Songbirds’ brains coordinate singing with intricate timing

As a bird sings, some neurons in its brain prepare to make the next sounds while others are synchronized with the current notes—a coordination of physical actions and brain activity that is needed to produce complex movements, new research at the University of Chicago shows.

In an article in the current issue of Nature, neuroscientist Daniel Margoliash and colleagues show, for the first time, how the brain is organized to govern skilled performance—a finding that may lead to new ways of understanding human speech production.

The new study shows that birds’ physical movements actually are made up of a multitude of smaller actions. “It is amazing that such small units of movements are encoded, and so precisely, at the level of the forebrain,” said Margoliash, a professor of organismal biology and anatomy and psychology at UChicago.

“This work provides new insight into how the physics of controlling vocal signals are represented in the brain to control vocalizations,” said Howard Nusbaum, a professor of psychology at UChicago and an expert on speech.

By decoding the neural representation of communication, Nusbaum explained, the research may shed light on speech problems such as stuttering or aphasia (a disorder following a stroke). And it offers an unusual window into how the brain and body carry out other kinds of complex movement, from throwing a ball to doing a backflip.

“A big question in muscle control is how the motor system organizes the dynamics of movement,” said Margoliash. Movements like reaching or grasping are difficult to study because they entail many variables, such as the angles of the shoulder, elbow, wrist and fingers; the forces of many muscles; and how these change over time,” he said.

"With all this complexity, it has been difficult to determine which of the many variables that describe movements are represented in the brain, and which of those are used to control movements," he said.

"It’s difficult to find a natural framework with which to analyze the activity of single neurons. The bird study provided us a perfect opportunity,” Margoliash said. Margoliash is a pioneer in the study of brain function in birds, with studies that include how learning occurs when a bird sleeps and recalls singing a song.

Pain from the brain: Study reveals how people with a severe unexplained psychological illness have abnormal activity in the brain

People in a vegetative state may feel pain

It is a nightmare situation. A person diagnosed as being in a vegetative state has an operation without anaesthetic because they cannot feel pain. Except, maybe they can.

Alexandra Markl at the Schön clinic in Bad Aibling, Germany, and colleagues studied people with unresponsive wakefulness syndrome (UWS) – also known as vegetative state – and identified activity in brain areas involved in the emotional aspects of pain. People with UWS can make reflex movements but can’t show subjective awareness.

There are two distinct neural networks that work together to create the sensation of pain. The more basic of the two – the sensory-discriminative network – identifies the presence of an unpleasant stimulus. It is the affective network that attaches emotions and subjective feelings to the experience. Crucially, without the activity of the emotional network, your brain detects pain but won’t interpret it as unpleasant.

Using PET scans, previous studies have detected activation in the sensory-discriminative network in people with UWS but their findings were consistent with a lack of subjective awareness, the hallmark of the condition.

Now Markl and her colleagues have found evidence of activation in the affective or emotional network too (Brain and Behavior).

Her team gave moderately painful electric shocks to 30 people with UWS, while scanning their brains using fMRI. Sixteen people had some kind of brain activation – seven only in the sensory network but nine in the affective network as well.

These results question whether some diagnoses should change from UWS to minimally conscious, which is characterised by some level of awareness.

"I don’t think this paper alone will change the clinical approach to people with diagnoses such as UWS," says Donald Weaver at Dalhousie University in Halifax, Nova Scotia, Canada, who was not involved in the work. But it will encourage future study, he says.

Changing a diagnosis depends on whether neurologists are ready to accept alternative ways of diagnosing disorders of consciousness, says Boris Kotchoubey at the Institute of Medical Psychology and Behavioural Neurobiology in Tübingen, Germany, who worked on the study.

Nonetheless, Kotchoubey is confident that the way people with UWS are cared for will change, even if their diagnoses remain the same. “I know that many doctors working with such patients have been instructed to treat their patients as if they can understand them and perceive at least something in the environment, perhaps pain, pleasure, or emotion,” he says.

But not all people are treated this way. Prior to the study, one of the people in Markl’s study was given no anaesthesia before a tracheotomy, which involves an incision in the neck to allow breathing without using the nose or mouth. As people with UWS are clinically considered unable to understand pain, doctors do not have to give an anaesthetic.

Small groups of brain cells store concepts for memory formation– from Luke Skywalker to your grandmother

Concepts in our minds – from Luke Skywalker to our grandmother - are represented by their own distinct group of neurons, according to new research involving a University of Leicester neuroscientist.

The research, by neuroscientist Professor Rodrigo Quian Quiroga from the University of Leicester Centre for Systems Neuroscience together with Professor Itzhak Fried, of the UCLA David Geffen School of Medicine, Tel Aviv Sourasky Medical Center and Tel Aviv University, and Professor Christof Koch, of the California Institute of Technology and Allen Institute for Brain Science, Seattle, is featured in a recent article of the prestigious Scientific American magazine.

