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03 Oct 2023
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How an Anti-Inflammatory Diet Can Help Tame an Autoimmune Condition

An estimated 23.5 million Americans, including my husband, suffer from an autoimmune condition — and their numbers are growing, though researchers don’t know why. You’ve likely heard of the most common autoimmune diseases — including type 1 diabetes, rheumatoid arthritis, multiple sclerosis, lupus, celiac disease, psoriasis, inflamatory bowel disease and Crohn’s disease — but you might be unaware that there are more than 80 named but lesser-known types. Through working as a nutritionist and living with my husband, I’ve learned the importance of diet in battling these disorders.

What is an autoimmune disease?

A healthy immune system can plainly distinguish between a foreign invader and its own body. When something inhibits the immune system’s ability to decipher what is safe and what is dangerous to the body, the immune system can attack its own healthy cells and tissues believing that they are threatening. This self-attack is an autoimmune condition.

What causes an immune system to attack its own healthy cells is still largely unknown but according to the National Institutes of Health, “There is a growing consensus that autoimmune diseases likely result from interactions between genetic and environmental factors.” There are studies that show that certain genes can predispose a person to certain autoimmune diseases, and this is why many autoimmune diseases show up in one family, as they do in my husband’s family where vasculitis, rheumatoid arthritis and alopecia all reside.

Yet simply having the gene doesn’t guarantee someone will get the disease. The gene is like fire kindling; there must also be a spark — or an environmental trigger — for there to be a blaze. Known triggers are infections, exposure to environmental toxins, hidden allergens, or stress and lack of sleep. Autoimmune conditions are like embers of a fire that never fully burns out. After the initial blaze, they can flare up again and again. We try to keep my husband’s condition tamped down through diet and exercise.

How a healthy lifestyle helps

Studies suggest that a healthy lifestyle can help keep the immune system balanced while less healthy situations can trigger the immune system to overreact. For instance, low vitamin D levels have been shown to be a risk factor for multiple sclerosis. Obesity has been linked to many autoimmune diseases, including MS, rheumatoid arthritis and psoriasis. Stress and anxiety have been shown to cause all kinds of autoimmune flares. On the other hand, anti-inflammatory dietary choices can lessen rheumatoid arthritis. Getting the right nutrients, maintaining a healthy weight, managing stress and sleeping regularly can help prevent an autoimmune flare.

“It is current knowledge that nutrition, the intestinal microbiota, the gut mucosal immune system, and autoimmune pathology are deeply intertwined,” reads a 2014 study, entitled “Role of ‘Western Diet’ in Inflammatory Autoimmune Diseases” and published in the journal Current Allergy and Asthma Reports. In other words, what we eat and the health of our digestive tract are directly connected to our autoimmune system. Other studies suggest that autoimmune issues can be managed by healing a damaged gut.

Think of the gut as the front line of defense in an army. It is the first location that foreign and potentially dangerous substances deeply interact with our bodies. This is likely why almost 70 percent of our immune system lies in and around our gut so that it can react when poisonous, dangerous, allergic or toxic things enter our systems.

Since the gut is so directly tied to the immune system and healing a damaged gut can potentially manage an autoimmune condition, it seems important to keep yours healthy. You can do this by cutting out foods that inflame the gut, limiting unnecessary medications that can alter the bacteria balance in the gut and consuming prebiotics (such as artichokes and asparagus), probiotics (such as kimchi and miso) and bone broth to build a healthy mix of bacteria.

Anti-inflammatory food choices

The following foods have been shown to cause inflammation so should be avoided if trying to balance the immune system and keep inflammation under control:

Sugar
Refined carbohydrates
Trans-fats
Omega 6 fatty acids
Processed foods and meat
Alcohol
Caffeine
Artificial sweeteners
Food dyes

The following foods have been shown to reduce inflammation:

Leafy greens
Fruits such as blueberries, strawberries and blackberries
Fatty fish, high in omega 3 fatty acids
Olive oil
Avocados
Nuts and seeds (if not allergic)
Herbs and spices such as turmeric, cumin and garlic
Vitamin D has been shown to help prevent inflammation and autoimmunity

When my husband was diagnosed, his doctors checked for underlying infections and allergies. When they didn’t find a specific trigger, he went on a strict anti-inflammatory diet for eight weeks. He took fish oil, vitamin D, vitamin C and zinc, and he did yoga, exercised regularly and got a lot more sleep than he usually did. These actions helped his body heal and not long afterward he was back throwing a baseball with our boys feeling like his energetic self. He’s only had one flare-up since, and it followed a few weeks of travel that affected his sleep patterns and stress levels. We will never know what sparked the wildfire, but we are forever thankful to know what tames it.

Original article here

01 Oct 2023
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The Power of Next

Whenever I am faced with life’s uncertainty, I ask myself the following questions: Why is this happening? What can I do to make it go away? How can I navigate this effectively? What can I learn from this experience?

Being at a crossroads can be challenging when what you know to be true suddenly isn’t. The straight and expected path you are on veers sharply, does a summersault, and flings you into unchartered territory leaving you unsure of what direction you are facing. Disoriented, the task of righting yourself can seem daunting. What do I do now? What are my next steps? So many asked questions, so many unanswered responses.

The ‘not knowing’ can be fertile ground for stress, anxiety, and fear to insidiously creep into your awareness. The question then becomes, “What can be done to mitigate the fallout and find direction?”

Baby Steps

Many years ago, I took a workshop on handling change, where the facilitator asked us to do one exercise every day for the rest of our lives (a pretty bold ask!). He asked us to change one thing every day. Simple, easy tasks that gently challenge any resistance to change thinking. Drive a different way to work. If you normally put your right shoe on first, today put your left shoe on first. Please note, I tried changing hands to brush my teeth and got toothpaste all over!

The goal of this exercise is to become more comfortable with daily changes, even small ones, thereby making the bigger, more challenging ones less scary. Now, I can’t say that I do this every day, but this exercise has provided comfort for me in times of turmoil.

While this exercise can be a preemptive approach to handling stress, I also found I needed an immediate touchstone that would provide me with some reassurance in the current moment that things were indeed going to be okay, I was going to be okay, in troubled times.

Next…

That touchstone for me lies in the concept of the word “next.” The Merriam-Webster dictionary describes the word next this way: in the time, place, or order nearest or immediately succeeding. It even has the word “succeed” in the definition!

When life gets challenging and I have been thoroughly flung into the unknown, I boldly (and sometimes confidently) say, “Next!” out loud. This shifts my energy, focus and intention away from the quagmire I find myself in and points me in a new direction. It’s amazing how saying this one word while keeping a curious spirit and open heart can provide a sense of comfort and possibilities.

Rather than dwelling on the unforeseen changes, I choose to look toward new possibilities. I may have no clue as to what those possibilities may be or when I will experience them, but I believe I will be guided. Many years ago, I purchased a greeting card that I had framed. On the card was a quote from Emily Dickinson that says, “I dwell in possibility.” That has been my sacred mantra and has served me well.

Next is possibility. Next is hope. Next is new beginnings. Next is sewn into the very fabric of forward motion. What are my next steps? What’s the next chapter for me? What’s next on the agenda?

As we get swept away and sometimes flung by life’s changes and challenges, stand in your power and declare…

Next!

Original article here

26 Sep 2023
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Humans Could Live up to 150 Years, New Research Suggests

The chorus of the theme song for the movie Fame, performed by actress Irene Cara, includes the line “I’m gonna live forever.” Cara was, of course, singing about the posthumous longevity that fame can confer. But a literal expression of this hubris resonates in some corners of the world—especially in the technology industry. In Silicon Valley, immortality is sometimes elevated to the status of a corporeal goal. Plenty of big names in big tech have sunk funding into ventures to solve the problem of death as if it were just an upgrade to your smartphone’s operating system.

