Posts Tagged ‘neuroscience’

Everyday experience makes it obvious – sometimes frustratingly so – that our working memory capacity is limited. We can only keep so many things consciously in mind at once. The results of a new study may explain why: They suggest that the “coupling,” or synchrony, of brain waves among three key regions breaks down in specific ways when visual working memory load becomes too much to handle.

“When you reach capacity there is a loss of feedback coupling,” said senior author Earl Miller, Picower Professor of Neuroscience at MIT’s Picower Institute for Learning and Memory. That loss of synchrony means the regions can no longer communicate with each other to sustain working memory.

Maximum working memory capacity – for instance the total number of images a person can hold in working memory at the same time – varies by individual but averages about four, Miller said. Researchers have correlated working memory capacity with intelligence.

Understanding what causes working memory to have an intrinsic limit is therefore important because it could help explain the limited nature of conscious thought and optimal cognitive performance, Miller said.

And because certain psychiatric disorders can lower capacity, said Miller and lead author Dimitris Pinotsis, a research affiliate in Miller’s lab, the findings could also explain more about how such disorders interfere with thinking.

“Studies show that peak load is lower in schizophrenics and other patients with neurological or psychiatric diseases and disorders compared to healthy people,” Pinotsis said. “Thus, understanding brain signals at peak load can also help us understand the origins of cognitive impairments.”

The study’s other author is Timothy Buschman, assistant professor at the Princeton University Neuroscience Institute and a former member of the Miller lab.

The new study published in the journal Cerebral Cortex is a detailed statistical analysis of data the Miller lab recorded when animal subjects played a simple game: They had to spot the difference when they were shown a set of squares on a screen and then, after a brief blank screen, a nearly identical set in which one square had changed color. The number of squares involved, hence the working memory load of each round, varied so that sometimes the task exceeded the animals’ capacity.

As the animals played, the researchers measured the frequency and timing of brain waves produced by ensembles of neurons in three regions presumed to have an important – though as yet unknown – relationship in producing visual working memory: the prefrontal cortex (PFC), the frontal eye fields (FEF), and the lateral intraparietal area (LIP).

The researchers’ goal was to characterize the crosstalk among these three areas, as reflected by patterns in the brain waves, and to understand specifically how that might change as load increased to the point where it exceeded capacity.

Though the researchers focused on these three areas, they didn’t know how they might work with each other. Using sophisticated mathematical techniques, they tested scores of varieties of how the regions “couple,” or synchronize, at high- and low-frequencies. The “winning” structure was whichever one best fit the experimental evidence.

“It was very open ended,” Miller said. “We modeled all different combinations of feedback and feedforward signals among the areas and waited to see where the data would lead.”

They found that the regions essentially work as a committee, without much hierarchy, to keep working memory going. They also found changes as load approached and then exceeded capacity.

“At peak memory load, the brain signals that maintain memories and guide actions based on these memories, reach their maximum,” Pinotsis said. “Above this peak, the same signals break down.”

In particular, above capacity the PFC’s coupling to other regions at low frequency stopped, Miller said.

Other research suggests that the PFC’s role might be to employ low-frequency waves to provide the feedback the keeps the working memory system in synch. When that signal breaks down, Miller said, the whole enterprise may as well. That may explain why memory capacity has a finite limit. In prior studies, he said, his lab has observed that the information in neurons degrades as load increases, but there wasn’t an obvious cut-off where working memory would just stop functioning.

“We knew that stimulus load degrades processing in these areas, but we hadn’t seen any distinct change that correlated with reaching capacity,” he said. “But we did see this with feedback coupling. It drops off when the subjects exceeded their capacity. The PFC stops providing feedback coupling to the FEF and LIP.”

Two sides to the story

Because the study game purposely varied where the squares appeared on the left or right side of the visual field, the data also added more evidence for a discovery Miller and colleagues first reported back in 2009: Visual working memory is distinct for each side of the visual field. People have independent capacities on their left and their right, research has confirmed.

The Miller Lab is now working on a new study that tracks how the three regions interact when working memory information must be shared across the visual field.

The insights Miller’s lab has produced into visual working memory led him to start the company SplitSage , which last month earned a patent for technology to measure people’s positional differences in visual working memory capacity. The company hopes to use insights from Miller’s research to optimize heads-up displays in cars and to develop diagnostic tests for disorders like dementia among other applications. Miller is the company’s chief scientist and Buschman is chair of the advisory board.

The more scientists learn about how working memory works, and more generally about how brain waves synchronize higher level cognitive functions, the more ways they may be able to apply that knowledge to help people, Miller said.

“If we can figure out what things rhythms are doing and how they are doing them and when they are doing them, we may be able to find a way to strengthen the rhythms when they need to be strengthened,” he said.

This article has been republished from materials provided by The Picower Institute for Learning and Memory. Note: material may have been edited for length and content. For further information, please contact the cited source.

Reference:
Dimitris A Pinotsis, Timothy J Buschman, Earl K Miller; Working Memory Load Modulates Neuronal Coupling, Cerebral Cortex, https://doi.org/10.1093/cercor/bhy065

https://www.technologynetworks.com/neuroscience/news/heavy-working-memory-load-sinks-brainwave-synch-299481?utm_campaign=Newsletter_TN_BreakingScienceNews&utm_source=hs_email&utm_medium=email&utm_content=61943552&_hsenc=p2ANqtz-9YXYfgZV0xyox9-5P2gNPpCxLjaaoa_RPBQqrpLSXU-va1pfx1t7Z-t-myuu0_NK28T90fFH7eTsE21icgPGmxbSMXfA&_hsmi=61943552

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By Elizabeth Bernstein

You’re feeling depressed. What have you been eating?

