Posts tagged psychology

ScienceDaily (Apr. 17, 2012) — At a time when obesity has become epidemic in American society, Dartmouth scientists have found that functional magnetic resonance imaging (fMRI) brain scans may be able to predict weight gain. In a study published April 18, 2012, in The Journal of Neuroscience, the researchers demonstrated a connection between fMRI brain responses to appetite-driven cues and future behavior.

Raspberry cheesecake. The people whose brains responded more strongly to food cues were the people who went on to gain more weight six months later, researchers said. (Credit: © JJAVA / Fotolia)

"This is one of the first studies in brain imaging that uses the responses observed in the scanner to predict important, real-world outcomes over a long period of time," says Todd Heatherton, the Lincoln Filene Professor in Human Relations in the department of psychological and brain sciences and a coauthor on the study. "Using brain activity to predict a consequential behavior outside the scanner is pretty novel."

Using fMRI, the researchers targeted a region of the brain known as the nucleus accumbens, often referred to as the brain’s “reward center,” in a group of incoming first-year college students. While undergoing scans, the subjects viewed images of animals, environmental scenes, appetizing food items, and people. Six months later, their weight and responses to questionnaires regarding interim sexual behavior were compared with their previously recorded weight and brain scan data.

"The people whose brains responded more strongly to food cues were the people who went on to gain more weight six months later," explains Kathryn Demos, first author on the paper. Demos, who conducted the research as part of her doctoral dissertation at Dartmouth, is currently on the research faculty at the Warren Alpert Medical School of Brown University.

The correlation between strong food image brain responses and weight gain was also present for sexual images and activity. “Just as cue reactivity to food images was investigated as potential predictors of weight gain, cue reactivity to sexual images was used to predict sexual desire,” the authors report.

The paper stresses “material specificity,” noting that the participants who responded to food images gained weight but did not engage in more sexual behavior, and vice versa. The authors go on to say that none of the non-food images predicted weight gain.

Heatherton and William Kelley, associate professor of psychological and brain science and a senior author on the paper, have a longstanding interest in psychological theories of self-regulation, also called self-control or willpower.

"We seek to understand situations in which people face temptations and try to not act on them," says Kelley.

The researchers note that the first step toward controlling cravings may be an awareness of how much you are affected by specific triggers in the environment, such as the arrival of the dessert tray in a restaurant.

"You need to actively be thinking about the behavior you want to control in order to regulate it," remarks Kelley. "Self-regulation requires a lot of conscious effort."

Source: Science Daily

ScienceDaily (Apr. 17, 2012) — Last year, researchers from the Perelman School of Medicine at the University of Pennsylvania found that small amounts of a misfolded brain protein can be taken up by healthy neurons, replicating within them to cause neurodegeneration. The protein, alpha-synuclein (a-syn), is commonly found in the brain, but forms characteristic clumps called Lewy bodies, in neurons of patients with Parkinson’s disease (PD) and other neurodegenerative disorders. They found that abnormal forms of a-syn called fibrils acted as “seeds” that induced normal a-syn to misfold and form aggregates.

These images show the brainstem from a control animal (top) and an animal injected with pathologic alpha-synuclein. Brown spots are immunostaining using an antibody specifically recognizing an abnormal form of alpha-synuclein. (Credit: Kelvin C. Luk, Ph.D., Perelman School of Medicine, University of Pennsylvania.)

In earlier studies at other institutions, when fetal nerve cells were transplanted into the brains of PD patients, some of the transplanted cells developed Lewy bodies. This suggested that the corrupted form of a-syn could somehow be transmitted from diseased neurons to healthy ones.

Now, in a follow-up study published in the Journal of Experimental Medicine, the team, led by senior author Virginia M.-Y Lee, PhD, director of the Center for Neurodegenerative Disease Research and professor of Pathology and Laboratory Medicine, showed that brain tissue from a PD mouse model, as well as synthetically produced a-syn fibrils, injected into young, symptom-free PD mice led to spreading of a-syn pathology. By three months after a single injection, neurons containing abnormal a-syn clumps were detected throughout the mouse brains. The inoculated mice died between 100 to 125 days post-inoculation, out of their typical two-year life span.

