Posts tagged neuroimaging
Articles and news from the latest research reports.
Predicting Who Will Have Chronic Pain
Abnormalities in brain axons predispose people to chronic back pain after injury
Abnormalities in the structure of the brain predispose people to develop chronic pain after a lower back injury, according to new Northwestern Medicine® research. The findings could lead to changes in the way physicians treat patients’ pain.
Most scientists and clinicians have assumed chronic back pain stems from the site of the original injury.
“We’ve found the pain is triggered by these irregularities in the brain,” said A. Vania Apkarian, senior author of the study and a professor of physiology at Northwestern University Feinberg School of Medicine. “We’ve shown abnormalities in brain structure connections may be enough to push someone to develop chronic pain once they have an injury.”
Based on MRI brain scans of people who had a new lower back injury, Northwestern scientists could predict with about 85 percent accuracy which patients’ pain would persist. The predictor was a specific irregularity or marker the scientists identified in the axons, pathways in the brain’s white matter that connect brain cells so they can communicate with each other.
The findings provide a new view of treating chronic pain, which affects nearly 100 million Americans and costs up to $635 billion a year to treat.
“We think the people who are vulnerable need to be treated aggressively with medication early on to prevent their pain from becoming chronic,” Apkarian said. “Last year, we showed people who take medication early on had a better chance of recovering. Medication does help.” Apkarian also is a member of the Robert H. Lurie Comprehensive Cancer Center of Northwestern University.
The research, funded by the National Institutes of Health, was published Sept. 16 in the journal Pain.
Brain abnormalities have been observed in other long-term chronic pain conditions. Apkarian’s study is the first to show brain structure abnormalities are a marker of a predisposition to the chronic pain, not a result of living with it.
The lead author of the study is Ali Mansour, M.D., formerly a postdoctoral fellow in Apkarian’s lab.
Apkarian’s research focuses on the relationship between chronic pain and the brain. One of his previous studies showed chronic pain patients lose gray matter volume over time.
Chronic pain is one of the most expensive health care conditions in the U.S. and takes an enormous toll on quality of life, yet there still is not a scientifically validated therapy for the condition. Lower back pain represents 28 percent of all causes of pain in the U.S.; about 23 percent of these patients suffer long-term pain.
The abnormalities identified in the study were found in multiple white matter axon bundles, some surrounding the nucleus accumbens and medial prefrontal cortex, two brain regions involved in processing emotion and pain. Last year, the Apkarian group showed that the physiological properties of these two regions identify which patients will persist with back pain. The new results identify a pre-existing culprit for these physiological responses to the injury.
“The brain abnormalities exist in the general population, but only those people with a back injury go on to develop the chronic pain,” Apkarian said.
For the study, Apkarian and his colleagues scanned the brains of 46 people who had an episode of lower back pain for at least four weeks and had not experienced any pain for at least one year before that. Their pain had to be rated at least five out of 10 on a pain scale for them to be included in the study.
Scientists followed the patients for a year, scanning their brains at the onset of study and one year later. After a year about half of them had improved, regardless of whether they took anything to treat the pain, and half of them continued to have pain. Those with the persistent pain had the same structural abnormalities in their white matter at the onset of the injury and after one year.
“The abnormality makes them vulnerable and predisposes them to enhanced emotional learning that then amplifies the pain and makes it more emotionally significant,” Apkarian said.
“Pain is becoming an enormous burden on the public,” said Linda Porter, the pain policy advisor at National Institute of Neurological Disorders and Stroke (NINDS) and a leader of the National Institutes of Health (NIH) Pain Consortium. “The U.S. government recently outlined steps to reduce the future burden of pain through broad-ranging efforts, including enhanced research. This study is a good example of the kind of innovative research we hope will reduce chronic pain, which affects a huge portion of the population.”
