Neuroscientists explore the intersection of music and memory

The soundtrack of this story begins with a vaguely recognizable and pleasant groove. But if I stop writing and just listen for a second, the music reveals itself completely. In Freddie Hubbard's comfortable, lilting trumpet solo over Herbie Hancock's melodic, repetitive piano vamping, I recognize "Cantaloupe Island." Then, with my fingers again poised at the keyboard, Freddie and Herbie fade into the background, followed by other instrumental music: captivating -- but not distracting -- sonic nutrition, feeding my concentration and productivity.

Somewhere, I think, Yiren Ren is studying, focused on her research that demonstrates how music impacts learning and memory. Possibly, she's listening to Norah Jones, or another musician she's comfortable with. Because that's how it works: The music we know and might love, music that feels predictable or even safe -- that music can help us study and learn. Meanwhile, Ren has also discovered, other kinds of music can influence our emotions and reshape old memories.

Ren, a sixth-year Ph.D. student in Georgia Tech's School of Psychology, explores these concepts as the lead author of two new research papers in the journals PLOS Oneand Cognitive, Affective, & Behavioral Neuroscience (CABN).

"These studies are connected because they both explore innovative applications of music in memory modulation, offering insights for both every day and clinical use," says Ren.

But the collective research explores music's impacts in very different ways, explains Ren's faculty advisor and co-author of the study, Thackery Brown.

"One paper looks at how music changes the quality of your memory when you're first forming it -- it's about learning," says Brown, a cognitive neuroscientist who runs the MAP (Memory, Affect, and Planning) Lab at Tech. "But the other study focuses on memories we already have and asks if we can change the emotions attached to them using music."

Making Moods With Music

When we watch a movie with a robust score -- music created to induce emotions -- what we're hearing guides us exactly where the composer wants us to go. In their CABN study, Ren, Brown, and their collaborators from the University of Colorado (including former Georgia Tech Assistant Professor Grace Leslie) report that this kind of "mood music" can also be powerful enough to change how we remember our past.

Their study included 44 Georgia Tech students who listened to film soundtracks while recalling a difficult memory. Ren is quick to point out that this was not a clinical trial, so these participants were not identified as people suffering from mood disorders: "We wanted to start off with a random group of people and see if music has the power to modulate the emotional level of their memories."

Turns out, it does. The participants listened to movie soundtracks and incorporated new emotions into their memories that matched the mood of the music. And the effect was lasting. A day later, when the participants recalled these same memories -- but without musical accompaniment -- their emotional tone still matched the tone of the music played the day before.

The researchers could watch all this happening with fMRI (functional magnetic resonance imaging). They could see the altered brain activity in the study participants, the increased connectivity between the amygdala, where emotions are processed, and other areas of the brain associated with memory and integrating information.

"This sheds light on the malleability of memory in response to music, and the powerful role music can play in altering our existing memories," says Ren.

Ren is herself a multi-instrumentalist who originally planned on being a professional musician. As an undergraduate at Boston University, she pursued a dual major in film production and sound design, and psychology.

She found a way to combine her interests in music and neuroscience and is interested in how music therapy can be designed to help people with mood disorders like post-traumatic stress disorder (PTSD) or depression, "particularly in cases where someone might overexaggerate the negative components of a memory," Ren says.

There is no time machine that will allow us to go back and insert happy music into the mix while a bad event is happening and a memory is being formed, "but we can retrieve old memories while listening to affective music," says Brown. "And perhaps we can help people shift their feelings and reshape the emotional tone attached to certain memories."

Embracing the Familiar

The second study asks a couple of old questions: Should we listen to music while we work or study? And if so, are there more beneficial types of music than others? The answer to both questions might lie, at least partially, within the expansive parameters of personal taste. But even so, there are limits.

Think back to my description of "Cantaloupe Island" at the beginning of this story and how a familiar old jazz standard helped keep this writer's brain and fingers moving. In the same way, Norah Jones helps Ren when she's working on new research around music and memory. But if, for some reason, I wanted to test my concentration, I'd play a different kind of jazz, maybe 1950s bebop with its frenetic pace and off-center tone, or possibly a chorus of screeching cats. Same effect. It would demand my attention, and no work would get done.

For this study, Ren combined her gifts as a musician and composer with her research interests in examining whether music can improve -- or impair -- our ability to learn or remember new information. "We wanted to probe music's potential as a mnemonic device that helps us remember information more easily," she says. (An example of a mnemonic device is "Every Good Boy Does Fine," which stands for E-G-B-D-F and helps new piano players learn the order of notes on a keyboard.)

This study's 48 participants were asked to learn sequences of abstract shapes while listening to different types of music. Ren played a piece of music, in a traditional or familiar pattern of tone, rhythm, and melody. She then played the exact same set of notes, but out of order, giving the piece an atonal structure.

When they listened to familiar, predictable music, participants learned and remembered the sequences of shapes quicker as their brains created a structured framework, or scaffold, for the new information. Meanwhile, music that was familiar but irregular (think of this writer and the bebop example) made it harder for participants to learn.

"Depending its familiarity and structure, music can help or hinder our memory," says Ren, who wants to deepen her focus on the neural mechanisms through which music influences human behavior.

She plans to finish her Ph.D. studies this December and is seeking postdoctoral research positions that will allow her to continue the work she's started at Georgia Tech. Building on that, Ren wants to develop music-based therapies for conditions like depression or PTSD, while also exploring new rehabilitation strategies for aging populations and individuals with dementia.

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Neuroscientists discover brain circuitry of placebo effect for pain relief

The placebo effect is very real. This we've known for decades, as seen in real-life observations and the best double-blinded randomized clinical trials researchers have devised for many diseases and conditions, especially pain. And yet, how and why the placebo effect occurs has remained a mystery. Now, neuroscientists have discovered a key piece of the placebo effect puzzle.

Publishing in Nature, researchers at the University of North Carolina School of Medicine- with colleagues from Stanford, the Howard Hughes Medical Institute, and the Allen Institute for Brain Science -- discovered a pain control pathway that links the cingulate cortex in the front of the brain, through the pons region of the brainstem, to cerebellum in the back of the brain.

The researchers, led by Greg Scherrer, PharmD, PhD, associate professor in the UNC Department of Cell Biology and Physiology, the UNC Neuroscience Center, and the UNC Department of Pharmacology, then showed that certain neurons and synapses along this pathway are highly activated when mice expect pain relief and experience pain relief, even when there is no medication involved.

"That neurons in our cerebral cortex communicate with the pons and cerebellum to adjust pain thresholds based on our expectations is both completely unexpected, given our previous understanding of the pain circuitry, and incredibly exciting," said Scherrer. "Our results do open the possibility of activating this pathway through other therapeutic means, such as drugs or neurostimulation methods to treat pain."

Scherrer and colleagues said research provides a new framework for investigating the brain pathways underlying other mind-body interactions and placebo effects beyond the ones involved in pain.

The Placebo Paradox

It is the human experience, in the face of pain, to want to feel better. As a result -- and in conjunction with millennia of evolution -- our brains can search for ways to help us feel better. It releases chemicals, which can be measured. Positive thinking and even prayer have been shown to benefit some patients. And the placebo effect -- feeling better even though there was no "real" treatment -- has been documented as a very real phenomenon for decades.

In clinical research, the placebo effect is often seen in what we call the "sham" treatment group. That is, individuals in this group receive a fake pill or intervention that is supposed to be inert; no one in the control group is supposed to see a benefit. Except that the brain is so powerful and individuals so desire to feel better that some experience a marked improvement in their symptoms. Some placebo effects are so strong that individuals are convinced they received a real treatment meant to help them.

In fact, it's thought that some individuals in the "actual" treatment group also derive benefit from the placebo effect. This is one of the reasons why clinical research of therapeutics is so difficult and demands as many volunteers as possible so scientists can parse the treatment benefit from the sham. One way to help scientists do this is to first understand what precisely is happening in the brain of someone experiencing the placebo effect.

Enter the Scherrer lab

The authors of the Nature paper knew that the scientific community's understanding of the biological underpinnings of pain relief through placebo analgesia -- when the positive expectation of pain relief is sufficient for patients to feel better -- came from human brain imaging studies, which showed activity in certain brain regions. Those imaging studies did not have enough precision to show what was actually happening in those brain regions. So Scherrer's team designed a set of meticulous, complementary, and time-consuming experiments to learn in more detail, with single nerve cell precision, what was happening in those regions.