"We think the spreading is via white-matter tracks through brain neural network connections," explains Lee. "This study will open new opportunities for novel Parkinson’s disease therapies."

One of the remaining questions is how, once inside a neuron, does the misfolded a-syn protein spread from cell to cell.

"It’s like a biochemical chain reaction," says first author Kelvin C. Luk, Ph.D., research associate, in the CNDR. Once inside the confines of a neuron, the misfolded a-syn recruits normally shaped a-syn protein that is present in the cell, causing them to eventually misfold. This occurs along the axons and dendrites (neuronal extensions that reach other neurons), leading to a dramatic accumulation of the abnormal protein. The misshapen a-syn then invades other neurons when they reach the synapse, the small space between neurons.

This transmission process is remarkably similar to what is seen in prions, the protein agents responsible for conditions such as transmissible spongiform encephalopathies ( mad cow disease). However, the researchers are quick to caution that there is no evidence that Parkinson’s or any related neurodegenerative diseases is either infectious or acquired.

The accumulation of misfolded proteins is a fundamental pathogenic process in neurodegenerative diseases, but the factors that trigger aggregation of a-syn are poorly understood.

The Penn team saw that misfolded a-syn propagated along major central nervous system pathways, reaching regions far beyond injection sites. What’s more, they showed for the first time that synthetically produced a-syn fibrils are sufficient to initiate a vicious cycle of Lewy body formation and transmission of the misfolded a-syn in mice.

The study demonstrates just how the Parkinson’s disease protein can spread in a patient’s brain in terms of uptake into a healthy neuron, expansion within the cell, and finally release to a neighboring neuron.

"Knowing this mechanism allows for possible immunotherapies to interrupt the chain reaction by stopping the mutant protein from spreading at the synapse," says Lee.

"Shedding light on how a-synuclein contributes to Parkinson’s disease and related Lewy body disorders is of significant interest both for understanding these diseases and developing potential treatments," said Beth-Anne Sieber, Ph.D., of the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health. "This study provides evidence for the progressive, pathological spread of a-synuclein through the brain."

Source: Science Daily

April 13th, 2012
By Kay H. Brodersen 

Researchers at ETH Zurich and the University of Zurich identify a new method of unerringly detecting the presence of pathophysiological changes in the brain.

Brain model (left) depicting brain activity stimulated by speech processing (yellow). The new method allows for the mathematical modeling of interactions between regions within the brain (right). The prism represents the transition or “Generative Embedding.” Image adapted from pr image by Brodersen KH/ ETH Zurich.

The new method was developed in order to gain a mechanistic understanding of schizophrenia and other spectrum disorders, which will lead to more accurate diagnoses and more effective treatments.

When mathematical genius John Nash was diagnosed with schizophrenia, the chance for recovery was slim. Medicine in the 1960’s simply had no convincing explanations for his condition. Alarmingly, things don’t look much better nowadays: depression, addiction, schizophrenia, and other spectrum disorders remain among the toughest challenges for medicine. This is because they are caused by complicated and largely unknown interactions between genes and the environment. Different disease mechanisms may underlie similar, or even identical, symptoms. This means that the effect of any given drug may vary hugely across individuals, resulting in trial-and-error treatment. In addition, conditions whose biological basis is not well-understood may be perceived as particularly stigmatizing.

Most spectrum disorders lack a physiological definition altogether; they are simply described in terms of particular symptoms. This is problematic when these symptoms are caused by different disease mechanisms. Conversely, existing disease classifications frequently group patients with disjoint symptoms under the same label: a person with delusions and disorganized thought, for instance, can be diagnosed with schizophrenia, just as somebody else suffering from hallucinations and movement problems. Examples such as this one show that the development of more specific diagnoses and more effective treatment will require a mechanistic understanding of the pathophysiological mechanisms underlying spectrum disorders.