Psychiatrists and therapists don’t often ask this question. But a growing body of research over the past decade shows that a healthy diet—high in fruits, vegetables, whole grains, fish and unprocessed lean red meat—can prevent depression. And an unhealthy diet—high in processed and refined foods—increases the risk for the disease in everyone, including children and teens.

Now recent studies show that a healthy diet may not only prevent depression, but could effectively treat it once it’s started.

Researchers, led by epidemiologist Felice Jacka of Australia’s Deakin University, looked at whether improving the diets of people with major depression would help improve their mood. They chose 67 people with depression for the study, some of whom were already being treated with antidepressants, some with psychotherapy, and some with both. Half of these people were given nutritional counseling from a dietitian, who helped them eat healthier. Half were given one-on-one social support—they were paired with someone to chat or play cards with—which is known to help people with depression.

After 12 weeks, the people who improved their diets showed significantly happier moods than those who received social support. And the people who improved their diets the most improved the most. The study was published in January 2017 in BMC Medicine. A second, larger study drew similar conclusions and showed that the boost in mood lasted six months. It was led by researchers at the University of South Australia and published in December 2017 in Nutritional Neuroscience.

And later this month in Los Angeles at the American Academy of Neurology’s annual meeting, researchers from Rush University Medical Center in Chicago will present results from their research that shows that elderly adults who eat vegetables, fruits and whole grains are less likely to develop depression over time.

The findings are spurring the rise of a new field: nutritional psychiatry. Dr. Jacka helped to found the International Society for Nutritional Psychiatry Research in 2013. It held its first conference last summer. She’s also launched Deakin University’s Food & Mood Centre, which is dedicated to researching and developing nutrition-based strategies for brain disorders.

The annual American Psychiatric Association conference has started including presentations on nutrition and psychiatry, including one last year by chef David Bouley on foods that support the peripheral nervous system. And some medical schools, including Columbia University’s Vagelos College of Physicians and Surgeons, are starting to teach psychiatry residents about the importance of diet on mental health.

Depression has many causes—it may be genetic, triggered by a specific event or situation, such as loneliness, or brought on by lifestyle choices. But it’s really about an unhealthy brain, and too often people forget this. “When we think of cardiac health, we think of strengthening an organ, the heart,” says Drew Ramsey, a psychiatrist in New York, assistant clinical professor of psychiatry at Columbia and author of “Eat Complete.” “We need to start thinking of strengthening another organ, the brain, when we think of mental health.”

A bad diet makes depression worse, failing to provide the brain with the variety of nutrients it needs, Dr. Ramsey says. And processed or deep-fried foods often contain trans fats that promote inflammation, believed to be a cause of depression. To give people evidenced-based information, Dr. Ramsey created an e-course called “Eat to Beat Depression.”

A bad diet also affects our microbiome—the trillions of micro-organisms that live in our gut. They make molecules that can alter the production of serotonin, a neurotransmitter found in the brain, says Lisa Mosconi, a neuroscientist, nutritionist and associate director of the Alzheimer’s Prevention Clinic at Weill Cornell Medical College in New York. The good and bad bacteria in our gut have complex ways to communicate with our brain and change our mood, she says. We need to maximize the good bacteria and minimize the bad.

So what should we eat? The research points to a Mediterranean-style diet made up primarily of fruits and vegetables, extra-virgin olive oil, yogurt and cheese, legumes, nuts, seafood, whole grains and small portions of red meat. The complexity of this diet will provide the nutrition our brain needs, regulate our inflammatory response and support the good bacteria in our gut, says Dr. Mosconi, author of “Brain Food: The Surprising Science of Eating for Cognitive Power.”

Can a good diet replace medicine or therapy? Not for everyone. But people at risk for depression should pay attention to the food they eat. “It really doesn’t matter if you need Prozac or not. We know that your brain needs nutrients,” Dr. Ramsey says. A healthy diet may work even when other treatments fail. And at the very least, it can serve as a supplemental treatment—one with no bad side effects, unlike antidepressants—that also has a giant upside. It can prevent other health problems, such as heart disease, obesity and diabetes.

Loretta Go, a 60-year-old mortgage consultant in Ballwin, Mo., suffered from depression for decades. She tried multiple antidepressants and cognitive behavioral therapy, but found little relief from symptoms including insomnia, crying jags and feelings of hopelessness. About five years ago, after her doctor wanted to prescribe yet another antidepressant, she refused the medicine and decided to look for alternative treatments.

Ms. Go began researching depression and learned about the importance of diet. When she read that cashews were effective in reducing depression symptoms, she ordered 100 pounds, stored them in the freezer, and started putting them in all her meals.

She also ditched processed and fried foods, sugar and diet sodas. In their place, she started to eat primarily vegetables and fruits, eggs, turkey and a lot of tofu. She bought a Vitamix blender and started making a smoothie with greens for breakfast each morning.

Within a few months, Ms. Go says she noticed a difference in her mood. She stopped crying all the time. Her insomnia went away and she had more energy. She also began enjoying activities again that she had given up when she was depressed, such as browsing in bookstores and volunteering at the animal shelter.

Ms. Go’s depression has never come back. “This works so well,” she says. “How come nobody else talks about this?”

https://www.wsj.com/articles/the-food-that-helps-battle-depression-1522678367

by Robbie Gonzalez

THE SHAPE ON the screen appears only briefly—just long enough for the test subject to commit it to memory. At the same time, an electrical signal snakes past the bony perimeter of her skull, down through a warm layer of grey matter toward a batch of electrodes near the center of her brain. Zap zap zap they go, in a carefully orchestrated pattern of pulses. The picture disappears from the screen. A minute later, it reappears, this time beside a handful of other abstract images. The patient pauses, recognizes the shape, then points to it with her finger.

