Posts tagged EEG
Articles and news from the latest research reports.
Sleep study reveals how the adolescent brain makes the transition to mature thinking
A new study conducted by monitoring the brain waves of sleeping adolescents has found that remarkable changes occur in the brain as it prunes away neuronal connections and makes the major transition from childhood to adulthood.
“We’ve provided the first long-term, longitudinal description of developmental changes that take place in the brains of youngsters as they sleep,” said Irwin Feinberg, professor emeritus of psychiatry and behavioral sciences and director of the UC Davis Sleep Laboratory. “Our outcome confirms that the brain goes through a remarkable amount of reorganization during puberty that is necessary for complex thinking.”
The research, published in the February 15 issue of American Journal of Physiology: Regulatory, Integrative and Comparative Physiology, also confirms that electroencephalogram, or EEG, is a powerful tool for tracking brain changes during different phases of life, and that it could potentially be used to help diagnose age-related mental illnesses. It is the final component in a three-part series of studies carried out over 10 years and involving more than 3,500 all-night EEG recordings. The data provide an overall picture of the brain’s electrical behavior during the first two decades of life.
Feinberg explained that scientists have generally assumed that a vast number of synapses are needed early in life to recover from injury and adapt to changing environments. These multiple connections, however, impair the efficient problem solving and logical thinking required later in life. His study is the first to show how this shift can be detected by measuring the brain’s electrical activity in the same children over the course of time.
Two earlier studies by Feinberg and his colleagues showed that EEG fluctuations during the deepest (delta or slow wave) phase of sleep, when the brain is most recuperative, consistently declined for 9- to 18-year-olds. The most rapid decline occurred between the ages of 12 and 16-1/2. This led the team to conclude that the streamlining of brain activity — or “neuronal pruning” — required for adult cognition occurs together with the timing of reproductive maturity.
Questions remained, though, about electrical activity patterns in the brains of younger children.
For the current study, Feinberg and his research team monitored 28 healthy, sleeping children between the ages of 6 and 10 for two nights every six months. The new findings show that synaptic density in the cerebral cortex reaches its peak at age 8 and then begins a slow decline. The recent findings also confirm that the period of greatest and most accelerated decline occurs between the ages of 12 and 16-1/2 years, at which point the drop markedly slows.
“Discovering that such extensive neuronal remodeling occurs within this 4-1/2 year timeframe during late adolescence and the early teen years confirms our view that the sleep EEG indexes a crucial aspect of the timing of brain development,” said Feinberg.
The latest study also confirms that EEG sleep analysis is a powerful approach for evaluating adolescent brain maturation, according to Feinberg. Besides being a relatively simple, accessible technology for measuring the brain’s electrical activity, it is more accurate than more cumbersome and expensive options.
“Structural MRI, for instance, has not been able to identify the adolescent accelerations and decelerations that are easily and reliably captured by sleep EEG,” said Feinberg. “We hope our data can aid the search for the unknown genetic and hormonal biomarkers that drive those fluctuations. Our data also provide a baseline for seeking errors in brain development that signify the onset of diseases such as schizophrenia, which typically first become apparent during adolescence. Once these underlying processes have been identified, it may become possible to influence adolescent brain changes in ways that promote normal development and correct emerging abnormalities.”
(Image: iStockphoto)
Punishment can enhance performance
The stick can work just as well as the carrot in improving our performance, a team of academics at The University of Nottingham has found.
A study led by researchers from the University’s School of Psychology, published recently in the Journal of Neuroscience, has shown that punishment can act as a performance enhancer in a similar way to monetary reward.
Dr Marios Philiastides, who led the work, said: “This work reveals important new information about how the brain functions that could lead to new methods of diagnosing neural development disorders such as autism, ADHD and personality disorders, where decision-making processes have been shown to be compromised.”
The Nottingham study aimed at looking at how the efficiency with which we make decisions based on ambiguous sensory information — such as visual or auditory — is affected by the potential for, and severity of, anticipated punishment.
Imposing penalties
To investigate this, they asked participants in the study to perform a simple perceptual task — asking them to judge whether a blurred shape behind a rainy window is a person or something else.
They punished incorrect decisions by imposing monetary penalties. At the same time, they measured the participants’ brain activity in response to different amounts of monetary punishment. Brain activity was recorded, non-invasively, using an EEG machine which detects and amplifies brain signals from the surface of the scalp through a set of small electrodes embedded in a swim-like cap fitted on the participants’ head.
They found that participants’ performance increased systematically as the amount of punishment increased, suggesting that punishment acts as a performance enhancer in a similar way to monetary reward.
