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.
Ljudi su već dugo očarani ljudskim mozgom. Istražujemo ga, opisujemo ga, crtamo ga, pravimo mapu ljudskog mozga. Tehnologija je značajno uticala na izgled mapa našeg sveta -- pomislite na Gugl mape, pomislite na GPS - isti preobražaj se dešava i u oblasti mapiranja mozga.
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.
Bacimo pogled na mozak. Većina ljudi, kada prvi put vidi svež ljudski mozak, kaže: "Ne podseća na ono što obično vidite kada vam neko pokaže mozak." Ono što vam je uglavnom pokazivano je prepariran mozak. Siv je. Ovaj spoljašnji sloj, to je vaskulatura , neverovatno je da se nalazi oko ljudskog mozga. To su krvni sudovi. 20 procenata kiseonika iz vaših pluća, 20 procenata krvi ispumpane iz vašeg srca, opslužuje ovaj jedan organ. Praktično, ako spojite dve pesnice, mozak je jedva malo veći od toga.
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.
Naučnici su negde krajem dvadesetog veka otkrili da prateći krvotok mogu neinvazivnim putem da mapiraju mesta aktivnosti u ljudskom mozgu. Na primer, mogu da pogledaju potiljačni deo mozga koji se nalazi otprilike ovde. Tu se nalazi mali mozak; održava vas u ovom momentu u uspravnom položaju. Meni omogućava da stojim. On je zadužen za održavanje ravnoteže. Sa strane se nalazi slepoočni režanj. Ovaj deo je zadužen za primarnu obradu zvuka -- tako da možete da čujete moje reči, i šaljete ih dalje u više centre za obradu govornih informacija Na prednjem delu mozga nalazi se centar za razmišljanje, donošenje odluka -- taj deo se poslednji formira, u odraslom dobu. Tu se odvijaju svi procesi vezani za donošenje odluka. To je mesto koje upravo sada odlučuje da verovatno nećete naručiti biftek za večeru.
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.
Ako pažljivije pogledate unutar mozga. ako posmatrate poprečni presek, možete uočiti da tu i nema baš mnogo struktura. Ali zapravo, postoji tu mnogo struktura. To su međusobno povezane ćelije i provodnici. Pre nekih sto godina, naučnici su izumeli način da oboje ćelije. To je prikazano ovde veoma svetlom plavom bojom. Možete uočiti zone koje predstavljaju obojena ćelijska tela neurona. Uočavate da nije jednolično. Primećujete mnogo više struktura. Spoljašnji deo ovog mozga je neokorteks. To je, moglo bi se reći, neprekidna jedinica za obradu informacija. Takođe možete uočiti i ono što leži ispod toga. Neobojeni regioni su delovi gde prolaze provodnici. Gustina ćelija je tu verovatno manja. U našem mozgu se nalazi oko 86 milijardi neurona. Kao što možete da vidite, nisu uniformno raspoređeni. Raspored neurona značajno određuje njihovu ulogu u mozgu. Naravno, kao što sam već spomenuo, s obzirom da smo počeli da mapiramo funkcije mozga sada možemo da ih povezujemo sa pojedinačnim ćelijama.
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.
Pogledajmo to detaljnije. Pogledajmo neurone. Kao što rekoh, imamo 86 milijardi neurona. Tu se nalaze i ove manje ćelije koje ćete videti. To su pomoćne ćelije - to je glija, to su astrociti. Sami neuroni su prijemnici informacija. Oni ih skladište i obrađuju. Svaki neuron je putem sinapsi povezan sa do 10 000 drugih neurona u vašem mozgu. Svaki neuron je sam po sebi poprilično jedinstven. Jedinstvene osobine i izdvojenih neurona i grupe neurona jedne strukture mozga su određene biohemijskim procesima koji se tu odvijaju. Proteini su za to zaduženi. Proteini koji upravljaju kretanjem jonskih kanala. Oni određuju sa kojim strukturama sarađuju ćelije nervnog sistema Upravljaju u principu svime što nervni sistem treba da uradi.
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.
