The Brain Benefits of Exercising With Other People

In 2020, the world spent more than $7 billion on supplements that promised to enhance brain health. We may as well be setting that money on fire. The quest for the perfect IQ-boosting pill, memory game, or creativity elixir has not been a successful one.

If you’re seeking that one weird trick to improve your brain health, the best place to look might be your feet. That’s the conclusion I reached after my journey through hundreds of studies assessing brain zapping, microdosing, games, and other popular interventions for my book, The Tailored Brain. It turns out one of the only legitimate ways to tailor our brains has been available to us all along: physical activity.

Getting moving has a number of effects that tie directly to the brain’s resilience, from increased blood flow to refreshed connections in the brain itself. But one of the less appreciated ways to enhance these effects even further is to engage with other brains while we engage in exercise.

Humans are, like elephants or naked mole rats, a social species. Evolution shaped us not as single brains making our way through life but as brain collectives, interacting, problem-solving, creating, and, yes, moving through the world, literally, together. A fascinating new hypothesis from evolutionary biology posits that physical activity builds a buffer against the insults of age so that we stick around and are healthy enough to support other people, not so we can sit alone in a cave or a castle and be lonely geniuses.

Interacting with others as we move can unburden our minds, leaving space for crisp new ideas, increased attention, memory power, and a lighter mood. The best news is that even modest amounts of activity offer benefits. Science says so.

How physical activity and social interaction work together

If you find yourself groaning at the idea of more exercise, that may be because “exercise” is an artificial form of physical activity, which can encompass many pursuits from gardening to shopping. And it may be that doing something social while we move around comes to us naturally.

Harvard evolutionary biologist Daniel Lieberman co-authored a recent review of evidence for the argument that physical activity is an evolutionary adaptation that supports brain health into old age. The idea is that as humans evolved, we moved around a lot to keep ourselves fed and cared for, which supported brain health. Both the physical activity and the healthy brain in turn made us able to care for younger generations into old age.

This idea is an evolutionary explanation for why humans survive well past the reproductive years, which is extremely rare among animals. It goes hand in hand with the “grandmother hypothesis,” which posits that in our post-reproductive years, we stick around to care for little ones in younger generations who carry our genes. By keeping them alive, we keep alive the genes we passed along to them, too. Lieberman and co-authors add to this picture by proposing that physical activity supports the brain and body “healthspan” that allows for a physically active old age.

Exercise gets molecules moving, too, for repairs and remodeling

Physical activity causes damage, Lieberman and his co-authors say, in the form of muscle breakdown and release of damaging oxidant molecules. But the scientists offer evidence that when we repair this damage, we overshoot a bit, leaving things even better off than when we started. A huge antioxidant release in response to oxidants from exercise, for example, could buffer against inflammation, which is linked to degenerative brain diseases.

Even a little exercise, like 20 to 30 minutes a few days a week, goes a long way. Moving around gets our blood moving, and that moves molecules to our brains more efficiently. It’s well known that physical activity can send more oxygen to the energy-hogging brain, for example. The presence of oxygen triggers cells to start using glucose, the brain’s preferred energy molecule.

Low glucose use in the brain has been linked to Alzheimer’s disease, even in people without symptoms who carry genetic risk variants for the condition. One 2017 study looked at how well the brains of 93 late-middle-aged adults metabolized glucose after physical activity. The researchers used devices to objectively track physical activity for a week and found a link between moderate physical activity and enhanced glucose use in the brain, which is an indicator of good brain health.

Another study using devices for objective physical activity measurement found that people with higher levels of daily physical activity and good motor abilities scored better on tests of cognition. The 454 participants in that 2019 study underwent the monitoring and testing in the years before their deaths, and agreed to donate their brains for analysis after their deaths.

Even when the brains showed changes linked to conditions such as Alzheimer’s disease, physical activity levels and motor ability each separately were associated with better performance on the cognitive tests. The researchers speculated that factors like physical activity could enhance the brain’s “cognitive reserve,” or ability to work around damage to the brain and maintain function.

Another measure of the brain’s flexibility and health is how easily it switches from one task to another, which is called “set shifting.” Set shifting is different from multitasking, which is when you’re doing two things at once, like talking on the phone and making dinner.

We use set shifting in social situations, for example: think of how you redirect mental resources at a party as you shift from talking with someone about the food to a conversation with someone else about the state of the nation. In a 2021 meta-analysis of 22 trials of how easily people engaged in set shifting, the authors found that light physical activity was associated with easier set shifting, especially for people who were older.

This ability to adapt fluidly as a situation shifts is the domain of the CEO in our heads, otherwise known as our executive function. Executive function is our ability to manage ourselves through working memory, self-control, and flexibility in thinking.

A meta-analysis published in 2020 assessed the findings of 36 randomized controlled trials of physical activity’s effects on brain-related measures of executive function. Trials like these are considered the most rigorous kind of research design. These 36 studies collectively included 4,577 young people, and the review pointed to links between physical activity and benefits for different aspects of executive function.

A similar kind of review, also published in 2020, looked at the results of 33 randomized trials that had included people over age 55 and also found a benefit of physical activity for executive function. Yet another analysis of 25 randomized trials found physical exercise-related improvements in several features of executive function in healthy adults age 60 and older.

These analyses of findings from more than 100 studies suggest that physical activity benefits the aging CEO in our brains. If Lieberman and his colleagues are right, one upshot may be a longer healthspan for our brains to match our life spans.

How supplements have turned out to be “brain enhancer” duds

The pursuit of the fountain of youth has never turned up a supplement that works as well as physical activity. Researchers initially thought omega-3 fatty acids might get some traction as brain improvers, especially for mood. These fatty acids stood out in uncontrolled studies, where scientists just observe people who have been exposed to a factor and compare them with those who haven’t.

These so-called observational studies hinted enough at brain benefit from these fatty acids that omega-3s became quite popular as an “evidence-based” brain supplement. Imaging also seemed to indicate that brain connections might reconfigure in presumably beneficial ways with omega-3 use.

We use these molecules in building our brains, so the defensible intuition was that we could take them in pill form and reap brain benefits. But when omega-3 supplements were entered into more rigorous randomized controlled trials, they didn’t keep their brain-based promises for effects on mood and anxiety. They didn’t even best corn oil for improving depression symptoms when added to an antidepressant therapy. And randomized studies of the effects of these fatty acids on cognitive impairment, along with mood, have found no benefit.

Generally speaking, no supplement stands out for brain benefits. Longtime stalwarts in some circles, including ginkgo biloba and vitamins B, D, and E, haven’t yielded protection from cognitive impairment in studies. So until we can get the effects of exercise into pills, the best we can do for cognitive enhancement is regular physical activity … perhaps with a dose of engagement with other brains.