Yet what if death simply cannot be hacked and longevity will always have a ceiling, no matter what we do? Researchers have now taken on the question of how long we can live if, by some combination of serendipity and genetics, we do not die from cancer, heart disease or getting hit by a bus. They report that when omitting things that usually kill us, our body’s capacity to restore equilibrium to its myriad structural and metabolic systems after disruptions still fades with time. And even if we make it through life with few stressors, this incremental decline sets the maximum life span for humans at somewhere between 120 and 150 years. In the end, if the obvious hazards do not take our lives, this fundamental loss of resilience will do so, the researchers conclude in findings published in May 2021 in Nature Communications.

“They are asking the question of ‘What’s the longest life that could be lived by a human complex system if everything else went really well, and it’s in a stressor-free environment?’” says Heather Whitson, director of the Duke University Center for the Study of Aging and Human Development, who was not involved in the paper. The team’s results point to an underlying “pace of aging” that sets the limits on life span, she says.

For the study, Timothy Pyrkov, a researcher at a Singapore-based company called Gero, and his colleagues looked at this “pace of aging” in three large cohorts in the U.S., the U.K. and Russia. To evaluate deviations from stable health, they assessed changes in blood cell counts and the daily number of steps taken and analyzed them by age groups.

For both blood cell and step counts, the pattern was the same: as age increased, some factor beyond disease drove a predictable and incremental decline in the body’s ability to return blood cells or gait to a stable level after a disruption. When Pyrkov and his colleagues in Moscow and Buffalo, N.Y., used this predictable pace of decline to determine when resilience would disappear entirely, leading to death, they found a range of 120 to 150 years. (In 1997 Jeanne Calment, the oldest person on record to have ever lived, died in France at the age of 122.)

The researchers also found that with age, the body’s response to insults could increasingly range far from a stable normal, requiring more time for recovery. Whitson says that this result makes sense: A healthy young person can produce a rapid physiological response to adjust to fluctuations and restore a personal norm. But in an older person, she says, “everything is just a little bit dampened, a little slower to respond, and you can get overshoots,” such as when an illness brings on big swings in blood pressure.

Measurements such as blood pressure and blood cell counts have a known healthy range, however, Whitson points out, whereas step counts are highly personal. The fact that Pyrkov and his colleagues chose a variable that is so different from blood counts and still discovered the same decline over time may suggest a real pace-of-aging factor in play across different domains.

Study co-author Peter Fedichev, who trained as a physicist and co-founded Gero, says that although most biologists would view blood cell counts and step counts as “pretty different,” the fact that both sources “paint exactly the same future” suggests that this pace-of-aging component is real.

The authors pointed to social factors that reflect the findings. “We observed a steep turn at about the age of 35 to 40 years that was quite surprising,” Pyrkov says. For example, he notes, this period is often a time when an athlete’s sports career ends, “an indication that something in physiology may really be changing at this age.”

The desire to unlock the secrets of immortality has likely been around as long as humans’ awareness of death. But a long life span is not the same as a long health span, says S. Jay Olshansky, a professor of epidemiology and biostatistics at the University of Illinois at Chicago, who was not involved in the work. “The focus shouldn’t be on living longer but on living healthier longer,” he says.

“Death is not the only thing that matters,” Whitson says. “Other things, like quality of life, start mattering more and more as people experience the loss of them.” The death modeled in this study, she says, “is the ultimate lingering death. And the question is: Can we extend life without also extending the proportion of time that people go through a frail state?”

The researchers’ “final conclusion is interesting to see,” Olshansky says. He characterizes it as “Hey, guess what? Treating diseases in the long run is not going to have the effect that you might want it to have. These fundamental biological processes of aging are going to continue.”

The idea of slowing down the aging process has drawn attention, not just from Silicon Valley types who dream about uploading their memories to computers but also from a cadre of researchers who view such interventions as a means to “compress morbidity”—to diminish illness and infirmity at the end of life to extend health span. The question of whether this will have any impact on the fundamental upper limits identified in the Nature Communications paper remains highly speculative. But some studies are being launched—testing the diabetes drug metformin, for example—with the goal of attenuating hallmark indicators of aging.

In this same vein, Fedichev and his team are not discouraged by their estimates of maximum human life span. His view is that their research marks the beginning of a longer journey. “Measuring something is the first step before producing an intervention,” Fedichev says. As he puts it, the next steps, now that the team has measured this independent pace of aging, will be to find ways to “intercept the loss of resilience.”

Original article here

22 Sep 2023
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Selfishness Is Learned

Many people cheat on taxes — no mystery there. But many people don’t, even if they wouldn’t be caught — now, that’s weird. Or is it? Psychologists are deeply perplexed by human moral behavior, because it often doesn’t seem to make any logical sense. You might think that we should just be grateful for it. But if we could understand these seemingly irrational acts, perhaps we could encourage more of them.

It’s not as though people haven’t been trying to fathom our moral instincts; it is one of the oldest concerns of philosophy and theology. But what distinguishes the project today is the sheer variety of academic disciplines it brings together: not just moral philosophy and psychology, but also biology, economics, mathematics, and computer science. They do not merely contemplate the rationale for moral beliefs, but study how morality operates in the real world, or fails to. David Rand of Yale University epitomizes the breadth of this science, ranging from abstract equations to large-scale societal interventions. “I’m a weird person,” he says, “who has a foot in each world, of model-making and of actual experiments and psychological theory building.”

In 2012 he and two similarly broad-minded Harvard professors, Martin Nowak and Joshua Greene, tackled a question that exercised the likes of Thomas Hobbes and Jean-Jacques Rousseau: Which is our default mode, selfishness or selflessness? Do we all have craven instincts we must restrain by force of will? Or are we basically good, even if we slip up sometimes?

They collected data from 10 experiments, most of them using a standard economics scenario called a public-goods game. Groups of four people, either American college students or American adults participating online, were given some money. They were allowed to place some of it into a pool, which was then multiplied and distributed evenly. A participant could maximize his or her income by contributing nothing and just sharing in the gains, but people usually gave something. Despite the temptation to be selfish, most people showed selflessness.

The fuzziness of psychological ideas makes them hard to test. If an experimental result doesn’t fit your theory of human behavior, you can fiddle with the definitions.

This finding was old news, but Rand and his colleagues wanted to know how much deliberation went into such acts of generosity. So in two of the experiments, subjects were prodded to think intuitively or deliberately; in two others, half of the subjects were forced to make their decision under time pressure and half were not; and in the rest, subjects could go at their own pace and some naturally made their decisions faster than others. If your morning commute is any evidence, people in a hurry would be extra selfish. But the opposite was true: Those who responded quickly gave more. Conversely, when people took their time to deliberate or were encouraged to contemplate their choice, they gave less.

The researchers worked under the assumption that snap judgments reveal our intuitive impulses. Our intuition, apparently, is to cooperate with others. Selfish behavior comes from thinking too much, not too little. Rand recently verified this finding in a meta-analysis of 51 similar studies from different research groups. “Most people think we are intuitively selfish,” Rand says — based on a survey he conducted—but “our lab experiments show that making people rely more on intuition increases cooperation.”

The cooperative impulse isn’t confined to an artificial experimental setting. In another paper, Rand and Ziv Epstein of Pomona College studied interviews with 51 recipients of the Carnegie Hero Medal, who had demonstrated extreme altruism by risking their lives to save others. Study participants read the interviews and rated the medalists on how much their thinking seemed intuitive versus deliberative. And intuition dominated. “I’m thankful I was able to act and not think about it,” a college student who rescued a 69-year-old woman from a car during a flash flood explained.

