Posts tagged brain

February 14th, 2012

Humans move between ‘patches’ in their memory using the same strategy as bees flitting between flowers for pollen or birds searching among bushes for berries.

Researchers at the University of Warwick and Indiana University have identified parallels between animals looking for food in the wild and humans searching for items within their memory – suggesting that people with the best ‘memory foraging’ strategies are better at recalling items.

Scientists asked people to name as many animals as they could in three minutes and then compared the results with a classic model of optimal foraging in the real world, the marginal value theorem, which predicts how long animals will stay in one patch before jumping to another.

Dr Thomas Hills, associate professor in the psychology department at the University of Warwick, said: “A bird’s food tends to be clumped together in a specific patch – for example on a bush laden with berries.

“But when the berries on a bush are depleted to the point where the bird’s energy is best focused on another more fruitful bush, it will move on.

“This kind of behaviour is predicted by the marginal value theorem, for a wide variety of animals.

“Because of the way human attention has evolved, we wondered if humans might use the same strategies to forage in memory. It turns out, they do.

“When faced with a memory task, we focus on specific clusters of information and jump between them like a bird between bushes. For example, when hunting for animals in memory, most people start with a patch of household pets—like dog, cat and hamster.

“But then as this patch becomes depleted, they look elsewhere. They might then alight on another semantically distinct ‘patch’, for example predatory animals such as lion, tiger and jaguar.”

The study shows that people who either stay too long or not long enough in one ‘patch’ did not recall as many animals as those who better judged the best time to switch between patches.

In other words, people who most closely adhered to the marginal value theorem produced more items.

The study Optimal Foraging in Semantic Memory, published in Psychological Review, asked 141 undergraduates (46 men and 95 women) at Indiana University to name as many animals as they could in three minutes.

They then analysed the responses using a categorisation scheme and also a semantic space model, called BEAGLE, which identifies clusters in the memory landscape based on the way words are related to one another in natural language.

Source: Neuroscience News 

February 14, 2012 

(Medical Xpress) — A UT Dallas undergraduate’s research is revealing new information about a key protein’s role in the development of epilepsy, autism and other neurological disorders. This work could one day lead to new treatments for the conditions.

Senior neuroscience student Francisco Garcia has worked closely with Dr. Marco Atzori, associate professor in the School of Behavioral and Brain Sciences (BBS), on several papers that outline their findings about interleukin 6 (IL-6) and hyper-excitability. An article on the project is slated for publication in Biological Psychiatry later this year.

Scientists know that stress elevates the levels of pro-inflammatory cytokines (signaling molecules used in intercellular communication) and promotes hyper-excitable conditions within the central nervous system. This hyper-excitability is thought to be a factor in epilepsy, autism and anxiety disorders.

Garcia and Atzori hypothesized that the protein IL-6 acutely and directly induces hyper-excitability by altering the balance between excitation and inhibition within synaptic communication. In other words, IL-6 is not just present when hyper-excitability occurs in the nervous system. It may actually cause it in some circumstances, Garcia said.

The UT Dallas research team administered IL-6 to rat brain tissue and monitored its synaptic excitability. The brain tissue exhibited higher than normal excitability in their synapses, a symptom that may lead to misfiring of signals in epilepsy and other conditions.

The researchers then injected sgp130 -a novel drug that acts as an IL-6 blocker- into the laboratory animals’ brains. The substance limited excitability and appeared to prevent the conditions that lead to related neurological and psychiatric disorders, Garcia said.

“This finding has the potential to lead to eventual new treatments for epilepsy, anxiety disorders or autism,” Garcia said.

The next stage of his research will involve looking at how IL-6 might affect development of other types of neurological problems. Human trials could follow sometime in the future.

Garcia is a native of Mexico, and he plans to pursue his master’s degree in neuroscience at UT Dallas after finishing his undergraduate studies. He credits the BBS faculty with allowing him to participate in laboratory experiments and expand his research skills.

“The UT Dallas faculty members have been great about giving me the opportunity to learn the techniques of a lab researcher,” he said. “It’s been a great experience to work as an undergraduate with such highly respected scientists as Dr. Atzori and Dr. Michael Kilgard.”

Atzori also praised Garcia’s efforts.

“Francisco has been an intelligent, hard-working and experimentally gifted student who contributed way more than the average undergraduate to the projects of the laboratory,” Atzori said. “I am proud that a fine piece of research with great potential for research and clinical applications has been carried out thanks to his enthusiasm and dedication. Francisco’s work in my laboratory is an example of the achievements possible when an institution like UT Dallas invests in and nurtures its research environment.”