Uveličanjem do sledećeg nivoa vidimo da su svi ovi proteini kodirani u našem genomu. Svako od nas ima 23 para hromozoma. Dobijemo jednu kopiju od majke, jednu od oca. Na ovim hromozomima se nalazi oko 25 000 gena. Geni su zapisani u našoj DNK. Priroda svake ćelije uslovljava određene biohemijske procese, a određena je podskupom uključenih gena od ukupno 25 000 prisutnih u genomu i merom njihove eksprimiranosti.
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.
Naš projekat ima za cilj da odgonetne ove parametre, da razume koji od ovih 25 000 gena su uključeni. Da bismo uradili takav projekat, očigledno je da su nam neophodni mozgovi. Tako da mi šaljemo laboratorijske tehničare na teren. Tražimo zdrave ljudske mozgove. Mi počinjemo u principu kod lekara-patologa, u mrtvačnici. Tu se donose mrtvi ljudi. Mi tražimo zdrave ljudske mozgove. Imamo puno kriterijuma po kojima biramo te mozgove. Zasigurno proverimo da su to bili zdravi ljudi stari između 20 i 60 godina, da su umrli prirodnom smrću bez povreda mozga, bez istorije psihijatrijskih bolesti, da nisu koristili droge - i proverimo toksikologiju. Pažljiivo se ophodimo prema mozgovima koje prihvatimo. Biramo one mozgove iz kojih možemo da izolujemo tkivo, gde možemo da dobijemo pristanak za preuzimanje tkiva u prva 24 sata posle smrti Moramo da budemo brzi u proceduri jer radimo sa RNK molekulima koji prenose informacije sa DNK do proteina, a veoma su nestabilni.
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.
Jedna napomena o prikupljanju mozgova: zbog načina na koji do organa dolazimo i budući da je neophodan pristanak, imamo mnogo više muških od ženskih mozgova. Veća je verovatnoća za muškarce da umru iznenadnom smrću u najboljim godinama Mnogo je veća verovatnoća da njihov životni partner da odobrenje za proceduru nego obrnuto.
(Laughter)
(smeh)
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.
Kada preuzmemo organ, na licu mesta napravimo nešto što se zove MR snimak. To je slikanje magnetnom rezonancom - MRI. To je standradni uzorak na osnovu kojeg ćemo analizirati ostatak podataka. Napravimo taj MR snimak. To je nešto kao satelitski snimak za našu mapu Sledeći korak je dobijanje nečega što nazivamo slikanje difuznom magnetnom rezonancom. To mapira velike provodnike u mozgu. To pak možete zamisliti kao mapiranje autoputeva među državama, ako želite. Potom izvadimo mozak iz lobanje i isečemo ga na deliće debljine jednog centimetra. Te uzorke potom zamrznemo, i pošaljemo ih u Sijetl. U Sijetlu preuzmemo uzorke, ovo je čitava jedna hemisfera ljudskog mozga, i postavimo uzorke u proslavljeni sekač mesa. Ovaj žilet pravi preseke kroz postavljeno tkivo i potom prebaci uzorak na mikroskopsku pločicu . Potom nanesemo na te uzorke određene boje i snimamo ih. Tada dobijamo našu prvu mapu.
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.
Stručnjaci potom dolaze na scenu i određuju anatomske odrednice uzoraka. Na to možete gledati kao na granice među državama, to su poprilično široki obrisi. Od ove tačke možemo dalje podeliti mozak na manje delove, koje potom postavimo na manji kriostat. To je prikazano ovde - zamrznuto tkivo koje sečemo. Uzorci su tanki 20 mikrona, debljine paperjaste dlake. Zapamtite da je tkivo zamrznuto. Možete ovde primetiti da koristimo staromodnu tehniku slikarske četkice. Dobijemo preparat za mikroskopiranje. Tada pažljivo otopimo uzorak na samoj pločici Posle toga će robot premazati uzorke jednom od ovih boja. Stručnjaci za anatomiju će zatim analizirati uzorak.
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.
Ovo je ono što mogu videti pod mikroskopom. Možete videti grupacije i oblike velikih i malih ćelija, i grupacija ćelija na raznim mestima. Od tog momenta, procedura je rutinska. Oni tada naprave referentni atlas. Ovo je detaljnija mapa.
