On Beyond: Our Social Brain and Autism Informal Computer Education Tracking Water

On Beyond: Our Social Brain and Autism Informal Computer Education Tracking Water

(swoosh, typing, and click) (upbeat music) – [Narrator] UC San Diego students learn how to teach computer
science to youngsters, how the chemistry of water
reveals it’s history. But first, is the potential
for conditions like autism a part of the human minds
extraordinary capacity for intellect and social cognition? All on this edition of On Beyond. (upbeat guitar music) (wasps buzzing) All animals need to know and
communicate with their own. So evolution has developed in every brain the ways we all recognize and
socialize with each other. But while other brains are social, no other brain is as social or can do what the human brain can. And it also seems that no other brain can experience conditions like autism. Are these two fates somehow intertwined? Alysson Muotri’s lab at the Sanford Consortium
for Regenerative Medicine is using brain organoids
to unravel this mystery. And with the help of an understanding of our evolutionary cousins, new insights are emerging. – A focus of our lab is autism. Conditions which make it
difficult or impossible for individuals to communicate and make emotional connections. There are many complex aspects to these different conditions. But they all share one things in common. Their roots are in the cerebral cortex. This thin outer layer of neurons that fire trillion of times
per second in our brains to understand and respond
to the world around us. Without this complexity, where do we start
looking for abnormalities that cause these conditions? Katerina Semendeferi’s work
in comparative neuroanatomy helps to guide us. She share what she has discovered about what makes brains social. And how that could be a source
of conditions like autism. – Humans have a brain that’s
about three times larger than that of the great
apes, our closest relatives. And that’s a huge difference. So in terms of absolute volume and absolute numbers of neurons, the brain is much much larger. So the questions is, are these larger brains that humans have just larger versions of
a smaller primate brain? And we now know that that is not the case. So humans are three times larger
than the brains of the apes but at the same time they
have also been reorganized. So it’s not like your taking
a brain of a chimpanzee and you zoom it up to three times and you get the human brain. That’s not what’s going on. The challenge is to see what exactly is it in that larger human
brain that has changed. Either differentially enlarged as a whole or differentially enlarged in
terms of specific parameters. For example it can be
the size of the neurons or the numbers of the neurons or the way the cortex and
the gray matter is organized. We have known for a long time now that the larger the brain gets, of course the more neurons it has, but the density of the neurons go down. And what does that mean? Well, when the brain gets bigger, connectivity gets even bigger. So larger brains have more neurons but they have even more connections. And that special connectivity
between specific structures is it what allows for social behavior for example to take place. So often we view the brain from the perspective of the cortex. We’re very corticocentric in a way. In reality the cortex is
selectively interconnected with other structures. And one very important
one for the social brain is the amygdala. And it sits in the very frontal
part of the temporal lobe. Amygdala is known now to
modulate and categorize stimuli. And then also allow the individual to process that information and then be in a position to
transfer emotional stimuli. It has a lot to do also
with fear or lack of fear. Our ability or inability
to process the intentions of people who surround us and it’s a critical part
of the social brain. In the amygdala of humans,
when compared to great apes, there are a lot of
things that have changed. Specifically with the lateral
nucleus of the amygdala. The lateral nucleus is a
gateway to the amygdala from the cortex. And it connects to the prefrontal cortex. We know that the frontal cortex is actually of critical importance when it comes to complex
social behaviors in humans to social behaviors and
to pretty much everything that we define as characteristic
of our own species. And it just so happens that at that area seems to also be a hotspot when it comes to
neurodevelopmental disorders like autism and Williams syndrome because it is heavily affected. So in the case of autism, one of the things that we have observed is that the neurons, the numbers and the density in the
frontal cortex goes way up. The dendritic trees are collapsed. The neurons are closer to each other and the connectivity is affected specifically in areas that have to do with social interactions. In the case of autism, we have an avoidance
of social interaction, and avoidance of eye gazing. In Williams syndrome we have the opposite. We have areas in there
with the frontal cortex that seem to have lower density
of neurons, fewer neurons. The way that the neurons are organized allows for more
connectivity in those areas that are involved in social cognition. So we have more branching. We have larger neurons. We have more opportunities
for receiving stimuli. In specific, those areas of the brain that do social brain kinds of things. Williams syndrome individuals