First, the researchers created an assay that generates in mice the expectation of pain relief and then very real placebo effect of pain relief. Then the researchers used a series of experimental methods to study the intricacies of the anterior cingulate cortex (ACC), which had been previously associated with the pain placebo effect. While mice were experiencing the effect, the scientists used genetic tagging of neurons in the ACC, imaging of calcium in neurons of freely behaving mice, single-cell RNA sequencing techniques, electrophysiological recordings, and optogenetics -- the use of light and fluorescent-tagged genes to manipulate cells.

These experiments helped them see and study the intricate neurobiology of the placebo effect down to the brain circuits, neurons, and synapses throughout the brain.

The scientists found that when mice expected pain relief, the rostral anterior cingulate cortex neurons projected their signals to the pontine nucleus, which had no previously established function in pain or pain relief. And they found that expectation of pain relief boosted signals along this pathway.

"There is an extraordinary abundance of opioid receptors here, supporting a role in pain modulation," Scherrer said. "When we inhibited activity in this pathway, we realized we were disrupting placebo analgesia and decreasing pain thresholds. And then, in the absence of placebo conditioning, when we activated this pathway, we caused pain relief.

Lastly, the scientists found that Purkinje cells -- a distinct class of large branch-like cells of the cerebellum -- showed activity patterns similar to those of the ACC neurons during pain relief expectation. Scherrer and first author Chong Chen, MD, PhD, a postdoctoral research associate in the Scherrer lab, said that this is cellular-level evidence for the cerebellum's role in cognitive pain modulation.

"We all know we need better ways to treat chronic pain, particularly treatments without harmful side effects and addictive properties," Scherrer said. "We think our findings open the door to targeting this novel neural pain pathway to treat people in a different but potentially more effective way."

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Illusion helps demystify the way vision works

For the first time, research shows that a certain kind of visual illusion, neon color spreading, works on mice. The study is also the first to combine the use of two investigative techniques called electrophysiology and optogenetics to study this illusion. Results from experiments on mice settle a long-standing debate in neuroscience about which levels of neurons within the brain are responsible for the perception of brightness.

We're all familiar with optical illusions; some are novelties, while some are all around us. Even as you look at the screen in front you, you are being fooled into thinking that you're seeing the color white. What you're really seeing is lots of red, green and blue elements packed so tightly together it gives the impression of being white. Another example is a fast rotating wheel or propeller, which can briefly look like it's reversing direction while it's accelerating to full speed. In any case, it might be surprising to know that optical illusions are not just fun to look at but can also be a useful tool to learn more about eyes, nerves, minds and brains.

Associate Professor Masataka Watanabe from the Department of Systems Innovation at the University of Tokyo is on a mission to understand more about the nature of consciousness. It's a vast subject area so naturally there are many ways to explore it, and amongst other things, he uses optical illusions. His most recent research looked at whether a certain kind of illusion that works on humans would also work on mice. And it turns out, it does. But why is this significant?

"Knowing this kind of illusion, called a neon-color-spreading illusion, works on mice as well as humans, is useful for neuroscientists like myself, as it means that mice can serve as useful test subjects for cases where humans cannot," said Watanabe. "To really understand what goes on inside the brain during perceptual experiences, we need to use certain methods that we cannot use on people. These include electrophysiology, the recording of neural activity with electrodes, and optogenetics, where light pulses enable or disable firing of specific neurons in a living brain."

Watanabe's experiment was the first of its kind to make use of both electrophysiology and optogenetics at the same time in animal test subjects exposed to the neon-color-spreading illusion, which allowed his team to see precisely what structures within the brain are responsible for processing the illusion.

"After a visual stimulus lands on the eye, it's carried to the brain by nerves and is then received by a series of layers of neurons called V1, V2 and so on, where V1 is the first and most basic layer, and V2 and above are considered higher layers," said Watanabe. "There is a long-standing debate in neuroscience about the role higher levels play in the perception of brightness and it was not an easy thing to study. Our experiment on mice has shown us that neurons in V1 responded not just to the illusion, but also to a nonillusory version of the same kind of pattern shown. But only when the illusory version was shown to the mice did neurons in V2 also play a crucial role: that of modulating the activity of neurons in V1, thus proving that V2 neurons do in fact play a role in the perception of brightness."

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RNA that doesn't age

Certain RNA molecules in the nerve cells in the brain last a life time without being renewed. Neuroscientists from Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) have now demonstrated that this is the case together with researchers from Germany, Austria and the USA. RNAs are generally short-lived molecules that are constantly reconstructed to adjust to environmental conditions. With their findings that have now been published in the journal Science, the research group hopes to decipher the complex aging process of the brain and gain a better understanding of related degenerative diseases.

Most cells in the human body are regularly renewed, thereby retaining their vitality.

However, there are exceptions: the heart, the pancreas and the brain consist of cells that do not renew throughout the whole lifespan, and yet still have to remain in full working order.

"Aging neurons are an important risk factor for neurodegenerative illnesses such as Alzheimer's," says Prof.

Dr. Tomohisa Toda, Professor of Neural Epigenomics at FAU and at the Max Planck Center for Physics and Medicine in Erlangen.

"A basic understanding of the aging process and which key components are involved in maintaining cell function is crucial for effective treatment concepts:"

In a joint study conducted together with neuroscientists from Dresden, La Jolla (USA) and Klosterneuburg (Austria), the working group led by Toda has now identified a key component of brain aging: the researchers were able to demonstrate for the first time that certain types of ribonucleic acid (RNA) that protect genetic material exist just as long as the neurons themselves.

"This is surprising, as unlike DNA, which as a rule never changes, most RNA molecules are extremely short-lived and are constantly being exchanged," Toda explains.

In order to determine the life span of the RNA molecules, the Toda group worked together with the team from Prof.

Dr. Martin Hetzer, a cell biologist at the Institute of Science and Technology Austria (ISTA). "We succeeded in marking the RNAs with fluorescent molecules and tracking their lifespan in mice brain cells," explains Tomohisa Toda, who has unique expertise in epigenetics and neurobiology and who was awarded an ERC Consolidator Grant for his research in 2023.

"We were even able to identify the marked long-lived RNAs in two year old animals, and not just in their neurons, but also in somatic adult neural stem cells in the brain."

In addition, the researchers discovered that the long-lived RNAs, that they referred to as LL-RNA for short, tend to be located in the cells' nuclei, closely connected to chromatin, a complex of DNA and proteins that forms chromosomes.

This indicates that LL-RNA play a key role in regulating chromatin.

In order to confirm this hypothesis, the team reduced the concentration of LL-RNA in an in-vitro experiment with adult neural stem cell models, with the result that the integrity of the chromatin was strongly impaired.

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The brain is 'programmed' for learning from people we like

Our brains are "programmed" to learn more from people we like -- and less from those we dislike. This has been shown by researchers in cognitive neuroscience in a series of experiments.

Memory serves a vital function, enabling us to learn from new experiences and update existing knowledge.

We learn both from individual experiences and from connecting them to draw new conclusions about the world.

This way, we can make inferences about things that we don't necessarily have direct experience of. This is called memory integration and makes learning quick and flexible.

Inês Bramão, associate professor of psychology at Lund University, provides an example of memory integration: Say you're walking in a park.

You see a man with a dog. A few hours later, you see the dog in the city with a woman.

Your brain quickly makes the connection that the man and woman are a couple even though you have never seen them together.

"Making such inferences is adaptive and helpful. But of course, there's a risk that our brain draws incorrect conclusions or remembers selectively," says Inês Bramão.

Important who provides the information

To examine what affects our ability to learn and make inferences, Inês Bramão, along with colleagues Marius Boeltzig and Mikael Johansson, set up experiments where participants were tasked with remembering and connecting different objects.

It could be a bowl, ball, spoon, scissors, or other everyday objects.

It turned out that memory integration, i.e., the ability to remember and connect information across learning events, was influenced by who presented it. If it was a person the participant liked, connecting the information was easier compared to when the information came from someone the participant disliked.

The participants provided individual definitions of 'like' and 'dislike' based on aspects such as political views, major, eating habits, favorite sports, hobbies, and music.

Can be translated to politics

The findings can be applied in real life, according to the researchers.

Inês Bramão takes a hypothetical example from politics:

"A political party argues for raising taxes to benefit healthcare. Later, you visit a healthcare center and notice improvements have been made. If you sympathize with the party that wanted to improve healthcare through higher taxes, you're likely to attribute the improvements to the tax increase, even though the improvements might have had a completely different cause."

About fundamental mechanisms

There's already vast research describing that people learn information differently depending on the source and how that characterizes polarization and knowledge resistance.

"What our research shows is how these significant phenomena can partly be traced back to fundamental principles that govern how our memory works," says Mikael Johansson, professor of psychology at Lund University.