The benefits of exercise and social interaction are a two-way street

When I talk about “being social,” the definition is broad and largely references connections between brains, in person or from far away in time or space. You and I are making a connection right now. Hello!

What I found in writing The Tailored Brain is an interesting interaction among a few easily accessible tools that seem to best serve our brains. You’ve met one: physical activity. Another is making connections with other people. When we connect with other people and hear their stories, we can boost general thinking capacity and enhance the influence of being physically active. Both can ease stress and anxiety, sand the edges off a bad mood, and lighten cognitive loads.

Strong social links on their own offer life span benefits that could be on par with quitting smoking. A 2020 study in China of almost 8,000 people age 45 or older found that social behaviors, including engaging in sports, benefit cognitive skills. The authors also concluded that the window of opportunity to take up these practices and gain improvements stays open into old age.

The benefits of exercise and social interaction are a two-way street. Physical activity eases anxiety, stress, and an overloaded brain, which makes space for us to truly engage socially. It’s tough to have empathy when your brain is sitting there like the “this is fine” meme featuring the dog in the room on fire. There’s no space left to react to, or try to interact with, or understand others.

But if we move around with others, as generations of humans have before us, we make that space. And if we share our burdens with each other on an evening walk, we get brain-boosting exercise and brain ease all at once, perhaps in a way that feels less forced and more like a fit for the brains that nature gave us.

Emily Willingham is a science journalist and author of The Tailored Brain: From Ketamine, to Keto, to Companionship, A User’s Guide to Feeling Better and Thinking Smarter (Basic Books, 2021) and Phallacy: Life Lessons from the Animal Penis (Avery, 2020). She is a regular contributor to Scientific American.

Emily Willingham is a science journalist and author of The Tailored Brain: From Ketamine, to Keto, to Companionship, A User’s Guide to Feeling Better and Thinking Smarter (Basic Books, 2021) and Phallacy: Life Lessons from the Animal Penis (Avery, 2020). She is a regular contributor to Scientific American.

Source: The brain benefits of exercising with other people – Vox

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What Happens To Our Brains When We Get Depressed

In the ’90s, when he was a doctoral student at the University of Lausanne, in Switzerland, neuroscientist Sean Hill spent five years studying how cat brains respond to noise. At the time, researchers knew that two regions—the cerebral cortex, which is the outer layer of the brain, and the thalamus, a nut-like structure near the centre—did most of the work. But, when an auditory signal entered the brain through the ear, what happened, specifically?

Which parts of the cortex and thalamus did the signal travel to? And in what order? The answers to such questions could help doctors treat hearing loss in humans. So, to learn more, Hill, along with his supervisor and a group of lab techs, anaesthetized cats and inserted electrodes into their brains to monitor what happened when the animals were exposed to sounds, which were piped into their ears via miniature headphones. Hill’s probe then captured the brain signals the noises generated.

The last step was to euthanize the cats and dissect their brains, which was the only way for Hill to verify where he’d put his probes. It was not a part of the study he enjoyed. He’d grown up on a family farm in Maine and had developed a reverence for all sentient life. As an undergraduate student in New Hampshire, he’d experimented on pond snails, but only after ensuring that each was properly anaesthetized. “I particularly loved cats,” he says, “but I also deeply believed in the need for animal data.” (For obvious reasons, neuroscientists cannot euthanize and dissect human subjects.)

Over time, Hill came to wonder if his data was being put to the best possible use. In his cat experiments, he generated reels of magnetic tape—printouts that resembled player piano scrolls. Once he had finished analyzing the tapes, he would pack them up and store them in a basement. “It was just so tangible,” he says. “You’d see all these data coming from the animals, but then what would happen with it? There were boxes and boxes that, in all likelihood, would never be looked at again.” Most researchers wouldn’t even know where to find them.

Hill was coming up against two interrelated problems in neuroscience: data scarcity and data wastage. Over the past five decades, brain research has advanced rapidly—we’ve developed treatments for Parkinson’s and epilepsy and have figured out, if only in the roughest terms, which parts of the brain produce arousal, anger, sadness, and pain—but we’re still at the beginning of the journey.

Scientists are still some way, for instance, from knowing the size and shape of each type of neuron (i.e., brain cell), the RNA sequences that govern their behavior, or the strength and frequency of the electrical signals that pass between them. The human brain has 86 billion neurons. That’s a lot of data to collect and record.

But, while brain data is a precious resource, scientists tend to lock it away, like secretive art collectors. Labs the world over are conducting brain experiments using increasingly sophisticated technology, from hulking magnetic-imaging devices to microscopic probes. These experiments generate results, which then get published in journals. Once each new data set has served this limited purpose, it goes . . . somewhere, typically onto a secure hard drive only a few people can access.

Hill’s graduate work in Lausanne was at times demoralizing. He reasoned that, for his research to be worth the costs to both the lab that conducted it and the cats who were its subjects, the resulting data—perhaps even all brain data—should live in the public domain. But scientists generally prefer not to share. Data, after all, is a kind of currency: it helps generate findings, which lead to jobs, money, and professional recognition. Researchers are loath to simply give away a commodity they worked hard to acquire. “There’s an old joke,” says Hill, “that neuroscientists would rather share toothbrushes than data.”

He believes that, if they don’t get over this aversion—and if they continue to stash data in basements and on encrypted hard drives—many profound questions about the brain will remain unanswered. This is not just a matter of academic curiosity: if we improve our understanding of the brain, we could develop treatments that have long eluded us for major mental illnesses.

In 2019, Hill became director of Toronto’s Krembil Centre for Neuroinformatics (KCNI), an organization working at the intersection of neuroscience, information management, brain modelling, and psychiatry. The basic premise of neuroinformatics is this: the brain is big, and if humans are going to have a shot at understanding it, brain science must become big too. The KCNI’s goal is to aggregate brain data and use it to build computerized models that, over time, become ever more complex—all to aid them in understanding the intricacy of a real brain.

There are about thirty labs worldwide explicitly dedicated to such work, and they’re governed by a central regulatory body, the International Neuroinformatics Coordinating Facility, in Sweden. But the KCNI stands out because it’s embedded in a medical institution: the Centre for Addiction and Mental Health (CAMH), Canada’s largest psychiatric hospital. While many other neuroinformatics labs study genetics or cognitive processing, the KCNI seeks to demystify conditions like schizophrenia, anxiety, and dementia. Its first area of focus is depression.

Fundamentally, we don’t have a biological understanding of depression.