So Rand made a strong case that people are intuitive cooperators, but he considered these findings just the start. It’s one thing to put forward an idea and some evidence for it — lots of past researchers have done that. It’s quite another to describe and explain that idea in a rigorous, mathematical fashion. Ironically, Rand figured he could make better sense of humans by stepping away from studying real ones.

The overwhelming majority of psychological theories are verbal: explanations of the ways people act using everyday language, with maybe a few terms of art thrown in. But words can be imprecise. It may be true that “cooperation is intuitive,” but when is it intuitive? And what exactly does “intuitive” mean? The fuzziness of psychological ideas makes them hard to test. If an experimental result doesn’t fit your theory of human behavior, you can fiddle with the definitions and claim you were right all along.

Rand has sought to create quantitative models. “Science is about developing theories,” he says, “not about developing a list of observations. And the reason formal models are so important is that if your goal is theory-building, then it’s essential that you have theories that are really clearly articulated and are falsifiable.”

To do that, he has developed computer simulations of society — The Sims, basically. These models represent collections of individual people described by computer “agents,” algorithms that capture a specific package of traits, such as a tendency to cooperate or not. You can do controlled experiments on these computerized citizens that would be impossible or unethical to do with real people. You can endow them with new personalities to see how they’d fare. You can observe social processes in action, on time scales ranging from seconds to generations, instead of just taking a snapshot of a person or group. You can watch the spread of certain behaviors throughout a population and how they influence other behaviors. Over time, the patterns that emerge can tell you things about large-scale social interaction that a lab experiment with a few real people never could.

One of the first such models, in the early 1970s, studied housing segregation. It represented a city as a 16-by-13 grid of squares, populated by two types of people: stars and circles. Each star would move to the nearest location in which at least half its neighbors were also stars — it had a slight bias to be among similar others. Circles did the same. Even these mild biases led quickly to stark segregation, with all-star and all-circle regions of the board — a much more extreme partitioning than any one agent sought. The researcher, the economist Thomas Schelling, used his model to help explain racial segregation in American cities. A neighborhood can splinter into homogeneous patches even when individual residents are hardly prejudiced at all. (Of course, in reality, segregation also reflects outright racism and explicit policies of exclusion.) Schelling’s work became a case study of how a group’s collective behavior can diverge from the desires of any one agent.

Such models have also been used to explore cooperation. In an influential paper in 1981, the political scientist Robert Axelrod programmed agents to play a simple game called the Prisoner’s Dilemma. Two players have to decide whether to cooperate with or betray the other, and they receive points based on their choices. The scoring system is set up to mimic an essential dilemma of social life. Together the players perform best if they both cooperate, yet each can maximize his or her own individual outcome, at the expense of the other, by acting selfishly. The game takes its name from a scenario in which the police interrogate two thieves, offering each a reward for ratting out his or her accomplice. The thieves aren’t able to communicate to reach a joint decision; they have to make their decisions independently. Acting rationally, each should rat out the other. But when they both act “rationally,” they actually end up with the most combined jail time.

It’s possible we’re born with a tendency to cooperate, but frequent cooperation (with beneficial results) is required to sustain our benevolence.

The game gets more interesting — and more analogous to real life — when you play multiple rounds with the same partner. Here, repeated cooperation is best not just for both partners as a unit but also for each individually. You can still occasionally double-cross your partner for extra points, however, as long as it doesn’t trigger later betrayal.

What is the best strategy, then? To find out, Axelrod solicited Prisoner’s Dilemma strategies from mathematicians, biologists, economists, political scientists, computer scientists, and physicists from around the world. Axelrod programmed his computerized agents with these strategies and made them play a round-robin tournament. Some strategies were quite sophisticated, but the winner was a simple one called tit-for-tat.

Tit-for-tat resembles human reciprocity. It starts with cooperation and, after that, does whatever the other player did on the previous round. An agent using the strategy extends an olive branch at first. If its opponent reciprocates, it keeps cooperating. But if its opponent double-crosses it, the tit-for-tat agent rescinds its peace offering until its opponent makes amends.

By combining the short-term temptation to be selfish with the long-term benefits of collaboration, the Prisoner’s Dilemma is an ideal model for human cooperation, and Rand has built on Axelrod’s work to understand why evolution might have favored intuitive selflessness.

Rand and his grad student Adam Bear considered a variant of the Prisoner’s Dilemma in which matchups were either one-shot or multiple-round, chosen at random.8 The computerized agents faced a tough choice. In a one-off, they would score more points by betraying their opponent, whereas in repeated play cooperation made more sense. But the uncertainty made it unclear which strategy was best. Rand and Bear then added a twist. An agent could elect to pay some points at the start of an encounter—representing the efforts of deliberation—to suss out what kind of matchup it would face, so that it could tailor its strategy.

The agent had to decide whether the advantage of foreknowledge outweighed its cost. The price of the tip-off varied randomly, and each agent was programmed with a maximum price it would agree to pay; if the price exceeded that amount, the agent did not receive any advance information and instead chose some default behavior, following its “intuition.” In this way, the simulation allowed for different personality types. Some agents intuitively cooperated, others intuitively betrayed. Some occasionally deliberated, others didn’t.

Is deliberation helpful? That’s not immediately obvious. Intuitive thinking is fast but inflexible. Deliberative thinking can achieve better outcomes but takes time and energy. To see which strategy excelled in the long run, Rand and Bear’s model simulated a process of evolution. A large population of agents played the game with one another and either proliferated or died depending on how well they did. This process can model either genetic evolution or cultural evolution, in which the weak players don’t actually die, but merely adopt stronger strategies through imitation.

Most of us are genuinely good. And if we’re not, we can be encouraged to be. The math is there.

Typically, one strategy swept through the population and replaced the alternatives. This victorious strategy depended on the precise parameters of the game. For example, Rand and Bear varied the probability that matchups would be single- or multiple-round. When most were multi-round, the winning agents defaulted to cooperating but deliberated if the price was right and switched to betrayal if they found they were in a one-shot game. But when most were one-shots, the agents that prevailed were no longer willing to pay to deliberate at all. They simply double-crossed their opponents. In other words, the model produced either wary cooperation or uncompromising betrayal.

This outcome was notable for what was missing. Agents that always cooperated usually died off completely. Likewise, almost no set of game parameters favored agents that defaulted to the double-cross but were sometimes willing to deliberate. Bear and Rand stared at this asymmetry for several weeks, baffled.

Finally, they had a breakthrough. They realized that when your default is to betray, the benefits of deliberating — seeing a chance to cooperate — are uncertain, depending on what your partner does. With each partner questioning the other, and each partner factoring in the partner’s questioning of oneself, the suspicion compounds until there’s zero perceived benefit to deliberating. If your default is to cooperate, however, the benefits of deliberating — occasionally acting selfishly — accrue no matter what your partner does, and therefore deliberation makes more sense.

So, it seems there is a firm evolutionary logic to the human instinct to cooperate but adjust if necessary — to trust but verify. We ordinarily cooperate with other people, because cooperation brings us benefits, and our rational minds let us decipher when we might occasionally gain by acting selfishly instead.

The model also ties up a loose end from Rand’s earlier studies of public-goods games. In that research, time pressure caused some people to cooperate more, but never caused anyone to cooperate less. This asymmetry now makes sense. The only people who would have shown that behavior were those who were willing to deliberate, but defaulted to betrayal; the time pressure would bring out their Machiavellian inclinations. Evidently such people are rare. If someone is deep-down selfish, rational deliberation will only make them more so. And the evolutionary model shows why. Defectors who have qualms are quickly winnowed out by genetic or cultural evolution.