We are more inclined to form new connections and update knowledge from information presented by groups we favor.

Innate way of handling information

Understanding the roots of polarization, resistance to new knowledge, and related phenomena from basic brain functions offers a deeper insight into these complex behaviors, the researchers argue.

So, it's not just about filter bubbles on social media but also about an innate way of assimilating information.

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Surprisingly simple model explains how brain cells organize and connect

A new study by physicists and neuroscientists from the University of Chicago, Harvard and Yale describes how connectivity among neurons comes about through general principles of networking and self-organization, rather than the biological features of an individual organism.

The research, published on January 17, 2024 in Nature Physics, accurately describes neuronal connectivity in a variety of model organisms and could apply to non-biological networks like social interactions as well.

"When you're building simple models to explain biological data, you expect to get a good rough cut that fits some but not all scenarios," said Stephanie Palmer, PhD, Associate Professor of Physics and Organismal Biology and Anatomy at UChicago and senior author of the paper.

"You don't expect it to work as well when you dig into the minutiae, but when we did that here, it ended up explaining things in a way that was really satisfying."

Understanding how neurons connect

Neurons form an intricate web of connections between synapses to communicate and interact with each other.

While the vast number of connections may seem random, networks of brain cells tend to be dominated by a small number of connections that are much stronger than most.

This "heavy-tailed" distribution of connections (so-called because of the way it looks when plotted on a graph) forms the backbone of circuitry that allows organisms to think, learn, communicate and move.

Despite the importance of these strong connections, scientists were unsure if this heavy-tailed pattern arises because of biological processes specific to different organisms, or due to basic principles of network organization.

To answer these questions, Palmer and Christopher Lynn, PhD, Assistant Professor of Physics at Yale University, and Caroline Holmes, PhD, a postdoctoral researcher at Harvard University, analyzed connectomes, or maps of brain cell connections.

The connectome data came from several different classic lab animals, including fruit flies, roundworms, marine worms and the mouse retina.

To understand how neurons form connections to one another, they developed a model based on Hebbian dynamics, a term coined by Canadian psychologist Donald Hebb in 1949 that essentially says, "neurons that fire together, wire together." This means the more two neurons activate together, the stronger their connection becomes.

Across the board, the researchers found these Hebbian dynamics produce "heavy-tailed" connection strengths just like they saw in the different organisms.

The results indicate that this kind of organization arises from general principles of networking, rather than something specific to the biology of fruit flies, mice, or worms.

The model also provided an unexpected explanation for another networking phenomenon called clustering, which describes the tendency of cells to link with other cells via connections they share.

A good example of clustering occurs in social situations. If one person introduces a friend to a third person, those two people are more likely to become friends with them than if they met separately.

"These are mechanisms that everybody agrees are fundamentally going to happen in neuroscience," Holmes said.

"But we see here that if you treat the data carefully and quantitatively, it can give rise to all of these different effects in clustering and distributions, and then you see those things across all of these different organisms."

Accounting for randomness

As Palmer pointed out, though, biology doesn't always fit a neat and tidy explanation, and there is still plenty of randomness and noise involved in brain circuits.

Neurons sometimes disconnect and rewire with each other -- weak connections are pruned, and stronger connections can be formed elsewhere.

This randomness provides a check on the kind of Hebbian organization the researchers found in this data, without which strong connections would grow to dominate the network.

The researchers tweaked their model to account for randomness, which improved its accuracy.

"Without that noise aspect, the model would fail," Lynn said.

"It wouldn't produce anything that worked, which was surprising to us. It turns out you actually need to balance the Hebbian snowball effect with the randomness to get everything to look like real brains."

Since these rules arise from general networking principles, the team hopes they can extend this work beyond the brain.

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From the first bite, our sense of taste helps pace our eating

When you eagerly dig into a long-awaited dinner, signals from your stomach to your brain keep you from eating so much you'll regret it -- or so it's been thought. That theory had never really been directly tested until a team of scientists at UC San Francisco recently took up the question.

The picture, it turns out, is a little different.

The team, led by Zachary Knight, PhD, a UCSF professor of physiology in the Kavli Institute for Fundamental Neuroscience, discovered that it's our sense of taste that pulls us back from the brink of food inhalation on a hungry day. Stimulated by the perception of flavor, a set of neurons -- a type of brain cell -- leaps to attention almost immediately to curtail our food intake.

"We've uncovered a logic the brainstem uses to control how fast and how much we eat, using two different kinds of signals, one coming from the mouth, and one coming much later from the gut," said Knight, who is also an investigator with the Howard Hughes Medical Institute and a member of the UCSF Weill Institute for Neurosciences. "This discovery gives us a new framework to understand how we control our eating."

The study, which appears Nov. 22, 2023 in Nature, could help reveal exactly how weight-loss drugs like Ozempic work, and how to make them more effective.

New views into the brainstem

Pavlov proposed over a century ago that the sight, smell and taste of food are important for regulating digestion. More recent studies in the 1970s and 1980s have also suggested that the taste of food may restrain how fast we eat, but it's been impossible to study the relevant brain activity during eating because the brain cells that control this process are located deep in the brainstem, making them hard to access or record in an animal that's awake.

Over the years, the idea had been forgotten, Knight said.

New techniques developed by lead author Truong Ly, PhD, a graduate student in Knight's lab, allowed for the first-ever imaging and recording of a brainstem structure critical for feeling full, called the nucleus of the solitary tract, or NTS, in an awake, active mouse. He used those techniques to look at two types of neurons that have been known for decades to have a role in food intake.

The team found that when they put food directly into the mouse's stomach, brain cells called PRLH (for prolactin-releasing hormone) were activated by nutrient signals sent from the GI tract, in line with traditional thinking and the results of prior studies.

However, when they allowed the mice to eat the food as they normally would, those signals from the gut didn't show up. Instead, the PRLH brain cells switched to a new activity pattern that was entirely controlled by signals from the mouth.

"It was a total surprise that these cells were activated by the perception of taste," said Ly. "It shows that there are other components of the appetite-control system that we should be thinking about."

While it may seem counterintuitive for our brains to slow eating when we're hungry, the brain is actually using the taste of food in two different ways at the same time. One part is saying, "This tastes good, eat more," and another part is watching how fast you're eating and saying, "Slow down or you're going to be sick."

"The balance between those is how fast you eat," said Knight.

The activity of the PRLH neurons seems to affect how palatable the mice found the food, Ly said. That meshes with our human experience that food is less appetizing once you've had your fill of it.

Brain cells that inspire weight-loss drugs

The PRLH-neuron-induced slowdown also makes sense in terms of timing. The taste of food triggers these neurons to switch their activity in seconds, from keeping tabs on the gut to responding to signals from the mouth.

Meanwhile, it takes many minutes for a different group of brain cells, called CGC neurons, to begin responding to signals from the stomach and intestines. These cells act over much slower time scales -- tens of minutes -- and can hold back hunger for a much longer period of time.

"Together, these two sets of neurons create a feed-forward, feed-back loop," said Knight. "One is using taste to slow things down and anticipate what's coming. The other is using a gut signal to say, 'This is how much I really ate. Ok, I'm full now!'"

The CGC brain cells' response to stretch signals from the gut is to release GLP-1, the hormone mimicked by Ozempic, Wegovy and other new weight-loss drugs.

These drugs act on the same region of the brainstem that Ly's technology has finally allowed researchers to study. "Now we have a way of teasing apart what's happening in the brain that makes these drugs work," he said.

A deeper understanding of how signals from different parts of the body control appetite would open doors to designing weight-loss regimens designed for the individual ways people eat by optimizing how the signals from the two sets of brain cells interact, the researchers said.

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Scientists regenerate neurons that restore walking in mice after paralysis from spinal cord injury

In a new study in mice, a team of researchers from UCLA, the Swiss Federal Institute of Technology, and Harvard University have uncovered a crucial component for restoring functional activity after spinal cord injury. The neuroscientists have shown that re-growing specific neurons back to their natural target regions led to recovery, while random regrowth was not effective.

In a 2018 study published in Nature, the team identified a treatment approach that triggers axons -- the tiny fibers that link nerve cells and enable them to communicate -- to regrow after spinal cord injury in rodents. But even as that approach successfully led to the regeneration of axons across severe spinal cord lesions, achieving functional recovery remained a significant challenge.

For the new study, published this week in Science, the team aimed to determine whether directing the regeneration of axons from specific neuronal subpopulations to their natural target regions could lead to meaningful functional restoration after spinal cord injury in mice. They first used advanced genetic analysis to identify nerve cell groups that enable walking improvement after a partial spinal cord injury.