The disease affects more than 260 million people around the world, but we barely understand it. We know that the balance between the prefrontal cortex (at the front of the brain) and the anterior cingulate cortex (tucked just behind it) plays some role in regulating mood, as does the chemical serotonin. But what actually causes depression? Is there a tiny but important area of the brain that researchers should focus on?

And does there even exist a singular disorder called depression, or is the label a catch-all denoting a bunch of distinct disorders with similar symptoms but different brain mechanisms? “Fundamentally,” says Hill, “we don’t have a biological understanding of depression or any other mental illness.”

The problem, for Hill, requires an ambitious, participatory approach. If neuroscientists are to someday understand the biological mechanisms behind mental illness—that is, if they are to figure out what literally happens in the brain when a person is depressed, manic, or delusional—they will need to pool their resources. “There’s not going to be a single person who figures it all out,” he says. “There’s never going to be an Einstein who solves a set of equations and shouts, ‘I’ve got it!’ The brain is not that kind of beast.”

The KCNI lab has the feeling of a tech firm. It’s an open-concept space with temporary workstations in lieu of offices, and its glassed-in meeting rooms have inspirational names, like “Tranquility” and “Perception.” The KCNI is a “dry centre”: it works with information and software rather than with biological tissue.

To obtain data, researchers forge relationships with other scientists and try to convince them to share what they’ve got. The interior design choices are a tactical part of this effort. “The space has to look nice,” says Dan Felsky, a researcher at the centre. “Colleagues from elsewhere must want to come in and collaborate with us.”

Yet it’s hard to forget about the larger surroundings. During one interview in the “Clarity” room, Hill and I heard a code-blue alarm, broadcast across CAMH, to indicate a medical emergency elsewhere in the hospital. Hill’s job doesn’t involve front line care, so he doesn’t personally work with patients, but these disruptions reinforce his sense of urgency. “I come from a discipline where scientists focus on theoretical subjects,” he says. “It’s important to be reminded that people are suffering and we have a responsibility to help them.”

Today, the science of mental illness is based primarily on the study of symptoms. Patients receive a diagnosis when they report or exhibit maladaptive behaviours—despair, anxiety, disordered thinking—associated with a given condition. If a significant number of patients respond positively to a treatment, that treatment is deemed effective. But such data reveals nothing about what physically goes on within the brain.

“When it comes to the various diseases of the brain,” says Helena Ledmyr, co-director of the International Neuroinformatics Coordinating Facility, “we know astonishingly little.” Shreejoy Tripathy, a KCNI researcher, gives modern civilization a bit more credit: “The ancient Egyptians would remove the brain when embalming people because they thought it was useless. In theory, we’ve learned a few things since then. In relation to how much we have left to learn, though, we’re not that much further along.”

Joe Herbert, a Cambridge University neuroscientist, offers a revealing comparison between the way mental versus physical maladies are diagnosed. If, in the nineteenth century, you walked into a doctor’s office complaining of shortness of breath, the doctor would likely diagnose you with dyspnea, a word that basically means . . . shortness of breath.

Today, of course, the doctor wouldn’t stop there: they would take a blood sample to see if you were anemic, do an X-ray to search for a collapsed lung, or subject you to an echocardiogram to spot signs of heart disease. Instead of applying a Greek label to your symptoms, they’d run tests to figure out what was causing them.

Herbert argues that the way we currently diagnose depression is similar to how we once diagnosed shortness of breath. The term depression is likely as useful now as dyspnea was 150 years ago: it probably denotes a range of wildly different maladies that just happen to have similar effects. “Psychiatrists recognize two types of depression—or three, if you count bipolar—but that’s simply on the basis of symptoms,” says Herbert. “Our history of medicine tells us that defining a disease by its symptoms is highly simplistic and inaccurate.”

The advantage of working with models, as the KCNI researchers do, is that scientists can experiment in ways not possible with human subjects. They can shut off parts of the model brain or alter the electrical circuitry. The disadvantage is that models are not brains. A model is, ultimately, a kind of hypothesis—an illustration, analogy, or computer simulation that attempts to explain or replicate how a certain brain process works.

Over the centuries, researchers have created brain models based on pianos, telephones, and computers. Each has some validity—the brain has multiple components working in concert, like the keys of a piano; it has different nodes that communicate with one another, like a telephone network; and it encodes and stores information, like a computer—but none perfectly describes how a real brain works. Models may be useful abstractions, but they are abstractions nevertheless.

Yet, because the brain is vast and mysterious and hidden beneath the skull, we have no choice but to model it if we are to study it. Debates over how best to model it, and whether such modelling should be done at the micro or macro scale, are hotly contested in neuroscience. But Hill has spent most of his life preparing to answer these questions.

Hill grew up in the ’70s and ’80s, in an environment entirely unlike the one in which he works. His parents were adherents of the back-to-the-land movement, and his father was an occasional artisanal toymaker. On their farm, near the coast of Maine, the family grew vegetables and raised livestock using techniques not too different from those of nineteenth-century homesteaders. They pulled their plough with oxen and, to fuel their wood-burning stove, felled trees with a manual saw.

When Hill and his older brother found out that the local public school had acquired a TRS-80, an early desktop computer, they became obsessed. The math teacher, sensing their passion, decided to loan the machine to the family for Christmas. Over the holidays, the boys became amateur programmers. Their favourite application was Dancing Demon, in which a devilish figure taps its feet to an old swing tune. Pretty soon, the boys had hacked the program and turned the demon into a monster resembling Boris Karloff in Frankenstein. “In the dark winter of Maine,” says Hill, “what else were we going to do?”

The experiments spurred conversation among the brothers, much of it the fevered speculation of young people who’ve read too much science fiction. They fantasized about the spaceships they would someday design. They also discussed the possibility of building a computerized brain. “I was probably ten or eleven years old,” Hill recalls, “saying to my brother, ‘Will we be able to simulate a neuron? Maybe that’s what we need to get artificial intelligence.’”

Roughly a decade later, as an undergraduate at the quirky liberal arts university Hampshire College, Hill was drawn to computational neuroscience, a field whose practitioners were doing what he and his brother had talked about: building mathematical, and sometimes even computerized, brain models.

In 2006, after completing his PhD, along with postgraduate studies in San Diego and Wisconsin, Hill returned to Lausanne to co-direct the Blue Brain Project, a radical brain-modelling lab in the Swiss Alps. The initiative had been founded a year earlier by Henry Markram, a South African Israeli neuroscientist whose outsize ambitions had made him a revered and controversial figure.