When it comes to getting people to cooperate more, Rand’s work brings good news. Our intuitions are not fixed at birth. We develop social heuristics, or rules of thumb for interpersonal behavior, based on the interactions we have. Change those interactions and you change behavior.

Rand, Nowak, and Greene tested that idea in their 2012 paper. They asked some subjects whether they’d ever played such economics games before. Those with previous experience didn’t become more generous when asked to think intuitively; they’d apparently become accustomed to the anonymous nature of such games and learned a new intuition. Unfortunately, it was a cynical one: They could get away with mooching off others. Similarly, subjects who reported that they couldn’t trust most of the people in their lives also didn’t become more generous when acting on intuition. It’s possible we’re born with a tendency to cooperate, but frequent cooperation (with beneficial results) is required to sustain our benevolence.

Happily, even the Grinch can expand his heart by three sizes, as Rand demonstrates in a recent study. First, he had test subjects play the Prisoner’s Dilemma for about 20 minutes with a variety of opponents. For half of the subjects, the average game lasted eight rounds, meaning cooperation was the best strategy; for half, the average game lasted a single round, which discouraged cooperation. Afterward, everyone played a public-goods game. Those stewed in cooperation gave significantly more money in the second phase of the experiment than did those without it. In less than half an hour, their intuitions had shifted.

How do you encourage cooperation in places where cooperation isn’t the norm? Corporate America comes to mind. “In a lot of situations people are basically rewarded for backstabbing and ladder-climbing,” Rand says. Rand and Bear’s modeling paper, in which intuitive defectors don’t trust each other enough even to consider whether cooperation would pay off, points to an answer. Rand suggests that, at least at first, incentives could come from above, so that the benefits of cooperating don’t depend solely on whether one’s partner cooperates. Companies might offer bonuses and recognition for helpful behavior. Once cooperation becomes a social heuristic, people will begin to cooperate when it benefits them, but also even when it doesn’t. Selflessness will be the new norm.

When selflessness is the norm, encouraging people to make decisions quickly can bring out their better angels. Extensions of this research reveal that we see quick or unthinking acts of generosity as particularly revealing of kindness, and that people may even use this signal strategically. In recent work, Rand and his collaborators have shown that people are faster to make decisions to cooperate when they know someone is watching, as if aware that others will judge them by their alacrity. Among other puzzles, Rand is currently trying to untangle this apparent paradox—the strategic use of intuition.

Rand’s work offers a correction to those misanthropes who peer into the hearts of men and women and see shadows. Most of us are genuinely good. And if we’re not, we can be encouraged to be. The math is there.

If you think seeing life as a set of economics games and cooperation as self-interest in disguise sounds dismal, it is actually not so distanced from what you might call virtue. “When I’m nice to other people, I’m not doing it because of some kind of calculation. I’m doing it because it feels good,” Rand says. “And the reason it feels good, I argue, is that it is actually payoff maximizing in the long run.”

Rand then adds a crucial clarification. “It feels good to be nice — unless the other person is a jerk,” he says. “And then it feels good to be mean.”

Tit for tat indeed.

Original article here

18 Sep 2023
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Voice Is the Next Big Platform, Unless You Have an Accent

My mother waited two months for her Amazon Echo to arrive. Then, she waited again — leaving it in the box until I came to help her install it. Her forehead crinkled as I download the Alexa app on her phone. Any device that requires vocal instructions makes my mother skeptical. She has bad memories of Siri. “She could not understand me,” my mom told me.

My mother was born in the Philippines, my father in India. Both of them speak English as a third language. In the nearly 50 years they’ve lived in the United States, they’ve spoken English daily — fluently, but with distinct accents and sometimes different phrasings than a native speaker. In their experience, that means Siri, Alexa, or basically any device that uses speech technology will struggle to recognize their commands.

My parents’ experience is hardly exclusive or unknown. (It’s even been chronicled in comedy, with this infamous trapped-in-a-voice-activated elevator sketch.) My sister-in-law told me she gave up on using Siri after it failed to recognize the “ethnic names” of her friends and family. I can vouch for the frustration: The other day, my command of “Text Zahir” morphed into “Text Zara here.”

Right now, it’s not much of a problem — but it’s slated to become more serious, given that we are in the middle of a voice revolution. Voice-based wearables, audio, and video entertainment systems are already here. Due in part to distracted drivers, voice control systems will soon be the norm in vehicles. Google Home and Amazon’s Alexa are radicalizing the idea of a “smart home” across millions of households in the US. That’s why it took so long for my mother’s Echo to arrive — the Echo was among Amazon’s bestsellers this holiday season, with a 900 percent increase from 2016 sales. It was backordered for weeks.

Overall, researchers estimate 24.5 million voice-driven devices will be delivered to Americans’ daily routines this year — evidence that underscores ComScore’s prediction that by 2020, half of all our searches will be performed by voice.

But as technology shifts to respond to our vocal chords, what happens to the huge swath of people who can’t be understood?

To train a machine to recognize speech, you need a lot of audio samples. First, researchers have to collect thousands of voices, speaking on a range of topics. They then manually transcribe the audio clips. This combination of data — audio clips and written transcriptions — allows machines to make associations between sound and words. The phrases that occur most frequently become a pattern for an algorithm to learn how a human speaks.

But an AI can only recognize what it’s been trained to hear. Its flexibility depends on the diversity of the accents to which it’s been introduced. Governments, academics, and smaller startups rely on collections of audio and transcriptions, called speech corpora, to bypass doing labor-intensive transcriptions themselves. The University of Pennsylvania’s Linguistic Data Consortium (LDC) is a powerhouse of these data sets, making them available under licensed agreements for companies and researchers. One of its most famous corpora is Switchboard.

Texas Instruments launched Switchboard in the early 1990s to build up a repository of voice data, which was then distributed by the LDC for machine learning programs. It’s a collection of roughly 2,400 telephone conversations, amassed from 543 people from around the US — a total of about 250 hours. Researchers lured the callers by offering them long-distance calling cards. A participant would dial in and be connected with another study participant. The two strangers would then chat spontaneously about a given topic — say, childcare or sports.

For years linguists have assumed that because the LDC is located in Philadelphia, the conversations skewed towards a Northeastern accent. But when Marsal Gavaldà, the director of machine intelligence at the messaging app Yik Yak, crunched the numbers in Switchboard’s demographic history, he found that the accent pool skewed more midwestern. South and North Midland accents comprised more than 40 percent of the voice data.

Other corpora exist, but Switchboard remains a benchmark for the models used in voice recognition systems. Case in point: Both IBM and Microsoft use Switchboard to test the word error rates for their voice-based systems. “From this set of just over 500 speakers, pretty much all engines have been trained,” says Gavaldà.

But building voice technology on a 26-year-old corpus inevitably lays a foundation for misunderstanding. English is professional currency in the linguistic marketplace, but numerous speakers learn it as a second, third, or fourth language. Gavaldà likens the process to drug trials. “It may have been tried in a hundred patients, [but] for a narrow demographic,” he tells me. “You try to extrapolate that to the general population, the dosage may be incorrect.”

Larger companies, of course, have to think globally to stay competitive — especially because most sales of smartphones happen outside the US Technology companies like Apple, Google, and Amazon have private, in-house methods of collecting this data for the languages and accents they’d like to accommodate. And the more consumers use their products the more their feedback will improve the products, through programs like Voice Traininglanguage on the Alexa app.