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.
Naši naučnici na osnovu toga analiziraju drugi delić tog tkiva uz pomoć laserske mikrodisekcije. Tehničar dobije uputstva. Obeleži region na uzorku. Zatim se u principu laserom napravi rez. Uočićete ovu plavu tačku koju laser iseca. Tkivo se odvoji od uzorka. To možete sada videti na pločici, to se dešava istovremeno. Ispod svega se nalazi posuda u kojoj sakupljamo tkivo. Mi uzmemo to tkivo, izolujemo iz njega RNK koristeći osnovnu tehnologiju, i onda to obeležimo fluorescentnom bojom. Uzmemo taj obeleženi materijal i prebacimo ga na nešto što zovemo mikroniz (microarray).
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.
Ovo se vama može učiniti da je samo skup tačkica, ali u principu svaka tačka predstavlja jedinstveni deo humanog genoma koji smo mi preneli na staklo. Tu se nalazi oko 60 000 elemenata, tako da je svaki od 25 000 gena u genomu predstavljen nekoliko puta. Kada prebacimo i vežemo naš uzorak za tu platformu, dobijemo jedinstveni otisak, možemo ga tako nazvati, koji pokazuje koji geni su eksprimirani, i u kom stepenu u tom uzorku
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.
Ovo ponavljamo nekoliko puta za svaki mozak koji dobijemo. Za svaki mozak radimo analizu hiljadu uzoraka. Deo mozga koji je ovde pokazan se naziva hipokampus. Zadužen je za učenje i pamćenje. Uzorci hipokampalnog regiona mozga čine 70 uzoraka od tih hiljadu uzoraka koje analiziramo. Analiza svakog uzorka nam da oko 50 000 nalaza, imamo ponovljena merenja i radimo sa hiljadu uzoraka.
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.
Otprilike, govorimo o setu od 50 miliona nalaza za svaki mozak koji analiziramo. Do sada smo obradili nalaze iz dva ljudska mozga. Sve te podatke smo integrisali u jednu celinu i pokazaću vam kako ta sinteza podataka izgleda. To je jedna ogromna baza podataka koja je besplatna i dostupna svim naučnicima na svetu. Čak ne moraju ni da se registruju da bi je koristili, istraživali ove podatke i došli do interesantnih informacija. Ovo su moduli koje smo uspostavili. Prepoznaćete sada strukture sa kojima smo započeli proceduru. Ove je MR snimak. To nam daje okvir rada. Ovde, sa desne strane, imamo operatorske funkcije koje omogućavaju da uveličate određeni deo, da označite pojedinačne strukture.
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.
Najvažnije je to što sada prevodimo naše nalaze u anatomsku mrežu mozga, to je opšta mreža koja omogućava ljudima da shvate gde su geni eksprimirani. Crvena boja predstavlja strukture u kojima je gen snažno eksprimiran. Zelenom bojom je označen "hladni" region gde gen nije uključen Za svaki gen imamo jedinstvenu šemu. Zapamtite da smo analizirali svih 25 000 gena u genomu i svi ti podaci su dostupni.
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.
Šta naučnici mogu iz svega toga da nauče? Mi sada počinjemo da analiziramo ove podatke. Trebalo bi da razumete određene osnovne principe. Navešću dva divna primera lekova, a to su "Prozak" i "Wellbutrin". To su uobičajeni antidepresivi koje lekari prepisuju Zapamtite da mi analiziramo gene. Oni su recepti za sintezu proteina. Proteini su meta lekova. Lekovi se vezuju za proteine i mogu da ih uključe ili isključe, itd. Ako želite da razumete mehanizam delovanja leka, treba da shvatite kako oni rade na način koji vi želite i kako čine ono što ne želite da čine. U analizi sporednih efekata lekova, itd., želite da znate gde su ti geni uključeni. Po prvi put smo u principu u stanju to da uradimo. Možemo analizirati istu stvar kod velikog broja ljudi.
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.
