Posts tagged neural activity

Life presents us with choices all the time: salad or pizza for lunch? Tea or coffee afterward? How we make these everyday decisions has been a topic of great interest to economists, who have devised theories about how we assign values to our options and use those values to make decisions.

An emerging field of study known as neuroeconomics is combining the economists’ insights with scientific study of the brain to learn more about decision-making processes and how they can go awry. In the Dec. 8 issue of Neuron, one of the field’s founders reports new links between brain cell activity and choices where two options have equal appeal.

“Neuroeconomics is not only helpful for the development of better economic theory, it is also relevant from a clinical point of view,” said author Camillo Padoa-Schioppa, PhD, assistant professor of neurobiology, economics and of biomedical engineering at Washington University School of Medicine in St. Louis. “There are a number of conditions that involve impaired economic decision-making, including drug addiction, brain injury, some forms of dementia, schizophrenia and obsessive-compulsive disorder.”

Scientists know that the orbitofrontal cortex, a region of the brain behind and above the eyes, plays a key role in making decisions. Patients with injuries to this part of the brain are often spectacularly bad at making decisions. They may do things like abandon longstanding relationships, gamble away money or lose it to swindlers, or become addicted to drugs.

To study the roles brain cells play in decision-making, Padoa-Schioppa developed a system for presenting primates a choice between two drinks, such as grape juice or apple juice. The type and amount of the drink varies, and researchers record the activity of individual brain neurons as the primates choose.

Based on the decisions of a single animal over multiple trials, scientists infer the subjective value the animal assigns to each drink and then look for ways this value is encoded in brain cells.

“For example, if we offer a larger amount of apple juice versus a smaller amount of grape juice, and the primate chooses each option equally often, we infer that this primate likes the grape juice better than the apple juice,” he explained. “The primate could be getting more juice by choosing the cup with apple juice, but it doesn’t always do so. That implies that the primate values grape juice more than apple juice.”

In 2006, Padoa-Schioppa and Harvard colleague John Assad, PhD, won international attention for using this system to identify brain cells whose firing rates encoded the subjective value of drink choices.

In a new analysis of data from the original experiment, Padoa-Schioppa showed that different groups of cells in the orbitofrontal cortex reflect different stages of the decision-making process.

“Some neurons encode the value of individual drinks; other neurons encode the choice outcome in a binary way ‒ these cells are either firing or silent depending on the chosen drink,” he explained. “Yet other neurons encode the value of the chosen option.”

Padoa-Schioppa then examined how different groups of cells determine decisions between options of equal value. He showed that toss-up decisions seemed to depend on changes in the initial state of the network of neurons in the orbitofrontal cortex.

“The fluctuations in the network took place before the primates were even offered a choice of juices, but they seem to somehow bias the decision,” Padoa-Schioppa said. “Neuronal signals are always noisy. In essence, close-call decisions are partly determined by random noise.”

He also found that decisions on choices of equal value were linked to the ease or difficulty with which nerve cells in parts of the orbitofrontal cortex communicate with each other. This property, known as synaptic efficacy, can be adjusted by the brain as part of the process of encoding information.

According to Padoa-Schioppa, these results provide new insights into the neuronal circuits that underlie economic decisions. He and his colleagues are using them to create a computational model of decision-making.

“The next step is to test that model,” Padoa-Schioppa said. “For example, we would like to bias decisions by artificially manipulating the activity of specific groups of cells.”

(Source: news.wustl.edu)

While the human brain is in a resting state, patterns of neuronal activity which are associated to specific memories may spontaneously reappear. Such recurrences contribute to memory consolidation – i.e. to the stabilization of memory contents. Scientists of the DZNE and the University of Bonn are reporting these findings in the current issue of The Journal of Neuroscience. The researchers headed by Nikolai Axmacher performed a memory test on a series of persons while monitoring their brain activity by functional magnetic resonance imaging (fMRI). The experimental setup comprised several resting states including a nap inside a neuroimaging scanner. The study indicates that resting periods can generally promote memory performance.

