The NW7US Beacon

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Bach to the blues, our emotions match music to colors

Whether we’re listening to Bach or the blues, our brains are wired to make music-color connections depending on how the melodies make us feel, according to new research from the University of California, Berkeley. For instance, Mozart’s jaunty Flute Concerto No. 1 in G major is most often associated with bright yellow and orange, whereas his dour Requiem in D minor is more likely to be linked to dark, bluish gray.

Moreover, people in both the United States and Mexico linked the same pieces of classical orchestral music with the same colors. This suggests that humans share a common emotional palette – when it comes to music and color – that appears to be intuitive and can cross cultural barriers, UC Berkeley researchers said.

“The results were remarkably strong and consistent across individuals and cultures and clearly pointed to the powerful role that emotions play in how the human brain maps from hearing music to seeing colors,” said UC Berkeley vision scientist Stephen Palmer, lead author of a paper published this week in the journal Proceedings of the National Academy of Sciences.

Using a 37-color palette, the UC Berkeley study found that people tend to pair faster-paced music in a major key with lighter, more vivid, yellow colors, whereas slower-paced music in a minor key is more likely to be teamed up with darker, grayer, bluer colors.

“Surprisingly, we can predict with 95 percent accuracy how happy or sad the colors people pick will be based on how happy or sad the music is that they are listening to,” said Palmer, who will present these and related findings at the International Association of Colour conference at the University of Newcastle in the U.K. on July 8.  At the conference, a color light show will accompany a performance by the Northern Sinfonia orchestra to demonstrate “the patterns aroused by music and color converging on the neural circuits that register emotion,” he said.

The findings may have implications for creative therapies, advertising and even music player gadgetry. For example, they could be used to create more emotionally engaging electronic music visualizers, computer software that generates animated imagery synchronized to the music being played. Right now, the colors and patterns appear to be randomly generated and do not take emotion into account, researchers said.

They may also provide insight into synesthesia, a neurological condition in which the stimulation of one perceptual pathway, such as hearing music, leads to automatic, involuntary experiences in a different perceptual pathway, such as seeing colors.  An example of sound-to-color synesthesia was portrayed in the 2009 movie The Soloist when cellist Nathaniel Ayers experiences a mesmerizing interplay of swirling colors while listening to the Los Angeles symphony. Artists such as Wassily Kandinksky and Paul Klee may have used music-to-color synesthesia in their creative endeavors.

Nearly 100 men and women participated in the UC Berkeley music-color study, of which half resided in the San Francisco Bay Area and the other half in Guadalajara, Mexico. In three experiments, they listened to 18 classical music pieces by composers Johann Sebastian Bach, Wolfgang Amadeus Mozart and Johannes Brahms that varied in tempo (slow, medium, fast) and in major versus minor keys.

In the first experiment, participants were asked to pick five of the 37 colors that best matched the music to which they were listening. The palette consisted of vivid, light, medium, and dark shades of red, orange, yellow, green, yellow-green, green, blue-green, blue, and purple.

Participants consistently picked bright, vivid, warm colors to go with upbeat music and dark, dull, cool colors to match the more tearful or somber pieces. Separately, they rated each piece of music on a scale of happy to sad, strong to weak, lively to dreary and angry to calm.  

Two subsequent experiments studying music-to-face and face-to-color associations supported the researchers’ hypothesis that “common emotions are responsible for music-to-color associations,” said Karen Schloss, a postdoctoral researchers at UC Berkeley and co-author of the paper. 

For example, the same pattern occurred when participants chose the facial expressions that “went best” with the music selections, Schloss said. Upbeat music in major keys was consistently paired with happy-looking faces while subdued music in minor keys was paired with sad-looking faces. Similarly, happy faces were paired with yellow and other bright colors and angry faces with dark red hues.

Next, Palmer and his research team plan to study participants in Turkey where traditional music employs a wider range of scales than just major and minor. “We know that in Mexico and the U.S. the responses are very similar,” he said. “But we don’t yet know about China or Turkey.”

Today’s Sun, with small sunspots peppering the solar disc. The left-most sunspot group is the origin of the recent flares…

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The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI

There’s a theory that human intelligence stems from a single algorithm.

