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Tuesday, January 21st, 2020
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| 12:00a |
Study uses physics to explain democratic elections It may seem surprising, but theories and formulas derived from physics turn out to be useful tools for understanding the ways democratic elections work, including how these systems break down and how they could be improved.
A new physics-based study finds that in the U.S., elections went through a transition in 1970, from a condition in which election results captured reasonably well the greater electorate’s political preferences, to a period of increasing instability, in which very small changes in voter preferences led to significant swings toward more extreme political outcomes in both directions.
The analysis also shows this instability can be associated with an unexpected situation in which outcomes swing in the opposite direction of how people’s true preferences are shifting. That is, a small move in prevailing opinions toward the left can result in a more right-wing outcome, and vice versa — a situation the researchers refer to as “negative representation.”
The findings appear in the journal Nature Physics, in a paper by Alexander Siegenfeld, a doctoral student in physics at MIT, and Yaneer Bar-Yam, the president of the New England Complex Systems Institute.
“Our country seems more divided than ever, with election outcomes resembling a pendulum swinging with ever increasing force,” Siegenfeld says. In this regime of “unstable” elections, he says, “a small change in electorate opinion can dramatically swing the election outcome, just as the direction of a small push to a boulder perched on top of a hill can dramatically change its final location.”
That’s partly a result of an increasingly polarized electorate, he explains. The researchers drew from a previous analysis that went through the Republican and Democratic party platforms in every presidential election year since 1944 and counted the number of polarizing words using a combination of machine learning and human analysis. The numbers show a relatively stable situation before 1970 but a dramatic increase in polarization since then.
The team then found that the Ising model, which was developed to explain the behavior of ferromagnets and other physical systems, is mathematically equivalent to certain models of elections and accurately describes the onset of instability in electoral systems.
“What happened in 1970 is a phase transition like the boiling of water. Elections went from stable to unstable,” explained Bar-Yam.
The increasing instability also results in part from the structure of party primary systems, which have greatly increased their role in candidate selection since the ’70s. Because the voters in primaries tend to have more extreme partisan views than those of the general electorate, politicians are more inclined to take positions to appeal to those voters — positions that may be more extreme than those favored by more mainstream voters, and thus less likely to win in the general election.
This long-term shift from a stable to unstable electoral situation closely resembles what happens to a ferromagnetic metal exposed to a magnetic field, Siegenfeld says, and can be described by the same mathematical formulas. But why should formulas derived for such unrelated subject matter be relevant to this field?
Siegenfeld says that’s because in physics, it’s not always necessary to know the details of the underlying objects or mechanisms to be able to produce useful and meaningful results. He compares that to the way physicists were able to describe the behavior of sound waves — which are essentially the aggregate motions of atoms — with great precision, long before they knew about the existence of atoms.
“When we apply physics to understanding the fundamental particles of our universe, we don’t actually know the underlying details of the theories,” he says. “Yet we can still make incredibly accurate predictions.”
Similarly, he says, researchers don’t need to understand the motives and opinions of individual voters to be able to carry out a meaningful analysis of their collective behavior. As the paper states, “understanding the collective behavior of social systems can benefit from methods and concepts from physics, not because humans are similar to electrons, but because certain large-scale behaviors can be understood without an understanding of the small-scale details.”
Another important finding from the study is the phenomenon of “negative representation.” This is when an overall shift to the left in voter opinions results in a rightward shift in the election outcome, or vice versa.
This can happen, for example, if voters are faced with a choice between a center-left candidate and a far-right candidate. If the overall sentiments of the electorate move further to the left, that may result in more far-left voters deciding to stay home on election day because the centrist candidate’s views are too far removed from their own. As a result, the far-right candidate ends up winning. Or, if a rightward swing in the electorate leads to the nomination of an extreme far-right candidate, that may increase the odds of a more liberal candidate winning the general election. “This negative representation undermines the entire purpose of democratic elections,” Siegenfeld says.
The study finds that in unstable electoral systems, there is always negative representation. But a number of measures that could help to counter the trend toward instability and thus also reduce the incidence of negative representation, the authors say.
One such solution to reducing election instability would be a shift toward ranked-voting systems, such as those used in Australia, Maine, and the cities of San Francisco and Cambridge, Massachusetts. Such systems reduce the need to select “lesser of two evils” candidates, and allow people to vote for their real preference without the disruptions caused by third-party candidates, they say.
Another approach would be to increase voter turnout, either through incentives, publicity, or legislation (such as Australia’s required voting). The lower the percentage of voter turnout, the greater the potential for instability, the researchers found.
“Most people say ‘go vote’ so your voice is heard,” Siegenfeld says. “What is less appreciated is that when candidates can count on people voting, it is more likely that future elections will become more stable. Our research scientifically demonstrates that high voter turnout helps democracy, since low voter turnout destabilizes elections and results in negative representation.”
“I love this research,” says Soren Jordan, an assistant professor of political science at Auburn University in Alabama, who was not involved in this work and wrote a commentary piece in Nature about it. “The cross-over is exciting, and seeing physicists do mathematical heavy lifting that’s really outside of the traditional scope and training of political science really enhances both disciplines.”
