My name is Daniel Colon-Ramos, I am an assistant
professor at Yale University and my lab is interested
in understanding how the architecture of structures
like the brain forms. And I spend most of my time thinking about
these questions, but today I wanted to do something a little bit
different. It actually doesn't have to do directly with research,
but I wanted to use the brain and you know, some general
musings, to basically to think about what can we learn
about the brain with regards to how we learn, how we generate
knowledge, and also how science works. So what I'm going to be doing
today, I'm going to jump into different topics. And again, this is not
a science talk, it's more like a general thought talk.
But I'm going to illustrate how we think about science and
through collaborations, through creating networks of knowledge,
we basically, as scientists, generate new knowledge. And in that,
I'm going to illustrate the importance of cooperativity and the importance
of collaboration, which is a topic that's seldom discussed
in the sciences. But is essential for creating new knowledge
and for furthering the sciences, in general.
So, the brain is made out of cells that are called neurons.
And there are more neurons in a single human brain
than there are stars in the whole Milky Way. So there are about
a hundred billion neurons. So if there are some out there that are
watching this talk, next time that you are sitting down and looking at
the sky, think that there are more neurons in your brain than there
are stars you are seeing in the skies. And basically, there are a lot
of them. And they connect in a very specific way. And they actually
underlay human behaviors, they underlay the capacity to communicate
for you to understand the stock, and the organization is critical in that
aspect. So we're interested in this question, in how we
said that the architecture of the brain develops. And my lab
in particular, pursues this question by using the nematode, C elegans,
as a model organism. C. elegans is a tiny, tiny worm. It's about the size
of a comma in a sentence. So some of you might be asking me, how
is it that you can claim that you understand how the human brain,
which is so complex, works by looking at such a tiny worm?
And I want to explain a little bit how we do that, because
this is actually how -- the way that we do it, and the way that
other colleagues in the field that use C. elegans or use other
model organisms do it, actually highlights how science is done and how
knowledge is generated. So, C. elegans as I mentioned is really
small. And the reason that we use it is because scientists have
created tools that allow us to examine questions that will otherwise
be very, very complicated to examine. Questions like how is it that
you deconstruct the architecture of a structure like the brain.
And in particular, we use C. elegans because it's the only animal
for which we know the wiring diagram of the whole nervous system.
So, somebody sat down and mapped out all of the neurons, all of the
cells that form part of the nervous system, and so we know who they're
connecting to, where they're positioned, and for many of them,
we know what behaviors they're important for. And all that knowledge
is actually very important, because we use that knowledge
to generate and create new knowledge. So why is that knowledge
important? And the reason that that knowledge is important is
because of evolution. So it's thanks to evolution that a lot of
the concepts that we find in, for example, C. elegans, they're actually
applicable to other organisms, to other animals, including ourselves.
And so much so, that in the past 10 years, 6 Nobel prizes
have been awarded to people working in C. elegans that have
made fundamental discoveries in C. elegans, which were then
widely applicable to other systems, which furthered our general
knowledge of how biology works. And they were recognized with
Nobel prizes. But the important part beyond the prize is that
because of evolution, we can use model organisms, be it
C. elegans or yeast or flies or mice, to be able to generate fundamental
knowledge that then can benefit humanity. So, that knowledge has
told us something fundamental, very important, about how the nervous
system works. Be it C. elegans or our own brains, neurons connect
to each other and cooperate to form networks. And that cooperativity
between these individual cells is what basically underlies the
power of the nervous system, the power of our own brains.
So neuron isolation is not that powerful, but in combination with
other neurons, it's capable of creating all these circuits which then
are capable of doing amazing things, like creating a concept of
reality and allowing communication. So, but one important aspect
is that the number of neurons is important, but what is more critical
than the number of the neurons is how they're organized.
So, much like having a bunch of cables does not make a computer,
having a bunch of neurons that are disorganized does not make
a nervous system. They have to be organized in a particular
way. And again, I want to bring as an example, C. elegans.
C. elegans only has 302 neurons, so that's far fewer neurons
than 100 billion neurons that you find in a single human brain.
