April 2, 2012

New research confirms that childhood onset temporal lobe epilepsy has a significant impact on brain aging. Study findings published in Epilepsia, a peer-reviewed journal of the International League Against Epilepsy (ILAE), show age-accelerated ventricular expansion outside the normal range in this patient population.

According to the Centers for Disease Control and Prevention (CDC), epilepsy affects nearly 2 million Americans. Temporal lobe epilepsy is the most common form of partial epilepsy, with 60% of all patients having this form of the disease. Previous evidence suggests that patients with childhood onset epilepsy have significant cognitive and developmental deficiencies, which continue into adulthood, particularly in those resistant to antiepileptic drugs.

Prior imaging studies of patients with temporal lobe epilepsy have shown abnormalities in brain structure in hippocampus, in thalamus and other subcortical structures, and also in cortical and white matter volume. However, there is limited knowledge of the effects of aging on these structural changes.

To characterize differences in brain structure and patterns of age-related change, Dr. Bruce Hermann and colleagues from the University of Wisconsin-Madison recruited 55 patients with chronic temporal lobe epilepsy and 53 healthy controls for their study. Participants were between the ages of 14 and 60, with patients having mean age of onset of epilepsy in childhood/adolescence. Magnetic resonance imaging (MRI) was used to measure cortical thickness, area and volume in the brains of all subjects.

In participants with epilepsy, there were extensive abnormalities in brain structure, involving subcortical regions, cerebellum and cortical gray matter thickness and volume in the temporal and extratemporal lobes. Furthermore, researchers found that increasing chronological age was associated with progressive changes in cortical, subcortical and cerebellar regions for both epilepsy subjects and healthy controls. The pattern of change was similar for both groups, but epilepsy patients always showed more extensive abnormalities. In particular, epilepsy patients displayed age-accelerated expansion of the lateral and third ventricles. “The anatomic abnormalities in patients with epilepsy indicate a significant neurodevelopmental impact,” said Dr. Hermann.

"Patients with epilepsy are burdened with significant neurodevelopmental challenges due to these cumulative brain abnormalities," concludes Dr. Hermann. "The consequences of these anatomical changes for epilepsy patients as they progress into elder years remain unknown and further study of the adverse effects in those of older chronological age is needed."

Provided by Wiley

Source: medicalxpress.com

April 2, 2012

One of the most frustrating challenges for some stroke patients can be the inability to find and speak words even if they know what they want to say. Speech therapy is laborious and can take months. New research is seeking to cut that time significantly, with the help of non-invasive brain stimulation.

"Non-invasive brain stimulation can allow painless, inexpensive, and apparently safe method for cognitive improvement with with potential long term efficacy," says Roi Cohen Kadosh of the University of Oxford. Recent results, presented this week at a meeting of cognitive neuroscientists in Chicago, offer exciting possibilities for improving variety of abilities – from speech to memory to numerical proficiency.

A focus of many of these studies is tDCS – transcranial direct current stimulation. In tDCS, researchers apply weak electrical currents to the head via electrodes for a short period of time, for example 20 minutes. The currents pass through the skull and alter spontaneous neural activity. Some types of stimulation excite the neurons, while others suppress them. Subjects usually feel only a slight tingling for less than 30 seconds. The effects of tDCS can last for up to 12 months, Cohen Kadosh says, “most likely due to molecular and cellular changes that are important mechanisms implementing learning and memory.”

Stimulating speech recovery

For Jenny Crinion of University College London, who is both a neuroscientist and clinical speech and language therapist, the interest in tDCS sprang from a desire to help stroke patients through their long recovery. While speech therapy works well at improving speech following aphasic stroke, it can be frustratingly slow. She hopes to pair brain-stimulation interventions with proven language-rehabilitation methods, Crinion says, “such that the same maximum recovery is ultimately achieved as with therapy alone but with fewer hours of rehab.”

Crinion’s current work focuses on understanding how tDCS affects the areas of the brain involved in speech production. She paired an fMRI picture-naming study with a 6-week-long tDCS and word-finding treatment study to see if brain stimulation could improve stroke patients’ speech both immediately after treatment and three months later. In the picture-naming task, people were presented with pictures of simple, everyday words such as car and asked to name them as quickly and accurately as possible.