Recent experiments during brain surgeries have shown that small groups of brain cells are responsible for encoding memories of specific people or objects.

These neurons may also represent different variations of one thing – from the name of a person to their appearance from many different viewpoints.

The researchers believe that single concepts may be held in as little as thousands of neurons or less – a tiny fraction of the billion or so neurons contained in the medial temporal lobe, which is a memory related structure within the brain.

The group were able to monitor the brain activity of consenting patients undergoing surgery to treat epilepsy. This allowed the team to monitor the activity of single neurons in conscious patients while they looked at images on laptop screens, creating and recalling memories.

In previous experiments, they had found that single neurons would ‘fire’ for specific concepts – such as Luke Skywalker – even when they were viewing images of him from different angles or simply hearing or reading his name.

They have also found that single neurons can also fire to related people and objects – for instance, the neuron that responded to Luke Skywalker also fired to Yoda, another Jedi from Star Wars.

They argue that relatively small groups of neurons hold concepts like Luke Skywalker and that related concepts such as Yoda are held by some but not all of the same neurons. At the same time, a completely separate set of neurons would hold an unrelated concept like Jennifer Aniston.

The group believes this partially overlapping representation of related concepts are the neural underpinnings of encoding associations, a key memory function.

Professor Quian Quiroga said: “After the first thrill when finding neurons in the human hippocampus with such remarkable firing characteristics, converging evidence from experiments we have been carrying out in the last years suggests that we may be hitting one of the key mechanisms of memory formation and recall.

“The abstract representation of concepts provided by these neurons is indeed ideal for representing the meaning of the sensory stimuli around us, the internal representation we use to form and retrieve memories. These concepts cells, we believe, are the building blocks of memory functions.”

Has evolution given humans unique brain structures?

Humans have at least two functional networks in their cerebral cortex not found in rhesus monkeys. This means that new brain networks were likely added in the course of evolution from primate ancestor to human. These findings, based on an analysis of functional brain scans, were published in a study by neurophysiologist Wim Vanduffel (KU Leuven and Harvard Medical School) in collaboration with a team of Italian and American researchers.

Our ancestors evolutionarily split from those of rhesus monkeys about 25 million years ago. Since then, brain areas have been added, have disappeared or have changed in function. This raises the question, ‘Has evolution given humans unique brain structures?’. Scientists have entertained the idea before but conclusive evidence was lacking. By combining different research methods, we now have a first piece of evidence that could prove that humans have unique cortical brain networks.

Professor Vanduffel explains: “We did functional brain scans in humans and rhesus monkeys at rest and while watching a movie to compare both the place and the function of cortical brain networks. Even at rest, the brain is very active. Different brain areas that are active simultaneously during rest form so-called ‘resting state’ networks. For the most part, these resting state networks in humans and monkeys are surprisingly similar, but we found two networks unique to humans and one unique network in the monkey.”

“When watching a movie, the cortex processes an enormous amount of visual and auditory information. The human-specific resting state networks react to this stimulation in a totally different way than any part of the monkey brain. This means that they also have a different function than any of the resting state networks found in the monkey. In other words, brain structures that are unique in humans are anatomically absent in the monkey and there no other brain structures in the monkey that have an analogous function. Our unique brain areas are primarily located high at the back and at the front of the cortex and are probably related to specific human cognitive abilities, such as human-specific intelligence.”

The study used fMRI (functional Magnetic Resonance Imaging) scans to visualise brain activity. fMRI scans map functional activity in the brain by detecting changes in blood flow. The oxygen content and the amount of blood in a given brain area vary according to a particular task, thus allowing activity to be tracked.

Researchers develop tool for reading the minds of mice

If you want to read a mouse’s mind, it takes some fluorescent protein and a tiny microscope implanted in the rodent’s head.

Stanford scientists have demonstrated a technique for observing hundreds of neurons firing in the brain of a live mouse, in real time, and have linked that activity to long-term information storage. The unprecedented work could provide a useful tool for studying new therapies for neurodegenerative diseases such as Alzheimer’s.

The researchers first used a gene therapy approach to cause the mouse’s neurons to express a green fluorescent protein that was engineered to be sensitive to the presence of calcium ions. When a neuron fires, the cell naturally floods with calcium ions. Calcium stimulates the protein, causing the entire cell to fluoresce bright green.

A tiny microscope implanted just above the mouse’s hippocampus – a part of the brain that is critical for spatial and episodic memory – captures the light of roughly 700 neurons. The microscope is connected to a camera chip, which sends a digital version of the image to a computer screen.