One step in this direction has recently been made by Kay Henning Brodersen and Klaas Enno Stephan at ETH Zurich and the University of Zurich. Within the framework of the SystemsX.ch project ‘Neurochoice’, the two researchers investigate how insights gained from mathematical models of decision making and underlying brain function can be translated into clinical applications. “Put simply, we develop ‘mathematical microscopes’ that allow us to estimate physiological or computational quantities that cannot be measured directly,” says Klaas Enno Stephan, director of the newly founded Translational Neuromodeling Unit (TNU) in Zurich. “This allows us to obtain more accurate classifications and gain deeper mechanistic insights into the underlying condition than previous attempts.”

To demonstrate the plausibility of their idea, the two scientists collaborated with a clinical team led by Alex Leff at University College London. They analysed brain activity from two groups of participants: one group of stroke patients that suffered from language impairments; and one group of healthy volunteers. While undergoing functional magnetic resonance imaging (fMRI), participants were asked to passively listen to speech. A mathematical model was then used to assess, separately within each participant, how brain regions involved in speech processing interacted. Notably, none of the brain regions included in the model had been affected by the stroke in the patients.

The researchers then asked whether it was possible to automatically detect the presence of a remote lesion from patterns of brain connectivity in the healthy part of the brain. “Using our model of brain function, we were able to diagnose patients with an accuracy of 98%,” says Brodersen, first author of the study. “This became possible by tying together dynamic causal models of neuronal dynamics with mathematical techniques from machine learning and Bayesian inference.” In contrast to subtle spectrum disorders, of course, this initial proof-of-principle study concerned a rather salient clinical condition, that is, language impairments caused by a stroke. In the future, Stephan and Brodersen therefore plan to investigate whether their approach might work equally well for those diseases where contemporary medicine is struggling, such as schizophrenia, depression, and addiction. The two researchers hope that their approach will help dissect these spectrum disorders into pathophysiologically well-defined subgroups. Identifying such subgroups would provide an important step towards more specific diagnoses and may eventually predict the most effective treatment for an individual patient.

Source: Neuroscience News

April 11, 2012

A vast majority of cells in the brain are glial, yet our understanding of how they are generated, a process called gliogenesis, has remained enigmatic. Researchers at Baylor College of Medicine have identified a novel transcripitonal cascade that controls these formative stages of gliogenesis and answered the longstanding question of how glial cells are generated from neural stem cells.

The findings appear in the current edition of Neuron.

"Most people are familiar with neurons, cells that process and transmit information in the brain. Glial cells, on the other hand, make-up about 80 percent of the cells in the brain and function by providing trophic support to neruons, participating in neurotransmission, myelin sheaths for axons, and comprise the blood brain barrier," said Dr. Benjamin Deneen, assistant professor of neuroscience at BCM. "Importantly, glia have been linked to numerous CNS pathologies, from brain tumors and spinal cord injury and several neurological disorders including, Retts Syndrome, ALS, and Multiple Sclerosis. Therefore deciphering how glial cells are generated is key to understanding brain function during health and disease."

As researchers began investigating glial development in chicks they started by going backwards – examing what steps were needed before the glial cells matured. They discovered that glial cells are specified in neural stem cells when the transcription factor NFIA is induced.

Taking another step back in the transcriptional cascade, they looked for what triggered NFIA induction.

"By comparing mouse and chick regulatory sequences we were able to perform enhancer screening in the chick to identify regulatory elements with activity that resembled NFIA induction. This method allowed us to pinpoint Sox9," said Peng Kang, postdoctoral associate in the Center for Stem Cell and Regenerative Medicine at BCM. "Subsequently, we found that Sox9 doesn’t just induce NFIA expression, it also associates with NFIA, forming a complex."

Just after the initiation of gliogenesis this complex was discovered to co-regulate a subset of genes that play important roles in mitochondria energy metabolism and glial precursor migration.

"Sox9 induces NFIA expression during glial initiation and then binds NFIA to drive lineage progression by cooperatively regulating a genetic program that controls cell migration and energy metabolism, two key processes associated with cellular differentiation," said Deneen. "We now need to ask what other proteins contribute to this process, and how does the nature of this complex evolve during astro-glial lineage progression."