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April 2, 2012

Sleep plays a powerful role in preserving our memories. But while recent research shows that wakefulness may cloud memories of negative or traumatic events, a new study has found that wakefulness also degrades positive memories. Sleep, it seems, protects positive memories just as it does negative ones, and that has important implications for the treatment of post-traumatic stress disorder.

"The study of how sleep helps us remember and process emotional information is still young," says Alexis Chambers of the University of Notre Dame. Past work has focused on the role of negative memories for sleep, in particular how insomnia is a healthy biological response for people to reduce negative memories and emotions associated with a traumatic event.

Two new studies presented this week at a meeting of cognitive neuroscientists in Chicago are exploring the flip side: how sleep treats the positive. “Only if we investigate all the possibilities within this field will we ever fully understand the processes underlying our sleep, memory, and emotions,” Chambers says.

Protecting the positive

To test how sleep affects positive memories, Rebecca Spencer of the University of Massachusetts, Amherst, and her colleagues split 70 young adults into two groups, one that got to sleep overnight and one that had to stay awake. Both groups viewed images of positive items, such as puppies and flowers, and neutral items, such as furniture or dinner plates. The researchers then tested the participants’ memories of and emotional reactions to the images 12 hours later, after either the period of sleep or wake.

They found that “sleep enhances our emotionally positive memories while these memories decay over wake,” Spencer says. “Positive memories may even be prioritized for processing during sleep.” But while people remembered the positive images more than the neutral ones, their emotional response to the positive images did not change over sleep versus wake. “It doesn’t matter if you went to sleep or stayed awake – what you thought was a ‘9’ – really great – you still think is a ‘9’,” she says. 

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April 2, 2012

(Medical Xpress) — A research team including University of Wyoming neurobiologist Jeff Woodbury has discovered a new technique to determine how the touch sensory system is organized in hairy skin, providing a new understanding of the sense of touch.

The journal Cell’s cover story features research findings by University of Wyoming neurobiologist Jeff Woodbury. He was part of a research team that is providing a new understanding of the sense of touch.

Their findings were selected to appear as the feature and cover article in Cell, one of the pre-eminent international journals in the biological sciences.

The research provides the first picture of how nerve cells that carry signals from hair on the skin are organized. Unlike all other senses, the skin is least amenable to study and has remained the most poorly understood.

"We have described the system that is in place to help explain how sensory information is processed to perceive the sense of touch," says Woodbury, an associate professor in the UW Department of Zoology and Physiology. He was part of a multidisciplinary research team led by David Ginty from Johns Hopkins University. Colleen Cassidy, a doctoral student in Woodbury’s lab, was a co-author of the study, which also included colleagues from the Howard Hughes Medical Institute at Rockefeller University, University of Pennsylvania and University of Pittsburgh.

"We have also been able to identify how combinations of nerve cells respond to fine-tactile stimuli, so we can now really begin to tease apart the circuitry of touch sensation," Woodbury adds. "One of the real breakthroughs is that, for the first time in more than 200 years of study, we now know the specific functions of some of the many different kinds of nerve endings in the skin. This is truly exciting and a major advance."

Mice have several different types of hair follicles in their coat, each of which is linked to the central nervous system by low-threshold wire-like nerve cells that stretch all the way to the spinal cord. There, the myriad signals carried from the skin are integrated, processed and sent to the brain.

This network of nerve endings in the skin of most hairy mammals, including humans, allows them to perceive fine tactile sensations, such as a drop of rain or an insect landing on their skin. The researchers now have a better understanding of how this complex system is organized. Before this discovery, Woodbury says there was no way to see how all of these different nerve cells were arranged — both in the skin and at the top of the spinal cord, where they end up.

The study, Woodbury says, opens doors to understanding not only touch, but skin senses such as temperature detection and pain.

"Touch is ultimately felt in the brain; it alerts us that something is going on," he says. "We have identified the logic of how this system is organized. We now know that each individual hair is a distinct sensory organ, and each one will detect different forces. A broad spectrum of frequencies within a given stimulus are ultimately recombined and analyzed until we become aware that something has happened, like a drop of rain or a light breeze."

