[Script Info]
Title: 
[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:09.43,0:00:11.03,Default,,0000,0000,0000,,Complexity.
Dialogue: 0,0:00:11.03,0:00:15.38,Default,,0000,0000,0000,,Nothing quite embodies this word\Nlike the human brain.
Dialogue: 0,0:00:15.38,0:00:19.68,Default,,0000,0000,0000,,So for centuries we've studied\Nthe complexity of the human brain
Dialogue: 0,0:00:19.68,0:00:22.51,Default,,0000,0000,0000,,using the tools and technology of the day,
Dialogue: 0,0:00:22.51,0:00:26.54,Default,,0000,0000,0000,,if that's pen and paper\Nfrom the age of da Vinci,
Dialogue: 0,0:00:26.54,0:00:29.64,Default,,0000,0000,0000,,through advents in microscopy
Dialogue: 0,0:00:29.64,0:00:32.56,Default,,0000,0000,0000,,to be able to look more deeply\Ninto the brain,
Dialogue: 0,0:00:32.56,0:00:36.22,Default,,0000,0000,0000,,to a lot of the new technologies\Nthat you've heard about today
Dialogue: 0,0:00:36.22,0:00:38.53,Default,,0000,0000,0000,,through imaging,\Nmagnetic resonance imaging,
Dialogue: 0,0:00:38.53,0:00:41.90,Default,,0000,0000,0000,,able to look at the details of the brain.
Dialogue: 0,0:00:41.90,0:00:44.37,Default,,0000,0000,0000,,Now one of the first things\Nyou notice when you look
Dialogue: 0,0:00:44.37,0:00:48.91,Default,,0000,0000,0000,,at a fresh human brain\Nis the amount of vasculature
Dialogue: 0,0:00:48.91,0:00:51.31,Default,,0000,0000,0000,,that's completely covering this.
Dialogue: 0,0:00:51.31,0:00:56.16,Default,,0000,0000,0000,,The brain is this metabolically\Nvoracious organ.
Dialogue: 0,0:00:56.18,0:01:01.24,Default,,0000,0000,0000,,Approximately a quarter\Nof the oxygen in your blood,
Dialogue: 0,0:01:01.24,0:01:04.78,Default,,0000,0000,0000,,approximately a fifth\Nof the glucose in your blood
Dialogue: 0,0:01:04.78,0:01:06.86,Default,,0000,0000,0000,,is being used by this organ.
Dialogue: 0,0:01:06.86,0:01:09.77,Default,,0000,0000,0000,,It's so metabolically active,\Nthere's a waste stream
Dialogue: 0,0:01:09.77,0:01:13.46,Default,,0000,0000,0000,,which comes out\Ninto your cerebral spinal fluid.
Dialogue: 0,0:01:13.46,0:01:17.67,Default,,0000,0000,0000,,You generate 0.5 liter of CSF every day.
Dialogue: 0,0:01:17.67,0:01:21.92,Default,,0000,0000,0000,,So, as you know, researchers\Nhave taken advantage
Dialogue: 0,0:01:21.92,0:01:25.22,Default,,0000,0000,0000,,of this massive amount of blood flow\Nand metabolic activity
Dialogue: 0,0:01:25.22,0:01:29.58,Default,,0000,0000,0000,,to begin to map regions of the brain,\Nto functionally annotate the brain
Dialogue: 0,0:01:29.58,0:01:31.08,Default,,0000,0000,0000,,in very meaningful ways.
Dialogue: 0,0:01:31.08,0:01:33.91,Default,,0000,0000,0000,,You'll hear a lot more\Nabout those kinds of studies,
Dialogue: 0,0:01:33.91,0:01:38.08,Default,,0000,0000,0000,,but basically taking advantage of the fact\Nthat there's active metabolism
Dialogue: 0,0:01:38.08,0:01:40.03,Default,,0000,0000,0000,,with certain tasks going on.
Dialogue: 0,0:01:40.03,0:01:42.09,Default,,0000,0000,0000,,You can put a living human in a machine
Dialogue: 0,0:01:42.09,0:01:44.41,Default,,0000,0000,0000,,and you can see various areas\Nthat are lighting up.
Dialogue: 0,0:01:44.41,0:01:48.38,Default,,0000,0000,0000,,For example, going around right now\Nis the temporal cortex,
Dialogue: 0,0:01:48.38,0:01:51.48,Default,,0000,0000,0000,,auditory processing going on there,\Nyou're listening to my words,
Dialogue: 0,0:01:51.48,0:01:53.15,Default,,0000,0000,0000,,you're processing what I'm saying.
