WEBVTT Kind: captions Language: en 1 00:00:00.180 --> 00:00:02.940 - The final guest video in this run is from Alie and Micah, 2 00:00:02.940 --> 00:00:06.720 a neuroscientist and a clinical therapist who run Neuro Transmissions. 3 00:00:06.730 --> 00:00:10.410 Their video has giant magnets, 3D printing, and a Star Wars action figure. 4 00:00:10.410 --> 00:00:12.370 Alie, Micah, it's all yours. 5 00:00:12.370 --> 00:00:15.430 - We're here at the Keck Center at UC San Diego. 6 00:00:15.430 --> 00:00:21.140 And this is a functional magnetic resonance imager, or an fMRI. 7 00:00:21.140 --> 00:00:23.600 - Well, functional, but not functioning. 8 00:00:23.600 --> 00:00:25.170 This is actually a dummy scanner 9 00:00:25.170 --> 00:00:28.150 that's used for educational and training purposes. 10 00:00:28.150 --> 00:00:31.410 An actual fMRI machine houses a 3-Tesla magnet 11 00:00:31.410 --> 00:00:36.260 that's more than 60,000 times more powerful than the Earth's magnetic field. 12 00:00:36.260 --> 00:00:40.090 And over 3,000 times more powerful than your average fridge magnet. 13 00:00:40.090 --> 00:00:42.300 If we were anywhere near the real deal, 14 00:00:42.300 --> 00:00:46.020 well, we would put our camera and our equipment at serious risk. 15 00:00:46.020 --> 00:00:49.740 - But why on earth would anyone possibly need a magnet so powerful? 16 00:00:49.740 --> 00:00:51.410 Well, some of the researchers here 17 00:00:51.410 --> 00:00:54.630 at UCSD are using fMRI to study the human brain 18 00:00:54.630 --> 00:00:58.750 in ways that 30 years ago just weren't even possible. 19 00:00:58.750 --> 00:01:02.100 - I'm Maggie, I'm a fourth-year graduate student at UC San Diego. 20 00:01:02.100 --> 00:01:03.740 - My name is Stephanie Nelli, 21 00:01:03.740 --> 00:01:07.460 I'm a sixth-year PhD student in John Serences' lab. 22 00:01:07.460 --> 00:01:11.250 - We study mostly selective attention and expectation and other cognitive factors 23 00:01:11.250 --> 00:01:13.680 and how they influence visual processing in humans. 24 00:01:13.680 --> 00:01:16.950 - My research is about really basic visual perception. 25 00:01:16.950 --> 00:01:19.070 How do we make sense of the world around us? 26 00:01:19.070 --> 00:01:21.530 How do we choose, out of the plethora of things 27 00:01:21.530 --> 00:01:24.760 that are constantly accosting our visual system, 28 00:01:24.760 --> 00:01:28.840 how does your brain make sense of the massive amount of information 29 00:01:28.840 --> 00:01:30.350 constantly bombarding it? 30 00:01:30.350 --> 00:01:33.000 fMRI itself was developed not very long ago, 31 00:01:33.000 --> 00:01:36.930 it's a very new technique, as far as human research goes. 32 00:01:36.930 --> 00:01:40.770 And it was developed in the '90s, I believe, actually in Bell Labs. 33 00:01:40.770 --> 00:01:44.780 - fMRI is a particular specialty of MRI called functional MRI, 34 00:01:44.780 --> 00:01:47.820 so what that does is basically, instead of measuring the difference 35 00:01:47.820 --> 00:01:50.210 between particular tissues, you're actually optimising 36 00:01:50.210 --> 00:01:54.040 to detect the difference between oxygenated vs. deoxygenated blood 37 00:01:54.040 --> 00:01:55.270 in a person's brain. 38 00:01:55.270 --> 00:01:59.700 - For a long time, it was impossible to look at the brain up close 39 00:01:59.700 --> 00:02:01.673 without cracking open someone's skull. 40 00:02:01.673 --> 00:02:02.506 [Micah laughs] 41 00:02:02.506 --> 00:02:06.120 And even if you got a brain from someone who's passed on, that's not all that useful 42 00:02:06.120 --> 00:02:08.160 for understanding how it works. 