(Image: Shutterstock)
Image: Eleven areas of the brain are showing differential activity levels in a Dartmouth study using functional MRI to measure how humans manipulate mental imagery. Credited to Alex Schlegel, Dartmouth College
Researchers discover how and where imagination occurs in human brains
New insights into ‘mental workspace’ may help advance artificial intelligence
Philosophers and scientists have long puzzled over where human imagination comes from. In other words, what makes humans able to create art, invent tools, think scientifically and perform other incredibly diverse behaviors?
The answer, Dartmouth researchers conclude in a new study, lies in a widespread neural network — the brain’s “mental workspace” — that consciously manipulates images, symbols, ideas and theories and gives humans the laser-like mental focus needed to solve complex problems and come up with new ideas.
Their findings, titled “Network structure and dynamics of the mental workspace,” appear the week of Sept. 16 in the Proceedings of the National Academy of Sciences.
"Our findings move us closer to understanding how the organization of our brains sets us apart from other species and provides such a rich internal playground for us to think freely and creatively," says lead author Alex Schlegel, a graduate student in the Department of Psychological and Brain Sciences. "Understanding these differences will give us insight into where human creativity comes from and possibly allow us to recreate those same creative processes in machines."
Scholars theorize that human imagination requires a widespread neural network in the brain, but evidence for such a “mental workspace” has been difficult to produce with techniques that mainly study brain activity in isolation. Dartmouth researchers addressed the issue by asking: How does the brain allow us to manipulate mental imagery? For instance, imagining a bumblebee with the head of a bull, a seemingly effortless task but one that requires the brain to construct a totally new image and make it appear in our mind’s eye.
In the study, 15 participants were asked to imagine specific abstract visual shapes and then to mentally combine them into new more complex figures or to mentally dismantle them into their separate parts. Researchers measured the participants’ brain activity with functional MRI and found a cortical and subcortical network over a large part of the brain was responsible for their imagery manipulations. The network closely resembles the “mental workspace” that scholars have theorized might be responsible for much of human conscious experience and for the flexible cognitive abilities that humans have evolved.
How schizophrenia affects the brain
UI study documents the illness’s effect on brain tissue
It’s hard to fully understand a mental disease like schizophrenia without peering into the human brain. Now, a study by University of Iowa psychiatry professor Nancy Andreasen uses brain scans to document how schizophrenia impacts brain tissue as well as the effects of anti-psychotic drugs on those who have relapses.
Andreasen’s study, published in the American Journal of Psychiatry, documented brain changes seen in MRI scans from more than 200 patients beginning with their first episode and continuing with scans at regular intervals for up to 15 years. The study is considered the largest longitudinal, brain-scan data set ever compiled, Andreasen says.
Schizophrenia affects roughly 3.5 million people, or about one percent of the U.S. population, according to the National Institutes of Health. Globally, some 24 million are affected, according to the World Health Organization.
The scans showed that people at their first episode had less brain tissue than healthy individuals. The findings suggest that those who have schizophrenia are being affected by something before they show outward signs of the disease.
“There are several studies, mine included, that show people with schizophrenia have smaller-than-average cranial size,” explains Andreasen, whose appointment is in the Carver College of Medicine. “Since cranial development is completed within the first few years of life, there may be some aspect of earliest development—perhaps things such as pregnancy complications or exposure to viruses—that on average, affected people with schizophrenia.”
Andreasen’s team learned from the brain scans that those affected with schizophrenia suffered the most brain tissue loss in the two years after the first episode, but then the damage curiously plateaued—to the group’s surprise. The finding may help doctors identify the most effective time periods to prevent tissue loss and other negative effects of the illness, Andreasen says.
The researchers also analyzed the effect of medication on the brain tissue. Although results were not the same for every patient, the group found that in general, the higher the anti-psychotic medication doses, the greater the loss of brain tissue.
“This was a very upsetting finding,” Andreasen says. “We spent a couple of years analyzing the data more or less hoping we had made a mistake. But in the end, it was a solid finding that wasn’t going to go away, so we decided to go ahead and publish it. The impact is painful because psychiatrists, patients, and family members don’t know how to interpret this finding. ‘Should we stop using antipsychotic medication? Should we be using less?’”
