Humans have long held a fascination for the human brain. We chart it, we've described it, we've drawn it, we've mapped it. Now just like the physical maps of our world that have been highly influenced by technology -- think Google Maps, think GPS -- the same thing is happening for brain mapping through transformation.
人类长时间的着迷于 人类的大脑。 我们讨论它,描述它。 我们已经画出了它。 我们已经把它地图化了。 现在,就像我们现实中的地图 被科技高度影响着—— 比如谷歌地图, 比如全球定位系统, 和它们一样,我们的大脑地图也在 经历变革。
So let's take a look at the brain. Most people, when they first look at a fresh human brain, they say, "It doesn't look what you're typically looking at when someone shows you a brain." Typically, what you're looking at is a fixed brain. It's gray. And this outer layer, this is the vasculature, which is incredible, around a human brain. This is the blood vessels. 20 percent of the oxygen coming from your lungs, 20 percent of the blood pumped from your heart, is servicing this one organ. That's basically, if you hold two fists together, it's just slightly larger than the two fists.
让我们来看一看大脑。 大多数人,当他们第一次看到新鲜的人脑时, 他们会说,“它看起来和一般 别人展现给我们的大脑不一样。” 一般,你以前看到的大脑是一个固定了的大脑。它是灰白色的。 这是大脑的外层,这是脉管系统。 它们不可思议的围绕着人类的大脑。 这是血管。 含有20% 由肺部供应的氧气。 你的心脏产生的20%的血液 都用来供应大脑这一个器官。 如果你握住你的两个拳头,它基本上 只比你的两个拳头大一点。
Scientists, sort of at the end of the 20th century, learned that they could track blood flow to map non-invasively where activity was going on in the human brain. So for example, they can see in the back part of the brain, which is just turning around there. There's the cerebellum; that's keeping you upright right now. It's keeping me standing. It's involved in coordinated movement. On the side here, this is temporal cortex. This is the area where primary auditory processing -- so you're hearing my words, you're sending it up into higher language processing centers. Towards the front of the brain is the place in which all of the more complex thought, decision making -- it's the last to mature in late adulthood. This is where all your decision-making processes are going on. It's the place where you're deciding right now you probably aren't going to order the steak for dinner.
科学家们在大约20世纪晚期的时候 发现他们可以通过非侵入式的方法 来追踪血液的流动 从而绘制出在人类大脑里活动进行的区域图。 举个例子,他们可以看到大脑后面的那一部分, 就是刚刚转过来的这里。 这里是小脑,它使你现在能保持正确的直立。 它使得我能站在这里。它是一个相互协调的活动中的一部分。 在侧面这里的是颞叶皮层。 我们听到的东西在这里被初级加工, 所以你现在可以听见我说的话 你正在把刚才听到的话传送到更高级的语言处理中心。 在大脑的前方这里 是产生所有复杂的思想,作出决定的地方, 它是最后成熟的地方,在我们到了成年期后期的时候。 这是你所有决策过程正在进行的地方。 这是你正在进行决定的地方, 你或许不会点一份牛排作为晚餐。
So if you take a deeper look at the brain, one of the things, if you look at it in cross-section, what you can see is that you can't really see a whole lot of structure there. But there's actually a lot of structure there. It's cells and it's wires all wired together. So about a hundred years ago, some scientists invented a stain that would stain cells. And that's shown here in the the very light blue. You can see areas where neuronal cell bodies are being stained. And what you can see is it's very non-uniform. You see a lot more structure there. So the outer part of that brain is the neocortex. It's one continuous processing unit, if you will. But you can also see things underneath there as well. And all of these blank areas are the areas in which the wires are running through. They're probably less cell dense. So there's about 86 billion neurons in our brain. And as you can see, they're very non-uniformly distributed. And how they're distributed really contributes to their underlying function. And of course, as I mentioned before, since we can now start to map brain function, we can start to tie these into the individual cells.