Dialogue: 0,0:01:53.15,0:01:56.79,Default,,0000,0000,0000,,Moving to the front of this brain\Nis your prefrontal cortex,
Dialogue: 0,0:01:56.79,0:01:58.89,Default,,0000,0000,0000,,your executive decision-making,
Dialogue: 0,0:01:58.89,0:02:02.15,Default,,0000,0000,0000,,your higher-thinking areas of the brain.
Dialogue: 0,0:02:02.15,0:02:08.15,Default,,0000,0000,0000,,And so the thing that\Nwe're very much interested in
Dialogue: 0,0:02:08.15,0:02:10.76,Default,,0000,0000,0000,,from the perspective\Nof the Allen Institute
Dialogue: 0,0:02:10.76,0:02:13.94,Default,,0000,0000,0000,,is to go deeper,\Nto get down to the cellular level.
Dialogue: 0,0:02:13.94,0:02:17.67,Default,,0000,0000,0000,,So when you look at this slice, it doesn't\Nreally look like gray matter, does it?
Dialogue: 0,0:02:17.67,0:02:20.69,Default,,0000,0000,0000,,It's more tan matter, or beige matter.
Dialogue: 0,0:02:20.69,0:02:25.85,Default,,0000,0000,0000,,And scientists about, I guess\Naround the late 1800's,
Dialogue: 0,0:02:25.85,0:02:28.95,Default,,0000,0000,0000,,discovered that they could\Nstain tissue in various ways,
Dialogue: 0,0:02:28.95,0:02:33.37,Default,,0000,0000,0000,,and this sort of came along\Nwith various microscopy techniques.
Dialogue: 0,0:02:33.37,0:02:37.22,Default,,0000,0000,0000,,And so this is a stain, it's called Nissl,\Nand it stains cell bodies,
Dialogue: 0,0:02:37.22,0:02:40.80,Default,,0000,0000,0000,,it stains the cell bodies purple.
Dialogue: 0,0:02:40.80,0:02:43.80,Default,,0000,0000,0000,,And so you can see\Na lot more structure and texture
Dialogue: 0,0:02:43.80,0:02:45.58,Default,,0000,0000,0000,,when you look at something like this.
Dialogue: 0,0:02:45.58,0:02:49.88,Default,,0000,0000,0000,,You can see the outer layers of the brain\Nand the neocortex,
Dialogue: 0,0:02:49.88,0:02:54.60,Default,,0000,0000,0000,,there's a six-layer structure, arguably\Nwhat makes us most uniquely human.
Dialogue: 0,0:02:54.60,0:02:58.53,Default,,0000,0000,0000,,As you've heard before about\Nthere's on average in a human,
Dialogue: 0,0:02:58.53,0:03:03.56,Default,,0000,0000,0000,,there's about 86 billion neurons,\Nand those 86 billion neurons
Dialogue: 0,0:03:03.56,0:03:05.75,Default,,0000,0000,0000,,you can see are not evenly distributed,
Dialogue: 0,0:03:05.75,0:03:09.35,Default,,0000,0000,0000,,they're very focused\Nin specific structures.
Dialogue: 0,0:03:09.35,0:03:11.62,Default,,0000,0000,0000,,And each of them\Nhas their own sort of function,
Dialogue: 0,0:03:11.62,0:03:15.23,Default,,0000,0000,0000,,both on an anatomic level\Nand at a cellular level.
Dialogue: 0,0:03:15.23,0:03:19.85,Default,,0000,0000,0000,,So if we zoom in on these cells,\Nwhat you can see is large cells
Dialogue: 0,0:03:19.85,0:03:23.08,Default,,0000,0000,0000,,and small support cells\Nthat are glials and astrocytes
Dialogue: 0,0:03:23.08,0:03:27.91,Default,,0000,0000,0000,,and these cells are as we know\Nconnected in a variety of different ways.
Dialogue: 0,0:03:27.91,0:03:31.72,Default,,0000,0000,0000,,And we like to think about,\Nalthough there's 86 billion cells,
Dialogue: 0,0:03:31.72,0:03:36.42,Default,,0000,0000,0000,,each cell might be considered a snowflake,\Nthey're actually able to be binned
Dialogue: 0,0:03:36.42,0:03:39.60,Default,,0000,0000,0000,,into a large number\Nof cell types or classes.
Dialogue: 0,0:03:39.60,0:03:43.92,Default,,0000,0000,0000,,What flavor of activity\Nthat particular cell class has
Dialogue: 0,0:03:43.92,0:03:49.32,Default,,0000,0000,0000,,is driven by the underlying genes\Nthat are turned on in that cell,
Dialogue: 0,0:03:49.32,0:03:53.28,Default,,0000,0000,0000,,those drive protein expression\Nwhich guide the function of those cells,
Dialogue: 0,0:03:53.28,0:03:56.13,Default,,0000,0000,0000,,who they're connected to,\Nwhat their morphology is,
Dialogue: 0,0:03:56.13,0:04:00.48,Default,,0000,0000,0000,,and we're very much interested\Nin understanding these cell classes.