are eager to come close, are eager to get to know strangers, have no fear of approaching people. Their language is extremely expressive and full of emotions. In addition to the frontal
cortex, the amygdala. In amygdala we have this
very interesting phenomenon where the lateral nucleus
in Williams is bigger and in autism is smaller. Two very different aspects of behavior. And interestingly enough, we have the same areas
in the brain affected in the two syndromes in
different directions, in opposite directions. In Williams we have the deletion of genes in chromosome 7. That makes it an ideal opportunity for scientists to look and
try to find associations between the deletion of these genes and compromises or changes
in the brain structure. Because it’s a very
specific small set of genes. In the case of autism, in many cases what we have
is duplication of genes. And it is clear that we have
two different mechanisms. Deletion on one hand,
duplication on the other that may be leading to
alterations in the neural systems that end up either
compromising or overextending the social capabilities of humans. Some of those same genes
may be also be involved in how the human brain got so
much bigger in human evolution and thus made our brain much
more susceptible probably to disorders like autism
or Williams syndrome. What this line of work with
the human tissue can give us is the full description of
how a typical human brain or in a typical human brain looks like. It is very important to be able to compare the kinds of information we get directly. How is it that this
cortical layers look like? What kinds of neurons
do we have in one layer as opposed to another? How many and what is the
density of the neurons in the frontal cortex? The power of what the cortical
orgonite can do for science is to modify the parameters to create different kinds of pathways using different genetic mechanisms by altering the typical cell migration, the typical duplication. By really controlling parameters to see which way we get into
a typically looking brain as opposed to in an atypical one. And what kind of in an atypical one. How is it that we got
from point A to point B? So putting the two lines of work together is very powerful I think. It is certainly our hope
that the discoveries that will come from
techniques like the stem cells and these cortical organoids will lead to early interventions to help our fellow humans
who have these disorders. – Brain organoids like these
are a unique and powerful tool to understand autism. In Katerina’s work, comparing the organization
and the structure of the brain has help us focus on where
to look for abnormalities. But, we also wanna know where the genetics of our highly social brain originated. And if, those genetics carry
the vulnerability for autism. This will tell us more
about the causes of autism. To do that, we are taking
a page from Katerina’s book and making a comparison of brain anatomy. By comparing our brain with that of our closest
evolutionary relative, the neanderthals. And only brain organoids
can help us do that. (rhythmic flute music) (lighthearted ethereal music) – [Narrator] UC San Diego’s Department of Computer
Science and Engineering recently introduced
teaching computer science in informal space. The first quarter of this innovative class was taught by Sarah Guthals, UC San Diego computer science alumna and co-founder of the computer
learning venture ThoughtSTEM. We caught up with Sarah to learn
more about the motivations, intent and results of the
course on both the students and the community the class reaches. – California in general is heading towards creating K-12 standards so that every kid in a K-12
public school in California will take computer science. But we don’t have enough
teachers to do it. Until that happens, we decided
that the best thing to do was to bring computer science
undergrads here at UCSD and give them some formal training in computer science education, specifically when their
not the full-time teacher. So that’s really where the
informal part comes in. Informal space just means
you’re not in a K-12 or a university classroom and with exams and standards and certain things you’re trying to meet. So whether it’s in the
classroom or at a library, it’s more about inspiring kids to just get excited about learning more. So we have about 30 students who are all juniors and
seniors in the course. And the course is really broken
up into three main projects. The first project is the
majority of the course where your going to learn
how to design an effective lesson plan for teaching
using an existing software. And so we do a lot of analysis
of things like Scratch and Alice and App Inventor. And we analyze not only the technology, but also how people teach with it. Then they build their own lesson plan and actually execute it
out in the community. The second project is a paper prototype. Now you’re gonna design a
new experience that someone, whether they’re a kid or an adult, could engage in and learn computer science for the first time. And then the final project
is an actual coding project where they learn how to
build a very basic animation with block-based programming language. Those blocks change a little
character on the screen. From the kids perspective
it says, “make bunny hop.” What my students are doing is actually writing the code behind it to translate that into a bunny actually hopping on the screen. Whether you’re going to grad school, or you’re going you know,
to start your own company, hacking together an experience like that can be really powerful. So I wanna make sure
