Neuroscience

Articles and news from the latest research reports.

Posts tagged brain activity

267 notes

Why we buy music New study shows what happens in the brain to make music rewarding A new study reveals what happens in our brain when we decide to purchase a piece of music when we hear it for the first time. The study, conducted at the Montreal Neurological Institute and Hospital – The Neuro, McGill University and published in the journal Science on April 12, pinpoints the specific brain activity that makes new music rewarding and predicts the decision to purchase music. Participants in the study listened to 60 previously unheard music excerpts while undergoing functional resonance imaging (fMRI) scanning, providing bids of how much they were willing to spend for each item in an auction paradigm. “When people listen to a piece of music they have never heard before, activity in one brain region can reliably and consistently predict whether they will like or buy it, this is the nucleus accumbens which is involved in forming expectations that may be rewarding,” says lead investigator Dr. Valorie Salimpoor, who conducted the research in Dr. Robert Zatorre’s lab at The Neuro and is now at Baycrest Health Sciences’ Rotman Research Institute. “What makes music so emotionally powerful is the creation of expectations. Activity in the nucleus accumbens is an indicator that expectations were met or surpassed, and in our study we found that the more activity we see in this brain area while people are listening to music, the more money they are willing to spend.” The second important finding is that the nucleus accumbens doesn’t work alone, but interacts with the auditory cortex, an area of the brain that stores information about the sounds and music we have been exposed to. The more a given piece was rewarding, the greater the cross-talk between these regions. Similar interactions were also seen between the nucleus accumbens and other brain areas, involved in high-level sequencing, complex pattern recognition and areas involved in assigning emotional and reward value to stimuli.   In other words, the brain assigns value to music through the interaction of ancient dopaminergic reward circuitry, involved in reinforcing behaviours that are absolutely necessary for our survival such as eating and sex, with some of the most evolved regions of the brain, involved in advanced cognitive processes that are unique to humans. “This is interesting because music consists of a series of sounds that when considered alone have no inherent value, but when arranged together through patterns over time can act as a reward, says Dr. Robert Zatorre, researcher at The Neuro and co-director of the International Laboratory for Brain, Music and Sound Research. “The integrated activity of brain circuits involved in pattern recognition, prediction, and emotion allow us to experience music as an aesthetic or intellectual reward.” “The brain activity in each participant was the same when they were listening to music that they ended up purchasing, although the pieces they chose to buy were all different,” adds Dr. Salimpoor. “These results help us to see why people like different music – each person has their own uniquely shaped auditory cortex, which is formed based on all the sounds and music heard throughout our lives. Also, the sound templates we store are likely to have previous emotional associations.” An innovative aspect of this study is how closely it mimics real-life music-listening experiences.  Researchers used a similar interface and prices as iTunes. To replicate a real life scenario as much as possible and to assess reward value objectively, individuals could purchase music with their own money, as an indication that they wanted to hear it again. Since musical preferences are influenced by past associations, only novel music excerpts were selected (to minimize explicit predictions) using music recommendation software (such as Pandora, Last.fm) to reflect individual preferences. The interactions between nucleus accumbens and the auditory cortex suggest that we create expectations of how musical sounds should unfold based on what is learned and stored in our auditory cortex, and our emotions result from the violation or fulfillment of these expectations. We are constantly making reward-related predictions to survive, and this study provides neurobiological evidence that we also make predictions when listening to an abstract stimulus, music, even if we have never heard the music before. Pattern recognition and prediction of an otherwise simple set of stimuli, when arranged together become so powerful as to make us happy or bring us to tears, as well as communicate and experience some of the most intense, complex emotions and thoughts. (Image: Peter Finnie and Ben Beheshti)

Why we buy music

New study shows what happens in the brain to make music rewarding

A new study reveals what happens in our brain when we decide to purchase a piece of music when we hear it for the first time. The study, conducted at the Montreal Neurological Institute and Hospital – The Neuro, McGill University and published in the journal Science on April 12, pinpoints the specific brain activity that makes new music rewarding and predicts the decision to purchase music.

Participants in the study listened to 60 previously unheard music excerpts while undergoing functional resonance imaging (fMRI) scanning, providing bids of how much they were willing to spend for each item in an auction paradigm. “When people listen to a piece of music they have never heard before, activity in one brain region can reliably and consistently predict whether they will like or buy it, this is the nucleus accumbens which is involved in forming expectations that may be rewarding,” says lead investigator Dr. Valorie Salimpoor, who conducted the research in Dr. Robert Zatorre’s lab at The Neuro and is now at Baycrest Health Sciences’ Rotman Research Institute. “What makes music so emotionally powerful is the creation of expectations. Activity in the nucleus accumbens is an indicator that expectations were met or surpassed, and in our study we found that the more activity we see in this brain area while people are listening to music, the more money they are willing to spend.”

The second important finding is that the nucleus accumbens doesn’t work alone, but interacts with the auditory cortex, an area of the brain that stores information about the sounds and music we have been exposed to. The more a given piece was rewarding, the greater the cross-talk between these regions. Similar interactions were also seen between the nucleus accumbens and other brain areas, involved in high-level sequencing, complex pattern recognition and areas involved in assigning emotional and reward value to stimuli.  

In other words, the brain assigns value to music through the interaction of ancient dopaminergic reward circuitry, involved in reinforcing behaviours that are absolutely necessary for our survival such as eating and sex, with some of the most evolved regions of the brain, involved in advanced cognitive processes that are unique to humans.

“This is interesting because music consists of a series of sounds that when considered alone have no inherent value, but when arranged together through patterns over time can act as a reward, says Dr. Robert Zatorre, researcher at The Neuro and co-director of the International Laboratory for Brain, Music and Sound Research. “The integrated activity of brain circuits involved in pattern recognition, prediction, and emotion allow us to experience music as an aesthetic or intellectual reward.”

“The brain activity in each participant was the same when they were listening to music that they ended up purchasing, although the pieces they chose to buy were all different,” adds Dr. Salimpoor. “These results help us to see why people like different music – each person has their own uniquely shaped auditory cortex, which is formed based on all the sounds and music heard throughout our lives. Also, the sound templates we store are likely to have previous emotional associations.”

An innovative aspect of this study is how closely it mimics real-life music-listening experiences.  Researchers used a similar interface and prices as iTunes. To replicate a real life scenario as much as possible and to assess reward value objectively, individuals could purchase music with their own money, as an indication that they wanted to hear it again. Since musical preferences are influenced by past associations, only novel music excerpts were selected (to minimize explicit predictions) using music recommendation software (such as Pandora, Last.fm) to reflect individual preferences.

The interactions between nucleus accumbens and the auditory cortex suggest that we create expectations of how musical sounds should unfold based on what is learned and stored in our auditory cortex, and our emotions result from the violation or fulfillment of these expectations. We are constantly making reward-related predictions to survive, and this study provides neurobiological evidence that we also make predictions when listening to an abstract stimulus, music, even if we have never heard the music before. Pattern recognition and prediction of an otherwise simple set of stimuli, when arranged together become so powerful as to make us happy or bring us to tears, as well as communicate and experience some of the most intense, complex emotions and thoughts.

(Image: Peter Finnie and Ben Beheshti)

Filed under brain brain activity music nucleus accumbens auditory cortex neuroscience science

192 notes

Study shows different brains have similar responses to music

Do the brains of different people listening to the same piece of music actually respond in the same way? An imaging study by Stanford University School of Medicine scientists says the answer is yes, which may in part explain why music plays such a big role in our social existence.

image

(Image: Anthony Ellis)

The investigators used functional magnetic resonance imaging to identify a distributed network of several brain structures whose activity levels waxed and waned in a strikingly similar pattern among study participants as they listened to classical music they’d never heard before. The results will be published online April 11 in the European Journal of Neuroscience.