But those 302 neurons are organized in such a way that allows
the animal to create a representation of its world to find mates,
to avoid predators, to find food. And that's what we're interested
in. We're interested in understanding how is it that those neurons
get organized, and how that organization then underlies the behavior
of the nematode. The human brain is obviously organized in a different
way, because we don't have the same pressures. The same evolutionary
pressures or the same needs as C. elegans. So we are -- our brains
are wired in a different way than the C. elegans brain, thankfully.
And one critical aspect of our brain, which is fascinating, at least to me,
is that our brains are actually wired to be wired. And what I mean
by that is that when C. elegans are born, or when reptiles are born,
they know what to do. It's almost like their behaviors are wired
and they know where to go. But when we're born, a new baby is born,
it's actually -- it looks like what Aristotle used to call a tabula rasa.
It looks like the mind is empty. It's not really empty, it's wired to achieve
something very important. And that something very important is to connect
to other humans, and to learn from other humans. That's what we
are connected to. And that capacity of our brain to connect to
other people, to be able to learn from others, to be able to
build on knowledge that was generated by others before us,
is fundamental for the sciences. So, knowledge to a certain extent,
can be considered a network of networks. Because our brain is
a network, and the knowledge that we're generating by connecting our
brains to other people is a network of networks. So, let me give you
an example of how this works in the real science world.
So, I became interested in understanding how the nervous system
of the nematode develops in embryos. But I didn't have the tools to
be able to do that, so I collaborated -- I linked my brain to
other experts that had tools that were very beneficial to my
research, and my research was beneficial to theirs.
One of them is Zhirong Bao, who is at Sloan Kettering.
He's a computer scientist turned developmental biologist.
And he developed a computer that he trained to be able to
observe, basically here you have a nematode embryo, where the nuclei
in the cells, the center of the cells, are labeled in green. And the computer
is going to basically visualize this embryo as it's developing
and it's going to keep track of every single cell, and the lineage
of every cell. So at any given time, the computer -- because we
for C. elegans, we know the lineage of every single cell, it knows
what each cell is and what it's going to become. So, you have this
tool on one hand, and on the other hand, we also collaborated,
Zhirong and I, with another scientist, he's a microscopist at the
NIH called Hari Shroff. And Hari developed a microscope that was much more
powerful than any microscope that existed at the time.
And allowed us to image the embryo continuously and seamlessly
for long periods of time without damaging the embryo. That work was
very important, and in combination with these computer tools,
allowed us to do things that we couldn't do before. So here's the
microscope at work, looking also at the development of this
embryo, but you can see it's happening much faster because
this microscope that Hari developed is 30 times faster than the
microscopes that we had before. So that all of a sudden, by linking
our brains, we were able to do more than we could have each
done individually. And this is actually very important because this
is how science is done at all levels, even if you were claiming
to be a scientist and work completely alone, you're actually
-- you're receiving knowledge from other colleagues that are
actually colleagues who could be contemporaries, or it could
be colleagues that passed away, that generated knowledge before
you came along, and you're building on that knowledge. So
in that sense, science is actually a network of networks, and it's
a community where we're continuously building on other people's
knowledge. And in our case here, we were able to then link
what Zhirong was doing, what I was doing, and what Hari was
doing, to then generate videos like the one that I'm showing you
here, of an embryo that is developing in real time, and you can see
the neurons in green, the nuclei in red. And all of a sudden,
when this embryo starts moving, you can see that we can actually
keep track of the individual cells because the microscope that Hari
developed is so efficient and so fast, and we can observe neural
developmental events that were previously inaccessible.
And in that way, answer questions that we couldn't answer
before. So I hope that with these examples, I have illustrated
to you a little bit how science works, how collaborations work,
the importance of collaborations in sciences, which is
fundamental but seldom discussed. And if you're interested
in these topics and you want to hear more, I invite you to
do a Google search of my last name with "ted blog,"
I have a blog on this topic, and I also have a Ted-x talk
that discusses in more depth, the importance of basic
research in biomedicine. Thank you.