What she’s doing is remarkable, not for what she remembers, but for how well she remembers. On average, she and seven other test subjects perform 37 percent better at the memory game with the brain pulses than they do without—making them the first humans on Earth to experience the memory-boosting benefits of a tailored neural prosthesis.

If you want to get technical, the brain-booster in question is a “closed-loop hippocampal neural prosthesis.” Closed loop because the signals passing between each patient’s brain and the computer to which it’s attached are zipping back and forth in near-real-time. Hippocampal because those signals start and end inside the test subject’s hippocampus, a seahorse-shaped region of the brain critical to the formation of memories. “We’re looking at how the neurons in this region fire when memories are encoded and prepared for storage,” says Robert Hampson, a neuroscientist at Wake Forest Baptist Medical Center and lead author of the paper describing the experiment in the latest issue of the Journal of Neural Engineering.

By distinguishing the patterns associated with successfully encoded memories from unsuccessful ones, he and his colleagues have developed a system that improves test subjects’ performance on visual memory tasks. “What we’ve been able to do is identify what makes a correct pattern, what makes an error pattern, and use microvolt level electrical stimulations to strengthen the correct patterns. What that has resulted in is an improvement of memory recall in tests of episodic memory.” Translation: They’ve improved short-term memory by zapping patients’ brains with individualized patterns of electricity.

Today, their proof-of-concept prosthetic lives outside a patient’s head and connects to the brain via wires. But in the future, Hampson hopes, surgeons could implant a similar apparatus entirely within a person’s skull, like a neural pacemaker. It could augment all manner of brain functions—not just in victims of dementia and brain injury, but healthy individuals, as well.

If the possibility of a neuroprosthetic future strikes you as far-fetched, consider how far Hampson has come already. He’s been studying the formation of memories in the hippocampus since the 1980s. Then, about two decades ago, he connected with University of Southern California neural engineer Theodore Berger, who had been working on ways to model hippocampal activity mathematically. The two have been collaborating ever since. In the early aughts, they demonstrated the potential of a neuroprosthesis in slices of brain tissue. In 2011 they did it in live rats. A couple years later, they pulled it off in live monkeys. Now, at long last, they’ve done it in people.

“In one sense, that makes this prosthesis a culmination,” Hampson says. “But in another sense, it’s just the beginning. Human memory is such a complex process, and there is so much left to learn. We’re only at the edge of understanding it.”

To test their system in human subjects, the researchers recruited people with epilepsy; those patients already had electrodes implanted in their hippocampi to monitor for seizure-related electrical activity. By piggybacking on the diagnostic hardware, Hampson and his colleagues were able to record, and later deliver, electrical activity.

You see, the researchers weren’t just zapping their subjects’ brains willy nilly. They determined where and when to deliver stimulation by first recording activity in the hippocampus as each test subject performed the visual memory test described above. It’s an assessment of working memory—the short-term mental storage bin you use to stash, say, a two-factor authentication code, only to retrieve it seconds later.

All the while, electrodes were recording the brain’s activity, tracking the firing patterns in the hippocampus when the patient guessed right and wrong. From those patterns, Berger, together with USC biomedical engineer Dong Song, created a mathematical model that could predict how neurons in each subject’s hippocampus would fire during successful memory-formation. And if you can predict that activity, that means you can stimulate the brain to mimic that memory formation.

Stimulating the patients’ hippocampi had a similar effect on longer-term memory retention—like your ability to remember where you parked when you leave the grocery store. In a second test, Hampson’s team introduced a 30- to 60-minute delay between displaying an image and asking the subjects to pull it out of a lineup. On average, test subjects performed 35 percent better in the stimulated trials.

The effect came as a shock to the researchers. “We weren’t surprised to see improvement, because we’d had success in our preliminary animal studies. We were surprised by the amount of improvement,” Hampson says. “We could tell, as we were running the patients, that they were performing better. But we didn’t appreciate how much better until we went back and analyzed the results.”

The results have impressed other researchers, as well. “The loss of one’s memories and the ability to encode new memories is devastating—we are who we are because of the memories we have formed throughout our lifetimes,” Rob Malenka, a psychiatrist and neurologist at Stanford University who was unaffiliated with the study, said via email. In that light, he says, “this very exciting neural prosthetic approach, which borders on science fiction, has great potential value. (Malenka has expressed cautious optimism about neuroprosthetic research in the past, noting as recently as 2015 that the translation of the technology from animal to human subjects would constitute “a huge leap.”) However, he says, it’s important to be remain clear-headed. “This kind of approach is certainly worth pursuing with vigor but I think it will still be decades before this kind of approach will ever be used routinely in large numbers of patient populations.”

Then again, with enough support, it could happen sooner than that. Facebook is working on brain computer interfaces; so is Elon Musk. Berger himself briefly served as the chief science officer of Kernel, an ambitious neurotechnology startup led by entrepreneur Bryan Johnson. “Initially, I was very hopeful about working with Bryan,” Berger says now. “We were both excited about the possibility of the work, and he was willing to put in the kind of money that would be required to see it thrive.”

