In this episode of SciTech Now, understanding the phenomenon of emergence; the evolution of octopus intelligence and understanding dementia in humans.
SciTech Now Episode 527
Coming up, solving the greatest unsolved mysteries of science.
Scientists have discovered that there are some emergent phenomena for which you can't predict that collective emergent behavior.
The evolution of cephalopod intelligence.
Cephalopods became intelligent to increase their chances to find and process food.
Fighting Alzheimer's with zombie cells.
Not only does this drug combination benefit Alzheimer's disease in our model, but it has been shown to benefit so many other health conditions that occur with aging.
It's all ahead.
Funding for this program is made possible by... ♪♪
Hello. I'm Hari Sreenivasan.
Welcome to our weekly program bringing you the latest breakthroughs in science, technology and innovation.
Let's get started.
Throughout nature, throngs of relatively simple elements can self-organize into behaviors that seem unexpectedly complex.
Scientists are beginning to understand why and how these phenomena emerge without a central organizing entity.
Take a look.
These ants are working in tandem to form a bridge.
Even though there's no leader giving orders, they all seem to know what to do.
Similarly, thousands of starlings fly in unison, creating complex formations in the sky.
Magnetic properties arise from the alignment of billions of electrons.
Intricate frost patterns crystallize on window panes.
Hurricanes form above churning oceans, and once clear highways suddenly get jammed with traffic.
These different systems all share something in common, Some sort of macro property or behavior arises spontaneously from many interacting micro parts.
It's a classic case of the whole being greater than the sum of its parts.
The behavior of each of those parts doesn't predict how they behave collectively.
Some of our greatest unsolved mysteries, like how life first began and how our brains give rise to consciousness, could be explained by this phenomenon, known as emergence.
How does complexity emerge from a simple starting point, and how do we even study that?
Let's look at the formation of a crystal lattice.
Think of molecules in a container.
At high temperatures, they'll bounce around independently in a fluid or gaseous state.
Poke them, and nothing happens to the system.
But lower the temperature, and they form a solid.
They crystallize, arranging themselves in a regular lattice, a balancing act between opposing forces maintains the distance between molecules.
Now poke them.
They'll try to restore the balance.
The key is the forces acting on the molecules don't change.
The drop in temperature added a new condition to the system.
The same rules created a different effect, and that's how the properties of the crystal lattice, like its rigidity, its elasticity and its long-range order emerge.
An abrupt change in the behavior of a physical system is something we typically think of as a phase transition.
In fact, that's how scientists often think about emergence in more complex systems.
Let's return to the bridge-building ants.
Like the molecules in the lattice, the ants as individuals obey the same behavioral rules no matter what they're doing.
They aren't trying to build structures, but when the ground drops away in front of the swarm, old rules about how close stay to their neighbors leads to the emergence of large-scale coordinated behavior.
Without that information about their neighbors, the bridge would break apart, just like how higher temperatures cause molecules to break from a solid lattice into a liquid state.
Emergence means that we can find hierarchies of new laws and structures that arise out of complexity at different scales.
Scientists are seeking to apply the framework of emergence to other areas of research, like how individual cells follow cues to move or transfer when organs are developing, or how groups of neurons fire together to help you make decisions.
Some researchers are even hoping to engineer such systems of their own to build robotic systems made up of small dumb parts that end up swarming together to perform useful tasks.
Perhaps this work can help us understand even deeper questions about the emergent nature of intelligence, consciousness and life itself.
Thomas Lin is the editor in chief of and the editor of two math and science books: 'The Prime Number Conspiracy,' and 'Alice and Bob Meet the Wall of Fire.'
He joins us now to discuss the unexplainable discoveries created by the emergence phenomenon.
What is the emergence phenomenon?
So if you think about science, throughout history, we've had amazing advances, and it's all really been done through this approach... this reductionist approach of taking something complicated and breaking it down into its simpler constituent parts, understanding those parts and then trying to understand more complicated interactions of those parts, right?
But more recently, in recent years, scientists have discovered that there are some emergent phenomena for which you can't necessarily predict that collective emergent behavior just by looking at the smaller individual parts.
Let me give you a couple of examples.
For example, there are big questions like consciousness, what is that?
Like, can we just look at individual neurons and what they're doing and figure out what consciousness is?
Or is it an emergent phenomenon where you have to study it at this other level where you can't ever add up what's happening in the neurons?
So just because we know that there's different parts of the brain doesn't necessarily mean that some of those parts doesn't lead to consciousness automatically.