The group also examined how relapses could affect brain tissue, including whether long periods of psychosis could be toxic to the brain. The results suggest that longer relapses were associated with brain tissue loss.
The insight could change how physicians use anti-psychotic drugs to treat schizophrenia, with the view that those with the disorder can lead productive lives with the right balance of care.
“We used to have hundreds of thousands of people chronically hospitalized. Now, most are living in the community, and this is thanks to the medications we have,” Andreasen notes. “But antipsychotic treatment has a negative impact on the brain, so … we must get the word out that they should be used with great care, because even though they have fewer side effects than some of the other medications we use, they are certainly not trouble free and can have lifelong consequences for the health and happiness of the people and families we serve.”
(Source: now.uiowa.edu)
Neural and Behavioral Evidence for an Intrinsic Cost of Self-Control
The capacity for self-control is critical to adaptive functioning, yet our knowledge of the underlying processes and mechanisms is presently only inchoate. Theoretical work in economics has suggested a model of self-control centering on two key assumptions: (1) a division within the decision-maker between two ‘selves’ with differing preferences; (2) the idea that self-control is intrinsically costly. Neuroscience has recently generated findings supporting the ‘dual-self’ assumption. The idea of self-control costs, in contrast, has remained speculative. We report the first independent evidence for self-control costs. Through a neuroimaging meta-analysis, we establish an anatomical link between self-control and the registration of cognitive effort costs. This link predicts that individuals who strongly avoid cognitive demand should also display poor self-control. To test this, we conducted a behavioral experiment leveraging a measure of demand avoidance along with two measures of self-control. The results obtained provide clear support for the idea of self-control costs.
Finally mapped: The brain region that distinguishes bits from bounty
In comparing amounts of things — be it the grains of sand on a beach, or the size of a sea gull flock inhabiting it — humans use a part of the brain that is organized topographically, researchers have finally shown. In other words, the neurons that work to make this “numerosity” assessment are laid out in a shape that allows those most closely related to communicate and interact over the shortest possible distance.
This layout, referred to as a topographical map, is characteristic of all primary senses — sight, hearing, touch, smell and taste — and scientists have long assumed that numerosity, while not a primary sense (but perceived similarly to one), might be characterized by such a map, too.
But they have not been able to find it, which has caused some doubt in the field as to whether a map for numerosity exists.
Now, however, Utrecht University’s Benjamin Harvey, along with his colleagues, have sussed out signals that illustrate the hypothesized numerosity map is real.
Numerosity, it is important to note, is distinct from symbolic numbers. “We use symbolic numbers to represent numerosity and other aspects of magnitude, but the symbol itself is only a representation,” Harvey said. He went on to explain that numerosity selectivity in the brain is derived from visual processing of image features, where symbolic number selectivity is derived by recognizing the shapes of numerals, written words, and linguistic sounds that represent numbers. “This latter task relies on very different parts of the brain that specialize in written and spoken language.”
Understanding whether the brain’s processing of numerosity and symbolic numbers is related, as we might be tempted to think, is just one area that will be better informed by Harvey’s new map.
To uncover it, he and his colleagues asked eight adult study participants to look at patterns of dots that varied in number over time, all the while analysing the neural response properties in a numerosity-linked part of their brain using high-field fMRI (functional magnetic resonance imaging). Use of this advanced neuroimaging method allowed them to scan the subjects for far fewer hours per sitting than would have been required with a less powerful scanning technology.
With the fMRI data that resulted, Harvey and his team used population receptive field modelling, which aims to measure neural response as directly and quantitatively as possible. “This was the key to our success,” Harvey said. It allowed the researchers to model the human fMRI response properties they observed following results of recordings from macaque neurons, in which numerosity experiments had been conducted more extensively.
Their efforts revealed a topographical layout of numerosity in the human brain; the small quantities of dots the participants observed were encoded by neurons in one part of the brain, and the larger quantities, in another.
