Posts Tagged Research

[WEB PAGE] Individual frequency can be used to control brain activity – News

Reviewed by Emily Henderson, B.Sc.Aug 17 2020

Individual frequency can be used to specifically influence certain areas of the brain and thus the abilities processed in them – solely by electrical stimulation on the scalp, without any surgical intervention. Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences have now demonstrated this for the first time.

Stroke, Parkinson’s disease and depression – these medical illnesses have one thing in common: they are caused by changes in brain functions. For a long time, research has therefore been conducted into ways of influencing individual brain functions without surgery in order to compensate for these conditions.

Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, have taken a decisive step. They have succeeded in precisely influencing the functioning of a single area of the brain. For a few minutes, they inhibited exactly the area that processes the sense of touch by specifically intervening in its rhythm. As a result, the area that was less networked with other brain regions, its so-called functional connectivity, decreased, and thus also the exchange of information with other brain networks.

This was possible because the researchers had previously determined each participant’s individual brain rhythm that occurs when perceiving touch. With the personal frequency, they were able to modulate the targeted areas of the brain one at a time in a very precise manner using what is known as transcranial alternating current stimulation. “This is an enormous advance,” explains Christopher Gundlach, first author of the underlying study. “In previous studies, connectivity fluctuated extensively when the current was distributed in different areas of the brain. The electrical current randomly sought its own path in the brain and thus affected different brain areas simultaneously in a rather imprecise manner.

In a preliminary study, the neuroscientists had already observed that this form of stimulation not only reduces the exchange of the targeted brain networks with other networks, it also affects the brain’s ability to process information, in this case the sense of touch. When the researchers inhibited the responsible somatosensory network, the perception threshold increased. The study participants only perceived stimuli when they were correspondingly strong. When, on the other hand, they stimulated the region, the threshold value dropped and the study participants already felt very gentle electrical stimuli.

The deliberate change in brain rhythm lasted only briefly. As soon as the stimulation is switched off, the effect disappears again. Nevertheless, the results are an important step towards a targeted therapy for diseases or disorders caused by disturbed brain functions”.

Bernhard Sehm, Study Leader

Targeted brain stimulation could help to improve, direct and, if necessary, attenuate the flow of information.

Source: Max Planck Institute for Human Cognitive and Brain Sciences

Journal reference: Gundlach, C., et al. (2020) Reduction of somatosensory functional connectivity by transcranial alternating current stimulation at endogenous mu-frequency.  NeuroImage. doi.org/10.1016/j.neuroimage.2020.117175.

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[WEB PAGE] International researchers propose new classification system of seizures

Epilepsy is a wide-spread neurological disorder that affects around 50 million people worldwide. It is characterized by recurrent epileptic seizures, which are sudden bursts of electrical activity in the brain. There are many different types of seizures, and a person with epilepsy can experience more than one type.

Clinicians today use EEG measurements, with electrodes either placed on a patient’s scalp or inside the brain, to identify when and where a seizure begins. But these measurements alone do not always provide enough information to understand the type of seizure and make optimal decisions regarding treatment.

Now, an international team of researchers led by Aix-Marseille University in France and the University of Michigan has proposed a new classification system of seizures based on a deep understanding and mathematical modelling of brain oscillations. “It represents the first objective and unbiased taxonomy of its kind”, says one of the lead authors, HBP-scientist Prof. Viktor Jirsa from Aix-Marseille University.

The researchers used “bifurcation theory” – a method commonly used in fields such as physics and engineering – to analyze data from over a hundred patients across the globe. Researchers from the University of Melbourne and Monash University, both in Australia, the University of Freiburg in Germany, and Kyoto University in Japan also contributed to the work. Seizures with similar properties were categorized into groups.

They found sixteen types of seizure dynamics – or ‘dynamotypes’ – with distinct characteristics. “Similar to the periodic table of elements in chemistry, we demonstrated the existence of a clear classification system of seizures”, says Jirsa.

