For centuries, doctors and scientists have
tried to unlock the mysteries of the human brain. How is it organized? Which areas control different mental functions,
and how is it all wired together to generate our subjective psychological experience? For the past 100 years, neuroscientists have
approached the brain like map-makers, charting its features and activities within well-defined
boundaries. The prefrontal cortex is celebrated as the
seat of rationality. The motor cortex plans and coordinates movement. The somatosensory cortex and parietal lobes
control our perception of the physical world. The temporal lobes process memories, language,
and emotion. The occipital lobe processes and integrates
visual information. And the cerebellum helps execute our body’s
motor commands. Scientists have looked at the brain through
the lens of our beliefs about what it means to be human. So when we're looking at parts of the brain,
trying to figure out what they do, scientists are usually using their beliefs about what
makes a human mind, and some of those ideas you can trace all the way back to Plato. Recent studies of traditional categories of
cognitive brain functions, like memory, show surprising amounts of activity that overlap
different parts of the brain – so much that the simple map and its strict categories lose
their meaning. The way that we've been conceptualizing the
mind doesn't map very well at all to the functions of different systems in the brain. These kinds of distinctions are very subjective
and it's probably better to try to look at the brain and figure out what its organizational
properties are without appealing to these culturally ladened categories, which aren't
respected by the brain. Russell Poldrack is doing just that. At his lab at Stanford University, he’s
taking a computational approach to understanding the organizing features of our mind. If you have people perform a bunch of different
psychological tasks that vary in the psychological functions that we think they engage, let's
collect a bunch of data on a bunch of different tasks and ask the data what kind of structure
there is. Poldrack's lab used machine learning to try
to isolate neural activity related to memory recall. But rather than simply mapping into memory
centers, the data correlated with more general constructs of activity — ones for which
we don't yet have names. What that has shown us in some cases is that
things that we might've thought were measuring the same thing really don't seem to be measuring
the same thing at all. I think we need to fundamentally rethink how
we conceptualize the functions of the brain. Within neuroscience, there's a broad agreement
that the brain is a computational machine and we need to understand
what the computations are that it's doing, and that we should be able to ultimately understand
psychological function in terms of those computations. Part of the challenge is that we don’t have
a great language for describing those computations other than math. So it raises essentially a question of whether
we're going to end up with models of the brain that are really good at predicting the activity
of the brain, but that we can't sort of give human understandable explanations to. Deep in the jungles of Southeast Asia lives
the world’s strangest flower. This is Rafflesia arnoldii. It’s affectionately known as the “corpse
flower” because it smells like rotting meat to attract pollinating flies. It’s the largest flower in the world, with
the size and weight of a small child. But the weirdness doesn’t end there. Rafflesia is not just a flower—it’s a
parasite. They require part or all of their nutrients
and water from another plant. As a result, we often find alien genetic material
in the genome of a parasitic plant—many times from the host. One of the hypotheses is that parasitic plants
steal from the host as a weapon to make them a better parasite. Liming Cai is the latest of a long line of
biologists to attempt to sequence Rafflesia’s notoriously unwieldy genome. Biologists struggled because the Rafflesia
genome features highly repetitive elements called transposons, known as jumping genes
for their ability to cut and paste themselves at repeating intervals. Most organisms silence these elements, but
Rafflesia is not most organisms. These highly repeated elements [are] causing
a lot of problems for a scientist trying to assemble genomes because it's basically like
putting a jigsaw puzzle, but every piece is identical. This year, with the help of a bioinformatics
team, Cai successfully created a draft genome for a species of Rafflesia. Her findings were even more shocking than
biologists had expected. There are a couple of things going on here
that really sort of blew my mind in the first place and really make us rethink what defines
a plant. So all plants have a similar set of genes. In Rafflesia, what we found is that it has
lost nearly half of the conserved plant genes, which is really a record-breaking finding. Cai also found that 90% of Rafflesia’s genome
consists of repeating DNA, like transposons. That’s highly unusual. No one knows why, but the answer may transform
our understanding of parasite genomics. With the advances of genome sequencing technology,
we can explore all the weird branches of the tree of life—how rules can be bent by all
sorts of really creative strategies. Life is really diverse and nature often surprises. In the early 20th century, sleep became a
popular topic for researchers. The weapon of choice was the newly invented
electroencephalograph, or EEG, a machine measuring electrical activity in the brain. This approach produced many insights, but
it also set up a bias in the studies: that sleep is a neurological phenomenon, and its
purpose and structure is located in the brain. Everybody has thought that sleep is of the
brain, by the brain, for the brain. This is a famous quote by Alan Hobson, who's
a brilliant sleep scientist that made some huge contributions to the field. But it really overlooks the fact that, in
fact, we're not brains. We’re organisms, we’re integrated. Everything we do is integrated with everything
else. The first cracks in this brain-centric view
started to show when the Swiss scientist Irene Tobler noticed that cockroaches sleep. Since then, we’ve learned that simpler creatures,
with less and less brain, also sleep. And recently, a new discovery has changed
the narrative entirely. This is a hydra. It’s one of the simplest forms of animal
life. Instead of a brain, hydras have nerve nets,
the most basic nervous systems in nature. This year, a group of Japanese scientists
demonstrated that hydras sleep. These tiny fresh-water organisms are living
proof that sleep evolved before brains. But if sleep didn’t evolve in and for the
brain, what is it for? More and more scientists are really looking
in peripheral tissues and asking how the body can impact the brain and how the brain can
impact the body specifically with respect to sleep regulation. In my lab, the current hypothesis is that
there are some situations that the brain can't fix itself. And in association with whatever damage has
taken place, sleep can lower the activation energy to have these circuits begin to find
that solution. So the idea then is that when you're asleep,
you're using less energy, but the energy that you are using, you're using in a different
way that you're supporting functions that you would not be able to otherwise support
if you were awake. The research on hydras is the latest in a
growing body of evidence that sleep first evolved to help regulate metabolism and enhance
repair, and only later took on brain-related functions. I really do believe that sleep and metabolism
are intertwined. So that's going to be the future.