This finding demonstrates that topography can emerge not just for lower-level cognitive functions, like the primary senses, but for higher-level cognitive functions, too.
"We are very excited that association cortex can produce emergent topographic structures," Harvey said.
Because scientists know a great deal about topographical maps (and have the tools to probe them), the work of Harvey et al. may help scientists better analyse the neural computation underlying number processing.
"We believe this will lead to a much more complete understanding of humans’ unique numerical and mathematical skills," Harvey said.
Having heard from others in the field about the difficulty associated with the hunt for a topographical map of numerosity, Harvey and colleagues were surprised to obtain the results they did.
They also found the variations between their subjects interesting.
"Every individual brain is a complex and very different system," Harvey explained. "I was very surprised then that the map we report is in such a consistent location between our subjects, and that numerosity preferences always increased in the same direction along the cortex."
"On the other hand," he continued, "the extent of individual differences … is also striking." Harvey explained that understanding the consequences of these differences for their subjects’ perception or task performance will require further study.
(Source: eurekalert.org)
New laser-based tool could dramatically improve the accuracy of brain tumor surgery
Imaging technique tells tumor tissue from normal tissue, could be used in operating room for real-time guidance of surgery
A new laser-based technology may make brain tumor surgery much more accurate, allowing surgeons to tell cancer tissue from normal brain at the microscopic level while they are operating, and avoid leaving behind cells that could spawn a new tumor.
This image of a human glioblastoma brain tumor in the brain of a mouse was made with stimulated Raman scattering, or SRS, microscopy. The technique allows the tumor (blue) to be easily distinguished from normal tissue (green) based on faint signals emitted by tissue with different cellular structures.
In a new paper, featured on the cover of the journal Science Translational Medicine, a team of University of Michigan Medical School and Harvard University researchers describes how the technique allows them to “see” the tiniest areas of tumor cells in brain tissue.
They used this technique to distinguish tumor from healthy tissue in the brains of living mice — and then showed that the same was possible in tissue removed from a patient with glioblastoma multiforme, one of the most deadly brain tumors.
Now, the team is working to develop the approach, called SRS microscopy, for use during an operation to guide them in removing tissue, and test it in a clinical trial at U-M. The work was funded by the National Institutes of Health.
A need for improvement in tumor removal
On average, patients diagnosed with glioblastoma multiforme live only 18 months after diagnosis. Surgery is one of the most effective treatments for such tumors, but less than a quarter of patients’ operations achieve the best possible results, according to a study published last fall in the Journal of Neurosurgery.
“Though brain tumor surgery has advanced in many ways, survival for many patients is still poor, in part because surgeons can’t be sure that they’ve removed all tumor tissue before the operation is over,” says co-lead author Daniel Orringer, M.D., a lecturer in the U-M Department of Neurosurgery who has worked with the Harvard team since a chance meeting with a team member during his U-M residency.
On the left, the view of the brain that neurosurgeons currently see during an operation using bright-field microscopy. On the right, an SRS microscopy view of the same area of brain - in this case, a mouse brain that has had human brain tumor tissue transplanted into it. SRS might someday allow surgeons to see this same view of patients’ brains.
“We need better tools for visualizing tumor during surgery, and SRS microscopy is highly promising,” he continues. “With SRS we can see something that’s invisible through conventional surgical microscopy.”
The SRS in the technique’s name stands for stimulated Raman scattering. Named for C.V. Raman, one of the Indian scientists who co-discovered the effect and shared a 1930 Nobel Prize in physics for it, Raman scattering involves allows researchers to measure the unique chemical signature of materials.
In the SRS technique, they can detect a weak light signal that comes out of a material after it’s hit with light from a non-invasive laser. By carefully analyzing the spectrum of colors in the light signal, the researchers can tell a lot about the chemical makeup of the sample.