Depending on one’s mood and activity different regions are active in the human brain. Perceptions and thoughts also influence this condition and this results in a pattern of neuronal activity which is linked to the experienced situation. When it is recalled, similar patterns, which are slumbering in the brain, are reactivated. How this happens, is still largely unknown.

The prevalent theory of memory formation assumes that memories are stored in a gradual manner. At first, the brain stores new information only temporarily. For memories to remain in the long term, a further step is required. „We call it consolidation“, Dr. Nikolai Axmacher explains, who is a researcher at the Department of Epileptology of the University of Bonn and at the Bonn site of the DZNE. “We do not know exactly how this happens. However, studies suggest that a process we call reactivation is of importance. When this occurs, the brain replays activity patterns associated with a particular memory. In principle, this is a familiar concept. It is a fact that things that are actively repeated and practiced are better memorized. However, we assume that a reactivation of memory contents may also happen spontaneously without there being an external trigger.”

A memory test inside the scanner
Axmacher and his team tested this hypothesis in an experiment that involved ten healthy participants with an average age of 24 years. They were shown a series of pictures, which displayed – among other things – frogs, trees, airplanes and people. Each of these pictures was associated with a white square as a label at a different location. The subjects were asked to memorize the position of the square. At the end of the experiment all images were shown again, but this time without the label. The study participants were then asked to indicate with a mouse cursor where the missing mark was originally located. Memory performance was measured as the distance between the correct and the indicated position.

“This is an associative task. Visual and spatial perceptions have to be linked together”, the researcher explains. “Such tasks involve several brain regions. These include the visual cortex and the hippocampus, which takes part in many memory processes.”

Brain activity was recorded by fMRI during the entire experiment, which lasted several hours and included resting periods and a nap inside the neuroimaging scanner.

Recurrent brain patterns increased the accuracy
For data processing a pattern recognition algorithm was trained to look for similarities between neuronal patterns observed during initial encoding and patterns appearing at later occasions. “This method is complex, but quite effective”, Axmacher says. “Analysis showed that neuronal activity associated with images that were shown initially did reappear during subsequent resting periods and in the sleeping phase.”

Memory performance correlated with the replay of neuronal activity patterns. “The more frequently a pattern had reappeared, the more accurate test participants could label the corresponding image”, Axmacher summarizes the findings. “These results support our assumption that neural patterns can spontaneously reappear and that they promote the formation of long-lasting memory contents. There was already evidence for this from animal studies. Our experiment shows that this phenomenon also happens in humans.”

Memory performance benefits from resting periods
The study indicates that resting periods can generally foster memory performance. “Though, our data did not show whether sleeping had a particular effect. This may be due to the experimental setup, which only allowed for a comparatively short nap”, Axmacher reckons. “By contrast, night sleep is considered to be beneficial for the consolidation of memory contents. But it usually takes many hours and includes multiple transitions between different stages of sleep. However, other studies suggest that even short naps may positively affect memory consolidation.”

An objective look at memory contents
It is up to speculation whether the recurring brain patterns triggered conscious memories or whether they remained below the threshold of perception. “I think it is reasonable to assume that during resting periods the test participants let their mind wander and that they recalled images they had just seen before. But this is a matter of subjective perception of the test participants. That’s something we did not look at because it is not essential for our investigation“, Axmacher says. “The strength of our approach lies rather in the fact that we look at memory contents from the outside, in an objective manner. And that we can evaluate them by pattern recognition. This opens ways to many questions of research. For example, brain patterns that reoccur spontaneously are also of interest in the context of experimental dream research.”

(Source: dzne.de)

Establishing links between genes, the brain and human behavior is a central issue in cognitive neuroscience research, but studying how genes influence cognitive abilities and behavior as the brain develops from childhood to adulthood has proven difficult.

Now, an international team of scientists has made inroads to understanding how genes influence brain structure and cognitive abilities and how neural circuits produce language.

The team studied individuals with a rare disorder known as Williams syndrome. By measuring neural activity in the brain associated with the distinct language skills and facial recognition abilities that are typical of the syndrome, they showed that Williams is due not to a single gene but to distinct subsets of genes, hinting that the syndrome is more complex than originally thought.

