The Universal ‘Anger Face’

This is Your Brain’s Blood Vessels on Drugs

A new method for measuring and imaging how quickly blood flows in the brain could help doctors and researchers better understand how drug abuse affects the brain, which may aid in improving brain-cancer surgery and tissue engineering, and lead to better treatment options for recovering drug addicts. The new method, developed by a team of researchers from Stony Brook University in New York, USA and the U.S. National Institutes of Health, was published today in The Optical Society’s (OSA) open-access journal Biomedical Optics Express.

The researchers demonstrated their technique by using a laser-based method of measuring how cocaine disrupts blood flow in the brains of mice. The resulting images are the first of their kind that directly and clearly document such effects, according to co-author Yingtian Pan, associate professor in the Department of Biomedical Engineering at Stony Brook University. “We show that quantitative flow imaging can provide a lot of useful physiological and functional information that we haven’t had access to before,” he says.

Drugs such as cocaine can cause aneurysm-like bleeding and strokes, but the exact details of what happens to the brain’s blood vessels have remained elusive—partly because current imaging tools are limited in what they can see, Pan says. But using their new and improved methods, the team was able to observe exactly how cocaine affects the tiny blood vessels in a mouse’s brain. The images reveal that after 30 days of chronic cocaine injection or even after just repeated acute injection of cocaine, there’s a dramatic drop in blood flow speed. The researchers were, for the first time, able to identify cocaine-induced microischemia, when blood flow is shut down—a precursor to a stroke.

Measuring blood flow is crucial for understanding how the brain is working, whether you’re a brain surgeon or a neuroscientist studying how drugs or disease influence brain physiology, metabolism and function, Pan said. Techniques like functional magnetic resonance imaging (fMRI) provide a good overall map of the flow of deoxygenated blood, but they don’t have a high enough resolution to study what happens inside tiny blood vessels called capillaries. Meanwhile, other methods like two-photon microscopy, which tracks the movement of red blood cells labeled with fluorescent dyes, have a small field of view that only measures few vessels at a time rather than blood flow in the cerebrovascular networks.

In the last few years, researchers including Pan and his colleagues have developed another method called optical coherence Doppler tomography (ODT). In this technique, laser light hits the moving blood cells and bounces back. By measuring the shift in the reflected light’s frequency—the same Doppler effect that causes the rise or fall of a siren’s pitch as it moves toward or away from you—researchers can determine how fast the blood is flowing.

It turns out that ODT offers a wide field of view at high resolution. “To my knowledge, this is a unique technology that can do both,” Pan said. And, it doesn’t require fluorescent dyes, which can trigger harmful side effects in human patients or leave unwanted artifacts—from interactions with a drug being tested, for example—when used for imaging animal brains.

Two problems with conventional ODT right now, however, are that it’s only sensitive to a limited range in blood-flow speeds and not sensitive enough to detect slow capillary flows, Pan explained. The researchers’ new method described in today’s Biomedical Optics Express paper incorporates a new processing method called phase summation that extends the range and allows for imaging capillary flows.

Another limitation of conventional ODT is that it doesn’t work when the blood vessel is perpendicular to the incoming laser beam. In an image, the part of the vessel that’s perpendicular to the line of sight wouldn’t be visible, instead appearing dark. But by tracking the blood vessel as it slopes up or down near this dark spot, the researchers developed a way to use that information to interpolate the missing data more accurately.

ODT can only see down to 1-1.5 millimeters below the surface, so the method is limited to smaller animals if researchers want to probe into deeper parts of the brain. But, Pan says, it would still be useful when the brain’s exposed in the operating room, to help surgeons operate on tumors, for example.

The new method is best suited to look at small blood vessels and networks, so it can be used to image the capillaries in the eye as well. Bioengineers can also use it to monitor the growth of new blood vessels when engineering tissue, Pan said. Additionally, information about blood flow in the brain could also be applied to developing new treatment options for recovering drug addicts.

New study throws into question long-held belief about depression

New evidence puts into doubt the long-standing belief that a deficiency in serotonin — a chemical messenger in the brain — plays a central role in depression. In the journal ACS Chemical Neuroscience, scientists report that mice lacking the ability to make serotonin in their brains (and thus should have been “depressed” by conventional wisdom) did not show depression-like symptoms.