Over the past 15 years, Sunney Xie, Ph.D., of the Department of Chemistry and Chemical Biology at Harvard University – the senior author of the new paper — has advanced the technique for high-speed chemical imaging. By amplifying the weak Raman signal by more than 10,000 times, it is now possible to make multicolor SRS images of living tissue or other materials. The team can even make 30 new images every second — the rate needed to create videos of the tissue in real time.
Seeing the brain’s microscopic architecture
A multidisciplinary team of chemists, neurosurgeons, pathologists and others worked to develop and test the tool. The new paper is the first time SRS microscopy has been used in a living organism to see the “margin” of a tumor – the boundary area where tumor cells infiltrate among normal cells. That’s the hardest area for a surgeon to operate – especially when a tumor has invaded a region with an important function.
As the images in the paper show, the technique can distinguish brain tumor from normal tissue with remarkable accuracy, by detecting the difference between the signal given off by the dense cellular structure of tumor tissue, and the normal healthy grey and white matter.
The authors suggest that SRS microscopy may be as accurate for detecting tumor as the approach currently used in brain tumor diagnosis – called H&E staining.
This image shows the same areas of brain, imaged with SRS microscopy (left) and conventional H&E staining, which is the current technique used to diagnose brain tumors at the tissue level. The research suggests that SRS microscopy could be as accurate as H&E staining in allowing doctors to see tumors - without having to remove tissue or inject dyes into the patient.
The paper contains data from a test that pitted H&E staining directly against SRS microscopy. Three surgical pathologists, trained in studying brain tissue and spotting tumor cells, had nearly the same level of accuracy no matter which images they studied. But unlike H&E staining, SRS microscopy can be done in real time, and without dyeing, removing or processing the tissue.
Next steps: A smaller laser, a clinical trial
The current SRS microscopy system is not yet small or stable enough to use in an operating room. The team is collaborating with a start-up company formed by members of Xie’s group, called Invenio Imaging Inc., which is developing a laser to perform SRS through inexpensive fiber-optic components. The team is also working with AdvancedMEMS Inc. to reduce the size of the probe that makes the images possible.
A validation study, to examine tissue removed from consenting U-M brain tumor patients, may begin as soon as next year.
(Source: uofmhealth.org)
Creating a ‘Window to the Brain’
A team of University of California, Riverside researchers have developed a novel transparent skull implant that literally provides a “window to the brain”, which they hope will eventually open new treatment options for patients with life-threatening neurological disorders, such as brain cancer and traumatic brain injury.
The team’s implant is made of the same ceramic material currently used in hip implants and dental crowns, yttria-stabilized zirconia (YSZ). However, the key difference is that their material has been processed in a unique way to make it transparent.
Since YSZ has already proven itself to be well-tolerated by the body in other applications, the team’s advancement now allows use of YSZ as a permanent window through which doctors can aim laser-based treatments for the brain, importantly, without having to perform repeated craniectomies, which involve removing a portion of the skull to access the brain.
The work also dovetails with President Obama’s recently-announced BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative, which aims to revolutionize the understanding of the human mind and uncover new ways to treat, prevent, and cure brain disorders. The team envisions potential for their YSZ windows to facilitate the clinical translation of promising brain imaging and neuromodulation technologies being developed under this initiative.
“This is a case of a science fiction sounding idea becoming science fact, with strong potential for positive impact on patients,” said Guillermo Aguilar, a professor of mechanical engineering at UC Riverside’s Bourns College of Engineering (BCOE).
Aguilar is part of 10-person team, comprised of faculty, graduate students and researchers from UC Riverside’s Bourns College of Engineering and School of Medicine, who recently published a paper “Transparent Nanocrystalline Yttria-Stabilized-Zirconia Calvarium Prosthesis” about their findings online in the journal Nanomedicine: Nanotechnology, Biology and Medicine.
Laser-based treatments have shown significant promise for many brain disorders. However, realization of this promise has been constrained by the need for performing a craniectomy to access the brain since most medical lasers are unable to penetrate the skull. The transparent YSZ implants developed by the UC Riverside team address this issue by providing a permanently implanted view port through the skull.