Provided by University of Texas at Dallas

Source: medicalxpress.com

February 14, 2012 in Neuroscience

February 14, 2012 by Bob Yirka in Neuroscience

(Medical Xpress) — A small team of researchers has found that various forms of child abuse can lead to stunted development in certain regions of the brain. The research carried out by Martin Teicher, Carl Anderson and Ann Polcari, all working in the Boston area, relied on questionnaires and MRI brain scans to determine that certain parts of the hippocampus, all known to be sensitive to stress, were up to six percent smaller in adults who as children had been sexually, verbally or physically abused. The team has published their results in the Proceedings of the National Academy of Sciences.

The three areas affected: the cornu ammonis, the dentate gyrus and the subiculum, all located in the hippocampus, are known to be vulnerable to stress which leads to less cell development than would normally occur in the absence of abuse.

To test the relationship between brain development and childhood abuse, the research team enlisted a group of otherwise healthy adult volunteers: 73 men and 120 women, all between the ages of 18 and 25. All were given questionnaires that delved into their childhood, specifically addressing issues of verbal, mental and physical abuse and other types of stresses such as the death of someone close to them or problems between parents. All were also given brain scans using an MRI machine. The team then compared the answers given on the questionnaires to the possibly impacted areas in the hippocampus of each volunteer. In so doing, they found that the brain regions under study were 5.8 to 6.5 percent smaller than average for those that reported such childhood stresses.

The researchers suggest that smaller brain regions due to childhood stressmay help explain the abnormally high levels of mental illness (depression, bi-polarism, anxiety, etc.) seen in adults who have endured abuse as children and why so many wind up with drug dependency problems. They also noted that one of the regions impacted, the subiculum, serves as a relay, moving information in and out of the hippocampus, which can have a direct impact on dopamine production. Those with reduced volume have been found to have problems with drug addiction and in some cases develop schizophrenia.

The researchers believe that increased stress leads to higher levels of the hormone cortisol, which in turn can slow or even stop the growth of new neurons in the brain which can result in permanently stunting certain brain regions.

The researchers are hoping their results will further highlight the damage that is done when children are subjected to adverse living conditions, leading perhaps to earlier interventions and possibly a means for developing treatments that may aid in preventing the stunting of brain regions, thus helping to pave the way for a better quality of life for those that have been abused as children.

Source: medicalxpress.com

Article Date: 14 Feb 2012 - 1:00 PST

Researchers at the Salk Institute have discovered a startling feature of early brain development that helps to explain how complex neuron wiring patterns are programmed using just a handful of critical genes. The findings, published in Cell, may help scientists develop new therapies for neurological disorders, such as amyotrophic lateral sclerosis (ALS), and provide insight into certain cancers.

The Salk researchers discovered that only a few proteins on the leading edge of a motor neuron’s axon - its outgoing electrical “wire” - and within the extracellular soup it travels through guide the nerve as it emerges from the spinal cord. These molecules can attract or repel the axon, depending on the long and winding path it must take to finally connect with its target muscle.

“The budding neuron has to detect the local environment it is growing through and decide where it is, and whether to grow straight, move to the left or right, or stop,” says the study’s senior investigator, Sam Pfaff, a professor in Salk’s Gene Expression Laboratory and a Howard Hughes Medical Institute investigator.

“It does this by mixing and matching just a handful of protein products to create complexes that tell a growing neuron which way to go, in the same way that a car uses the GPS signals it receives to guide it through an unfamiliar city,” he says.

The brain contains millions of times the number of neuron connections than the number of genes found in the DNA of brain cells. This is one of the first studies to try and understand how a growing neuron integrates many different pieces of information in order to navigate to its eventual target and make a functional connection.

“We focused on motor neurons that control muscle movements, but the same kind of thing is going on throughout embryonic development of the entire nervous system, during which millions of axons make trillions of decisions as they move to their targets,” he says. “It is the exquisite specificity with which they grow that underlies the basic architecture and proper function of the nervous system.”

These findings might eventually shed new light on a number of clinical disorders related to faulty nerve cell functioning, such as ALS, which is also known as Lou Gehrig’s disease, says the first author on the paper, Dario Bonanomi, a post-doctoral researcher in Pfaff’s laboratory.

“These are the motor neurons that die in diseases like Lou Gehrig’s disease and that are linked to a genetic disorder in children known as spinal muscle atrophy,” Bonanomi says.