The system could lead clinicians to a better understanding of seizures and how they should be treated. “Seizure types react differently to treatments. For instance, some seizures can be stopped through electric stimulation, others not, dependent on their dynamotype. The systems scientific basis is theory work developed around the Epileptor, a central epilepsy model we developed in the Human Brain Project that is also at the heart of a large clinical trial running now”, the researcher explains.

Classification, however, is not explanation. There is much work ahead of us to better understand epilepsy mechanisms. This is where EBRAINS will play a key role, as it provides the tools connecting cellular, network and brain imaging signals aiding in mechanism discovery. ”

Prof. Viktor Jirsa, HBP-Scientist from Aix-Marseille University

EBRAINS is a new shared digital brain research infrastructure for the European Union that the Human Brain Project (HBP) is building.

Within the HBP, Jirsa and his team had first begun adapting the open network simulator The Virtual Brain towards applications in epilepsy. The work has laid the foundations for project EPINOV (“Improving EPilepsy surgery management and progNOsis using Virtual brain technology”) a multi-year project involving more than a dozen French hospitals that is funded by the French state. EPINOV tests whether the use of the personalized HBP modeling technology for epilepsy networks can improve surgery preparation in drug-resistant patients.

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[NEWS] Novel artificial intelligence algorithm helps detect brain tumor

 

A brain tumor is a mass of abnormal cells that grow in the brain. In 2016 alone, there were 330,000 incident cases of brain cancer and 227,000 related-deaths worldwide. Early detection is crucial to improve patient prognosis, and thanks to a team of researchers, they developed a new imaging technique and artificial intelligence algorithm that can help doctors accurately identify brain tumors.

 

Image Credit: create jobs 51 / Shutterstock.com

Image Credit: create jobs 51 / Shutterstock.com

Published in the journal Nature Medicine, the study reveals a new method that combines modern optical imaging and an artificial intelligence algorithm. The researchers at New York University studied the accuracy of machine learning in producing precise and real-time intraoperative diagnosis of brain tumors.

In the past, the only way to diagnose brain tumors is through hematoxylin and eosin staining of processed tissue in time. Plus, interpretation of the findings relies on pathologists who examine the specimen. The researchers hope the new method will provide a better and more accurate diagnosis, which can help initiate effective treatments right away.

In cancer treatment, the earlier cancer has been diagnosed, the earlier the oncologists can start the treatment. In most cases, early detection improves health outcomes. The researchers have found that their novel method of detection yielded a 94.6 percent accuracy, compared to 93.9 percent for pathology-based interpretation.

The imaging technique

The researchers used a new imaging technique called stimulated Raman histology (SRH), which can reveal tumor infiltration in human tissue. The technique collects scattered laser light and emphasizes features that are not usually seen in many body tissue images.

With the new images, the scientists processed and studied using an artificial intelligence algorithm. Within just two minutes and thirty seconds, the researchers came up with a brain tumor diagnosis. The fast detection of brain cancer can help not only in diagnosing the disease early but also in implementing a fast and effective treatment plan. With cancer caught early, treatments may be more effective in killing cancer cells.

The team also utilized the same technology to accurately identify and remove undetectable tumors that cannot be detected by conventional methods.

“As surgeons, we’re limited to acting on what we can see; this technology allows us to see what would otherwise be invisible, to improve speed and accuracy in the OR, and reduce the risk of misdiagnosis. With this imaging technology, cancer operations are safer and more effective than ever before,” Dr. Daniel A. Orringer, associate professor of Neurosurgery at NYU Grossman School of Medicine, said.

Study results

The study is a walkthrough of various ideas and efforts by the research team. First off, they built the artificial intelligence algorithm by training a deep convolutional neural network (CNN), containing more than 2.5 million samples from 415 patients. The method helped them group and classify tissue samples into 13 categories, representing the most common types of brain tumors, such as meningioma, metastatic tumors, malignant glioma, and lymphoma.

For validation, the researchers recruited 278 patients who are having brain tumor resection or epilepsy surgery at three university medical centers. The tumor samples from the brain were examined and biopsied. The researchers grouped the samples into two groups – control and experimental.

The team assigned the control group to be processed traditionally in a pathology laboratory. The process spans 20 to 30 minutes. On the other hand, the experimental group had been tested and studied intraoperatively, from getting images and processing the examination through CNN.