43 00:02:08.160 --> 00:02:11.790 When Leonardo Da Vinci dissected the human brain in the 16th century 44 00:02:11.790 --> 00:02:15.510 it was with the intention of finding the seat of the human soul. 45 00:02:15.510 --> 00:02:17.561 Spoiler alert, he didn't. 46 00:02:17.561 --> 00:02:19.050 - Unsurprisingly, the functions 47 00:02:19.050 --> 00:02:21.350 of different brain areas were essentially a mystery 48 00:02:21.350 --> 00:02:23.660 well after the scientific revolution. 49 00:02:23.660 --> 00:02:26.630 But fMRI changed all that by giving scientists 50 00:02:26.630 --> 00:02:29.830 the ability to see the brain working in real time, 51 00:02:29.830 --> 00:02:32.740 track activities in different brain regions, 52 00:02:32.740 --> 00:02:34.620 and read your mind. 53 00:02:34.620 --> 00:02:39.820 - No, unfortunately not for us scientists, an fMRI machine cannot read the mind. 54 00:02:39.820 --> 00:02:43.620 It can tell you basically where blood is being transported to in the brain. 55 00:02:43.620 --> 00:02:45.670 So which parts of the brain are active. 56 00:02:45.670 --> 00:02:49.630 - An fMRI scan can tell you when someone is doing some cognitive task, 57 00:02:49.630 --> 00:02:52.230 what kind of patterns of brain activity you see. 58 00:02:52.230 --> 00:02:55.560 So which areas are active, what information are those areas representing. 59 00:02:55.560 --> 00:02:59.070 For instance, if you have someone look at different images and you measure MRI 60 00:02:59.070 --> 00:03:02.520 while they do that, then later if you have that same person come in and you say, 61 00:03:02.520 --> 00:03:03.740 okay, think about something. 62 00:03:03.740 --> 00:03:07.120 Now, based on that information, I can guess what you were thinking about. 63 00:03:07.120 --> 00:03:09.240 - I could probably say you're looking to the left 64 00:03:09.240 --> 00:03:11.320 by looking at your neural activity 65 00:03:11.320 --> 00:03:14.060 or I could say you're looking at a horizontal line 66 00:03:14.060 --> 00:03:15.960 by looking at your neural activity. 67 00:03:15.960 --> 00:03:19.570 However, am I gonna be able to tell what you're daydreaming about 68 00:03:19.570 --> 00:03:22.170 or who you're in love with or something like that? 69 00:03:22.170 --> 00:03:27.780 No, I don't think think that's gonna happen in my lifetime but, you know, 70 00:03:27.780 --> 00:03:31.260 I said it on camera so we'll be able to... [laughs]. 71 00:03:31.260 --> 00:03:34.830 - It might not quite make sense how a magnet does all of this, 72 00:03:34.830 --> 00:03:37.210 so let's break down the process step by step. 73 00:03:37.210 --> 00:03:39.820 Let's say that Rey here has been having 74 00:03:39.820 --> 00:03:45.700 some neurologically linked problems and a doctor refers her for an fMRI. 75 00:03:45.700 --> 00:03:49.191 All of her Force powers are messing with her head. 76 00:03:49.191 --> 00:03:53.600 "Oh no, Kylo Ren keeps appearing in my mind! 77 00:03:53.600 --> 00:03:57.493 "I can't stop thinking about his hot torso. 78 00:03:57.500 --> 00:03:58.800 "Ohhh!" 79 00:03:59.780 --> 00:04:01.980 - The technicians place her on the table, 80 00:04:01.980 --> 00:04:04.880 give her some earplugs and stabilise her head 81 00:04:04.880 --> 00:04:06.230 so she can't move it at all. 82 00:04:06.230 --> 00:04:09.510 If the head moves during the scan, the images will come out fuzzy. 