“It is also a jumping off point to try and understand the basis for defects that might arise during fetal development of the nervous system,” he added. “A better understanding of those signals might help to be able to regenerate and rewire circuits following diseases or injuries of the nervous system.”

The researchers say the study also offers insights into cancer development, because a protein the researchers found to be crucial to the “push and pull” signaling system - Ret- is also linked to cancer. Mutations that activate Ret are linked to a number of different kinds of tumors.

The other protein receptors described in the study, known as Ephs, have also been implicated in cancer, Pfaff says.

“This study suggests that the way cells detect signals in their environment is likely a universal strategy,” he says, “and we know that genes and proteins known to function primarily during embryonic development have been linked to cancer.”

“Controlling neuronal growth requires very potent signaling molecules, and it makes sense they would be linked to disease,” Pfaff says. “We hope our findings help further unravel these connections.”

Source: Medical News Today 

Article Date: 14 Feb 2012 - 1:00 PST

A distinctive pattern of brain activity associated with conditions including deep anesthesia, coma and congenital brain disorders appears to represent the brain’s shift into a protective, low-activity state in response to reduced metabolic energy. A mathematical model developed by a Massachusetts General Hospital (MGH)-based research team accurately predicts and explains for the first time how the condition called burst suppression is elicited when brain cells’ energy supply becomes insufficient. Their report has been released online in PNAS Early Edition.

“The seemingly unrelated brain states that lead to burst suppression - deep anesthesia, coma, hypothermia and some developmental brain disorders - all represent a depressed metabolic state,” says Emery Brown, MD, PhD, of the MGH Department of Anesthesia, Critical Care and Pain Medicine, senior author of the report. “We believe we have identified something fundamental about brain neurochemistry, neuroanatomy and neurophysiology that may help us plan better therapies for brain protection and design future anesthetics.”

Burst suppression is an electroencephalogram (EEG) pattern in which periods of normal, high brain activity - the bursts - are interrupted by stretches of greatly reduced activity that can last 10 seconds or longer. Burst suppression has been observed in deep general anesthesia, in induced hypothermia - used to protect the brain or other structures from damage caused by trauma or reduced blood flow - in coma, and in infants with serious neurodevelopmental disorders. It also has transiently been observed in some premature infants. Previous investigations of burst suppression focused on characterizing the structure of the EEG patterns and understanding the brain’s responsiveness to external stimuli while in this state, not on the underlying mechanism.

Lead author ShiNung Ching, PhD, a postdoctoral fellow in Brown’s lab, had been working with Nancy Kopell, PhD, a professor of Mathematics at Boston University and co-author of the PNAS article, to develop mathematical models of different brain states under general anesthesia. In developing a model for burst suppression, they focused on what the associated conditions have in common - a significant reduction in the brain’s metabolic state. In order for a signal to pass from one nerve cell to another, the balance between sodium ions outside the cell and potassium ions within the cell needs to be correct. Maintaining that balance requires that structures called ion pumps, fueled by the cellular energy molecule ATP, function correctly. The model developed by Ching and his colleagues revealed that, when brain energy supplies drop too low and cause a deficiency in ATP, potassium leaks from the nerve cells and signal transmission halts.

“It looks like burst suppression shifts the brain into an altered physiologic state to allow for the regeneration of ATP, which is the essential metabolic substrate,” Ching explains. “During suppression, the brain is trying to recover enough ATP to restart. If the substrate doesn’t regenerate quickly enough, the system will have these brief bursts of activity, stop and then need to recover again. The length of suppression is governed by how quickly ATP regenerates, which matches the observation that the deeper someone is anesthetized, the longer the periods of suppression.”

Brown adds, “When we use general anesthesia to place patients with serious neurologic injuries into induced comas to allow their brains to heal, we take them down to a level of burst suppression. But there are a lot of questions regarding how deeply anesthetized an individual patient should be - how often the bursts should occur - and how long we should maintain that state. By elucidating what appears to be a fundamental energy-preserving mechanism within the brain, this model may help us think about using burst suppression to guide induced coma and track recovery from brain injuries. This is also a great example of how studying anesthesia can help us learn something very basic about the brain.”  

Source: Medical News Today

ScienceDaily (Feb. 13, 2012) — Only by employing complex machine-learning techniques to decipher repeated advanced brain scans were researchers at NewYork-Presbyterian/Weill Cornell able to provide evidence that a patient with a severe brain injury could, in her way, communicate accurately.