The idea arises from experiments suggesting that the portion of your brain dedicated to processing sound from your ears could also handle sight for your eyes. This is possible only while your brain is in the earliest stages of development, but it implies that the brain is — at its core — a general-purpose machine that can be tuned to specific tasks.

About seven years ago, Stanford computer science professor Andrew Ng stumbled across this theory, and it changed the course of his career, reigniting a passion for artificial intelligence, or AI. “For the first time in my life,” Ng says, “it made me feel like it might be possible to make some progress on a small part of the AI dream within our lifetime.”

In the early days of artificial intelligence, Ng says, the prevailing opinion was that human intelligence derived from thousands of simple agents working in concert, what MIT’s Marvin Minsky called “The Society of Mind.” To achieve AI, engineers believed, they would have to build and combine thousands of individual computing modules. One agent, or algorithm, would mimic language. Another would handle speech. And so on. It seemed an insurmountable feat.

When he was a kid, Andrew Ng dreamed of building machines that could think like people, but when he got to college and came face-to-face with the AI research of the day, he gave up. Later, as a professor, he would actively discourage his students from pursuing the same dream. But then he ran into the “one algorithm” hypothesis, popularized by Jeff Hawkins, an AI entrepreneur who’d dabbled in neuroscience research. And the dream returned.

It was a shift that would change much more than Ng’s career. Ng now leads a new field of computer science research known as Deep Learning, which seeks to build machines that can process data in much the same way the brain does, and this movement has extended well beyond academia, into big-name corporations like Google and Apple. In tandem with other researchers at Google, Ng is building one of the most ambitious artificial-intelligence systems to date, the so-called Google Brain.

This movement seeks to meld computer science with neuroscience — something that never quite happened in the world of artificial intelligence. “I’ve seen a surprisingly large gulf between the engineers and the scientists,” Ng says. Engineers wanted to build AI systems that just worked, he says, but scientists were still struggling to understand the intricacies of the brain. For a long time, neuroscience just didn’t have the information needed to help improve the intelligent machines engineers wanted to build.

What’s more, scientists often felt they “owned” the brain, so there was little collaboration with researchers in other fields, says Bruno Olshausen, a computational neuroscientist and the director of the Redwood Center for Theoretical Neuroscience at the University of California, Berkeley.

The end result is that engineers started building AI systems that didn’t necessarily mimic the way the brain operated. They focused on building pseudo-smart systems that turned out to be more like a Roomba vacuum cleaner than Rosie the robot maid from the Jetsons.

But, now, thanks to Ng and others, this is starting to change. “There is a sense from many places that whoever figures out how the brain computes will come up with the next generation of computers,” says Dr. Thomas Insel, the director of the National Institute of Mental Health.

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Study shows that individual brain cells track where we are and how we move

Leaving the house in the morning may seem simple, but with every move we make, our brains are working feverishly to create maps of the outside world that allow us to navigate and to remember where we are.

Take one step out the front door, and an individual brain cell fires. Pass by your rose bush on the way to the car, another specific neuron fires. And so it goes. Ultimately, the brain constructs its own pinpoint geographical chart that is far more precise than anything you’d find on Google Maps.

But just how neurons make these maps of space has fascinated scientists for decades. It is known that several types of stimuli influence the creation of neuronal maps, including visual cues in the physical environment — that rose bush, for instance — the body’s innate knowledge of how fast it is moving, and other inputs, like smell. Yet the mechanisms by which groups of neurons combine these various stimuli to make precise maps are unknown.

To solve this puzzle, UCLA neurophysicists built a virtual-reality environment that allowed them to manipulate these cues while measuring the activity of map-making neurons in rats. Surprisingly, they found that when certain cues were removed, the neurons that typically fire each time a rat passes a fixed point or landmark in the real world instead began to compute the rat’s relative position, firing, for example, each time the rodent walked five paces forward, then five paces back, regardless of landmarks. And many other mapping cells shut down altogether, suggesting that different sensory cues strongly influence these neurons.

Finally, the researchers found that in this virtual world, the rhythmic firing of neurons that normally speeds up or slows down depending on the rate at which an animal moves, was profoundly altered. The rats’ brains maintained a single, steady rhythmic pattern.