“This is a crucial first step towards an innovative new concept that would provide a clinically-viable means for optically accessing the brain, on-demand, over large areas, and on a chronically-recurring basis, without need for repeated craniectomies,” said team member Dr. Devin Binder, a clinician and an associate professor of biomedical sciences at UC Riverside.
Although the team’s YSZ windows are not the first transparent skull implants to be reported, they are the first that could be conceivably used in humans, which is a crucial distinction. This is due to the inherent toughness of YSZ, which makes it far more resistant to shock and impact than the glass-based implants previously demonstrated by others. This not only enhances safety, but it may also reduce patient self-consciousness, since the reduced vulnerability of the implant could minimize the need for conspicuous protective headgear.
Schizophrenia symptoms linked to faulty ‘switch’ in brain
Scientists at The University of Nottingham have shown that psychotic symptoms experienced by people with schizophrenia could be caused by a faulty ‘switch’ within the brain.
In a study published today in the leading journal Neuron, they have demonstrated that the severity of symptoms such as delusions and hallucinations which are typical in patients with the psychiatric disorder is caused by a disconnection between two important regions in the brain — the insula and the lateral frontal cortex.
The breakthrough, say the academics, could form the basis for better, more targeted treatments for schizophrenia with fewer side effects.
The four-year study, led by Professor Peter Liddle and Dr Lena Palaniyappan in the University’s Division of Psychiatry and based in the Institute of Mental Health, centred on the insula region, a segregated ‘island’ buried deep within the brain, which is responsible for seamless switching between inner and outer world.
"Powerful explanation"
Dr Lena Palaniyappan, a Wellcome Trust Research Fellow, said: “In our daily life, we constantly switch between our inner, private world and the outer, objective world. This switching action is enabled by the connections between the insula and frontal cortex. This switch process appears to be disrupted in patients with schizophrenia. This could explain why internal thoughts sometime appear as external objective reality, experienced as voices or hallucinations in this condition. This could also explain the difficulties in ‘internalising’ external material pleasures (e.g. enjoying a musical tune or social events) that result in emotional blunting in patients with psychosis. Our observation offers a powerful mechanistic explanation for the formation of psychotic symptoms.”
Several brain regions are engaged when we are lost in thought or, for example, remembering a past event. However, when interrupted by a loud noise or another person speaking we are able to switch to using our frontal cortex area of the brain, which processes this external information. With a disruption in the connections from the insula, such switching may not be possible.
Compromised brain function
The Nottingham scientists used functional MRI (fMRI) imaging to compare the brains of 35 healthy volunteers with those of 38 schizophrenic patients. The results showed that whereas the majority of healthy patients were able to make this switch between regions, the patients with schizophrenia were less likely to shift to using their frontal cortex.
The insular and frontal cortex form a sensitive ‘salience’ loop within the brain — the insular should stimulate the frontal cortex while in turn the frontal cortex should inhibit the insula — but in patients with schizophrenia this system was found to be seriously compromised.
The results suggest that detecting the lack of a positive influence from the insula to the frontal cortex using fMRI could have a high degree of predictive value in identifying patients with schizophrenia.
The results of the study offer vital information for the development of more effective treatments for the condition.
Schizophrenia is one of the most common serious mental health conditions affecting around 1 in 100 people. Its onset occurs most commonly in a patient’s late teens or early 20s which can have devastating consequences for their future.
Genetic and environmental triggers
Scientists remain unsure what causes schizophrenia but believe it could be a combination of a genetic predisposition to the condition combined with environmental factors. Drug use is known to be a key trigger – people who use cannabis, or stimulant drugs, are three to four times more likely to go on to develop recurrent psychotic symptoms.
It is also believed that underdevelopment of the brain in the womb caused by complications in the mother’s pregnancy and in early childhood linked to issues such as malnutrition could play a key part. Previous observations from this research group have also uncovered the presence of unusually smooth folding patterns of the brain over the insula region in patients, suggesting an impairment in the normal development of this structure in schizophrenia.