Their study, published in the Feb. 13 issue of the Archives of Neurology, demonstrates how difficult it is to determine whether a patient can communicate using only measured brain activity, even if it is possible for them to generate reliable patterns of brain activation in response to instructed commands. Patients in a minimally conscious state or who have locked-in syndrome (normal cognitive function with severe motor impairment) and can follow commands in the absence of a motor response may not generate clearly interpretable communications using the same patterns of brain activity, the researchers say.

While less sophisticated methods have been shown successful, the authors say their new approach provides important new insights into brain function and level of consciousness. It also identifies mechanisms of variation in brain activity supporting cognitive function after injury.

"In these studies we have reanalyzed earlier published data that demonstrated an effort to communicate using brain activations alone that apparently failed but was nonetheless a clear effort to generate a response," says Dr. Nicholas D. Schiff, professor of neurology and neuroscience and professor of public health at Weill Cornel Medical College, and a neurologist at NewYork-Presbyterian Hospital/Weill Cornell Medical Center. "Importantly, the reanalysis with new, more sensitive methods provides evidence that the problem with communication may reflect a mismatch of our expectations in designing the assessment, rather than a failure on the subject’s part in an attempt to accurately communicate with us."

"Our study shows that multivariate, machine-learning methods can be useful in determining whether patients are attempting to communicate, specifically when applied to data that already show evidence of a signal in univariate, more standard methods of analysis," says the study’s lead author, Jonathan Bardin, a fourth-year neuroscience graduate student at Weill Cornell Medical College.

"It is our clinical and ethical imperative to learn as much as possible about their ability to communicate," he says. "A simple bedside exam is not good enough."

"We need a set of methods that are both powerful and simple, and we are not there yet, as this study shows," adds Dr. Schiff. "We are using quite complex tasks to perhaps detect just the few of many patients who are conscious."

Patients Differ in Abilities

This study is a continuation of NewYork-Presbyterian/Weill Cornell research into how fMRI can establish a line of communication with brain-injured patients in order to understand if they can benefit from rehabilitation, and to gauge their level of pain and other clinical parameters that would improve care and quality of life.

It specifically follows up on a study published in the journal Brain last February that demonstrated use of fMRI to detect consciousness in six patients (either locked-in or minimally conscious) resulted in a wide, and largely unpredictable, variation in the ability of patients to respond to a simple command (such as “imagine swimming — now stop”) and then using the same command to answer simple yes/no or multiple-choice questions. This variation was apparent when compared with their ability to interact at the bedside using gestures or voice.

Some patients unable to communicate by gestures or voice were unable to do the mental tests, while others unable to communicate by gestures or voice were intermittently able to answer the researchers’ questions using mental imagery. And, intriguingly, some patients with the ability to communicate through gestures or voice were unable to do the mental tasks.

The researchers say these findings suggest that no exam yet exists at this time that can accurately assess the higher-level functioning that may be, and certainly seems to be, occurring in a number of severely brain-injured patients.

"There are people whose personal autonomy is abridged because they don’t have a good motor channel to express themselves despite, in some cases, having a clear mind and opinions and desires about themselves and the world," Dr. Schiff says about those results.

"Not all minimally conscious patients are the same, and not all patients with locked-in syndrome are the same," he says.

Sensitive and Flexible Methods Are Needed

This main new result of this study is a reinterpretation of findings from a 25-year-old patient who was the only one of six who showed an ability to use the fMRI signal for communication in the earlier research. But her results were confusing because it seemed that she was consistently responding to the answer that was directly after the correct answer, Bardin says.

"It’s often seen in patients like this — she had a stroke that damaged her brain — that there can be a cognitive delay in some area of the brain. FMRI is a readout of blood flow instead of actual neural activity, so these delays could be caused by an interruption of blood flow due to damage or could just mean they are working on the problem more slowly, and the answer looks wrong because it is given in the next response period."

To understand this, Bardin employed a newer technique, which he says has sprung out of machine-learning research, to instruct a computer to evaluate multiple fMRI scans from the patient after she answered the two questions a number of times.

This so-called multivariate approach used the same data gathered for the first study, which, in the typical “univariate” analysis, specifically looks at functioning in the brain’s Supplementary Motor Area (SMA), which is active when “normal” subjects imagine doing something.

In contrast, the multivariate analysis examines whether there is a pattern of activity in any part of the brain that is consistent from one scan to the next.

"When there is significant damage to the brain, it can rewire itself so that functions associated with SMA could be processed somewhere else," Bardin says.

Using this complex approach, the researchers found that, indeed, the patient had consistently attempted to communicate answers to both questions — but at a delayed speed.