Dialogue: 0,0:04:00.48,0:04:02.16,Default,,0000,0000,0000,,So how do we do that?
Dialogue: 0,0:04:02.16,0:04:05.77,Default,,0000,0000,0000,,Well, we look inside the cell\Nat the nucleus,
Dialogue: 0,0:04:05.77,0:04:07.86,Default,,0000,0000,0000,,-- and it will get to the nucleus --
Dialogue: 0,0:04:07.86,0:04:10.86,Default,,0000,0000,0000,,and so inside we've got\N23 pairs of chromosomes,
Dialogue: 0,0:04:10.86,0:04:12.75,Default,,0000,0000,0000,,got a pair from mom, a pair from dad,
Dialogue: 0,0:04:12.75,0:04:17.87,Default,,0000,0000,0000,,on those chromosomes about 25,000 genes\Nand we're very much again interested in
Dialogue: 0,0:04:17.87,0:04:22.22,Default,,0000,0000,0000,,understanding which\Nof these 25,000 genes are turned on
Dialogue: 0,0:04:22.22,0:04:24.48,Default,,0000,0000,0000,,at what levels they're turned on.
Dialogue: 0,0:04:24.48,0:04:28.08,Default,,0000,0000,0000,,Those are going to, of course, drive\Nthe underlying biochemistry of the cells
Dialogue: 0,0:04:28.08,0:04:33.09,Default,,0000,0000,0000,,they're turned on in and again every cell\Nin our bodies more or less has these
Dialogue: 0,0:04:33.09,0:04:35.42,Default,,0000,0000,0000,,and we want to understand better
Dialogue: 0,0:04:35.42,0:04:41.55,Default,,0000,0000,0000,,what the driving biochemistry\Ndriven by our genome is.
Dialogue: 0,0:04:41.55,0:04:44.97,Default,,0000,0000,0000,,So how do we do that?
Dialogue: 0,0:04:47.61,0:04:51.32,Default,,0000,0000,0000,,We're going to deconstruct a brain\Nin several easy steps.
Dialogue: 0,0:04:51.33,0:04:54.21,Default,,0000,0000,0000,,So we start\Nat a medical examiner's office.
Dialogue: 0,0:04:54.21,0:04:56.51,Default,,0000,0000,0000,,This is a place\Nwhere the dead are brought in
Dialogue: 0,0:04:56.51,0:04:58.67,Default,,0000,0000,0000,,and obviously as you saw before
Dialogue: 0,0:04:58.67,0:05:03.15,Default,,0000,0000,0000,,for the kind of work we do,\N[it] is not non-invasive,
Dialogue: 0,0:05:03.15,0:05:08.75,Default,,0000,0000,0000,,we actually need\Nto obtain fresh brain tissue
Dialogue: 0,0:05:08.75,0:05:13.13,Default,,0000,0000,0000,,and we need to obtain it within 24 hours\Nbecause the tissues start to degrade.
Dialogue: 0,0:05:13.13,0:05:15.99,Default,,0000,0000,0000,,We also wanted for our projects\Nto have normal tissue,
Dialogue: 0,0:05:15.99,0:05:18.90,Default,,0000,0000,0000,,as much normal as we could possibly get.
Dialogue: 0,0:05:18.90,0:05:24.85,Default,,0000,0000,0000,,So over the course of a two-\Nor three-year collection time window
Dialogue: 0,0:05:24.85,0:05:30.54,Default,,0000,0000,0000,,we collected 6 very high-quality brains,\N5 of them were male, 1 was female.
Dialogue: 0,0:05:30.54,0:05:35.61,Default,,0000,0000,0000,,That's only because males\Ntend to die untimely deaths
Dialogue: 0,0:05:35.61,0:05:39.78,Default,,0000,0000,0000,,more frequently than females,\Nand then to add to that,
Dialogue: 0,0:05:39.78,0:05:42.82,Default,,0000,0000,0000,,females are much more likely\Nto give consent
Dialogue: 0,0:05:42.82,0:05:45.66,Default,,0000,0000,0000,,for us to take the brain than vice versa.
Dialogue: 0,0:05:45.66,0:05:49.38,Default,,0000,0000,0000,,We have to figure that one out.
Dialogue: 0,0:05:49.38,0:05:52.52,Default,,0000,0000,0000,,We've heard people say,\N"He wasn't using it anyway!"
Dialogue: 0,0:05:52.52,0:05:55.49,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:05:56.90,0:06:00.56,Default,,0000,0000,0000,,So, once the brain comes in\Nwe have to move very, very quickly.