There were noted errors in both the experimental and control groups but were unique from each other. The new tool can help centers detect and diagnose brain tumors, particularly those without expert neuropathologists.

“SRH will revolutionize the field of neuropathology by improving decision-making during surgery and providing expert-level assessment in the hospitals where trained neuropathologists are not available,” Dr. Matija Snuderl, associate professor in the Department of Pathology at NYU Grossman School of Medicine, explained.

Journal references:

Patel, A., Fisher, J, Nichols, E., et al. (2019). Global, regional, and national burden of brain and other CNS cancer, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology. https://www.thelancet.com/journals/laneur/article/PIIS1474-4422(18)30468-X/fulltext#%20

Hollon, T., Pandian, B, Orringer, D. (2019). Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks. Nature Medicine. https://www.nature.com/articles/s41591-019-0715-9

 

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[WEB SITE] Depression: MedlinePlus

Also called: Clinical depression, Dysthymic disorder, Major depressive disorder, Unipolar depression

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Summary

Depression is a serious medical illness. It’s more than just a feeling of being sad or “blue” for a few days. If you are one of the more than 19 million teens and adults in the United States who have depression, the feelings do not go away. They persist and interfere with your everyday life. Symptoms can include

  • Feeling sad or “empty”
  • Loss of interest in favorite activities
  • Overeating, or not wanting to eat at all
  • Not being able to sleep, or sleeping too much
  • Feeling very tired
  • Feeling hopeless, irritable, anxious, or guilty
  • Aches or pains, headaches, cramps, or digestive problems
  • Thoughts of death or suicide

Depression is a disorder of the brain. There are a variety of causes, including genetic, biological, environmental, and psychological factors. Depression can happen at any age, but it often begins in teens and young adults. It is much more common in women. Women can also get postpartum depression after the birth of a baby. Some people get seasonal affective disorder in the winter. Depression is one part of bipolar disorder.

There are effective treatments for depression, including antidepressants, talk therapy, or both.

NIH: National Institute of Mental Health

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[WEB PAGE] Study reveals three effective treatments to stop epilepsy seizures

 

There are effective treatments to stop life-threatening epilepsy seizures when the initial treatment has failed, a sweeping new study reveals.

The study offers important answers about three such emergency drugs that are used to treat prolonged seizures, known as status epilepticus, even though physicians have had little understanding of the drugs’ effectiveness. Until now, there has been no clear indication of which is best or how much should be given.

The study found that the three drugs – intravenous levetiracetam, fosphenytoin, and valproate – were all about equally effective at stopping the potentially deadly seizures when the default choice, benzodiazepines, proved unable to do so. The results were so clear that the shocked researchers stopped their trial early.

When we planned the study, we didn’t even know if these drugs work 10%, 25% or 50% of the time. So the big, big takeaway is that each of these drugs works about 45 percent of the time. And this is an important finding because it tells us patients can get better. They don’t have to be placed on a on a ventilator [breathing machine].”

Jaideep Kapur, MBBS, PhD, investigator and the head of the University of Virginia Brain Institute

Effect on Clinical Practice

The study’s findings, published in the prestigious New England Journal of Medicine, both affirm existing clinical practices and suggest a major change.

Doctors can feel confident that their preferred drug of choice is as effective as the other options, Kapur noted, but they also should significantly increase how much levetiracetam they give when they choose it.

“Prior to this, people were using their best guess as to which drug to use and how much of it to use. And this puts those things to rest and tells you exactly how much of which to use, and what to expect,” said Kapur, of the UVA School of Medicine’s Department of Neurology.

The trial organizers tested the maximum safe dose of each of the drugs so there would be no question whether too little had been used to gauge the medicine’s effectiveness. In so doing, they gave twice as much levetiracetam as many doctors administer.

“When I started 25 years ago, there was not a single scientifically proven drug [for status epilepticus]. We didn’t know which drug to use, even for the first-line treatment, and how much of them to use,” Kapur said. “And 25 years later, we can treat more than 80% of the patients – 85% of the patients – using scientifically proven drugs. 85% of our patients will get better, will stop having seizures and start waking up. That is the effect of scientific research on improving care of patients, and this is real.”