they have those skills. In general though, what they can walk away with is having an understanding of
analyzing a different population of who you’re building an experience for. So, a lesson plan around teaching coding is still building a technical experience for a certain population, kids in this instance. And whether they’re building that, or they’re building the
next, you know, iPhone app, they need to understand how
to analyze that population. What are the constraints
of the technology? What can they promise? And what can the actually build? And then do so effectively. And that’s what we really
focus on in this course. – [Narrator] After weeks
of study and preparation, groups went to schools and
libraries throughout San Diego. We followed one group to a
Saturday morning workshop at a local library. – Our teaching project was focused on kids ages 7 to 12. They’re still excited about
like small little games in animations so that’s why we targeted that age range. We were really trying to teach the kids that it could be fun to code. So what we were using for
our project was Scratch. And it’s this online
browser-based platform that allows kids to build like
simple animations in games. Basically you’d click and drag blocks into the coding environment. – We basically just
wanted to introduce them to the kind of reasoning that you need to be a computer scientist which is logical reasoning. – It helps instill like a
very logical way of thinking for the kids. And teach them some of the
core concepts like “for loops” and “If I’ll” statements. You know it introduces
the concepts of variables. It helps them get into the right mindset before they go into
text-based programming. ‘Cause as I found out, kids
are not very good at typing (laughs) especially at that young a age. And so it’s a lot easier
to just click and drag and then just type a couple of things in than having to worry about syntax. So I think it’s a great tool
for kinds to learn how to code. – More than any technical knowledge, the most important thing that the students could walk away with is the
knowledge that it’s exciting, computer science is exciting. And that there’s fun
things that they know about and they understand on their
level that they can make that they might not have felt
empowered to make before. So, we have an activity where
we’re not using the computer and an activity where using the computer. And the activity when we’re
not using the computer was kinda to get students to just generally understand
the idea of what computers do and how computers take instructions and use those instructions to
do things that humans want. So students paired up. One student would get
a page full of drawings and the other student
would get a grid paper. Hence the student with the drawings would try to get the
student with the grid paper to draw the drawings without
actually seeing them. And the idea is that the
student with the drawings has to communicate exactly what they want the student
with the grid paper to draw. Which is exactly what computers do. So the person with the
pictures is like a programmer and the person with the grid
paper is like the computer who has to execute the instructions. The other activity that we did was to get students to understand
the concept of debugging, which is fixing programs that don’t work. – One of the first things that we learned as computer science majors
was how to fix things. That’s something that you
spend so much time doing as a software engineer. – We gave them program we already made, we showed them how it worked and then we gave them a broken
version of that program. And guided them through the different ways that they could fix it. – [Sarah Yao] It’s kinda
like detective work, they have to figure out what the bug is. And also, you know, understanding
that people make mistakes, but you can fix it. You can figure it out and be like, “Okay, this is what happened, “and now we have to do this
to make it work again.” – It’s very important that
students know for a fact that everyone in computer
science is making just as many if not more mistakes as they are. It’s something you have to get used to and comfortable with so that you can actually learn and grow. – For me, when I did that as a CS major, it was super rewarding when I finally had the finished
product that was working. So I wanted the kids to be able to have that same experience. I think the fact that all the kids were able to work through the bugs and have a working program at
the end was a huge success. – That worked out nicely because
we were able to teach them computer science concepts, like conditional statements and such without them even realizing
that they were learning. – So many of the students walked
away happy and like excited about them. They were making things that
we hadn’t imagined they could. – The biggest success is
giving them confidence enough to try it on their own. – They all had smiles
going out saying like, “I just made my first game.” And seeing they can do it. – [Narrator] The rewards
of smiles and knowledge shared during the workshop are precious. But more valuable are the takeaways that will serve students
well beyond this experience. – One of the most interesting things that I’ve taken away from it is, target audience is really important. That you can tailor your
lesson to your target audience in a very specific and useful way and really get them to engage substantially more than
they would have otherwise. An example being, one