But even if larger tech companies are making headway in collecting more specific data, they’re motivated by the market to not share it with anyone — which is why it takes so long for the technology to trickle down. This secrecy also applied to my reporting of this piece. Amazon never replied to my request for comment, a spokesperson for Google directed me to a blog post outlining its deep learning techniques, and an Apple PR representative noted that Siri is now customized for 36 countries and supports 21 languages, language variants, and accents.

Outside the US, companies are aware of the importance of catering to accents. The Chinese search engine company Baidu, for one, says its deep learning approach to speech recognition achieves accuracy in English and Mandarin better than humans, and it’s developing a “deep speech” algorithm that will recognize a range of dialects and accents. “China has a fairly deep awareness of what’s happening in the English-speaking world, but the opposite is not true,” Baidu chief scientist Andrew Ng told The Atlantic.

Yet smaller companies and individuals who can’t invest in collecting data on their own are beholden to cheaper, more readily available databases that may not be as diverse as their target demographics. “[The data’s] not really becoming more diverse, at least from my perspective,” Arlo Faria, a speech researcher at the conference transcription startup Remeeting, tells me. Remeeting, for example, has used a corpus called Fisher that includes a group of non-native English speakers — but Fisher’s accents are largely left up to chance, depending on who happened to participate in the data collection. There are some Spanish and Indian accents, for instance, but very few British accents, Faria recalls.

That’s why, very often, voice recognition technology reacts to accents differently than humans, says Anne Wootton, co-founder and CEO of the Oakland-based audio search platform Pop Up Archive, “Oftentimes the software does a better job with like, Indian accents than deep Southern, like Shenandoah Valley accents,” she says. “I think that’s a reflection of what the training data includes or does not include.”

Rachael Tatman, a PhD candidate at the University of Washington’s Department of Linguistics who focuses on sociolinguistics, noted that the underrepresented groups in these data sets tend to be groups that are marginalized in general. A typical database of American voices, for example, would lack poor, uneducated, rural, non-white, non-native English voices. “The more of those categories you fall into, the worse speech recognition is for you,” she says.

Still, Jeffrey Kofman, the CEO and co-founder of Trint, another automated speech-to-text software based in the UK, is confident accent recognition is something speech science will be able to eventually solve. We video chatted on the Trint platform itself, where Australian English is now available alongside British and North American English as transcription accents. Trint also offers speech-to-text in a dozen European languages, and plans to add South Asian English sometime this year, he said.

Collecting data is expensive and cumbersome, which is why certain key demographics take priority. For Kofman, that’s South Asian accents, “because there are so many people from India, Pakistan, and those countries here in England, in the US and Canada, who speak very clearly but with a distinct accent,” he says. Next, he suspects, he’ll prioritize South African accents.

Obviously, it’s not just technology that discriminates against people with accents. It’s also other people. Mass media and globalization are having a huge effect on how people sound. Speech experts have documented the decline of certain regional American accents since as early as 1960, for example, in favor of a more homogenous accent fit for populations from mixed geographic areas. This effect is exacerbated when humans deal with digital assistants or operators; they tend to use a voice devoid of colloquialisms and natural cadence.

Or, in other words, a voice devoid of an identity and accent.

As voice recognition technology becomes better, using a robotic accent to communicate with a device stands to be challenged — if people feel less of a need to talk to their devices as if they are machines, they can start talking to them as naturally as they would a friend. And while some accent reduction coaches find their clients use voice assistants to practice neutralizing their thick foreign or regional accents, Lisa Wentz, a public speaking coach in San Francisco who works in accent reduction, says that she doesn’t recommend it.

That’s because, she tells me, most of her clients are aiming for other people to understand them. They don’t want to have to repeat themselves or feel like their accents prevent others from hearing them. Using devices that aren’t ready for different voices, then, only stands to make this feeling echo.

My mother and I set up her Alexa app together. She wasn’t very excited about it. I could already imagine her distrust and fear of a car purported to drive by the command of her voice. My mother would never ride in it; the risk of crashing would be too real. Still, she tried out a couple of questions on the Echo.

“Alexa, play ‘Que sera sera,’” my mother said.

“I can’t find the song ‘Kiss your ass era.’”

My mom laughed, less out of frustration and more out of amusement. She tried again, this time speaking slower, as if she were talking to a child. “Alexa, play ‘Que sera sera.’” She sang out the syllables of sera in a slight melody, so that the device could clearly hear “se-rah.”

Alexa understood, and found what my mom was looking for. “Here’s a sample of ‘Que sera sera,’ by Doris Day,” she said, pronouncing the sera a bit harsher — “se-raw.”

The 1964 hit started to play, and my mother smiled at the pleasure of recognition.

Original article here

14 Sep 2023
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Why You Should Cultivate a Fluid Sense of Self

If you want to learn something about change there is no better place to look than evolution. Nothing represents a continuous and unrelenting cycle of order, disorder, and reorder on a grander scale. For long periods of time, Earth is relatively stable. Sweeping changes—warming, cooling, or an asteroid falling from space, for example—occur. These inflection points are followed by periods of disruption and chaos. Eventually, Earth, and everything on it, regains stability, but that stability is somewhere new.

During this cycle, some species get selected out. Others survive and thrive. Species in the latter group tend to have high degrees of what evolutionary biologists call “complexity.” Complexity is comprised of two elements: differentiation and integration. Differentiation is the degree to which a species is composed of parts that are distinct in structure or function from one another. Integration is the degree to which those distinct parts communicate and enhance each other’s goals to create a cohesive whole.

Consider Homo sapiens (you and me), by far the most abundant and widespread species of primate. we have large frames, four limbs, opposable thumbs, body temperature that is somewhat resistant to external conditions, good vision and hearing, digestive tracts that can accommodate a variety of nutrients, and the capacity for language and understanding. In other words, we are a highly differentiated species. But we also have enormous brains and advanced nervous systems that integrate all of these parts into a cohesive whole. The combination of these qualities—widespread differentiation and strong integration—makes us a decidedly complex species. Our complexity is how we got here today and why, hopefully, we’ll stick around for at least a bit longer.

Though change at the individual level, the primary concern of my new book Master of Change, is different than change on an evolutionary scale, there is still much we can learn from evolution’s foundational principles, lessons that apply to the horizons of our own lives. If we want to survive and thrive during ongoing cycles of change and disorder, then we, too, can benefit from developing our own versions of complexity.

As a matter of fact, there is a psychological construct called self-complexity. Essentially, it says that the key to a strong and enduring identity—one that is equal parts rugged and flexible, that can navigate the inevitable changes we all face—is to diversify your sense of self.

The more you define yourself by any one activity, the more fragile you become. If that activity doesn’t go well or something changes unexpectedly, you lose a sense of who you are. But with self-complexity, you have develop multiple components to your identity.

We all can wear many hats: examples include writer, spouse, artist, parent, employee, neighbor, entrepreneur, baker, and creative, to name just a few. Take an inventory of your own identities. Are there any upon which you are over-reliant for meaning and self-worth? What would it look like to diversify your sense of self? Even if you desire to go “all in” on a certain endeavor, you’ve got to ensure that you don’t leave others completely behind.

I’ve come to use the metaphor of a house for identity. If your house only has one room in it, and that rooms floods, you are going to be very disoriented. But if your house has multiple rooms, you can seek refuge in the others while you weather the storm. It’s okay to put spend a lot of time in one room—so long as you have other rooms available when the one you are currently pouring yourself into changes.

For example: there are times when I lean heavily into each of my main identities—father, husband, writer, coach, friend, athlete, and neighbor. I’ve learned that keeping all of these identities strong ensures that when things don’t go well in one area of my life I can rely on the others to pick me up, which helps me to stay grounded and navigate whatever challenge I am facing.