83 00:04:09.510 --> 00:04:12.830 Next, the table slides into this large, doughnut-shaped 84 00:04:12.830 --> 00:04:15.880 section which houses the ultra-powerful magnet. 85 00:04:15.880 --> 00:04:17.810 The strong magnetic field of this magnet 86 00:04:17.810 --> 00:04:22.490 then actually turns the hydrogen atoms in our blood. 87 00:04:22.490 --> 00:04:23.900 - Wait, what? 88 00:04:23.900 --> 00:04:28.060 - Yeah, the human body has a lot of hydrogen atoms because well, 89 00:04:28.060 --> 00:04:31.200 we're mostly made up of H₂O, that's water. 90 00:04:31.200 --> 00:04:35.450 The magnetic field from the fMRI interacts with the protons in the hydrogen atoms 91 00:04:35.450 --> 00:04:39.360 and makes those protons essentially point in the same direction. 92 00:04:39.360 --> 00:04:42.380 That's right, your molecules are magnetic. 93 00:04:42.380 --> 00:04:44.490 Hence, the magnetic resonance part 94 00:04:44.490 --> 00:04:46.530 of magnetic resonance imaging. 95 00:04:46.530 --> 00:04:47.793 - Once Rey's in position, she'll hear a series 96 00:04:47.793 --> 00:04:50.844 of very loud clangs and beeps. 97 00:04:50.844 --> 00:04:58.100 [MRI machine beeps repeatedly] 98 00:04:58.100 --> 00:05:00.710 But these sounds aren't just the hottest new beat, 99 00:05:00.710 --> 00:05:02.320 they actually serve a purpose. 100 00:05:02.320 --> 00:05:06.120 Every clang you hear is a radio wave pulse being fired off. 101 00:05:06.120 --> 00:05:10.500 This radio wave disrupts the uniform direction of the protons and pushes them 102 00:05:10.500 --> 00:05:12.770 in slightly different directions. 103 00:05:12.770 --> 00:05:13.960 Here's the cool part. 104 00:05:13.960 --> 00:05:16.510 As the protons move back into realignment, 105 00:05:16.510 --> 00:05:19.800 they release their very own small radio signal 106 00:05:19.800 --> 00:05:21.570 and those signals are then detected 107 00:05:21.570 --> 00:05:24.380 by the fMRI machine's radio receiver, 108 00:05:24.380 --> 00:05:27.870 which starts taking snapshots of cross-sections of your brain, 109 00:05:27.870 --> 00:05:29.640 which you hear as the beeping sound. 110 00:05:29.640 --> 00:05:33.470 After some complicated computation, what shows up on the computer screen 111 00:05:33.470 --> 00:05:35.360 is a series of images that show both 112 00:05:35.360 --> 00:05:38.960 the anatomy of your brain and highlighted areas 113 00:05:38.960 --> 00:05:40.700 where there's more blood flow. 114 00:05:40.700 --> 00:05:41.580 Pretty cool, right? 115 00:05:41.580 --> 00:05:46.430 - Yeah, so fMRI doesn't actually measure your brain activity. 116 00:05:46.430 --> 00:05:49.270 It can't detect your individual neurons firing, 117 00:05:49.270 --> 00:05:51.547 as cool as that would be. 118 00:05:51.547 --> 00:05:55.110 fMRI machines actually detect what's called the BOLD signal. 119 00:05:55.110 --> 00:05:58.750 - So the BOLD signal stands for blood-oxygen-level dependent signal 120 00:05:58.750 --> 00:06:02.390 and it's basically an index of how much oxygenated haemoglobin 121 00:06:02.390 --> 00:06:05.303 is in a person's blood at a particular point in their brain. 122 00:06:05.303 --> 00:06:10.260 - Neurons themselves don't keep a high store of glucose hanging around 123 00:06:10.260 --> 00:06:14.330 so that they can do their job and so the blood vessels, 124 00:06:14.330 --> 00:06:16.770 through these things called astrocytes, actually, 125 00:06:16.770 --> 00:06:19.550 help supply neurons with the glucose 126 00:06:19.550 --> 00:06:21.730 and oxygen that they need to do their signalling. 