The researchers then found that merely regenerating axons from these nerve cells across the spinal cord lesion without specific guidance had no impact on functional recovery. However, when the strategy was refined to include using chemical signals to attract and guide the regeneration of these axons to their natural target region in the lumbar spinal cord, significant improvements in walking ability were observed in a mouse model of complete spinal cord injury.

"Our study provides crucial insights into the intricacies of axon regeneration and requirements for functional recovery after spinal cord injuries," said Michael Sofroniew, MD, PhD, professor of neurobiology at the David Geffen School of Medicine at UCLA and a senior author of the new study. "It highlights the necessity of not only regenerating axons across lesions but also of actively guiding them to reach their natural target regions to achieve meaningful neurological restoration."

The authors say understanding that re-establishing the projections of specific neuronal subpopulations to their natural target regions holds significant promise for the development of therapies aimed at restoring neurological functions in larger animals and humans. However, the researchers also acknowledge the complexity of promoting regeneration over longer distances in non-rodents, necessitating strategies with intricate spatial and temporal features. Still, they conclude that applying the principles laid out in their work "will unlock the framework to achieve meaningful repair of the injured spinal cord and may expedite repair after other forms of central nervous system injury and disease."

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Brain recordings capture musicality of speech -- with help from Pink Floyd

As the chords of Pink Floyd's "Another Brick in the Wall, Part 1," filled the surgery suite, neuroscientists at Albany Medical Center diligently recorded the activity of electrodes placed on the brains of patients undergoing epilepsy surgery.

The goal? To capture the electrical activity of brain regions tuned to attributes of the music -- tone, rhythm, harmony and words -- to see if they could reconstruct what the patient was hearing.

More than a decade later, after detailed analysis of data from 29 such patients by neuroscientists at the University of California, Berkeley, the answer is clearly yes.

The phrase "All in all it was just a brick in the wall" comes through recognizably in the reconstructed song, its rhythms intact, and the words muddy, but decipherable. This is the first time researchers have reconstructed a recognizable song from brain recordings.

The reconstruction shows the feasibility of recording and translating brain waves to capture the musical elements of speech, as well as the syllables. In humans, these musical elements, called prosody -- rhythm, stress, accent and intonation -- carry meaning that the words alone do not convey.

Because these intracranial electroencephalography (iEEG) recordings can be made only from the surface of the brain -- as close as you can get to the auditory centers -- no one will be eavesdropping on the songs in your head anytime soon.

But for people who have trouble communicating, whether because of stroke or paralysis, such recordings from electrodes on the brain surface could help reproduce the musicality of speech that's missing from today's robot-like reconstructions.

"It's a wonderful result," said Robert Knight, a neurologist and UC Berkeley professor of psychology in the Helen Wills Neuroscience Institute who conducted the study with postdoctoral fellow Ludovic Bellier. "One of the things for me about music is it has prosody and emotional content. As this whole field of brain machine interfaces progresses, this gives you a way to add musicality to future brain implants for people who need it, someone who's got ALS or some other disabling neurological or developmental disorder compromising speech output. It gives you an ability to decode not only the linguistic content, but some of the prosodic content of speech, some of the affect. I think that's what we've really begun to crack the code on."

As brain recording techniques improve, it may be possible someday to make such recordings without opening the brain, perhaps using sensitive electrodes attached to the scalp. Currently, scalp EEG can measure brain activity to detect an individual letter from a stream of letters, but the approach takes at least 20 seconds to identify a single letter, making communication effortful and difficult, Knight said.

"Noninvasive techniques are just not accurate enough today. Let's hope, for patients, that in the future we could, from just electrodes placed outside on the skull, read activity from deeper regions of the brain with a good signal quality. But we are far from there," Bellier said.

Bellier, Knight and their colleagues reported the results today in the journal PLOS Biology, noting that they have added "another brick in the wall of our understanding of music processing in the human brain."

Reading your mind? Not yet.

The brain machine interfaces used today to help people communicate when they're unable to speak can decode words, but the sentences produced have a robotic quality akin to how the late Stephen Hawking sounded when he used a speech-generating device.

"Right now, the technology is more like a keyboard for the mind," Bellier said. "You can't read your thoughts from a keyboard. You need to push the buttons. And it makes kind of a robotic voice; for sure there's less of what I call expressive freedom."

Bellier should know. He has played music since childhood -- drums, classical guitar, piano and bass, at one point performing in a heavy metal band. When Knight asked him to work on the musicality of speech, Bellier said, "You bet I was excited when I got the proposal."

In 2012, Knight, postdoctoral fellow Brian Pasley and their colleagues were the first to reconstruct the words a person was hearing from recordings of brain activity alone.

More recently, other researchers have taken Knight's work much further. Eddie Chang, a UC San Francisco neurosurgeon and senior co-author of the 2012 paper, has recorded signals from the motor area of the brain associated with jaw, lip and tongue movements to reconstruct the speech intended by a paralyzed patient, with the words displayed on a computer screen.

That work, reported in 2021, employed artificial intelligence to interpret the brain recordings from a patient trying to vocalize a sentence based on a set of 50 words.

While Chang's technique is proving successful, the new study suggests that recording from the auditory regions of the brain, where all aspects of sound are processed, can capture other aspects of speech that are important in human communication.

"Decoding from the auditory cortices, which are closer to the acoustics of the sounds, as opposed to the motor cortex, which is closer to the movements that are done to generate the acoustics of speech, is super promising," Bellier added. "It will give a little color to what's decoded."

For the new study, Bellier reanalyzed brain recordings obtained in 2012 and 2013 as patients were played an approximately 3-minute segment of the Pink Floyd song, which is from the 1979 album The Wall. He hoped to go beyond previous studies, which had tested whether decoding models could identify different musical pieces and genres, to actually reconstruct music phrases through regression-based decoding models.

Bellier emphasized that the study, which used artificial intelligence to decode brain activity and then encode a reproduction, did not merely create a black box to synthesize speech. He and his colleagues were also able to pinpoint new areas of the brain involved in detecting rhythm, such as a thrumming guitar, and discovered that some portions of the auditory cortex -- in the superior temporal gyrus, located just behind and above the ear -- respond at the onset of a voice or a synthesizer, while other areas respond to sustained vocals.

The researchers also confirmed that the right side of the brain is more attuned to music than the left side.

"Language is more left brain. Music is more distributed, with a bias toward right," Knight said.

"It wasn't clear it would be the same with musical stimuli," Bellier said. "So here we confirm that that's not just a speech-specific thing, but that's it's more fundamental to the auditory system and the way it processes both speech and music."

Knight is embarking on new research to understand the brain circuits that allow some people with aphasia due to stroke or brain damage to communicate by singing when they cannot otherwise find the words to express themselves.

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New study links brain waves directly to memory

Neurons produce rhythmic patterns of electrical activity in the brain. One of the unsettled questions in the field of neuroscience is what primarily drives these rhythmic signals, called oscillations. University of Arizona researchers have found that simply remembering events can trigger them, even more so than when people are experiencing the actual event.

The researchers, whose findings are published in the journal Neuron, specifically focused on what are known as theta oscillations, which emerge in the brain's hippocampus region during activities like exploration, navigation and sleep. The hippocampus plays a crucial role in the brain's ability to remember the past.

Prior to this study, it was believed that the external environment played a more important role in driving theta oscillations, said Arne Ekstrom, professor of cognition and neural systems in the UArizona Department of Psychology and senior author of the study. But Ekstrom and his collaborators found that memory generated in the brain is the main driver of theta activity.

"Surprisingly, we found that theta oscillations in humans are more prevalent when someone is just remembering things, compared to experiencing events directly," said lead study author Sarah Seger, a graduate student in the Department of Neuroscience.

The results of the study could have implications for treating patients with brain damage and cognitive impairments, including patients who have experienced seizures, stroke and Parkinson's disease, Ekstrom said. Memory could be used to create stimulations from within the brain and drive theta oscillations, which could potentially lead to improvements in memory over time, he said.

UArizona researchers collaborated on the study with researchers from the University of Texas Southwestern Medical Center in Dallas, including neurosurgeon Dr. Brad Lega and research technician Jennifer Kriegel. The researchers recruited 13 patients who were being monitored at the center in preparation for epilepsy surgery. As part of the monitoring, electrodes were implanted in the patients' brains for detecting occasional seizures. The researchers recorded the theta oscillations in the hippocampus of the brain.

The patients participated in a virtual reality experiment, in which they were given a joystick to navigate to shops in a virtual city on a computer. When they arrived at the correct destination, the virtual reality experiment was paused. The researchers asked the participants to imagine the location at which they started their navigation and instructed them to mentally navigate the route they just passed through. The researchers then compared theta oscillations during initial navigation to participants' subsequent recollection of the route.