But the partnership crumbled, right in the middle of Kernel’s first clinical test. Berger declines to go into details, except to say that Johnson—either out of hubris or ignorance—wanted to move too fast. (Johnson declined to comment for this story.)

https://www.wired.com/story/hippocampal-neural-prosthetic?mbid=nl_040618_daily_list3_p1&CNDID=50678559


Roughly the same number of new nerve cells (dots) exist in the hippocampus of people in their 20s (three hippocampi shown, top row) as in people in their 70s (bottom). Blue marks the dentate gyrus, where new nerve cells are born.

BY LAUREL HAMERS

Healthy people in their 70s have just as many young nerve cells, or neurons, in a memory-related part of the brain as do teenagers and young adults, researchers report in the April 5 Cell Stem Cell. The discovery suggests that the hippocampus keeps generating new neurons throughout a person’s life.

The finding contradicts a study published in March, which suggested that neurogenesis in the hippocampus stops in childhood (SN Online: 3/8/18). But the new research fits with a larger pile of evidence showing that adult human brains can, to some extent, make new neurons. While those studies indicate that the process tapers off over time, the new study proposes almost no decline at all.

Understanding how healthy brains change over time is important for researchers untangling the ways that conditions like depression, stress and memory loss affect older brains.

When it comes to studying neurogenesis in humans, “the devil is in the details,” says Jonas Frisén, a neuroscientist at the Karolinska Institute in Stockholm who was not involved in the new research. Small differences in methodology — such as the way brains are preserved or how neurons are counted — can have a big impact on the results, which could explain the conflicting findings. The new paper “is the most rigorous study yet,” he says.

Researchers studied hippocampi from the autopsied brains of 17 men and 11 women ranging in age from 14 to 79. In contrast to past studies that have often relied on donations from patients without a detailed medical history, the researchers knew that none of the donors had a history of psychiatric illness or chronic illness. And none of the brains tested positive for drugs or alcohol, says Maura Boldrini, a psychiatrist at Columbia University. Boldrini and her colleagues also had access to whole hippocampi, rather than just a few slices, allowing the team to make more accurate estimates of the number of neurons, she says.

To look for signs of neurogenesis, the researchers hunted for specific proteins produced by neurons at particular stages of development. Proteins such as GFAP and SOX2, for example, are made in abundance by stem cells that eventually turn into neurons, while newborn neurons make more of proteins such as Ki-67. In all of the brains, the researchers found evidence of newborn neurons in the dentate gyrus, the part of the hippocampus where neurons are born.

Although the number of neural stem cells was a bit lower in people in their 70s compared with people in their 20s, the older brains still had thousands of these cells. The number of young neurons in intermediate to advanced stages of development was the same across people of all ages.

Still, the healthy older brains did show some signs of decline. Researchers found less evidence for the formation of new blood vessels and fewer protein markers that signal neuroplasticity, or the brain’s ability to make new connections between neurons. But it’s too soon to say what these findings mean for brain function, Boldrini says. Studies on autopsied brains can look at structure but not activity.

Not all neuroscientists are convinced by the findings. “We don’t think that what they are identifying as young neurons actually are,” says Arturo Alvarez-Buylla of the University of California, San Francisco, who coauthored the recent paper that found no signs of neurogenesis in adult brains. In his study, some of the cells his team initially flagged as young neurons turned out to be mature cells upon further investigation.

But others say the new findings are sound. “They use very sophisticated methodology,” Frisén says, and control for factors that Alvarez-Buylla’s study didn’t, such as the type of preservative used on the brains.

M. Boldrini et al. Human hippocampal neurogenesis persists throughout aging. Cell Stem Cell. Vol. 22, April 5, 2018, p. 589. doi:10.1016/j.stem.2018.03.015.

S.F. Sorrells et al. Human hippocampal neurogenesis drops sharply in children to undetectable levels in adults. Nature. Vol. 555, March 15, 2018, p. 377. doi: 10.1038/nature25975.

https://www.sciencenews.org/article/human-brains-make-new-nerve-cells-and-lots-them-well-old-age

by Emily Mullin

When David Graham wakes up in the morning, the flat white box that’s Velcroed to the wall of his room in Robbie’s Place, an assisted living facility in Marlborough, Massachusetts, begins recording his every movement.

It knows when he gets out of bed, gets dressed, walks to his window, or goes to the bathroom. It can tell if he’s sleeping or has fallen. It does this by using low-power wireless signals to map his gait speed, sleep patterns, location, and even breathing pattern. All that information gets uploaded to the cloud, where machine-learning algorithms find patterns in the thousands of movements he makes every day.

The rectangular boxes are part of an experiment to help researchers track and understand the symptoms of Alzheimer’s.

It’s not always obvious when patients are in the early stages of the disease. Alterations in the brain can cause subtle changes in behavior and sleep patterns years before people start experiencing confusion and memory loss. Researchers think artificial intelligence could recognize these changes early and identify patients at risk of developing the most severe forms of the disease.

Spotting the first indications of Alzheimer’s years before any obvious symptoms come on could help pinpoint people most likely to benefit from experimental drugs and allow family members to plan for eventual care. Devices equipped with such algorithms could be installed in people’s homes or in long-term care facilities to monitor those at risk. For patients who already have a diagnosis, such technology could help doctors make adjustments in their care.

Drug companies, too, are interested in using machine-learning algorithms, in their case to search through medical records for the patients most likely to benefit from experimental drugs. Once people are in a study, AI might be able to tell investigators whether the drug is addressing their symptoms.

Currently, there’s no easy way to diagnose Alzheimer’s. No single test exists, and brain scans alone can’t determine whether someone has the disease. Instead, physicians have to look at a variety of factors, including a patient’s medical history and observations reported by family members or health-care workers. So machine learning could pick up on patterns that otherwise would easily be missed.