The computer then displays near real-time video of the mouse’s brain activity as a mouse runs around a small enclosure, which the researchers call an arena.

The neuronal firings look like tiny green fireworks, randomly bursting against a black background, but the scientists have deciphered clear patterns in the chaos.

"We can literally figure out where the mouse is in the arena by looking at these lights," said Mark Schnitzer, an associate professor of biology and of applied physics and the senior author on the paper, recently published in the journal Nature Neuroscience.

When a mouse is scratching at the wall in a certain area of the arena, a specific neuron will fire and flash green. When the mouse scampers to a different area, the light from the first neuron fades and a new cell sparks up.

"The hippocampus is very sensitive to where the animal is in its environment, and different cells respond to different parts of the arena," Schnitzer said. "Imagine walking around your office. Some of the neurons in your hippocampus light up when you’re near your desk, and others fire when you’re near your chair. This is how your brain makes a representative map of a space."

The group has found that a mouse’s neurons fire in the same patterns even when a month has passed between experiments. “The ability to come back and observe the same cells is very important for studying progressive brain diseases,” Schnitzer said.

Research team discovers: brain does not process sensory information sufficiently

The reason why some people are worse at learning than others has been revealed by a research team from Berlin, Bochum, and Leipzig, operating within the framework of the Germany-wide network “Bernstein Focus State Dependencies of Learning”. They have discovered that the main problem is not that learning processes are inefficient per se, but that the brain insufficiently processes the information to be learned. The scientists trained the subjects’ sense of touch to be more sensitive. In subjects who responded well to the training, the EEG revealed characteristic changes in brain activity, more specifically in the alpha waves. These alpha waves show, among other things, how effectively the brain exploits the sensory information needed for learning. “An exciting question now is to what extent the alpha activity can be deliberately influenced with biofeedback”, says PD Dr. Hubert Dinse from the Neural Plasticity Lab of the Ruhr-Universität Bochum. “This could have enormous implications for therapy after brain injury or, quite generally, for the understanding of learning processes.” The research team from the Ruhr-Universität, the Humboldt Universität zu Berlin, Charité – Universitätsmedizin Berlin and the Max Planck Institute (MPI) for Human Cognitive and Brain Sciences reported their findings in the Journal of Neuroscience.

Learning without attention: passive training of the sense of touch

How well we learn depends on genetic aspects, the individual brain anatomy, and, not least, on attention. “In recent years we have established a procedure with which we trigger learning processes in people that do not require attention”, says Hubert Dinse. The researchers were, therefore, able to exclude attention as a factor. They repeatedly stimulated the participants’ sense of touch for 30 minutes by electrically stimulating the skin of the hand. Before and after this passive training, they tested the so-called “two-point discrimination threshold”, a measure of the sensitivity of touch. For this, they applied gentle pressure to the hand with two needles and determined the smallest distance between the needles at which the patient still perceived them as separate stimuli. On average, the passive training improved the discrimination threshold by twelve percent—but not in all of the 26 participants. Using EEG, the team studied why some people learned better than others.

Imaging the brain state using EEG: the alpha waves are decisive

The cooperation partners from Berlin and Leipzig, PD Dr. Petra Ritter, Dr. Frank Freyer, and Dr. Robert Becker recorded the subjects’ spontaneous EEG before and during passive training. They then identified the components of the brain activity related to improvement in the discrimination test. The alpha activity was decisive, i.e., the brain activity was in the frequency range 8 to 12 hertz. The higher the alpha activity before the passive training, the better the people learned. In addition, the more the alpha activity decreased during passive training, the more easily they learned. These effects occurred in the somatosensory cortex, that is, where the sense of touch is located in the brain.

Researchers seek new methods for therapy

“How the alpha rhythm manages to affect learning is something we investigate with computer models”, says PD Dr. Petra Ritter, Head of the Working Group “Brain Modes” at the MPI Leipzig and the Berlin Charité. “Only when we understand the complex information processing in the brain, can we intervene specifically in the processes to help disorders”, adds Petra Ritter. New therapies are the aim of the cooperation network, which Ritter coordinates, the international “Virtual Brain” project, which her team collaborates on, and the “Neural Plasticity Lab”, chaired by Hubert Dinse at the RUB.

Learning is dependent on access to sensory information

A high level of alpha activity counts as a marker of the readiness of the brain to exploit new incoming information. Conversely, a strong decrease of alpha activity during sensory stimulation counts as an indicator that the brain processes stimuli particularly efficiently. The results, therefore, suggest that perception-based learning is highly dependent on how accessible the sensory information is. The alpha activity, as a marker of constantly changing brain states, modulates this accessibility.

Brain imaging research shows how unconscious processing improves decision-making

When faced with a difficult decision, it is often suggested to “sleep on it” or take a break from thinking about the decision in order to gain clarity.