During the actual navigation process using the joystick, the oscillations were less frequent and shorter in duration compared to oscillations that occurred when participants were just imagining the route. So, the researchers conclude that memory is a strong driver of theta oscillations in humans.

One way to compensate for impaired cognitive function is by using cognitive training and rehabilitation, Ekstrom said.

"Basically, you take a patient who has memory impairments, and you try to teach them to be better at memory," he said.

In the future, Ekstrom is planning to conduct this research in freely walking patients as opposed to patients in beds and find how freely navigating compares to memory with regard to brain oscillations.

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Scientists complete first map of an insect brain

Researchers have completed the most advanced brain map to date, that of an insect, a landmark achievement in neuroscience that brings scientists closer to true understanding of the mechanism of thought.

The international team led by Johns Hopkins University and the University of Cambridge produced a breathtakingly detailed diagram tracing every neural connection in the brain of a larval fruit fly, an archetypal scientific model with brains comparable to humans.

The work, likely to underpin future brain research and to inspire new machine learning architectures, appears today in the journal Science.

"If we want to understand who we are and how we think, part of that is understanding the mechanism of thought," said senior author Joshua T. Vogelstein, a Johns Hopkins biomedical engineer who specializes in data-driven projects including connectomics, the study of nervous system connections. "And the key to that is knowing how neurons connect with each other."

The first attempt at mapping a brain -- a 14-year study of the roundworm begun in the 1970s, resulted in a partial map and a Nobel Prize. Since then, partial connectomes have been mapped in many systems, including flies, mice, and even humans, but these reconstructions typically only represent only a tiny fraction of the total brain. Comprehensive connectomes have only been generated for several small species with a few hundred to a few thousand neurons in their bodies-a roundworm, a larval sea squirt, and a larval marine annelid worm.

This team's connectome of a baby fruit fly, Drosophila melanogaster larva, is the most complete as well as the most expansive map of an entire insect brain ever completed. It includes 3,016 neurons and every connection between them: 548,000.

"It's been 50 years and this is the first brain connectome. It's a flag in the sand that we can do this," Vogelstein said. "Everything has been working up to this."

Mapping whole brains is difficult and extremely time-consuming, even with the best modern technology. Getting a complete cellular-level picture of a brain requires slicing the brain into hundreds or thousands of individual tissue samples, all of which have to be imaged with electron microscopes before the painstaking process of reconstructing all those pieces, neuron by neuron, into a full, accurate portrait of a brain. It took more than a decade to do that with the baby fruit fly. The brain of a mouse is estimated to be a million times larger than that of a baby fruit fly, meaning the chance of mapping anything close to a human brain isn't likely in the near future, maybe not even in our lifetimes.

The team purposely chose the fruit fly larva because, for an insect, the species shares much of its fundamental biology with humans, including a comparable genetic foundation. It also has rich learning and decision-making behaviors, making it a useful model organism in neuroscience. And for practical purposes, its relatively compact brain can be imaged and its circuits reconstructed within a reasonable time frame.

Even so, the work took the University of Cambridge and Johns Hopkins 12 years. The imaging alone took about a day per neuron.

Cambridge researchers created the high-resolution images of the brain and manually studied them to find individual neurons, rigorously tracing each one and linking their synaptic connections.

Cambridge handed off the data to Johns Hopkins, where the team spent more than three years using original code they created to analyze the brain's connectivity. The Johns Hopkins team developed techniques to find groups of neurons based on shared connectivity patterns, and then analyzed how information could propagate through the brain.

In the end, the full team charted every neuron and every connection, and categorized each neuron by the role it plays in the brain. They found that the brain's busiest circuits were those that led to and away from neurons of the learning center.

The methods Johns Hopkins developed are applicable to any brain connection project, and their code is available to whoever attempts to map an even larger animal brain, Vogelstein said, adding that despite the challenges, scientists are expected to take on the mouse, possibly within the next decade. Other teams are already working on a map of the adult fruit fly brain. Co-first author Benjamin Pedigo, a Johns Hopkins doctoral candidate in Biomedical Engineering, expects the team's code could help reveal important comparisons between connections in the adult and larval brain. As connectomes are generated for more larva and from other related species, Pedigo expects their analysis techniques could lead to better understanding of variations in brain wiring.

The fruit fly larva work showed circuit features that were strikingly reminiscent of prominent and powerful machine learning architectures. The team expects continued study will reveal even more computational principles and potentially inspire new artificial intelligence systems.

"What we learned about code for fruit flies will have implications for the code for humans," Vogelstein said. "That's what we want to understand -- how to write a program that leads to a human brain network."

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Learning with all your senses: Multimodal enrichment as the optimal learning strategy of the future

Many educational approaches assume that integrating complementary sensory and motor information into the learning experience can enhance learning, for example gestures help in learning new vocabulary in foreign language classes. In her recent publication, neuroscientist Katharina von Kriegstein from Technische Universität Dresden and Brian Mathias of the University of Aberdeen summarize these methods under the term "multimodal enrichment." This means enrichment with multiple senses and movement. Numerous current scientific studies prove that multimodal enrichment can enhance learning outcomes. Experiments in classrooms show similar results.

In the review article, the two researchers compare these findings with cognitive, neuroscience, and computational theories of multimodal enrichment. Recent neuroscience research has found that the positive effects of enriched learning are associated with response in brain regions that serve perception and motor function. For example, hearing a recently learned foreign language word, may elicit activity in motor brain regions if the word was associated with the performance of a congruent gesture during learning. These brain responses are causal to the benefits of multimodal enrichment for learning outcome. Computer algorithms confirm this hypothesis.

"The brain is optimized for learning with all the senses and with movement. Brain structures for perception and motor skills work together to promote this type of learning. We hope that our deeper understanding of the brain's learning mechanisms, will facilitate the development of optimal learning strategies in the future," explains Brian Mathias.

Katharina von Kriegstein adds, "The results of the literature we reviewed contribute to our understanding of why several long-used learning strategies, such as parts of the Montessori method, are effective. They also provide clear clues as to why some approaches are not as effective. Recently uncovered neuroscientific mechanisms may inspire the updating of cognitive and computational theories of learning, providing new hypotheses about learning. We anticipate that such an interdisciplinary and evidence-based approach will lead to the optimization of learning and teaching strategies in the future, for both humans and artificial systems."

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Human brain organoids implanted into mouse cortex respond to visual stimuli for first time

A team of engineers and neuroscientists has demonstrated for the first time that human brain organoids implanted in mice have established functional connectivity to the animals' cortex and responded to external sensory stimuli. The implanted organoids reacted to visual stimuli in the same way as surrounding tissues, an observation that researchers were able to make in real time over several months thanks to an innovative experimental setup that combines transparent graphene microelectrode arrays and two-photon imaging.

The team, led by Duygu Kuzum, a faculty member in the University of California San Diego Department of Electrical and Computer Engineering, details their findings in the Dec. 26 issue of the journal Nature Communications. Kuzum's team collaborated with researchers from Anna Devor's lab at Boston University; Alysson R. Muotri's lab at UC San Diego; and Fred H. Gage's lab at the Salk Institute.

Human cortical organoids are derived from human induced pluripotent stem cells, which are usually derived themselves from skin cells. These brain organoids have recently emerged as promising models to study the development of the human brain, as well as a range of neurological conditions.

But until now, no research team had been able to demonstrate that human brain organoids implanted in the mouse cortex were able to share the same functional properties and react to stimuli in the same way. This is because the technologies used to record brain function are limited, and are generally unable to record activity that lasts just a few milliseconds.

The UC San Diego-led team was able to solve this problem by developing experiments that combine microelectrode arrays made from transparent graphene, and two-photon imaging, a microscopy technique that can image living tissue up to one millimeter in thickness.

"No other study has been able to record optically and electrically at the same time," said Madison Wilson, the paper's first author and a Ph.D. student in Kuzum's research group at UC San Diego. "Our experiments reveal that visual stimuli evoke electrophysiological responses in the organoids, matching the responses from the surrounding cortex."

The researchers hope that this combination of innovative neural recording technologies to study organoids will serve as a unique platform to comprehensively evaluate organoids as models for brain development and disease, and investigate their use as neural prosthetics to restore function to lost, degenerated or damaged brain regions.

"This experimental setup opens up unprecedented opportunities for investigations of human neural network-level dysfunctions underlying developmental brain diseases," said Kuzum.