The findings, reported in the May 2 online edition of the journal Science, provide further clues to how the brain learns and makes memories.

The mystery of how cells determine place

“Place cells” are individual neurons located in the brain’s hippocampus that create maps by registering specific places in the outside environment. These cells are crucial for learning and memory. They are also known to play a role in such conditions as post-traumatic stress disorder and Alzheimer’s disease when damaged.

For some 40 years, the thinking had been that the maps made by place cells were based primarily on visual landmarks in the environment, known as distal cues — a tall tree, a building — as well on motion, or gait, cues. But, as UCLA neurophysicist and senior study author Mayank Mehta points out, other cues are present in the real world: the smell of the local pizzeria, the sound of a nearby subway tunnel, the tactile feel of one’s feet on a surface. These other cues, which Mehta likes to refer to as “stuff,” were believed to have only a small influence on place cells.

Could it be that these different sensory modalities led place cells to create individual maps, wondered Mehta, a professor with joint appointments in the departments of neurology, physics and astronomy. And if so, do these individual maps cooperate with each other, or do they compete? No one really knew for sure.

Virtual reality reveals new clues

To investigate, Mehta and his colleagues needed to separate the distal and gait cues from all the other “stuff.” They did this by crafting a virtual-reality maze for rats in which odors, sounds and all stimuli, except distal and gait cues, were removed. As video of a physical environment was projected around them, the rats, held by a harness, were placed on a ball that rotated as they moved. When they ran, the video would move along with them, giving the animals the illusion that they were navigating their way through an actual physical environment.

As a comparison, the researchers had the rats — six altogether — run a real-world maze that was visually identical to the virtual-reality version but that included the additional “stuff” cues. Using micro-electrodes 10 times thinner than a human hair, the team measured the activity of some 3,000 space-mapping neurons in the rats’ brains as they completed both mazes.

What they found intrigued them. The elimination of the “stuff” cues in the virtual-reality maze had a huge effect: Fully half of the neurons being recorded became inactive, despite the fact that the distal and gate cues were similar in the virtual and real worlds. The results, Mehta said, show that these other sensory cues, once thought to play only a minor role in activating the brain, actually have a major influence on place cells.

And while in the real world, place cells responded to fixed, absolute positions, spiking at those same positions each time rats passed them, regardless of the direction they were moving — a finding consistent with previous experiments — this was not the case in the virtual-reality maze.

“In the virtual world,” Mehta said, “we found that the neurons almost never did that. Instead, the neurons spiked at the same relative distance in the two directions as the rat moved back and forth. In other words, going back to the front door-to-car analogy, in a virtual world, the cell that fires five steps away from the door when leaving your home would not fire five steps away from the door upon your return. Instead, it would fire five steps away from the car when leaving the car. Thus, these cells are keeping track of the relative distance traveled rather than absolute position. This gives us evidence for the individual place cell’s ability to represent relative distances.”

Mehta thinks this is because neuronal maps are generated by three different categories of stimuli — distal cues, gait and “stuff” — and that all are competing for control of neural activity. This competition is what ultimately generates the “full” map of space.

“All the external stuff is fixed at the same absolute position and hence generates a representation of absolute space,” he said. “But when all the stuff is removed, the profound contribution of gait is revealed, which enables neurons to compute relative distances traveled.”

The researchers also made a new discovery about the brain’s theta rhythm. It is known that place cells use the rhythmic firing of neurons to keep track of “brain time,” the brain’s internal clock. Normally, Mehta said, the theta rhythm becomes faster as subjects run faster, and slower as running speed decreases. This speed-dependent change in brain rhythm was thought to be crucial for generating the ‘brain time’ for place cells. But the team found that in the virtual world, the theta rhythm was uninfluenced by running speed.

“That was a surprising and fascinating discovery, because the ‘brain time’ of place cells was as precise in the virtual world as in the real world, even though the speed-dependence of the theta rhythm was abolished,” Mehta said. “This gives us a new insight about how the brain keeps track of space-time.”