Donald Kuhn and colleagues at the John D. Dingell VA Medical Center and Wayne State University School of Medicine note that depression poses a major public health problem. More than 350 million people suffer from it, according to the World Health Organization, and it is the leading cause of disability across the globe. In the late 1980s, the now well-known antidepressant Prozac was introduced. The drug works mainly by increasing the amounts of one substance in the brain — serotonin. So scientists came to believe that boosting levels of the signaling molecule was the key to solving depression. Based on this idea, many other drugs to treat the condition entered the picture. But now researchers know that 60 to 70 percent of these patients continue to feel depressed, even while taking the drugs. Kuhn’s team set out to study what role, if any, serotonin played in the condition.

To do this, they developed “knockout” mice that lacked the ability to produce serotonin in their brains. The scientists ran a battery of behavioral tests. Interestingly, the mice were compulsive and extremely aggressive, but didn’t show signs of depression-like symptoms. Another surprising finding is that when put under stress, the knockout mice behaved in the same way most of the normal mice did. Also, a subset of the knockout mice responded therapeutically to antidepressant medications in a similar manner to the normal mice. These findings further suggest that serotonin is not a major player in the condition, and different factors must be involved. These results could dramatically alter how the search for new antidepressants moves forward in the future, the researchers conclude.

Researchers publish first study of brain activation in MS using fNIRS

Using functional near infrared spectroscopy (fNIRS), Kessler Foundation researchers have shown differential brain activation patterns between people with multiple sclerosis (MS) and healthy controls. This is the first MS study in which brain activation was studied using fNIRS while participants performed a cognitive task. The article, “Neuroimaging and cognition using functional near infrared spectroscopy (fNIRS) in multiple sclerosis,” was published online on June 11 by Brain Imaging and Behavior. Authors are Jelena Stojanovic-Radic, PhD, Glenn Wylie, DPhil, Gerald Voelbel, PhD, Nancy Chiaravalloti, PhD, and John DeLuca, PhD.

Researchers compared 13 individuals with MS with 12 controls for their performance on a working memory task with four levels of difficulty. Most such studies have employed functional magnetic resonance imaging (fMRI); fNIRS has been used infrequently in clinical populations, and has not been applied previously to neuroimaging research in MS.  Studies comparing fMRI findings with those of fNIRS, however, show broad agreement in terms of activation patterns.

Results showed differences in activation between the groups that were dependent on task load. The MS group had an increase in activation at low task difficulty and a decrease in activation at high task difficulty. Conversely, in the control group, activation decreased with low task difficulty and increased with high task difficulty. Performance accuracy was lower in the MS group for low task load; there were no differences between the groups at the higher task loads.  

“The data we obtained via fNIRS are consistent with fMRI data for clinical populations. We demonstrated that fNIRS is capable of detecting neuronal activation with a reasonable degree of detail,” noted Glenn Wylie, DPhil, associate director of Neuroscience and the Neuroimaging Center at Kessler Foundation. “We attribute the differences in brain activation patterns to the effort expended during the working memory task rather than to differences in speed of processing,” he added. “Because fNIRS is more portable and easier to use that fMRI, it may offer advantages in monitoring cognitive interventions that require frequent scans.”

In addition to working memory, future research in clinical populations should focus on processing speed and episodic memory, cognitive functions that are also affected in MS.

(Image credit)

Neuroscientists watch imagination happening in the brain

“You may say I’m a dreamer, but I’m not the only one,” sang John Lennon in his 1971 song Imagine.

And thanks to the dreams of a BYU student, we now know more about where and how imagination happens in our brains.

Stefania Ashby and her faculty mentor devised experiments using MRI technology that would help them distinguish pure imagination from related processes like remembering.

“I was thinking a lot about planning for my own future and imagining myself in the future, and I started wondering how memory and imagination work together,” Ashby said. “I wondered if they were separate or if imagination is just taking past memories and combining them in different ways to form something I’ve never experienced before.”

There’s a bit of scientific debate over whether memory and imagination truly are distinct processes. So Ashby and her faculty mentor devised MRI experiments to put it to the test.