"We spend a lot of time listening to music — often in groups, and often in conjunction with synchronized movement and dance," said Vinod Menon, PhD, a professor of psychiatry and behavioral sciences and the study’s senior author. "Here, we’ve shown for the first time that despite our individual differences in musical experiences and preferences, classical music elicits a highly consistent pattern of activity across individuals in several brain structures including those involved in movement planning, memory and attention."

The notion that healthy subjects respond to complex sounds in the same way, Menon said, could provide novel insights into how individuals with language and speech disorders might listen to and track information differently from the rest of us.

The new study is one in a series of collaborations between Menon and co-author Daniel Levitin, PhD, a psychology professor at McGill University in Montreal, dating back to when Levitin was a visiting scholar at Stanford several years ago.

To make sure it was music, not language, that study participants’ brains would be processing, Menon’s group used music that had no lyrics. Also excluded was anything participants had heard before, in order to eliminate the confounding effects of having some participants who had heard the musical selection before while others were hearing it for the first time. Using obscure pieces of music also avoided tripping off memories such as where participants were the first time they heard the selection.

The researchers settled on complete classical symphonic musical pieces by 18th-century English composer William Boyce, known to musical cognoscenti as “the English Bach” because his late-baroque compositions in some respects resembled those of the famed German composer. Boyce’s works fit well into the canon of Western music but are little known to modern Americans.

Next, Menon’s group recruited 17 right-handed participants (nine men and eight women) between the ages of 19 and 27 with little or no musical training and no previous knowledge of Boyce’s works. (Conventional maps of brain anatomy are based on studies of right-handed people. Left-handed people’s brains tend to deviate from that map.)

While participants listened to Boyce’s music through headphones with their heads maintained in a fixed position inside an fMRI chamber, their brains were imaged for more than nine minutes. During this imaging session, participants also heard two types of “pseudo-musical” stimuli containing one or another attribute of music but lacking in others. In one case, all of the timing information in the music was obliterated, including the rhythm, with an effect akin to a harmonized hissing sound. The other pseudo-musical input involved maintaining the same rhythmic structure as in the Boyce piece but with each tone transformed by a mathematical algorithm to another tone so that the melodic and harmonic aspects were drastically altered.

The team identified a hierarchal network stretching from low-level auditory relay stations in the midbrain to high-level cortical brain structures related to working memory and attention, and beyond that to movement-planning areas in the cortex. These regions track structural elements of a musical stimulus over time periods lasting up to several seconds, with each region processing information according to its own time scale.

Activity levels in several different places in the brain responded similarly from one individual to the next to music, but less so or not at all to pseudo-music. While these brain structures have been implicated individually in musical processing, their identifications had been obtained by probing with artificial laboratory stimuli, not real music. Nor had their coordination with one another been previously observed.

Notably, subcortical auditory structures in the midbrain and thalamus showed significantly greater synchronization in response to musical stimuli. These structures have been thought to passively relay auditory information to higher brain centers, Menon said. “But if they were just passive relay stations, their responses to both types of pseudo-music would have been just as closely synchronized between individuals as to real music.” The study demonstrated, for the first time, that those structures’ activity levels respond preferentially to music rather than to pseudo-music, suggesting that higher-level centers in the cortex direct these relay stations to closely heed sounds that are specifically musical in nature.

The fronto-parietal cortex, which anchors high-level cognitive functions including attention and working memory, also manifested intersubject synchronization — but only in response to music and only in the right hemisphere.

Interestingly, the structures involved included the right-brain counterparts of two important structures in the brain’s left hemisphere, Broca’s and Geschwind’s areas, known to be crucial for speech and language interpretation.

"These right-hemisphere brain areas track non-linguistic stimuli such as music in the same way that the left hemisphere tracks linguistic sequences," said Menon.

In any single individual listening to music, each cluster of music-responsive areas appeared to be tracking music on its own time scale. For example, midbrain auditory processing centers worked more or less in real time, while the right-brain analogs of the Broca’s and Geschwind’s areas appeared to chew on longer stretches of music. These structures may be necessary for holding musical phrases and passages in mind as part of making sense of a piece of music’s long-term structure.

"A novelty of our work is that we identified brain structures that track the temporal evolution of the music over extended periods of time, similar to our everyday experience of music listening," said postdoctoral scholar Daniel Abrams, PhD, the study’s first author.

The preferential activation of motor-planning centers in response to music, compared with pseudo-music, suggests that our brains respond naturally to musical stimulation by foreshadowing movements that typically accompany music listening: clapping, dancing, marching, singing or head-bobbing. The apparently similar activation patterns among normal individuals make it more likely our movements will be socially coordinated.

"Our method can be extended to a number of research domains that involve interpersonal communication. We are particularly interested in language and social communication in autism," Menon said. "Do children with autism listen to speech the same way as typically developing children? If not, how are they processing information differently? Which brain regions are out of sync?"

(Source: eurekalert.org)

Filed under brain brain activity music brain structure fMRI psychology neuroscience science

64 notes

Lights, Chemistry, Action: New Method for Mapping Brain Activity Building on their history of innovative brain-imaging techniques, scientists at the U.S. Department of Energy’s Brookhaven National Laboratory and collaborators have developed a new way to use light and chemistry to map brain activity in fully-awake, moving animals. The technique employs light-activated proteins to stimulate particular brain cells and positron emission tomography (PET) scans to trace the effects of that site-specific stimulation throughout the entire brain. As described in a paper published online today in the Journal of Neuroscience, the method will allow researchers to map exactly which downstream neurological pathways are activated or deactivated by stimulation of targeted brain regions, and how that brain activity correlates with particular behaviors and/or disease conditions. "This technique gives us a new way to look at the function of specific brain cells and map which brain circuits are active in a wide range of neuropsychiatric diseases — from depression to Parkinson’s disease, neurodegenerative disorders, and drug addiction — and also to monitor the effects of various treatments," said the paper’s lead author, Panayotis (Peter) Thanos, a neuroscientist and director of the Behavioral Neuropharmacology and Neuroimaging Section — part of the National Institute on Alcohol Abuse and Alcoholism (NIAAA) Laboratory of Neuroimaging at Brookhaven Lab — and a professor at Stony Brook University. "Because the animals are awake and able to move during stimulation, we can also directly study how their behavior correlates with brain activity," he said. The new brain-mapping method combines very recent advances in a field known as “optogenetics” — the use of optics (light activation) and genetics (genetically coded light-sensitive proteins) to control the activity of individual neurons, or nerve cells — and Brookhaven’s historical development of radioactively labeled chemical tracers to track biological activity with PET scanners.  The scientists used a modified virus to deliver a light-sensitive protein to particular brain cells in rats. Genetic coding can deliver the protein to specifically targeted brain-cell receptors. Then, after stimulating those proteins with light shone through an optical fiber inserted through a tiny tube called a cannula, they monitored overall brain activity using a radiotracer known as 18FDG, which serves as a stand-in for glucose, the body’s (and brain’s) main source of energy.  The unique chemistry of 18FDG causes it to be temporarily “trapped” inside cells that are hungry for glucose — those activated by the brain stimulation — and remain there long enough for the detectors of a PET scanner to pick up the radioactive signal, even after the animals are anesthetized to ensure they stay still for scanning. But because the animals were awake and moving when the tracer was injected and the brain cells were being stimulated, the scans reveal what parts of the brain were activated (or deactivated) under those conditions, giving scientists important information about how those brain circuits function and correlate with the animals’ behaviors. "In this paper, we wanted to stimulate the nucleus accumbens, a key part of the brain involved in reward that is very important to understanding drug addiction," Thanos said. "We wanted to activate the cells in that area and see which brain circuits were activated and deactivated in response."  The scientists used the technique to trace activation and deactivation in number of key pathways, and confirmed their results with other analysis techniques.  The method can reveal even more precise effects. "If we want to know more about the role played by specific types of receptors — say the dopamine D1 or D2 receptors involved in processing reward — we could tailor the light-sensitive protein probe to specifically stimulate one or the other to tease out those effects," he said. Another important aspect is that the technique does not require the scientists to identify in advance the regions of the brain they want to investigate, but instead provides candidate brain regions involved anywhere in the brain – even regions not well understood. "We look at the whole brain," Thanos said. "We take the PET images and co-register them with anatomical maps produced with magnetic resonance imaging (MRI), and use statistical techniques to do comparisons voxel by voxel. That allows us to identify which areas are more or less activated under the conditions we are exploring without any prior bias about what regions should be showing effects.” After they see a statistically significant effect, they use the MRI maps to identify the locations of those particular voxels to see what brain regions they are in. "This opens it up to seeing an effect in any region in the brain — even parts where you would not expect or think to look — which could be a key to new discoveries," he said.

