Posts tagged brain activity
Articles and news from the latest research reports.
Study links hippocampus with unconscious bias
The hippocampus is an area of the brain known to be one in which links between memories are formed, but until now it was not known that this brain region is involved in steering the brain towards making particular choices over others when faced with new decisions for which we have no previous experiences to draw on.
In a paper published in the journal Science, research psychologists G. Elliott Wimmer and Daphna Shohamy of Columbia University in New York report on their study, which used functional magnetic resonance imaging (fMRI) of regions of the brain. In the study, they asked 31 volunteers to complete a three-part task while in the machine. Throughout the task their brain activity was determined by the fMRI.
The results suggest that several areas of the brain are involved in evaluating new stimuli and associating them with previous memories, but the process is strongly associated with the hippocampus.
The findings could have application, for example, in the design of new products, which could incorporate aspects of earlier products (such as color, logo or font) to stimulate the association and produce an unconscious bias towards those products over other equally new products.
The findings also suggest that misguided biases such as racism could stem from unconscious associations. (Guilt by association is a commonly known bias.) These biases have long been known, but the current study clearly shows their association with the hippocampus.
Is this the most unpleasant sound in the world?
The ear-splitting screech of a knife on a glass bottle has been identified as the worst sound to the human ear by scientists who studied the brain’s response to unpleasant noises.
People who listened to a series of 74 recordings while having their brain activity measured by an MRI scanner rated the sound of a fork on a glass as the second worst noise, followed by chalk on a blackboard.
The scans revealed that unpleasant sounds provoked a stronger response in the brain than pleasant ones such as the noise of blubbing water. While sounds are processed in the brain’s auditory cortex, uncomfortable noises activate the amygdala, a separate brain region which processes emotions.
The researchers studied a group of 13 volunteers and found that sounds with a frequency of between 2,000 and 5,000 Hz, the range at which our ears are the most sensitive, were the hardest to bear.
Although it remains unclear why our ears are most sensitive to this type of sound, researchers noted that screams, which we naturally find uncomfortable, fall within the same range.
Dr Sukhbinder Kumar of Newcastle University, author of the study, which was published in the Journal of Neuroscience, said: “It appears there is something very primitive kicking in. It’s a possible distress signal from the amygdala to the auditory cortex.”
His colleague Prof Tim Griffiths added: “This might be a new inroad into emotional disorders and disorders like tinnitus and migraine, in which there seems to be heightened perception of the unpleasant aspects of sounds.”
The Circuitry of Uncertainty
The human brain likes to make predictions about how the world works. Imagine, for example, that you move to a new town. At first, you don’t know where to go for dinner. But after weeks of trying different restaurants, you pick a favorite, a little Thai place that makes the best green curry. Several months later, however, you notice the curry isn’t as spicy and the vegetables seem undercooked. At first you give your favorite place the benefit of the doubt. But after a few more so-so dinners, you suddenly realize that something must have changed—perhaps the owner hired a new chef—and your notion that this is the best place around is no longer valid. So you begin searching for a new favorite restaurant.
Neuroscientists have long been interested in this adaptability, particularly in the moment when an individual discards an old belief and begins to formulate a new one. “You go from being confident in your model of the world to being uncertain and then abandoning the model altogether,” says Alla Karpova, a group leader at the Howard Hughes Medical Institute’s Janelia Farm Research Campus. She and her colleagues wondered what goes on in the brain when this happens. In rats, they found that the rejection of an old belief correlates with abrupt changes in activity in the medial prefrontal cortex, a brain region involved in cognitive functions such as reward anticipation and decision-making. The team’s research is published in the October 5, 2012, issue of Science.
Whether you like someone can affect how your brain processes their actions, according to new research from the Brain and Creativity Institute at the USC Dornsife College of Letters, Arts and Sciences.
Most of the time, watching someone else move causes a “mirroring” effect — that is, the parts of our brains responsible for motor skills are activated by watching someone else in action.
But a study by USC researchers appearing in PLOS ONE shows that whether you like the person you’re watching can actually have an effect on brain activity related to motor actions and lead to “differential processing” — for example, thinking the person you dislike is moving more slowly than they actually are.
“We address the basic question of whether social factors influence our perception of simple actions,” said Lisa Aziz-Zadeh, assistant professor with the Brain and Creativity Institute and the Division of Occupational Science. “These results indicate that an abstract sense of group membership, and not only differences in physical appearance, can affect basic sensory-motor processing.”
The BCMI-MIdAS (Brain-Computer Music Interface for Monitoring and Inducing Affective States) project
The central purpose of the project is to develop technology for building innovative intelligent systems that can monitor our affective state, and induce specific affective states through music, automatically and adaptively. This is a highly interdisciplinary project, which will address several technical challenges at the interface between science, technology and performing arts/music (incorporating computer-generated music and machine learning).
Research questions
- How can music change affective states and what are the specific musical traits (i.e., the parameters of a piece of music) that elicit such states?
- How can we control such traits in a piece of music in order to induce specific affective states in a participant?
- How can we effectively detect information about affective states induced by music in the EEG signal, going beyond EEG asymmetry and characterising information contained in synchronisation patterns?