What you want to do is challenge yourself to integrate the various elements of your identity into a cohesive whole. This allows you to emphasize and de-emphasize certain parts of your identity at different periods of time. The result is a fluid sense of self.

Unlike other types of matter, fluid contains both mass and volume but not shape. This allows it to flow over and around obstacles, changing form while retaining substance, neither getting stuck nor fracturing when unforeseen impediments manifest on its path. Cultivating a fluid sense of self allows you to do the same. By developing and nurturing multiple parts of your identity, you can more easily navigate change.

A large body of research shows that when there is too great a fusion between one’s identity and their pursuit, then anxiety, depression, and burnout frequently result. This is especially true for athlete’s during periods of change and transition, when one’s dominant—and all to often, sole— sense of identity feels at risk. Yet while it may be heightened for athletes, it’s a pattern that holds true in all lines of work and all walks of life: if you want to be excellent and experience something fully, then you’ve got to go all in, but only to a point. If your identity becomes too enmeshed in any one concept or endeavor—be it your age, how you look in the mirror, a relationship, or your career—then you are likely to face significant distress when things change, which, for better or worse, they always do.

None of the above is permission to be laissez-faire or go through the motions. Caring deeply about the people, activities, and projects you love is key to a rich and meaningful existence. The problem is not caring deeply; it is when your identity becomes too rigidly attached to any single object or endeavor.

Original article here

11 Sep 2023
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Scientists may be on brink of discovering fifth force of nature

The tantalising theory that a fifth force of nature could exist has been given a boost thanks to unexpected wobbling by a subatomic particle, physicists have revealed.

According to current understanding, there are four fundamental forces in nature, three of which – the electromagnetic force and the strong and weak nuclear forces – are explained by the standard model of particle physics.

However, the model does not explain the other known fundamental force, gravity, or dark matter – a strange and mysterious substance thought to make up about 27% of the universe.

Now researchers have said there could be another, fifth, fundamental force of nature.

Dr Mitesh Patel, from Imperial College London, said: “We’re talking about a fifth force because we can’t necessarily explain the behaviour [in these experiments] with the four we know about.”

The data comes from experiments at the Fermilab US particle accelerator facility, which explored how subatomic particles called muons – similar to electrons but about 200 times heavier – move in a magnetic field.

Patel says the muons behave a bit like a child’s spinning top, in rotating around the axis of the magnetic field. However, as the muons move, they wobble. The frequency of that wobble can be predicted by the standard model.

But the experimental results from FermiLab do not appear to match those predictions.

Prof Jon Butterworth of University College London, who works on the Atlas experiment at the Large Hadron Collider (LHC) at Cern, said: “The wobbles are due to the way the muon interacts with a magnetic field. They can be calculated very precisely in the standard model but that calculation involves quantum loops, with known particles appearing in those loops.

“If the measurements don’t line up with the prediction, that could be a sign that there is some unknown particle appearing in the loops – which could, for example, be the carrier of a fifth force.”

The findings follow previous work from FermiLab that showed similar results.

But Patel said there was a “fly in the ointment”, noting that between the first results and the new data, uncertainty has increased around the theoretical prediction of the frequency.

That, he said, could shift the situation. “Maybe what they are seeing is standard scientific thinking – the so-called standard model,” Patel said.

There are other issues. Butterworth said: “If the discrepancy is confirmed, we will be sure there is something new and exciting but we won’t be sure exactly what it is.

“Ideally the discrepancy would inform new theoretical ideas that would lead to new predictions – for example, of how we might find the particle that carries the new force, if that’s what it is. The final confirmation would then be building an experiment to directly discover that particle.”

The experiments at Fermilab are not the only ones to suggest the possibility of a fifth force: work at the LHC has also produced tantalising findings, albeit with a different type of experiment looking at the rate at which muons and electrons are produced as certain particles decay.

But Patel, who worked on the LHC experiments, said those results were now less coherent.

“They are different experiments, measuring different things, and there may or may not be a connection,” he said.

Butterworth added that the unexpected frequency of the muons’ wobbles was one of the longest-standing and most significant discrepancies between a measurement and the standard model.

“The measurement is a great achievement, and very unlikely to be in error now,” he said. “So if the theory predictions get sorted out, this could indeed be the first confirmed evidence for a fifth force – or something else strange and beyond the standard model.”

Original article here

06 Sep 2023
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So…How Do Adults Make New Friends?

In approximately one month and 10 days, I’ll be on my way to making one of the larger decisions of my adult life (so far, anyway); I’m moving to Austin, Texas, approximately 2,000 miles and one hell of a road trip away from my family and almost my entire friend group back in New York. While I have many questions about my move—chief among them, “How much should a mattress cost?” and “Will everyone hate me for being a Brooklyn transplant?”—nothing has loomed larger in my mind than the question of friendship, or, more specifically, how a full-grown adult goes about making new friends with no partner or kids to act as built-in buffers.

Of course, a big move is hardly the only circumstance in which an otherwise reasonably socialized adult might find herself craving new friendships. The COVID-19 pandemic shrunk our social circles considerably, with many of us spending the last year-plus in the company of family and only our absolute closest BFFs. As the world slowly reopens, it stands to reason that we might want to seek out new connections—and feel somewhat unsure about where to start (especially as COVID-19 rates continue to climb in many cities).

Anxiety about friend-making isn’t so uncommon, according to clinical psychologist and friendship researcher Dr. Miriam Kirmayer, although some of these nerves may be linked to misconceptions about how meaningful friendships actually come about. “There does seem to be, for many people, this belief that friendships should just happen—whether we’re in a new city or a new phase of life—and that our people, so to speak, will magically show up. As beautiful as that is, that isn’t the reality for most people,” explains Kirmayer. “My best advice is to be very intentional with how we approach making friends; seek out opportunities, experiences and activities where we are likely to meet new people with whom we share something in common. My second piece of advice is to try and choose wisely, or, in other words, choose opportunities where we will have more frequent interactions, because we know that friendships often require that frequency of interaction in order to develop.”

Conventional wisdom has it that you should pick popular yet slightly off-the-beaten path activities, like a running group or a knitting club, to meet new people. But what about those of us for whom a good Friday night hinges on the strength of a gummy edible and the availability of a new episode of The Bold Type on Hulu? I’m not trying to paint myself as a total couch potato, but…let’s just say my social style is definitely on the “chill” side, not so much the “go hiking and meet new people on top of a mountain at 7:00 a.m.” side. My quest for new friendships almost feels like dating, something I’m meh at yet very enthusiastic about, except that I don’t have a great frame of reference for what “success” would look like. Does friendship success equal a hangout invite? A standing Saturday-night bar crawl? Godparent-ing each other’s children? How will I know when I’ve cracked it, socially speaking?

For some people, social success—however they define it—can spring from a source as prosaic as social media. Mijal Tenenbaum, 27, moved to Los Angeles with only a few loose acquaintances at her disposal. She DM-ed one of them on Twitter and invited them out to brunch, and while that plan never came to be, Tenenbaum’s new friend did invite her to Disneyland, of all places. Today, the two are best friends, and Tenenbaum’s advice to people in similar situations (whether they’re in a new city or just feeling socially stagnant) would be: “If you get good vibes from an acquaintance or Twitter mutual, reach out and give them a chance! Even if you’re a little insecure and you don’t know them well, just go for it.”

