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.
人類長久以來對人腦 感到著迷。 我們試圖繪製它、解釋它、 我們已經將它畫出來、 已經繪製了它。 就像是真實事件的地圖一樣, 繪製腦袋圖也受科技影響很深-- 像是谷哥地圖, 像是衛星定位-- 同樣的事情在繪製腦袋圖時 也同樣在發生。
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.
所以讓我們來瞭解一下腦袋。 很多人,當他們第一次看到人腦的時候 會說:「這不是一般人家給你看腦的時候 會看到的東西。」 大部份時候你會看到的是已經固定的腦。是灰色的。 這外面的這一層,這是微血管, 圍繞在腦袋邊緣, 非常驚人。 這些是血管。 從肺中得到的 是百分之二十的氧氣、 百分之二十從你的心臟中泵出來的血液, 都是供應給這個器官。 簡單的說, 如果你把你的兩個拳頭放在一起, 它僅僅比這兩個拳頭大一點點而已。
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.
科學家在二十世紀末時 學到如何利用非侵入性的手法 追蹤血液流向 來瞭解人腦正在工作的區域。 舉例來說,他們可以從腦部背後 這樣追蹤來到這裡。 這是小腦,就是讓你現在保持著頭上腳下姿勢的東西。 它跟協調性動作有關,讓我現在可以站著。 在這裡是顳葉皮層。 這裡跟聽覺處理有關: 就是說你現在正在聽我講話, 你把這個資訊送到語言處理中心。 在腦的前面 是這個更複雜、跟做決定有關的東西。 它是最晚成熟的部位,直到成年時期才發育完成。 這是你腦袋做所有決定的地方。 這是你現在正在決定 你晚上是不是要點牛排當晚餐的地方。
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.
所以如果你更進一步地看我們的腦袋, 如果你看這個切片圖, 你會看到 這邊沒有很多結構。 但事實上這邊是有很多結構的。 這些是細胞被串聯在一起。 大概在一百年前, 一些科學家發明了一個可以染細胞的染劑。 在這裡可以看到淡淡的藍色。 你可以看到有些區域 有著被染色的細胞。 但你也可以看到它並不規律。你可以看到更多的結構。 在腦袋的外層 是大腦皮層。 你可以說它是一個連續的單位。 但你也可以看到在它下面還有很多其他的結構。 而這些空白的區域 就是連接網絡經過的地方。 這些區域的細胞密度有可能比較低。 所以我們腦袋中有86億個神經元。 而且就像你們看到的,他們沒有非常規律地分佈。 而他們如何分佈的 事實上和他們的功能有關。 而且就像我之前提到的, 因為我們已經開始繪製腦袋功能解析圖了, 我們可以試圖將這些細胞連接起來。
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.
讓我們更進一步地觀察。 讓我們看看這些神經元。 就像我剛剛說的,我們有86億神經元。 你們還可以看到還有這些更小的細胞。 這些是支持細胞, 叫作星狀膠細胞。 但接收到訊息的 是神經本身。 它們將訊息儲存並作處理。 每個神經元可經由突觸 連接到最多一萬個其它也在腦部的神經元。 且每一個神經元 都有它的獨特性。 單一神經元和 某些聚在同一區域的神經元的獨特性 是源於基本的 生化特性。 也就是蛋白質。 蛋白質控制像是離子通道輸送功能這類的事情。 蛋白質也決定神經系統與什麼東西合作。 基本上蛋白質控制了 所有與神經系統有關係的東西。
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.
所以如果我們更深入地看, 這些蛋白質 是由我們的基因所決定的。 我們有23對染色體。 其中一條來自於母親,另一條來自父親。 在這些染色體上, 大約有25,000個基因。 這些基因被寫在DNA裡面。 而細胞本質 這些基層的生化組成, 就是由這25,000個基因 來決定何時被啓動 及如何被啓動的。
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.
所以我們的計畫 就是研究這些結果, 試圖瞭解這25,000個基因中的哪一些是被啓動的。 所以要做這樣的實驗, 我們明顯地需要腦袋。 所以我們派了實驗室技師 來幫我們搜集正常的人腦。 我們從法醫的辦公室 出發。 這是一個死人會被帶到的地方。 我們想要正常的人腦。 我們對我們需要的腦袋有很多要求。 我們需要確定 我們得到的腦袋是在20到60歲之間、 是自然死的、 沒有任何腦部傷害、 沒有任何心裡疾病、 沒有長期用藥-- 我們會要做一系列的毒物檢查。 且我們要非常謹慎地 對待我們要拿的腦袋。 我們選擇 可以從中拿到組織的腦袋, 且我們需要在死亡後24小時內 拿到取組織的許可。 因為我們想要測量的RNA(核糖核酸) 代表著各個基因的表現量-- 這是非常不穩定的, 所以我們需要很快的速度完成實驗。
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.
