Posts tagged brain activity
Articles and news from the latest research reports.
A Load Off Your Mind
Engineering professors are devising a brain scanner that will sense when you’re going into information overload
Picture an air-traffic controller tracking 10 planes approaching an airport. Now imagine he’s having trouble focusing on all 10 aircraft, perhaps because he’s been up all night or just has a lot on his mind. What would happen if his computer sensed his mental fatigue, removed one plane from his oversight and reassigned it to a controller who just started her shift?
The scenario might seem like science fiction, but with new technology being developed by Tufts researchers Robert Jacob and Sergio Fantini, it could be quite real someday. Jacob and Fantini have developed a brain-scanning device that allows a computer to sense the level of mental exertion of its user and adjust tasks accordingly to achieve the correct balance between boredom and overload.
“Humans and computers are two powerful information processors connected by this miserably narrow bandwidth—a mouse and a keyboard,” says Jacob, a professor of computer science in the School of Engineering. Jacob’s challenge is to find ways to create a more direct connection between machine and human brain to make both more efficient.
Pinpointing the Brain’s Arbitrator
We tend to be creatures of habit. In fact, the human brain has a learning system that is devoted to guiding us through routine, or habitual, behaviors. At the same time, the brain has a separate goal-directed system for the actions we undertake only after careful consideration of the consequences. We switch between the two systems as needed. But how does the brain know which system to give control to at any given moment? Enter The Arbitrator.
Researchers at the California Institute of Technology (Caltech) have, for the first time, pinpointed areas of the brain—the inferior lateral prefrontal cortex and frontopolar cortex—that seem to serve as this “arbitrator” between the two decision-making systems, weighing the reliability of the predictions each makes and then allocating control accordingly. The results appear in the current issue of the journal Neuron.
According to John O’Doherty, the study’s principal investigator and director of the Caltech Brain Imaging Center, understanding where the arbitrator is located and how it works could eventually lead to better treatments for brain disorders, such as drug addiction, and psychiatric disorders, such as obsessive-compulsive disorder. These disorders, which involve repetitive behaviors, may be driven in part by malfunctions in the degree to which behavior is controlled by the habitual system versus the goal-directed system.
"Now that we have worked out where the arbitrator is located, if we can find a way of altering activity in this area, we might be able to push an individual back toward goal-directed control and away from habitual control," says O’Doherty, who is also a professor of psychology at Caltech. "We’re a long way from developing an actual treatment based on this for disorders that involve over-egging of the habit system, but this finding has opened up a highly promising avenue for further research."
In the study, participants played a decision-making game on a computer while connected to a functional magnetic resonance imaging (fMRI) scanner that monitored their brain activity. Participants were instructed to try to make optimal choices in order to gather coins of a certain color, which were redeemable for money.
During a pre-training period, the subjects familiarized themselves with the game—moving through a series of on-screen rooms, each of which held different numbers of red, yellow, or blue coins. During the actual game, the participants were told which coins would be redeemable each round and given a choice to navigate right or left at two stages, knowing that they would collect only the coins in their final room. Sometimes all of the coins were redeemable, making the task more habitual than goal-directed. By altering the probability of getting from one room to another, the researchers were able to further test the extent of participants’ habitual and goal-directed behavior while monitoring corresponding changes in their brain activity.
With the results from those tests in hand, the researchers were able to compare the fMRI data and choices made by the subjects against several computational models they constructed to account for behavior. The model that most accurately matched the experimental data involved the two brain systems making separate predictions about which action to take in a given situation. Receiving signals from those systems, the arbitrator kept track of the reliability of the predictions by measuring the difference between the predicted and actual outcomes for each system. It then used those reliability estimates to determine how much control each system should exert over the individual’s behavior. In this model, the arbitrator ensures that the system making the most reliable predictions at any moment exerts the greatest degree of control over behavior.
"What we’re showing is the existence of higher-level control in the human brain," says Sang Wan Lee, lead author of the new study and a postdoctoral scholar in neuroscience at Caltech. "The arbitrator is basically making decisions about decisions."