In neuroscience today, there are robust debates as to how complex a brain model should be. Some researchers seek to design clean, elegant models. That’s a fitting description of the Nobel Prize–winning work of Alan Hodgkin and Andrew Huxley, who, in 1952, drew handwritten equations and rudimentary illustrations—with lines, symbols, and arrows—describing how electrical signals exit a neuron and travel along a branch-like cable called an axon.

Other practitioners seek to make computer-generated maps that incorporate hundreds of neurons and tens of thousands of connections, image fields so complicated that Michelangelo’s Sistine Chapel ceiling looks minimalist by comparison. The clean, simple models demystify brain processes, making them understandable to humans. The complex models are impossible to comprehend: they offer too much information to take in, attempting to approximate the complexity of an actual brain.

Markram’s inclinations are maximalist. In a 2009 TED Talk, he said that he aimed to build a computer model so comprehensive and biologically accurate that it would account for the location and activity of every human neuron. He likened this endeavour to mapping out a rainforest tree by tree. Skeptics wondered whether such a project was feasible. The problem isn’t merely that there are numerous trees in a rainforest: it’s also that each tree has its own configuration of boughs and limbs. The same is true of neurons.

Each is a microscopic, blob-like structure with dense networks of protruding branches called axons and dendrites. Neurons use these branches to communicate. Electrical signals run along the axons of one neuron and then jump, over a space called a synapse, to the dendrites of another. The 86 billion neurons in the human brain each have an average of 10,000 synaptic connections. Surely, skeptics argued, it was impossible, using available technology, to make a realistic model from such a complicated, dynamic system.

In 2006, Markram and Hill got to work. The initial goal was to build a hyper-detailed, biologically faithful model of a “microcircuit” (i.e., a cluster of 31,000 neurons) found within the brain of a rat. With a glass probe called a patch clamp, technicians at the lab penetrated a slice of rat brain, connected to each individual neuron, and recorded the electrical signals it sent out.

By injecting dye into the neurons, the team could visualize their shape and structure. Step by step, neuron by neuron, they mapped out the entire communication network. They then fed the data into a model so complex that it required Blue Gene, the IBM supercomputer, to run.

In 2015, they completed their rat microcircuit. If they gave their computerized model certain inputs (say, a virtual spark in one part of the circuit), it would predict an output (for instance, an electrical spark elsewhere) that corresponded to biological reality. The model wasn’t doing any actual cognitive processing: it wasn’t a virtual brain, and it certainly wasn’t thinking.

But, the researchers argued, it was predicting how electrical signals would move through a real circuit inside a real rat brain. “The digital brain tissue naturally behaves like the real brain tissue,” reads a statement on the Blue Brain Project’s website. “This means one can now study this digital tissue almost like one would study real brain tissue.”

The breakthrough, however, drew fresh criticisms. Some neuroscientists questioned the expense of the undertaking. The team had built a multimillion-dollar computer program to simulate an already existing biological phenomenon, but so what? “The question of ‘What are you trying to explain?’ hadn’t been answered,” says Grace Lindsay, a computational neuroscientist and author of the book Models of the Mind. “A lot of money went into the Blue Brain Project, but without some guiding goal, the whole thing seemed too open ended to be worth the resources.”

Others argued that the experiment was not just profligate but needlessly convoluted. “There are ways to reduce a big system down to a smaller system,” says Adrienne Fairhall, a computational neuroscientist at the University of Washington. “When Boeing was designing airplanes, they didn’t build an entire plane just to figure out how air flows around the wings. They scaled things down because they understood that a small simulation could tell them what they needed to know.” Why seek complexity, she argues, at the expense of clarity and elegance?

The harshest critics questioned whether the model even did what it was supposed to do. When building it, the team had used detailed information about the shape and electrical signals of each neuron. But, when designing the synaptic connections—that is, the specific locations where the branches communicate with one another—they didn’t exactly mimic biological reality, since the technology for such detailed brain mapping didn’t yet exist. (It does now, but it’s a very recent development.)

Instead, the team built an algorithm to predict, based on the structure of the neurons and the configuration of the branches, where the synaptic connections were likely to be. If you know the location and shape of the trees, they reasoned, you don’t need to perfectly replicate how the branches intersect.

But Moritz Helmstaedter—a director at the Max Planck Institute for Brain Research, in Frankfurt, Germany, and an outspoken critic of the project—questions whether this supposition is true. “The Blue Brain model includes all kinds of assumptions about synaptic connectivity, but what if those assumptions are wrong?” he asks. The problem, for Helmstaedter, isn’t just that the model could be inaccurate: it’s that there’s no way to fully assess its accuracy given how little we know about brain biology.

If a living rat encounters a cat, its brain will generate a flight signal. But, if you present a virtual input representing a cat’s fur to the Blue Brain model, will the model generate a virtual flight signal too? We can’t tell, Helmstaedter argues, in part because we don’t know, in sufficient detail, what a flight signal looks like inside a real rat brain.

Hill takes these comments in stride. To criticisms that the project was too open-ended, he responds that the goal wasn’t to demystify a specific brain process but to develop a new kind of brain modelling based in granular biological detail.

The objective, in other words, was to demonstrate—to the world and to funders—that such an undertaking was possible. To criticisms that the model may not work, Hill contends that it has successfully reproduced thousands of experiments on actual rats. Those experiments hardly prove that the simulation is 100 percent accurate—no brain model is—but surely they give it credibility.

And, to criticisms that the model is needlessly complicated, he counters that the brain is complicated too. “We’d been hearing for decades that the brain is too complex to be modelled comprehensively,” says Hill. “Markram put a flag in the ground and said, ‘This is achievable in a finite amount of time.

The specific length of time is a matter of some speculation. In his TED Talk, Markram implied that he might build a detailed human brain model by 2019, and he began raising money toward a new initiative, the Human Brain Project, meant to realize this goal. But funding dried up, and Markram’s predictions came nowhere close to
panning out.

The Blue Brain Project, however, remains ongoing. (The focus, now, is on modelling a full mouse brain.) For Hill, it offers proof of concept for the broader mission of neuroinformatics. It has demonstrated, he argues, that when you systemize huge amounts of data, you can build platforms that generate reliable insights about the brain. “We showed that you can do incredibly complex data integration,” says Hill, “and the model will give rise to biologically realistic responses.”

When Hill was approached by recruiters on behalf of CAMH to ask if he might consider leaving the Blue Brain Project to start a neuroinformatics lab in Toronto, he demurred. “I’d just become a Swiss citizen,” he says, “and I didn’t want to go.” But the hospital gave him a rare opportunity: to practice cutting-edge neuroscience in a clinical setting. CAMH was formed, in 1998, through a merger of four health care and research institutions.

