 55 degrees C, the cells are dead. 635 00:38:41,159 --> 00:38:43,159 But this is just the beginning. 636 00:38:43,159 --> 00:38:48,159 MRI-guided focused ultrasound can take away the pain of bone cancer. 637 00:38:48,159 --> 00:38:53,159 There are clinical trials with prostate cancer and breast cancer, and many more. 638 00:38:53,159 --> 00:38:56,159 The most exciting one right now that's in clinical trial 639 00:38:56,159 --> 00:39:00,159 is the one that's actually being used to stop intentional tremor. 640 00:39:00,159 --> 00:39:03,159 So intentional tremor is when patients develop like this, 641 00:39:03,159 --> 00:39:08,159 what I'm doing with my hand, and are unable to write or eat or feed themselves. 642 00:39:08,159 --> 00:39:12,159 And this technique, when targeted to the correct part of the brain, 643 00:39:12,159 --> 00:39:14,159 stops that tremor immediately. 644 00:39:14,159 --> 00:39:18,159 With this technique, they can now use a transducer around the head 645 00:39:18,159 --> 00:39:22,159 and allow the ultrasound to enter the brain non-invasively. 646 00:39:22,159 --> 00:39:26,159 And that's leading to some very exciting applications. 647 00:39:26,159 --> 00:39:29,159 For example, in Brisbane, Australia, 648 00:39:29,159 --> 00:39:35,159 another form of ultrasound is being tested for treatment of Alzheimer's disease. 649 00:39:35,159 --> 00:39:41,159 Jürgen Goetz and Gerhard Leinenga set up an experiment using mice 650 00:39:41,159 --> 00:39:47,159 born with a gene mutation that produces the amyloid plaque associated with Alzheimer's. 651 00:39:48,159 --> 00:39:51,159 As naturally curious animals, 652 00:39:51,159 --> 00:39:56,159 normal wild mice will explore all three parts of a Y-maze. 653 00:39:58,159 --> 00:40:02,159 But mice with Alzheimer's can't remember where they've been before 654 00:40:02,159 --> 00:40:07,159 and tend to explore the same area over and over again. 655 00:40:07,159 --> 00:40:13,159 Pulses of ultrasound gently open the barrier that protects the brain from infection, 656 00:40:13,159 --> 00:40:18,159 allowing a protein from the blood to stimulate waste removal cells 657 00:40:18,159 --> 00:40:21,159 that clear out the toxic clumps of plaque. 658 00:40:24,159 --> 00:40:26,159 We use pulsed ultrasound. 659 00:40:26,159 --> 00:40:29,159 And because it's pulsed, the tissue is not heating up. 660 00:40:29,159 --> 00:40:33,159 After the ultrasound treatment, when the mice enter the maze again, 661 00:40:33,159 --> 00:40:37,159 they're able to explore just as well as healthy mice. 662 00:40:37,159 --> 00:40:42,159 And the nice thing is, we show a restoration of memory functions. 663 00:40:42,159 --> 00:40:49,159 So basically, we are able to restore memory functions to what one finds in... 664 00:40:49,159 --> 00:40:54,159 And we can also use the ultrasound to find out what's going on in the mice. 665 00:40:54,159 --> 00:41:00,159 We have restored memory functions to what one finds in non-Alzheimer's mice. 666 00:41:00,159 --> 00:41:08,159 And I'm highly confident that what we have found in mice can eventually be translated... 667 00:41:08,159 --> 00:41:13,159 So the sound we can't hear is curing disease. 668 00:41:13,159 --> 00:41:18,159 And the sound we can hear shaped our history, 669 00:41:18,159 --> 00:41:22,159 brings harmony to the structures we build, 670 00:41:22,159 --> 00:41:25,159 helps us navigate the natural world, 671 00:41:25,159 --> 00:41:28,159 and helps us discover the natural world. 672 00:41:28,159 --> 00:41:32,159 And so, we can't hear the sound we can't hear. 673 00:41:32,159 --> 00:41:37,159 The sound we can hear shapes our history to the structures we build, 674 00:41:37,159 --> 00:41:41,159 helps us navigate the natural world, 675 00:41:41,159 --> 00:41:48,159 and creates fascinating geometry that may hold the key to other mysteries. 676 00:41:48,159 --> 00:41:51,159 Sonic magic indeed.