Lights, Chemistry, Action: New Method for Mapping Brain Activity

Building on their history of innovative brain-imaging techniques, scientists at the U.S. Department of Energy’s Brookhaven National Laboratory and collaborators have developed a new way to use light and chemistry to map brain activity in fully-awake, moving animals. The technique employs light-activated proteins to stimulate particular brain cells and positron emission tomography (PET) scans to trace the effects of that site-specific stimulation throughout the entire brain. As described in a paper published online today in the Journal of Neuroscience, the method will allow researchers to map exactly which downstream neurological pathways are activated or deactivated by stimulation of targeted brain regions, and how that brain activity correlates with particular behaviors and/or disease conditions.

"This technique gives us a new way to look at the function of specific brain cells and map which brain circuits are active in a wide range of neuropsychiatric diseases — from depression to Parkinson’s disease, neurodegenerative disorders, and drug addiction — and also to monitor the effects of various treatments," said the paper’s lead author, Panayotis (Peter) Thanos, a neuroscientist and director of the Behavioral Neuropharmacology and Neuroimaging Section — part of the National Institute on Alcohol Abuse and Alcoholism (NIAAA) Laboratory of Neuroimaging at Brookhaven Lab — and a professor at Stony Brook University. "Because the animals are awake and able to move during stimulation, we can also directly study how their behavior correlates with brain activity," he said.

The new brain-mapping method combines very recent advances in a field known as “optogenetics” — the use of optics (light activation) and genetics (genetically coded light-sensitive proteins) to control the activity of individual neurons, or nerve cells — and Brookhaven’s historical development of radioactively labeled chemical tracers to track biological activity with PET scanners. 

The scientists used a modified virus to deliver a light-sensitive protein to particular brain cells in rats. Genetic coding can deliver the protein to specifically targeted brain-cell receptors. Then, after stimulating those proteins with light shone through an optical fiber inserted through a tiny tube called a cannula, they monitored overall brain activity using a radiotracer known as 18FDG, which serves as a stand-in for glucose, the body’s (and brain’s) main source of energy. 

The unique chemistry of 18FDG causes it to be temporarily “trapped” inside cells that are hungry for glucose — those activated by the brain stimulation — and remain there long enough for the detectors of a PET scanner to pick up the radioactive signal, even after the animals are anesthetized to ensure they stay still for scanning. But because the animals were awake and moving when the tracer was injected and the brain cells were being stimulated, the scans reveal what parts of the brain were activated (or deactivated) under those conditions, giving scientists important information about how those brain circuits function and correlate with the animals’ behaviors.

"In this paper, we wanted to stimulate the nucleus accumbens, a key part of the brain involved in reward that is very important to understanding drug addiction," Thanos said. "We wanted to activate the cells in that area and see which brain circuits were activated and deactivated in response." 

The scientists used the technique to trace activation and deactivation in number of key pathways, and confirmed their results with other analysis techniques. 

The method can reveal even more precise effects.

"If we want to know more about the role played by specific types of receptors — say the dopamine D1 or D2 receptors involved in processing reward — we could tailor the light-sensitive protein probe to specifically stimulate one or the other to tease out those effects," he said.

Another important aspect is that the technique does not require the scientists to identify in advance the regions of the brain they want to investigate, but instead provides candidate brain regions involved anywhere in the brain – even regions not well understood.

"We look at the whole brain," Thanos said. "We take the PET images and co-register them with anatomical maps produced with magnetic resonance imaging (MRI), and use statistical techniques to do comparisons voxel by voxel. That allows us to identify which areas are more or less activated under the conditions we are exploring without any prior bias about what regions should be showing effects.”

After they see a statistically significant effect, they use the MRI maps to identify the locations of those particular voxels to see what brain regions they are in.

"This opens it up to seeing an effect in any region in the brain — even parts where you would not expect or think to look — which could be a key to new discoveries," he said.

Filed under brain brain activity brain cells neurodegenerative diseases neuroimaging optogenetics neuroscience science

114 notes

First objective measure of pain discovered in brain scan patterns For the first time, scientists have been able to predict how much pain people are feeling by looking at images of their brains, according to a new study led by the University of Colorado Boulder. The findings, published today in the New England Journal of Medicine, may lead to the development of reliable methods doctors can use to objectively quantify a patient’s pain. Currently, pain intensity can only be measured based on a patient’s own description, which often includes rating the pain on a scale of one to 10. Objective measures of pain could confirm these pain reports and provide new clues into how the brain generates different types of pain. The new research results also may set the stage for the development of methods using brain scans to objectively measure anxiety, depression, anger or other emotional states. “Right now, there’s no clinically acceptable way to measure pain and other emotions other than to ask a person how they feel,” said Tor Wager, associate professor of psychology and neuroscience at CU-Boulder and lead author of the paper. The research team, which included scientists from New York University, Johns Hopkins University and the University of Michigan, used computer data-mining techniques to comb through images of 114 brains that were taken when the subjects were exposed to multiple levels of heat, ranging from benignly warm to painfully hot. With the help of the computer, the scientists identified a distinct neurologic signature for the pain. “We found a pattern across multiple systems in the brain that is diagnostic of how much pain people feel in response to painful heat.” Wager said. Going into the study, the researchers expected that if a pain signature could be found it would likely be unique to each individual. If that were the case, a person’s pain level could only be predicted based on past images of his or her own brain. But instead, they found that the signature was transferable across different people, allowing the scientists to predict how much pain a person was being caused by the applied heat, with between 90 and 100 percent accuracy, even with no prior brain scans of that individual to use as a reference point. The scientists also were surprised to find that the signature was specific to physical pain. Past studies have shown that social pain can look very similar to physical pain in terms of the brain activity it produces. For example, one study showed that the brain activity of people who have just been through a relationship breakup — and who were shown an image of the person who rejected them — is similar to the brain activity of someone feeling physical pain. But when Wager’s team tested to see if the newly defined neurologic signature for heat pain would also pop up in the data collected earlier from the heartbroken participants, they found that the signature was absent. Finally, the scientists tested to see if the neurologic signature could detect when an analgesic was used to dull the pain. The results showed that the signature registered a decrease in pain in subjects given a painkiller. The results of the study do not yet allow physicians to quantify physical pain, but they lay the foundation for future work that could produce the first objective tests of pain by doctors and hospitals. To that end, Wager and his colleagues are already testing how the neurologic signature holds up when applied to different types of pain. “I think there are many ways to extend this study, and we’re looking to test the patterns that we’ve developed for predicting pain across different conditions,” Wager said. “Is the predictive signature different if you experience pressure pain or mechanical pain, or pain on different parts of the body? “We’re also looking towards using these same techniques to develop measures for chronic pain. The pattern we have found is not a measure of chronic pain, but we think it may be an ‘ingredient’ of chronic pain under some circumstances. Understanding the different contributions of different systems to chronic pain and other forms of suffering is an important step towards understanding and alleviating human suffering.”

First objective measure of pain discovered in brain scan patterns

For the first time, scientists have been able to predict how much pain people are feeling by looking at images of their brains, according to a new study led by the University of Colorado Boulder.