It treats over 34,000 psychiatric patients each year and employs more than 140 scientists, many of whom study the brain. Its mission, therefore, is both psychiatric and neuroscientific—a combination that appealed to Hill. “I’ve spoken to psychiatrists who’ve told me, ‘Neuroscience doesn’t matter,’” he says. “In their work, they don’t think about brain biology. They think about treating the patient in front of them.” Such biases, he argues, reveal a profound gap between brain research and the illnesses that clinicians see daily. At the KCNI, he’d have a chance to bridge that gap.

The business of data-gathering and brain-modelling may seem dauntingly abstract, but the goal, ultimately, is to figure out what makes us human. The brain, after all, is the place where our emotional, sensory, and imaginative selves reside. To better understand how the modelling process works, I decided to shadow a researcher and trace an individual data point from its origins in a brain to its incorporation in a KCNI model.

Last February, I met Homeira Moradi, a neuroscientist at Toronto Western Hospital’s Krembil Research Institute who shares data with the KCNI. Because of where she works, she has access to the rarest and most valuable resource in her field: human brain tissue. I joined her at 9 a.m., in her lab on the seventh floor. Below us, on the ground level, Taufik Valiante, a neurosurgeon, was operating on an epileptic patient. To treat epilepsy and brain cancer, surgeons sometimes cut out small portions of the brain. But, to access the damaged regions, they must also remove healthy tissue in the neocortex, the high-functioning outer layer of the brain.

Moradi gets her tissue samples from Valiante’s operating room, and when I met her, she was hard at work weighing and mixing chemicals. The solution in which her tissue would sit would have to mimic, as closely as possible, the temperature and composition of an actual brain. “We have to trick the neurons into thinking they’re still at home,” she said.

She moved at the frenetic pace of a line cook during a dinner rush. At some point that morning, Valiante’s assistant would text her from the OR to indicate that the tissue was about to be extracted. When the message came through, she had to be ready. Once the brain sample had been removed from the patient’s head, the neurons within it would begin to die. At best, Moradi would have twelve hours to study the sample before it expired.

The text arrived at noon, by which point we’d been sitting idly for an hour. Suddenly, we sprang into action. To comply with hospital policy, which forbids Moradi from using public hallways where a visitor may spot her carrying a beaker of brains, we approached the OR indirectly, via a warren of underground tunnels.

The passages were lined with gurneys and illuminated, like catacombs in an Edgar Allan Poe story, by dim, inconsistent lighting. I hadn’t received permission to witness the operation, so I waited for Moradi outside the OR and was able to see our chunk of brain only once we’d returned to the lab. It didn’t look like much—a marble-size blob, gelatinous and slightly bloody, like gristle on a steak.

Under a microscope, though, the tissue was like nothing I’d ever seen. Moradi chopped the sample into thin pieces, like almond slices, which went into a small chemical bath called a recording chamber. She then brought the chamber into another room, where she kept her “rig”: an infrared microscope attached to a manual arm.

She put the bath beneath the lens and used the controls on either side of the rig to operate the arm, which held her patch clamp—a glass pipette with a microscopic tip. On a TV monitor above us, we watched the pipette as it moved through layers of brain tissue resembling an ancient root system—tangled, fibrous, and impossibly dense.

Moradi needed to bring the clamp right up against the wall of a cell. The glass had to fuse with the neuron without puncturing the membrane. Positioning the clamp was maddeningly difficult, like threading the world’s smallest needle. It took her the better part of an hour to connect to a pyramidal neuron, one of the largest and most common cell types in our brain sample.

Once we’d made the connection, a filament inside the probe transmitted the electrical signals the neuron sent out. They went first into an amplifier and then into a software application that graphed the currents—strong pulses with intermittent weaker spikes between them—on an adjacent computer screen. “Is that coming from the neuron?” I asked, staring at the screen. “Yes,” Moradi replied. “It’s talking to us.”

A depressive brain is a noisy one. What if scientists could locate the neurons causing the problem?

It had taken us most of the day, but we’d successfully produced a tiny data set—information that may be relevant to the study of mental illness. When neurons receive electrical signals, they often amplify or dampen them before passing them along to adjacent neurons. This function, called gating, enables the brain to select which stimuli to pay attention to. If successive neurons dampen a signal, the signal fades away.

If they amplify it, the brain attends more closely. A popular theory of depression holds that the illness has something to do with gating. In depressive patients, neurons may be failing to dampen specific signals, thereby inducing the brain to ruminate unnecessarily on negative thoughts. A depressive brain, according to this theory, is a noisy one. It is failing to properly distinguish between salient and irrelevant stimuli. But what if scientists could locate and analyze a specific cluster of neurons (i.e., a circuit) that was causing the problem?

Etay Hay, an Israeli neuroscientist and one of Hill’s early hires at the KCNI, is attempting to do just that. Using Moradi’s data, he’s building a model of a “canonical” circuit—that is, a circuit that appears thousands of times, with some variations, in the outer layer of the brain. He believes a malfunction in this circuit may underlie some types of treatment-resistant depression.

The circuit contains pyramidal neurons, like the one Moradi recorded from, that communicate with smaller cells, called interneurons. The interneurons dampen the signals the pyramidal neurons send them. It’s as if the interneurons are turning down the volume on unwanted thoughts. In a depressive brain, however, the interneurons may be failing to properly reduce the signals, causing the patient to get stuck in negative-thought loops.

Etienne Sibille, another CAMH neuroscientist, has designed a drug that increases communication between the interneurons and the pyramidal neurons in Hay’s circuit. In theory, this drug should enable the interneurons to better do their job, tamp down on negative thoughts, and improve cognitive function.

This direct intervention, which occurs at the cellular level, could be more effective than the current class of antidepressants, called SSRIs, which are much cruder. “They take a shotgun approach to depression,” says Sibille, “by flooding the entire brain with serotonin.” (That chemical, for reasons we don’t fully understand, can reduce depressive symptoms, albeit only in some people.)

Sibille’s drug, however, is more targeted. When he gives it to mice who seem listless or fearful, they perk up considerably. Before testing it on humans, Sibille hopes to further verify its efficacy. That’s where Hay comes in. He has finished his virtual circuit and is now preparing to simulate Sibille’s treatment. If the simulation reduces the overall amount of noise in the circuit, the drug can likely proceed to human trials, a potentially game-changing breakthrough.

Hill’s other hires at the KCNI have different specialties from Hay’s but similar goals. Shreejoy Tripathy is building computer models to predict how genes affect the shape and behaviour of neurons. Andreea Diaconescu is using video games to collect data that will allow her to better model early stage psychosis.