127 00:06:21.730 --> 00:06:24.000 - When you have neural activity that happens in your brain, 128 00:06:24.000 --> 00:06:26.330 a bunch of blood will rush to that area 129 00:06:26.330 --> 00:06:30.700 and it turns out that oxygenated and deoxygenated haemoglobin in your blood 130 00:06:30.700 --> 00:06:34.360 have different magnetic properties. So deoxygenated haemoglobin 131 00:06:34.360 --> 00:06:38.580 will disrupt the magnetic field more than oxygenated haemoglobin will 132 00:06:38.580 --> 00:06:40.850 and it'll actually cause a decrease in the signal. 133 00:06:40.850 --> 00:06:44.330 So when you look at an fMRI image, the higher the signal you have, 134 00:06:44.330 --> 00:06:46.480 the more oxygen is in your blood at that point. 135 00:06:46.480 --> 00:06:47.693 And so you actually can measure 136 00:06:47.693 --> 00:06:50.730 with the BOLD signal after these neural events occur. 137 00:06:50.730 --> 00:06:53.850 That basically tells you how much energy was consumed at that location. 138 00:06:53.850 --> 00:06:55.920 - Now, it's not perfect. 139 00:06:55.920 --> 00:06:58.370 It can't detect changes instantaneously 140 00:06:58.370 --> 00:07:02.080 or tell you exactly what kinds of signals are being sent. 141 00:07:02.080 --> 00:07:04.010 - But even with its limitations, 142 00:07:04.010 --> 00:07:07.720 it lets us better understand which brain regions do what. 143 00:07:07.720 --> 00:07:13.260 Using fMRI, scientists have been able to identify 180 distinct brain regions. 144 00:07:13.260 --> 00:07:16.230 Better understanding the roles of different brain regions means 145 00:07:16.230 --> 00:07:19.330 that doctors can use that information to help treat and support patients 146 00:07:19.330 --> 00:07:22.740 with neurological disorders or brain injuries. 147 00:07:22.740 --> 00:07:26.860 fMRI technology is cool, but both of us wanted more. 148 00:07:26.870 --> 00:07:30.730 We wanted to get into the machine and see what our own brains looked like. 149 00:07:30.730 --> 00:07:34.430 Maggie and Steph asked me to participate in a pilot research study looking 150 00:07:34.430 --> 00:07:38.650 at how humans distinguish between faces and I jumped at the chance to help out. 151 00:07:38.650 --> 00:07:43.370 - I didn't participate in the study but I was able to get a structural scan. 152 00:07:43.370 --> 00:07:45.040 It doesn't measure blood flow 153 00:07:45.040 --> 00:07:48.690 but it does give you a high resolution image of your brain's anatomy. 154 00:07:48.690 --> 00:07:51.370 It was a strange experience, being inside. 155 00:07:51.370 --> 00:07:54.280 It felt like being in a plastic coffin. 156 00:07:54.280 --> 00:07:56.470 I can see why some people get claustrophobic. 157 00:07:56.470 --> 00:08:00.550 - And participating in the study was harder than I expected. 158 00:08:00.550 --> 00:08:02.540 While the task I was doing was easy, 159 00:08:02.540 --> 00:08:04.560 it was hard to stay focused on doing 160 00:08:04.560 --> 00:08:09.150 the same thing over and over for almost two hours. 161 00:08:09.150 --> 00:08:12.325 But it was also really cool to see the results. 162 00:08:12.325 --> 00:08:15.870 - And yet, we could not pass up on the opportunity of a lifetime. 163 00:08:15.870 --> 00:08:18.800 - I mean, sure it's cool to see your brain on a screen 164 00:08:18.800 --> 00:08:22.040 but imagine holding it in your hands. 