"Solutions to understanding the connections between genes, neural circuits and behavior are now emerging from a unique union of genetics and neuroscience," says Julie Korenberg, a University of Utah professor and an adjunct professor at the Salk Institute, who led the genetics aspects on the new study.

The study was led by Debra Mills, a professor of cognitive neuroscience at Bangor University in Wales. Ursula Bellugi, a professor at the Salk Institute for Biological Studies in La Jolla, was also integrally involved in the research.

Korenberg was convinced that with Mills’ approach of directly measuring the brain’s electrical firing they could solve the puzzle of precisely which genes were responsible for building the brain wiring underlying the different reaction to human faces in Williams syndrome.

"We also discovered," says Mills, "that in those with Williams syndrome, the brain processes language and faces abnormally from early childhood through middle age. This was a surprise because previous studies had suggested that part of the Williams brain functions normally in adulthood, with little understanding about how it developed."

The results of the study were published November 12, 2013 in Developmental Neuropsychology.

Williams syndrome is caused by the deletion of one of the two usual copies of approximately 25 genes from chromosome 7, resulting in mental impairment. Nearly everyone with the condition is missing these same genes, although a few rare individuals retain one or more genes that most people with Williams have lost. Korenberg was the early pioneer of studying these individuals with partial gene deletions as a way of gathering clues to the specific function of those genes and gene networks. The syndrome affects approximately 1 in 10,000 people around the world, including an estimated 20,000 to 30,000 individuals in the United States.

Although individuals with Williams experience developmental delays and learning disabilities, they are exceptionally sociable and possess remarkable verbal abilities and facial recognition skills in relation to their lower IQ. Bellugi has long observed that sociability also seems to drive language and has spent much of her career studying those with Williams syndrome.

"Williams offers us a window into how the brain works at many different levels," says Bellugi. "We have the tools to measure the different cognitive abilities associated with the syndrome, and thanks to Julie and Debbie we are now able to combine this with studies of the underlying genetic and neurological aspects."

Suspecting that specific genes might lie at the origins of brain plasticity, functional changes in the brain that occur with new knowledge or experiences, and that these genes might be linked to the unusual proficiencies of those with Williams, the team enrolled individuals of various ages in their study. They drew from children, adolescents and adults who all had the full genetic deletion for Williams syndrome and compared them with their non-affected peers. Their study is additionally significant for being one of the first to examine the brain structure and its functioning in children with Williams. And, as Korenberg predicted, a critical piece of the puzzle came from including in their study two adults with partial genetic deletions for Williams.

Using highly sensitive sensors to measure brain activity, the researchers, led by Mills, presented their study participants with both visual and auditory stimuli in the form of unfamiliar faces and spoken sentences. They charted the small changes in voltage generated by the areas of the brain responding to these stimuli, a process known as event-related potentials (ERPs). Mills was the first to publish studies on Williams syndrome using ERPs, developed the ERP markers for this study, and oversaw its design and analysis.

Mills identified ERP markers of brain plasticity in Williams syndrome in children and adults of varying ages and developmental stages. These findings are important because the brains of people with Williams are structured differently than those of people without the syndrome. In the Williams brain, the dorsal areas (along the back and top), which help control vision and spatial understanding, are undersized. The ventral areas (at the front and the bottom), which influence language, facial recognition, emotion and social drive, are relatively normal in size.

It was previously believed that in individuals with Williams, the ventral portion of the brain operated normally. What the team discovered, however, was that this area of the brain also processed information differently than those without the syndrome, and did so throughout development, from childhood to the adult years. This suggests that the brain was compensating in order to analyze information; in other words, it was exhibiting plasticity. Of additional importance, the distinct ERP markers identified by Mills are so characteristic of the different brain organization in Williams that this information alone is approximately 90 percent accurate when analyzing brain activity to identify someone with Williams syndrome.

Other key findings of the study resulted from comparing the ERPs of participants with full Williams deletion with those with partial genetic deletions. While psychological tests focused on facial recognition show no difference between these groups, the scientists found differences in these recognition abilities on the ERP measurements, which look directly at neural activity. Thus, the scientists were able to see how very slight genetic differences affected brain activity, which will allow them identify the roles of sub-sets of Williams genes in brain development and in adult facial recognition abilities.