At the neural level, the academics identified multiple and distinct brain activations induced by punishment and distributed throughout different areas of the brain. Crucially, the timing of these activations confirmed that the punishment does not influence the way in which the brain processes the sensory evidence but does have an impact on the brain’s decision maker responsible for decoding sensory information at a later stage in the decision-making process.
Incentive-based motivation
Finally, they showed that those participants who showed the greatest improvements in performance also showed the biggest changes in brain activity. This is a key finding as it provides a potential route to study differences between individuals and their personality traits in order to characterise why some may respond better to reward and punishment than others.
A more thorough understanding of the influence of punishment on decision-making and how we make choices could lead to useful information on how to use incentive-based motivation to encourage certain behaviour.
The paper, Temporal Characteristics of the Influence of Punishment on Perceptual Decision Making in the Human Brain, is available online via the Journal of Neuroscience.
Mind-controlled exoskeleton to help disabled people walk again
Every year thousands of people in Europe are paralysed by a spinal cord injury. Many are young adults, facing the rest of their lives confined to a wheelchair. Although no medical cure currently exists, in the future they could be able to walk again thanks to a mind-controlled robotic exoskeleton being developed by EU-funded researchers.
The system, based on innovative ‘Brain-neural-computer interface’ (BNCI) technology - combined with a light-weight exoskeleton attached to users’ legs and a virtual reality environment for training - could also find applications in the rehabilitation of stroke victims and in assisting astronauts rebuild muscle mass after prolonged periods in space.
In the United Kingdom, every eight hours someone suffers a spinal cord injury, often leading to partial or full lower-body paralysis. In the United States, more than 250.000 people are living with paralysis as a result of damage to their spinal cord, usually because of a traffic accident, fall or sporting injury. Many are under the age of 50, and with no known medical cure or way of repairing damaged spinal nerves they face the rest of their lives in a wheelchair.
But by bypassing the spinal cord entirely and routing brain signals to a robotic exoskeleton, they should be able to get back on their feet. That is the ultimate goal of researchers working in the ‘Mind-controlled orthosis and VR-training environment for walk empowering' (Mindwalker) project, a three-year initiative supported by EUR 2.75 million in funding from the European Commission.
'Mindwalker was proposed as a very ambitious project intended to investigate promising approaches to exploit brain signals for the purpose of controlling advanced orthosis, and to design and implement a prototype system demonstrating the potential of related technologies,' explains Michel Ilzkovitz, the project coordinator at Space Applications Services in Belgium.
The team’s approach relies on an advanced BNCI system that converts electroencephalography (EEG) signals from the brain, or electromyography (EMG) signals from shoulder muscles, into electronic commands to control the exoskeleton.
The Laboratory of Neurophysiology and Movement Biomechanics at the Université Libre de Bruxelles (ULB) focused on the exploitation of EEG and EMG signals treated by an artificial neural network, while the Foundation Santa Lucia in Italy developed techniques based on EMG signals modelled by the coupling of neural and biomechanical oscillators.
One approach for controlling the exoskeleton uses so-called ‘steady-state visually evoked potential’, a method that reads flickering visual stimuli produced at different frequencies to induce correlated EEG signals. Detection of these EEG signals is used to trigger commands such as ‘stand’, ‘walk’, ‘faster’ or ‘slower’.
A second approach is based on processing EMG signals generated by the user’s shoulders and exploits the natural arm-leg coordination in human walking: arm-swing patterns can be perceived in this way and converted into control signals commanding the exoskeleton’s legs.
A third approach, ‘ideation’, is also based on EEG-signal processing. It uses the identification and exploitation of EEG Theta cortical signals produced by the natural mental process associated with walking. The approach was investigated by the Mindwalker team but had to be dropped due to the difficulty, and time needed, in turning the results of early experiments into a fully exploitable system.
Regardless of which method is used, the BNCI signals have to be filtered and processed before they can be used to control the exoskeleton. To achieve this, the Mindwalker researchers fed the signals into a ‘Dynamic recurrent neural network’ (DRNN), a processing technique capable of learning and exploiting the dynamic character of the BNCI signals.
'This is appealing for kinematic control and allows a much more natural and fluid way of controlling an exoskeleton,' Mr Ilzkovitz says.
The team adopted a similarly practical approach for collecting EEG signals from the user’s scalp. Most BNCI systems are either invasive, requiring electrodes to be placed directly into brain tissue, or require users to wear a ‘wet’ capon their head, necessitating lengthy fitting procedures and the use of special gels to reduce the electrical resistance at the interface between the skin and the electrodes. While such systems deliver signals of very good quality and signal-to-noise ratio, they are impractical for everyday use.