About the Epilepsy Seizure Trial

The randomized, double-blinded trial looked at the effect of the drugs in 384 patients at 57 emergency departments in the United States between November 2015 and the end of October 2017.

The researchers originally planned to study 795 patients over five years, but the results were so clear that was deemed unnecessary. “Clinical trials are notorious for going over long and over budget, and we came in under budget,” Kapur said.

That was possible, he said, because of the participation of many top experts in both the United States and Europe. Participating sites included the University of Michigan, Medical University of South Carolina, UVA, Children’s National Medical Center in Washington, D.C., and many more.

“It was an amazingly accomplished group of people,” Kapur said. “We had the best experts from all over the United States and Europe. For me, it’s been a great joy working with the team as the leader of the Brain Institute. That’s the spirit I want to bring to UVA. That’s really what motivated me to start the Brain Institute: to fashion these teams within UVA, so that we can do really significant, societally impactful research.”

UVA Emergency Medicine physician Stephen Huff, MD, led the study at the UVA site, which enrolled seven subjects. Amy Fansler, Emily Gray and Lea Becker helped organize the study.

Kapur expressed his gratitute to all the patients who participated in the study. “President Ryan [UVA President Jim Ryan] has said we must be great and good,” Kapur said, “and this is the kind of good we want to do.”

Next Steps

The researchers are now looking more closely at the drugs’ effectiveness and dosing in children. That will offer important information on how best to treat the young patients, as the causes of status epilepticus in adults and children often differ.

 

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[WEB SITE] Traumatic brain injuries could be healed using peptide hydrogels

Traumatic brain injury (TBI) –– defined as a bump, blow or jolt to the head that disrupts normal brain function –– sent 2.5 million people in the U.S. to the emergency room in 2014, according to statistics from the U.S. Centers for Disease Control and Prevention. Today, researchers report a self-assembling peptide hydrogel that, when injected into the brains of rats with TBI, increased blood vessel regrowth and neuronal survival.

The researchers will present their results at the American Chemical Society (ACS) Fall 2019 National Meeting & Exposition. ACS, the world’s largest scientific society, is holding the meeting here through Thursday. It features more than 9,500 presentations on a wide range of science topics.

“When we think about traumatic brain injuries, we think of soldiers and athletes,” says Biplab Sarkar, Ph.D., who is presenting the work at the meeting. “But most TBIs actually happen when people fall or are involved in motor vehicle accidents. As the average age of the country continues to rise, the number of fall-related accidents in particular will also increase.”

TBIs encompass two types of injuries. Primary injury results from the initial mechanical damage to neurons and other cells in the brain, as well as blood vessels. Secondary injuries, which can occur seconds after the TBI and last for years, include oxidative stress, inflammation and disruption of the blood-brain barrier. “The secondary injury creates this neurotoxic environment that can lead to long-term cognitive effects,” Sarkar says. For example, TBI survivors can experience impaired motor control and an increased rate of depression, he says. Currently, there is no effective regenerative treatment for TBIs.

Sarkar and Vivek Kumar, Ph.D., the project’s principal investigator, wanted to develop a therapy that could help treat secondary injuries.

We wanted to be able to regrow new blood vessels in the area to restore oxygen exchange, which is reduced in patients with a TBI. Also, we wanted to create an environment where neurons can be supported and even thrive.”

Biplab Sarkar, Ph.D., New Jersey Institute of Technology

The researchers, both at the New Jersey Institute of Technology, had previously developed peptides that can self-assemble into hydrogels when injected into rodents. By incorporating snippets of particular protein sequences into the peptides, the team can give them different functions. For example, Sarkar and Kumar previously developed angiogenic peptide hydrogels that grow new blood vessels when injected under the skin of mice.

To adapt their technology to the brain, Sarkar and Kumar modified the peptide sequences to make the material properties of the hydrogel more closely resemble those of brain tissue, which is softer than most other tissues of the body. They also attached a sequence from a neuroprotective protein called ependymin. The researchers tested the new peptide hydrogel in a rat model of TBI. When injected at the injury site, the peptides self-assembled into a hydrogel that acted as a neuroprotective niche to which neurons could attach.