所以如果你更深入地看看大脑, 其中一部分,如果你看它的横截面, 你能发现的是 你不能真正地看到整个的,大部分的大脑结构。 但是大脑里确实有很多结构。 它的细胞和它的神经线全部都连接在一起。 所以在几百年前, 一些科学家发明了一种染色剂可以将细胞染色。 这里淡蓝色显示的就是。 你可以看到这些地方 正常的细胞体被染色了。 你可以看到它是非常不均一的,你可以看到有很多的结构。 在大脑外层部分 是新大脑皮层。 如果你愿意的话,它是一个可以连续处理的部件。 但是你可以看到在那之下的东西也是。 所有的这些空白区域 是所有脑神经线路穿过的地方。 这些地方的细胞密度或许会低一些。 我们的大脑中大约有860亿神经元。 正如你所见,它们的分布很不均一。 而它们的分布正好构成了 它们潜在的功能。 当然,正如我之前所提到, 我们现在可以开始绘制大脑功能地图了。 我们可以开始将这些功能嵌入每一个独立的细胞。
So let's take a deeper look. Let's look at neurons. So as I mentioned, there are 86 billion neurons. There are also these smaller cells as you'll see. These are support cells -- astrocytes glia. And the nerves themselves are the ones who are receiving input. They're storing it, they're processing it. Each neuron is connected via synapses to up to 10,000 other neurons in your brain. And each neuron itself is largely unique. The unique character of both individual neurons and neurons within a collection of the brain are driven by fundamental properties of their underlying biochemistry. These are proteins. They're proteins that are controlling things like ion channel movement. They're controlling who nervous system cells partner up with. And they're controlling basically everything that the nervous system has to do.
让我们来更深入地观察一下。 看那些神经元。 正如我刚才提到的,这里有860亿神经元。 还有一些你现在看到的小细胞。 它们是支持细胞——星形神经胶质细胞。 而且神经本身 是接收输入信息的。 它们存储信息,它们加工信息。 每一个神经元是由突触 与你大脑中其他10000个神经元相连接的。 而且每个神经元本身 大部分是独特的。 独立的神经元和大脑里一系列的神经元 的独特特性 是由它们潜在的基本化学生物性能 所驱使的。 就是蛋白质。 蛋白质控制着像离子移动通道这样的事情。 它们控制着神经系统各细胞相联系的部分。 而且它们还控制着 基本上与神经系统相有关的一切事。
So if we zoom in to an even deeper level, all of those proteins are encoded by our genomes. We each have 23 pairs of chromosomes. We get one from mom, one from dad. And on these chromosomes are roughly 25,000 genes. They're encoded in the DNA. And the nature of a given cell driving its underlying biochemistry is dictated by which of these 25,000 genes are turned on and at what level they're turned on.
所以当我们更加深入地去观察 所有的这些蛋白质 都被我们的基因组编码了。 我们每个人都有23对染色体。 我们从母亲那继承一半,从父亲那继承一半。 而且在这些染色体上 大约有25000个基因。 它们在DNA中被译成编码。 一个特定细胞的天性 操纵着它潜在的生物化学性能 这个天性由这25000 启动的基因 和他们启动的级别所指示。
And so our project is seeking to look at this readout, understanding which of these 25,000 genes is turned on. So in order to undertake such a project, we obviously need brains. So we sent our lab technician out. We were seeking normal human brains. What we actually start with is a medical examiner's office. This a place where the dead are brought in. We are seeking normal human brains. There's a lot of criteria by which we're selecting these brains. We want to make sure that we have normal humans between the ages of 20 to 60, they died a somewhat natural death with no injury to the brain, no history of psychiatric disease, no drugs on board -- we do a toxicology workup. And we're very careful about the brains that we do take. We're also selecting for brains in which we can get the tissue, we can get consent to take the tissue within 24 hours of time of death. Because what we're trying to measure, the RNA -- which is the readout from our genes -- is very labile, and so we have to move very quickly.