In line with previous findings from the O’Doherty lab and elsewhere, the researchers saw in the brain scans that an area known as the posterior putamen was active at times when the model predicted that the habitual system should be calculating prediction values. Going a step further, they examined the connectivity between the posterior putamen and the arbitrator. What they found might explain how the arbitrator sets the weight for the two learning systems: the connection between the arbitrator area and the posterior putamen changed according to whether the goal-directed or habitual system was deemed to be more reliable. However, no such connection effects were found between the arbitrator and brain regions involved in goal-directed learning. This suggests that the arbitrator may work mainly by modulating the activity of the habitual system.
"One intriguing possibility arising from these findings, which we will need to test in future work, is that being in a habitual mode of behavior may be the default state," says O’Doherty. "So when the arbitrator determines you need to be more goal-directed in your behavior, it accomplishes this by inhibiting the activity of the habitual system, almost like pressing the breaks on your car when you are in drive."
How Your Memory Rewrites the Past
Your memory is a wily time traveler, plucking fragments of the present and inserting them into the past, reports a new Northwestern Medicine® study. In terms of accuracy, it’s no video camera.
Rather, the memory rewrites the past with current information, updating your recollections with new experiences.
Love at first sight, for example, is more likely a trick of your memory than a Hollywood-worthy moment.
“When you think back to when you met your current partner, you may recall this feeling of love and euphoria,” said lead author Donna Jo Bridge, a postdoctoral fellow in medical social sciences at Northwestern University Feinberg School of Medicine. “But you may be projecting your current feelings back to the original encounter with this person.”
The study is published Feb. 5 in the Journal of Neuroscience.
This the first study to show specifically how memory is faulty, and how it can insert things from the present into memories of the past when those memories are retrieved. The study shows the exact point in time when that incorrectly recalled information gets implanted into an existing memory.
To help us survive, Bridge said, our memories adapt to an ever-changing environment and help us deal with what’s important now.
“Our memory is not like a video camera,” Bridge said. “Your memory reframes and edits events to create a story to fit your current world. It’s built to be current.”
All that editing happens in the hippocampus, the new study found. The hippocampus, in this function, is the memory’s equivalent of a film editor and special effects team.
For the experiment, 17 men and women studied 168 object locations on a computer screen with varied backgrounds such as an underwater ocean scene or an aerial view of Midwest farmland. Next, researchers asked participants to try to place the object in the original location but on a new background screen. Participants would always place the objects in an incorrect location.
For the final part of the study, participants were shown the object in three locations on the original screen and asked to choose the correct location. Their choices were: the location they originally saw the object, the location they placed it in part 2 or a brand new location.
“People always chose the location they picked in part 2,” Bridge said. “This shows their original memory of the location has changed to reflect the location they recalled on the new background screen. Their memory has updated the information by inserting the new information into the old memory.”
Participants took the test in an MRI scanner so scientists could observe their brain activity. Scientists also tracked participants’ eye movements, which sometimes were more revealing about the content of their memories – and if there was conflict in their choices — than the actual location they ended up choosing.
The notion of a perfect memory is a myth, said Joel Voss, senior author of the paper and an assistant professor of medical social sciences and of neurology at Feinberg.
“Everyone likes to think of memory as this thing that lets us vividly remember our childhoods or what we did last week,” Voss said. “But memory is designed to help us make good decisions in the moment and, therefore, memory has to stay up-to-date. The information that is relevant right now can overwrite what was there to begin with.”
Bridge noted the study’s implications for eyewitness court testimony. “Our memory is built to change, not regurgitate facts, so we are not very reliable witnesses,” she said.
A caveat of the research is that it was done in a controlled experimental setting and shows how memories changed within the experiment. “Although this occurred in a laboratory setting, it’s reasonable to think the memory behaves like this in the real world,” Bridge said.