This can be used to predict symptom severity and provide more effective treatment plans. Joanna Yu is building the BrainHealth Databank, a digital repository for anonymized data—on symptoms, metabolism, medications, and side effects—from over 1,000 CAMH patients with depression. Yu’s team will employ AI to analyze the information and predict which treatment may offer the best outcome for each individual.

Similarly, Dan Felsky is helping to run a five-year study on over 300 youth patients at CAMH, incorporating data from brain scans, cognitive tests, and doctors’ assessments. “The purpose,” he says, “is to identify signs that a young person may go on to develop early adult psychosis, one of the most severe manifestations of mental illness.”

All of these researchers are trained scientists, but their work can feel more like engineering: they’re each helping to build the digital infrastructure necessary to interpret the data they bring in.

Sibille’s work, for instance, wouldn’t have been possible without Hay’s computer model, which in turn depends on Moradi’s brain-tissue lab, in Toronto, and on data from hundreds of neuron recordings conducted in Seattle and Amsterdam. This collaborative approach, which is based in data-sharing agreements and trust-based relationships, is incredibly efficient. With a team of three trainees, Hay built his model in a mere twelve months. “If just one lab was generating my data,” he says, “I’d have kept it busy for twenty years.” Read more……

Simon Lewsen, a Toronto-based writer, contributes to Azure, Precedent, enRoute, the Globe and Mail, and The Atlantic. In 2020, he won a National Magazine Award.

Source: What Happens to Our Brains When We Get Depressed? | The Walrus

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Hey, There’s a Second Brain In Your Gut

Scientists have known for years that there’s a “second brain” of autonomous neurons in your long, winding human digestive tract—but that’s about where their knowledge of the so-called abdominal brain ends.

Now, research published in 2020 shows that scientists have catalogued 12 different kinds of neurons in the enteric nervous system (ENS) of mice. This “fundamental knowledge” unlocks a huge number of paths to new experiments and findings.

The gut brain greatly affects on how you body works. Your digestive system has a daily job to do as part of your metabolism, but it’s also subject to fluctuations in functionality, and otherwise related to your emotions.

More: Getting the Inside Dope on Ketamine’s Mysterious Ability to Rapidly Relieve Depression

Digestive symptoms and anxiety can be comorbid, and your gut is heavily affected by stress. So scientists believe having a better understanding of what happens in your ENS could lead to better medicines and treatments for a variety of conditions, as well as improved knowledge of the connection between the ENS and central nervous system.

The research appears in Nature Neuroscience. In a related commentary, scientist Julia Ganz explains what the researchers found and why it’s so important:

“Using single-cell RNA-sequencing to profile the developing and juvenile ENS, the authors discovered a conceptually new model of neuronal diversification in the ENS and establish a new molecular taxonomy of enteric neurons based on a plethora of molecular markers.”

Neuronal diversification happens in, well, all the organisms that have neurons. Similar to stem cells, neurons develop first as more generic “blanks” and then into functional specialties. The human brain has types like sensory and motor neurons, each of which has subtypes. There are so many subtypes, in fact, that scientists aren’t sure how to even fully catalog them yet.

More: Here’s How Long Alcohol-Induced Brain Damage Persists After Drinking

Neurons of the same superficial type are different in the brain versus the brain stem—let alone in the digestive tract. So researchers had to start at the very beginning and trace how these neurons develop. They tracked RNA, which determines how DNA is expressed in the cells made by your body, to follow how neurons formed both before and after birth. Some specialties emerge in utero, and some split and form afterward.

To find this new information, the scientists developed a finer way to separate and identify cells. Ganz explains:

“Using extensive co-staining with established markers, they were able to relate the twelve neuron classes to previously discovered molecular characteristics of functional enteric neuron types, thus classifying the ENCs into excitatory and inhibitory motor neurons, interneurons, and intrinsic primary afferent neurons.”

With a sharper protocol and new information, the researchers were able to confirm and expand on the existing body of ENS neuron knowledge. And now they can work on finding out what each of the 12 ENS neuron types is responsible for, they say.

By isolating different kinds and “switching” them on or off using genetic information, scientists can try to identify what’s missing from the function of the mouse ENS. And studying these genes could lead to new treatments that use stem cells or RNA to control the expression of harmful genes.

The Mind-Gut Connection is something that people have intuitively known for a long time but science has only I would say in the last few years gotten a grasp and acceptance of this concept. It essentially means that your brain has intimate connections with the gut and another entity in our gut, the second brain, which is about 100 million nerve cells that are sandwiched in between the layers of the gut.

And they can do a lot of things on their own in terms of regulating our digestive processes. But there’s a very intimate conversation between that little brain, the second brain in the gut and our main brain. They use the same neurotransmitters. They’re connected by nerve pathways. And so we have really an integrated system from our brain to the little brain in the gut and it goes in both directions.

The little brain, or the second brain, in the gut you’re not able to see it because as I said it’s spread out through the entire length of the gut from your esophagus to the end of your large intestine, several layers of nerve cells interconnected. And what they do is even if you – and you can do this in animal experiments if you completely disconnect this little brain in the gut from your main brain this little brain can completely take care of all the digestive processes, the contractions, peristaltic reflex, regulation of blood flow in the intestine.

And it has many sensors so it knows exactly what’s going on inside the gut, what goes on in the wall of the gut, any distention, any chemicals. All of this is being picked up by these sensory nerves, fed into the interior nervous system, the second brain. And then the second brain generates these stereotypic responses. So when you vomit, when you have diarrhea, when you have normal digestion, all of this is encoded in programs in your second brain.

What the second brain can’t do it cannot generate any conscious perceptions or gut feelings. That really is the only ability that allows us to do this and perceive all the stuff that goes on inside of us is really the big brain and the specific areas and circuits within the brain that process information that comes up from the gut. Still most of that information is not really consciously perceived. So 95 percent of all this massive amount of information coming from the gut is processed, integrated with other inputs that the brain gets from the outside, from smell, visual stimuli.

And only a very small portion is then actually made conscious. So when you feel good after a meal or when you ate the wrong thing and you’re nauseated those are the few occasions where actually we realize and become aware of our gut feelings. Even though a lot of other stuff is going on in this brain-gut access all the time.

When we talk about the connection between depression and the gut there’s some very intriguing observations both clinically but also now more recently scientifically that make it highly plausible that there is an integrate connection between serotonin in the gut, serotonin in our food, depression and gut function.

By: Caroline Delbert

Caroline Delbert is a writer, book editor, researcher, and avid reader. She’s also an enthusiast of just about everything.