demographic uses mobile phones more than the other. So when you target your
lesson for mobile phones, they really engage a lot ’cause they understand how to use it, they understand the visual
language and everything so the importance of
targeting your lessons and the power of that is
one of the big takeaways. – I’m not actually going to be going into software engineering, I’m going to be going
into technical sales. And so I will have to
actually be talking to people, teaching people things
about new technology. And sometimes those
people will be technical, sometimes those people will
have no technical background. And so, I would say probably
the most interesting thing that I’ve learned is
teaching people in general, like going through the
whole process of learning how to consider all of
these different factors definitely is going to
help me in the future. – It’s a course that will teach you things that you’ve never learned before in any other computer science class. Hard skills are important but if you want to be a leader, it is critical that you are emotionally, socially, culturally intelligent. And this course gives you the opportunity to practice those things. – That was really one of the
important foundational pieces to this course. It’s not just coding. There are people involved, and there are people
that you’re building for. There are people you need to
sell to in terms of investments or your ideas to get a go ahead. And all of that stuff really matters if you wanna make good software. That’s why Google and Microsoft and Amazon heavily recruit from UCSD. Because they know that you know what effective technical
communication looks like. – [Narrator] While building
the tools of success in its students, teaching computer
science in informal space has also created the promise
of sharing these tools with the community. – [Sarah] One thing that
came out of this course that I’m very excited about is that we started a student
org where the UCSD students are gonna continue to go out
into the community and teach. – We decided to start
a student organization that will focus on outreach
called “CS Foreach” – CS Foreach is dedicated
in the short term to getting the USCD students
out into the community to actually teach novices how to program. – [Nadah] We have two primary goals. We’re working on establishing
a semester long program with two high schools in the district. – The long term goals include actually contributing to novice
programming tools like Scratch and App Inventor. And potentially even building our own, so USCD kind of gets on the map in terms of computer science
education contributions. – So I think just
everything that UCSD does around the community and the things that UCSD does in the computer science department around supporting students
outside of just coding has set us up to succeed. (upbeat rhythmic music) (rhythmic flute music) – [Katie Markovich] The main
method of my dissertation is to try to get at
this question which is, “Where’s the water gonna
go in the mountains “with climate change? “Where’s the water gonna
go without the snow?” (distant bleeping) – [Narrator] Whether in
Chile or in California, hydrologist Katie Markovich
is looking for ways to understand water
resources and climate change. – [Katie] The thing that
is tricky for California is that we have that Mediterranean climate so all of the water is falling in the course of a couple of
months in the winter season. So, what we used to have was the snowpack which was basically an
intermediate reservoir which holds that water. Until late spring, early summer
when it starts to melt out which is very convenient for us because we’re able to store
enough water in the reservoirs for the winter which serve for
water supply, flood control and hydropower. So, for climate change,
what that means is that, we essentially just have a longer drought. Because that rain is gonna
fall at the same time. And it’s gonna fall as rain and not snow. It is a challenge for California because right now we’re not set up for that type of a climate system. – [Narrator] Less snow and more rain as most climate projections predict, is a challenge for our
California infrastructure. Chile, like California,
faces climate driven shifts in the proportions of snow, rain and groundwater availability. Dr. Markovich’s team went
in search of water sources in the Diguillin river
east of Concepción, Chile. – [Katie] So the team snow
survey was Lauren Foster who is a PHD candidate,
Colorado School of Mines working with Reed Maxwell, Stephen Maples who works here at UC Davis with Graham Fogg and then myself. So, Steve came to help me out when I had to go and
sample this sort of really, really far and potentially dangerous site. – [Stephen] I was the
resident avalanche safety sorta point person going down there so that was my role was to kind keep an eye out
on the avalanche conditions and backcountry travel
and things like that. – [Katie] The end goal is to build a model to be able to project what’s gonna happen when the snow melts too soon or the precipitation falls as rain. In order to to do that, you need to use these big, you know, integrated hydrologic models. So it’s not just groundwater
that I’m simulating, I’m simulating surface water
and I’m stimulating vegetation and then you know, climate that’s acting as basically like the
driving forces of the model. – The really challenging
scientific questions are happening at the
interfaces between disciplines. So there’s a lot of interaction between the hydrologic science community and the climate science community. – [Katie] So that’s