They asked study participants to provide 60 personal photographs for the “remember” section of the experiment. Participants also filled out a questionnaire beforehand to determine which scenarios would be unfamiliar to them and thus a better fit for the “imagine” section.

The researchers then showed people their own photographs during an MRI session to elicit brain activity that is strictly memory-based. A statistical analysis revealed distinctive patterns for memory and imagination.

“We were able to see the distinctions even in those small regions of the hippocampus,” Ashby said. “It’s really neat that we can see the difference between those two tasks in that small of a brain region.”

Ashby co-authored the study with BYU psychology and neuroscience professor Brock Kirwan for the journal Cognitive Neuroscience. Kirwan studies memory at Brigham Young University, and Ashby is one of many students that he has mentored.

“Stefania came in really excited about this project, she pitched it to me, and basically sold it to me right there,” Kirwan said. “It was really cool because it gave me a chance to become more immersed and really broaden my horizons.”

Stefania graduated in 2011 and is currently working as a research associate at UC Davis, where she uses neuroimaging to study individuals at risk of psychotic disorders such as schizophrenia. Her plan is to earn a Ph.D. in neuroscience and continue researching.

Electric Current to Brain Boosts Memory

Stimulating a particular region in the brain via non-invasive delivery of electrical current using magnetic pulses, called Transcranial Magnetic Stimulation, improves memory, reports a new Northwestern Medicine® study.

The discovery opens a new field of possibilities for treating memory impairments caused by conditions such as stroke, early-stage Alzheimer’s disease, traumatic brain injury, cardiac arrest and the memory problems that occur in healthy aging.

“We show for the first time that you can specifically change memory functions of the brain in adults without surgery or drugs, which have not proven effective,” said senior author Joel Voss, assistant professor of medical social sciences at Northwestern University Feinberg School of Medicine. “This noninvasive stimulation improves the ability to learn new things. It has tremendous potential for treating memory disorders.”

The study was published August 29 in Science.

The study also is the first to demonstrate that remembering events requires a collection of many brain regions to work in concert with a key memory structure called the hippocampus – similar to a symphony orchestra. The electrical stimulation is like giving the brain regions a more talented conductor so they play in closer synchrony. 

“It’s like we replaced their normal conductor with Muti,” Voss said, referring to Riccardo Muti, the music director of the renowned Chicago Symphony Orchestra. “The brain regions played together better after the stimulation.”

The approach also has potential for treating mental disorders such as schizophrenia in which these brain regions and the hippocampus are out of sync with each other, affecting memory and cognition.    

TMS Boosts Memory 

The Northwestern study is the first to show TMS improves memory long after treatment. In the past, TMS has been used in a limited way to temporarily change brain function to improve performance during a test, for example, making someone push a button slightly faster while the brain is being stimulated. The study shows that TMS can be used to improve memory for events at least 24 hours after the stimulation is given.

Finding the Sweet Spot

It isn’t possible to directly stimulate the hippocampus with TMS because it’s too deep in the brain for the magnetic fields to penetrate. So, using an MRI scan, Voss and colleagues identified a superficial brain region a mere centimeter from the surface of the skull with high connectivity to the hippocampus. He wanted to see if directing the stimulation to this spot would in turn stimulate the hippocampus. It did.

“I was astonished to see that it worked so specifically,” Voss said.

When TMS was used to stimulate this spot, regions in the brain involved with the hippocampus became more synchronized with each other, as indicated by data taken while subjects were inside an MRI machine, which records the blood flow in the brain as an indirect measure of neuronal activity.

The more those regions worked together due to the stimulation, the better people were able to learn new information.

How the Study Worked

Scientists recruited 16 healthy adults ages 21 to 40. Each had a detailed anatomical image taken of his or her brain as well as 10 minutes of recording brain activity while lying quietly inside an MRI scanner. Doing this allowed the researchers to identify each person’s network of brain structures that are involved in memory and well connected to the hippocampus. The structures are slightly different in each person and may vary in location by as much as a few centimeters.

“To properly target the stimulation, we had to identify the structures in each person’s brain space because everyone’s brain is different,” Voss said. 