165 00:08:22.050 --> 00:08:26.210 What does my own unique brain really look like? 166 00:08:26.210 --> 00:08:29.650 Well, as it turns out, we're able to find out. 167 00:08:29.650 --> 00:08:33.460 - Thanks to modern software, we're able to take the 2D slices of our brains 168 00:08:33.460 --> 00:08:36.050 and compose them into a 3D render 169 00:08:36.050 --> 00:08:37.600 and print them out. 170 00:08:37.600 --> 00:08:39.371 Cue the time lapse. 171 00:08:55.771 --> 00:08:58.600 - Well, look at that beautiful brain. 172 00:08:58.600 --> 00:09:01.764 - I really liked how the rainbow filament turned out on this. 173 00:09:01.764 --> 00:09:03.520 - Yeah, it's so pretty. - This turned out really cool. 174 00:09:03.520 --> 00:09:06.750 - I know, and I really like my glow-in-the-dark print. 175 00:09:06.750 --> 00:09:08.340 It's super bright. 176 00:09:08.340 --> 00:09:11.920 - The grooves are much wider in yours, and not quite as tightly packed, 177 00:09:11.920 --> 00:09:14.620 whereas mine is super tightly folded. 178 00:09:14.620 --> 00:09:16.570 - It's cool that you can see the inside too, 179 00:09:16.570 --> 00:09:19.960 the hippocampus and all these different brain regions. 180 00:09:19.960 --> 00:09:24.640 - Obviously I knew that my brain wasn't perfectly symmetrical, no one's brain is, 181 00:09:24.640 --> 00:09:28.220 but you can really see very obvious differences. 182 00:09:28.220 --> 00:09:32.530 It's really interesting to see, like, oh, that's my brain's shape. 183 00:09:32.530 --> 00:09:35.310 - Right, I didn't really think about that before. 184 00:09:35.310 --> 00:09:37.180 - Every time someone comes over to our house 185 00:09:37.180 --> 00:09:39.082 I'll be like, did you see my brain? 186 00:09:39.082 --> 00:09:40.748 - Lemme show you my brain. - Lemme show you my brain! 187 00:09:40.748 --> 00:09:43.930 - It's incredible that we have the technology to track the activity 188 00:09:43.930 --> 00:09:45.370 of a live human brain. 189 00:09:45.370 --> 00:09:48.310 fMRI has pushed neuroscience to new heights 190 00:09:48.310 --> 00:09:51.680 and has given us a glimpse into the seat of human consciousness. 191 00:09:51.680 --> 00:09:53.890 And only somewhat less incredible 192 00:09:53.890 --> 00:09:55.990 is the fact that we can use those same images 193 00:09:55.990 --> 00:09:59.290 to build 3D models so we can create a life-size version 194 00:09:59.290 --> 00:10:00.870 of our own brains. 195 00:10:00.870 --> 00:10:04.190 How funny that just a chunk of squishy cells this big 196 00:10:04.190 --> 00:10:05.880 can come up with such incredible tools 197 00:10:05.880 --> 00:10:08.980 to help us better understand our minds and ourselves. 198 00:10:08.980 --> 00:10:12.850 - Huge thanks to Maggie and Steph from the Serences lab for their expertise 199 00:10:12.850 --> 00:10:16.330 and to UCSD for giving us access to their scanner. 200 00:10:16.330 --> 00:10:21.350 And thanks to Tom for giving nerds like us the chance to share our brainy love. 201 00:10:21.350 --> 00:10:22.893 Maybe we'll see you later? 202 00:10:22.893 --> 00:10:23.830 - Maybe? 203 00:10:23.830 --> 00:10:26.470 - Until next time, we're Neuro Transmissions, 204 00:10:26.470 --> 00:10:27.830 over and out. 205 00:10:27.830 --> 00:10:29.770 - Thank you folks, go subscribe to Neuro Transmissions. 206 00:10:29.770 --> 00:10:32.100 I would recommend starting with Micah's video 207 00:10:32.100 --> 00:10:33.650 on training a cat to high five 208 00:10:33.650 --> 00:10:36.380 or Alie's video on how marijuana affects your brain. 209 00:10:36.380 --> 00:10:38.090 And that's it! I'm back next week 210 00:10:38.090 --> 00:10:39.473 and I will see you then.