Once the different sensory neurons are identified, researchers could test hypotheses about the role of these cells in the process of sensation.

"For example, researchers could study the animal, in the presence or absence of each of the different types of sensory cells, to determine differences in the animal’s behavior," Woodbury says. "It will be possible to shut them off, take them out of the picture, to see how the animal responds to different types of stimulation. The key to understanding any system is first to gain a marker to identify all the different components, and we have made a major step in that direction."

Provided by University of Wyoming

Source: medicalxpress.com

April 2, 2012

New research published in the April issue of The Journal of Nuclear Medicine reveals that systemic inflammation causes an increase in depressive symptoms and metabolic changes in the parts of the brain responsible for mood and motivation. With this finding, researchers can begin to test potential treatments for depression for patients that experience symptoms that are related to inflammation in the body or within the brain.

Multiple studies in rodents have shown that inflammation in the body has effects on the brain. This has also been shown in a few human studies—both through measurements of behavioral changes and brain imaging—when subjects were engaged in various computer tasks. The study “Glucose Metabolism in the Insula and Cingulate Is Affected by Systemic Inflammation in Humans,” however, for the first time measured brain activity when subjects were at rest.

"In the study we used F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET), which can accurately measure glucose metabolism in the brain, to determine which brain regions responded to systemic inflammation. Since the subjects were at rest, the changes we observed in the brain can only attributed to systemic inflammation," noted Jonas Hannestad, MD, PhD, lead author of the article.

In the study, nine healthy individuals received a double-blind endotoxin (which elicits systemic inflammation and mild depressive symptoms such as fatigue and reduced social interest) and placebo on different days. After administration, F-18 FDG PET was used to measure the differences in the cerebral metabolic rate of glucose in the insula, cingulate and amygdala regions of the brain. Behavior changes were also primarily assessed on the Montgomery-Asberg Depression Rating Scale (MADRS).

A statistical analysis of the results showed that endotoxin administration was associated with a higher normalized glucose metabolism (NMG) in the insula and lower NMG in the cingulate compared to the placebo; there was no significant difference in the NMG in the amygdala. Seven of nine subjects had an increase in NMG in the insula and a decrease in NMG in the cingulate, and all nine subjects had a decrease in NMG in the right anterior cingulate, suggesting that systemic inflammation induces fundamental physiologic changes in regional brain glucose metabolism. In addition, the MADRS increased for each subject after endotoxin administration, whereas no significant change was noted with the placebo.

Most researchers agree that depression is not a homogeneous disease, but rather that there are multiple mechanisms that can lead to similar symptoms. “If we can show that a subtype of depression is caused in part by inflammation,” said Hannestad, “we can test the ability of treatments that reduce inflammation in only patients in whom we believe inflammation plays a role. In the future, I expect that researchers in this field will be able to develop more precise PET measures that can be used to distinguish between, for instance, a person with ‘inflammatory depression’ and a person with another kind of depression. PET could then be used as diagnostic biomarker to separate subtypes of depression and as a therapeutic biomarker to detect the response to treatment.”

Nearly 17 percent of adults experience depression at some point over their lifetime, with 30.4 percent of cases classified as severe, according to the U.S. National Institute of Mental Health. Fifty-seven percent of adults with depression report receiving treatment in the past 12 months, although 37.8 percent receive minimally adequate treatment.

Provided by Society of Nuclear Medicine

Source: medicalxpress.com

April 2, 2012

A team of University of Pittsburgh mathematicians is using computational models to better understand how the structure of neural variability relates to such functions as short-term memory and decision making. In a paper published online April 2 in Proceedings of the National Academy of Sciences (PNAS), the Pitt team examines how fluctuations in brain activity can impact the dynamics of cognitive tasks.

Previous recordings of neural activity during simple cognitive tasks show a tremendous amount of trial-to-trial variability. For example, when a person was instructed to hold the same stimulus in working, or short-term, memory during two separate trials, the brain cells involved in the task showed very different activity during the two trials.

