When you’re expecting something—like the meal you’ve ordered at a restaurant—or when something captures your interest, unique electrical rhythms sweep through your brain.
These waves are called gamma oscillations and they reflect a symphony of cells—both excitatory and inhibitory—playing together in an orchestrated way. Though their role has been debated, gamma waves have been associated with higher-level brain function, and disturbances in the patterns have been tied to schizophrenia, Alzheimer’s disease, autism, epilepsy and other disorders.
Now, new research from the Salk Institute shows that little known supportive cells in the brain known as astrocytes may in fact be major players that control these waves.
In a study published July 28 in the Proceedings of the National Academy of Sciences, Salk researchers report a new, unexpected strategy to turn down gamma oscillations, by disabling not neurons but astrocytes—cells type traditionally thought to provide more of a support role in the brain. In the process, the team showed that astrocytes, and the gamma oscillations they help shape, are critical for some forms of memory.
"This is what could be called a smoking gun," says co-author Terrence Sejnowski, head of the Computational Neurobiology Laboratory at the Salk Institute for Biological Sciences and a Howard Hughes Medical Institute investigator. "There are hundreds of papers linking gamma oscillations with attention and memory, but they are all correlational. This is the first time we have been able to do a causal experiment, where we selectively block gamma oscillations and show that it has a highly specific impact on how the brain interacts with the world."
A collaboration among the labs of Salk professors Sejnowski, Inder Verma and Stephen Heinemann found that activity in the form of calcium signaling in astrocytes immediately preceded gamma oscillations in the brains of mice. This suggested that astrocytes, which use many of the same chemical signals as neurons, could be influencing these oscillations.
To test their theory, the group used a virus carrying tetanus toxin to disable the release of chemicals released selectively from astrocytes, effectively eliminating the cells’ ability to communicate with neighboring cells. Neurons were unaffected by the toxin.
After adding a chemical to trigger gamma waves in the animals’ brains, the researchers found that brain tissue with disabled astrocytes produced shorter gamma waves than in tissue containing healthy cells. And after adding three genes that would allow the researchers to selectively turn on and off the tetanus toxin in astrocytes at will, they found that gamma waves were dampened in mice whose astrocytes were blocked from signaling. Turning off the toxin reversed this effect.
The mice with the modified astrocytes seemed perfectly healthy. But after several cognitive tests, the researchers found that they failed in one major area: novel object recognition. A healthy mouse spent more time with a new item placed in its environment than it did with familiar items, as expected.
In contrast, the group’s new mutant mouse treated all objects the same. “That turned out to be a spectacular result in the sense that novel object recognition memory was not just impaired, it was gone—as if we were deleting this one form of memory, leaving others intact,” Sejnowski says.
The results were surprising, in part because astrocytes operate on a seconds- or longer timescale whereas neurons signal far faster, on the millisecond scale. Because of that slower speed, no one suspected astrocytes were involved in the high-speed brain activity needed to make quick decisions.
"What I thought quite unique was the idea that astrocytes, traditionally considered only guardians and supporters of neurons and other cells, are also involved in the processing of information and in other cognitive behavior," says Verma, a professor in the Laboratory of Genetics and American Cancer Society Professor.
It’s not that astrocytes are quick—they’re still slower than neurons. But the new evidence suggests that astrocytes are actively supplying the right environment for gamma waves to occur, which in turn makes the brain more likely to learn and change the strength of its neuronal connections.
Sejnowski says that the behavioral result is just the tip of the iceberg. “The recognition system is hugely important,” he says, adding that it includes recognizing other people, places, facts and things that happened in the past. With this new discovery, scientists can begin to better understand the role of gamma waves in recognition memory, he adds.
An evolutionarily ancient and tiny part of the brain tracks expectations about nasty events, finds new UCL research.
The study, published in Proceedings of the National Academy of Sciences, demonstrates for the first time that the human habenula, half the size of a pea, tracks predictions…
The human mind can rapidly absorb and analyze new information as it flits from thought to thought. These quickly changing brain states may be encoded by synchronization of brain waves across different brain regions, according to a new study from MIT neuroscientists.
The researchers found that as monkeys learn to categorize different patterns of dots, two brain areas involved in learning — the prefrontal cortex and the striatum — synchronize their brain waves to form new communication circuits.
“We’re seeing direct evidence for the interactions between these two systems during learning, which hasn’t been seen before. Category-learning results in new functional circuits between these two areas, and these functional circuits are rhythm-based, which is key because that’s a relatively new concept in systems neuroscience,” says Earl Miller, the Picower Professor of Neuroscience at MIT and senior author of the study, which appears in the June 12 issue of Neuron.
There are millions of neurons in the brain, each producing its own electrical signals. These combined signals generate oscillations known as brain waves, which can be measured by electroencephalography (EEG). The research team focused on EEG patterns from the prefrontal cortex —the seat of the brain’s executive control system — and the striatum, which controls habit formation.