Dialogue: 0,0:06:00.56,0:06:06.32,Default,,0000,0000,0000,,So first we capture\Na magnetic resonance image.
Dialogue: 0,0:06:06.32,0:06:08.50,Default,,0000,0000,0000,,This, of course,\Nwill look very familiar to you,
Dialogue: 0,0:06:08.50,0:06:12.00,Default,,0000,0000,0000,,but this is going to be the structure\Nin which we hang all this information,
Dialogue: 0,0:06:12.00,0:06:15.55,Default,,0000,0000,0000,,it's also a common coordinate framework\Nby which the many, many researchers
Dialogue: 0,0:06:15.55,0:06:17.27,Default,,0000,0000,0000,,who do imaging studies can map
Dialogue: 0,0:06:17.27,0:06:20.39,Default,,0000,0000,0000,,into our ultimate database,\Nan Atlas framework.
Dialogue: 0,0:06:20.39,0:06:22.96,Default,,0000,0000,0000,,We also collect diffusion tensor images,
Dialogue: 0,0:06:22.96,0:06:25.41,Default,,0000,0000,0000,,so we get some of the wiring\Nfrom these brains.
Dialogue: 0,0:06:25.41,0:06:27.89,Default,,0000,0000,0000,,And then the brain\Nis removed from the skull.
Dialogue: 0,0:06:27.89,0:06:32.88,Default,,0000,0000,0000,,It's slabbed and frozen solid,\Nand then it's shipped to Seattle
Dialogue: 0,0:06:32.88,0:06:35.22,Default,,0000,0000,0000,,where we have\Nthe Allen Institute for Brain Science.
Dialogue: 0,0:06:35.22,0:06:37.20,Default,,0000,0000,0000,,We have great technicians\Nwho've worked out
Dialogue: 0,0:06:37.20,0:06:39.45,Default,,0000,0000,0000,,a lot of great techniques\Nfor further processing.
Dialogue: 0,0:06:39.75,0:06:45.75,Default,,0000,0000,0000,,So first, we take a very thin section,\Nthis is a 25 micron thin section,
Dialogue: 0,0:06:45.75,0:06:48.15,Default,,0000,0000,0000,,which is about a baby's hair width.
Dialogue: 0,0:06:48.15,0:06:52.30,Default,,0000,0000,0000,,That's transferred to a microscope slide\Nand then that is stained
Dialogue: 0,0:06:52.30,0:06:55.51,Default,,0000,0000,0000,,with one of those histological stains\Nthat I talked about before.
Dialogue: 0,0:06:55.51,0:06:58.91,Default,,0000,0000,0000,,And this is going to give us more contrast\Nas our team of anatomists
Dialogue: 0,0:06:58.91,0:07:02.72,Default,,0000,0000,0000,,start to make assignments of anatomy.
Dialogue: 0,0:07:04.80,0:07:07.24,Default,,0000,0000,0000,,So we digitize these images,
Dialogue: 0,0:07:07.24,0:07:11.17,Default,,0000,0000,0000,,everything goes from being\Nwet lab to being dry lab.
Dialogue: 0,0:07:11.17,0:07:15.97,Default,,0000,0000,0000,,And then combined with anatomy\Nthat we get from the MR,
Dialogue: 0,0:07:15.97,0:07:17.96,Default,,0000,0000,0000,,we further fragment the brain.
Dialogue: 0,0:07:17.96,0:07:24.48,Default,,0000,0000,0000,,This is to get it into a smaller framework\Nfor which we can do this.
Dialogue: 0,0:07:24.48,0:07:27.28,Default,,0000,0000,0000,,So here's a technician\Nwho's doing additional cutting.
Dialogue: 0,0:07:27.28,0:07:30.40,Default,,0000,0000,0000,,This is again a 25 micron thin section.
Dialogue: 0,0:07:30.40,0:07:32.61,Default,,0000,0000,0000,,You'll see da Vinci's tools,\Nthe paintbrush,
Dialogue: 0,0:07:32.61,0:07:35.20,Default,,0000,0000,0000,,being used here to smooth this out.
Dialogue: 0,0:07:35.20,0:07:38.78,Default,,0000,0000,0000,,This is fresh frozen brain tissue.
Dialogue: 0,0:07:39.24,0:07:42.94,Default,,0000,0000,0000,,And it can be very carefully\Nmelted to a microscope slide.
Dialogue: 0,0:07:42.94,0:07:45.11,Default,,0000,0000,0000,,You'll note that there's a barcode\Non the slide.
Dialogue: 0,0:07:45.11,0:07:47.01,Default,,0000,0000,0000,,We process 1000's and 1000's of samples,
Dialogue: 0,0:07:47.01,0:07:50.65,Default,,0000,0000,0000,,we track all of it in a backend\Ninformation management system.