By combining these one-in-a-million people with tools capable of directly measuring brain activity, the scientists now have the unprecedented opportunity to study the genetic underpinnings of mental disorders. The results of this study not only advance science’s understanding of the links between genes, the brain and behavior, but may lead to new insight into such disorders as autism, Down syndrome and schizophrenia.

"By greatly narrowing the specific genes involved in social disorders, our findings will help uncover targets for treatment and provide measures by which these and other treatments are successful in alleviating the desperation of autism, anxiety and other disorders," says Korenberg.

(Source: salk.edu)

Our sense of smell is often the first response to environmental stimuli. Odors trigger neurons in the brain that alert us to take action. However, there is often more than one odor in the environment, such as in coffee shops or grocery stores. How does our brain process multiple odors received simultaneously?

Barani Raman, PhD, of the School of Engineering & Applied Science at Washington University in St. Louis, set out to find an answer. Using locusts, which have a relatively simple sensory system ideal for studying brain activity, he found the odors prompted neural activity in the brain that allowed the locust to correctly identify the stimulus, even with other odors present.

The results were published in Nature Neuroscience as the cover story of the December 2013 print issue.

The team uses a computer-controlled pneumatic pump to administer an odor puff to the locust, which has olfactory receptor neurons in its antennae, similar to sensory neurons in our nose. A few seconds after the odor puff is given, the locust gets a piece of grass as a reward, as a form of Pavlovian conditioning. As with Pavlov’s dog, which salivated when it heard a bell ring, trained locusts anticipate the reward when the odor used for training is delivered. Instead of salivating, they open their palps, or finger-like projections close to the mouthparts, when they predict the reward. Their response was less than half of a second. The locusts could recognize the trained odors even when another odor meant to distract them was introduced prior to the target cue.

“We were expecting this result, but the speed with which it was done was surprising,” says Raman, assistant professor of biomedical engineering. “It took only a few hundred milliseconds for the locust’s brain to begin tracking a novel odor introduced in its surrounding. The locusts are processing chemical cues in an extremely rapid fashion.”

“There were some interesting cues in the odors we chose,” Raman says. “Geraniol, which smells like rose to us, was an attractant to the locusts, but citral, which smells like lemon to us, is a repellant to them. This helped us identify principles that are common to the odor processing.

Raman has spent a decade learning how the human brain and olfactory system operate to process scent and odor signals. His research seeks to take inspiration from the biological olfactory system to develop a device for noninvasive chemical sensing. Such a device could be used in homeland security applications to detect volatile chemicals and in medical diagnostics, such as a device to test blood-alcohol level.

This study is the first in a series seeking to understand the principles of olfactory computation, Raman says.

“There is a precursory cue that could tell the brain there is a predator in the environment, and it has to predict what will happen next,” Raman says. “We want to determine what kinds of computations have to be done to make those predictions.”

In addition, the team is looking to answer other questions.

“Neural activity in the early processing centers does not terminate until you stop the odor pulse,” he says. “If you have a lengthy pulse – 5 or 10 seconds long – what is the role of neural activity that persists throughout the stimulus duration and often even after you terminate the stimulus? What are the roles of the neural activity generated at different points in time, and how do they help the system adapt to the environment? Those questions are still not clear.”

(Source: news.wustl.edu)

New research on pond snails has revealed that high levels of stress can block memory processes. Researchers from the University of Exeter and the University of Calgary trained snails and found that when they were exposed to multiple stressful events they were unable remember what they had learned.

Previous research has shown that stress also affects human ability to remember. This study, published in the journal PLOS ONE, found that experiencing multiple stressful events simultaneously has a cumulative detrimental effect on memory.

Dr Sarah Dalesman, a Leverhulme Trust Early Career Fellow, from Biosciences at the University of Exeter, formally at the University of Calgary, said: “It’s really important to study how different forms of stress interact as this is what animals, including people, frequently experience in real life. By training snails, and then observing their behaviour and brain activity following exposure to stressful situations, we found that a single stressful event resulted in some impairment of memory but multiple stressful events prevented any memories from being formed.” 