Additionally, these findings may also help researchers to understand how certain brain tumors might begin to form, as these same developmental processes and proteins are found in both adult and pediatric brain tumors. A more comprehensive understanding how this regulatory cascade operates during development, could eventually lead to better treatment targets for brain tumors.

Provided by Baylor College of Medicine

Source: medicalxpress.com

April 11, 2012

No matter what novel objects we come to behold, our brains effortlessly take us from an initial “What’s that?” to “Oh, that old thing” after a few casual encounters. In research that helps shed light on the malleability of this recognition process, Brown University neuroscientists have teased apart the potentially different roles that two distinct cell types may play.

In a study published in the journal Neuron, the researchers document that this kind of learning is based in the inferior temporal cortex (ITC), a brain area buried deep in the skull. Scientists already knew the area was important for visual recognition of familiar items, but they hadn’t figured out the steps required to move from novelty to familiarity, a process they refer to as “plasticity.”

"We know little about that because of the level at which this plasticity is taking place," said senior author David Sheinberg, professor of neuroscience and a member of the Brown Institute for Brain Science. "The inner workings made up of individual neurons make it very hard to actually track what’s going on at that level."

Working with two monkeys, in whom they monitored single neuron activity using tiny microelectrodes, Sheinberg and graduate student Luke Woloszyn tracked the firing patterns of individual neurons in the ITC while monkeys viewed 125 objects they had been trained to recognize and 125 others that they had never seen before.

The scientists found that the two major classes of cells found in the brain, excitatory and inhibitory, responded differently depending on what the monkeys saw. Excitatory neurons were especially active when the monkeys saw a preferred familiar object — the familiar image, out of the 125 such images, that the cell “liked” best. Although the particular preferred familiar image varied across the sample of neurons, almost every excitatory cell had at least one familiar image to which it responded more robustly than its preferred novel image, Sheinberg said. Inhibitory neurons, meanwhile, were much more active when the monkeys saw any novel image, independent of the object’s actual identity. 

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April 10, 2012

Scientists report that they have mapped the physical architecture of intelligence in the brain. Theirs is one of the largest and most comprehensive analyses so far of the brain structures vital to general intelligence and to specific aspects of intellectual functioning, such as verbal comprehension and working memory.

A new study found that specific structures, primarily on the left side of the brain, are vital to general intelligence and executive function (the ability to regulate and control behavior). Brain regions that are associated with general intelligence and executive function are shown in color, with red indicating common areas, orange indicating regions specific to general intelligence, and yellow indicating areas specific to executive function. Credit: Aron Barbey

Their study, published in Brain: A Journal of Neurology, is unique in that it enlisted an extraordinary pool of volunteer participants: 182 Vietnam veterans with highly localized brain damage from penetrating head injuries.

"It’s a significant challenge to find patients (for research) who have brain damage, and even further, it’s very hard to find patients who have focal brain damage," said University of Illinois neuroscience professor Aron Barbey, who led the study. Brain damage – from stroke, for example – often impairs multiple brain areas, he said, complicating the task of identifying the cognitive contributions of specific brain structures.

But the very focal brain injuries analyzed in the study allowed the researchers “to draw inferences about how specific brain structures are necessary for performance,” Barbey said. “By studying how damage to particular brain regions produces specific forms of cognitive impairment, we can map the architecture of the mind, identifying brain structures that are critically important for specific intellectual abilities.”

The researchers took CT scans of the participants’ brains and administered an extensive battery of cognitive tests. They pooled the CT data to produce a collective map of the cortex, which they divided into more than 3,000 three-dimensional units called voxels. By analyzing multiple patients with damage to a particular voxel or cluster of voxels and comparing their cognitive abilities with those of patients in whom the same structures were intact, the researchers were able to identify brain regions essential to specific cognitive functions, and those structures that contribute significantly to intelligence.

"We found that general intelligence depends on a remarkably circumscribed neural system," Barbey said. "Several brain regions, and the connections between them, were most important for general intelligence."

These structures are located primarily within the left prefrontal cortex (behind the forehead), left temporal cortex (behind the ear) and left parietal cortex (at the top rear of the head) and in “white matter association tracts” that connect them. (Watch a video about the findings.)