Dialogue: 0,0:07:50.65,0:07:53.54,Default,,0000,0000,0000,,Those are stained.
Dialogue: 0,0:07:53.54,0:07:57.14,Default,,0000,0000,0000,,And then we get\Nmore detailed anatomic information.
Dialogue: 0,0:07:57.14,0:07:58.45,Default,,0000,0000,0000,,That information...
Dialogue: 0,0:08:01.92,0:08:08.18,Default,,0000,0000,0000,,This is a laser capture microscope.
Dialogue: 0,0:08:08.18,0:08:12.64,Default,,0000,0000,0000,,The lab technician is actually describing\Nan area on that slide.
Dialogue: 0,0:08:12.64,0:08:15.24,Default,,0000,0000,0000,,And a laser, you see the blue light\Ncutting around there,
Dialogue: 0,0:08:15.24,0:08:19.41,Default,,0000,0000,0000,,very James Bond-like,\Ncutting out part of that.
Dialogue: 0,0:08:19.41,0:08:21.97,Default,,0000,0000,0000,,And underneath there,\Nyou can see the blue light again,
Dialogue: 0,0:08:21.97,0:08:23.54,Default,,0000,0000,0000,,from the microscope in real-time,
Dialogue: 0,0:08:23.54,0:08:28.80,Default,,0000,0000,0000,,it's collecting,\Nin a microscope tube, that tissue.
Dialogue: 0,0:08:28.80,0:08:30.62,Default,,0000,0000,0000,,We extract RNA,
Dialogue: 0,0:08:30.62,0:08:35.21,Default,,0000,0000,0000,,RNA is the product of the genes\Nthat are being turned on,
Dialogue: 0,0:08:35.21,0:08:38.06,Default,,0000,0000,0000,,and we label it,\Nwe put a fluorescent tag on it.
Dialogue: 0,0:08:38.06,0:08:39.78,Default,,0000,0000,0000,,Now what you are looking at here
Dialogue: 0,0:08:39.78,0:08:43.13,Default,,0000,0000,0000,,is a constellation\Nof the entire human genome
Dialogue: 0,0:08:43.13,0:08:45.47,Default,,0000,0000,0000,,spread out over a glass slide.
Dialogue: 0,0:08:45.47,0:08:48.58,Default,,0000,0000,0000,,Those little bits are representing\Nthe 25,000 genes.
Dialogue: 0,0:08:48.58,0:08:52.54,Default,,0000,0000,0000,,There's about 60,000 of these spots\Nand that fluorescently labeled RNA
Dialogue: 0,0:08:52.54,0:08:56.92,Default,,0000,0000,0000,,is put onto this microscope slide\Nand then we read out quantitatively
Dialogue: 0,0:08:56.92,0:09:00.94,Default,,0000,0000,0000,,what genes are turned on at what levels.
Dialogue: 0,0:09:00.94,0:09:04.64,Default,,0000,0000,0000,,So we do this over and over and over again\Nfor brains that we've collected;
Dialogue: 0,0:09:04.64,0:09:07.20,Default,,0000,0000,0000,,as I mentioned we've collected\N6 brains in total.
Dialogue: 0,0:09:07.20,0:09:10.81,Default,,0000,0000,0000,,We collect samples\Nfrom about 1000 structures in every brain
Dialogue: 0,0:09:10.81,0:09:14.50,Default,,0000,0000,0000,,that we've looked at,\Nso it's a massive amount of data.
Dialogue: 0,0:09:14.50,0:09:18.96,Default,,0000,0000,0000,,And we pull all of this together,\Nback into a common framework,
Dialogue: 0,0:09:18.96,0:09:22.76,Default,,0000,0000,0000,,that is a free and open resource\Nfor scientists around the world to use.
Dialogue: 0,0:09:22.76,0:09:24.76,Default,,0000,0000,0000,,So at the Allen Institute\Nfor Brain Science,
Dialogue: 0,0:09:24.76,0:09:28.67,Default,,0000,0000,0000,,we've been generating these kinds\Nof data resources for almost a decade.
Dialogue: 0,0:09:28.67,0:09:32.44,Default,,0000,0000,0000,,They're free to use for anybody,\Nthey're online tools,
Dialogue: 0,0:09:32.44,0:09:38.35,Default,,0000,0000,0000,,just for example today a given workday,\Nthere'll be about 1000 unique visitors
Dialogue: 0,0:09:38.35,0:09:43.63,Default,,0000,0000,0000,,that come in from labs around the world,\Nto come use our resources and data.