所以我们的项目 是寻找这个读出器, 并理解这25000个基因中哪些被启动了。 所以为了进行这样的一个项目, 我们明显需要大脑。 所以我们派实验室技术员外出。 我们寻找正常的人类大脑。 我们真正开始的地方是 一个验尸员的办公室。 那是个死人被带去的地方。 我们寻找的是正常的人类大脑。 我们根据许多参考数据来选的大脑 我们希望确保 我们得到的大脑是20到60岁正常人的大脑, 他们是自然死亡的 大脑没有受到损伤, 他们不能有精神病史, 我们会做毒性检查确保他们 没有滥用药物的历史。 我们对我们所选取的大脑 非常小心。 我们也选取那些 我们可以得到脑组织的大脑。 我们得得到同意去提取 24小时内死亡的人的大脑的脑组织。 因为我们试图要去测量的东西——RNA核糖核酸 就是我们基因里的读出器-- 是非常易变的。 所以我们必须要快速行动。
One side note on the collection of brains: because of the way that we collect, and because we require consent, we actually have a lot more male brains than female brains. Males are much more likely to die an accidental death in the prime of their life. And men are much more likely to have their significant other, spouse, give consent than the other way around.
在收集大脑上有一点要提示: 因为我们收集的方式, 并且需要许可 所以我们事实上得到的男性大脑比女性大脑多。 男性更有可能在他们生命的青壮年时期意外死亡。 男性的家友,他的配偶 更加容易给我们许可。 相比之下,反过来,女性的配偶很少给我们许可。
(Laughter)
笑声
So the first thing that we do at the site of collection is we collect what's called an MR. This is magnetic resonance imaging -- MRI. It's a standard template by which we're going to hang the rest of this data. So we collect this MR. And you can think of this as our satellite view for our map. The next thing we do is we collect what's called a diffusion tensor imaging. This maps the large cabling in the brain. And again, you can think of this as almost mapping our interstate highways, if you will. The brain is removed from the skull, and then it's sliced into one-centimeter slices. And those are frozen solid, and they're shipped to Seattle. And in Seattle, we take these -- this is a whole human hemisphere -- and we put them into what's basically a glorified meat slicer. There's a blade here that's going to cut across a section of the tissue and transfer it to a microscope slide. We're going to then apply one of those stains to it, and we scan it. And then what we get is our first mapping.
我们在采集地点做的第一件事 是收集我们所说的核磁共振——MR。 这是核磁共振成像-MRI。 它是一个标准的模版,通过它我们可以留住其他的数据。 所以我们收集这个MR 你可以把这个当做是我们地图的卫星图。 接下来我们要做的事 是收集叫做弥散张量成像的东西。 这张地图是在大脑中连接的大量神经。 再次重申,如果你愿意你可以把这想象成 和制作我们的洲际间高速公路地图一样。 这个大脑是从头盖骨上分离的 然后把它切成一厘米的薄片。 那些是冷冻的固体, 然后它们被运到西雅图。 在西雅图,我们拿这个 这是一个完整的人脑的半球体 我们把它放进一个基本是改造过的肉类切片机。 这有一个刀片可以切 大脑脑组织的一部分 并转换成一个显微镜载片。 我们将会对它进行着色 并扫描它。 然后我们就得到了第一副地图。
So this is where experts come in and they make basic anatomic assignments. You could consider this state boundaries, if you will, those pretty broad outlines. From this, we're able to then fragment that brain into further pieces, which then we can put on a smaller cryostat. And this is just showing this here -- this frozen tissue, and it's being cut. This is 20 microns thin, so this is about a baby hair's width. And remember, it's frozen. And so you can see here, old-fashioned technology of the paintbrush being applied. We take a microscope slide. Then we very carefully melt onto the slide. This will then go onto a robot that's going to apply one of those stains to it. And our anatomists are going to go in and take a deeper look at this.
专家就是从这里入手 并制作基本的解剖作业。 如果你愿意你可以思考州的边界, 那些漂亮宽阔的轮廓。 从这开始我们可以更进一步把大脑切成碎片 使它可以放在一个更小的低温恒温器上。 就是这里展示的这个-- 这个冷冻过的脑组织,它正在被切割。 这是20微米的厚度,大约和婴儿的头发一样粗。 记住,它是冷冻的 所以你可以看到 古老的笔刷技术正在被应用。 我们拿一个显微镜载片。 然后我们非常小心的让它融化在载片上。 然后它会被送到一个机器人那 在那它会被涂上那些染色剂中的一种。 我们的解剖学家们这时候会进入并且更深入的了解它们。
So again this is what they can see under the microscope. You can see collections and configurations of large and small cells in clusters and various places. And from there it's routine. They understand where to make these assignments. And they can make basically what's a reference atlas. This is a more detailed map.