The researchers also found that brain regions for planning, self-control and other aspects of executive function overlap to a significant extent with regions vital to general intelligence.

The study provides new evidence that intelligence relies not on one brain region or even the brain as a whole, Barbey said, but involves specific brain areas working together in a coordinated fashion.

"In fact, the particular regions and connections we found support an emerging body of neuroscience evidence indicating that intelligence depends on the brain’s ability to integrate information from verbal, visual, spatial and executive processes," he said.

The findings will “open the door to further investigations into the biological basis of intelligence, exploring how the brain, genes, nutrition and the environment together interact to shape the development and continued evolution of the remarkable intellectual abilities that make us human,” Barbey said.

Provided by University of Illinois at Urbana-Champaign

Source: medicalxpress.com

April 9, 2012 by Stuart Mason Dambrot      

(Medical Xpress) — The link between dreaming and rapid eye movement (REM) sleep are well understood – but the fact that consciousness is reduced during nonrapid eye movement (NREM) sleep is not. Recently, scientists in the Cyclotron Research Centre at the University of Liège, in Liège, Belgium, and the Institut National de la Santé et de la Recherche Médicale at the Université Pierre et Marie Curie in Paris, and the Functional Neuroimaging Unit at the Montreal Geriatrics Institute, investigated NREM sleep with the hypothesis that this phenomenon is associated with increased modularity of the brain’s functional activity during these periods. Using functional clustering – which estimates how integration is hierarchically organized within and across the constituent parts of a system they found that while in NREM sleep, hierarchically-organized large-scale neural networks were disaggregated into smaller independent modules. The researchers concluded that this difference could reduce the ability of the brain to integrate information, thereby accounting for the decreased consciousness experienced during NREM sleep.

(A) The six networks extracted during wakefulness. (B) Levels of brain hierarchical integration. (C) Increases in functional clustering ratio in the brain and the six networks (all significant with a probability >0.95). Networks: dATT, dorsal attentional; DM, default mode; EC, executive control; MOT, sensorimotor; SAL, salience; VIS, visual. Copyright © PNAS, doi: 10.1073/pnas.111113310

Led by Pierre Maquet at the Cyclotron Research Centre and Habib Benali at the Institut National de la Santé et de la Recherche Médicale, the team faced a fundamental challenge in framing their research. Maquet first notes that there is currently no consensus on what consciousness really is, let alone how it arises.

“For many years,” he explains to Medical Xpress, “Giulio Tononi put forward the hypothesis that consciousness is related to the ability of the brain to integrate information. Our objective was simply to test this hypothesis, using novel tools allowing for the computation of information exchange within the brain and a set of EEG/fMRI data recorded in the same individuals during wakefulness and deep NREM sleep.” The latter state, he adds, is arguably the condition associated with the most reduce conscious content in normal human volunteers.

Maquet notes that the team used methods devised by Benali. “These allow us to measure the hierarchical organization of integration – i.e., information. The data itself,” he continues, “were acquired in Liège. Conducting simultaneous EEG/fMRI recordings in sleeping volunteers is not that easy.” Moreover, he notes, in practice, their findings are only one small step toward a better understanding of consciousness – and, for that matter, unconsciousness.

“The results were rather unexpected in that the amount of information exchanged in the brain actually increased during sleep. However, the patterns of exchange between regions were different than during wakefulness. Essentially, there was an increased information exchange within small clusters of mainly homologous brain areas whereas communication between clusters significantly decreased during sleep.” Thus, he points out, the data support their hypothesis.

The team has already defined the next steps in their research, says Maquet, who acknowledges that fMRI suffers from a rather sluggish signal. “The next step is to apply the methods to EEG, which has a much better time resolution.” He also states that it might it be possible to transition to in silico modeling, and that there are attempts in this direction in some laboratories.