The phenomenon of brain-wave synchronization likely precedes the changes in synapses, or connections between neurons, believed to underlie learning and long-term memory formation, Miller says. That process, known as synaptic plasticity, is too time-consuming to account for the human mind’s flexibility, he believes.
“If you can change your thoughts from moment to moment, you can’t be doing it by constantly making new connections and breaking them apart in your brain. Plasticity doesn’t happen on that kind of time scale,” says Miller, who is a member of MIT’s Picower Institute for Learning and Memory. “There’s got to be some way of dynamically establishing circuits to correspond to the thoughts we’re having in this moment, and then if we change our minds a moment later, those circuits break apart somehow. We think synchronized brain waves may be the way the brain does it.”
The paper’s lead author is former Picower Institute postdoc Evan Antzoulatos, who is now at the University of California at Davis.
Miller’s lab has previously shown that during category-learning, neurons in the striatum become active early, followed by slower activation of neurons in the prefrontal cortex. “The striatum learns very simple things really quickly, and then its output trains the prefrontal cortex to gradually pick up on the bigger picture,” Miller says. “The striatum learns the pieces of the puzzle, and then the prefrontal cortex puts the pieces of the puzzle together.”
In the new study, the researchers wanted to investigate whether this activity pattern actually reflects communication between the prefrontal cortex and striatum, or if each region is working independently. To do this, they measured EEG signals as monkeys learned to assign patterns of dots into one of two categories.
At first, the animals were shown just two different examples, or “exemplars,” from each category. After each round, the number of exemplars was doubled. In the early stages, the animals could simply memorize which exemplars belonged to each category. However, the number of exemplars eventually became too large for the animals to memorize all of them, and they began to learn the general traits that characterized each category.
By the end of the experiment, when the researchers were showing 256 novel exemplars, the monkeys were able to categorize all of them correctly.
As the monkeys shifted from rote memorization to learning the categories, the researchers saw a corresponding shift in EEG patterns. Brain waves known as “beta bands,” produced independently by the prefrontal cortex and the striatum, began to synchronize with each other. This suggests that a communication circuit is forming between the two regions, Miller says.
“There is some unknown mechanism that allows these resonance patterns to form, and these circuits start humming together,” he says. “That humming may then foster subsequent long-term plasticity changes in the brain, so real anatomical circuits can form. But the first thing that happens is they start humming together.”
A little later, as an animal nailed down the two categories, two separate circuits formed between the striatum and prefrontal cortex, each corresponding to one of the categories.
“This is the first paper that provides data suggesting that coupling in the beta-band between prefrontal cortex and striatum may play a key role in category-formation. In addition to revealing a novel mechanism involved in category-learning, the results also contribute to better understanding of the significance of coupled beta-band oscillations in the brain,” says Andreas Engel, a professor of physiology at the University Medical Center Hamburg-Eppendorf in Germany.
“Expanding your knowledge”
Previous studies have shown that during cognitively demanding tasks, there is increased synchrony between the frontal cortex and visual cortex, but Miller’s lab is the first to show specific patterns of synchrony linked to specific thoughts.
Miller and Antzoulatos also showed that once the prefrontal cortex learns the categories and sends them to the striatum, they undergo further modification as new information comes in, allowing more expansive learning to take place. This iteration can occur over and over.
“That’s how you get the open-ended nature of human thought. You keep expanding your knowledge,” Miller says. “The prefrontal cortex learning the categories isn’t the end of the game. The cortex is learning these new categories and then forming circuits that can send the categories down to the striatum as if it’s just brand-new material for the brain to elaborate on.”
In follow-up studies, the researchers are now looking at how the brain learns more abstract categories, and how activity in the striatum and prefrontal cortex might reflect that type of abstraction.
#learning #studying #neurology #medicine #plasticity #memory
What are three findings numbered here? Diagnosis? ANSWER: http://goo.gl/M0vXWQ
#riglers triad #surgery #radiology #learning
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Does the language you speak influence how you think?
Studies show that our language affects how we experience the world, playing a role in everything from how we save for retirement to the colors we see.
You won’t believe how much influence your language has over you.
#language #mother-tongue #learning
New research from the Department of Neuroscience at the University of Minnesota reveals that rats show regret, a cognitive behavior once thought to be uniquely and fundamentally human.
Research findings were recently published in Nature Neuroscience.
To measure the cognitive behavior of regret, A. David Redish, Ph.D., a professor of neuroscience in the University of Minnesota Department of Neuroscience, and Adam Steiner, a graduate student in the Graduate Program in Neuroscience, who led the study, started from the definitions of regret that economists and psychologists have identified in the past.