Dialogue: 0,0:09:43.63,0:09:47.62,Default,,0000,0000,0000,,They get access to tools like this,\Nwhich allows them to see
Dialogue: 0,0:09:47.62,0:09:50.96,Default,,0000,0000,0000,,all of that anatomy and the structure\Nthat we created before
Dialogue: 0,0:09:50.96,0:09:55.73,Default,,0000,0000,0000,,and to start mapping in then the things\Nthat they're particularly interested in.
Dialogue: 0,0:09:55.73,0:09:57.92,Default,,0000,0000,0000,,So in this case you're looking\Nat the structure
Dialogue: 0,0:09:57.92,0:09:59.100,Default,,0000,0000,0000,,and they're going to look\Nat these color balls
Dialogue: 0,0:09:59.100,0:10:02.67,Default,,0000,0000,0000,,are representing a particular gene\Nthey're interested in
Dialogue: 0,0:10:02.67,0:10:05.39,Default,,0000,0000,0000,,that's either being turned up or down
Dialogue: 0,0:10:05.39,0:10:11.67,Default,,0000,0000,0000,,in those various areas depending upon\Nthe heat color that's specified there.
Dialogue: 0,0:10:11.67,0:10:14.53,Default,,0000,0000,0000,,So what are people doing\Nwhen they start using these resources?
Dialogue: 0,0:10:14.53,0:10:17.48,Default,,0000,0000,0000,,Well, one of the things\Nthat you might hear lots about
Dialogue: 0,0:10:17.48,0:10:19.74,Default,,0000,0000,0000,,is human genetic studies.
Dialogue: 0,0:10:19.74,0:10:23.31,Default,,0000,0000,0000,,Obviously, if you're very interested\Nin understanding disease
Dialogue: 0,0:10:23.31,0:10:25.58,Default,,0000,0000,0000,,there's a genetic underpinning\Nto many of them.
Dialogue: 0,0:10:25.58,0:10:28.22,Default,,0000,0000,0000,,So you'd like more information,\Nyou do a large-scale study
Dialogue: 0,0:10:28.22,0:10:31.28,Default,,0000,0000,0000,,and you get out of those studies\Ncollections of genes
Dialogue: 0,0:10:31.28,0:10:34.79,Default,,0000,0000,0000,,and one of the first things you're going\Nto want to know is more information.
Dialogue: 0,0:10:34.79,0:10:41.04,Default,,0000,0000,0000,,Is there something I can learn\Nabout the location of these genes
Dialogue: 0,0:10:41.04,0:10:44.18,Default,,0000,0000,0000,,that gives me additional clues\Nas to their function,
Dialogue: 0,0:10:44.18,0:10:49.19,Default,,0000,0000,0000,,ways in which I might intervene\Nin the disease process.
Dialogue: 0,0:10:49.19,0:10:52.42,Default,,0000,0000,0000,,They're also very interested\Nin understanding human genetic diversity.
Dialogue: 0,0:10:52.42,0:10:55.42,Default,,0000,0000,0000,,We've only looked at 6 brains,
Dialogue: 0,0:10:55.42,0:10:58.98,Default,,0000,0000,0000,,but, as we know,\Nevery human is very unique.
Dialogue: 0,0:10:58.98,0:11:00.62,Default,,0000,0000,0000,,We celebrate our differences;
Dialogue: 0,0:11:00.62,0:11:05.22,Default,,0000,0000,0000,,this is a snapshot of the great workforce\Nat the Allen Institute for Brain Science
Dialogue: 0,0:11:05.22,0:11:09.17,Default,,0000,0000,0000,,who does all the great work\Nthat I'm talking about today.
Dialogue: 0,0:11:09.17,0:11:15.36,Default,,0000,0000,0000,,But remarkably when we look at this level\Nat the underlying data,
Dialogue: 0,0:11:15.36,0:11:20.06,Default,,0000,0000,0000,,and this is a lot of data from\N2 completely unrelated individuals,
Dialogue: 0,0:11:20.06,0:11:24.31,Default,,0000,0000,0000,,there's a very high degree\Nof correlation, correspondence.
Dialogue: 0,0:11:24.31,0:11:27.01,Default,,0000,0000,0000,,So this is looking at thousands\Nof different measurements
Dialogue: 0,0:11:27.01,0:11:30.12,Default,,0000,0000,0000,,of gene expression across\Nmany, many different areas of the brain;
Dialogue: 0,0:11:30.12,0:11:32.42,Default,,0000,0000,0000,,and there's a very high degree\Nof correspondence.
Dialogue: 0,0:11:32.42,0:11:33.92,Default,,0000,0000,0000,,This was very reassuring to us.