what I’m doing in Chile, actually is to try to get
at these signatures of water so the snow signature and then the spring snowmelt signature because that’s gonna be slightly
different from the snow. In the summertime because they also have a Mediterranean climate, we can assume that pretty
much any of the water that’s in the rivers is
coming from groundwater and so that’s gonna help me get at that groundwater signature. So once I have those, I’ll be able to do that
sort of inverse calculation of stream flow in the river in my system to show how, you know,
through proportions of water coming from snow versus
groundwater shift over time. And then compare that to a model. – [Narrator] This will help water managers and land loose planners in Chile consider their water portfolio as they invest in infrastructure. For California, much of the
large infrastructure projects have already been built. But Chile has a chance to plan
with climate change in mind. (whooshing water) – And especially in the mountains, there’s just not a lot of data. It’s just really hard to
access a lot of these regions. So that was what we were
doing this past summer which was winter down there, was digging snow pits
and taking snow cores. So, snow pits are really
fun as it turns out. You basically just dig a
pit and you make a wall and you just sample with depth, you know, 10 centimeters at a time. And with that you’re able to
get the changes in density of the snowpack with depth, which is important for determining
the actual water content of the snow. And you’re also taking
samples of each of those to get at the isotopic
signature with depth. And so, that ultimately is
kind of like a depth for time. Because we know that these events are deposited sequentially. And because I can’t collect
every single snow event while I’m down there, you can sample that and sort
of infer how that signature might change as the season progresses. – [Narrator] Though the
chemical properties of an atom are determined by the number of protons, each element is also
sub-classed into isotopes by variations in the number of neutrons. All oxygen has eight protons, and usually eight neutrons. Detectable by specialized lab equipment, Oxygen-18 has ten neutrons,
making it heavier. – A signature is basically, I’m referring to the
stable isotopic signature. So water is made of
hydrogen and oxygen atoms and so when I say a signature I mean that unique combination of light isotope to heavy isotope of oxygen or of hydrogen. A signature will be different
in space and in time, always. Even in the same stream, you
can go upstream and downstream and that signature is gonna vary. And you can take the ratio of
the slightly heavier oxygen against the lighter one. And with that, be able to
track signatures of water. So we know that rain is
gonna be a little bit lighter because it’s the stuff that evaporates off and the lighter one’s
gonna evaporate off sooner. And then we know as that rain travels across the land surface, it’s also gonna get increasingly lighter ’cause the heavier stuff
is gonna rain out first. And then when you get up the snow, that signature is super
depleted as we call. It’s basically gonna be a
really really light signature. So, with these techniques, we’re able to then take
a sample of river water and back calculate what
proportion of that came from snow and what proportion of
that came from groundwater. – [Stephen] I think California
can provide a lotta guidance for what to do and
especially what not to do for other places that are
starting to experience some issues in terms of water
supply, water reliability and things like that. As the human footprint
on water grows worldwide, I think a lotta places
can look to California for the sorts of do’s and don’ts – My work is going to
inform UC Water’s goals of connecting all of
these stores of water, you know, the snowpack
in mountain groundwater and the front range, all the way to the Central Valley aquifers and irrigated agriculture. I just really love that I can
contribute in that small way to the growing awareness
of climate change. (lighthearted music) (upbeat music)

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5 thoughts on “On Beyond: Our Social Brain and Autism Informal Computer Education Tracking Water”

  • Refusing to expose the brain swelling CAUSED and claimed on the incert packaging of all BANKZines is the OPPORTUNITIES for more authoritative fakers.

  • Now for the ambitious ones in the science community to define the perfect "cognitively neuro-typical" human being? Much like the recent creation of the silicon crystal ball equaling exactly one kilogram. So, how do we judge the precise baseline of "normality" and what individuals or groups get to define it with enough precision that the odds of unforeseen mistakes or harms are near zero? My guess is that it can't be done. Applying an ever expanding vocabulary of elitist clinical terminology such as ADHD or Autism among many others is more of a way to place humans who are otherwise doing no harm into unaccountable boxes and inaccessible folders for the assumed "neuro-typical" professionals to examine at will. Simply to make decisions on behalf of those who are non-transparently placed into those boxes unbeknownst for the convenience of the "system". Until such time the medical community can show me a perfect one kilogram silicon crystal ball of human cognition, I'll remain a skeptic as to who is "normal" without question.