(Source: northwestern.edu)
Brain Scans Show We Take Risks Because We Can’t Stop Ourselves
A new study correlating brain activity with how people make decisions suggests that when individuals engage in risky behavior, such as drunk driving or unsafe sex, it’s probably not because their brains’ desire systems are too active, but because their self-control systems are not active enough.
This might have implications for how health experts treat mental illness and addiction or how the legal system assesses a criminal’s likelihood of committing another crime.
Researchers from The University of Texas at Austin, UCLA and elsewhere analyzed data from 108 subjects who sat in a magnetic resonance imaging (MRI) scanner — a machine that allows researchers to pinpoint brain activity in vivid, three-dimensional images — while playing a video game that simulates risk-taking.
The researchers used specialized software to look for patterns of activity across the whole brain that preceded a person’s making a risky choice or a safe choice in one set of subjects. Then they asked the software to predict what other subjects would choose during the game based solely on their brain activity. The software accurately predicted people’s choices 71 percent of the time.
“These patterns are reliable enough that not only can we predict what will happen in an additional test on the same person, but on people we haven’t seen before,” said Russell Poldrack, director of UT Austin’s Imaging Research Center and professor of psychology and neuroscience.
When the researchers trained their software on much smaller regions of the brain, they found that just analyzing the regions typically involved in executive functions such as control, working memory and attention was enough to predict a person’s future choices. Therefore, the researchers concluded, when we make risky choices, it is primarily because of the failure of our control systems to stop us.
“We all have these desires, but whether we act on them is a function of control,” said Sarah Helfinstein, a postdoctoral researcher at UT Austin and lead author of the study that appears online this week in the journal Proceedings of the National Academy of Sciences.
Helfinstein said that additional research could focus on how external factors, such as peer pressure, lack of sleep or hunger, weaken the activity of our brains’ control systems when we contemplate risky decisions.
“If we can figure out the factors in the world that influence the brain, we can draw conclusions about what actions are best at helping people resist risks,” said Helfinstein.
To simulate features of real-world risk-taking, the researchers used a video game called the Balloon Analogue Risk Task (BART) that past research has shown correlates well with self-reported risk-taking such as drug and alcohol use, smoking, gambling, driving without a seatbelt, stealing and engaging in unprotected sex.
While playing the BART, the subject sees a balloon on the screen and is asked to make either a risky choice (inflate the balloon a little and earn a few cents) or a safe choice (stop the round and “cash out,” keeping whatever money was earned up to that point). Sometimes inflating the balloon causes it to burst and the player loses all the cash earned from that round. After each successful balloon inflation, the game continues with the chance of earning another standard-sized reward or losing an increasingly large amount. Many health-relevant risky decisions share this same structure, such as when deciding how many alcoholic beverages to drink before driving home or how much one can experiment with drugs or cigarettes before developing an addiction.
The data for this study came from the Consortium for Neuropsychiatric Phenomics at UCLA, which recruited adults from the Los Angeles area for researchers to examine differences in response inhibition and working memory between healthy adults and patients diagnosed with bipolar disorder, schizophrenia, or adult attention deficit hyperactivity disorder (ADHD). Only data collected from healthy participants were included in the present analyses.
Autistic Brains Create More Information at Rest
New research from Case Western Reserve University and University of Toronto neuroscientists finds that the brains of autistic children generate more information at rest – a 42% increase on average. The study offers a scientific explanation for the most typical characteristic of autism – withdrawal into one’s own inner world. The excess production of information may explain a child’s detachment from their environment.
Published at the end of December in Frontiers in Neuroinformatics, this study is a follow-up to the authors’ prior finding that brain connections are different in autistic children. This paper determined that the differences account for the increased complexity within their brains.
“Our results suggest that autistic children are not interested in social interactions because their brains generate more information at rest, which we interpret as more introspection in line with early descriptions of the disorder,” said Roberto Fernández Galán, PhD, senior author and associate professor of neurosciences at Case Western Reserve School of Medicine.