The findings, published today in the New England Journal of Medicine, may lead to the development of reliable methods doctors can use to objectively quantify a patient’s pain. Currently, pain intensity can only be measured based on a patient’s own description, which often includes rating the pain on a scale of one to 10. Objective measures of pain could confirm these pain reports and provide new clues into how the brain generates different types of pain.

The new research results also may set the stage for the development of methods using brain scans to objectively measure anxiety, depression, anger or other emotional states.

“Right now, there’s no clinically acceptable way to measure pain and other emotions other than to ask a person how they feel,” said Tor Wager, associate professor of psychology and neuroscience at CU-Boulder and lead author of the paper.

The research team, which included scientists from New York University, Johns Hopkins University and the University of Michigan, used computer data-mining techniques to comb through images of 114 brains that were taken when the subjects were exposed to multiple levels of heat, ranging from benignly warm to painfully hot. With the help of the computer, the scientists identified a distinct neurologic signature for the pain.

“We found a pattern across multiple systems in the brain that is diagnostic of how much pain people feel in response to painful heat.” Wager said.

Going into the study, the researchers expected that if a pain signature could be found it would likely be unique to each individual. If that were the case, a person’s pain level could only be predicted based on past images of his or her own brain. But instead, they found that the signature was transferable across different people, allowing the scientists to predict how much pain a person was being caused by the applied heat, with between 90 and 100 percent accuracy, even with no prior brain scans of that individual to use as a reference point.

The scientists also were surprised to find that the signature was specific to physical pain. Past studies have shown that social pain can look very similar to physical pain in terms of the brain activity it produces. For example, one study showed that the brain activity of people who have just been through a relationship breakup — and who were shown an image of the person who rejected them — is similar to the brain activity of someone feeling physical pain.

But when Wager’s team tested to see if the newly defined neurologic signature for heat pain would also pop up in the data collected earlier from the heartbroken participants, they found that the signature was absent.

Finally, the scientists tested to see if the neurologic signature could detect when an analgesic was used to dull the pain. The results showed that the signature registered a decrease in pain in subjects given a painkiller.

The results of the study do not yet allow physicians to quantify physical pain, but they lay the foundation for future work that could produce the first objective tests of pain by doctors and hospitals. To that end, Wager and his colleagues are already testing how the neurologic signature holds up when applied to different types of pain.

“I think there are many ways to extend this study, and we’re looking to test the patterns that we’ve developed for predicting pain across different conditions,” Wager said. “Is the predictive signature different if you experience pressure pain or mechanical pain, or pain on different parts of the body?

“We’re also looking towards using these same techniques to develop measures for chronic pain. The pattern we have found is not a measure of chronic pain, but we think it may be an ‘ingredient’ of chronic pain under some circumstances. Understanding the different contributions of different systems to chronic pain and other forms of suffering is an important step towards understanding and alleviating human suffering.”

Filed under brain pain pain intensity chronic pain brain activity neuroscience science

141 notes

Non-Invasive Mapping Helps to Localize Language Centers Before Brain Surgery A new functional magnetic resonance imaging (fMRI) technique may provide neurosurgeons with a non-invasive tool to help in mapping critical areas of the brain before surgery, reports a study in the April issue of Neurosurgery, official journal of the Congress of Neurological Surgeons. The journal is published by Lippincott Williams & Wilkins, a part of Wolters Kluwer Health. Evaluating brain fMRI responses to a “single, short auditory language task” can reliably localize critical language areas of the brain—in healthy people as well as patients requiring brain surgery for epilepsy or tumors, according to the new research by Melanie Genetti, PhD, and colleagues of Geneva University Hospitals, Switzerland. Brief fMRI Task for Functional Brain MappingThe researchers designed and evaluated a quick and simple fMRI task for use in functional brain mapping. Functional MRI can show brain activity in response to stimuli (in contrast to conventional brain MRI, which shows anatomy only). Before neurosurgery for severe epilepsy or brain tumors, functional brain mapping provides essential information on the location of critical brain areas governing speech and other functions. The standard approach to brain mapping is direct electrocortical stimulation (ECS)—recording brain activity from electrodes placed on the brain surface. However, this requires several hours of testing and may not be applicable in all patients. Previous studies have compared fMRI techniques with ECS, but mainly for determining the side of language function (lateralization) rather than the precise location (localization). The new fMRI task was developed and evaluated in 28 healthy volunteers and in 35 patients undergoing surgery for brain tumors or epilepsy. The test used a brief (eight minutes) auditory language stimulus in which the patients heard a series of sense and nonsense sentences. Functional MRI scans were obtained to localize the brain areas activated by the language task—activated areas would “light up,” reflecting increased oxygenation. A subgroup of patients also underwent ECS, the results of which were compared to fMRI. Non-invasive Test Accurately Localizes Critical Brain AreasBased on responses to the language stimulus, fMRI showed activation of the anterior and posterior (front and rear) language areas of the brain in about 90 percent of subjects—neurosurgery patients as well as healthy volunteers. Functional MRI activation was weaker and the language centers more spread-out in the patient group. These differences may have reflected brain adaptations to slow-growing tumors or longstanding epilepsy. Five of the epilepsy patients also underwent ECS using brain electrodes, the results of which agreed well with the fMRI findings. Two patients had temporary problems with language function after surgery. In both cases, the deficits were related to surgery or complications (bleeding) in the language area identified by fMRI. Functional brain mapping is important for planning for complex neurosurgery procedures. It provides a guide for the neurosurgeon to navigate safely to the tumor or other diseased area, while avoiding damage to critical areas of the brain. An accurate, non-invasive approach to brain mapping would provide a valuable alternative to the time-consuming ECS procedure. "The proposed fast fMRI language protocol reliably localized the most relevant language areas in individual subjects," Dr. Genetti and colleagues conclude. In its current state, the new test probably isn’t suitable as the only approach to planning surgery—too many areas "light up" with fMRI, which may limit the surgeon’s ability to perform more extensive surgery with necessary confidence. The researchers add, "Rather than a substitute, our current fMRI protocol can be considered as a valuable complementary tool that can reliably guide ECS in the surgical planning of epileptogenic foci and of brain tumors."

Non-Invasive Mapping Helps to Localize Language Centers Before Brain Surgery

A new functional magnetic resonance imaging (fMRI) technique may provide neurosurgeons with a non-invasive tool to help in mapping critical areas of the brain before surgery, reports a study in the April issue of Neurosurgery, official journal of the Congress of Neurological Surgeons. The journal is published by Lippincott Williams & Wilkins, a part of Wolters Kluwer Health.

Evaluating brain fMRI responses to a “single, short auditory language task” can reliably localize critical language areas of the brain—in healthy people as well as patients requiring brain surgery for epilepsy or tumors, according to the new research by Melanie Genetti, PhD, and colleagues of Geneva University Hospitals, Switzerland.

Brief fMRI Task for Functional Brain Mapping
The researchers designed and evaluated a quick and simple fMRI task for use in functional brain mapping. Functional MRI can show brain activity in response to stimuli (in contrast to conventional brain MRI, which shows anatomy only). Before neurosurgery for severe epilepsy or brain tumors, functional brain mapping provides essential information on the location of critical brain areas governing speech and other functions.

The standard approach to brain mapping is direct electrocortical stimulation (ECS)—recording brain activity from electrodes placed on the brain surface. However, this requires several hours of testing and may not be applicable in all patients. Previous studies have compared fMRI techniques with ECS, but mainly for determining the side of language function (lateralization) rather than the precise location (localization).

The new fMRI task was developed and evaluated in 28 healthy volunteers and in 35 patients undergoing surgery for brain tumors or epilepsy. The test used a brief (eight minutes) auditory language stimulus in which the patients heard a series of sense and nonsense sentences.

Functional MRI scans were obtained to localize the brain areas activated by the language task—activated areas would “light up,” reflecting increased oxygenation. A subgroup of patients also underwent ECS, the results of which were compared to fMRI.