这是他们在显微镜下看到的景象。 你可以在聚集群和不同区域看到 大大小小的细胞 聚集和结构。 这是一个程序,他们知道哪里去完成这些作业。 而且他们可以制作基本上所涉及到的地图集。 这是一个更详细的地图。
Our scientists then use this to go back to another piece of that tissue and do what's called laser scanning microdissection. So the technician takes the instructions. They scribe along a place there. And then the laser actually cuts. You can see that blue dot there cutting. And that tissue falls off. You can see on the microscope slide here, that's what's happening in real time. There's a container underneath that's collecting that tissue. We take that tissue, we purify the RNA out of it using some basic technology, and then we put a florescent tag on it. We take that tagged material and we put it on to something called a microarray.
我们的科学家用这个 返回到另一片大脑组织上 并且做激光扫描纤维解剖。 所以技术人员得到指令。 他们沿着那的一个地方划线。 然后激光真的做切割。 你可以看到正在切割的蓝点,然后那片脑组织脱落。 你可以看到在显微镜载片这里, 现在正在立即发生的事。 这有一个容器在下面收集这些脑组织。 我们用一些基本的技术, 从这些脑组织里 净化出RNA 然后我们放一个荧光标签在上面。 我们拿标记过的材料 然后我们把它放在一些叫做微阵列芯片的东西上。
Now this may look like a bunch of dots to you, but each one of these individual dots is actually a unique piece of the human genome that we spotted down on glass. This has roughly 60,000 elements on it, so we repeatedly measure various genes of the 25,000 genes in the genome. And when we take a sample and we hybridize it to it, we get a unique fingerprint, if you will, quantitatively of what genes are turned on in that sample.
现在你可能认为你看到的是一群圆点, 但是事实上每一个独立的小点 都是一片我们点在玻璃片上的 独特的人类基因组。 它大约含有60000个元素在上面, 所以我们反复地测量基因组25000个基因中 各种各样的基因。 当我们得到一个样本而且我们让它与玻璃片吻合 我们得到一个独特的指纹, 如果你愿意那个例子里的大量的基因都会开启。
Now we do this over and over again, this process for any given brain. We're taking over a thousand samples for each brain. This area shown here is an area called the hippocampus. It's involved in learning and memory. And it contributes to about 70 samples of those thousand samples. So each sample gets us about 50,000 data points with repeat measurements, a thousand samples.
现在我们一遍一遍地做这件事, 对任何得到的大脑。 我们从一个大脑上可以得到一千个样本。 这里显示的这个区域是大脑海马区。 它牵扯到学习和记忆。 它可以贡献1000个样本中的 大约70个样本。 每个样本给我们50000个数据点 使用重复测量得到一千个样本。
So roughly, we have 50 million data points for a given human brain. We've done right now two human brains-worth of data. We've put all of that together into one thing, and I'll show you what that synthesis looks like. It's basically a large data set of information that's all freely available to any scientist around the world. They don't even have to log in to come use this tool, mine this data, find interesting things out with this. So here's the modalities that we put together. You'll start to recognize these things from what we've collected before. Here's the MR. It provides the framework. There's an operator side on the right that allows you to turn, it allows you to zoom in, it allows you to highlight individual structures.
所以大约我们有 5千万数据点 从一个贡献的脑中得到。 我们现在完成了 从两个人类大脑所获得的数据。 我们把所有的这些放在一起 在一个东西里, 我将向你展示这个综合体看起来是什么样子的。 它基本上是一个大的信息数据集 世界上任何的科学家都可以免费得到里面的数据。 他们甚至都不用登陆来使用这个工具, 开采这些数据,从其中找出更多有趣的东西。 所以这是我们把这些放在一起的模型。 你从我们之前收集的数据开始了解这些事情。 这是磁共振。它提供一个框架。 这里左边有一个操纵杆可以让你扳动。 它可以帮你放大, 它可以帮你标记独立的结构。
But most importantly, we're now mapping into this anatomic framework, which is a common framework for people to understand where genes are turned on. So the red levels are where a gene is turned on to a great degree. Green is the sort of cool areas where it's not turned on. And each gene gives us a fingerprint. And remember that we've assayed all the 25,000 genes in the genome and have all of that data available.