The Mindwalker team therefore turned to a ‘dry’ technology developed by Berlin-based eemagine Medical Imaging Solutions: a cap covered in electrodes that the user can fit themselves, and which uses innovative electronic components to amplify and optimise signals before sending them to the neural network.
'The dry EEG cap can be placed by the subject on their head by themselves in less than a minute, just like a swimming cap,' Mr Ilzkovitz says.
How the brain loses and regains consciousness
Study reveals brain patterns produced by a general anesthesia drug; work could help doctors better monitor patients.
Since the mid-1800s, doctors have used drugs to induce general anesthesia in patients undergoing surgery. Despite their widespread use, little is known about how these drugs create such a profound loss of consciousness.
In a new study that tracked brain activity in human volunteers over a two-hour period as they lost and regained consciousness, researchers from MIT and Massachusetts General Hospital (MGH) have identified distinctive brain patterns associated with different stages of general anesthesia. The findings shed light on how one commonly used anesthesia drug exerts its effects, and could help doctors better monitor patients during surgery and prevent rare cases of patients waking up during operations.
Anesthesiologists now rely on a monitoring system that takes electroencephalogram (EEG) information and combines it into a single number between zero and 100. However, that index actually obscures the information that would be most useful, according to the authors of the new study, which appears in the Proceedings of the National Academy of Sciences the week of March 4.
“When anesthesiologists are taking care of someone in the operating room, they can use the information in this article to make sure that someone is unconscious, and they can have a specific idea of when the person may be regaining consciousness,” says senior author Emery Brown, an MIT professor of brain and cognitive sciences and health sciences and technology and an anesthesiologist at MGH.
'Network' analysis of the brain may explain features of autism
A look at how the brain processes information finds a distinct pattern in children with autism spectrum disorders. Using EEGs to track the brain’s electrical cross-talk, researchers from Boston Children’s Hospital have found a structural difference in brain connections. Compared with neurotypical children, those with autism have multiple redundant connections between neighboring brain areas at the expense of long-distance links.
The study, using a “network analysis” like that used to study airlines or electrical grids, may help in understanding some classic behaviors in autism. It was published February 27 in BioMed Central’s open access journal BMC Medicine, accompanied by a commentary.
"We examined brain networks as a whole in terms of their capacity to transfer and process information," says Jurriaan Peters, MD, of the Department of Neurology at Boston Children’s Hospital, who is co-first author of the paper with Maxime Taquet, a PhD student in Boston Children’s Computational Radiology Laboratory. "What we found may well change the way we look at the brains of autistic children."
Peters, Taquet and senior authors Simon Warfield, PhD, of the Computational Radiology Laboratory and Mustafa Sahin, MD, PhD, of Neurology, analyzed EEG recordings from two groups of autistic children: 16 children with classic autism, and 14 children whose autism is part of a genetic syndrome known as tuberous sclerosis complex (TSC). They compared these readings with EEGs from two control groups—46 healthy neurotypical children and 29 children with TSC but not autism.
In both groups with autism, there were more short-range connections within different brain region, but fewer connections linking far-flung areas.
A brain network that favors short-range over long-range connections seems to be consistent with autism’s classic cognitive profile—a child who excels at specific, focused tasks like memorizing streets, but who cannot integrate information across different brain areas into higher-order concepts.
"For example, a child with autism may not understand why a face looks really angry, because his visual brain centers and emotional brain centers have less cross-talk," Peters says. "The brain cannot integrate these areas. It’s doing a lot with the information locally, but it’s not sending it out to the rest of the brain."
Choosing Wisely: AAN Cites Five Things to Question
In 2012, the AAN joined the Choosing Wisely campaign, a project initiated by the American Board of Internal Medicine (ABIM) Foundation to promote appropriate medical decision-making and the stewardship of health care resources. The campaign is designed to help consumers and physicians engage in conversations about the overuse of particular tests, procedures, and treatments and to help patients make smart and effective care choices.
In February 2013, the AAN participated in a news conference with the ABIM Foundation and Consumer Reports, where medical specialties announced their lists of the top five questionable tests and procedures each selected for patients and physicians to consider.
Read AAN’s Five Things Physicians and Patients Should Question
The AAN’s complete recommendations were published online ahead of print in the February 21, 2013, issue of Neurology®.