A week after injecting the hydrogel, the team examined the rats’ brains. They found that in the presence of the hydrogel, survival of the brain cells dramatically improved, resulting in about twice as many neurons at the injury site in treated rats than in control animals with brain injury. In addition, the researchers saw signs of new blood vessel formation. “We saw some indications that the rats in the treated group were more ambulatory than those in the control group, but we need to do more experiments to actually quantify that,” Sarkar says.

According to Kumar, one of the next steps will be to study the behavior of the treated animals to assess their functional recovery from TBI. The researchers are also interested in treating rats with a combination of their previous angiogenic peptide and their new neurogenic version to see if this could enhance recovery. And finally, they plan to find out if the peptide hydrogels work for more diffuse brain injuries, such as concussions. “We’ve seen that we can inject these materials into a defined injury and get good tissue regeneration, but we’re also collaborating with different groups to find out if it could help with the types of injuries we see in soldiers, veterans and even people working at construction sites who experience blast injuries,” Kumar says.

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[WEB SITE] AI helps identify patients in need of advanced care for depression

Depression is a worldwide health predicament, affecting more than 300 million adults. It is considered the leading cause of disability and contributor to the overall global burden of disease. Detecting people in need of advanced depression care is crucial.

Now, a team of researchers at the Regenstrief Institute found a way to help clinicians detect and identify patients in need of advanced care for depression. The new method, which uses machine learning or artificial intelligence (AI), can help reduce the number of people who experience depressive symptoms that could potentially lead to suicide.

The World Health Organization (WHO) reports that close to 800,000 people die due to suicide each year, making it the leading cause of death among people between the ages of 15 and 29 years old.

Major depression is one of the most common mental illness worldwide. In the United States, an estimated 17.3 million adults had at least one major depressive episode, accounting to about 7.1 percent of all adults in the country.

Image Credit: Zapp2Photo / Shutterstock

Image Credit: Zapp2Photo / Shutterstock

Predicting patients who need treatment

The study, which was published in the Journal of Medical Internet Research, unveils a new way to determine patients who might need advanced care for depression. The decision model can predict who might need more treatment than what the primary care provider can offer.

Since some forms of depression are far more severe and need advanced care by certified medical health providers, knowing who is at risk is essential. But identifying these patients is very challenging. In line with this, the researchers formulated a method that scrutinizes a comprehensive range of patient-level diagnostic, behavioral, and demographic data, including past clinic visit history from a statewide health information.

Using the data, health care providers can now build a technique on properly predicting patients in need of advanced care. The machine learning algorithm combined both behavioral and clinical data from the statewide health information exchange, called the Indiana Network for Patient Care.

“Our goal was to build reproducible models that fit into clinical workflows,” Dr. Suranga N. Kasthurirathne, a research scientist at Regenstrief Institute, and study author said.

“This algorithm is unique because it provides actionable information to clinicians, helping them to identify which patients may be more at risk for adverse events from depression,” he added.

The researchers used the new model to train random forest decision models that can predict if there’s a need for advanced care among the overall patient population and those at higher risk of depression-related adverse events.

It’s important to consider making models that can fit different patient populations. This way, the health care provider has the option to choose the best screening approach he or she needs.

“We demonstrated the ability to predict the need for advanced care for depression across various patient populations with considerable predictive performance. These efforts can easily be integrated into existing hospital workflows,” the investigators wrote in the paper.

Identifying patients in need of advanced care is important

With the high number of people who have depression, one of the most important things to do is determine who are at a higher risk of potential adverse effects, including suicide.

Depression has different types, depending on the level of risk involved. For instance, people with mild depression forms may not need assistance and can recover faster. On the other hand, those who have severe depression may require advanced care aside from what primary care providers can offer.

They may need to undergo treatment such as medications and therapies to improve their condition. Hence, the new method can act like a preventive measure to reduce the incidence of adverse events related to the condition such as suicide.