最重要的是 我们现在正在绘制地图的这个解剖学上的框架, 它是我们通常所理解的基因启动的地方。 所以红色的级别 是基因开启到一个良好的级别。 绿色的是稍稍有些不活跃的地方,它没有被启动。 每一个基因都给我们一个指纹。 记住我们已经化验了所有25000个基因组中的基因 并且用所有的可用数据。
So what can scientists learn about this data? We're just starting to look at this data ourselves. There's some basic things that you would want to understand. Two great examples are drugs, Prozac and Wellbutrin. These are commonly prescribed antidepressants. Now remember, we're assaying genes. Genes send the instructions to make proteins. Proteins are targets for drugs. So drugs bind to proteins and either turn them off, etc. So if you want to understand the action of drugs, you want to understand how they're acting in the ways you want them to, and also in the ways you don't want them to. In the side effect profile, etc., you want to see where those genes are turned on. And for the first time, we can actually do that. We can do that in multiple individuals that we've assayed too.
所以我们的科学家从这些数据中学到了什么呢? 我们自己仅仅开始看这些数据 有一些基本的你想了解的东西 药品中有两个很好的例子, 百忧解和安非他酮。 它们都是通常规定的抗抑郁类药物。 现在记住,我们正在化验基因。 基因发送指令来合成蛋白质。 蛋白质是药物的目标。 所以药物和蛋白质是捆绑在一起的 把它们其中的一个去掉,等等 如果你想去理解药物的行动, 你想要理解它们有没有按照你想要它们行动的方式 和不想让它们行动的方式运行。 在副作用方面等 你想明白那些基因在哪儿可以开启。 第一次我们可以确确实实做到。 我们可以做到成倍的个体我们也可以化验。
So now we can look throughout the brain. We can see this unique fingerprint. And we get confirmation. We get confirmation that, indeed, the gene is turned on -- for something like Prozac, in serotonergic structures, things that are already known be affected -- but we also get to see the whole thing. We also get to see areas that no one has ever looked at before, and we see these genes turned on there. It's as interesting a side effect as it could be. One other thing you can do with such a thing is you can, because it's a pattern matching exercise, because there's unique fingerprint, we can actually scan through the entire genome and find other proteins that show a similar fingerprint. So if you're in drug discovery, for example, you can go through an entire listing of what the genome has on offer to find perhaps better drug targets and optimize.
所以现在我们可以看透大脑。 我们可以看到这独特的指纹。 我们得到确认 我们确实确认基因 可以为一些类似百忧解的东西打开 这些东西含血清素的结构,这些东西已经知道是可以起作用的 但是我们还没有看到整个事情的全部。 我们还有机会看了一些以前从来没有人看到过的区域, 我们看到这些基因在那些地方启动。 这是一个非常非常有趣的副作用。 另一个你可以这样做的原因是 因为它是一个联系的匹配模型, 因为有独特的指纹, 我们可以确确实实地扫描整个基因组 并发现其他的蛋白质 显示同样的指纹。 举个例子,如果你是在研究药物, 你可以浏览 整个已经提供的基因组列表 来发现更好的药物目标并优化。
Most of you are probably familiar with genome-wide association studies in the form of people covering in the news saying, "Scientists have recently discovered the gene or genes which affect X." And so these kinds of studies are routinely published by scientists and they're great. They analyze large populations. They look at their entire genomes, and they try to find hot spots of activity that are linked causally to genes. But what you get out of such an exercise is simply a list of genes. It tells you the what, but it doesn't tell you the where. And so it's very important for those researchers that we've created this resource. Now they can come in and they can start to get clues about activity. They can start to look at common pathways -- other things that they simply haven't been able to do before.