The researchers say that one approach to analyze fMRI scans is not better than the other for all patients and that univariate methods should always be carried out first. Multivariate approaches can be especially sensitive to noise, leading to false positives if used on their own. If the standard approach reveals a signal, the multivariate approach could be used to gain further insights and possibly identify response in patients where the univariate results are ambiguous.

"We did all these things to simply show that we think this patient was trying to communicate," Bardin says. "You have to be very careful in your data analysis before saying anything strongly about what a patient can or cannot do."

"Rigid experimental paradigms like those used in the field can very well miss important information about these patients," Dr. Schiff says. "This is all extremely complex and messy, but we should expect that. Given the injuries some of our patients suffer, their cognitive abilities are very difficult to detect behaviorally or through simplistic tests or scans."

Source: Science Daily

ScienceDaily (Feb. 13, 2012) — Cognitive loss and brain degeneration currently affect millions of adults, and the number will increase, given the population of aging baby boomers. Today, nearly 20 percent of people age 65 or older suffer from mild cognitive impairment and 10 percent have dementia.

These are baseline and follow-up brain scans of a patient who converted to Alzheimer’s disease after two years (images to right of white line) that shows high medial temporal binding at baseline (lower left) and follow-up (lower right), but also demonstrates more baseline binding in frontal (upper images) and lateral temporal regions. Warmer colors (yellows, reds indicate higher binding levels. A second patient did not convert to Alzheimer’s after two years (images to left of white line) showing medial temporal (lower scans), but very mild frontal (upper scans) binding at baseline and follow-up. (Credit: UCLA)

UCLA scientists previously developed a brain-imaging tool to help assess the neurological changes associated with these conditions. The UCLA team now reports in the February issue of the journal Archives of Neurology that the brain-scan technique effectively tracked and predicted cognitive decline over a two-year period.

The team has created a chemical marker called FDDNP that binds to both plaque and tangle deposits — the hallmarks of Alzheimer’s disease — which can then be viewed using a positron emission tomography (PET) brain scan, providing a “window into the brain.” Using this method, researchers are able to pinpoint where in the brain these abnormal protein deposits are accumulating.

"We are finding that this may be a useful neuro-imaging marker that can detect changes early, before symptoms appear, and it may be helpful in tracking changes in the brain over time," said study author Dr. Gary Small, UCLA’s Parlow-Solomon Professor on Aging and a professor of psychiatry at the Semel Institute for Neuroscience and Human Behavior at UCLA.

Small noted that FDDNP-PET scanning is the only available brain-imaging technique that can assess tau tangles. Autopsy findings have found that tangles correlate with Alzheimer’s disease progression much better than do plaques.

For the study, researchers performed brain scans and cognitive assessments on the subjects at baseline and then again two years later. The study involved 43 volunteer paricipants, with an average age of 64, who did not have dementia. At the start of the study, approximately half (22) of the participants had normal aging and the other half (21) had mild cognitive impairment, or MCI, a condition that increases a person’s risk of developing Alzheimer’s disease.

Researchers found that for both groups, increases in FDDNP binding in the frontal, posterior cingulate and global areas of the brain at the two-year follow-up correlated with progression of cognitive decline. These areas of the brain are involved in decision-making, complex reasoning, memory and emotions. Higher initial baseline FDDNP binding in both subject groups was associated with a decline in cognitive functioning in areas such as language and attention at the two-year follow-up.

"We found that increases in FDDNP binding in key brain areas correlated with increases in clinical symptoms over time," said study author Dr. Jorge R. Barrio, who holds UCLA’s Plott Chair in Gerentology and is a professor of molecular and medical pharmacology at the David Geffen School of Medicine at UCLA. "Initial binding levels were also predictive of future cognitive decline."

Among the subjects with mild cognitive impairment, the level of initial binding in the frontal and parietal areas of the brain provided the greatest accuracy in identifying those who developed Alzheimer’s disease after two years. Of the 21 subjects with MCI, six were diagnosed with Alzheimer’s at follow-up, and these six subjects had higher initial frontal and parietal binding values than the other subjects in the MCI group.

In the normal aging subjects, three developed mild cognitive impairment after two years. Two of these three participants had had the highest baseline binding values in the temporal, parietal and frontal brain regions among this group.

Researchers said the next step in research will involve a longer duration of follow-up with larger samples of subjects. In addition, the team is using this brain-imaging technique in clinical trials to help track novel therapeutics for brain aging, such as curcumin, a chemical found in turmeric spice.