He adds, “This model is an excellent heuristic for understanding some critical phenomena, like how slow-moving concepts like partisanship can still yield large-scale effects in aggregate outcomes.”
The research was supported by the National Science Foundation and the Hertz Foundation | | 12:40p |
With these neurons, extinguishing fear is its own reward When you expect a really bad experience to happen and then it doesn’t, it’s a distinctly positive feeling. A new study of fear extinction training in mice may suggest why: The findings not only identify the exact population of brain cells that are key for learning not to feel afraid anymore, but also show that these neurons are the same ones that help encode feelings of reward.
The study, published Jan. 14 in Neuron by scientists at MIT’s Picower Institute for Learning and Memory, specifically shows that fear extinction memories and feelings of reward alike are stored by neurons that express the gene Ppp1r1b in the posterior of the basolateral amygdala (pBLA), a region known to assign associations of aversive or rewarding feelings, or “valence,” with memories. The study was conducted by Xiangyu Zhang, an MIT graduate student, Joshua Kim, a former graduate student, and Susumu Tonegawa, professor of biology and neuroscience at RIKEN-MIT Laboratory of Neural Circuit Genetics at the Picower Institute for Learning and Memory at MIT and Howard Hughes Medical Institute.
“We constantly live at the balance of positive and negative emotion,” Tonegawa says. “We need to have very strong memories of dangerous circumstances in order to avoid similar circumstances to recur. But if we are constantly feeling threatened we can become depressed. You need a way to bring your emotional state back to something more positive.”
Overriding fear with reward
In a prior study, Kim showed that Ppp1r1b-expressing neurons encode rewarding valence and compete with distinct Rspo2-expressing neurons in the BLA that encode negative valence. In the new study, Zhang, Kim, and Tonegawa set out to determine whether this competitive balance also underlies fear and its extinction.
In fear extinction, an original fearful memory is thought to be essentially overwritten by a new memory that is not fearful. In the study, for instance, mice were exposed to little shocks in a chamber, making them freeze due to the formation of fearful memory. But the next day, when the mice were returned to the same chamber for a longer period of time without any further little shocks, freezing gradually dissipated; hence, this treatment is called fear extinction training. The fundamental question, then, is whether the fearful memory is lost or just suppressed by the formation of a new memory during the fear extinction training.
While the mice underwent fear extinction training the scientists watched the activity of the different neural populations in the BLA. They saw that Ppp1r1b cells were more active and Rspo2 cells were less active in mice that experienced fear extinction. They also saw that while Rspo2 cells were mostly activated by the shocks and were inhibited during fear extinction, Ppp1r1b cells were mostly active during extinction memory training and retrieval, but were inhibited during the shocks.
These and other experiments suggested to the authors that the hypothetical fear extinction memory may be formed in the Ppp1r1b neuronal population, and the team went on to demonstrate this vigorously. For this, they employed the technique previously pioneered in their lab for the identification and manipulation of the neuronal population that holds specific memory information, memory “engram” cells. Zhang labeled Ppp1r1b neurons that were activated during retrieval of fear extinction memory with the light-sensitive protein channelrhodopsin. When these neurons were activated by blue laser light during a second round of fear extinction training, it enhanced and accelerated the extinction. Moreover, when the engram cells were inhibited by another optogenetic technique, fear extinction was impaired because the Ppp1r1b engram neurons could no longer suppress the Rspo2 fear neurons. That allowed the fear memory to regain primacy.
These data met the fundamental criteria for the existence of engram cells for fear extinction memory within the pBLA Ppp1r1b cell population: activation and reactivation by recall and enduring and off-line maintenance of the acquired extinction memory.
Because Kim had previously shown Ppp1r1b neurons are activated by rewards and drive appetitive behavior and memory, the team sequentially tracked Ppp1r1b cell activity in mice that eagerly received a water reward followed by a food reward followed by fear extinction training and fear extinction memory retrieval. The overlap of Ppp1r1b neurons activated by fear extinction versus water reward was as high as the overlap of neurons activated by water versus food reward. And finally, artificial optogenetic activation of Ppp1r1b extinction memory engram cells was as effective as optogenetic activation of Ppp1r1b water reward-activated neurons in driving appetitive behaviors. Reciprocally, artificial optogenetic activation of water-responding Ppp1r1b neurons enhanced fear extinction training as efficiently as optogenetic activation of fear extinction memory engram cells. These results demonstrate that fear extinction is equivalent to bona fide rewards and therefore provide the neuroscientific basis for the widely held experience in daily life: omission of expected punishment is a reward.
What next?
By establishing this intimate connection between fear extinction and reward, and by identifying a genetically defined neuronal population (Ppp1r1b) that plays a crucial role in fear extinction, this study provides potential therapeutic targets for treating fear disorders like post-traumatic stress disorder and anxiety, Zhang says.