Kuzum's lab first developed the transparent graphene electrodes in 2014 and has been advancing the technology since then. The researchers used platinum nanoparticles to lower the impedance of graphene electrodes by 100 times while keeping them transparent. The low-impedance graphene electrodes are able to record and image neuronal activity at both the macroscale and single cell levels.

By placing an array of these electrodes on top of the transplanted organoids, researchers were able to record neural activity electrically from both the implanted organoid and the surrounding host cortex in real time. Using two-photon imaging, they also observed that mouse blood vessels grew into the organoid providing necessary nutrients and oxygen to the implant.

Researchers applied a visual stimulus-an optical white light LED-to the mice with implanted organoids, while the mice were under two-photon microscopy. They observed electrical activity in the electrode channels above the organoids showing that the organoids were reacting to the stimulus in the same way as surrounding tissue. The electrical activity propagated from the area closest to the visual cortex in the implanted organoids area through functional connections. In addition, their low noise transparent graphene electrode technology enabled electrical recording of spiking activity from the organoid and the surrounding mouse cortex. Graphene recordings showed increases in the power of gamma oscillations and phase locking of spikes from organoids to slow oscillations from mouse visual cortex. These findings suggest that the organoids had established synaptic connections with surrounding cortex tissue three weeks after implantation, and received functional input from the mouse brain. Researchers continued these chronic multimodal experiments for eleven weeks and showed functional and morphological integration of implanted human brain organoids with the host mice cortex.

Next steps include longer experiments involving neurological disease models, as well as incorporating calcium imaging in the experimental set up to visualize spiking activity in organoid neurons. Other methods could also be used to trace axonal projections between organoid and mouse cortex.

"We envision that, further along the road, this combination of stem cells and neurorecording technologies will be used for modeling disease under physiological conditions; examining candidate treatments on patient-specific organoids; and evaluating organoids' potential to restore specific lost, degenerated or damaged brain regions," Kuzum said.

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Silent synapses are abundant in the adult brain

MIT neuroscientists have discovered that the adult brain contains millions of "silent synapses" -- immature connections between neurons that remain inactive until they're recruited to help form new memories.

Until now, it was believed that silent synapses were present only during early development, when they help the brain learn the new information that it's exposed to early in life. However, the new MIT study revealed that in adult mice, about 30 percent of all synapses in the brain's cortex are silent.

The existence of these silent synapses may help to explain how the adult brain is able to continually form new memories and learn new things without having to modify existing conventional synapses, the researchers say.

"These silent synapses are looking for new connections, and when important new information is presented, connections between the relevant neurons are strengthened. This lets the brain create new memories without overwriting the important memories stored in mature synapses, which are harder to change," says Dimitra Vardalaki, an MIT graduate student and the lead author of the new study.

Mark Harnett, an associate professor of brain and cognitive sciences, is the senior author of the paper, which appears today in Nature. Kwanghun Chung, an associate professor of chemical engineering at MIT, is also an author.

A surprising discovery

When scientists first discovered silent synapses decades ago, they were seen primarily in the brains of young mice and other animals. During early development, these synapses are believed to help the brain acquire the massive amounts of information that babies need to learn about their environment and how to interact with it. In mice, these synapses were believed to disappear by about 12 days of age (equivalent to the first months of human life).

However, some neuroscientists have proposed that silent synapses may persist into adulthood and help with the formation of new memories. Evidence for this has been seen in animal models of addiction, which is thought to be largely a disorder of aberrant learning.

Theoretical work in the field from Stefano Fusi and Larry Abbott of Columbia University has also proposed that neurons must display a wide range of different plasticity mechanisms to explain how brains can both efficiently learn new things and retain them in long-term memory. In this scenario, some synapses must be established or modified easily, to form the new memories, while others must remain much more stable, to preserve long-term memories.

In the new study, the MIT team did not set out specifically to look for silent synapses. Instead, they were following up on an intriguing finding from a previous study in Harnett's lab. In that paper, the researchers showed that within a single neuron, dendrites -- antenna-like extensions that protrude from neurons -- can process synaptic input in different ways, depending on their location.

As part of that study, the researchers tried to measure neurotransmitter receptors in different dendritic branches, to see if that would help to account for the differences in their behavior. To do that, they used a technique called eMAP (epitope-preserving Magnified Analysis of the Proteome), developed by Chung. Using this technique, researchers can physically expand a tissue sample and then label specific proteins in the sample, making it possible to obtain super-high-resolution images.

While they were doing that imaging, they made a surprising discovery. "The first thing we saw, which was super bizarre and we didn't expect, was that there were filopodia everywhere," Harnett says.

Filopodia, thin membrane protrusions that extend from dendrites, have been seen before, but neuroscientists didn't know exactly what they do. That's partly because filopodia are so tiny that they are difficult to see using traditional imaging techniques.

After making this observation, the MIT team set out to try to find filopodia in other parts of the adult brain, using the eMAP technique. To their surprise, they found filopodia in the mouse visual cortex and other parts of the brain, at a level 10 times higher than previously seen. They also found that filopodia had neurotransmitter receptors called NMDA receptors, but no AMPA receptors.

A typical active synapse has both of these types of receptors, which bind the neurotransmitter glutamate. NMDA receptors normally require cooperation with AMPA receptors to pass signals because NMDA receptors are blocked by magnesium ions at the normal resting potential of neurons. Thus, when AMPA receptors are not present, synapses that have only NMDA receptors cannot pass along an electric current and are referred to as "silent."

Unsilencing synapses

To investigate whether these filopodia might be silent synapses, the researchers used a modified version of an experimental technique known as patch clamping. This allowed them to monitor the electrical activity generated at individual filopodia as they tried to stimulate them by mimicking the release of the neurotransmitter glutamate from a neighboring neuron.

Using this technique, the researchers found that glutamate would not generate any electrical signal in the filopodium receiving the input, unless the NMDA receptors were experimentally unblocked. This offers strong support for the theory the filopodia represent silent synapses within the brain, the researchers say.

The researchers also showed that they could "unsilence" these synapses by combining glutamate release with an electrical current coming from the body of the neuron. This combined stimulation leads to accumulation of AMPA receptors in the silent synapse, allowing it to form a strong connection with the nearby axon that is releasing glutamate.

The researchers found that converting silent synapses into active synapses was much easier than altering mature synapses.

"If you start with an already functional synapse, that plasticity protocol doesn't work," Harnett says. "The synapses in the adult brain have a much higher threshold, presumably because you want those memories to be pretty resilient. You don't want them constantly being overwritten. Filopodia, on the other hand, can be captured to form new memories."

"Flexible and robust"

The findings offer support for the theory proposed by Abbott and Fusi that the adult brain includes highly plastic synapses that can be recruited to form new memories, the researchers say.

"This paper is, as far as I know, the first real evidence that this is how it actually works in a mammalian brain," Harnett says. "Filopodia allow a memory system to be both flexible and robust. You need flexibility to acquire new information, but you also need stability to retain the important information."

The researchers are now looking for evidence of these silent synapses in human brain tissue. They also hope to study whether the number or function of these synapses is affected by factors such as aging or neurodegenerative disease.

"It's entirely possible that by changing the amount of flexibility you've got in a memory system, it could become much harder to change your behaviors and habits or incorporate new information," Harnett says. "You could also imagine finding some of the molecular players that are involved in filopodia and trying to manipulate some of those things to try to restore flexible memory as we age."

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Mathematicians explain how some fireflies flash in sync

Stake out in Pennsylvania's Cook State Forest at the right time of year and you can see one of nature's great light shows: swarms of fireflies that synchronize their flashes like strings of Christmas lights in the dark.

A new study by Pitt mathematicians shows that math borrowed from neuroscience can describe how swarms of these unique insects coordinate their light show, capturing key details about how they behave in the wild.

"This firefly has a quick sequence of flashes, and then a big pause before the next burst," said Jonathan Rubin, professor and chair of the Department of Mathematics in the Kenneth P. Dietrich School of Arts and Sciences. "We knew a good framework for modeling this that could capture a lot of the features, and we were curious how far we could push it."

Male fireflies produce a glow from their abdomens to call out to potential mates, sending out blinking patterns in the dark to woo females of their own species. Synchronous fireflies of the species Photinus carolinus take it a step further, coordinating their blinking throughout entire swarms. It's a rare trait -- there are only a handful of such species in North America -- and the striking lights they produce draw crowds to locations where the insects are known to gather.

They've also attracted the interest of mathematicians seeking to understand how they synchronize their blinks. It's just one example of how synchronization can evolve from randomness, a process that has intrigued mathematicians for centuries. One famous example from the 1600s showed that pendulum clocks hung next to one another synchronize through vibrations that travel through the wall, and the same branch of math can be used to describe everything from the action of intestines to audience members clapping.