Dialogue: 0,0:11:33.92,0:11:36.93,Default,,0000,0000,0000,,First, because when you generate\Ndata on this scale,
Dialogue: 0,0:11:36.93,0:11:38.80,Default,,0000,0000,0000,,you want to make sure it's high quality,
Dialogue: 0,0:11:38.80,0:11:41.06,Default,,0000,0000,0000,,so reproducibility is obviously important,
Dialogue: 0,0:11:41.06,0:11:43.93,Default,,0000,0000,0000,,but it was also important\Nbecause we feel that it's given us
Dialogue: 0,0:11:43.93,0:11:46.90,Default,,0000,0000,0000,,a great snapshot into the human brain.
Dialogue: 0,0:11:46.90,0:11:50.87,Default,,0000,0000,0000,,And the people using the data,\Neven with our low N, have confidence
Dialogue: 0,0:11:50.87,0:11:53.94,Default,,0000,0000,0000,,that what they're seeing\Nhas some relevance.
Dialogue: 0,0:11:53.94,0:11:58.01,Default,,0000,0000,0000,,Now, not everything is correlated here,\Nyou can see some outliers,
Dialogue: 0,0:11:58.01,0:12:00.72,Default,,0000,0000,0000,,and, of course, those outliers\Nare going to be interesting
Dialogue: 0,0:12:00.72,0:12:03.04,Default,,0000,0000,0000,,related to human differences.
Dialogue: 0,0:12:03.04,0:12:04.86,Default,,0000,0000,0000,,We did a study a couple of years ago,
Dialogue: 0,0:12:04.86,0:12:09.24,Default,,0000,0000,0000,,in which we tried to understand\Na little better about those differences,
Dialogue: 0,0:12:09.24,0:12:12.50,Default,,0000,0000,0000,,and looked at multiple individuals\Nand different gene products,
Dialogue: 0,0:12:12.50,0:12:15.99,Default,,0000,0000,0000,,and what we find, as a tendency\Nand as a rule,
Dialogue: 0,0:12:15.99,0:12:19.57,Default,,0000,0000,0000,,is that those differences tend to be\Nin very specific cell populations
Dialogue: 0,0:12:19.57,0:12:23.80,Default,,0000,0000,0000,,or cell types, cell classes,\Nas I mentioned before.
Dialogue: 0,0:12:23.80,0:12:27.41,Default,,0000,0000,0000,,So, this is an example\Nof 2 different genes that are turned on
Dialogue: 0,0:12:27.41,0:12:29.93,Default,,0000,0000,0000,,in very specific layers of the neocortex
Dialogue: 0,0:12:29.93,0:12:32.77,Default,,0000,0000,0000,,only in one individual\Nand not found in another.
Dialogue: 0,0:12:32.77,0:12:36.40,Default,,0000,0000,0000,,Now we have no idea\Nif that's due to environmental changes,
Dialogue: 0,0:12:36.40,0:12:39.27,Default,,0000,0000,0000,,environmental influences\Nor if it's just genetics,
Dialogue: 0,0:12:39.27,0:12:43.20,Default,,0000,0000,0000,,but we did do a study in which we looked\Nat the mouse several years ago
Dialogue: 0,0:12:43.20,0:12:48.12,Default,,0000,0000,0000,,and we were looking at genes\Nthat encode for, in this case a DRD2,
Dialogue: 0,0:12:48.12,0:12:52.25,Default,,0000,0000,0000,,the gene listed on the top\Nis a dopamine receptor.
Dialogue: 0,0:12:52.25,0:12:58.58,Default,,0000,0000,0000,,Tyrosine hydroxylase, TH, is a gene\Ninvolved in dopamine biosynthesis
Dialogue: 0,0:12:58.58,0:13:03.39,Default,,0000,0000,0000,,and those 2 gene products\Nare very different in the cell types
Dialogue: 0,0:13:03.39,0:13:06.04,Default,,0000,0000,0000,,in these individual mouse brains.
Dialogue: 0,0:13:06.04,0:13:11.64,Default,,0000,0000,0000,,So, over on the left is "C57 Black 6"\Nwhich is a commonly used mouse strain,
Dialogue: 0,0:13:11.64,0:13:15.46,Default,,0000,0000,0000,,and then spread at the other end\Nis a wild type strain.
Dialogue: 0,0:13:15.46,0:13:19.70,Default,,0000,0000,0000,,And so the further you go\Nthe more genetically unrelated you are.
Dialogue: 0,0:13:19.70,0:13:23.80,Default,,0000,0000,0000,,And when we looked in total across,\Nsort of evolution if you will,
Dialogue: 0,0:13:23.80,0:13:25.52,Default,,0000,0000,0000,,across genetic relatedness,
Dialogue: 0,0:13:25.52,0:13:28.20,Default,,0000,0000,0000,,the further you were\Ngenetically unrelated,
Dialogue: 0,0:13:28.20,0:13:30.33,Default,,0000,0000,0000,,the more of these\Nvery specific cell types,
Dialogue: 0,0:13:30.33,0:13:32.93,Default,,0000,0000,0000,,specific changes, you could see.