- How can we use the EEG to monitor the affective state induced by music on-line (i.e., in “real-time”)?
- How can we produce a generative music system capable of generating music embodying musical traits aimed at inducing specific affective states, observable in the EEG of the participant?
- How can we build an intelligent adaptive system for monitoring and inducing affective states through music on-line?
(Source: cmr.soc.plymouth.ac.uk)
At this year’s Tokyo Games Show, Japanese purveyor of electronically-augmented fashion Neurowear unveiled the successor to its Necomimi brain-activated cat ears. It’s called Shippo, and it’s a brain-controlled motorized tail that responds to the user’s current emotional state with corresponding wagging.
Shippo requires a NeuroSky electroencephalograph (EEG) headset, alongside a clip-on heart monitor, in order to observe brain activity and pick up on the user’s emotional state. This information is then translated to wagging, which will be soft and slow or hard and fast, depending on whether one is relaxing or excited/anxious. The EEG headset communicates with the fluffy appendage via a Bluetooth connection.
Neuroscientists are trying to work out why the brain does so much when it seems to be doing nothing at all.
For volunteers, a brain-scanning experiment can be pretty demanding. Researchers generally ask participants to do something — solve mathematics problems, search a scene for faces or think about their favoured political leaders — while their brains are being imaged.
But over the past few years, some researchers have been adding a bit of down time to their study protocols. While subjects are still lying in the functional magnetic resonance imaging (fMRI) scanners, the researchers ask them to try to empty their minds. The aim is to find out what happens when the brain simply idles. And the answer is: quite a lot.
Mark Mallman plans to create music for seven straight days and nights by wiring himself up to sensors that translate his brain waves into music around the clock.
(Source: wired.co.uk)
Network of neurons: a dynamic model of brain activity
Looking at a tangled mass of network cables plugged into a crowded router doesn’t yield much insight into the network traffic that runs through the hardware.
Similarly, Lynn H. Matthias Professor of Electrical and Computer Engineering Barry Van Veen says that looking at the three pounds of interwoven neurons that make up the hardware of the human brain doesn’t give the complete picture of the brain activity that supports human cognition and consciousness.
Working with multiple collaborators, Van Veen has applied signal analysis techniques to the electric or magnetic fields measured noninvasively at the scalp through electroencephalography (EEG) or magnetoencephalography (MEG) to develop methods for identifying network models of brain function — essentially, traffic patterns of neural activity present in the human brain.
"It’s analogous to coming up with a new microscope," says Van Veen.
Having a reliable traffic map of normal brain function provides a baseline for comparison for understanding how different disorders, substances and devices affect the brain. “Now that we’ve got the tool ready, the opportunities to try it out on scientifically interesting questions are really blossoming,” says Van Veen.
For instance, network models may provide a better blueprint for how medical devices can interface with the brain. Van Veen recently began working with biomedical engineering Associate Professor Justin Williams to apply his work toward making better brain-machine interfaces.
But the implications of network models go beyond engineering questions. The effect of alcohol on the brain just begs for network analysis, according to Van Veen. The network model could allow researchers to see precisely which parts of the brain are altered by alcohol consumption. It could provide insight into how short-term memory works, help explain the effects of schizophrenia and monitor treatment, help measure the depth and effectiveness of different types of anesthesia, and even help give insight into the brain activity that precedes — or prevents — a miraculous recovery from a coma.
"We’re developing this tool as a significant improvement over what people have had access to before," says Van Veen. "The possibilities for using it to study different aspects of brain function are nearly unlimited."
(Source: news.wisc.edu)
Scientists Read Monkeys’ Inner Thoughts: Brain Activity Decoded While Monkeys Avoid Obstacle to Touch Target
ScienceDaily (July 19, 2012) — By decoding brain activity, scientists were able to “see” that two monkeys were planning to approach the same reaching task differently — even before they moved a muscle.
The obstacle-avoidance task is a variation on the center-out reaching task in which an obstacle sometimes prevents the monkey from moving directly to the target. The monkey must first place a cursor (yellow) on the central target (purple). This was the starting position. After the first hold, a second target appeared (green). After the second hold an obstacle appeared (red box). After the third hold, the center target disappeared, indicating a “go” for the monkey, which then moved the cursor out and around the obstacle to the target. (Credit: Moran/Pearce)
Anyone who has looked at the jagged recording of the electrical activity of a single neuron in the brain must have wondered how any useful information could be extracted from such a frazzled signal.
But over the past 30 years, researchers have discovered that clear information can be obtained by decoding the activity of large populations of neurons.
Now, scientists at Washington University in St. Louis, who were decoding brain activity while monkeys reached around an obstacle to touch a target, have come up with two remarkable results.
Their first result was one they had designed their experiment to achieve: they demonstrated that multiple parameters can be embedded in the firing rate of a single neuron and that certain types of parameters are encoded only if they are needed to solve the task at hand.
Their second result, however, was a complete surprise. They discovered that the population vectors could reveal different planning strategies, allowing the scientists, in effect, to read the monkeys’ minds.