At present, treatment involves a combination of antipsychotic medications, psychological therapies and social interventions. Currently, only one in five patients with schizophrenia achieve complete recovery and many patients who develop the condition in the long-term struggle to find a treatment that is 100 per cent effective in managing their condition.
Antipsychotic drugs, though effective in a number of patients, have poor acceptance rates due to the side effect burden meaning that many patients stop taking them in the longer run, leading to recurrence of disabling symptoms.
Researchers in Nottingham are also looking at a technique called TMS – transcranial magnetic stimulation — which uses a powerful magnetic pulse to stimulate the brain regions that are malfunctioning.
Compassion-based therapy
Despite the fact that the insular region is buried so deeply within the brain that TMS would usually be ineffective, the results of the Nottingham study suggest that the loop between the insular and the frontal cortex could be exploited for TMS– if a pulse is delivered to the frontal lobe it could stimulate the insula and reset the ‘switch’.
Other future treatment options could include the use of a compassion-based meditation therapy called mindfulness, which may have the potential to ‘reset’ the switching function of the insula and can promote physical changes within the brain. Meditation over a long period of time has been shown to increase the folding patterns within the insula area of the brain. These ideas are in its early stages at present, but may deliver more focussed treatment approaches in the longer term.
How sleep helps brain learn motor task
Sleep helps the brain consolidate what we’ve learned, but scientists have struggled to determine what goes on in the brain to make that happen for different kinds of learned tasks. In a new study, researchers pinpoint the brainwave frequencies and brain region associated with sleep-enhanced learning of a sequential finger tapping task akin to typing, or playing piano.
You take your piano lesson, you go to sleep and when you wake up your fingers are better able to play that beautiful sequence of notes. How does sleep make that difference? A new study helps to explain what happens in your brain during those fateful, restful hours when motor learning takes hold.
"The mechanisms of memory consolidations regarding motor memory learning were still uncertain until now," said Masako Tamaki, a postdoctoral researcher at Brown University and lead author of the study that appears Aug. 21 in the Journal of Neuroscience. “We were trying to figure out which part of the brain is doing what during sleep, independent of what goes on during wakefulness. We were trying to figure out the specific role of sleep.”
In part because it employed three different kinds of brain scans, the research is the first to precisely quantify changes among certain brainwaves and the exact location of that changed brain activity in subjects as they slept after learning a sequential finger-tapping task. The task was a sequence of key punches that is cognitively akin to typing or playing the piano.
Specifically, the results of complex experiments performed at Massachusetts General Hospital and then analyzed at Brown show that the improved speed and accuracy volunteers showed on the task after a few hours sleep was significantly associated with changes in fast-sigma and delta brainwave oscillations in their supplementary motor area (SMA), a region on the top-middle of the brain. These specific brainwave changes in the SMA occurred during a particular phase of sleep known as “slow-wave” sleep.
Scientists have shown that sleep improves many kinds of learning, including the kind of sequential finger-tapping motor tasks addressed in the study, but they haven’t been sure about why or how. It’s an intensive activity for the brain to consolidate learning and so the brain may benefit from sleep perhaps because more energy is available or because distractions and new inputs are fewer, said study corresponding author Yuka Sasaki, a research associate professor in Brown’s Department of Cognitive, Linguistic & Psychological Sciences.
"Sleep is not just a waste of time," Sasaki said.
The extent of reorganization that the brain accomplishes during sleep is suggested by the distinct roles the two brainwave oscillations appear to play. The authors wrote that the delta oscillations appeared to govern the changes in the SMA’s connectivity with other areas of the cortex, while the fast-sigma oscillations appeared to pertain to changes within the SMA itself.
Meticulous measurements
Possible roles for fast-sigma and delta brainwaves and for the SMA had suggestive support in the literature before this study, but no one had obtained much proof in part because doing so requires a complex experimental protocol.