David Graham, one of Vahia’s patients, has one of the AI-powered devices in his room at Robbie’s Place, an assisted living facility in Marlborough, Massachusetts.

Graham, unlike the four other patients with such devices in their rooms, hasn’t been diagnosed with Alzheimer’s. But researchers are monitoring his movements and comparing them with patterns seen in patients who doctors suspect have the disease.

Dina Katabi and her team at MIT’s Computer Science and Artificial Intelligence Laboratory initially developed the device as a fall detector for older people. But they soon realized it had far more uses. If it could pick up on a fall, they thought, it must also be able to recognize other movements, like pacing and wandering, which can be signs of Alzheimer’s.

Katabi says their intention was to monitor people without needing them to put on a wearable tracking device every day. “This is completely passive. A patient doesn’t need to put sensors on their body or do anything specific, and it’s far less intrusive than a video camera,” she says.

How it works

Graham hardly notices the white box hanging in his sunlit, tidy room. He’s most aware of it on days when Ipsit Vahia makes his rounds and tells him about the data it’s collecting. Vahia is a geriatric psychiatrist at McLean Hospital and Harvard Medical School, and he and the technology’s inventors at MIT are running a small pilot study of the device.

Graham looks forward to these visits. During a recent one, he was surprised when Vahia told him he was waking up at night. The device was able to detect it, though Graham didn’t know he was doing it.

The device’s wireless radio signal, only a thousandth as powerful as wi-fi, reflects off everything in a 30-foot radius, including human bodies. Every movement—even the slightest ones, like breathing—causes a change in the reflected signal.

Katabi and her team developed machine-learning algorithms that analyze all these minute reflections. They trained the system to recognize simple motions like walking and falling, and more complex movements like those associated with sleep disturbances. “As you teach it more and more, the machine learns, and the next time it sees a pattern, even if it’s too complex for a human to abstract that pattern, the machine recognizes that pattern,” Katabi says.

Over time, the device creates large readouts of data that show patterns of behavior. The AI is designed to pick out deviations from those patterns that might signify things like agitation, depression, and sleep disturbances. It could also pick up whether a person is repeating certain behaviors during the day. These are all classic symptoms of Alzheimer’s.

“If you can catch these deviations early, you will be able to anticipate them and help manage them,” Vahia says.

In a patient with an Alzheimer’s diagnosis, Vahia and Katabi were able to tell that she was waking up at 2 a.m. and wandering around her room. They also noticed that she would pace more after certain family members visited. After confirming that behavior with a nurse, Vahia adjusted the patient’s dose of a drug used to prevent agitation.


Ipsit Vahia and Dina Katabi are testing an AI-powered device that Katabi’s lab built to monitor the behaviors of people with Alzheimer’s as well as those at risk of developing the disease.

Brain changes

AI is also finding use in helping physicians detect early signs of Alzheimer’s in the brain and understand how those physical changes unfold in different people. “When a radiologist reads a scan, it’s impossible to tell whether a person will progress to Alzheimer’s disease,” says Pedro Rosa-Neto, a neurologist at McGill University in Montreal.

Rosa-Neto and his colleague Sulantha Mathotaarachchi developed an algorithm that analyzed hundreds of positron-emission tomography (PET) scans from people who had been deemed at risk of developing Alzheimer’s. From medical records, the researchers knew which of these patients had gone on to develop the disease within two years of a scan, but they wanted to see if the AI system could identify them just by picking up patterns in the images.

Sure enough, the algorithm was able to spot patterns in clumps of amyloid—a protein often associated with the disease—in certain regions of the brain. Even trained radiologists would have had trouble noticing these issues on a brain scan. From the patterns, it was able to detect with 84 percent accuracy which patients ended up with Alzheimer’s.

Machine learning is also helping doctors predict the severity of the disease in different patients. Duke University physician and scientist P. Murali Doraiswamy is using machine learning to figure out what stage of the disease patients are in and whether their condition is likely to worsen.

“We’ve been seeing Alzheimer’s as a one-size-fits all problem,” says Doraiswamy. But people with Alzheimer’s don’t all experience the same symptoms, and some might get worse faster than others. Doctors have no idea which patients will remain stable for a while or which will quickly get sicker. “So we thought maybe the best way to solve this problem was to let a machine do it,” he says.

He worked with Dragan Gamberger, an artificial-intelligence expert at the Rudjer Boskovic Institute in Croatia, to develop a machine-learning algorithm that sorted through brain scans and medical records from 562 patients who had mild cognitive impairment at the beginning of a five-year period.

Two distinct groups emerged: those whose cognition declined significantly and those whose symptoms changed little or not at all over the five years. The system was able to pick up changes in the loss of brain tissue over time.

A third group was somewhere in the middle, between mild cognitive impairment and advanced Alzheimer’s. “We don’t know why these clusters exist yet,” Doraiswamy says.

Clinical trials

From 2002 to 2012, 99 percent of investigational Alzheimer’s drugs failed in clinical trials. One reason is that no one knows exactly what causes the disease. But another reason is that it is difficult to identify the patients most likely to benefit from specific drugs.

AI systems could help design better trials. “Once we have those people together with common genes, characteristics, and imaging scans, that’s going to make it much easier to test drugs,” says Marilyn Miller, who directs AI research in Alzheimer’s at the National Institute on Aging, part of the US National Institutes of Health.

Then, once patients are enrolled in a study, researchers could continuously monitor them to see if they’re benefiting from the medication.

“One of the biggest challenges in Alzheimer’s drug development is we haven’t had a good way of parsing out the right population to test the drug on,” says Vaibhav Narayan, a researcher on Johnson & Johnson’s neuroscience team.