Source: Pocket

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Critics:

The enteric nervous system (ENS) or intrinsic nervous system is one of the main divisions of the autonomic nervous system (ANS) and consists of a mesh-like system of neurons that governs the function of the gastrointestinal tract. It is capable of acting independently of the sympathetic and parasympathetic nervous systems, although it may be influenced by them. The ENS is also called the second brain. It is derived from neural crest cells.

The enteric nervous system is capable of operating independently of the brain and spinal cord,but does rely on innervation from the autonomic nervous system via the vagus nerve and prevertebral ganglia in healthy subjects. However, studies have shown that the system is operable with a severed vagus nerve.

The neurons of the enteric nervous system control the motor functions of the system, in addition to the secretion of gastrointestinal enzymes. These neurons communicate through many neurotransmitters similar to the CNS, including acetylcholine, dopamine, and serotonin. The large presence of serotonin and dopamine in the gut are key areas of research for neurogastroenterologists.

Neurogastroenterology societies

See also

3 Simple Habits That Can Protect Your Brain From Cognitive Decline

You might think that the impact of aging on the brain is something you can’t do much about. After all, isn’t it an inevitability? To an extent, as we may not be able to rewind the clock and change our levels of higher education or intelligence (both factors that delay the onset of symptoms of aging).

But adopting specific lifestyle behaviors–whether you’re in your thirties or late forties–can have a tangible effect on how well you age. Even in your fifties and beyond, activities like learning a new language or musical instrument, taking part in aerobic exercise, and developing meaningful social relationships can do wonders for your brain. There’s no question that when we compromise on looking after ourselves, our aging minds pick up the tab.

The Aging Process and Cognitive Decline

Over time, there is a build-up of toxins such as tau proteins and beta-amyloid plaques in the brain that correlate to the aging process and associated cognitive decline. Although this is a natural part of growing older, many factors can exacerbate it. Stress, neurotoxins such as alcohol and lack of (quality and quantity) sleep can speed up the process.

Neuroplasticity–the function that allows the brain to change and develop in our lifetime–has three mechanisms: synaptic connection, myelination, and neurogenesis. The key to resilient aging is improving neurogenesis, the birth of new neurons. Neurogenesis happens far more in babies and children than adults.

A 2018 study by researchers at Columbia University shows that in adults, this type of neuroplastic activity occurs in the hippocampus, the part of the brain that lays down memories. This makes sense as we respond to and store new experiences every day, and cement them during sleep. The more we can experience new things, activities, people, places, and emotions, the more likely we are to encourage neurogenesis.

With all this in mind, we can come up with a three-point plan to encourage “resilient aging” by activating neurogenesis in the brain:

1. Get your heart rate up

Aerobic exercise such as running or brisk walking has a potentially massive impact on neurogenesis. A 2016 rat study found that endurance exercise was most effective in increasing neurogenesis. It wins out over HIIT sessions and resistance training, although doing a variety of exercise also has its benefits.

Aim to do aerobic exercise for 150 minutes per week, and choose the gym, the park, or natural landscape over busy roads to avoid compromising brain-derived neurotrophic factor production (BDNF), a growth factor that encourages neurogenesis that aerobic exercise can boost. However, exercising in polluted areas decreases production.

If exercising alone isn’t your thing, consider taking up a team sport or one with a social element like table tennis. Exposure to social interaction can also increase the neurogenesis, and in many instances, doing so lets you practice your hand-eye coordination, which research has suggested leads to structural changes in the brain that may relate to a range of cognitive benefit. This combination of coordination and socializing has been shown to increase brain thickness in the parts of the cortex related to social/emotional welfare, which is crucial as we age.

2. Change your eating patterns

Evidence shows that calorie restriction, intermittent fasting, and time-restricted eating encourage neurogenesis in humans. In rodent studies, intermittent fasting has been found to improve cognitive function and brain structure, and reduce symptoms of metabolic disorders such as diabetes.

Reducing refined sugar will help reduce oxidative damage to brain cells, too, and we know that increased oxidative damage has been linked with a higher risk of developing Alzheimer’s disease. Twenty-four hour water-only fasts have also been proven to increase longevity and encourage neurogenesis.

Try any of the following, after checking with your doctor:

  • 24-hour water-only fast once a month
  •  Reducing your calorie intake by 50%-60% on two non-consecutive days of the week for two to three months or on an ongoing basis
  • Reducing calories by 20% every day for two weeks. You can do this three to four times a year
  • Eating only between 8 a.m. to 8 p.m., or 12 p.m. to 8 p.m. as a general rule

3. Prioritize sleep

Sleep helps promote the brain’s neural “cleaning” glymphatic system, which flushes out the build-up of age-related toxins in the brain (the tau proteins and beta amyloid plaques mentioned above). When people are sleep-deprived, we see evidence of memory deficits, and if you miss a whole night of sleep, research proves that it impacts IQ. Aim for seven to nine hours, and nap if it suits you. Our need to sleep decreases as we age.

Of course, there are individual exceptions, but having consistent sleep times and making sure you’re getting sufficient quality and length of sleep supports brain resilience over time. So how do you know if you’re getting enough? If you naturally wake up at the same time on weekends that you have to during the week, you probably are.

If you need to lie-in or take long naps, you’re probably not. Try practicing mindfulness or yoga nidra before bed at night, a guided breath-based meditation that has been shown in studies to improve sleep quality. There are plenty of recordings online if you want to experience it.

Pick any of the above that work for you and build it up until it becomes a habit, then move onto the next one and so on. You might find that by the end of the year, you’ll feel even healthier, more energized, and motivated than you do now, even as you turn another year older.

By: Fast Company / Tara Swart

Dr. Tara Swart is a neuroscientist, leadership coach, author, and medical doctor. Follow her on Twitter at @TaraSwart.

Source: Open-Your-Mind-Change

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Critics:

Cognitive deficit is an inclusive term to describe any characteristic that acts as a barrier to the cognition process.

The term may describe

Mild cognitive impairment (MCI) is a neurocognitive disorder which involves cognitive impairments beyond those expected based on an individual’s age and education but which are not significant enough to interfere with instrumental activities of daily living. MCI may occur as a transitional stage between normal aging and dementia, especially Alzheimer’s disease. It includes both memory and non-memory impairments.Mild cognitive impairment has been relisted as mild neurocognitive disorder in DSM-5, and in ICD-11.

The cause of the disorder remains unclear, as well as its prevention and treatment. MCI can present with a variety of symptoms, but is divided generally into two types.