A key advantage of the team’s approach was relying on functional clustering rather than so-called total integration in neural network analysis. “This is a big question,” states Maquet. “We don’t know what is the information exchanged within clusters, and I don’t see any technique that could currently answer this question in humans. More generally,” he adds, “it is thought that NREM sleep is regulated by the homeostasis of synaptic strength, and perhaps by neuronal energy metabolism.” These assumptions, he concludes, are being studied in animal models.

Source: medicalxpress.com

April 5th, 2012

Discovery of key link between circadian rhythms and metabolism may lead to new therapies for sleep disorders and diabetes.

The discovery of a major gear in the biological clock that tells the body when to sleep and metabolize food may lead to new drugs to treat sleep problems and metabolic disorders, including diabetes.

Scientists at the Salk Institute for Biological Studies, led by Ronald M. Evans, a professor in Salk’s Gene Expression Laboratory, showed that two cellular switches found on the nucleus of mouse cells, known as REV-ERB-α and REV-ERB-β, are essential for maintaining normal sleeping and eating cycles and for metabolism of nutrients from food.

The findings, reported March 29 in Nature, describe a powerful link between circadian rhythms and metabolism and suggest a new avenue for treating disorders of both systems, including jet lag, sleep disorders, obesity and diabetes.

“This fundamentally changes our knowledge about the workings of the circadian clock and how it orchestrates our sleep-wake cycles, when we eat and even the times our bodies metabolize nutrients,” says Evans. “Nuclear receptors can be targeted with drugs, which suggests we might be able to target REV-ERB-α and β to treat disorders of sleep and metabolism.”

Nurses, emergency personnel and others who work shifts that alter the normal 24-hour cycle of waking and sleeping are at much higher risk for a number of diseases, including metabolic disorders such as diabetes. To address this, scientists are trying to understand precisely how the biological clock works and uncover possible targets for drugs that could adjust the circadian rhythm in people with sleep disorders and circadian-associated metabolic disorders.

In mammals, the circadian timing system is orchestrated by a central clock in the brain and subsidiary clocks in most other organs. The master clock in the brain is set by light and determines the overall diurnal or nocturnal preference of an animal, including sleep-wake cycles and feeding behavior.

Scientists knew that two genes, BMAL1 and CLOCK, worked together at the core of the clock’s molecular machinery to activate the network of circadian genes. In this way, BMAL1 acts like the accelerator on a car, activating genes to rev up our physiology each morning so that we are alert, hungry and physically active.

Prior to this work REV-ERB-α and β were thought to play only a minor role in these cycles, possibly working together to slow CLOCK-BMAL1 activity to make minor adjustments to keep the clock running on time.

However, genetic studies of two genes with similar functions can be very difficult and thus the real importance of REV-ERB-α and β remained mysterious.

The Salk scientists got around this hurdle by developing mice in which both genes could be turned off in the liver at any point by giving them an estrogen derivative called tamoxifen. Now mice could develop normally to adulthood, at which point the scientists could turn off REV-ERB-α and REV-ERB-β in their livers—an organ crucial to maintaining the correct balance of sugar and fat in blood—to see what effects it had on circadian rhythms and metabolism.

“When we turned off both receptors, the animal’s biological clocks went haywire,” says Han Cho, first author on the paper and a postdoctoral researcher in Evan’s laboratory. “The mice started running on their exercise wheels when they should have been resting. This suggested REV-ERB-α and REV-ERB-β aren’t an auxiliary system that makes minor adjustments, but an integral part of the clock’s core mechanism. Without them, the clock can’t function properly.”

Digging more deeply into the clockworks, the Salk scientists mapped out the genes that the REV-ERBs control to keep the body operating on the right schedule, finding that they overlap with hundreds of the same genes controlled by CLOCK and BMAL1. This and other findings suggested that the REV-ERBs, act as a break on the genes BMAL1 activates.

“We thought that the core of the clock was an accelerator, and that all REV-ERB-α and REV-ERB-β did was to pull the foot off that pedal,” says Evans. “What we’ve shown is that these receptors act directly as a break to slow clock activity. Now we’ve got a accelerator and a break, each equally important in creating the daily rhythm of the clock.”