"A big challenge in neuroscience is translating variability expressed at the cellular and brain-circuit level with that in cognitive behaviors," said Brent Doiron, assistant professor of mathematics in Pitt’s Kenneth P. Dietrich School of Arts and Sciences and the project’s principal investigator. "It’s a fact that short-term memory degrades over time. If you try to recall a stored memory, there likely will be errors, and these cognitive imperfections increase the longer that short-term memory is engaged."

Doiron explains that brain cells increase activity during short-term memory functions. But this activity randomly drifts over time as a result of stochastic (or chance) forces in the brain. This drifting is what Doiron’s team is trying to better understand.

"As mathematicians, what we’re really trying to do is relate the structure and dynamics of this stochastic variability of brain activity to the variability in cognitive performance," said Doiron. "Linking the variability at these two levels will give important clues about the neural mechanisms that support cognition."

Using a combination of statistical mechanics and nonlinear system theory, the Pitt team examined the responses of a model of a simplified memory network proposed to be operative in the prefrontal cortex. When sources of neural variability were distributed over the entire network, as opposed to only over subsections, the performance of the memory network was enhanced. This helped the Pitt team make the prediction published in PNAS, that brain wiring affects how neural networks contend with—and ultimately express—variability in memory and decision making.

Recently, experimental neurosciencists are getting a better understanding of how the brain is wired, and theories like those published in PNAS by Doiron’s group give a context for their findings within a cognitive framework. The Doiron group plans to apply the general principle of linking brain circuitry to neural variability in a variety of sensory, motor, and memory/decision-making frameworks.

Provided by University of Pittsburgh

Source: medicalxpress.com

April 2nd, 2012

Therapy to mend parts of the brain damaged by strokes has moved a step closer, thanks to research at Monash University’s Australian Regenerative Medicine Institute (ARMI) and the Florey Neuroscience Institutes (FNI).

Scientists, James Bourne and Jihane Homman-Ludiye, of ARMI, and Tobias Merson, of FNI, have discovered precursor cells in the visual processing region of the brains of young marmoset monkeys which can form new brain cells in a culture dish.

The work, published recently in the journal, PLoS One, raises the possibility of new therapies for victims of brain injuries such as stroke.

Commenting on the work, Stem Cells Australia’s Professor Martin Pera said “These results, which point strongly to the existence of stem cells in the primate cortex, have important implications for understanding normal brain function and add to a growing body of evidence that stem or progenitor cells may participate in the repair of injuries to this critical region of the brain.”

The team isolated a type of cell from the brain tissue of two-week-old marmoset monkeys, which have similar brains to humans.

They exposed the cells to various combinations of growth factors – proteins that promote cell proliferation – to see if the cells would multiply and form neurons in the culture dish.

Some of the cells started to multiply to form clusters of cells called neurospheres – the forerunners of mature brain cells – when treated with two specific growth factors. This puts them in a class of cells called neural progenitors. Like stem cells, these cells can convert into specialist cells to form various tissues.

It was once thought that our full complement of brain cells was fixed at birth. That view has been toppled in recent decades with the discovery of stem cells in the human brain that can form new neurons in adulthood, said Dr Merson, a neuroscientist.

But until now, those cells have been thought to be limited to two regions of the brain, including the hippocampus, which is involved in memory and learning.

The team’s breakthrough suggests that cells with the ability to form new neurons after birth are much more widespread in the brain. The cells under investigation in this latest research were isolated from the primary visual cortex, the brain structure at the back of the head involved in the processing of stimuli from the eyes. “This structure is very big in humans and other primates and is often affected by brain injury,” Dr Bourne said.

“Our results support the view that this region of the brain has the potential to generate new neurons at later stages than once thought,” Dr Merson said. “We were surprised at how easily we were able to generate the proliferating neurospheres. We were able to propagate them, and keep them in culture for up to a year.”

He said other regions of the brain involved in sensory processing could harbour similar cells.

The scientists plan further research to see if the production of new neurons after birth occurs naturally in the primary visual cortex, and whether the mechanism could be activated after injury.

“It could be plausible to manipulate the progenitor cells to produce more neurons,” Dr Bourne said.