For Hannah Smith, 27, friendship began at home—quite literally—when she moved to San Francisco in 2019 without knowing anyone. Smith sublet three different rooms through Craigslist before she finally signed a month-to-month lease in the perfect place (which she also found through Craigslist), eventually turning a roommate from her final apartment into one of her best friends. “Low-commitment living situations can be a great way to get to know people in a new place,” says Smith, although she adds that this strategy might be somewhat complicated by the ongoing effects of COVID-19.

One popular method for friend-making endorsed by Kirmayer is volunteering, which is exactly how Courtney Gustafson, 31, ended up meeting her two best friends. “During the pandemic, I happened upon a colony of feral cats, started caring for them, made them an Instagram, and then two different people reached out to offer help with the cats,” says Gustafson. “The three of us turned out to be around the same age and have a lot in common, and now we are a cat rescue/best friend team of 3!”

Ultimately, there’s no perfect way to predict the success of a new friendship. After all, you could join a volunteer effort or a cooking club and meet absolutely nobody you bond with, or you could meet your all-time, Elena Ferrante–novel–level soulmate at a random party you almost skipped. Still, as more people get vaccinated and life ever-so-creepingly returns to “normal,” it’s worth thinking about whether the friendships in your life are giving you what you need and want. If they’re not, maybe you should DM that cool-seeming Twitter person, sublet with a friendly acquaintance, or bond over a mutual love of feral cats—because after all, without true and lasting friendships, who would have the courage tell us when we were being annoying on the internet?

Original article here

02 Sep 2023
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This Is Where Your Childhood Memories Went

We called them fairy rocks. They were just colorful specks of gravel—the kind you might buy for a fish tank—mixed into my preschool’s playground sand pit. But my classmates and I endowed them with magical properties, hunted them like treasure, and carefully sorted them into piles of sapphire, emerald, and ruby. Sifting the sand for those mystical gems is one of my earliest memories. I was no older than 3 at the time. My memory of kindergarten has likewise been reduced to isolated moments: tracing letters on tan paper with pink dashed lines; watching a movie about ocean creatures; my teacher slicing up a giant roll of parchment so we could all finger-paint self-portraits.

When I try to recall my life before my fifth birthday, I can summon only these glimmers—these match strikes in the dark. Yet I know I must have thought and felt and learned so much. Where did all those years go?

Psychologists have named this dramatic forgetting “childhood amnesia.” On average, people’s memories stretch no farther than age three and a half. Everything before then is a dark abyss. “This is a phenomenon of longstanding focus,” says Patricia Bauer of Emory University, a leading expert on memory development. “It demands our attention because it’s a paradox: Very young children show evidence of memory for events in their lives, yet as adults we have relatively few of these memories.”

In the last few years, scientists have finally started to unravel precisely what is happening in the brain around the time that we forsake recollection of our earliest years. “What we are adding to the story now is the biological basis,” says Paul Frankland, a neuroscientist at the Hospital for Sick Children in Toronto. This new science suggests that as a necessary part of the passage into adulthood, the brain must let go of much of our childhood.

Sigmund Freud gave childhood amnesia its name in the early 1900s. He argued that adults forgot their earliest years of life in the process of repressing disturbing memories of sexual awakening. While a handful of psychologists saw merit in this claim, the most commonly accepted explanation for childhood amnesia was that children simply couldn’t form stable memories until age 7—even though there was little evidence to support this idea. For nearly 100 years, psychologists assumed that memories of infancy did not endure because they were never durable in the first place.

The late 1980s marked the beginning of a reformation in child psychology. Bauer and other psychologists began to test infant memory by performing a series of actions—such as building a simple toy gong and striking it—and then waiting to see if a child could imitate the actions in the right order, after a delay ranging from minutes to months.

“Mice performed worse on certain kinds of memory tests after living in a cage with a running wheel.

This work laid bare the contradiction at the heart of childhood amnesia: Infants can create and access memories in their first few years of life, yet most of these memories eventually vanish at a rate far beyond the typical forgetting of the past we experience as adults.

Maybe, some researchers thought, enduring memories require language or a sense of self, both of which we lack as infants. But although verbal communication and self-awareness undoubtedly strengthen human memories, their absence could not be the whole explanation for childhood amnesia. After all, certain animals that have large and complex brains relative to their body size—such as mice and rats—but do not have language or, presumably, our level of self-awareness, also lose the memories they make in infancy.

Perhaps, then, researchers reasoned, the paradox had a more fundamental physical basis that was common to people and other big-brained mammals. The question was, what?

Between birth and our early teens, the brain is still laying down some of its fundamental circuitry and thickening its electrical pathways with fatty tissue to make them more conductive. In a massive surge of growth, the brain sprouts innumerable new bridges between neurons. In fact, we have far more links between brain cells in our earliest years than we end up with in adulthood; most are pruned away. All that excess brain mass is the wet clay from which our genes and experiences sculpt a brain to suit its particular environment. Without such limber brains, young children would never be able to learn as much as quickly as they do.

As Bauer and others discovered, this adaptability comes with a price. While the brain undergoes this prolonged development outside the womb, the large and complex network of disparate brain regions that collectively create and maintain our memories is still under construction, Bauer explains, and not as capable of forming memories as it will be in adulthood. As a consequence, the long-term memories formed in our first three years of life are the least stable memories we ever make and highly prone to disintegrating as we age.

In early 2018, Frankland and his colleagues published a study indicating another way the brain relinquishes our childhood memories: not only do they degrade, but they also become concealed. A few years back, Frankland and his wife Sheena Josselyn—also a neuroscientist at the Hospital for Sick Children—started to notice that the mice they studied performed worse on certain kinds of memory tests after living in a cage with a running wheel.

“Our earliest memories are often insoluble blends of genuine recollections, narratives we sponged up from others, and imaginary scenes dreamt up by the subconscious.

As the couple knew, exercise on a running wheel promotes neurogenesis—the growth of whole new neurons—in the seahorse-shaped hippocampus, a brain region that is essential for memory. But while neurogenesis in the adult hippocampus likely contributes to the ability to learn and remember, Karl Deisseroth of Stanford University and others had suggested that it might also necessitate a certain amount of forgetting. Just as a forest has room for only so many trees, the hippocampus can hold only so many neurons. New brain cells might crowd the territory of other neurons or even replace them altogether, which could in turn break or reconfigure the small circuits that likely store individual memories. Perhaps, then, the especially high rate of neurogenesis in infancy was partly responsible for childhood amnesia.

To put this notion to the test, Frankland and Josselyn transferred infant and adult mice from the plastic shoebox-sized cages they had known all their lives to larger metal cages they had never seen before. In these new containers, they zapped the rodents’ feet with mild electric shocks. The mice quickly learned to associate the metal cages with the shocks, stiffening with fear whenever they were returned to those enclosures.

While baby mice began to forget about this connection after a single day—relaxing when they found themselves in the shock cages—adult mice never forgot about the danger. But when adults ran on a hamster wheel after the shocks—thereby stimulating neurogenesis—they started to mirror infants in their forgetfulness. Prozac, which also encourages neural growth, had the same effect. Conversely, when the researchers hindered neurogenesis in infant mice with drugs or genetic engineering, the young animals formed much more stable memories.

To get a really close look at how neurogenesis might change memory, Frankland and Josselyn used a virus to insert a gene encoding a green fluorescent protein into the DNA of the mice’s newly sprouted brain cells. The glowing dye revealed that the new cells were not replacing old ones; rather, they were joining existing circuitry. That suggests that, technically, the many little circuits of neurons that store our earliest memories are not wiped out by neurogenesis. Instead, they are thoroughly restructured, which probably explains why the original memories become so difficult to recall. “We think it’s an accessibility issue,” Frankland says, “but it’s sort of a semantic issue too. If a memory becomes impossible to access, then it is effectively erased.”