But new brain imaging research from Carnegie Mellon University, published in the journal “Social Cognitive and Affective Neuroscience,” finds that the brain regions responsible for making decisions continue to be active even when the conscious brain is distracted with a different task. The research provides some of the first evidence showing how the brain unconsciously processes decision information in ways that lead to improved decision-making.

"This research begins to chip away at the mystery of our unconscious brains and decision-making," said J. David Creswell, assistant professor of psychology in CMU’s Dietrich College of Humanities and Social Sciences and director of the Health and Human Performance Laboratory. "It shows that brain regions important for decision-making remain active even while our brains may be simultaneously engaged in unrelated tasks, such as thinking about a math problem. What’s most intriguing about this finding is that participants did not have any awareness that their brains were still working on the decision problem while they were engaged in an unrelated task."

The party in your brain

A team of political scientists and neuroscientists has shown that liberals and conservatives use different parts of the brain when they make risky decisions, and these regions can be used to predict which political party a person prefers. The new study suggests that while genetics or parental influence may play a significant role, being a Republican or Democrat changes how the brain functions.

Dr. Darren Schreiber, a researcher in neuropolitics at the University of Exeter, has been working in collaboration with colleagues at the University of California, San Diego on research that explores the differences in the way the brain functions in American liberals and conservatives. The findings are published in the journal PLOS ONE on 13 February.

In a prior experiment, participants had their brain activity measured as they played a simple gambling game. Dr. Schreiber and his UC San Diego collaborators were able to look up the political party registration of the participants in public records. Using this new analysis of 82 people who performed the gambling task, the academics showed that Republicans and Democrats do not differ in the risks they take. However, there were striking differences in the participants’ brain activity during the risk-taking task.

Democrats showed significantly greater activity in the left insula, a region associated with social and self-awareness. Meanwhile Republicans showed significantly greater activity in the right amygdala, a region involved in the body’s fight-or-flight system. These results suggest that liberals and conservatives engage different cognitive processes when they think about risk.

In fact, brain activity in these two regions alone can be used to predict whether a person is a Democrat or Republican with 82.9% accuracy. By comparison, the longstanding traditional model in political science, which uses the party affiliation of a person’s mother and father to predict the child’s affiliation, is only accurate about 69.5% of the time. And another model based on the differences in brain structure distinguishes liberals from conservatives with only 71.6% accuracy.

The model also outperforms models based on differences in genes. Dr. Schreiber said: “Although genetics have been shown to contribute to differences in political ideology and strength of party politics, the portion of variation in political affiliation explained by activity in the amygdala and insula is significantly larger, suggesting that affiliating with a political party and engaging in a partisan environment may alter the brain, above and beyond the effect of heredity.”

These results may pave the way for new research on voter behaviour, yielding better understanding of the differences in how liberals and conservatives think. According to Dr. Schreiber: “The ability to accurately predict party politics using only brain activity while gambling suggests that investigating basic neural differences between voters may provide us with more powerful insights than the traditional tools of political science.”

Long memories in brain activity explain streaks in individual behaviour

Even with a constant task, human performance fluctuates in time-scales from seconds to minutes in a fractal manner. In a recent study a Finnish research group found that the individual variability in the brain dynamics as indexed by the neuronal scaling laws predicted the individual behavioral variability and the conscious detection of very weak sensory stimuli. These data indicate that individual neuronal dynamics underlie the individual variability in human cognition and performance. Results may also have a strong impact in understanding the neuronal mechanism of neuropsychiatric diseases in which behavioral dynamics are abnormal.

Human performance in cognitive tasks varies from moment-to-moment so that the similar behavioral performance is clustered into streaks. The neuronal dynamics underlying this behavioral variability has remained unknown.

Similar scale-free and power-law distributed “avalanche dynamics” is observed in many natural systems such as sand piles, earthquakes, gene regulation, and also brain activity. However, the functional significance of the neuronal scale-free behavior has remained unknown. It is also unclear whether it is just epiphenomena without any further significance. 

"We investigated whether the individual variability in the scaling-laws governing the detection of auditory and visual stimuli presented in the threshold of detection could be predicted by the variability in the neuronal scaling laws", explains Matias Palva, project leader in the Neuroscience Center of the University of Helsinki, Finland.

The researchers used magneto- and electroencephalography to record non-invasively human brain activity during the task performance. They found that both the behavioral and neuronal dynamics were characterized by scale-free dynamics. Individual variability in the neuronal scaling laws predicted the individual scaling laws in behavioral performance.

"These results suggest that the individual behavioral and psychophysical variability in task performance is largely a result of the inherent variability in the individual neuronal dynamics", says project leader Satu Palva.

(Image: Harry Sieplinga, HMS/Getty Images)