Non-invasive Test Accurately Localizes Critical Brain Areas
Based on responses to the language stimulus, fMRI showed activation of the anterior and posterior (front and rear) language areas of the brain in about 90 percent of subjects—neurosurgery patients as well as healthy volunteers. Functional MRI activation was weaker and the language centers more spread-out in the patient group. These differences may have reflected brain adaptations to slow-growing tumors or longstanding epilepsy.

Five of the epilepsy patients also underwent ECS using brain electrodes, the results of which agreed well with the fMRI findings. Two patients had temporary problems with language function after surgery. In both cases, the deficits were related to surgery or complications (bleeding) in the language area identified by fMRI.

Functional brain mapping is important for planning for complex neurosurgery procedures. It provides a guide for the neurosurgeon to navigate safely to the tumor or other diseased area, while avoiding damage to critical areas of the brain. An accurate, non-invasive approach to brain mapping would provide a valuable alternative to the time-consuming ECS procedure.

"The proposed fast fMRI language protocol reliably localized the most relevant language areas in individual subjects," Dr. Genetti and colleagues conclude. In its current state, the new test probably isn’t suitable as the only approach to planning surgery—too many areas "light up" with fMRI, which may limit the surgeon’s ability to perform more extensive surgery with necessary confidence. The researchers add, "Rather than a substitute, our current fMRI protocol can be considered as a valuable complementary tool that can reliably guide ECS in the surgical planning of epileptogenic foci and of brain tumors."

Filed under brain language fMRI epilepsy brain surgery brain activity medicine neuroscience science

279 notes

Scientists discover how brains change with new skills The phrase “practice makes perfect” has a neural basis in the brain. Researchers have discovered a set of common changes in the brain upon learning a new skill. They have essentially detected a neural marker for the reorganization the brain undergoes when a person practices and become proficient at a task. Successful training not only prompts skill-specific changes in the brain, but also more global changes that are consistent across many different types of skills training, the researchers report in the journal Neurorehabilitation and Neural Repair. Their results indicate that as you become more adept at a skill, your brain no longer needs to work as hard at it. The brain, they report, shifts from more controlled to more automatic processing as a skill is learned, regardless of the specific type of training, they said. “The training-related changes we found – that signify a shift to a more ‘efficient’ configuration of brain networks – provide a potential new brain marker for training effectiveness,” said neuroscientist Nathan Spreng, assistant professor of human development and the Rebecca Q. and James C. Morgan Sesquicentennial Faculty Fellow in Cornell’s College of Human Ecology. “Such neural markers are increasingly being used to inform the design of new or more-targeted interventions to improve cognitive and motor functioning in aging, brain injury or disease,” he added. The study is the most comprehensive review of the neural correlates of training to date and the first to associate training with alterations in large-scale brain networks, said Spreng, who was awarded the distinction of “rising star” in March by the Association for Psychological Science. The researchers conducted a systematic meta-analysis of 38 neuroimaging studies of cognitive and motor skills training interventions in healthy young adults – more than 500 participants in all. Using a quantitative literature review method, they analyzed functional neuroimaging data and mapped the patterns of brain activity changes before and after the training across the individual experiments. The researchers found that the brain regions that are involved in attention-demanding activities are less active after training compared with before, whereas the brain regions that typically are at rest (known as the default network), became more active. Specifically, training resulted in decreased activity in brain regions involved in effortful control and attention that closely overlap with the frontoparietal control and dorsal attention networks. Increased activity was found after training, however, in the default network that is involved in self-reflective activities, including future planning or even day dreaming. Thus, skill mastery is associated with increased activity in areas not engaged in skill performance, and this shift can be detected in the large-scale networks of the brain. “The power of meta-analysis methods to systematically and quantitatively review neuroimaging studies makes possible discoveries such as ours that can provide new insights into how the brain functions; this helps us lay the foundation for better treatments of brain disorders in the future,” said Spreng. “There have now been over 100,000 neuroimaging papers published, so these types of meta-analytic reviews offer new opportunities to identify common patterns of brain activity across a larger and more diverse array of studies,” he added. (Image: iStockphoto)

Scientists discover how brains change with new skills

The phrase “practice makes perfect” has a neural basis in the brain. Researchers have discovered a set of common changes in the brain upon learning a new skill. They have essentially detected a neural marker for the reorganization the brain undergoes when a person practices and become proficient at a task.

Successful training not only prompts skill-specific changes in the brain, but also more global changes that are consistent across many different types of skills training, the researchers report in the journal Neurorehabilitation and Neural Repair. Their results indicate that as you become more adept at a skill, your brain no longer needs to work as hard at it. The brain, they report, shifts from more controlled to more automatic processing as a skill is learned, regardless of the specific type of training, they said.

“The training-related changes we found – that signify a shift to a more ‘efficient’ configuration of brain networks – provide a potential new brain marker for training effectiveness,” said neuroscientist Nathan Spreng, assistant professor of human development and the Rebecca Q. and James C. Morgan Sesquicentennial Faculty Fellow in Cornell’s College of Human Ecology. “Such neural markers are increasingly being used to inform the design of new or more-targeted interventions to improve cognitive and motor functioning in aging, brain injury or disease,” he added.

The study is the most comprehensive review of the neural correlates of training to date and the first to associate training with alterations in large-scale brain networks, said Spreng, who was awarded the distinction of “rising star” in March by the Association for Psychological Science.

The researchers conducted a systematic meta-analysis of 38 neuroimaging studies of cognitive and motor skills training interventions in healthy young adults – more than 500 participants in all. Using a quantitative literature review method, they analyzed functional neuroimaging data and mapped the patterns of brain activity changes before and after the training across the individual experiments.

The researchers found that the brain regions that are involved in attention-demanding activities are less active after training compared with before, whereas the brain regions that typically are at rest (known as the default network), became more active.

Specifically, training resulted in decreased activity in brain regions involved in effortful control and attention that closely overlap with the frontoparietal control and dorsal attention networks. Increased activity was found after training, however, in the default network that is involved in self-reflective activities, including future planning or even day dreaming. Thus, skill mastery is associated with increased activity in areas not engaged in skill performance, and this shift can be detected in the large-scale networks of the brain.

“The power of meta-analysis methods to systematically and quantitatively review neuroimaging studies makes possible discoveries such as ours that can provide new insights into how the brain functions; this helps us lay the foundation for better treatments of brain disorders in the future,” said Spreng.

“There have now been over 100,000 neuroimaging papers published, so these types of meta-analytic reviews offer new opportunities to identify common patterns of brain activity across a larger and more diverse array of studies,” he added.

(Image: iStockphoto)

Filed under brain neural markers cognitive functioning training brain activity neuroscience science