The authors quantified information as engineers normally do but instead of applying it to signals in electronic devices, they applied it to brain activity recorded with magnetoencephalography (MEG). They showed that autistic children’s brains at rest generate more information than non-autistic children. This may explain their lack of interest in external stimuli, including interactions with other people.
The researchers also quantified interactions between brain regions, i.e., the brain’s functional connectivity, and determined the inputs to the brain in the resting state allowing them to interpret the children’s introspection level.
“This is a novel interpretation because it is a different attempt to understand the children’s cognition by analyzing their brain activity,” said José L. Pérez Velázquez, PhD, first author and professor of neuroscience at University of Toronto Institute of Medical Science and Department of Pediatrics, Brain and Behavior Center.
“Measuring cognitive processes is not trivial; yet, our findings indicate that this can be done to some extent with well-established mathematical tools from physics and engineering.”
This study provides quantitative support for the relatively new “Intense World Theory” of autism proposed by neuroscientists Henry and Kamila Markram of the Brain Mind Institute in Switzerland, which describes the disorder as the result of hyper-functioning neural circuitry, leading to a state of over-arousal. More generally, the work of Galán and Pérez Velázquez is an initial step in the investigation of how information generation in the brain relates to cognitive/psychological traits and will begin to frame neurophysiological data into psychological aspects. The team now aims to apply a similar approach to patients with schizophrenia.
Brain structure, function predict future memory performance in children, adolescents
Assessing structural and functional changes in the brain may predict future memory performance in healthy children and adolescents, according to a study appearing January 29 in The Journal of Neuroscience. The findings shed new light on cognitive development and suggest MRI and other tools may one day help identify children at risk for developmental challenges earlier than current testing methods allow.
Working memory capacity — the ability to hold onto information for a short period of time — is one of the strongest predictors of future achievements in math and reading. While previous studies showed that MRI could predict current working memory performance in children, scientists were unsure if MRI could predict their future cognitive capacity.
In the current study, Henrik Ullman, Rita Almeida, PhD, and Torkel Klingberg, MD, PhD, at the Karolinska Institutet in Sweden evaluated the cognitive abilities of a group of healthy children and adolescents and measured each child’s brain structure and function using MRI. Based on the MRI data collected during this initial testing, the researchers found they could predict the children’s working memory performance two years later, a prediction that was not possible using the cognitive tests.
“Our results suggest that future cognitive development can be predicted from anatomical and functional information offered by MRI above and beyond that currently achieved by cognitive tests,” said Ullman, the lead author of the study. “This has wide implications for understanding the neural mechanisms of cognitive development.”
The scientists recruited 62 children and adolescents between the ages of 6 and 20 years to the lab, where they completed working memory and reasoning tests. They also received multiple MRI scans to assess brain structure and changes in brain activity as they performed a working memory task. Two years later, the group returned to the lab to perform the same cognitive tests.
Using a statistical model, the researchers evaluated whether MRI data obtained during the initial tests correlated with the children’s working memory performance during the follow-up visit. They found that while brain activity in the frontal cortex correlated with children’s working memory at the time of the initial tests, activity in the basal ganglia and thalamus predicted how well children scored on the working memory tests two years later.
“This study is another contribution to the growing body of neuroimaging research that yields insights into unraveling present and predicting future cognitive capacity in development,” said Judy Illes, PhD, a neuroethicist at the University of British Columbia. “However, the appreciation of this important new knowledge is simpler than its application to everyday life. How a child performs today and tomorrow relies on multiple positive and negative life events that cannot be assessed by today’s technology alone.”
(Source: alphagalileo.org)
Expanding our view of vision
Every time you open your eyes, visual information flows into your brain, which interprets what you’re seeing. Now, for the first time, MIT neuroscientists have noninvasively mapped this flow of information in the human brain with unique accuracy, using a novel brain-scanning technique.
This technique, which combines two existing technologies, allows researchers to identify precisely both the location and timing of human brain activity. Using this new approach, the MIT researchers scanned individuals’ brains as they looked at different images and were able to pinpoint, to the millisecond, when the brain recognizes and categorizes an object, and where these processes occur.