We don't know exactly how that happens, and so another example is take a look at ants.
Individually, they don't know much.
There's not, like, a leader who is directing things, and yet ants, together, somehow can form bridges over gaps.
They can form rafts when they're in...
With their bodies.
...like, in water, with their bodies, and it's something that they do collectively, a spontaneous behavior that is in some ways intelligent, and it does something amazing, but that individual ants can't do, and you can't predict necessarily based on their individual behaviors, and so this is a way that scientists are now using to try to understand many different complicated states of... whether it's states of matter or of different phenomena that emerge in ways that can't be predicted by their individual parts.
How do we study something like emergence?
Yeah, that's a great question.
Basically, one of the ways that researchers think about emergence is through the lens of phase transition.
So another example of emergence is you have liquid water, and it's sort of free-flowing, and the water molecules are, you know, going where they want, and at a certain temperature, water freezes and takes on this more sort of crystal-like ordered structure, and it's not something that just gradually happens where, you know, you can tell what the individual water molecules are, you know, all trying to go the same way and then trying to create this more rigid crystal structure, but it just happens.
At the right temperature, there's this emergent behavior and a phase change into ice, and that's a similar thing that's happening when you look at ants, whether you look in other complex phenomena that seems to emerge out of simpler states.
So there is not a pattern in loose flowing water, but when it freezes, it does emerge... there emerges a pattern, right?
So if you can study that, you can study other types of emerging phenomena and see at what moment in the transition a pattern is emerging.
Right, and so there's many different kinds of phase transitions and many didn't kinds of of emergent behavior.
Another example is if you think about magnetism for example.
If you have electric charges that don't get oriented the same way, all of a sudden, you get magnetism.
And what can you do from learn from doing that or watching that phase transition?
How do kind of apply that to other fields of science or even just different phenomena?
One thing is to, again, to take the language of phase transitions from physics and apply it in many areas to understand how you get this shift because again, just studying these individual microscopic parts won't necessarily get you any closer to understanding the emergent phenomenon, and so that's one thing is they use the science of phase transitions.
Another is that in some ways, it just tells you that some things can't be studied or that you're not going to get very far by studying it in the old way, and you have to take a new approach and look at the emergent phenomena itself, and sometimes you want to study that at this sort of more macroscopic level.
This is what religions have been saying for a long time, you know?
The sum is greater than the parts.
That there is some sort of a collective consciousness, that the ants have a vibe where they know for their collective survival, they have to build a raft with their bodies, right?
But...Or in the speak of religion, that there is a God, and that it can't be studied just by looking at one part of this or one part of that.
Yeah, philosophically, I mean, it sort of leads to interesting questions, but, you know, the way I look at this is that it doesn't necessarily mean that there aren't... that things are no longer deterministic, right?
That these things that are happening at the individual level of particles and individual ants don't actually lead to the phenomenon in some deterministic way.
For example, researchers have found that the ants do follow simple algorithms, so the ants, for example, when they realize, 'Oh, I'm on top of another ant.
This is what I have to do now.'
Not what they have to do, but that's just what they do, and once they follow these algorithms, then that emergent behavior, this collective behavior, emerges, and so it's not necessarily that the smaller parts don't ultimately lead to this more complicated behavior.
It's that it may not be possible, though, to understand all the direct connections from one to the other.
So if we can figure out the algorithms of how ants behave when they're on top of one another, can we figure out how humans behave when we interact with each other on how we vote or don't vote or how we take collective actions that seem inspired by who know's what?
Yeah, I think, I mean I thinks one of the big questions, right?
Is that, in studying emergent behavior, you want to be able to understand how economics works, how people behave.
You want to understand other things, too, that may be fundamental to natural as well that right now we can't by breaking it down.
Our ability to take individual particles, for example, and exactly calculate how they interact, is pretty limited actually.
Once you even just get a few particles going, it gets super complicated super fast, and so this could be a very powerful way to understand things in a very scientific way, not getting into any kind of mysticism or anything like that.
But without necessarily relying on something that is just way too complex, and so emergent phenomena are everywhere.
Again, it could be the origins of like, very likely were an emergent phenomenon as well when you had individual molecules, and somehow things came together in a certain way, and consciousness, all these big questions.
This is a powerful way to think about it, and again, it's through the understanding of phase transitions that they're trying to take a scientific approach to this.
Thomas Lin Of thanks for joining us.
During June 2017, a team of NASA and university scientists conducted the Convective Processes Experiment, also known as CPEX.