More importantly, training health care teams to successfully identify patients with severe depression can help resolve the problem. With the proper application of the novel technique, many people with depression can be treated accordingly, reducing serious complications.

Depression signs and symptoms

Health care providers need to properly identify patients with depression. The common signs and symptoms of depression include feelings of hopelessness and helplessness, loss of interest in daily activities, sleep changes, irritability, anger, appetite changes, weight changes, self-loathing, loss of energy, problems in concentrating, reckless behavior, memory problems, and unexplained pains and aches.


Journal reference:

Suranga N Kasthurirathne, Paul G Biondich, Shaun J Grannis, Saptarshi Purkayastha, Joshua R Vest, Josette F Jones. (2019). Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach. Journal of Medical Internet Research. https://www.jmir.org/2019/7/e13809/


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[NEWS] New Virtual Reality Therapy game could offer relief for patients with chronic pain, mobility issues

News-MedicalA Virtual Reality Therapy game (iVRT) which could introduce relief for patients suffering from chronic pain and mobility issues has been developed by a team of UK researchers.

Dr Andrew Wilson and colleagues from Birmingham City University built the CRPS app in collaboration with clinical staff at Sandwell and West Birmingham Hospitals NHS Trust for a new way to tackle complex regional pain syndrome and to aid people living with musculoskeletal conditions.

Using a head mounted display and controllers, the team created an immersive and interactive game which mimics the processes used in traditional ‘mirror therapy’ treatment. Within the game, players are consciously and subconsciously encouraged to stretch, move and position the limbs that are affected by their conditions.

Mirror therapy is a medical exercise intervention where a mirror is used to create areflective illusion that encourages patient’s brain to move their limb more freely. This intervention is often used by occupational therapists and physiotherapists to treat CRPS patients who have experienced a stroke. This treatment has proven to be successful exercises are often deemed routine and mundane by patients, which contributes to decline in the completion of therapy.

Work around the CRPS project, which could have major implications for other patient rehabilitation programmes worldwide when fully realised, was presented at the 12th European Conference on Game Based Learning (ECGBL) in France late last year.

Dr Wilson, who leads Birmingham City University’s contribution to a European research study into how virtual reality games can encourage more physical activity, and how movement science in virtual worlds can be used for both rehabilitation and treatment adherence, explained, “The first part of the CRPS project was to examine the feasibility of being able to create a game which reflects the rehabilitation exercises that the clinical teams use on the ground to reduce pain and improve mobility in specific patients.”

“By making the game enjoyable and playable we hope family members will play too and in doing so encourage the patient to continue with their rehabilitation. Our early research has shown that in healthy volunteers both regular and casual gamers enjoyed the game which is promising in terms of our theory surrounding how we may support treatment adherence by exploiting involvement of family and friends in the therapy processes.”

The CRPS project was realized through collaborative working between City Hospital, Birmingham, and staff at the School of Computing and Digital Technology, and was developed following research around the provision of a 3D virtual reality ophthalmoscopy trainer.

Andrea Quadling, Senior Occupational Therapist at Sandwell Hospital, said “The concept of using virtual reality to treat complex pain conditions is exciting, appealing and shows a lot of potential. This software has the potential to be very helpful in offering additional treatment options for people who suffer with CRPS.”

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[WEB SITE] Researchers study how neurostimulator can improve rehabilitation for stroke patients

 

Researchers at The Ohio State University Wexner Medical Center are among the first in the world studying how a specific type of neurostimulator can improve rehabilitation for stroke patients.

As part of the clinical trial, an electrical device called a vagus nerve stimulator is surgically implanted in the patient’s chest wall. The Vivistim device, which connects to the vagus nerve in the neck, is used to “rewire” circuits in the brain associated with certain motor functions. Stroke can result in the loss of brain tissue and negatively affect various bodily functions from speech to movement, depending on the location of the stroke.

In an earlier pilot study, this approach known as Paired Vagus Nerve Stimulation was shown to benefit approximately 85 percent of the people who received the nerve stimulation, said Dr. Marcie Bockbrader, research physiatrist for the Neurological Institute at The Ohio State University Wexner Medical Center.