How Neurology Tests and Procedures Were identified
The AAN established a Choosing Wisely Working Group to develop its list of recommendations. Members of this group were selected to broadly represent varying practice settings and neurological subspecialties. Neurologists with expertise in evidence-based medicine and a broad range of subspecialty disciplines were also included. The working group solicited recommendations from AAN members, which were then rated based upon their judgments of harm and benefit that would result based upon compliance with the recommendation. Based on committee voting and a literature review, candidate recommendations were sent to relevant AAN sections, committees, specialty societies and patient advocacy groups for review and comment. The working group reviewed this feedback and voted on the final top five recommendations, which were approved by the AAN Practice Committee and Board of Directors.
Research team discovers: brain does not process sensory information sufficiently
The reason why some people are worse at learning than others has been revealed by a research team from Berlin, Bochum, and Leipzig, operating within the framework of the Germany-wide network “Bernstein Focus State Dependencies of Learning”. They have discovered that the main problem is not that learning processes are inefficient per se, but that the brain insufficiently processes the information to be learned. The scientists trained the subjects’ sense of touch to be more sensitive. In subjects who responded well to the training, the EEG revealed characteristic changes in brain activity, more specifically in the alpha waves. These alpha waves show, among other things, how effectively the brain exploits the sensory information needed for learning. “An exciting question now is to what extent the alpha activity can be deliberately influenced with biofeedback”, says PD Dr. Hubert Dinse from the Neural Plasticity Lab of the Ruhr-Universität Bochum. “This could have enormous implications for therapy after brain injury or, quite generally, for the understanding of learning processes.” The research team from the Ruhr-Universität, the Humboldt Universität zu Berlin, Charité – Universitätsmedizin Berlin and the Max Planck Institute (MPI) for Human Cognitive and Brain Sciences reported their findings in the Journal of Neuroscience.
Learning without attention: passive training of the sense of touch
How well we learn depends on genetic aspects, the individual brain anatomy, and, not least, on attention. “In recent years we have established a procedure with which we trigger learning processes in people that do not require attention”, says Hubert Dinse. The researchers were, therefore, able to exclude attention as a factor. They repeatedly stimulated the participants’ sense of touch for 30 minutes by electrically stimulating the skin of the hand. Before and after this passive training, they tested the so-called “two-point discrimination threshold”, a measure of the sensitivity of touch. For this, they applied gentle pressure to the hand with two needles and determined the smallest distance between the needles at which the patient still perceived them as separate stimuli. On average, the passive training improved the discrimination threshold by twelve percent—but not in all of the 26 participants. Using EEG, the team studied why some people learned better than others.
Imaging the brain state using EEG: the alpha waves are decisive
The cooperation partners from Berlin and Leipzig, PD Dr. Petra Ritter, Dr. Frank Freyer, and Dr. Robert Becker recorded the subjects’ spontaneous EEG before and during passive training. They then identified the components of the brain activity related to improvement in the discrimination test. The alpha activity was decisive, i.e., the brain activity was in the frequency range 8 to 12 hertz. The higher the alpha activity before the passive training, the better the people learned. In addition, the more the alpha activity decreased during passive training, the more easily they learned. These effects occurred in the somatosensory cortex, that is, where the sense of touch is located in the brain.
Researchers seek new methods for therapy
“How the alpha rhythm manages to affect learning is something we investigate with computer models”, says PD Dr. Petra Ritter, Head of the Working Group “Brain Modes” at the MPI Leipzig and the Berlin Charité. “Only when we understand the complex information processing in the brain, can we intervene specifically in the processes to help disorders”, adds Petra Ritter. New therapies are the aim of the cooperation network, which Ritter coordinates, the international “Virtual Brain” project, which her team collaborates on, and the “Neural Plasticity Lab”, chaired by Hubert Dinse at the RUB.
Learning is dependent on access to sensory information
A high level of alpha activity counts as a marker of the readiness of the brain to exploit new incoming information. Conversely, a strong decrease of alpha activity during sensory stimulation counts as an indicator that the brain processes stimuli particularly efficiently. The results, therefore, suggest that perception-based learning is highly dependent on how accessible the sensory information is. The alpha activity, as a marker of constantly changing brain states, modulates this accessibility.
Two minds are better than one
Scientists at the Essex have been working with NASA on a project where they controlled a virtual spacecraft by thought alone.
Using BCI (brain-computer interface) technology, they found that combining the brain power of two people could be more accurate in steering a spacecraft than one person. BCIs convert signals generated from the brain into control commands for various applications, including virtual reality and hands-free control.
Researchers at Essex have already been undertaking extensive projects into using BCI to help people with disabilities to enable spelling, mouse control or to control a wheelchair. The research involves the user carrying our certain mental tasks which the computer then translates into commands to move the wheelchair in different directions.
The University has built-up an international reputation for its BCI research and is expanding its work into the new area of collaborative BCI, where tasks are performed by combining the signals of multiple BCI users.