194 notes

Avoid impulsive acts by imagining future benefits Why is it so hard for some people to resist the least little temptation, while others seem to possess incredible patience, passing up immediate gratification for a greater long-term good? The answer, suggests a new brain imaging study from Washington University in St. Louis, lies in how effective people are at feeling good right now about all the future benefits that may come from passing up a smaller immediate reward. Researchers found that activity in two regions of the brain distinguished impulsive and patient people. “Activity in one part of the brain, the anterior prefrontal cortex, seems to show whether you’re getting pleasure from thinking about the future reward you are about to receive,” explains study co-author Todd Braver, PhD, professor of psychology in Arts & Sciences. “People can relate to this idea that when you know something good is coming, just that waiting can feel pleasurable.” The study, which was published in the first issue of the Journal of Neuroscience this year, was designed to examine what happens in the brain as people wait for a reward, especially whether people characterized as “impulsive” would show different brain responses than those considered “patient.” The lead author of the study was Koji Jimura, then a postdoctoral researcher in Braver’s Cognitive Control and Psychopathology Laboratory, and now a research associate professor at the Tokyo Institute of Technology, in Japan. Unlike previous research on delayed gratification that had people choose between hypothetical rewards of money over long delays (e.g, $500 now or $1,000 a year from now), this Washington University study presented their participants with real rewards of squirts of juice that they chose to receive either immediately or after a delay of up to a minute. “It’s kind of funny because we treated the people in our study like researchers that work with animals do, and we actually squirted juice into their mouths,” Braver says. Results show that a brain region called the ventral striatum (VS) ramped up its activity in impulsive people as they got closer and closer to receiving their delayed reward. The VS activity of patient people, on the other hand, stayed more constant. The researchers interpreted these different brain responses to mean that impulsive people initially did not find the prospect of waiting for a reward very appealing. However, as they approached the time they’d receive that reward, they became more excited and their VS reflected that excitement. “This gradual increase may reflect impatience or excessive anticipation of the upcoming reward in impulsive individuals,” says Jimura. This was unlike patient people, who were likely content with waiting for the reward from the start, as no changes in VS activity were observed for them. The most novel finding of the study concerned the anterior prefrontal cortex (aPFC). This is the part of the brain that helps you think about the future. Here, we found that the patient people heightened activity in the aPFC when they first started waiting for they reward, which then decreased as the time to receive the reward approached. Impulsive people didn’t show this brain activity pattern. “The aPFC appears to allow you to create a mental simulation of the future. It helps you consider what it’ll be like getting the future reward. In this way, you can get access to the utility and satisfaction in the present,” says Braver. By thinking about the future reward, patient people were able to gain what economists call “anticipatory utility.” While their reward was far away in time, they were giddy with anticipation in the present. Conversely, impulsive people weren’t thinking beyond the present and so did not feel pleasure when they were told they had to wait. Their excitement built only as they got closer to receiving their reward. Overall this study suggests that people may be impulsive because they do not or cannot imagine the future, so they prefer rewards right away. This research could be useful for assessing the effects of clinical treatments for impulsivity problems, which can lead to issues such as problem gambling and substance abuse disorders. A similar brain imaging approach as was used in the Washington University study could allow clinicians to track the effects of an intervention on changes not only in impulsive behavior but also changes in patients’ brain responses. “One possible treatment approach could be to enhance mental functions in aPFC, a brain region well-known to be associated with cognitive control,” says Jimura. By increasing cognitive control, impulsive patients could learn to reject their immediate impulses. Impulsivity occurs not only in a clinical setting but also every day in our own lives. Applying his research to his personal life, Braver says, “When I’m successful at achieving long-term goals it’s from explicitly trying to activate that goal and imagining each decision as helping me achieve it, to keep me on track.” Perhaps adopting this strategy of focusing on the long-term could help us move past present distractions and move toward our future goals.

Avoid impulsive acts by imagining future benefits

Why is it so hard for some people to resist the least little temptation, while others seem to possess incredible patience, passing up immediate gratification for a greater long-term good?

The answer, suggests a new brain imaging study from Washington University in St. Louis, lies in how effective people are at feeling good right now about all the future benefits that may come from passing up a smaller immediate reward. Researchers found that activity in two regions of the brain distinguished impulsive and patient people.

“Activity in one part of the brain, the anterior prefrontal cortex, seems to show whether you’re getting pleasure from thinking about the future reward you are about to receive,” explains study co-author Todd Braver, PhD, professor of psychology in Arts & Sciences. “People can relate to this idea that when you know something good is coming, just that waiting can feel pleasurable.”

The study, which was published in the first issue of the Journal of Neuroscience this year, was designed to examine what happens in the brain as people wait for a reward, especially whether people characterized as “impulsive” would show different brain responses than those considered “patient.”

The lead author of the study was Koji Jimura, then a postdoctoral researcher in Braver’s Cognitive Control and Psychopathology Laboratory, and now a research associate professor at the Tokyo Institute of Technology, in Japan.

Unlike previous research on delayed gratification that had people choose between hypothetical rewards of money over long delays (e.g, $500 now or $1,000 a year from now), this Washington University study presented their participants with real rewards of squirts of juice that they chose to receive either immediately or after a delay of up to a minute.

“It’s kind of funny because we treated the people in our study like researchers that work with animals do, and we actually squirted juice into their mouths,” Braver says.

Results show that a brain region called the ventral striatum (VS) ramped up its activity in impulsive people as they got closer and closer to receiving their delayed reward. The VS activity of patient people, on the other hand, stayed more constant.

The researchers interpreted these different brain responses to mean that impulsive people initially did not find the prospect of waiting for a reward very appealing. However, as they approached the time they’d receive that reward, they became more excited and their VS reflected that excitement.

“This gradual increase may reflect impatience or excessive anticipation of the upcoming reward in impulsive individuals,” says Jimura. This was unlike patient people, who were likely content with waiting for the reward from the start, as no changes in VS activity were observed for them.

The most novel finding of the study concerned the anterior prefrontal cortex (aPFC). This is the part of the brain that helps you think about the future. Here, we found that the patient people heightened activity in the aPFC when they first started waiting for they reward, which then decreased as the time to receive the reward approached. Impulsive people didn’t show this brain activity pattern.

“The aPFC appears to allow you to create a mental simulation of the future. It helps you consider what it’ll be like getting the future reward. In this way, you can get access to the utility and satisfaction in the present,” says Braver.

By thinking about the future reward, patient people were able to gain what economists call “anticipatory utility.” While their reward was far away in time, they were giddy with anticipation in the present. Conversely, impulsive people weren’t thinking beyond the present and so did not feel pleasure when they were told they had to wait. Their excitement built only as they got closer to receiving their reward.

Overall this study suggests that people may be impulsive because they do not or cannot imagine the future, so they prefer rewards right away. This research could be useful for assessing the effects of clinical treatments for impulsivity problems, which can lead to issues such as problem gambling and substance abuse disorders. A similar brain imaging approach as was used in the Washington University study could allow clinicians to track the effects of an intervention on changes not only in impulsive behavior but also changes in patients’ brain responses.

“One possible treatment approach could be to enhance mental functions in aPFC, a brain region well-known to be associated with cognitive control,” says Jimura. By increasing cognitive control, impulsive patients could learn to reject their immediate impulses.

Impulsivity occurs not only in a clinical setting but also every day in our own lives. Applying his research to his personal life, Braver says, “When I’m successful at achieving long-term goals it’s from explicitly trying to activate that goal and imagining each decision as helping me achieve it, to keep me on track.” Perhaps adopting this strategy of focusing on the long-term could help us move past present distractions and move toward our future goals.

Filed under brain brain activity prefrontal cortex impulsivity reward pleasure neuroscience science