“This nerve stimulation is like turning on a switch, making the patient’s brain more receptive to therapy,” Bockbrader said. “The goal is to see if we can improve motor recovery in people who have what is, in effect, a brain pacemaker implanted in their body. The idea is to combine this brain pacing with normal rehab, and see if patients who’ve been through all of the other usual therapies after a stroke can get even better.”

The study is recruiting patients who suffered a stroke and have been left with poor arm function as a result. The study is open to patients who have suffered a stroke at least nine months ago up to 10 years ago.


Each participant will receive three one-hour sessions of intensive physiotherapy each week for six weeks to help improve their arm function.

Half of the group will also receive an implanted vagus nerve stimulator. During rehabilitation therapy sessions, when a patient correctly performs an exercise, the therapist pushes a button to trigger the device to stimulate the vagus nerve. This neurostimulator signals the brain to remember that movement.

“We are trying to see if this neurostimulator could be used to boost the effective therapy, creating a sort of ‘supercharged therapy.’ We want to determine if patients can recover more quickly through the use of this stimulation,” Bockbrader said.

Previous research indicates that vagus nerve stimulation causes the release of the brain’s own chemicals, called neurotransmitters that will help the brain form new neural connections which might improve participant’s ability to use their arm.

Traditional vagus nerve stimulation has been used in the United States and around the world to treat more than 100,000 patients for epilepsy.

 

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[WEB SITE] Researchers demonstrate synaptic plasticity in new-born neurons

Repeated stimulation enlarges dendritic spines

Even in adult brains, new neurons are generated throughout a lifetime. In a publication in the scientific journal PNAS, a research group led by Goethe University describes plastic changes of adult-born neurons in the hippocampus, a critical region for learning: frequent nerve signals enlarge the spines on neuronal dendrites, which in turn enables contact with the existing neural network.

Practice makes perfect, and constant repetition promotes the ability to remember. Researchers have been aware for some time that repeated electrical stimulation strengthens neuron connections (synapses) in the brain. It is similar to the way a frequently used trail gradually widens into a path. Conversely, if rarely used, synapses can also be removed – for example, when the vocabulary of a foreign language is forgotten after leaving school because it is no longer practiced. Researchers designate the ability to change interconnections permanently and as needed as the plasticity of the brain.

Plasticity is especially important in the hippocampus, a primary region associated with long-term memory, in which new neurons are formed throughout life. The research groups led by Dr Stephan Schwarzacher (Goethe University), Professor Peter Jedlicka (Goethe University and Justus Liebig University in Gieβen) and Dr Hermann Cuntz (FIAS, Frankfurt) therefore studied the long-term plasticity of synapses in new-born hippocampal granule cells. Synaptic interconnections between neurons are predominantly anchored on small thorny protrusions on the dendrites called spines. The dendrites of most neurons are covered with these spines, similar to the thorns on a rose stem.

In their recently published work, the scientists were able to demonstrate for the first time that synaptic plasticity in new-born neurons is connected to long-term structural changes in the dendritic spines: repeated electrical stimulation strengthens the synapses by enlarging their spines. A particularly surprising observation was that the overall size and number of spines did not change: when the stimulation strengthened a group of synapses, and their dendritic spines enlarged, a different group of synapses that were not being stimulated simultaneously became weaker and their dendritic spines shrank.

“This observation was only technically possible because our students Tassilo Jungenitz and Marcel Beining succeeded for the first time in examining plastic changes in stimulated and non-stimulated dendritic spines within individual new-born cells using 2-photon microscopy and viral labeling,” says Stephan Schwarzacher from the Institute for Anatomy at the University Hospital Frankfurt. Peter Jedlicka adds: “The enlargement of stimulated synapses and the shrinking of non-stimulated synapses was at equilibrium. Our computer models predict that this is important for maintaining neuron activity and ensuring their survival.”

The scientists now want to study the impenetrable, spiny forest of new-born neuron dendrites in detail. They hope to better understand how the equilibrated changes in dendritic spines and their synapses contribute the efficient storing of information and consequently to learning processes in the hippocampus.

 

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