To make their findings, Sasaki, Tamaki and their team asked each of their 15 subjects to volunteer for the motor learning experiments. For the first three nights, nine subjects simply slept at whatever their preferred bedtime was while their brains were scanned both with magnetoencephalography (MEG), which measures the oscillations with precise timing, and polysomnography, which keeps track of sleep phase. By this time the researchers had good baseline measurements of their brain activity and subjects had become accustomed to sleeping in the lab.
On day 4, the subjects learned the finger-tapping task on their non-dominant hand (to purposely make it harder to learn). The subjects were then allowed to go to sleep for three hours and were again scanned with PSG and MEG. Then the researchers woke them up. An hour later they asked the subjects to perform the tapping task. As a control, six other subjects did not sleep after learning the task, but were also asked to perform it four hours after being trained. Those who slept did the task faster and more accurately than those who did not.
On day 5, the researchers scanned each volunteer with an magnetic resonance imaging machine, which maps brain anatomy, so that they could later see where the MEG oscillations they had observed were located in each subject’s brain.
In all, the experimenters tracked 5 different oscillation frequencies in eight brain regions (four distinct regions on each of the brain’s two sides). Sasaki said she expected the most significant activity to take place in the “M1” brain region, which governs motor control, but instead the significant changes occurred in the SMA on the opposite side of the trained hand.
What was especially important about the delta and fast-sigma oscillations was that they fit two key criteria with statistical significance: they changed substantially after subjects were trained in the task and the strength of that change correlated with the degree of the subject’s performance improvement on the task.
After performing the experiments, the team of Sasaki, Tamaki and co-author Takeo Watanabe moved from MGH to Brown, where they have set up a new sleep lab. They have since begun a project to further study how the brain consolidates learning. In this case they’re looking at visual learning tasks.
"Will we see similar effects?" Sasaki asked. "Would it be with similar frequency bands and a similar organization of neighboring brain areas?"
To find out, some volunteers will just have to sleep on it.
Computer can read letters directly from the brain
By analysing MRI images of the brain with an elegant mathematical model, it is possible to reconstruct thoughts more accurately than ever before. In this way, researchers from Radboud University Nijmegen have succeeded in determining which letter a test subject was looking at. The journal Neuroimage has accepted the article, which will be published soon. A preliminary version of the article can be read online.
Functional MRI scanners have been used in cognition research primarily to determine which brain areas are active while test subjects perform a specific task. The question is simple: is a particular brain region on or off? A research group at the Donders Institute for Brain, Cognition and Behaviour at Radboud University has gone a step further: they have used data from the scanner to determine what a test subject is looking at. The researchers ‘taught’ a model how small volumes of 2x2x2 mm from the brain scans - known as voxels - respond to individual pixels. By combining all the information about the pixels from the voxels, it became possible to reconstruct the image viewed by the subject. The result was not a clear image, but a somewhat fuzzy speckle pattern. In this study, the researchers used hand-written letters.
Prior knowledge improves model performance
‘After this we did something new’, says lead researcher Marcel van Gerven. ‘We gave the model prior knowledge: we taught it what letters look like. This improved the recognition of the letters enormously. The model compares the letters to determine which one corresponds most exactly with the speckle image, and then pushes the results of the image towards that letter. The result was the actual letter, a true reconstruction.’
‘Our approach is similar to how we believe the brain itself combines prior knowledge with sensory information. For example, you can recognise the lines and curves in this article as letters only after you have learned to read. And this is exactly what we are looking for: models that show what is happening in the brain in a realistic fashion. We hope to improve the models to such an extent that we can also apply them to the working memory or to subjective experiences such as dreams or visualisations. Reconstructions indicate whether the model you have created approaches reality.’
Improved resolution; more possibilities
‘In our further research we will be working with a more powerful MRI scanner,’ explains Sanne Schoenmakers, who is working on a thesis about decoding thoughts. ‘Due to the higher resolution of the scanner, we hope to be able to link the model to more detailed images. We are currently linking images of letters to 1200 voxels in the brain; with the more powerful scanner we will link images of faces to 15,000 voxels.’