The researchers found that the firing of place cells was very precise, down to one-hundredth of a second, “so fast that we humans cannot perceive it but neurons can,” Mehta said. “We have found that this very precise spiking of neurons with respect to ‘brain-time’ is crucial for learning and making new memories.”

Mehta said the results, taken together, provide insight into how distinct sensory cues both cooperate and compete to influence the intricate network of neuronal activity. Understanding how these cells function is key to understanding how the brain makes and retains memories, which are vulnerable to such disorders as Alzheimer’s and PTSD.

“Ultimately, understanding how these intricate neuronal networks function is a key to developing therapies to prevent such disorders,” he said.

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Missing link in Parkinson’s disease found

Researchers at Washington University School of Medicine in St. Louis have described a missing link in understanding how damage to the body’s cellular power plants leads to Parkinson’s disease and, perhaps surprisingly, to some forms of heart failure.

These cellular power plants are called mitochondria. They manufacture the energy the cell requires to perform its many duties. And while heart and brain tissue may seem entirely different in form and function, one vital characteristic they share is a massive need for fuel.

Working in mouse and fruit fly hearts, the researchers found that a protein known as mitofusin 2 (Mfn2) is the long-sought missing link in the chain of events that control mitochondrial quality.

The findings are reported April 26 in the journal Science.

The new discovery in heart cells provides some explanation for the long known epidemiologic link between Parkinson’s disease and heart failure.

“If you have Parkinson’s disease, you have a more than two-fold increased risk of developing heart failure and a 50 percent higher risk of dying from heart failure,” says senior author Gerald W. Dorn II, MD, the Philip and Sima K. Needleman Professor of Medicine. “This suggested they are somehow related, and now we have identified a fundamental mechanism that links the two.”

Heart muscle cells and neurons in the brain have huge numbers of mitochondria that must be tightly monitored. If bad mitochondria are allowed to build up, not only do they stop making fuel, they begin consuming it and produce molecules that damage the cell. This damage eventually can lead to Parkinson’s or heart failure, depending on the organ affected. Most of the time, quality-control systems in a healthy cell make sure damaged or dysfunctional mitochondria are identified and removed.

Over the past 15 years, scientists have described much of this quality-control system. Both the beginning and end of the chain of events are well understood. And since 2006, scientists have been working to identify the mysterious middle section of the chain – the part that allows the internal environment of sick mitochondria to communicate to the rest of the cell that it needs to be destroyed.

“This was a big question,” Dorn says. “Scientists would draw the middle part of the chain as a black box. How do these self-destruct signals inside the mitochondria communicate with proteins far away in the surrounding cell that orchestrate the actual destruction?”

“To my knowledge, no one has connected an Mfn2 mutation to Parkinson’s disease,” Dorn says. “And until recently, I don’t think anybody would have looked. This isn’t what Mfn2 is supposed to do.”

Mitofusin 2 is known for its role in fusing mitochondria together, so they might exchange mitochondrial DNA in a primitive form of sexual reproduction.

“Mitofusins look like little Velcro loops,” Dorn says. “They help fuse together the outer membranes of mitochondria. Mitofusins 1 and 2 do pretty much the same thing in terms of mitochondrial fusion. What we have done is describe an entirely new function for Mfn2.”

The mitochondrial quality-control system begins with what Dorn calls a “dead man’s switch.”

“If the mitochondria are alive, they have to do work to keep the switch depressed to prevent their own self-destruction,” Dorn says.

Specifically, mitochondria work to import a molecule called PINK. Then they work to destroy it. When mitochondria get sick, they can’t destroy PINK and its levels begin to rise. Then comes the missing link that Dorn and his colleague Yun Chen, PhD, senior scientist, identified. Once PINK levels get high enough, they make a chemical change to Mfn2, which sits on the surface of mitochondria. This chemical change is called phosphorylation. Phosphorylated Mfn2 on the surface of the mitochondria can then bind with a molecule called Parkin that floats around in the surrounding cell.

Once Parkin binds to Mfn2 on sick mitochondria, Parkin labels the mitochondria for destruction. The labels then attract special compartments in the cell that “eat” and destroy the sick mitochondria. As long as all links in the quality-control system work properly, the cells’ damaged power plants are removed, clearing the way for healthy ones.