另外一個值得一提的是: 因為我們這樣的做法, 也就是我們需要得到許可, 我們得到的男性腦袋遠多於女性腦袋。 男性比女性更有可能在壯年時期死於意外事件。 而且男性比女性 更容易取得他的重要伴侶、另一半的許可 願意讓我們拿他的腦袋。
(Laughter)
(笑聲)
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.
在我們取到樣本後的第一件事情 就是取得我們叫作MR的東西。 這是一張MRI也就是核磁共振影像。 這是一張基準圖,我們用它來跟我們取得的影像做比較。 我們取得這個叫MR的東西。 你可以把這個想成是我們想要繪製的地圖的衛星圖。 接下來我們要做的是 取得一個叫做彌散張量圖的東西。 這可以幫忙繪製腦袋中比較明顯的連結。 你可以把這個想像成 地圖上的高速公路。 從頭骨中取出腦袋後, 我們將之切成約一公分後的切片。 這些切片冷凍後 被送到西雅圖。 在西雅圖,我們會拿到這個, 這是整個人腦半球, 然後把它放在一個基本上是切肉機的東西。 這邊有刀片,可以從組織中 切出一部份 然後將它放到顯微鏡玻片上。 用染劑將之染色後 就可以掃描了。 我們就可以得到第一張圖。
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.
這裡是專業學者來 將基本的結構標示出來的時候。 你可以把這個想像成各州的界限, 就是那些很容易劃分的界限。 從這裡,我們可以開始將腦袋進一步分成幾個小部份, 然後我們可以把這些部份分開存放於低溫存放器中。 這就是在做這件事情: 這是冷凍組織切片的過程。 這是20微米厚的切片,大約跟嬰兒頭髮一樣厚。 而且別忘了,這是冷凍的。 所以在這裡你可以看到, 古早的水彩筆方法被運用在這上面。 我們拿一片玻片, 很小心地將它熔在另一片玻片上。 然後讓機器人 加入染劑。 然後我們的解剖學家要更進一步的解析這個樣本。
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.
這是我們在顯微鏡下看到的東西。 你可以看到一些 大大小小的細胞 聚集在各處的一些構造。 從這裡開始就是例行事務。這些學者知道各個結構應該在哪裡。 他們可以建立一個像是圖鑒的東西。 就是一個更精準的地圖。
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.
我們的科學家利用這個資訊 再回到原本的樣本 並做雷射切割。 技師得到這個指令, 他們在這裡劃線, 也就是雷射切割的地方。 你可以看到這些雷射切割的藍點,然後整個組織會被切下。 你可以從這個影片看到 顯微玻片上發生的事情。 在這個下面有個桶子會接住所有切下的組織。 我們利用一些簡單的技術 將這個組織中的 RNA純化, 然後加上螢光顯色。 我們將顯色的東西 放到一個叫做芯片的東西上。
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.
你們可能會覺得這看起來像是一堆點點, 但這上面每一個點 都代表著人類基因的一個片段。 每個片段都被我們點在玻片上。 這上面大約有60,000個元素, 所以我們一直重複著測量 基因組中25,000個基因的表現量。 當我們拿一個樣本並將它跟芯片中的片段配對, 我們可以得到一個像是指紋般特殊的組合, 可以告訴我們樣本中哪些基因是被啓動的。
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.
我們對每一個我們拿到的腦袋 重複這件事情。 我們可以從一個腦袋中取得超過一千個樣本。 這個部位叫作海馬迴。 它跟學習和記憶有關。 在我們的一千個樣本中, 它大概佔了七十個。 所以我們大約有一千個樣本, 每個樣本可以給我們大約50,000個點。
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.
所以每一個腦袋 我們大約有五千萬個點。 目前我們大概做了 兩個人腦多的數據。 我們把這些數據 合成一體, 且我會給你們看我們怎麼做的。 基本上就是一個很大的數據組, 讓世界上所有科學家都可以用的數據。 他們不需要登入就可以使用、 挖掘、尋找他們想要的東西。 這是我們目前建構出來的模型。 你們會開始認識這些我們蒐集來的東西。 這是MR,它給我們一個骨架。 在右邊這裡可以控制讓圖轉動, 可以讓你放大, 也可以將特定的區域上色。
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.
但更重要的是, 我們是從這樣的解剖骨架來繪製我們的圖, 一個人類用來瞭解基因在何處被啓動的骨架。 這些紅色的 是基因表現量很高的地方。 綠色是基因沒有被啓動的地方。 而每一個基因給我們一個類似指紋的東西。 別忘了我們已經對基因組裡面25,000個基因做了這樣的實驗, 所以我們有所有基因的資料。
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.