This restructuring of memory circuits means that, while some of our childhood memories are truly gone, others persist in a scrambled, refracted way. Studies have shown that people can retrieve at least some childhood memories by responding to specific prompts—dredging up the earliest recollection associated with the word “milk,” for example—or by imagining a house, school, or specific location tied to a certain age and allowing the relevant memories to bubble up on their own.

But even if we manage to untangle a few distinct memories that survive the tumultuous cycles of growth and decay in the infant brain, we can never fully trust them; some of them might be partly or entirely fabricated. Through her pioneering research, Elizabeth Loftus of the University of California, Irvine has demonstrated that our earliest memories in particular are often insoluble blends of genuine recollections, narratives we sponged up from others, and imaginary scenes dreamt up by the subconscious.

In one set of groundbreaking experiments conducted in 1995, Loftus and her colleagues presented volunteers with short stories about their childhood provided by relatives. Unbeknownst to the study participants, one of these stories—about being lost in a mall at age 5—was mostly fiction. Yet a quarter of the volunteers said they had a memory of the experience. And even when they were told that one of the stories they had read was invented, some participants failed to realize it was the lost-in-a-mall story.

When I was a toddler, I got lost in Disneyland. Here is what I recall: It was December and I was watching a toy train loop through a Christmas village. When I turned around, my parents had disappeared. Dread dripped down my body like cold molasses. I began blubbering and wandering the park, searching for them. A stranger approached me and took me to a giant building filled with TV screens playing feeds from security cameras all over the park. Did I see my parents on any of the screens? I did not. We went back to the train where we found my parents. I ran into their arms, overcome with joy and relief.

Recently, for the first time in quite a while, I asked my mom exactly what she remembers about that day in Disneyland. She says it was spring or summer and that she and my family last saw me beside the remote control Jungle Cruise boats, not the railroad near the entrance of the park. As soon as they realized I was missing, they went straight to the Lost and Found Center. A park official had indeed discovered me and brought me to the center, where I had been placated with ice cream.

It was unsettling to have what I thought was a pretty accurate memory so thoroughly contradicted, so I asked my mom to search our family photo albums for some hard evidence. All she could find were pictures from an earlier trip. We will probably never have any tangible proof of what happened. We are left with something far more elusive: those tiny embers of the past, embedded in our mind, twinkling like fool’s gold.

Original article here

30 Aug 2023
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The Mystery Genes That Are Keeping You Alive

One could be forgiven for a little genetic déjà vu.

Launched in 1990, the Human Genome Project unveiled its first readout of the human DNA sequence with great fanfare in 2000. The human genome was declared essentially complete in 2003—but it took nearly 20 more years before the final, complete version was released.

This did not mark the end of humankind’s genetic puzzle, however. A new study has mapped the yawning gap between reading our genes and understanding them. Vast parts of the genome—areas the study authors have nicknamed the “Unknome”—are made of genes whose function we still don’t know.

This has important implications for medicine: Genes are the instructions for making the protein building blocks of the body. Plenty of those still shrouded in darkness could have profound medical significance and may hold the keys to disorders of development, cancer, neurodegeneration, and more.

The study makes it embarrassingly clear just how many important genes we know little to nothing about. It estimates that a fifth of human genes with a vital function are still essentially a mystery. The good news is that the research also outlines how scientists can focus on those mystery genes. “We might now be at the beginning of the end of the Unknome,” says Matthew Freeman of the Dunn School of Pathology at the University of Oxford, a coauthor of the study.

The research team used two tools to find the gaps in our knowledge. First, using the plethora of existing databases of genetic information, they compared the genetic codes of many different species to reveal genes that look roughly similar.

These riffs on a genetic theme are known as conserved genes, and even if we don’t understand what they do, we know that they must be important because nature is parsimonious and tends to use the same genetic machinery to do important jobs in different organisms. “The one thing we could be confident of is that, if important, these genes would be quite well-conserved across evolution,” says Freeman.

Once they had found similar genetic riffs in worms, humans, flies, bacteria, and other organisms, the researchers could look at what was known about the function of these clearly important genes and score them accordingly, with a high “knownness” score reflecting solid understanding.

Because so much genetic information is already available on hundreds of genomes and recorded in a standardized way, it was possible to automate this scoring process. “We then asked how many of those [conserved genes] have a score of less than one, where essentially nothing is known about them,” says Freeman. “To our surprise, two decades after the first human genome, it is still an extraordinary number.”

In all, the total number of human genes with a knownness score of 1 or less is currently 1,723 out of 19,664.

By the same token, the top 10 genes identified by the team’s rummage through genetic databases corresponded with “all the most famous genes, which is reassuring,” says Sean Munro of the Laboratory of Molecular Biology in Cambridge, a study coauthor. “We recognized every single one of them, and there are already thousands of papers about each of them.”

When it came to the substantial number that were unknown, the team conducted one more study, using the best understood (at the genetic level) organism of all: Drosophila melanogaster. These fruit flies have been the subject of research for more than a century because they are easy and inexpensive to breed, have a short life cycle, produce lots of young, and can be genetically modified in numerous ways.

The team used gene editing to dial down the use of around 300 low-scoring genes found in both humans and fruit flies. “We found that one-quarter of these unknown genes were lethal—when knocked out, they caused the flies to die, and yet nobody had ever known anything about them,” says Freeman. “Another 25 percent of them caused changes in the flies—phenotypes—that we could detect in many ways.” These genes were linked with fertility, development, locomotion, protein quality control, and resilience to stress. “That so many fundamental genes are not understood was eye-opening,” Freeman says. It’s possible that variation in these genes could have very big impacts on human health.

All of this “unknomics” information is held on a database, which the team is making available for other researchers to use to discover new biology. The next step may be to hand the data on these mystery genes and the mystery proteins they create over to AI.

DeepMind’s AlphaFold, for example, can provide important insights into what mystery proteins do, notably by revealing how they interact with other proteins, says Alex Bateman of the European Bioinformatics Institute, based near Cambridge, UK. So can cryo-EM, which is a way of producing images of large, complex molecules, he says. And a University College London team has shown a systematic way to use machine learning to figure out what proteins do in yeast.

The Unknome is unusual in that it’s a biology database that will shrink as we understand it better. The paper shows that over the past decade “we have moved from 40 percent to 20 percent of the human proteome having a certain level of unknownness,” says Bateman. However, at current progress rates, working out the function of all human protein-coding genes could take more than half a century, Freeman estimates.

The discovery that so many genes remain misunderstood reflects what is called the streetlight effect, or the drunkard’s search principle, an observational bias that occurs when people only search for something where it is easiest to look. In this case, it has caused what Freeman and Munro call a “bias in biological research toward the previously studied.”

The same goes for researchers, who tend to get funding for research in relatively well-understood areas, rather than going off into what Freeman calls the wilderness. This is why the database is so important, Munro explains—it fights back against the economics of academia, which avoids things that are very poorly understood. “There is a need for a different type of support to address these unknowns,” says Munro.

But even with the database becoming available and researchers picking through it, there will still be some knowledge blind spots. The study focused on genes that are responsible for proteins. Over the past two decades, uncharted areas of the genome have also been found to harbor the code for small RNAs—scraps of genetic material that can affect other genes, and which are critical regulators of normal development and bodily functions. There may be more “unknown unknowns” lurking in the human genome.

For now, there’s still plenty to get into, and Freeman hopes this work will encourage others to study the genetic Terra Incognita: “There’s more than enough Unknome for anyone who wants to explore genuinely new biology.”

Original article here