你们大部分人可能对基因组协会的研究 非常熟悉 以人们通常在新闻中看到的形式: 科学家们最近发现了影响X染色体 的基因。 这一类的研究 被科学家们例行公事的颁布 他们很棒。他们分析了大量的人口。 他们着眼于他们整个的基因组, 他们试图找出 与基因有原因关连的这些活跃热点。 但是你从这些试验中得到的 只是简单的基因列表。 它可以告诉你是什么但是没法让你知道在哪。 所以对那些研究员来说我们发现的这些资源 是非常重要的。 现在他们可以来我们这 并得到开始活动的线索。 他们可以开始考虑通常的途径—— 其他的以前他们没有办法做到的途径。
So I think this audience in particular can understand the importance of individuality. And I think every human, we all have different genetic backgrounds, we all have lived separate lives. But the fact is our genomes are greater than 99 percent similar. We're similar at the genetic level. And what we're finding is actually, even at the brain biochemical level, we are quite similar. And so this shows it's not 99 percent, but it's roughly 90 percent correspondence at a reasonable cutoff, so everything in the cloud is roughly correlated. And then we find some outliers, some things that lie beyond the cloud. And those genes are interesting, but they're very subtle. So I think it's an important message to take home today that even though we celebrate all of our differences, we are quite similar even at the brain level.
所以我想这些特别的观众 可以理解个性的重要性。 我认为每一个人, 我们都有不同的遗传的背景, 我们都有各自的生活。 但是事实是 我们的基因组有超过99%的都是一样的。 我们在遗传的级别上是一样的。 我们发现的事实是 甚至在大脑的生物化学级别上 我们都是非常相似的。 所以这显示它不是99% 但是它大约90%一致 在一个合理的结算下 所以显然每一件事都是大概相关联的。 然后我们发现了一些异常值, 一些隐藏在云雾后的事情。 那些基因是非常有趣的, 但是它们是很微妙的。 所以我想它是一个很重要的信息 今天你们可以带回家的 是尽管我们庆幸我们所有的不同, 我们还是非常相像的 甚至在大脑层面。
Now what do those differences look like? This is an example of a study that we did to follow up and see what exactly those differences were -- and they're quite subtle. These are things where genes are turned on in an individual cell type. These are two genes that we found as good examples. One is called RELN -- it's involved in early developmental cues. DISC1 is a gene that's deleted in schizophrenia. These aren't schizophrenic individuals, but they do show some population variation. And so what you're looking at here in donor one and donor four, which are the exceptions to the other two, that genes are being turned on in a very specific subset of cells. It's this dark purple precipitate within the cell that's telling us a gene is turned on there. Whether or not that's due to an individual's genetic background or their experiences, we don't know. Those kinds of studies require much larger populations.
这些不同看起来像什么呢? 这是一个研究的例子 我们跟踪并研究这些不同到底是什么 而且它们是非常精妙的。 我们发现的是基因以独立的细胞类型呈现。 我们发现了两个基因作为很好的例子。 一个叫做RELN——它被包含在一个早期的发展线索中。 DISC1是一个 在精神分裂症中被删除的基因。 这些不是导致精神分裂症的个体, 但是它们确实显示了一些人类的变化。 所以我们在寻找的是 在捐献者一和捐献者四中, 这两个捐献者的大脑与其他两个不同, 基因在细胞的不同子集中 被打开。 是在细胞中这个深紫色的沉淀 告诉我们那里有一个基因被打开了。 不论那是归因于 一个独立的基因背景或者它的经历。 我们不知道。 这种研究需要更大量的人类大脑。
So I'm going to leave you with a final note about the complexity of the brain and how much more we have to go. I think these resources are incredibly valuable. They give researchers a handle on where to go. But we only looked at a handful of individuals at this point. We're certainly going to be looking at more. I'll just close by saying that the tools are there, and this is truly an unexplored, undiscovered continent. This is the new frontier, if you will. And so for those who are undaunted, but humbled by the complexity of the brain, the future awaits.
所以我给你们一条最后的注释 有关于大脑的复杂性 我们还有漫漫长路需要探索。 我想这些资源是无价之宝。 它们给研究员们 指出一条道路。 但是我们现在只是研究了少数的个体。 我们很确定我们要去研究更多的。 在结束时我想说 工具在那里, 而且这是一个真正的未被勘察过,未被发现的领域。 如果你愿意,这是一个新的前沿 对那些勇敢的 但是深感大脑的复杂性很重要的人 未来在等着你们。
Thanks.
谢谢。
(Applause)
掌声