He says machine-learning algorithms will greatly speed the process of recruiting patients for drug studies. And if AI can pick out which patients are most likely to get worse more quickly, it will be easier for investigators to tell if a drug is having any benefit.

That way, if doctors like Vahia notice signs of Alzheimer’s in a person like Graham, they can quickly get him signed up for a clinical trial in hopes of curbing the devastating effects that would otherwise come years later.

Miller thinks AI could be used to diagnose and predict Alzheimer’s in patients in as soon as five years from now. But she says it’ll require a lot of data to make sure the algorithms are accurate and reliable. Graham, for one, is doing his part to help out.

https://www.technologyreview.com/s/609236/ai-can-spot-signs-of-alzheimers-before-your-family-does/

By Rafi Letzter

Scientists in Switzerland dosed test subjects with LSD to investigate how patients with severe mental disorders lose track of where they end and other people begin.

Both LSD and certain mental disorders, most notably schizophrenia, can make it difficult for people to distinguish between themselves and others. And that can impair everyday mental tasks and social interactions, said Katrin Preller, one of the lead authors of the study and a psychologist at the University Hospital of Psychiatry in Zurich. By studying how LSD breaks down people’s senses of self, the researchers aimed to find targets for future experimental drugs to treat schizophrenia.

“Healthy people take having this coherent ‘self’ experience for granted,” Preller told Live Science, “which makes it difficult to explain why it’s so important.”

Depression, she said, also relates to the sense of self. Whereas people with schizophrenia can lose track of themselves entirely, people with depression tend to “ruminate” on themselves, unable to break obsessive, self-oriented patterns of thought.

But this kind of phenomenon is challenging to study, Preller said.

“If you want to investigate self-experience, you have to manipulate it,” Preller said. “And there are very few substances that can actually manipulate sense of self while patients are lying in our MRI scanner.”

One of the substances that can, however, is LSD. And that’s why this experiment happened in Zurich, Preller said. Switzerland is one of the few countries where it’s possible to use LSD on human beings for scientific research. (Doing so is still quite difficult, though, requiring lots of oversight.)

The experiment itself didn’t sound like the most exciting use of the drug for the test subjects, all of whom were physically healthy and did not have schizophrenia or other illnesses After taking the drug, the subjects lay inside MRI machines with video goggles strapped to their faces, trying to make eye contact with a computer-generated avatar. Once they accomplished this, the subjects then tried to look off at another point in space that the avatar was also looking at. This is the kind of social task, Preller said, that’s very difficult if your sense of self has broken down.

Every study subject tried the task three times: once sober, once on LSD, and once after taking both LSD and a substance called ketanserin. This substance blocks LSD from interacting with a particular serotonin receptor in the brain, which researchers call “5-HT2.”

Previous studies on animals had suggested that 5-HT2 played a key role in LSD’s ability to mess with sense of self. The researchers suspected that blocking the receptor in humans might somewhat reduce the effect of LSD.

But it turned out to more than “somewhat” block the effect: There was no difference between the performance of subjects who took ketanserin and the placebo group.

“This was surprising to us, because LSD interacts with a lot of receptors [in the brain], not just 5-HT2,” Preller said.

But LSD’s most dramatic measurable effects entirely abated when subjects first took ketanserin.

That tentatively indicates that 5-HT2 plays an important role in regulating sense of self in the brain, Preller said. The next step, she added, is to work on drugs that target that receptor and see if they might alleviate some of the symptoms of severe psychiatric illnesses that affect the sense of self.

The paper detailing the study’s results was published today (March 19) at The Journal of Neuroscience.

https://www.livescience.com/62059-schizophrenia-lsd-sense-self.html#?utm_source=ls-newsletter&utm_medium=email&utm_campaign=03202018-ls


Illustration by Paweł Jońca

by Helen Thomson

In March 2015, Li-Huei Tsai set up a tiny disco for some of the mice in her laboratory. For an hour each day, she placed them in a box lit only by a flickering strobe. The mice — which had been engineered to produce plaques of the peptide amyloid-β in the brain, a hallmark of Alzheimer’s disease — crawled about curiously. When Tsai later dissected them, those that had been to the mini dance parties had significantly lower levels of plaque than mice that had spent the same time in the dark.

Tsai, a neuroscientist at Massachusetts Institute of Technology (MIT) in Cambridge, says she checked the result; then checked it again. “For the longest time, I didn’t believe it,” she says. Her team had managed to clear amyloid from part of the brain with a flickering light. The strobe was tuned to 40 hertz and was designed to manipulate the rodents’ brainwaves, triggering a host of biological effects that eliminated the plaque-forming proteins. Although promising findings in mouse models of Alzheimer’s disease have been notoriously difficult to replicate in humans, the experiment offered some tantalizing possibilities. “The result was so mind-boggling and so robust, it took a while for the idea to sink in, but we knew we needed to work out a way of trying out the same thing in humans,” Tsai says.

Scientists identified the waves of electrical activity that constantly ripple through the brain almost 100 years ago, but they have struggled to assign these oscillations a definitive role in behaviour or brain function. Studies have strongly linked brainwaves to memory consolidation during sleep, and implicated them in processing sensory inputs and even coordinating consciousness. Yet not everyone is convinced that brainwaves are all that meaningful. “Right now we really don’t know what they do,” says Michael Shadlen, a neuroscientist at Columbia University in New York City.