The pond snail, Lymnaea stagnalis, has easily observable behaviours linked to memory and large neurons in the brain, both useful benefits when studying memory processes. They also respond to stressful events in a similar way to mammals, making them a useful model species to study learning and memory.

In the study, the pond snails were trained to reduce how often they breathed outside water. Usually pond snails breathe underwater and absorb oxygen through their skin. In water with low oxygen levels the snails emerge and inhale air using a basic lung opened to the air via a breathing hole.

To train the snails not to breathe air they were placed in poorly oxygenated water and their breathing holes were gently poked every time they emerged to breathe. Snail memory was tested by observing how many times the snails attempted to breathe air after they had received their training. Memory was considered to be present if there was a reduction in the number of times they opened their breathing holes. The researchers also assessed memory by monitoring neural activity in the brain. 

Immediately before training, the snails were exposed to two different stressful experiences, low calcium - which is stressful as calcium is necessary for healthy shells - and overcrowding by other pond snails.

When faced with the stressors individually, the pond snails had reduced ability to form long term memory, but were still able to learn and form short and intermediate term memory lasting from a few minutes to hours. However, when both stressors were experienced at the same time, results showed that they had additive effects on the snails’ ability to form memory and all learning and memory processes were blocked. 

Future work will focus on the effects of stress on different populations of pond snail.

(Source: exeter.ac.uk)

Joint research from the University of Alabama at Birmingham Department of Psychology and Auburn University indicates that brain scans show signs of autism that could eventually support behavior-based diagnosis of autism and effective early intervention therapies. The findings appear online today in Frontiers in Human Neuroscience as part of a special issue on brain connectivity in autism.

“This research suggests brain connectivity as a neural signature of autism and may eventually support clinical testing for autism,” said Rajesh Kana, Ph.D., associate professor of psychology and the project’s senior researcher. “We found the information transfer between brain areas, causal influence of one brain area on another, to be weaker in autism.”

The investigators found that brain connectivity data from 19 paths in brain scans predicted whether the participants had autism, with an accuracy rate of 95.9 percent.

Kana, working with a team including Gopikrishna Deshpande, Ph.D., from Auburn University’s MRI Research Center, studied 15 high-functioning adolescents and adults with autism, as well as 15 typically developing control participants ages 16-34 years. Kana’s team collected all data in his autism lab at UAB that was then analyzed using a novel connectivity method at Auburn.

The current study showed that adults with autism spectrum disorders processed social cues differently than typical controls. It also revealed the disrupted brain connectivity that explains their difficulty in understanding social processes.

“We can see that there are consistently weaker brain regions due to the disrupted brain connectivity,” Kana said. “There’s a very clear difference.”

Participants in this study were asked to choose the most logical of three possible endings as they watched a series of comic strip vignettes while a functional MRI scanner measured brain activity.

The scenes included a glass about to fall off a table and a man enjoying the music of a street violinist and giving him a cash tip. Most participants in the autism group had difficulty in finding a logical end to the violinist scenario, which required an understanding of emotional and mental states. The current study showed that adults with autism spectrum disorders struggle to process subtle social cues, and altered brain connectivity may underlie their difficulty in understanding social processes.

“We can see that the weaker connectivity hinders the cross-talk among brain regions in autism,” Kana said.

Kana plans to continue his research on autism.

“Over the next five to 10 years, our research is going in the direction of finding objective ways to supplement the diagnosis of autism with medical testing and testing the effectiveness of intervention in improving brain connectivity,” Kana said.

Autism is currently diagnosed through interviews and behavioral observation. Although autism can be diagnosed by 18 months, in reality, earliest diagnoses occur around ages 4-6 as children face challenges in school or social settings.

“Parents usually have a longer road before getting a firm diagnosis for their child now,” Kana said. “You lose a lot of intervention time, which is so critical. Brain imaging may not be able to replace the current diagnostic measures; but if it can supplement them at an earlier age, that’s going to be really helpful.”

(Source: uab.edu)