“This method gives you a visualization of ‘when’ and ‘where’ at the same time. It’s a window into processes happening at the millisecond and millimeter scale,” says Aude Oliva, a principal research scientist in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).
Oliva is the senior author of a paper describing the findings in the Jan. 26 issue of Nature Neuroscience. Lead author of the paper is CSAIL postdoc Radoslaw Cichy. Dimitrios Pantazis, a research scientist at MIT’s McGovern Institute for Brain Research, is also an author of the paper.
Honesty beats dishonesty for making you feel good
A University of Toronto report based on two neural imaging studies that monitored brain activity has found a reward given for telling the truth gives people greater satisfaction than the same reward given for deceit.
These studies were published recently in the neuroscience journals Neuropsychologia and NeuroImage.
"Our findings together show that people typically find truth-telling to be more rewarding than lying in different types of deceptive situations,” said Professor Kang Lee,whose research is funded in part by the Social Sciences and Humanities Research Council.
The findings are based on two studies of Chinese participants using a new neuroimaging method called near-infrared spectroscopy. The studies are among the first to address the question of whether lying makes people feel better or worse than telling the truth.
The studies explored two different types of deception. In first-order deception, the recipient does not know the deceiver is lying. In second-order deception, the deceivers are fully aware that the recipient knows their intention, such as bluffing in poker.
The researchers were surprised to find that a liar’s cortical reward system was more active when a reward was gained through truth-telling than lying. This was true in both types of deception.
Researchers also found that in both types of deception, telling a lie produced greater brain activations than telling the truth in the frontal lobe, suggesting lying is cognitively more taxing than truth-telling and uses more neural resources.
The researchers hope this study will advance understanding of the neural mechanisms underlying lying, a ubiquitous and frequent human behaviour, and help to diagnose pathological liars who may have different neural responses when lying or telling the truth.
Training your brain using neurofeedback
A new brain-imaging technique enables people to ‘watch’ their own brain activity in real time and to control or adjust function in pre-determined brain regions. The study from the Montreal Neurological Institute and Hospital – The Neuro, McGill University and the McGill University Health Centre, published in NeuroImage, is the first to demonstrate that magnetoencephalography (MEG) can be used as a potential therapeutic tool to control and train specific targeted brain regions. This advanced brain-imaging technology has important clinical applications for numerous neurological and neuropsychiatric conditions.
MEG is a non-invasive imaging technology that measures magnetic fields generated by nerve cell circuits in the brain. MEG captures these tiny magnetic fields with remarkable accuracy and has unrivaled time resolution - a millisecond time scale across the entire brain. “This means you can observe your own brain activity as it happens,” says Dr. Sylvain Baillet, acting Director of the Brain Imaging Centre at The Neuro and lead investigator on the study. “We can use MEG for neurofeedback – a process by which people can see on-going physiological information that they aren’t usually aware of, in this case, their own brain activity, and use that information to train themselves to self-regulate. Our ultimate hope and aim is to enable patients to train specific regions of their own brain, in a way that relates to their particular condition. For example neurofeedback can be used by people with epilepsy so that they could train to modify brain activity in order to avoid a seizure.”
In this proof of concept study, participants had nine sessions in the MEG and used neurofeedback to reach a specific target. The target was to look at a coloured disc on a display screen and find their own strategy to change the disc’s colour from dark red to bright yellow white, and to maintain that bright colour for as long as possible. The disc colour was indexed on a very specific aspect of their ongoing brain activity: the researchers had set it up so that the experiment was accessing predefined regions of the motor cortex in the participants’ brain. The colour presented was changing according to a predefined combination of slow and faster brain activity within these regions. This was possible because the researchers combined MEG with MRI, which provides information on the brain’s structures, known as magnetic source imaging (MSI).