Each participant then underwent a memory test, consisting of a set of arbitrary associations between faces and words that they were asked to learn and remember. After establishing their baseline ability to perform on this memory task, participants received brain stimulation 20 minutes a day for five consecutive days. 

During the week they also received additional MRI scans and tests of their ability to remember new sets of arbitrary word and face parings to see how their memory changed as a result of the stimulation. Then, at least 24 hours after the final stimulation, they were tested again.

At least one week later, the same experiment was repeated but with a fake placebo stimulation. The order of real stimulation and placebo portions of the study was reversed for half of the participants, and they weren’t told which was which.

Both groups performed better on memory tests as a result of the brain stimulation. It took three days of stimulation before they improved.

“They remembered more face-word pairings after the stimulation than before, which means their learning ability improved,” Voss said. “That didn’t happen for the placebo condition or in another control experiment with additional subjects.”

In addition, the MRI showed the stimulation caused the brain regions to become more synchronized with each other and the hippocampus. The greater the improvement in the synchronicity or connectivity between specific parts of the network, the better the performance on the memory test. “The more certain brain regions worked together because of the stimulation, the more people were able to learn face-word pairings, “ Voss said.

Using TMS to stimulate memory has multiple advantages, noted first author Jane Wang, a postdoctoral fellow in Voss’s lab at Feinberg. “No medication could be as specific as TMS for these memory networks,” Wang said. “There are a lot of different targets and it’s not easy to come up with any one receptor that’s involved in memory.”

The Future 

“This opens up a whole new area for treatment studies where we will try to see if we can improve function in people who really need it,“ Voss said.

His current study was with people who had normal memory, in whom he wouldn’t expect to see a big improvement because their brains are already working effectively.

“But for a person with brain damage or a memory disorder, those networks are disrupted so even a small change could translate into gains in their function,” Voss said.

In an upcoming trial, Voss will study the electrical stimulation’s effect on people with early-stage memory loss.

Voss cautioned that years of research are needed to determine whether this approach is safe or effective for patients with Alzheimer’s disease or similar disorders of memory.

Scientists Discover Why Learning Tasks Can Be Difficult

Learning a new skill is easier when it is related to an ability we already have. For example, a trained pianist can learn a new melody easier than learning how to hit a tennis serve.

Scientists from the Center for the Neural Basis of Cognition (CNBC) — a joint program between Carnegie Mellon University and the University of Pittsburgh — have discovered a fundamental constraint in the brain that may explain why this happens. Published as the cover story in the Aug. 28, 2014, issue of Nature, they found for the first time that there are limitations on how adaptable the brain is during learning and that these restrictions are a key determinant for whether a new skill will be easy or difficult to learn. Understanding the ways in which the brain’s activity can be “flexed” during learning could eventually be used to develop better treatments for stroke and other brain injuries.

Lead author Patrick T. Sadtler, a Ph.D. candidate in Pitt’s Department of Bioengineering, compared the study’s findings to cooking.

"Suppose you have flour, sugar, baking soda, eggs, salt and milk. You can combine them to make different items - bread, pancakes and cookies — but it would be difficult to make hamburger patties with the existing ingredients," Sadtler said. "We found that the brain works in a similar way during learning. We found that subjects were able to more readily recombine familiar activity patterns in new ways relative to creating entirely novel patterns."

For the study, the research team trained animals to use a brain-computer interface (BCI), similar to ones that have shown recent promise in clinical trials for assisting quadriplegics and amputees.

"This evolving technology is a powerful tool for brain research," said Daofen Chen, program director at the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health (NIH), which supported this research. "It helps scientists study the dynamics of brain circuits that may explain the neural basis of learning."

The researchers recorded neural activity in the subject’s motor cortex and directed the recordings into a computer, which translated the activity into movement of a cursor on the computer screen. This technique allowed the team to specify the activity patterns that would move the cursor. The test subjects’ goal was to move the cursor to targets on the screen, which required them to generate the patterns of neural activity that the experimenters had requested. If the subjects could move the cursor well, that meant that they had learned to generate the neural activity pattern that the researchers had specified.