Using a suite of instruments onboard NASA's DC-8 flying laboratory, scientists collected data on wind, temperature and humidity around the subtropical waters of Florida.
The campaign had two primary goals -- to better understand the growth and decay of convective clouds and to demonstrate wind measurement from space using a NASA wind LIDAR instrument called DAWN in anticipation of the European Space Agency's Aeolus satellite, which is due for launch in 2018.
One LIDAR is a laser beam.
It doesn't diverge like a radar beam, so it's very small illumination volume.
It's pointed downward in the case of the DC-8 here.
So we're profiling below the aircraft, and we achieve the wind measurements by looking at the winds from several different directions.
Each day during the campaign, the science team conducted weather briefings to determine if conditions were favorable for observing convective activity and where their potential target locations would be.
Once the team decided that weather conditions were right, a pre-flight briefing was held to go over the mission objectives and the flight path.
♪♪ The CPEX team flew a total of 16 science flights over the course of the campaign, ranging from 6 to 8 hours in duration.
In addition to LIDAR, radar and radiometer instruments, the team also used DropSens that collected data from inside the storm or storm system being studied.
Fire in the hole.
♪♪ Three, two, one, go.
This is called a DropSen, where you have a electronic weather station that falls ballistically from the plane.
So you drop it out, and it falls, and it transmits back its position based on its GPS, and so we got the wind speed and direction that way, and then it has very accurate sensors for temperature and humidity and pressure and a sea surface temperature.
So right before it splashes, it gets a sea surface temperature.
So it's measuring about seven different things all at once, and when it hits the water, it's gone.
Data collected from the CPEX mission will advance understanding of the atmosphere and help improve the accuracy of weather and climate models.
For more information on CPEX, visit www.nasa.gov/earthex.
It's been established that an octopus is pretty smart, but why and how did it evolve to be that way?
In fact, the same should be asked of the class of beings.
Joining us via Google Hangout is Piero Amodio, a PhD candidate at the University of Cambridge, England, whose work specializes in animal intelligence.
Thanks for joining us.
So why are they so smart?
Well, we still don't know.
Our hypothesis is that they become smart mainly for... in response to two evolutionary pressures.
The first one was essentially to avoid being eaten because octopus in their close relative, the cuttlefish and the squid, they lost the external shell during their evolution.
This key event will increase substantially their predatory pressure, so they become vulnerable to many, many, many predators.
So the idea is that by becoming smart, they could avoid being eaten.
The second hypothesis we have made is that cephalopods became intelligent to increase their chances to find and process food.
So octopuses feed on many kind of food and required some kind of specialization in acquiring the food.
For instance, they need to pull open mussels and other bivalves, so by becoming smart, they could ensure to adopt as many kind of food, many kind of foraging activities.
How do we know their intelligence?
How do we measure it?
The trippy thing about intelligence is that it cannot be measured directly, so we need proxies, and usually there are two proxies that are used.
One is brain size, and the other one is, like, the flexibility of their behavior.
So we know that octopuses have quite large brain relative to their body size, and so this is some supporting evidence for their intelligence.
At the same time, they perform some very complex behavior from tool use and problem solving to very complex anti-predatory strategies.
So taken together, these two proxies suggest that these invertebrates are quite smart.
Do they have memories?
Yeah, of course they have memories.
They have short memories and long-term memories as we have.
As you've been studying this, what impressed you most about how cephalopods, how intelligent they are and how they function.
The most remarkable aspect to me is that they are... they tend...So octopuses are solitary creatures, while the species of cephalopods that are group living, like the squid, but overall cephalopods do not engage in very complex social bonds, and the complexity of social life is considered a key factor in the evolution of intelligence for vertebrates, such as the apes, cetaceans, and smart birds.
So the idea that animals may become too smart but living in a very simple social environment, to me, something extremely fascinating to study.
The second aspect is that they are fast life history.
So octopuses live just 1 or 2 years, while, again, all these other... All these vertebrates group live many years, and so these differences in this evolutionary strategies are remarkable.
So octopuses are the evidence the intelligence may be evolving through different evolutionary paths.
Pointing out how long they live, there's almost a little paradox here, that even though they're so short-lived, they're still really smart.
So our idea here is that when species are subject to very strong predatory pressure, it means they can be eaten really frequently by many other species.
The most safe strategy for them is to reproduce really early on in their life because can be risky to postpone the reproduction event later on in life because you can get eaten before you can have the chance to reproduce, so that's why we think that they... even though they become smart, they could not become long-living because it's a strategy that's not really supported by being subject to all this strong predatory pressure.