From the basic scientific point of view, Tonegawa says, how fear extinction training specifically activates Ppp1r1b neurons would be an important question to address. More imaginatively, results showing how Ppp1r1b neurons override Rspo2 neurons in fear extinction raises an intriguing question about whether a reciprocal dynamic might also occur in the brain and behavior. Investigating “joy extinction” via these mechanisms might be an interesting research topic.
The research was supported by the RIKEN Brain Science Institute, the Howard Hughes Medical Institute, and the JPB Foundation. | | 1:40p |
Putting a finger on the switch of a chronic parasite infection Toxoplasma gondii (T. gondii) is a parasite that chronically infects up to a quarter of the world’s population, causing toxoplasmosis, a disease that can be dangerous, or even deadly, for the immunocompromised and for developing fetuses. One reason that T. gondii is so pervasive is that the parasites are tenacious occupants once they have infected a host. They can transition from an acute infection stage into a quiescent life cycle stage and effectively barricade themselves inside of their host’s cells. In this protected state, they become impossible to eliminate, leading to long-term infection.
Researchers used to think that a combination of genes were involved in triggering the parasite’s transition into its chronic stage, due to the complexity of the process and because a gene essential for differentiation had not been identified. However, new research from Sebastian Lourido, Whitehead Institute member and assistant professor of biology at MIT, and MIT graduate student Benjamin Waldman has identified a sole gene whose protein product is the master regulator, which is both necessary and sufficient for the parasites to make the switch. Their findings, which appeared online in the journal Cell on Jan. 16, illuminate an important aspect of the parasite’s biology and provide researchers with the tools to control whether and when T. gondii transitions, or undergoes differentiation. These tools may prove valuable for treating toxoplasmosis, since preventing the parasites from assuming their chronic form keeps them susceptible to both treatment and elimination by the immune system.
T. gondii spreads when a potential host, which can be any warm-blooded animal, ingests infected tissue from another animal — in the case of humans, by eating undercooked meat or unwashed vegetables — or when the parasite’s progeny are shed by an infected cat, T. gondii’s target host for sexual reproduction. When T. gondii parasites first invade the body, they are in a quickly replicating part of their life cycle, called the tachyzoite stage. Tachyzoites invade a cell, isolate themselves by forming a sealed compartment from the cell’s membrane, and then replicate inside of it until the cell explodes, at which point they move on to another cell to repeat the process. Although the tachyzoite stage is when the parasites do the most damage, it’s also when they are easily targetable by the immune system and medical therapies.
In order for the parasites to make their stay more permanent, they must differentiate into bradyzoites, a slow-growing stage, during which they are less susceptible to drugs and have too little effect on the body to trigger the immune system. Bradyzoites construct an extra-thick wall to isolate their compartment in the host cell and encyst themselves inside of it. This reservoir of parasites remains dormant and undetectable until, under favorable conditions, they can spring back into action, attacking their host or spreading to new ones.
Although the common theory was that multiple genes collectively orchestrate the transition from tachyzoite to bradyzoite, Lourido and Waldman suspected that there was instead a single master regulator.
“Differentiation is not something a parasite wants to do halfway, which could leave them vulnerable,” Waldman says. “Multiple genes means more chances for things to go wrong, so you would want a master regulator to ensure that differentiation happens cleanly.”
To investigate this hypothesis, Waldman used CRISPR-based screens to knock out T. gondii genes, and then tested to see if the parasite could still differentiate from tachyzoite to bradyzoite. Waldman monitored whether the parasites were differentiating by developing a strain of T. gondii that fluoresces in its bradyzoite stage. The researchers also performed a first-of-its-kind single-cell RNA sequencing of T. gondii in collaboration with members of Alex Shalek’s lab in the MIT Department of Chemistry. This sequencing allowed the researchers to profile the genes’ activity at each stage in unprecedented detail, shedding light on changes in gene expression during the parasite’s cell-cycle progression and differentiation.
The experiments identified one gene, which the researchers named Bradyzoite-Formation Deficient 1 (BFD1), as the only gene both sufficient and necessary to prevent the transition from tachyzoite to bradyzoite: the master regulator. Not only was T. gondii unable to make the transition without the BFD1 protein, but Waldman found that artificially increasing its production induced the parasites to become bradyzoites, even without the usual stress triggers required to cue the switch. This means that the researchers can now control Toxoplasma differentiation in the lab.
These findings may inform research into potential therapies for toxoplasmosis, or even a vaccine.
“Toxoplasma that can’t differentiate is a good candidate for a live vaccine, because the immune system can eliminate an acute infection very effectively,” Lourido says.
The researchers’ findings also have implications for food production. T. gondii and other cyst-forming parasites that use BFD1 can infect livestock. Further research into the gene could inform the development of vaccines for farm animals as well as humans.
“Chronic infection is a huge hurdle to curing many parasitic diseases,” Lourido says. “We need to study and figure out how to manipulate the transition from the acute to chronic stages in order to eradicate these diseases.”
This study was supported by an NIH Director’s Early Independence Award, a grant from the Mathers Foundation, the Searle Scholars Program, the Beckman Young Investigator Program, a Sloan Fellowship in Chemistry, the National Institutes of Health, and the Bill and Melinda Gates Foundation. |
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