Amnestic MCI (aMCI) is mild cognitive impairment with memory loss as the predominant symptom; aMCI is frequently seen as a prodromal stage of Alzheimer’s disease. Studies suggest that these individuals tend to progress to probable Alzheimer’s disease at a rate of approximately 10% to 15% per year.[needs update]It is possible that being diagnosed with cognitive decline may serve as an indicator of aMCI.

Nonamnestic MCI (naMCI) is mild cognitive impairment in which impairments in domains other than memory (for example, language, visuospatial, executive) are more prominent. It may be further divided as nonamnestic single- or multiple-domain MCI, and these individuals are believed to be more likely to convert to other dementias (for example, dementia with Lewy bodies).

See also

Scientists Find an Odd Link Between Aspirin, Air Pollution, and Male Brains

If you look at the smudged skylines of Los Angeles, California or Beijing, China, the haziness creates the illusion of cities shrouded in perpetual gray. That smog is driven by a pollutant that doesn’t just ruin the view — it worms its way into the brain, influencing the health of people exposed.

In a new study, scientists find another reason why air pollution is bad for the brain — this time zeroing in on the effect it has on men’s brain health. The study examines the negative effect of fine particulate matter, also known as PM 2.5 pollution. You might know it as black carbon or “soot.”

“Our study is the first one that demonstrates that exposure to PM2.5, even just over a few weeks, can impair cognitive performance,” lead author Xu Gao tells Inverse. Gao is an assistant professor at Peking University and a researcher affiliated with Columbia University.

What’s new — Scientists are increasingly unearthing new information about how the tainted air we breathe harms our bodies, whether it’s worsening the severity of Covid-19 or reducing men’s sperm count.

Gao and colleagues found air pollution is associated with considerable negative short-term effects on cognitive health in a sample of older white men. This finding was published Monday in the journal Nature Aging.

The study suggests PM 2.5 levels not usually considered hazardous can still cause individuals to suffer from cognitive decline due to short-term air pollution. This implies “there is no safe zone for PM 2.5,” Gao says.

Interestingly, the researchers found that men who take what’s known as non-steroidal anti-inflammatory drugs (NSAIDS) did not suffer as many harmful effects from PM 2.5 pollution. These anti-inflammatory medications include pills like aspirin.

This finding emerged although NSAIDs don’t have any known relationship to cognitive performance. The researchers suspect NSAIDs have a “modifying effect” on the inflammatory responses prompted by inhaling polluted air.

These findings are preliminary — Gao says it’s too early to endorse taking NSAIDs as a way to protect oneself from air pollution. However, he does venture to say people on these medications “may have additional benefits.”

Air pollution is associated with an ever-growing laundry list of health risks, including:

PM 2.5 pollution is especially harmful. These tiny air particles are 2.5 microns or less in size — for comparison, human hair is roughly 70 microns in diameter. This category of pollution is why you see gray horizons in cities like Los Angeles — it’s associated with smog and poor air quality. It’s arguably the greatest environmental risk factor for human mortality.

But there is some good news amidst all this doom and gloom. Some recent studies, for example, suggest exercise can offset some of the harmful effects of air pollution — even in urban areas.

Air pollution deaths have also declined by half between 1990 and 2010, correlating with improved federal regulations on air quality. But it can still do considerable short-term and long-term damage to the human mind, according to this latest Nature Aging study.

How they did it — The scientists analyzed data from 954 men in the Boston area between 1995 and 2021. The average age of a man in the study data was 69-years-old. None had chronic health conditions, but 64 percent were former smokers.

The participants were also questioned about their use of NSAIDs, including aspirin. They also took cognitive tests, including tests on their ability to remember words and repeat numbers, as well as screening exercises used to test for dementia.The researchers also analyzed this data in conjunction with information on weather patterns in the Boston area, since air pollution varies by season and is greater in the winter.

Finally, they obtained data on air pollution from a Harvard University supersite, which they used as a baseline to measure air pollution in the Greater Boston areas.

Using this information, the researchers were able to paint a picture of cognitive health that correlates with short-term air pollution and also study any potential effects of NSAIDs on cognitive performance.

Why it matters — Media and policymakers have focused, rightly so, on the number of deaths resulting from air pollution each year, which now number 200,000 annually in the U.S — and that’s just from the air that meets EPA standards.

Much less attention has been paid to air pollution’s impacts on short-term and long-term cognitive performance. The research that has been done has found air pollution can impair the cognitive performance of children, and influence cognitive decline in older adults.

Although this new study focuses on short-term effects, the researchers also conducted a sensitivity analysis to include the effects of long-term exposure to air pollution. And while preliminary, the findings don’t bode well for the human mind’s ability to withstand air pollution in the long run.

“We found that both short and long exposures were related to cognitive function,” Gao says. But the study has limitations — The study team acknowledges that their work is just a starting point. Much more research needs to be done to expand on their intriguing findings — and go beyond the scope of the study’s design.

For example, the study only focuses on older white men, “which suggests the possibility that the results might not be generalizable to other ethnic groups and/or women” the team writes. Gao would like to conduct further research involving people of different ages, races, and genders to confirm whether similar effects would occur among various demographics.

“We believe that younger people may have a better adaptive response to air pollution than the elderly. Females are also different from males with respect to health outcomes,” Gao says.

Meanwhile, scientists have long known that communities of color suffer disproportionately from air pollution. A recent Science study found Black and Hispanic individuals experience particularly high levels of PM 2.5 pollution — the subject of this study.

The researchers also analyzed this data in conjunction with information on weather patterns in the Boston area, since air pollution varies by season and is greater in the winter.

But the study has limitations — The study team acknowledges that their work is just a starting point. Much more research needs to be done to expand on their intriguing findings — and go beyond the scope of the study’s design.

What’s next — Ultimately, what’s needed is more information on both the long-term impacts of air pollution on cognitive health and the relationship between NSAIDs and air pollution. This research could be used to inform future policy, both in the U.S. and abroad.

And while Gao suggests NSAIDs could be helpful in treating the cognitive effects of air pollution, it is not a replacement for policies that reduce the actual source of pollution. Recent efforts by the Biden administration to move toward electric vehicles, as well as California’s stricter vehicle emissions standards, could help shift the tide against air pollution.

“Although our study shows that taking NSAIDs may be a solution to air pollution’s harm, [it’s] definitely not the final answer to the threats of air pollution. Changing our policies of air pollution towards a more restrictive manner is still warranted,” Gao says.

But it’s data that drives policy forward — evidence that pollution isn’t just a topic on our minds, it literally influences the brain.

By: Tara Yarlagadda

Source: Scientists find an odd link between aspirin, air pollution, and male brains

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