"Tracking the effectiveness of such treatments may help accelerate drug discovery efforts," Small, the author of the new book "The Alzheimer’s Prevention Program," said. "Because FDDNP appears to predict who will develop dementia, it may be particularly useful in tracking the effectiveness of interventions designed to delay the onset of dementia symptoms and eventually prevent the disease."

Small recently received research approval from the U.S. Food and Drug Administration to use FDDNP-PET to study people with mild cognitive impairment to determine whether a high-potency form of curcumin — a spice with anti-amyloid, anti-tau and anti-inflammatory properties — can prevent Alzheimer’s disease and the accumulation of plaques and tangles in the brain.

UCLA owns three U.S. patents on the FDDNP chemical marker. The Office of Intellectual Property at UCLA is actively seeking a commercial partner to bring this promising technology to market.

Source: Science Daily

ScienceDaily (Feb. 10, 2012) — A distinctive pattern of brain activity associated with conditions including deep anesthesia, coma and congenital brain disorders appears to represent the brain’s shift into a protective, low-activity state in response to reduced metabolic energy. A mathematical model developed by a Massachusetts General Hospital (MGH)-based research team accurately predicts and explains for the first time how the condition called burst suppression is elicited when brain cells’ energy supply becomes insufficient. Their report has been released online in PNAS Early Edition.

"The seemingly unrelated brain states that lead to burst suppression — deep anesthesia, coma, hypothermia and some developmental brain disorders — all represent a depressed metabolic state," says Emery Brown, MD, PhD, of the MGH Department of Anesthesia, Critical Care and Pain Medicine, senior author of the report. "We believe we have identified something fundamental about brain neurochemistry, neuroanatomy and neurophysiology that may help us plan better therapies for brain protection and design future anesthetics."

Burst suppression is an electroencephalogram (EEG) pattern in which periods of normal, high brain activity — the bursts — are interrupted by stretches of greatly reduced activity that can last 10 seconds or longer. Burst suppression has been observed in deep general anesthesia, in induced hypothermia — used to protect the brain or other structures from damage caused by trauma or reduced blood flow — in coma, and in infants with serious neurodevelopmental disorders. It also has transiently been observed in some premature infants. Previous investigations of burst suppression focused on characterizing the structure of the EEG patterns and understanding the brain’s responsiveness to external stimuli while in this state, not on the underlying mechanism.

Lead author ShiNung Ching, PhD, a postdoctoral fellow in Brown’s lab, had been working with Nancy Kopell, PhD, a professor of Mathematics at Boston University and co-author of the PNAS article, to develop mathematical models of different brain states under general anesthesia. In developing a model for burst suppression, they focused on what the associated conditions have in common — a significant reduction in the brain’s metabolic state. In order for a signal to pass from one nerve cell to another, the balance between sodium ions outside the cell and potassium ions within the cell needs to be correct. Maintaining that balance requires that structures called ion pumps, fueled by the cellular energy molecule ATP, function correctly. The model developed by Ching and his colleagues revealed that, when brain energy supplies drop too low and cause a deficiency in ATP, potassium leaks from the nerve cells and signal transmission halts.

"It looks like burst suppression shifts the brain into an altered physiologic state to allow for the regeneration of ATP, which is the essential metabolic substrate," Ching explains. "During suppression, the brain is trying to recover enough ATP to restart. If the substrate doesn’t regenerate quickly enough, the system will have these brief bursts of activity, stop and then need to recover again. The length of suppression is governed by how quickly ATP regenerates, which matches the observation that the deeper someone is anesthetized, the longer the periods of suppression."

Brown adds, “When we use general anesthesia to place patients with serious neurologic injuries into induced comas to allow their brains to heal, we take them down to a level of burst suppression. But there are a lot of questions regarding how deeply anesthetized an individual patient should be — how often the bursts should occur — and how long we should maintain that state. By elucidating what appears to be a fundamental energy-preserving mechanism within the brain, this model may help us think about using burst suppression to guide induced coma and track recovery from brain injuries. This is also a great example of how studying anesthesia can help us learn something very basic about the brain.”

Brown is the Warren Zapol Professor of Anesthesia at Harvard Medical School. He also is a professor of Computational Neuroscience and Health Sciences and Technology at Massachusetts Institute of Technology. Additional co-authors of the PNAS report are Patrick Purdon, PhD, MGH Anesthesia, and Sujith Vijayan, PhD, Boston University Mathematics. The study was supported by grants from the National Institutes of Health and the National Science Foundation.

Source: Science Daily