272 notes

Scientists Decode Dreams With Brain Scans It used to be that what happened in your dreams was your own little secret. But today scientists report for the first time that they’ve successfully decoded details of people’s dreams using brain scans. Before you reach for your tin hat, you should know that the scientists managed this feat only with the full cooperation of their research subjects, and they only decoded dreams after the fact, not in real time. The thought police won’t be busting you for renting bowling shoes from Saddam Hussein or whatever else you’ve been up to in your dreams. All the same, the work is yet another impressive step for researchers interested in decoding mental states from brain activity, and it opens the door to a new way of studying dreaming, one of the most mysterious and fascinating aspects of the human experience. In the first part of the new study, neuroscientist Yukiyasu Kamitani and colleagues at the Advanced Telecommunications Research Institute International in Kyoto, Japan monitored three young men as they tried to get some sleep inside an fMRI scanner while the machine monitored their brain activity. The researchers also monitored each volunteer’s brain activity with EEG electrodes, and when they saw an EEG signature indicative of dreaming, they woke him up to ask what he’d been dreaming about. Technically speaking, this is what researchers call ”hypnagogic imagery,” the dream-like state that occurs as people fall asleep. In the interest of saving time, Kamitani and colleagues chose to study this type of imagery rather than the dreams that tend to occur during REM sleep later in the night. They woke up each subject at least 200 times over the course of several days to build up a database of dream reports. In the second part of the experiment, Kamitani and colleagues developed a visual imagery decoder based on machine learning algorithms. They trained the decoder to classify patterns of brain activity recorded from the same three men while they were awake and watching a video montage of hundreds of images selected from several online databases. After the decoder for each person had been trained, the researchers could input a pattern of brain activity and have the decoder predict which image was most likely to have produced that pattern of brain activity. But that much has been done before. Where Kamitani’s team went beyond previous work was in feeding the decoder patterns of brain activity collected while the subjects were dreaming. This enabled them to correctly identify objects the men had seen in their dreams, they report Apr. 4 in Science. Or rather, they could identify the type of object a subject had seen: it could predict that a man had dreamt about a car, not that he’d been cruising around in a Maserati. And the decoder only worked when the researchers gave it a pair of possible objects to chose from (whether it was a man or a chair, for example). “Our dream decoding is still very primitive,” Kamitani said. Decoding color, action, or emotion is also still beyond the scope of the technology, Kamitani says. Also, it only seems to work for imagery that occurred — at most — about 15 seconds before waking up. Finally, the decoder is unique to each person. To decode the dreams of another person, the team would have to train up a new decoder by having that person view hundreds of images. Even so, it’s remarkable that it works as well as it does, says neuroscientist Jack Gallant of the University of California, Berkeley and a pioneer of decoding mental states from brain scans. ”It took just a huge amount of non-glamorous work to do this, and they deserve big props for that,” Gallant said. With refinements, Gallant says the method could be useful for studying the nature and function of dreams. “There’s the classic question of when you dream are you actively generating these movies in your head, or is it that when you wake up you’re essentially confabulating it,” Gallant said. “What this shows you is there’s at least some correspondence between what the brain is doing during dreaming and what it’s doing when you’re awake.” Kamitani is thinking about the possibilities too. ”One theory states that dreaming is for strengthening memory, but another theory states dreaming is for forgetting,” he said. “We could record the frequency of decoded dream contents for each memory item and see the correlation between the frequency and the memory performance.”

Scientists Decode Dreams With Brain Scans

It used to be that what happened in your dreams was your own little secret. But today scientists report for the first time that they’ve successfully decoded details of people’s dreams using brain scans.

Before you reach for your tin hat, you should know that the scientists managed this feat only with the full cooperation of their research subjects, and they only decoded dreams after the fact, not in real time. The thought police won’t be busting you for renting bowling shoes from Saddam Hussein or whatever else you’ve been up to in your dreams.

All the same, the work is yet another impressive step for researchers interested in decoding mental states from brain activity, and it opens the door to a new way of studying dreaming, one of the most mysterious and fascinating aspects of the human experience.

In the first part of the new study, neuroscientist Yukiyasu Kamitani and colleagues at the Advanced Telecommunications Research Institute International in Kyoto, Japan monitored three young men as they tried to get some sleep inside an fMRI scanner while the machine monitored their brain activity. The researchers also monitored each volunteer’s brain activity with EEG electrodes, and when they saw an EEG signature indicative of dreaming, they woke him up to ask what he’d been dreaming about.

Technically speaking, this is what researchers call ”hypnagogic imagery,” the dream-like state that occurs as people fall asleep. In the interest of saving time, Kamitani and colleagues chose to study this type of imagery rather than the dreams that tend to occur during REM sleep later in the night. They woke up each subject at least 200 times over the course of several days to build up a database of dream reports.

In the second part of the experiment, Kamitani and colleagues developed a visual imagery decoder based on machine learning algorithms. They trained the decoder to classify patterns of brain activity recorded from the same three men while they were awake and watching a video montage of hundreds of images selected from several online databases. After the decoder for each person had been trained, the researchers could input a pattern of brain activity and have the decoder predict which image was most likely to have produced that pattern of brain activity.

But that much has been done before. Where Kamitani’s team went beyond previous work was in feeding the decoder patterns of brain activity collected while the subjects were dreaming. This enabled them to correctly identify objects the men had seen in their dreams, they report Apr. 4 in Science. Or rather, they could identify the type of object a subject had seen: it could predict that a man had dreamt about a car, not that he’d been cruising around in a Maserati. And the decoder only worked when the researchers gave it a pair of possible objects to chose from (whether it was a man or a chair, for example).

“Our dream decoding is still very primitive,” Kamitani said.

Decoding color, action, or emotion is also still beyond the scope of the technology, Kamitani says. Also, it only seems to work for imagery that occurred — at most — about 15 seconds before waking up.

Finally, the decoder is unique to each person. To decode the dreams of another person, the team would have to train up a new decoder by having that person view hundreds of images.

Even so, it’s remarkable that it works as well as it does, says neuroscientist Jack Gallant of the University of California, Berkeley and a pioneer of decoding mental states from brain scans. ”It took just a huge amount of non-glamorous work to do this, and they deserve big props for that,” Gallant said.

With refinements, Gallant says the method could be useful for studying the nature and function of dreams.

“There’s the classic question of when you dream are you actively generating these movies in your head, or is it that when you wake up you’re essentially confabulating it,” Gallant said. “What this shows you is there’s at least some correspondence between what the brain is doing during dreaming and what it’s doing when you’re awake.”

Kamitani is thinking about the possibilities too. ”One theory states that dreaming is for strengthening memory, but another theory states dreaming is for forgetting,” he said. “We could record the frequency of decoded dream contents for each memory item and see the correlation between the frequency and the memory performance.”

Filed under brain activity neural activity sleep dreaming dreams dream decoding fMRI neuroscience science

51 notes

EEG Identifies Seizures in Hospital Patients Electroencephalogram (EEG), which measures and records electrical activity in the brain, is a quick and efficient way of determining whether seizures are the cause of altered mental status (AMS) and spells, according to a study by scientists at the UC San Francisco. The research, which focused on patients who had been given an EEG after being admitted to the hospital for symptoms such as AMS and spells, appears on March 27 in Mayo Clinic Proceedings. “We have demonstrated a surprisingly high frequency of seizures – more than 7 percent – in a general inpatient population,” said senior investigator John Betjemann, MD, a UCSF assistant professor of neurology. “This tells us that EEG is an underutilized diagnostic tool, and that seizures may be an underappreciated cause of spells and AMS.” The results are important, he said, because EEG can identify treatable causes of AMS or spells, and because “it can prompt the physician to look for an underlying reason for seizures in persons who did previously have them.” Seizures are treatable with a number of FDA-approved anticonvulsants, he said, “so patients who are quickly diagnosed can be treated more rapidly and effectively. This may translate to shorter lengths of stay and improved patient outcomes.” In one of the first studies of its kind, Betjemann and his team analyzed the medical records of 1,048 adults who were admitted to a regular inpatient unit of a tertiary care hospital and who underwent an EEG. They found that 7.4 percent of the patients had a seizure of some kind while being monitored. “As I tell my patients, seizures come in all different flavors, from a dramatic convulsion to a subtle twitching of the face or hand or finger,” said Betjemann. “There might be no outward manifestation at all, other than that the person seems a little spacey. It’s easily missed by family members and physicians alike, but can be picked up by EEG.” Another 13.4 percent of patients had epileptiform discharges, which are abnormal patterns that indicate patients are at an increased risk of seizures. Almost 65 percent of patients had their first seizure within one hour of EEG recording, and 89 percent within six hours. “This is good news for smaller hospitals that don’t have 24 hour EEG coverage, but that do have a technician on duty during the day,” Betjemann said. He speculated that lack of 24-hour coverage is a major reason that EEG is not used as an inpatient diagnostic tool as often as it might be. “This paper shows that, fortunately, it’s not necessary. Almost two thirds of patients with seizures can be identified in the first hour, and almost 90 percent in the course of a shift.” EEGs are easy to obtain, painless and noninvasive, said Betjemann. “The technician applies some paste and electrodes and hooks up the machine. All the patient has to do is rest in bed.” Betjemann said that the next logical research step would be a prospective study. “We have to start at the beginning, see if patients are altered when they are admitted, and do an EEG in a formal standardized setting. Then we’d want to see how often EEG is changing the management of patients – either starting or stopping medications,” he said. “A patient may be having spells, and an EEG might tell you this is not a seizure, and that it’s important not to treat it with anti-epileptic medications.” (Image: Rex Features)

EEG Identifies Seizures in Hospital Patients

Electroencephalogram (EEG), which measures and records electrical activity in the brain, is a quick and efficient way of determining whether seizures are the cause of altered mental status (AMS) and spells, according to a study by scientists at the UC San Francisco.