那, 科學家們可以從這學到什麼? 我們也是才剛開始瞭解這些資料的。 有一些較基本的是你們可能會想要知道的。 兩個很棒的例子是藥物: 百憂解和Wellbutrin(抗憂鬱藥物)。 這些是常被用來治療憂鬱的藥物。 別忘了我們是在瞭解基因。 基因告訴我們的身體要製造蛋白質。 蛋白質是藥物的目標。 也就是說藥物和蛋白質結合 然後可以抑制蛋白質作用之類的。 所以如果你想要瞭解藥物是如何運作的, 你需要瞭解藥物是怎麼樣做到你想要它做的事, 和你不希望藥物做的事。 像是副作用之類的。 你想要知道各個基因是如何被啓動的。 而且是有史以来,我們真的可以這麼做。 且我們可以對不只一個樣本怎麼做。
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.
所以現在我們可以來看這個腦袋。 我們可以看這些特異的指紋。 我們可以確認它。 我們可以確認某些特定的基因是被啓動的: 像是百憂解這樣的東西, 它有羥色胺結構、我們已經知道會有影響, 但我們在這裡也可以看到整個架構。 我們可以看到以前看不到的東西, 我們可以看到這些基因被啓動。 這也有可能是很有趣的副作用。 另外一個你可以做的事是 你可以從這些資料中找出相關的部份。 因為這樣的指紋是獨特的, 我們可以掃過整個基因組 並尋找其他有相似指紋 的蛋白質。 舉例來說如果你是在做藥物研發, 你可以 掃過整個基因組 然後試著找到更好的藥物的目標而從中優化。
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.
在座的各位 可能對於掃描整個基因組的觀念 來自於新聞中一些字句。 像是:「科學家最近找到一個基因 會影響X。」 這樣的研究 常常被科學家發表。 且這是很好的。他們可以分析很大的族群。 他們可以看整個基因組, 然後試圖找到一些基因 容易影響的地方。 但事實上這樣的研究 只能找到一張基因列表。 它告訴你什麼基因,但沒辦法告訴你在哪裡表現。 所以對這些研究者來說, 我們就是給他們一個資源。 現在他們可以來 並開始尋找這些表現的痕跡。 他們現在可以去看是不是有共同的路徑, 是不是有其它他們沒有找到的東西。
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.
所以我想在座的各位 可以理解個體差異的重要性。 我認為每一個人 都有不一樣的基因背景, 我們都有不一樣的人生。 但事實上, 我們的基因組有超過百分之九十九是一樣的。 在基因的層面下我們非常相似。 而我們現在看到的是, 就算是在腦袋的生化層面上, 我們也是非常相似的。 所以這代表著不是百分之九十九, 但大約百分之九十 是個非常合理的範圍, 也就是說大部份的東西是相似的。 然後我們會找到一些「局外人」, 就是那些不在範圍內的數據。 且這些基因是很有趣的, 但他們不是很明顯的。 所以我想這是我今天要說的 一件很重要的事情 就是就算我們認為我們之間很不同, 但事實上我們是很相似的, 就算是在腦袋層面也是。
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.
這些相異處是什麼呢? 這是一個我們做的 用來瞭解這些相異處是什麼的研究。 這些相異處是很不明顯的。 像是各種不同細胞的哪些基因被啓動了。 這是我們找到兩個比較好的例子。 一個是RELN,它跟早期發育有關。 DISC1也是個基因, 是在精神分裂患者中被移除的基因。 這些不是精神分裂患者, 但他們也有個體差異。 所以你們現在看到的是 第一個捐贈者和第四個捐贈者。 它們的基因跟另外兩個不同, 他們的基因 在非常特定的細胞被啓動。 這些細胞內的深紫色的沈澱物 告訴我們那裡有哪些基因被啓動。 但到底是跟個體基因行有關 還是跟他們的經驗有關, 我們不知道。 這樣的研究需要更多更多的個體。
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.
所以我要跟你們說的最後一件事是 腦袋有多麼的複雜 和我們還還有多少研究需要做。 我認為這些資源非常重要。 這些資源讓研究者 知道接下來要怎麼做。 但目前我們只看了一些個體。 我們將來當然會看更多。 我最後只能說 我們需要的工具已經有了, 而且這是一個還沒被瞭解、還沒被研究的課題。 這是一個新推進。 所以給那些沒被嚇倒 但仍然對腦袋很感興趣的各位, 未來就在此。
Thanks.
謝謝。
(Applause)
(掌聲)