from the world's big
When Squirrels Roamed the Plains
Iain Couzin is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Princeton University, where he manages the Couzin Lab. His research focuses on collective behavior and self-organized pattern formation in a variety of biological systems, including fish schools, bird flocks, insect swarms, human crowds, and cellular networks.
Question: How much non-conformity do we observe among animal groups?\r\n
Iain Couzin: Non-conformity within these groups often tends to be very dangerous. So individuals that stand out within the group are often those that are taken by the predator. So there's a strong selection pressure, not only to look like the other individuals in the group, but also to behave like other individuals in the group.\r\n
And also, if one were to consider a predator sort of attacking a fish school or a bird flock, you know, the reason that the concerted motion, these waves work so effectively, is because everyone is essentially following a similar type of rule. If you tried to do something completely different, you could of course cause congestion, you could cause a pile up within these groups, and that would of course be selected out of the population and so individuals that follow such rules tend not to last very long.\r\n
Question: Does acting collectively ever harm animals?\r\n
Iain Couzin: So, you know, in a wide range of scenarios, there is a risk that animals face. By copying the behavior of each other, they risk a sort of cascade of misinformation. And this is actually akin to what happens sometimes in human societies when people start believing something without actually checking it out themselves. So if a decision depends on that made by a few individuals at the start of the process, then everyone then joins in and decides that they agree with that without actually having assessed the information directly themselves, then this can lead to the sort of autocatalysis and the spread of maladaptive information.\r\n
Now what we found in animals is that they're, the way that they interact with each other is tuned to minimize this risk. But, you know, there's a compromise as well because it does sometimes happen that they do make mistakes, of course. Because if you really were to sort of look at all of the information and assess it, that takes time. And time is precious. And so just like, you know, a human when you're looking for say, an insurance policy or whatever, you don't actually read all of the details, all of the fine print of all of the alternatives. You tend to look online and perhaps believe what Google tells you, or perhaps you ask a few friends who you trust. And then you rely on that information.\r\n
And so, you know, we also have this type of positive feedback, so our decision making, as well, is interested by these social processes.\r\n
Question: What is the truth behind the cliché of suicidal lemmings?\r\n
Iain Couzin: It is, of course, a myth. The lemmings don't actually hurl themselves off cliffs. You know, these animals are highly susceptible to population fluctuations. And so the predators tend to sort of increase in number and the rodents can increase in number and so on. And this can actually lead to vast fluctuations, so one year there may be many, many individuals, other years very few. And also, I can't remember the exact example of the lemmings, but there's huge potential in these populations for mass migration, for individuals to migrate en masse. And, you know, even in North America, the squirrel that we see everywhere, the grey squirrel, used to, once upon a time, not that long ago, a few hundred years ago, used to form mass migrations as far as you could see, there are descriptions of squirrels and they, when they come to rivers, they all swim across the rivers and people would go out with, you know, guns and dogs and, you know, and just, it was a phenomenon.\r\n
And, you know, also, there's an extinct bird now called the passenger pigeon, which also used to live in the United States. When these flocks were so dense during their migrations that the sky would go black. You know, and these, of course, have been the, the passenger pigeons have been wiped out by man and the squirrels' environment is now so fragmented, the forest is so fragmented, that no longer do they form these mass migrations. But these kind of collective behaviors are actually ubiquitous, you know, that all scales from, you know, bacterial colonies to, you know, very large aggregates like locusts, that we study, which are some of the largest groups on the planet.
Recorded on December 15, 2009
Interviewed by Austin Allen
From the formerly migratory North American squirrel to the much-misunderstood lemming, biologist Iain Couzin explains the power of animal collectives.
If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.
- Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
- Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
- One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.