Now, a growing body of evidence, including Tsai’s findings, hint at a meaningful connection to neurological disorders such as Alzheimer’s and Parkinson’s diseases. The work offers the possibility of forestalling or even reversing the damage caused by such conditions without using a drug. More than two dozen clinical trials are aiming to modulate brainwaves in some way — some with flickering lights or rhythmic sounds, but most through the direct application of electrical currents to the brain or scalp. They aim to treat everything from insomnia to schizophrenia and premenstrual dysphoric disorder.

Tsai’s study was the first glimpse of a cellular response to brainwave manipulation. “Her results were a really big surprise,” says Walter Koroshetz, director of the US National Institute of Neurological Disorders and Stroke in Bethesda, Maryland. “It’s a novel observation that would be really interesting to pursue.”


A powerful wave

Brainwaves were first noticed by German psychiatrist Hans Berger. In 1929, he published a paper describing the repeating waves of current he observed when he placed electrodes on people’s scalps. It was the world’s first electroencephalogram (EEG) recording — but nobody took much notice. Berger was a controversial figure who had spent much of his career trying to identify the physiological basis of psychic phenomena. It was only after his colleagues began to confirm the results several years later that Berger’s invention was recognized as a window into brain activity.

Neurons communicate using electrical impulses created by the flow of ions into and out of each cell. Although a single firing neuron cannot be picked up through the electrodes of an EEG, when a group of neurons fires again and again in synchrony, it shows up as oscillating electrical ripples that sweep through the brain.

Those of the highest frequency are gamma waves, which range from 25 to 140 hertz. People often show a lot of this kind of activity when they are at peak concentration. At the other end of the scale are delta waves, which have the lowest frequency — around 0.5 to 4 hertz. These tend to occur in deep sleep (see ‘Rhythms of the mind’).

At any point in time, one type of brainwave tends to dominate, although other bands are always present to some extent. Scientists have long wondered what purpose, if any, this hum of activity serves, and some clues have emerged over the past three decades. For instance, in 1994, discoveries in mice indicated that the distinct patterns of oscillatory activity during sleep mirrored those during a previous learning exercise. Scientists suggested that these waves could be helping to solidify memories.

Brainwaves also seem to influence conscious perception. Randolph Helfrich at the University of California, Berkeley, and his colleagues devised a way to enhance or reduce gamma oscillations of around 40 hertz using a non-invasive technique called transcranial alternating current stimulation (tACS). By tweaking these oscillations, they were able to influence whether a person perceived a video of moving dots as travelling vertically or horizontally.

The oscillations also provide a potential mechanism for how the brain creates a coherent experience from the chaotic symphony of stimuli hitting the senses at any one time, a puzzle known as the ‘binding problem’. By synchronizing the firing rates of neurons responding to the same event, brainwaves might ensure that the all of the relevant information relating to one object arrives at the correct area of the brain at exactly the right time. Coordinating these signals is the key to perception, says Robert Knight, a cognitive neuroscientist at the University of California, Berkeley, “You can’t just pray that they will self-organize.”


Healthy oscillations

But these oscillations can become disrupted in certain disorders. In Parkinson’s disease, for example, the brain generally starts to show an increase in beta waves in the motor regions as body movement becomes impaired. In a healthy brain, beta waves are suppressed just before a body movement. But in Parkinson’s disease, neurons seem to get stuck in a synchronized pattern of activity. This leads to rigidity and movement difficulties. Peter Brown, who studies Parkinson’s disease at the University of Oxford, UK, says that current treatments for the symptoms of the disease — deep-brain stimulation and the drug levodopa — might work by reducing beta waves.

People with Alzheimer’s disease show a reduction in gamma oscillations5. So Tsai and others wondered whether gamma-wave activity could be restored, and whether this would have any effect on the disease.

They started by using optogenetics, in which brain cells are engineered to respond directly to a flash of light. In 2009, Tsai’s team, in collaboration with Christopher Moore, also at MIT at the time, demonstrated for the first time that it is possible to use the technique to drive gamma oscillations in a specific part of the mouse brain6.

Tsai and her colleagues subsequently found that tinkering with the oscillations sets in motion a host of biological events. It initiates changes in gene expression that cause microglia — immune cells in the brain — to change shape. The cells essentially go into scavenger mode, enabling them to better dispose of harmful clutter in the brain, such as amyloid-β. Koroshetz says that the link to neuroimmunity is new and striking. “The role of immune cells like microglia in the brain is incredibly important and poorly understood, and is one of the hottest areas for research now,” he says.

If the technique was to have any therapeutic relevance, however, Tsai and her colleagues had to find a less-invasive way of manipulating brainwaves. Flashing lights at specific frequencies has been shown to influence oscillations in some parts of the brain, so the researchers turned to strobe lights. They started by exposing young mice with a propensity for amyloid build-up to flickering LED lights for one hour. This created a drop in free-floating amyloid, but it was temporary, lasting less than 24 hours, and restricted to the visual cortex.

To achieve a longer-lasting effect on animals with amyloid plaques, they repeated the experiment for an hour a day over the course of a week, this time using older mice in which plaques had begun to form. Twenty-four hours after the end of the experiment, these animals showed a 67% reduction in plaque in the visual cortex compared with controls. The team also found that the technique reduced tau protein, another hallmark of Alzheimer’s disease.

Alzheimer’s plaques tend to have their earliest negative impacts on the hippocampus, however, not the visual cortex. To elicit oscillations where they are needed, Tsai and her colleagues are investigating other techniques. Playing rodents a 40-hertz noise, for example, seems to cause a decrease in amyloid in the hippocampus — perhaps because the hippo-campus sits closer to the auditory cortex than to the visual cortex.