"Regret is the recognition that you made a mistake, that if you had done something else, you would have been better off," said Redish. "The difficult part of this study was separating regret from disappointment, which is when things aren’t as good as you would have hoped. The key to distinguishing between the two was letting the rats choose what to do."
Redish and Steiner developed a new task that asked rats how long they were willing to wait for certain foods. “It’s like waiting in line at a restaurant,” said Redish. “If the line is too long at the Chinese food restaurant, then you give up and go to the Indian food restaurant across the street.”
In this task, which they named “Restaurant Row,” the rat is presented with a series of food options but has limited time at each “restaurant.”
Research findings show rats were willing to wait longer for certain flavors, implying they had individual preferences. Because they could measure the rats’ individual preferences, Steiner and Redish could measure good deals and bad deals. Sometimes, the rats skipped a good deal and found themselves facing a bad deal.
"In humans, a part of the brain called the orbitofrontal cortex is active during regret. We found in rats that recognized they had made a mistake, indicators in the orbitofrontal cortex represented the missed opportunity. Interestingly, the rat’s orbitofrontal cortex represented what the rat should have done, not the missed reward. This makes sense because you don’t regret the thing you didn’t get, you regret the thing you didn’t do," said Redish.
Redish adds that results from Restaurant Row allow neuroscientists to ask additional questions to better understand why humans do things the way they do. By building upon this animal model of regret, Redish believes future research could help us understand how regret affects the decisions we make.
#Decisions #regret #choices #animals #humans
In study published today in Science, researchers at NYU Langone Medical Center show for the first time that sleep after learning encourages the growth of dendritic spines, the tiny protrusions from brain cells that connect to other brain cells and facilitate the passage of information across synapses, the junctions at which brain cells meet. Moreover, the activity of brain cells during deep sleep, or slow-wave sleep, after learning is critical for such growth.
The findings, in mice, provide important physical evidence in support of the hypothesis that sleep helps consolidate and strengthen new memories, and show for the first time how learning and sleep cause physical changes in the motor cortex, a brain region responsible for voluntary movements.
“We’ve known for a long time that sleep plays an important role in learning and memory. If you don’t sleep well you won’t learn well,” says senior investigator Wen-Biao Gan, PhD, professor of neuroscience and physiology and a member of the Skirball Institute of Biomolecular Medicine at NYU Langone Medical Center. “But what’s the underlying physical mechanism responsible for this phenomenon? Here we’ve shown how sleep helps neurons form very specific connections on dendritic branches that may facilitate long-term memory. We also show how different types of learning form synapses on different branches of the same neurons, suggesting that learning causes very specific structural changes in the brain.”
On the cellular level, sleep is anything but restful: Brain cells that spark as we digest new information during waking hours replay during deep sleep, also known as slow-wave sleep, when brain waves slow down and rapid-eye movement, as well as dreaming, stops. Scientists have long believed that this nocturnal replay helps us form and recall new memories, yet the structural changes underpinning this process have remained poorly understood.
To shed light on this process, Dr. Gan and colleagues employed mice genetically engineered to express a fluorescent protein in neurons. Using a special laser-scanning microscope that illuminates the glowing fluorescent proteins in the motor cortex, the scientists were then able to track and image the growth of dendritic spines along individual branches of dendrites before and after mice learned to balance on a spin rod. Over time mice learned how to balance on the rod as it gradually spun faster. “It’s like learning to ride a bike,” says Dr. Gan. “Once you learn it, you never forget.”
After documenting that mice, in fact, sprout new spines along dendritic branches, within six hours after training on the spinning rod, the researchers set out to understand how sleep would impact this physical growth. They trained two sets of mice: one trained on the spinning rod for an hour and then slept for 7 hours; the second trained for the same period of time on the rod but stayed awake for 7 hours. The scientists found that the sleep-deprived mice experienced significantly less dendritic spine growth than the well-rested mice. Furthermore, they found that the type of task learned determined which dendritic branches spines would grow.
Running forward on the spinning rod, for instance, produced spine growth on different dendritic branches than running backward on the rod, suggesting that learning specific tasks causes specific structural changes in the brain.
“Now we know that when we learn something new, a neuron will grow new connections on a specific branch,” says Dr. Gan. “Imagine a tree that grows leaves (spines) on one branch but not another branch. When we learn something new, it’s like we’re sprouting leaves on a specific branch.”
Finally, the scientists showed that brain cells in the motor cortex that activate when mice learn a task reactivate during slow-wave deep sleep. Disrupting this process, they found, prevents dendritic spine growth. Their findings offer an important insight into the functional role of neuronal replay—the process by which the sleeping brain rehearses tasks learned during the day—observed in the motor cortex.
“Our data suggest that neuronal reactivation during sleep is quite important for growing specific connections within the motor cortex,” Dr. Gan adds.