"Synchrony is important for a lot of things, good and bad," said co-author Bard Ermentrout, distinguished professor of mathematics in the Dietrich School. "Physicists, mathematicians, we're all interested in synchronization."

To crack the fireflies' light show, the Pitt team used a more complex model called an "elliptic burster" that's used to describe the behavior of brain cells. The duo, along with then-undergrad Madeline McCrea (A&S '22) published details of their model Oct. 26 in the Journal of the Royal Society Interface.

The first step was to simulate the blinks of a single firefly, then expand to a pair to see how they matched their flashing rates to one another. Next, the team moved to a bigger swarm of simulated insects to see how number, distance and flying speed affect the resulting blinks.

Varying the distances each firefly could "see" each other and respond to one another changed the insects' light show, they found: By tweaking the parameters, they could produce patterns of blinks that looked like either ripples or spirals.

The results line up with several recently published observations about real-life synchronous fireflies -- for instance, that individual fireflies are inconsistent while groups flash more regularly, and that when new fireflies join the swarm, they're already perfectly in time.

"It captured a lot of the finer details that they saw in the biology, which was cool," said Ermentrout. "We didn't expect that."

The math also makes some predictions that could inform firefly research -- for instance, light pollution and the time of day both may alter the patterns produced by fireflies by changing how well they can see one another's blinks.

McCrea worked on the research as an undergraduate supported by the department's Painter Fellowship, which gave her funding to work on the project through the summer. "She was awesome working on this project, and really persistent," said Rubin.

The team is the first to use this particular brain-cell framework to model fireflies, which several different research teams are trying to understand using different types of math. "It's more of a wild west research topic," said Ermentrout. "It's early days, and who knows where things are going to go from here?"

Ermentrout and Rubin also hopeful that the math will capture the imagination of those inspired by the glow of fireflies. In the midst of this project, Rubin himself decided to head up to Cook State Forest to see if he could spot his research subjects firsthand.

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How the brain generates rhythmic behavior

Many of our bodily functions, such as walking, breathing, and chewing, are controlled by brain circuits called central oscillators, which generate rhythmic firing patterns that regulate these behaviors.

MIT neuroscientists have now discovered the neuronal identity and mechanism underlying one of these circuits: an oscillator that controls the rhythmic back-and-forth sweeping of tactile whiskers, or whisking, in mice. This is the first time that any such oscillator has been fully characterized in mammals.

The MIT team found that the whisking oscillator consists of a population of inhibitory neurons in the brainstem that fires rhythmic bursts during whisking. As each neuron fires, it also inhibits some of the other neurons in the network, allowing the overall population to generate a synchronous rhythm that retracts the whiskers from their protracted positions.

"We have defined a mammalian oscillator molecularly, electrophysiologically, functionally, and mechanistically," says Fan Wang, an MIT professor of brain and cognitive sciences and a member of MIT's McGovern Institute for Brain Research. "It's very exciting to see a clearly defined circuit and mechanism of how rhythm is generated in a mammal."

Wang is the senior author of the study, which appears today in Nature. The lead authors of the paper are MIT research scientists Jun Takatoh and Vincent Prevosto.

Rhythmic behavior

Most of the research that clearly identified central oscillator circuits has been done in invertebrates. For example, Eve Marder's lab at Brandeis University found cells in the stomatogastric ganglion in lobsters and crabs that generate oscillatory activity to control rhythmic motion of the digestive tract.

Characterizing oscillators in mammals, especially in awake behaving animals, has proven to be highly challenging. The oscillator that controls walking is believed to be distributed throughout the spinal cord, making it difficult to precisely identify the neurons and circuits involved. The oscillator that generates rhythmic breathing is located in a part of the brain stem called the pre-Bötzinger complex, but the exact identity of the oscillator neurons is not fully understood.

"There haven't been detailed studies in awake behaving animals, where one can record from molecularly identified oscillator cells and manipulate them in a precise way," Wang says.

Whisking is a prominent rhythmic exploratory behavior in many mammals, which use their tactile whiskers to detect objects and sense textures. In mice, whiskers extend and retract at a frequency of about 12 cycles per second. Several years ago, Wang's lab set out try to identify the cells and the mechanism that control this oscillation.

To find the location of the whisking oscillator, the researchers traced back from the motor neurons that innervate whisker muscles. Using a modified rabies virus that infects axons, the researchers were able to label a group of cells presynaptic to these motor neurons in a part of the brainstem called the vibrissa intermediate reticular nucleus (vIRt). This finding was consistent with previous studies showing that damage to this part of the brain eliminates whisking.

The researchers then found that about half of these vIRt neurons express a protein called parvalbumin, and that this subpopulation of cells drives the rhythmic motion of the whiskers. When these neurons are silenced, whisking activity is abolished.

Next, the researchers recorded electrical activity from these parvalbumin-expressing vIRt neurons in brainstem in awake mice, a technically challenging task, and found that these neurons indeed have bursts of activity only during the whisker retraction period. Because these neurons provide inhibitory synaptic inputs to whisker motor neurons, it follows that rhythmic whisking is generated by a constant motor neuron protraction signal interrupted by the rhythmic retraction signal from these oscillator cells.

"That was a super satisfying and rewarding moment, to see that these cells are indeed the oscillator cells, because they fire rhythmically, they fire in the retraction phase, and they're inhibitory neurons," Wang says.

"New principles"

The oscillatory bursting pattern of vIRt cells is initiated at the start of whisking. When the whiskers are not moving, these neurons fire continuously. When the researchers blocked vIRt neurons from inhibiting each other, the rhythm disappeared, and instead the oscillator neurons simply increased their rate of continuous firing.

This type of network, known as recurrent inhibitory network, differs from the types of oscillators that have been seen in the stomatogastric neurons in lobsters, in which neurons intrinsically generate their own rhythm.

"Now we have found a mammalian network oscillator that is formed by all inhibitory neurons," Wang says.

The MIT scientists also collaborated with a team of theorists led by David Golomb at Ben-Gurion University, Israel, and David Kleinfeld at the University of California at San Diego. The theorists created a detailed computational model outlining how whisking is controlled, which fits well with all experimental data. A paper describing that model is appearing in an upcoming issue of Neuron.

Wang's lab now plans to investigate other types of oscillatory circuits in mice, including those that control chewing and licking.

Read more at Science Daily

Sprint then stop? Brain is wired for the math to make it happen

Your new apartment is just a couple of blocks down the street from the bus stop but today you are late and you see the bus roll past you. You break into a full sprint. Your goal is to get to the bus as fast as possible and then to stop exactly in front of the doors (which are never in exactly the same place along the curb) to enter before they close. To stop quickly and precisely enough, a new MIT study in mice finds, the mammalian brain is niftily wired to implement principles of calculus.

One might think that coming to a screeching halt at a target after a flat out run would be as simple as a reflex, but catching a bus or running right up to a visually indicated landmark to earn a water reward (as the mice did), is a learned, visually guided, goal-directed feat. In such tasks, which are a major interest in the lab of senior author Mriganka Sur, Newton Professor of Neuroscience in The Picower Institute for Learning and Memory at MIT, the crucial decision to switch from one behavior (running) to another (stopping) comes from the brain's cortex, where the brain integrates the learned rules of life with sensory information to guide plans and actions.

"The goal is where the cortex comes in," said Sur, a faculty member of MIT's Department of Brain and Cognitive Sciences. "Where am I supposed to stop to achieve this goal of getting on the bus."

And that's also where it gets complicated. The mathematical models of the behavior that postdoc and study lead author Elie Adam developed predicted that a "stop" signal going directly from the M2 region of the cortex to regions in the brainstem, which actually control the legs, would be processed too slowly.

"You have M2 that is sending a stop signal, but when you model it and go through the mathematics, you find that this signal, by itself, would not be fast enough to make the animal stop in time," said Adam, whose work appears in the journal Cell Reports.

So how does the brain speed up the process? What Adam, Sur and co-author Taylor Johns found was that M2 sends the signal to an intermediary region called the subthalamic nucleus (STN), which then sends out two signals down two separate paths that re-converge in the brainstem. Why? Because the difference made by those two signals, one inhibitory and one excitatory, arriving one right after the other turns the problem from one of integration, which is a relatively slow adding up of inputs, to differentiation, which is a direct recognition of change. The shift in calculus implements the stop signal much more quickly.

Adam's model employing systems and control theory from engineering -- accurately -- predicted the speed needed for a proper stop and that differentiation would be necessary to achieve it, but it took a series of anatomical investigations and experimental manipulations to confirm the model's predictions.