Tsai and her colleague Ed Boyden, a neuro-scientist at MIT, have now formed a company, Cognito Therapeutics in Cambridge, to test similar treatments in humans. Last year, they started a safety trial, which involves testing a flickering light device, worn like a pair of glasses, on 12 people with Alzheimer’s.

Caveats abound. The mouse model of Alzheimer’s disease is not a perfect reflection of the disorder, and many therapies that have shown promise in rodents have failed in humans. “I used to tell people — if you’re going to get Alzheimer’s, first become a mouse,” says Thomas Insel, a neuroscientist and psychiatrist who led the US National Institute of Mental Health in Bethesda, Maryland, from 2002 until 2015.

Others are also looking to test how manipulating brainwaves might help people with Alzheimer’s disease. “We thought Tsai’s study was outstanding,” says Emiliano Santarnecchi at Harvard Medical School in Boston, Massachusetts. His team had already been using tACS to stimulate the brain, and he wondered whether it might elicit stronger effects than a flashing strobe. “This kind of stimulation can target areas of the brain more specifically than sensory stimulation can — after seeing Tsai’s results, it was a no-brainer that we should try it in Alzheimer’s patients.”

His team has begun an early clinical trial in which ten people with Alzheimer’s disease receive tACS for one hour daily for two weeks. A second trial, in collaboration with Boyden and Tsai, will look for signals of activated microglia and levels of tau protein. Results are expected from both trials by the end of the year.

Knight says that Tsai’s animal studies clearly show that oscillations have an effect on cellular metabolism — but whether the same effect will be seen in humans is another matter. “In the end, it’s data that will win out,” he says.

The studies may reveal risks, too. Gamma oscillations are the type most likely to induce seizures in people with photosensitive epilepsy, says Dora Hermes, a neuroscientist at Stanford University in California. She recalls a famous episode of a Japanese cartoon that featured flickering red and blue lights, which induced seizures in some viewers. “So many people watched that episode that there were almost 700 extra visits to the emergency department that day.”

A brain boost

Nevertheless, there is clearly a growing excitement around treating neurological diseases using neuromodulation, rather than pharmaceuticals. “There’s pretty good evidence that by changing neural-circuit activity we can get improvements in Parkinson’s, chronic pain, obsessive–compulsive disorder and depression,” says Insel. This is important, he says, because so far, pharmaceutical treatments for neurological disease have suffered from a lack of specificity. Koroshetz adds that funding institutes are eager for treatments that are innovative, non-invasive and quickly translatable to people.

Since publishing their mouse paper, Boyden says, he has had a deluge of requests from researchers wanting to use the same technique to treat other conditions. But there are a lot of details to work out. “We need to figure out what is the most effective, non-invasive way of manipulating oscillations in different parts of the brain,” he says. “Perhaps it is using light, but maybe it’s a smart pillow or a headband that could target these oscillations using electricity or sound.” One of the simplest methods that scientists have found is neurofeedback, which has shown some success in treating a range of conditions, including anxiety, depression and attention-deficit hyperactivity disorder. People who use this technique are taught to control their brainwaves by measuring them with an EEG and getting feedback in the form of visual or audio cues.

Phyllis Zee, a neurologist at Northwestern University in Chicago, Illinois, and her colleagues delivered pulses of ‘pink noise’ — audio frequencies that together sound a bit like a waterfall — to healthy older adults while they slept. They were particularly interested in eliciting the delta oscillations that characterize deep sleep. This aspect of sleep decreases with age, and is associated with a decreased ability to consolidate memories.

So far, her team has found that stimulation increased the amplitude of the slow waves, and was associated with a 25–30% improvement in recall of word pairs learnt the night before, compared with a fake treatment7. Her team is midway through a clinical trial to see whether longer-term acoustic stimulation might help people with mild cognitive impairment.

Although relatively safe, these kinds of technologies do have limitations. Neurofeedback is easy to learn, for instance, but it can take time to have an effect, and the results are often short-lived. In experiments that use magnetic or acoustic stimulation, it is difficult to know precisely what area of the brain is being affected. “The field of external brain stimulation is a little weak at the moment,” says Knight. Many approaches, he says, are open loop, meaning that they don’t track the effect of the modulation using an EEG. Closed loop, he says, would be more practical. Some experiments, such as Zee’s and those involving neuro-feedback, already do this. “I think the field is turning a corner,” Knight says. “It’s attracting some serious research.”

In addition to potentially leading to treatments, these studies could break open the field of neural oscillations in general, helping to link them more firmly to behaviour and how the brain works as a whole.

Shadlen says he is open to the idea that oscillations play a part in human behaviour and consciousness. But for now, he remains unconvinced that they are directly responsible for these phenomena — referring to the many roles people ascribe to them as “magical incantations”. He says he fully accepts that these brain rhythms are signatures of important brain processes, “but to posit the idea that synchronous spikes of activity are meaningful, that by suddenly wiggling inputs at a specific frequency, it suddenly elevates activity onto our conscious awareness? That requires more explanation.”

Whatever their role, Tsai mostly wants to discipline brainwaves and harness them against disease. Cognito Therapeutics has just received approval for a second, larger trial, which will look at whether the therapy has any effect on Alzheimer’s disease symptoms. Meanwhile, Tsai’s team is focusing on understanding more about the downstream biological effects and how to better target the hippocampus with non-invasive technologies.

For Tsai, the work is personal. Her grandmother, who raised her, was affected by dementia. “Her confused face made a deep imprint in my mind,” Tsai says. “This is the biggest challenge of our lifetime, and I will give it all I have.”

https://www.nature.com/articles/d41586-018-02391-6