The £500,000 project with NASA’s Jet Propulsion Lab in Pasadena, California, involved two people together steering a virtual spacecraft to a planet using a unique BCI mouse, developed by scientists at Essex.
Using electroencephalography (EEG), the two users wore a cap with electrodes which picked up different patterns in the brainwaves depending on what they were focusing their attention on a screen – in this case one of the eight directional dots of the cursor. Brain signals representing the users’ chosen direction, as interpreted by the computer, were then merged in real time to produce control commands for steering the spacecraft.
As Professor Riccardo Poli, for the University’s School of Computer Science and Electronic Engineering, explained, the experiment was very intense and involved a lot of concentration. With two people taking part in the test, the results were more accurate as the system could cope if one of the users had a brief lapse in concentration.
Analysis of this collaborative approach showed that two minds could be better than one at producing accurate trajectories. Combining signals also helped reduce the random “noise” that hinders EEG signals, such as heartbeat, breathing, swallowing and muscle activity. “When you average signals from two people’s brains, the noise cancels out a bit,” added Professor Poli.
Professor Poli said an exciting development for BCI research in the future relates to joint decision making, where a physiological signal, like pressing a button, and brain activity can be combined to give a superior result. “It is like measuring someone’s gut feeling,” added Professor Poli.
(Source: essex.ac.uk)
When the mind controls the machines
Stroke survivors, as well as patients suffering from other serious conditions, may have to deal with the partial or complete inability to move one or more of their limbs. In the most severe cases, the sufferer may become fully paralyzed and in need of permanent assistance.
The TOBI project (Tools for brain-computer interaction) is financed by the European Commission under the Seventh Framework Programme for Research (FP7) and is coordinated by EPFL. Since 2008 it has focused on the use of the signals transmitted by the brain. The electrical activity that takes place in the brain when the patient focuses on a particular task such as lifting an arm is detected by electroencephalography (EEG) through electrodes placed in a cap worn by the patient. Subsequently, a computer reads the signals and turns them into concrete actions as, for instance, moving a cursor on a screen.
Tests involving more than 100 patients
Based on this idea, researchers from thirteen institutions together with TOBI project partners have developed various technologies aimed at either obtaining better signal quality, making them clearer, or translating them into useful and functional applications. During the research, more than 100 patients or handicapped users had the opportunity to test the devices. Three of the technologies developed within the framework of TOBI were publicly presented at the closing seminar of the research program that took place in Sion from 23 to 25 January 2013.
- Robotino, for helping rebuild social ties when bedridden. Combining EEG, signal recognition, obstacle sensors and the internet, researchers have been able to develop a small robot equipped with a camera and a screen that can be controlled remotely by physically disabled people. Thanks to this device, the patient can take a virtual walk in a familiar environment, meet her/his relatives and talk to them, even if they are thousands of miles away from each other.
- Braintree, for writing texts and internet surfing. Researchers have also developed a graphical interface specially adapted for web browsing by severely disabled people. By thinking, the patient is able to move a cursor in a tree structure in order to type a character or choose a command. Depending on the specific situation, the sensors can also detect residual muscular activity to complement the management of the device.
- Functional electrical stimulation, to restore some basic mobility. Coupling EEG with electrical muscle stimulation can allow a patient to voluntarily control the movement of a paralyzed limb. In some cases, intensive training using this system has allowed the patients to regain control of the limb and keep it without assistance. A report on this technique can be seen in this video.
The results of the TOBI research program have restored patients’ hope. They will constitute the basis of subsequent developments to be conducted among the research partners or at industrial level. As for EPFL, such results will be the core of its health research chairs at the new EPFL Valais Wallis academic cluster, which can also count on the participation and support of the SuvaCare rehabilitation clinic in Sion.
Science Needs a Second Opinion: Researchers Find Flaws in Study of Patients in “Vegetative State”
A team of researchers led by Weill Cornell Medical College is calling into question the published statistics, methods and findings of a highly publicized research study that claimed bedside electroencephalography (EEG) identified evidence of awareness in three patients diagnosed to be in a vegetative state.
The new reanalysis study led by Weill Cornell neurologists Drs. Andrew Goldfine, Jonathan Victor, and Nicholas Schiff, published in the Jan. 26 issue of the journal Lancet, reports the statistical results and methodology used by a research team led by University of Western Ontario scientists and published online Nov. 9, 2011, also in the Lancet, was flawed in a number of crucial ways. Due to these errors, the reanalysis concludes it is impossible to determine whether or not these vegetative state study subjects demonstrated any degree of awareness during the testing.
(Image: RightBrainPhotography)