First, Adam confirmed that indeed M2 was producing a surge in neural activity only when the mice needed to achieve their trained goal of stopping at the landmark. He also showed it was sending the resulting signals to the STN. Other stops for other reasons did not employ that pathway. Moreover, artificially activating the M2-STN pathway compelled the mice to stop and artificially inhibiting it caused mice overrun the landmark somewhat more often.

The STN certainly then needed to signal the brainstem -- specifically the pedunculopontine nucleus (PPN) in the mesenecephalic locomotor region. But when the scientists looked at neural activity starting in the M2 and then quickly resulting in the PPN, they saw that different types of cells in the PPN responded with different timing. Particularly, before the stop, excitatory cells were active and their activity reflected the speed of the animal during stops. Then, looking at the STN, they saw two kinds of surges of activity around stops -- one slightly slower than the other -- that were conveyed either directly to PPN through excitation or indirectly via the substantia nigra pars reticulata (SNr) through inhibition. The net result of the interplay of these signals in the PPN was an inhibition sharpened by excitation. That sudden change could be quickly found by differentiation to implement stopping.

"An inhibitory surge followed by excitation can create a sharp [change of] signal," Sur said.

The study dovetails with other recent papers. Working with Picower Institute investigator Emery N. Brown, Adam recently produced a new model of how deep brain stimulation in the STN quickly corrects motor problems that result from Parkinson's disease. And last year members of Sur's lab, including Adam, published a study showing how the cortex overrides the brain's more deeply ingrained reflexes in visually guided motor tasks. Together such studies contribute to understanding how the cortex can consciously control instinctually wired motor behaviors but also how important deeper regions, such as the STN, are to quickly implementing goal-directed behavior. A recent review from the lab expounds on this.

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Working memory depends on reciprocal interactions across the brain

How does the brain keep in mind a phone number before dialling? Working memory is an essential component of cognition, allowing the brain to remember information temporarily and use it to guide future behaviour. While many previous studies have revealed the involvement of several brain areas, until now it remained unclear as to how these multiple regions interact to represent and maintain working memory.

In a new study, published today in Nature, neuroscientists at the Sainsbury Wellcome Centre at UCL investigated the reciprocal interactions between two brain regions that represent visual working memory in mice. The team found that communication between these two loci of working memory, parietal cortex and premotor cortex, was co-dependent on instantaneous timescales.

"There are many different types of working memory and over the past 40 years scientists have been trying to work out how these are represented in the brain. Sensory working memory in particular has been challenging to study, as during standard laboratory tasks many other processes are happening simultaneously, such as timing, motor preparation, and reward expectation," said Dr Ivan Voitov, Research Fellow in the Mrsic-Flogel lab and first author on the paper.

To overcome this challenge, the SWC researchers compared a working memory-dependent task with a simpler working memory-independent task. In the working memory task, mice were given a sensory stimulus followed by a delay and then had to match the next stimulus to the one they saw prior to the delay. This meant that during the delay the mice needed a representation in their working memory of the first stimulus to succeed in the task and receive a reward. In contrast, in the working memory-independent task, the decision the mice made on the secondary stimulus was unrelated to the first stimulus.

By contrasting these two tasks, the researchers were able to observe the part of the neural activity that was dependent on working memory as opposed to the natural activity that was just related to the task environment. They found that most neural activity was unrelated to working memory, and instead working memory representations were embedded within 'high-dimensional' modes of activity, meaning that only small fluctuations around the mean firing of individual cells were together carrying the working memory information.

To understand how these representations are maintained in the brain, the neuroscientists used a technique called optogenetics to selectively silence parts of the brain during the delay period and observed the disruption to what the mice were remembering. Interestingly, they found that silencing working memory representations in either one of the parietal or premotor cortical areas led to similar deficits in the mice's ability to remember the previous stimulus, implying that these representations were instantaneously co-dependent on each other during the delay.

To test this hypothesis, the researchers disrupted one area while recording the activity that was being communicated back to it by the other area. When they disrupted parietal cortex, the activity that was being communicated by premotor cortex to parietal cortex was largely unchanged in terms of average activity. However, the representation of working memory activity specifically was disrupted. This was also true in the reverse experiment, when they disrupted premotor cortex and looked at parietal cortex and also observed working memory-specific disruption of cortical-cortical communication.

"By recording from and manipulating long-range circuits in the cerebral cortex, we uncovered that working memory resides within co-dependent activity patterns in cortical areas that are interconnected, thereby maintaining working memory through instantaneous reciprocal communication," said Professor Tom Mrsic-Flogel, Director of the Sainsbury Wellcome Centre and co-author on the paper.

The next step for the researchers is to look for patterns of activity that are shared between these areas. They also plan to study more sophisticated working memory tasks that modulate the specific information that is being stored in working memory in addition to its strength. For this, the neuroscientists will use interleaved distractors containing sensory information that bias what the mouse thinks is the next target. Such experiments will allow them to develop a more nuanced understanding of working memory representations.

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Video game players show enhanced brain activity, decision-making skill study

Frequent players of video games show superior sensorimotor decision-making skills and enhanced activity in key regions of the brain as compared to non-players, according to a recent study by Georgia State University researchers.

The authors, who used functional magnetic resonance imaging (FMRI) in the study, said the findings suggest that video games could be a useful tool for training in perceptual decision-making.

"Video games are played by the overwhelming majority of our youth more than three hours every week, but the beneficial effects on decision-making abilities and the brain are not exactly known," said lead researcher Mukesh Dhamala, associate professor in Georgia State's Department of Physics and Astronomy and the university's Neuroscience Institute.

"Our work provides some answers on that," Dhamala said. "Video game playing can effectively be used for training -- for example, decision-making efficiency training and therapeutic interventions -- once the relevant brain networks are identified."

Dhamala was the adviser for Tim Jordan, the lead author of the paper, who offered a personal example of how such research could inform the use of video games for training the brain.

Jordan, who received a Ph.D. in physics and astronomy from Georgia State in 2021, had weak vision in one eye as a child. As part of a research study when he was about 5, he was asked to cover his good eye and play video games as a way to strengthen the vision in the weak one. Jordan credits video game training with helping him go from legally blind in one eye to building strong capacity for visual processing, allowing him to eventually play lacrosse and paintball. He is now a postdoctoral researcher at UCLA.

The Georgia State research project involved 47 college-age participants, with 28 categorized as regular video game players and 19 as non-players.

The subjects laid inside an FMRI machine with a mirror that allowed them to see a cue immediately followed by a display of moving dots. Participants were asked to press a button in their right or left hand to indicate the direction the dots were moving, or resist pressing either button if there was no directional movement.

The study found that video game players were faster and more accurate with their responses.

Analysis of the resulting brain scans found that the differences were correlated with enhanced activity in certain parts of the brain.

"These results indicate that video game playing potentially enhances several of the subprocesses for sensation, perception and mapping to action to improve decision-making skills," the authors wrote. "These findings begin to illuminate how video game playing alters the brain in order to improve task performance and their potential implications for increasing task-specific activity."

The study also notes there was no trade-off between speed and accuracy of response -- the video game players were better on both measures.

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Study examines why the memory of fear is seared into our brains

Experiencing a frightening event is likely something you'll never forget. But why does it stay with you when other kinds of occurrences become increasingly difficult to recall with the passage of time?

A team of neuroscientists from the Tulane University School of Science and Engineering and Tufts University School of Medicine have been studying the formation of fear memories in the emotional hub of the brain -- the amygdala -- and think they have a mechanism.

In a nutshell, the researchers found that the stress neurotransmitter norepinephrine, also known as noradrenaline, facilitates fear processing in the brain by stimulating a certain population of inhibitory neurons in the amygdala to generate a repetitive bursting pattern of electrical discharges. This bursting pattern of electrical activity changes the frequency of brain wave oscillation in the amygdala from a resting state to an aroused state that promotes the formation of fear memories.

Published recently in Nature Communications, the research was led by Tulane cell and molecular biology professor Jeffrey Tasker, the Catherine and Hunter Pierson Chair in Neuroscience, and his PhD student Xin Fu.

Tasker used the example of an armed robbery. "If you are held up at gunpoint, your brain secretes a bunch of the stress neurotransmitter norepinephrine, akin to an adrenaline rush," he said.

"This changes the electrical discharge pattern in specific circuits in your emotional brain, centered in the amygdala, which in turn transitions the brain to a state of heightened arousal that facilitates memory formation, fear memory, since it's scary. This is the same process, we think, that goes awry in PTSD and makes it so you cannot forget traumatic experiences."

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