The results showed that the subjects learned to generate some neural activity patterns more easily than others, since they only sometimes achieved accurate cursor movements. The harder-to-learn patterns were different from any of the pre-existing patterns, whereas the easier-to-learn patterns were combinations of pre-existing brain patterns. Because the existing brain patterns likely reflect how the neurons are interconnected, the results suggest that the connectivity among neurons shapes learning.

"We wanted to study how the brain changes its activity when you learn, and also how its activity cannot change. Cognitive flexibility has a limit — and we wanted to find out what that limit looks like in terms of neurons," said Aaron P. Batista, assistant professor of bioengineering at Pitt.

Byron M. Yu, assistant professor of electrical and computer engineering and biomedical engineering at Carnegie Mellon, believes this work demonstrates the utility of BCI for basic scientific studies that will eventually impact people’s lives.

"These findings could be the basis for novel rehabilitation procedures for the many neural disorders that are characterized by improper neural activity," Yu said. "Restoring function might require a person to generate a new pattern of neural activity. We could use techniques similar to what were used in this study to coach patients to generate proper neural activity."

(Image: Fotolia)

Scientists Link Alcohol-Dependence Gene to Neurotransmitter

Scientists at The Scripps Research Institute (TSRI) have solved the mystery of why a specific signaling pathway can be associated with alcohol dependence.

This signaling pathway is regulated by a gene, called neurofibromatosis type 1 (Nf1), which TSRI scientists found is linked with excessive drinking in mice. The new research shows Nf1 regulates gamma-aminobutyric acid (GABA), a neurotransmitter that lowers anxiety and increases feelings of relaxation.

“This novel and seminal study provides insights into the cellular mechanisms of alcohol dependence,” said TSRI Associate Professor Marisa Roberto, a co-author of the paper. “Importantly, the study also offers a correlation between rodent and human data.”

In addition to showing that Nf1 is key to the regulation of the GABA, the research, which was published recently in the journal Biological Psychiatry, shows that variations in the human version of the Nf1 gene are linked to alcohol-dependence risk and severity in patients.

Pietro Paolo Sanna, associate professor at TSRI and the study’s corresponding author, was optimistic about the long-term clinical implications of the work. “A better understanding of the molecular processes involved in the transition to alcohol dependence will foster novel strategies for prevention and therapy,” he said.

A Genetic Culprit

Researchers have long sought a gene or genes that might be responsible for risk and severity of alcohol dependence. “Despite a significant genetic contribution to alcohol dependence, few risk genes have been identified to date, and their mechanisms of action are generally poorly understood,” said TSRI Staff Scientist Vez Repunte-Canonigo, co-first author of the paper with TSRI Research Associate Melissa Herman.

This research showed that Nf1 is one of those rare risk genes, but the TSRI researchers weren’t sure exactly how Nf1 affected the brain. The TSRI research team suspected that Nf1 might be relevant to alcohol-related GABA activity in an area of the brain called the central amygdala, which is important in decision-making and stress- and addiction-related processes.

“As GABA release in the central amygdala has been shown to be critical in the transition from recreational drinking to alcohol dependence, we thought that Nf1 regulation of GABA release might be relevant to alcohol consumption,” said Herman.

The team tested several behavioral models, including a model in which mice escalate alcohol drinking after repeated withdrawal periods, to study the effects of partially deleting Nf1. In this experiment, which simulated the transition to excessive drinking that is associated with alcohol dependence in humans, they found that mice with functional Nf1 genes steadily increased their ethanol intake starting after just one episode of withdrawal. Conversely, mice with a partially deleted Nf1 gene showed no increase in alcohol consumption.

Investigating further, the researchers found that in mice with partially deleted Nf1 genes, alcohol consumption did not further increase GABA release in the central amygdala. In contrast, in mice with functional Nf1 genes, alcohol consumption resulted in an increase in central amygdala GABA.

In the second part of the study, a collaboration with a distinguished group of geneticists at various U.S. institutions, the team analyzed data on human variations of the Nf1 gene from about 9,000 people. The results showed an association between the gene and alcohol-dependence risk and severity.

The team sees the new findings as “pieces to the puzzle.” Sanna believes future research should focus on exactly how Nf1 regulates the GABA system and how gene expression may be altered during early development.