Dialogue: 0,0:13:33.81,0:13:36.50,Default,,0000,0000,0000,,So at the Allen Institute\Nfor the next decade
Dialogue: 0,0:13:36.50,0:13:38.83,Default,,0000,0000,0000,,we're embarking\Non a pretty ambitious program
Dialogue: 0,0:13:38.83,0:13:43.44,Default,,0000,0000,0000,,to start to understand the cell types,\Nunderstand the cell differences
Dialogue: 0,0:13:43.44,0:13:46.96,Default,,0000,0000,0000,,and how they ultimately relate\Nto the functional properties of the brain.
Dialogue: 0,0:13:46.96,0:13:50.78,Default,,0000,0000,0000,,This is, I think, critical information\Nfor the entire field,
Dialogue: 0,0:13:50.78,0:13:54.09,Default,,0000,0000,0000,,to start linking up all\Nof these fundamental parts
Dialogue: 0,0:13:54.09,0:13:57.33,Default,,0000,0000,0000,,which are the cells,\Nto how they're connected,
Dialogue: 0,0:13:57.33,0:14:00.62,Default,,0000,0000,0000,,the underlying molecules\Nthat drive those connections,
Dialogue: 0,0:14:00.62,0:14:04.42,Default,,0000,0000,0000,,the underlying molecules driving\Nthe electrophysiological properties,
Dialogue: 0,0:14:04.42,0:14:06.55,Default,,0000,0000,0000,,the electrochemical properties
Dialogue: 0,0:14:06.55,0:14:09.99,Default,,0000,0000,0000,,and then ultimately\Nthe functional properties of those cells.
Dialogue: 0,0:14:09.99,0:14:14.21,Default,,0000,0000,0000,,So we're doing this\Nin 3 different areas of research.
Dialogue: 0,0:14:14.21,0:14:17.27,Default,,0000,0000,0000,,First, we're focusing on the mouse,\Nthe mouse visual system,
Dialogue: 0,0:14:17.27,0:14:21.20,Default,,0000,0000,0000,,to look at, in real-time,\Nin the living animal,
Dialogue: 0,0:14:21.20,0:14:25.79,Default,,0000,0000,0000,,the functions of a variety\Nof different cells.
Dialogue: 0,0:14:25.79,0:14:28.90,Default,,0000,0000,0000,,We're linking these in this concept\Nin the middle of cell types,
Dialogue: 0,0:14:28.90,0:14:33.65,Default,,0000,0000,0000,,trying to really understand\Nthe underlying molecules
Dialogue: 0,0:14:33.65,0:14:37.26,Default,,0000,0000,0000,,in all the properties\Nas they relate to those functions
Dialogue: 0,0:14:37.26,0:14:40.11,Default,,0000,0000,0000,,and then we're looking at the human.
Dialogue: 0,0:14:40.11,0:14:44.01,Default,,0000,0000,0000,,In the human we're doing this both\Nin the middle and cell types
Dialogue: 0,0:14:44.01,0:14:46.74,Default,,0000,0000,0000,,using the tissue driven work\Nthat I talked about before,
Dialogue: 0,0:14:46.74,0:14:51.80,Default,,0000,0000,0000,,but also we're doing it in vitro\Nusing stem cell technology.
Dialogue: 0,0:14:51.80,0:14:55.36,Default,,0000,0000,0000,,We're learning how to make\Nvery specific cell types within the dish
Dialogue: 0,0:14:55.36,0:14:58.36,Default,,0000,0000,0000,,and then being able to test\Nthose functional properties
Dialogue: 0,0:14:58.36,0:15:04.65,Default,,0000,0000,0000,,and go back and forth between\Nwhat we learn in the mouse to the human.
Dialogue: 0,0:15:04.65,0:15:08.62,Default,,0000,0000,0000,,So, with that I will finish\Nand just say that it's an exciting time
Dialogue: 0,0:15:08.62,0:15:11.49,Default,,0000,0000,0000,,to be in biology and an exciting time\Nto be in neuroscience.
Dialogue: 0,0:15:11.49,0:15:15.49,Default,,0000,0000,0000,,I think the technology of the day\Nhas come well beyond the pen and paper
Dialogue: 0,0:15:15.49,0:15:20.58,Default,,0000,0000,0000,,and it's really time for a renaissance in\Nour understanding of this complex organ.
Dialogue: 0,0:15:20.58,0:15:21.99,Default,,0000,0000,0000,,Thanks.
Dialogue: 0,0:15:21.99,0:15:24.18,Default,,0000,0000,0000,,(Applause)