Source: Neuroscience News

ScienceDaily (Apr. 2, 2012) — Scientists from the Florida campus of The Scripps Research Institute have shown in animal models that the loss of memory that comes with aging is not necessarily a permanent thing.

In a new study published this week in an advance, online edition of the journal Proceedings of the National Academy of Science, Ron Davis, chair of the Department of Neuroscience at Scripps Florida, and Ayako Tonoki-Yamaguchi, a research associate in Davis’s lab, took a close look at memory and memory traces in the brains of both young and old fruit flies.

What they found is that like other organisms — from mice to humans — there is a defect that occurs in memory with aging. In the case of the fruit fly, the ability to form memories lasting a few hours (intermediate-term memory) is lost due to age-related impairment of the function of certain neurons. Intriguingly, the scientists found that stimulating those same neurons can reverse these age-related memory defects.

"This study shows that once the appropriate neurons are identified in people, in principle at least, one could potentially develop drugs to hit those neurons and rescue those memories affected by the aging process," Davis said. "In addition, the biochemistry underlying memory formation in fruit flies is remarkably conserved with that in humans so that everything we learn about memory formation in flies is likely applicable to human memory and the disorders of human memory."

While no one really understands what is altered in the brain during the aging process, in the current study the scientists were able to use functional cellular imaging to monitor the changes in the fly’s neuron activity before and after learning.

"We are able to peer down into the fly brain and see changes in the brain," Davis said. "We found changes that appear to reflect how intermediate-term memory is encoded in these neurons."

Olfactory memory, which was used by the scientists, is the most widely studied form of memory in fruit flies — basically pairing an odor with a mild electric shock. These tactics produce short-term memories that persist for around a half-hour, intermediate-term memory that lasts a few hours, and long-term memory that persists for days.

The team found that in aged animals, the signs of encoded memory were absent after a few hours. In that way, the scientists also learned exactly which neurons in the fly are altered by aging to produce intermediate-term memory impairment. This advance, Davis notes, should greatly help scientists understand how aging alters neuronal function.

Intriguingly, the scientists took the work a step further and stimulated these neurons to see if the memory could be rescued. To do this, the scientists placed either cold-activated or heat-activated ion channels in the neurons known to become defective with aging and then used cold or heat to stimulate them. In both cases, the intermediate-term memory was successfully rescued.

Source: Science Daily

ScienceDaily (Apr. 2, 2012) — An international team of researchers involving the University of Adelaide has made a major discovery that could lead to more effective treatment of severe pain using morphine.

Morphine is an extremely important drug for pain relief, but it can lead to a range of side-effects — such as patients developing tolerance to morphine and increased sensitivity to pain. Until now, how this occurs has remained a mystery.

The team from the University of Colorado and University of Adelaide has shown for the first time how opioid drugs, such as morphine, create an inflammatory response in the brain — by activating an immune receptor in the brain.

They have also demonstrated how this brain immune receptor can be blocked, laying the groundwork for the development of new therapeutic drugs that improve the effectiveness of morphine while reducing many of its problematic side effects.

The results of this research are published April 2 in the Proceedings of the National Academy of Sciences (PNAS).

"Because morphine is considered to be such an important drug in the management of moderate to severe pain in patients right around the world, we believe these results will have far-reaching benefits," says study co-author Dr Mark Hutchinson, ARC Research Fellow in the University of Adelaide’s School of Medical Sciences.

Dr Hutchinson’s team, including University of Adelaide colleague Professor Andrew Somogyi, conducted studies in mice to validate the work done at the University of Colorado by the teams of Assistant Professor Hubert Yin and Professor Linda Watkins.

"For some time it’s been assumed that the inflammatory response from morphine was being caused via the classical opioid receptors," says Dr Hutchinson.

"However, we found instead that morphine binds to an immune receptor complex called toll-like receptor 4 (TLR4), and importantly this occurs in a very similar way to how this receptor detects bacteria.

"Our experiments in mice have shown that if this relationship with the immune receptor is disrupted, it will prevent the inflammatory response.

"This is an exciting result because it opens up possibilities for future drugs that promote the beneficial actions of morphine while negating some of the harmful side effects. This could lead to major advances in patient and palliative care," he says.