“The remarkable thing is that with each training session, the participants were able to reach the target aim faster, even though we were raising the bar for the target objective in each session, the way you raise the bar each time in a high jump competition. These results showed that participants were successfully using neurofeedback to alter their pattern of brain activity according to a predefined objective in specific regions of their brain’s motor cortex, without moving any body part. This demonstrates that MEG source imaging can provide brain region-specific real time neurofeedback and that longitudinal neurofeedback training is possible with this technique.”
These findings pave the way for MEG as an innovative therapeutic approach for treating patients. To date, work with epilepsy patients has shown the most promise but there is great potential to use MEG to investigate other neurological syndromes and neuropsychiatric disorders (e.g., stroke, dementia, movement disorders, chronic depression, etc). MEG has potential to reveal dynamics of brain activity involved in perception, cognition and behaviour: it has provided unique insight on brain functions (language, motor control, visual and auditory perception, etc.) and dysfunctions (movement disorders, tinnitus, chronic pain, dementia, etc.).
Dr. Baillet and his team are collaborating presently with Prof. Isabelle Peretz at Université de Montréal to use this technique with people that have amusia, a disorder that makes them unable to process musical pitch. It is hypothesized that amusia results from poor connectivity between the auditory cortex and prefrontal regions in the brain. In an ongoing study, the team is measuring the intensity of functional connectivity between these brain regions in amusic patients and aged-matched healthy controls. Using MEG-neurofeedback, they hope to take advantage of the brain’s plasticity to reinforce the functional connectivity between the target brain regions. If the approach demonstrates an improvement in pitch discrimination in participants, that will demonstrate the clinical and rehabilitative applications of this approach. The baseline measurements have been taken already, and the training sessions will take place over this year.
(Source: mcgill.ca)
Speech means using both sides of our brain
We use both sides of our brain for speech, a finding by researchers at New York University and NYU Langone Medical Center that alters previous conceptions about neurological activity. The results, which appear in the journal Nature, also offer insights into addressing speech-related inhibitions caused by stroke or injury and lay the groundwork for better rehabilitation methods.
“Our findings upend what has been universally accepted in the scientific community—that we use only one side of our brains for speech,” says Bijan Pesaran, an associate professor in NYU’s Center for Neural Science and the study’s senior author. “In addition, now that we have a firmer understanding of how speech is generated, our work toward finding remedies for speech afflictions is much better informed.”
Many in the scientific community have posited that both speech and language are lateralized—that is, we use only one side of our brains for speech, which involves listening and speaking, and language, which involves constructing and understanding sentences. However, the conclusions pertaining to speech generally stem from studies that rely on indirect measurements of brain activity, raising questions about characterizing speech as lateralized.
To address this matter, the researchers directly examined the connection between speech and the neurological process.
Specifically, the study relied on data collected at NYU ECoG, a center where brain activity is recorded directly from patients implanted with specialized electrodes placed directly inside and on the surface of the brain while the patients are performing sensory and cognitive tasks. Here, the researchers examined brain functions of patients suffering from epilepsy by using methods that coincided with their medical treatment.
“Recordings directly from the human brain are a rare opportunity,” says Thomas Thesen, director of the NYU ECoG Center and co-author of the study.
“As such, they offer unparalleled spatial and temporal resolution over other imaging technologies to help us achieve a better understanding of complex and uniquely human brain functions, such as language,” adds Thesen, an assistant professor at NYU Langone.
In their examination, the researchers tested the parts of the brain that were used during speech. Here, the study’s subjects were asked to repeat two “non-words”—“kig” and “pob.” Using non-words as a prompt to gauge neurological activity, the researchers were able to isolate speech from language.
An analysis of brain activity as patients engaged in speech tasks showed that both sides of the brain were used—that is, speech is, in fact, bi-lateral.
“Now that we have greater insights into the connection between the brain and speech, we can begin to develop new ways to aid those trying to regain the ability to speak after a stroke or injuries resulting in brain damage,” observes Pesaran. “With this greater understanding of the speech process, we can retool rehabilitation methods in ways that isolate speech recovery and that don’t involve language.”
(Source: nyu.edu)