“But if you have a mutation in PINK, you get Parkinson’s disease,” Dorn says. “And if you have a mutation in Parkin, you get Parkinson’s disease. About 10 percent of Parkinson’s disease is attributed to these or other mutations that have been identified.”

According to Dorn, the discovery of Mfn2’s relationship to PINK and Parkin opens the doors to a new genetic form of Parkinson’s disease. And it may help improve diagnosis for both Parkinson’s disease and heart failure.

“I think researchers will look closely at inherited Parkinson’s cases that are not explained by known mutations,” Dorn says. “They will look for loss of function mutations in Mfn2, and I think they are likely to find some.”

Similarly, as a cardiologist, Dorn and his colleagues already have detected mutations in Mfn2 that appear to explain certain familial forms of heart failure, the gradual deterioration of heart muscle that impairs blood flow to the body. He speculates that looking for mutations in PINK and Parkin might be worthwhile in heart failure as well.

“In this case, the heart has informed us about Parkinson’s disease, but we may have also described a Parkinson’s disease analogy in the heart,” he says. “This entire process of mitochondrial quality control is a relatively small field for heart specialists, but interest is growing.”

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Study Shows How Parkinson’s Disease Protein Acts like a Virus

A protein known to be a key player in the development of Parkinson’s disease is able to enter and harm cells in the same way that viruses do, according to a Loyola University Chicago Stritch School of Medicine study.

The protein is called alpha-synuclein. The study shows how, once inside a neuron, alpha synuclein breaks out of lysosomes, the digestive compartments of the cell. This is similar to how a cold virus enters a cell during infection. The finding eventually could lead to the development of new therapies to delay the onset of Parkinson’s disease or halt or slow its progression, researchers said.

The study by virologist Edward Campbell, PhD, and colleagues, was published April 25, 2013 in the journal PLOS ONE.

Alpha-synuclein plays a role in the normal functioning of healthy neurons. But in Parkinson’s disease patients, the protein turns bad, aggregating into clumps that lead to the death of neurons in the area of the brain responsible for motor control. Previous studies have shown that these protein aggregates can enter and harm cells. Campbell and colleagues showed how alpha synuclein can bust out of lysosomes, small structures that collectively serve as the cell’s digestive system. The rupture of these bubble-like structures, known as vesicles, releases enzymes that are toxic to the rest of the cell.

“The release of lysosomal enzymes is sensed as a ‘danger signal’ by cells, since similar ruptures are often induced by invading bacteria or viruses,” said Chris Wiethoff, a collaborator on the study. “Lysosomes are often described as ‘suicide bags’ because when they are ruptured by viruses or bacteria, they induce oxidative stress that often leads to the death of the affected cell.”

In a viral or bacterial infection, the deaths of such infected cells may overall be a good thing for the infected individual. But in Parkinson’s disease, this same protective mechanism may lead to the death of neurons and enhance the spread of alpha-synuclein between cells in the brain, Campbell said. “This might explain the progressive nature of Parkinson’s disease. More affected cells leads to the spread of more toxic alpha-synuclein aggregates in the brain,” Campbell said. “This is very similar to what happens in a spreading viral infection.”

Campbell stressed that these studies need to be followed up and confirmed in other models of Parkinson’s disease. “Using cultured cells, we have made some exciting observations. However, we need to understand how lysosomal rupture is affecting disease progression in animal models of Parkinson’s disease and, ultimately, the brains of people affected by Parkinson’s disease. Can we interfere with the ability of alpha-synuclein to rupture lysosomes in these settings? And will that have a positive effect on disease progression? These are the questions we are excited to be asking next.”

Jeffrey H. Kordower, PhD, professor of neurological sciences, professor of neurosurgery and director of the Research Center for Brain Repair at Rush University Medical Center, said the study “is an important finding by a group of investigators who are beginning to make their impact in the field of Parkinson’s disease. This paper adds to the growing concept that alpha-synuclein, a  main culprit in the cause of Parkinson’s disease, can transfer from cell to cell. This paper elegantly puts a mechanism behind such a transfer. The findings will help shape the direction of Parkinson’s disease research for years to come.”