Source: Science Daily

ScienceDaily (Apr. 2, 2012) — As computer scientists this year celebrate the 100_th anniversary of the birth of the mathematical genius Alan Turing, who set out the basis for digital computing in the 1930s to anticipate the electronic age, they still quest after a machine as adaptable and intelligent as the human brain.

Now, computer scientist Hava Siegelmann of the University of Massachusetts Amherst, an expert in neural networks, has taken Turing’s work to its next logical step. She is translating her 1993 discovery of what she has dubbed “Super-Turing” computation into an adaptable computational system that learns and evolves, using input from the environment in a way much more like our brains do than classic Turing-type computers. She and her post-doctoral research colleague Jeremie Cabessa report on the advance in the current issue of Neural Computation.

"This model is inspired by the brain," she says. "It is a mathematical formulation of the brain’s neural networks with their adaptive abilities." The authors show that when the model is installed in an environment offering constant sensory stimuli like the real world, and when all stimulus-response pairs are considered over the machine’s lifetime, the Super Turing model yields an exponentially greater repertoire of behaviors than the classical computer or Turing model. They demonstrate that the Super-Turing model is superior for human-like tasks and learning.

"Each time a Super-Turing machine gets input it literally becomes a different machine," Siegelmann says. "You don’t want this for your PC. They are fine and fast calculators and we need them to do that. But if you want a robot to accompany a blind person to the grocery store, you’d like one that can navigate in a dynamic environment. If you want a machine to interact successfully with a human partner, you’d like one that can adapt to idiosyncratic speech, recognize facial patterns and allow interactions between partners to evolve just like we do. That’s what this model can offer."

Classical computers work sequentially and can only operate in the very orchestrated, specific environments for which they were programmed. They can look intelligent if they’ve been told what to expect and how to respond, Siegelmann says. But they can’t take in new information or use it to improve problem-solving, provide richer alternatives or perform other higher-intelligence tasks.

In 1948, Turing himself predicted another kind of computation that would mimic life itself, but he died without developing his concept of a machine that could use what he called “adaptive inference.” In 1993, Siegelmann, then at Rutgers, showed independently in her doctoral thesis that a very different kind of computation, vastly different from the “calculating computer” model and more like Turing’s prediction of life-like intelligence, was possible. She published her findings in Science and in a book shortly after.

"I was young enough to be curious, wanting to understand why the Turing model looked really strong," she recalls. "I tried to prove the conjecture that neural networks are very weak and instead found that some of the early work was faulty. I was surprised to find out via mathematical analysis that the neural models had some capabilities that surpass the Turing model. So I re-read Turing and found that he believed there would be an adaptive model that was stronger based on continuous calculations."

Each step in Siegelmann’s model starts with a new Turing machine that computes once and then adapts. The size of the set of natural numbers is represented by the notation aleph-zero, ℵ₀, representing also the number of different infinite calculations possible by classical Turing machines in a real-world environment on continuously arriving inputs. By contrast, Siegelmann’s most recent analysis demonstrates that Super-Turing computation has 2^ℵ0, possible behaviors. “If the Turing machine had 300 behaviors, the Super-Turing would have 2³⁰⁰, more than the number of atoms in the observable universe,” she explains.

The new Super-Turing machine will not only be flexible and adaptable but economical. This means that when presented with a visual problem, for example, it will act more like our human brains and choose salient features in the environment on which to focus, rather than using its power to visually sample the entire scene as a camera does. This economy of effort, using only as much attention as needed, is another hallmark of high artificial intelligence, Siegelmann says.

"If a Turing machine is like a train on a fixed track, a Super-Turing machine is like an airplane. It can haul a heavy load, but also move in endless directions and vary its destination as needed. The Super-Turing framework allows a stimulus to actually change the computer at each computational step, behaving in a way much closer to that of the constantly adapting and evolving brain," she adds.

Siegelmann and two colleagues recently were notified that they will receive a grant to make the first ever Super-Turing computer, based on Analog Recurrent Neural Networks. The device is expected to introduce a level of intelligence not seen before in artificial computation.

Source: Science Daily