Sada možemo da pregledamo ceo mozak. Uočićemo taj jedinstveni otisak gena. Tako dobijamo potvrdu. Dobijamo potvrdu da je gen zaista uključen za delovanje "Prozaca" u delovima koji proizvode serotonin, što smo svakako već znali, ali sada možemo analizirati sve. Sada možemo da analiziramo delove mozga koje niko pre nas nije analizirao, možemo uočiti eksprimiranje tih gena. Interesantno je onoliko koliko neželjeni efekti mogu biti interesantni. Druga primena ovih podataka je u vežbama za pronalaženje šema, usled toga što je to jedinstveni potpis gena, možete na osnovu ovoga analizirati čitav genom i naći i druge proteine koji imaju sličan potpis. Ukoliko se bavite otkrivanjem novih aktivnih supstanci, onda možete da analizirate celu listu proteina koji genom nudi i možda pronađete bolje mete za lekove i usavršite lek.
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.
Verovatno su vam poznate studije koje se bave analizom čitavog genoma koje su dobro medijski propraćene, pa nalećete na izjave: "Naučnici su nedavno otkrili da je ovaj gen ili geni povezan sa osobinom X." Naučnici rutinski objavljuju studije ovog tipa i one su odlične. Analiziraju velike populacije ljudi. Analiziraju čitave genome, i pokušavaju da dođu do ključne osobine koja je uzročno povezana sa genima. Ovakvim vežbicama dolazite samo do liste gena. To vam govori o "šta", ali vam ne kaže ništa o "gde". Tako da je veoma važno za ove istraživače da smo stvorili ovu bazu podataka. Sada mogu uz pomoć baze podataka i da razumeju aktivnost gena. Mogu se baviti istraživanjem zajedničkih mehanizama, i drugih fenomena koje prosto ranije nisu mogli da rade.
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.
Smatram da publika ovde shvata važnost posebnosti. Smatram da svaki čovek, svi imamo drukčiju genetičku pozadinu, svi smo živeli drukčije živote. Ali činjenica je da su naši genomi međusobno više od 99 odsto slični. Na genetičkom nivou mi smo slični. Pronašli smo da smo čak i na nivou biohemijskih procesa u mozgu veoma slični. Vidimo ovde da sličnost nije 99 odsto, već postoji oko 90 odsto sličnosti kada postavite razumne parametre i time je sve u ovom oblaku delimično povezano. Potom pronađemo neke izuzetke, ono što se nalazi izvan ovog oblaka. Ovi geni su interesantni, ali imaju blage efekte. Mislim da je najznačajnija poruka koju treba da ponesete sa ovog predavanja ta da iako slavimo razlike među nama, mi smo veoma slični, čak i na nivou mozga.
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.
Kako izgledaju te razlike? Ovo je primer studije koja prati i nadovezuje se na priču gde smo tačno odredili te razlike -- razlike su veoma suptilne. Ovo su primeri gena koji su eksprimirani u određenom tipu ćelija. Ova dva gena su zaista dobri primeri. Jedan je nazvan RELN -- bitan je za rano razviće. A DISC1 je gen koji je mutiran u šizofreniji. Ovo nisu šizofreni ljudi, ali pokazuju određeni stepen varijabilnosti u populaciji. Ovde možete videti donora broj jedan i broj četiri, koji se razlikuju u odnosu na ostala dva, jer su geni eksprimirani u veoma određenoj grupi ćelija. Ovaj tamno ljubičasti talog u ćeliji nam govori da je gen eksprimiran. Ne znamo da li je to uslovljeno razlikama u ličnoj genetičkoj pozadini ili je uslovljeno iskustvom. Ovakav tip studija zahteva analizu znatno većih populacija.
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.
Završiću izlaganje komentarom o složenosti mozga i tome koliko još treba naučimo. Smatram da su ovakve baze podataka neopisivo korisne. Pružaju istraživačima smernice u kom pravcu treba da razmišljaju. Analizirali smo mali broj osoba do sada. Sigurno ćemo analizirati više ljudi. Završiću komentarom da sada imamo oruđe, a ovo je zaista neistraženi, neotkriveni kontinent. Ovo je, moglo bi se reći, naš novi horizont. One koji nisu obeshrabreni, već očarani složenošću mozga, čeka budućnost.
Thanks.
Hvala.
(Applause)
(aplauz)