The scientists also found that the REV-ERBs control the activity of hundreds of genes involved metabolism, including those responsible for controlling levels of fats and bile. The mice in which REV-ERB-α and REV-ERB-β were turned off had high levels of fat and sugar in their blood—common problems in people with metabolic disorders.

“This explains how our cellular metabolism is tied to daylight cycles determined by the movements of the sun and the earth,” says Satchidananda Panda, an associate professor in Salk’s Regulatory Biology Laboratory and co-author on the paper. “Now we want to find ways of leveraging this mechanism to fix a person’s metabolic rhythms when they are disrupted by travel, shift work or sleep disorders.”

Source: Neuroscience News

April 4, 2012

Brain pacemakers have a long-term effect in patients with the most severe depression. This has now been proven by scientists from the Bonn University Medical Center. Eleven patients took part in the study over a period of two to five years. A lasting reduction in symptoms of more than 50 percent was seen in nearly half of the subjects. The results are now being presented in the current edition of the journal Neuropsychopharmacology.

People with severe depression are constantly despondent, lacking in drive, withdrawn and no longer feel joy. Most suffer from anxiety and the desire to take their own life. Approximately one out of every five people in Germany suffers from depression in the course of his/her life – sometimes resulting in suicide. People with depression are frequently treated with psychotherapy and medication. “However, many patients are not helped by any therapy,” says Prof. Dr. Thomas E. Schläpfer from the Bonn University Medical Center for Psychiatry and Psychotherapy. “Many spend more than ten years in bed – not because they are tired, but because they have no drive at all and they are unable to get up.”

One possible alternative is “deep brain stimulation,” in which electrodes are implanted in the patient’s brain. The target point is the nucleus accumbens - an area of the brain known as the gratification center. There, a weak electrical current stimulates the nerve cells. Brain pacemakers of this type are often used today by neurosurgeons and neurologists to treat ongoing muscle tremors in Parkinson’s disease.

A 2009 study proved an antidepressive effect

In 2009, the Bonn scientists were able to establish that brain pacemakers also demonstrate an effect in the most severely depressed patients. Ten subjects who underwent implantation of electrodes in the nucleus accumbens all experienced relief of symptoms. Half of the subjects had a particularly noticeable response to the stimulation by the electrodes.

"In the current study, we investigated whether these effects last over the long term or whether the effects of the deep brain stimulation gradually weaken in patients," says Prof. Schläpfer. There are always relapses in the case of psychotherapy or drug treatment. Many patients had already undergone up to 60 treatments with psychotherapy, medications and electroconvulsive therapy, to no avail. "By contrast, in the case of deep brain stimulation, the clinical improvement continues steadily for many years." The scientists observed a total of eleven patients over a period of two to five years. "Those who initially responded to the deep brain stimulation are still responding to it even today," says the Bonn psychiatrist, summarizing the results. During the study, one patient committed suicide. "That is very unfortunate," says Prof. Schläpfer. "However, this cannot always be prevented in the case of patients with very severe depression."

he current study shows that the positive effects last for years

Even after a short amount of time, the study participants demonstrated an improvement in symptoms. “The intensity of the anxiety symptoms decreased and the subjects’ drive improved,” reports the psychiatrist. “After many years of illness, some were even able to work again.” With the current publication, the scientists have now demonstrated that the positive effects do not decrease over a longer period of time. “An improvement in symptoms was recorded for all subjects; for nearly half of the subjects, the extent of the symptoms was more than 50 percent below that of the baseline, even years after the start of treatment,” says Prof. Schläpfer. “There were no serious adverse effects of the therapy recorded.”

The long-term effect is now confirmed with the current study. How precisely the electrical stimulation is able to alter the function of the nucleus accumbens is not yet known. “Research is still needed in this area,” says Prof. Schläpfer. “Using imaging techniques, it was proven that the electrodes actually activate the nucleus accumbens.” The deep brain stimulation method may signify hope for people who suffer from the most severe forms of depressive diseases. “However, it will still take quite a bit of time before this therapeutic method becomes a part of standard clinical practice,” says the Bonn scientist.

Provided by University of Bonn 

Source: medicalxpress.com