What can we learn about other species through your work around cephalopods and octopuses?
I guess the key point is that sometimes we tend to use a kind of anthropocentric approach, so we tend to think that because primates or us follow this evolutionary path, this is the only way intelligence can emerge, but the octopuses are maybe the evidence that intelligence can emerge through different paths, and it's extremely interesting because cephalopods are separated from vertebrates but by approximately 500 million years of independent evolution, so all the aspect we can see of cephalopods arose independently from vertebrates, so I think this is a kind of evolutionary experiment that is super interesting to look into.
Piero Amodio from the University of Cambridge, thanks so much.
Studies suggest there's a link between dying cells in the brain and Alzheimer's disease.
These stagnant dying cells are called zombie cells.
Let's discover how scientists at the University of Texas at San Antonio are studying zombie cells in mice to better understand dementia in humans.
So Alzheimer's disease is the leading cause of dementia worldwide.
In the US, it affects over 5.6 million Americans.
The greatest risk factor is age, so as we all age, we do increase the risk of developing Alzheimer's disease, and at the age of 65 and older, you have a one... Around the age of 65, there's a one in 10 chance you will develop Alzheimer's disease, and that risk continues to increase the older one gets.
Many of you might have experienced Alzheimer's through family members who have had Alzheimer's or might have it now, in which case, you've seen the changes in behavior.
You've seen the changes in their lives.
Well, these mice, who are now healthy mice, once they have Alzheimer's, we'll notice the dramatic behavioral changes in them as well.
Tell me a little bit about mice and why mice and why they're beneficial.
So mice are... Of all of the model organisms that can be used, mice have a lot of benefits.
They are mammals.
They are relatively short-lived, and there's a lot of genetics in the mice that have already been investigated and different models of Alzheimer's disease that can be used, so we can model different aspects of Alzheimer's disease in different mouse models.
After we dissect out the brain, we freeze half of it, and with that half that's frozen, we can look at molecular information, so gene expression, protein expression levels and those sorts of things.
With the other half of the brain, we fix it, and it's like formaldehyde.
And so this is half of a mouse's brain, and then after it's fixed, we section it on... We can use a lot of different types of instruments to section the brain into very thin sections, and with those thin sections, then we can stain them and look for different components that have changed in the brain, and so in this plate, we actually have sectioned brain, but in each one of these wells is a different section of the mouse's brain.
And so then, with these sections, we can mount them onto microscope slides and do what's called histology.
So we stain the brains for different proteins and cell types.
These are MRI images from our mice, and the first one we have is a healthy control mouse, and really what I want you to focus on is this area right here.
These are the ventricles, and they're very small.
There are...in this particular imagine, they show up as white, the fluid shows up as white, and you can see they're very, very small.
Now, if we look at the Alzheimer's disease mouse, which is the one here in the middle, you can see these white areas are very large, so that is corresponding to the increase in ventricle volume.
All of that is fluid, and also you can see just the size of this brain compared to this brain.
It's much smaller.
So these are the Alzheimer's mice that were given the placebo, or the sugar pill.
These are the Alzheimer's mice that, instead of getting the placebo, got the drug treatment.
So they still do have larger ventricles.
These mice were already sick, so in the study, we didn't necessarily expect to regrow all of the damage that had been done, but we were interested in whether or not we could stop the progression from... of disease getting any further.
So what we saw is that these mice had much smaller white areas and on this particular side, it's a lot smaller, and the brains are actually bigger as well when compared to the mice that got the placebo.
There are treatments that can modify behaviors, modify some of the symptoms, but actually preventing the disease, stopping the disease or curing the disease, none of those treatment options are available.
So when my grandmother passed away, I had just graduated college, and I decided that this is... was a very important question that I wanted to spend my life investigating.
So we're really excited about this research, and it's very important because we here in San Antonio for the first time, showed that this drug combination has benefit in Alzheimer's disease, and not only does this drug combination benefit Alzheimer's disease in our model, but it has been shown to benefit so many other health conditions that occur with aging, and Alzheimer's disease patients, they have more comorbid medical conditions than other patients, so if all goes well and this is effective at treating the brain, it may also help a lot of their other systemic issues that are failing as well to increase a healthy life span.
And that wraps it up for this time.
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Until then, I'm Hari Sreenivasan.
Thanks for watching.
Funding for this program is made possible by... ♪♪ ♪♪ ♪♪ ♪♪ ♪♪ ♪♪