The research, which focused on patients who had been given an EEG after being admitted to the hospital for symptoms such as AMS and spells, appears on March 27 in Mayo Clinic Proceedings.

“We have demonstrated a surprisingly high frequency of seizures – more than 7 percent – in a general inpatient population,” said senior investigator John Betjemann, MD, a UCSF assistant professor of neurology. “This tells us that EEG is an underutilized diagnostic tool, and that seizures may be an underappreciated cause of spells and AMS.”

The results are important, he said, because EEG can identify treatable causes of AMS or spells, and because “it can prompt the physician to look for an underlying reason for seizures in persons who did previously have them.”

Seizures are treatable with a number of FDA-approved anticonvulsants, he said, “so patients who are quickly diagnosed can be treated more rapidly and effectively. This may translate to shorter lengths of stay and improved patient outcomes.”

In one of the first studies of its kind, Betjemann and his team analyzed the medical records of 1,048 adults who were admitted to a regular inpatient unit of a tertiary care hospital and who underwent an EEG. They found that 7.4 percent of the patients had a seizure of some kind while being monitored.

“As I tell my patients, seizures come in all different flavors, from a dramatic convulsion to a subtle twitching of the face or hand or finger,” said Betjemann. “There might be no outward manifestation at all, other than that the person seems a little spacey. It’s easily missed by family members and physicians alike, but can be picked up by EEG.”

Another 13.4 percent of patients had epileptiform discharges, which are abnormal patterns that indicate patients are at an increased risk of seizures.

Almost 65 percent of patients had their first seizure within one hour of EEG recording, and 89 percent within six hours.

“This is good news for smaller hospitals that don’t have 24 hour EEG coverage, but that do have a technician on duty during the day,” Betjemann said.

He speculated that lack of 24-hour coverage is a major reason that EEG is not used as an inpatient diagnostic tool as often as it might be. “This paper shows that, fortunately, it’s not necessary. Almost two thirds of patients with seizures can be identified in the first hour, and almost 90 percent in the course of a shift.”

EEGs are easy to obtain, painless and noninvasive, said Betjemann. “The technician applies some paste and electrodes and hooks up the machine. All the patient has to do is rest in bed.”

Betjemann said that the next logical research step would be a prospective study. “We have to start at the beginning, see if patients are altered when they are admitted, and do an EEG in a formal standardized setting. Then we’d want to see how often EEG is changing the management of patients – either starting or stopping medications,” he said. “A patient may be having spells, and an EEG might tell you this is not a seizure, and that it’s important not to treat it with anti-epileptic medications.”

(Image: Rex Features)

Filed under electroencephalogram EEG brain activity seizures neuroscience science

73 notes

Pesticide combination affects bees’ ability to learn Two new studies have highlighted a negative impact on bees’ ability to learn following exposure to a combination of pesticides commonly used in agriculture. The researchers found that the pesticides, used in the research at levels shown to occur in the wild, could interfere with the learning circuits in the bee’s brain. They also found that bees exposed to combined pesticides were slower to learn or completely forgot important associations between floral scent and food rewards. In the study published today (27 March 2013) in Nature Communications, the University of Dundee’s Dr Christopher Connolly and his team investigated the impact on bees’ brains of two common pesticides: pesticides used on crops called neonicotinoid pesticides, and another type of pesticide, coumaphos, that is used in honeybee hives to kill the Varroa mite, a parasitic mite that attacks the honey bee. The intact bees’ brains were exposed to pesticides in the lab at levels predicted to occur following exposure in the wild and brain activity was recorded. They found that both types of pesticide target the same area of the bee brain involved in learning, causing a loss of function. If both pesticides were used in combination, the effect was greater. The study is the first to show that these pesticides have a direct impact on pollinator brain physiology. It was prompted by the work of collaborators Dr Geraldine Wright and Dr Sally Williamson at Newcastle University who found that combinations of these same pesticides affected learning and memory in bees. Their studies established that when bees had been exposed to combinations of these pesticides for 4 days, as many as 30% of honeybees failed to learn or performed poorly in memory tests. Again, the experiments mimicked levels that could be seen in the wild, this time by feeding a sugar solution mixed with appropriate levels of pesticides. Dr Geraldine Wright said: “Pollinators perform sophisticated behaviours while foraging that require them to learn and remember floral traits associated with food. Disruption in this important function has profound implications for honeybee colony survival, because bees that cannot learn will not be able to find food.” Together the researchers expressed concerns about the use of pesticides that target the same area of the brain of insects and the potential risk of toxicity to non-target insects. Moreover, they said that exposure to different combinations of pesticides that act at this site may increase this risk. Dr Christopher Connolly said: “Much discussion of the risks posed by the neonicotinoid insecticides has raised important questions of their suitability for use in our environment. However, little consideration has been given to the miticidal pesticides introduced directly into honeybee hives to protect the bees from the Varroa mite. We find that both have negative impact on honeybee brain function. "Together, these studies highlight potential dangers to pollinators of continued exposure to pesticides that target the insect nervous system and the importance of identifying combinations of pesticides that could profoundly impact pollinator survival."

Pesticide combination affects bees’ ability to learn

Two new studies have highlighted a negative impact on bees’ ability to learn following exposure to a combination of pesticides commonly used in agriculture. The researchers found that the pesticides, used in the research at levels shown to occur in the wild, could interfere with the learning circuits in the bee’s brain. They also found that bees exposed to combined pesticides were slower to learn or completely forgot important associations between floral scent and food rewards.

In the study published today (27 March 2013) in Nature Communications, the University of Dundee’s Dr Christopher Connolly and his team investigated the impact on bees’ brains of two common pesticides: pesticides used on crops called neonicotinoid pesticides, and another type of pesticide, coumaphos, that is used in honeybee hives to kill the Varroa mite, a parasitic mite that attacks the honey bee.

The intact bees’ brains were exposed to pesticides in the lab at levels predicted to occur following exposure in the wild and brain activity was recorded. They found that both types of pesticide target the same area of the bee brain involved in learning, causing a loss of function. If both pesticides were used in combination, the effect was greater.

The study is the first to show that these pesticides have a direct impact on pollinator brain physiology. It was prompted by the work of collaborators Dr Geraldine Wright and Dr Sally Williamson at Newcastle University who found that combinations of these same pesticides affected learning and memory in bees. Their studies established that when bees had been exposed to combinations of these pesticides for 4 days, as many as 30% of honeybees failed to learn or performed poorly in memory tests. Again, the experiments mimicked levels that could be seen in the wild, this time by feeding a sugar solution mixed with appropriate levels of pesticides.

Dr Geraldine Wright said: “Pollinators perform sophisticated behaviours while foraging that require them to learn and remember floral traits associated with food. Disruption in this important function has profound implications for honeybee colony survival, because bees that cannot learn will not be able to find food.”

Together the researchers expressed concerns about the use of pesticides that target the same area of the brain of insects and the potential risk of toxicity to non-target insects. Moreover, they said that exposure to different combinations of pesticides that act at this site may increase this risk.

Dr Christopher Connolly said: “Much discussion of the risks posed by the neonicotinoid insecticides has raised important questions of their suitability for use in our environment. However, little consideration has been given to the miticidal pesticides introduced directly into honeybee hives to protect the bees from the Varroa mite. We find that both have negative impact on honeybee brain function.

"Together, these studies highlight potential dangers to pollinators of continued exposure to pesticides that target the insect nervous system and the importance of identifying combinations of pesticides that could profoundly impact pollinator survival."

Filed under bees pesticides learning brain activity brain function memory neuroscience science

free counters