This is your brain on Vivaldi and Beatles

Listening to music activates large networks in the brain, but different kinds of music are processed differently. A team of researchers from Finland, Denmark and the UK has developed a new method for studying music processing in the brain during a realistic listening situation. Using a combination of brain imaging and computer modeling, they found areas in the auditory, motor, and limbic regions to be activated during free listening to music. They were furthermore able to pinpoint differences in the processing between vocal and instrumental music. The new method helps us to understand better the complex brain dynamics of brain networks and the processing of lyrics in music. The study was published in the journal NeuroImage.

Using functional magnetic resonance imaging (fMRI), the research team, led by Dr. Vinoo Alluri from the University of Jyväskylä, Finland, recorded the brain responses of individuals while they were listening to music from different genres, including pieces by Antonio Vivaldi, Miles Davis, Booker T. & the M.G.’s, The Shadows, Astor Piazzolla, and The Beatles. Following this, they analyzed the musical content of the pieces using sophisticated computer algorithms to extract musical features related to timbre, rhythm and tonality. Using a novel cross-validation method, they subsequently located activated brain areas that were common across the different musical stimuli.

The study revealed that activations in several areas in the brain belonging to the auditory, limbic, and motor regions were activated by all musical pieces. Notable, areas in the medial orbitofrontal region and the anterior cingulate cortex, which are relevant for self-referential appraisal and aesthetic judgments, were found to be activated during the listening. A further interesting finding was that vocal and instrumental music were processed differently. In particular, the presence of lyrics was found to shift the processing of musical features towards the right auditory cortex, which suggests a left-hemispheric dominance in the processing of the lyrics. This result is in line with previous research, but now for the first time observed during continuous listening to music.

"The new method provides a powerful means to predict brain responses to music, speech, and soundscapes across a variety of contexts", says Dr. Vinoo Alluri.

Sleep deprivation linked to junk food cravings

A sleepless night makes us more likely to reach for doughnuts or pizza than for whole grains and leafy green vegetables, suggests a new study from UC Berkeley that examines the brain regions that control food choices. The findings shed new light on the link between poor sleep and obesity.

Using functional magnetic resonance imaging (fMRI), UC Berkeley researchers scanned the brains of 23 healthy young adults, first after a normal night’s sleep and next, after a sleepless night. They found impaired activity in the sleep-deprived brain’s frontal lobe, which governs complex decision-making, but increased activity in deeper brain centers that respond to rewards. Moreover, the participants favored unhealthy snack and junk foods when they were sleep deprived.

“What we have discovered is that high-level brain regions required for complex judgments and decisions become blunted by a lack of sleep, while more primal brain structures that control motivation and desire are amplified,” said Matthew Walker, a UC Berkeley professor of psychology and neuroscience and senior author of the study published today (Tuesday, Aug. 6) in the journal Nature Communications.

Moreover, he added, “high-calorie foods also became significantly more desirable when participants were sleep-deprived. This combination of altered brain activity and decision-making may help explain why people who sleep less also tend to be overweight or obese.”

Previous studies have linked poor sleep to greater appetites, particularly for sweet and salty foods, but the latest findings provide a specific brain mechanism explaining why food choices change for the worse following a sleepless night, Walker said.

“These results shed light on how the brain becomes impaired by sleep deprivation, leading to the selection of more unhealthy foods and, ultimately, higher rates of obesity,” said Stephanie Greer, a doctoral student in Walker’s Sleep and Neuroimaging Laboratory and lead author of the paper. Another co-author of the study is Andrea Goldstein, also a doctoral student in Walker’s lab.

In this newest study, researchers measured brain activity as participants viewed a series of 80 food images that ranged from high-to low-calorie and healthy and unhealthy, and rated their desire for each of the items. As an incentive, they were given the food they most craved after the MRI scan.

Food choices presented in the experiment ranged from fruits and vegetables, such as strawberries, apples and carrots, to high-calorie burgers, pizza and doughnuts. The latter are examples of the more popular choices following a sleepless night.

On a positive note, Walker said, the findings indicate that “getting enough sleep is one factor that can help promote weight control by priming the brain mechanisms governing appropriate food choices.”

Could the Government Get a Search Warrant for Your Thoughts?

We don’t have a mind reading machine. But what if we one day did? The technique of functional MRI (fMRI), which measures changes in localized brain activity over time, can now be used to infer information regarding who we are thinking about, what we have seen, and the memories we are recalling. As the technology for inferring thought from brain activity continues to improve, the legal questions regarding its potential application in criminal and civil trials are gaining greater attention.

Last year, a Maryland man on trial for murdering his roommate tried to introduce results from an fMRI-based lie detection test to bolster his claim that the death was a suicide. The court ruled (PDF) the test results inadmissible, noting that the “fMRI lie detection method of testing is not yet accepted in the scientific community.” In a decision last year to exclude fMRI lie detection test results submitted by a defendant in a different case, the Sixth Circuit was even more skeptical, writing (PDF) that “there are concerns with not only whether fMRI lie detection of ‘real lies’ has been tested but whether it can be tested.”

So far, concerns regarding reliability have kept thought-inferring brain measurements out of U.S. (but not foreign) courtrooms. But is technology the only barrier? Or, if more mature, reliable brain scanning methods for detecting truthfulness and reading thoughts are developed in the future, could they be employed not only by defendants hoping to demonstrate innocence but also by prosecutors attempting to establish guilt? Could prosecutors armed with a search warrant compel an unwilling suspect to submit to brain scans aimed at exploring his or her innermost thoughts?

The answer surely ought to be no. But getting to that answer isn’t as straightforward as it might seem. The central constitutional question relates to the Fifth Amendment, which states that “no person … shall be compelled in any criminal case to be a witness against himself.” In interpreting the Fifth Amendment, courts have distinguished between testimonial evidence, which is protected from compelled self-incriminating disclosure, and physical evidence, which is not. A suspected bank robber cannot refuse to participate in a lineup or provide fingerprints. But he or she can decline to answer a detective who asks, “Did you rob the bank last week?”

So is the information in a brain scan physical or testimonial? In some respects, it’s a mix of both. As Dov Fox wrote in a 2009 law review article, “Brain imaging is difficult to classify because it promises distinctly testimonial-like information about the content of a person’s mind that is packaged in demonstrably physical-like form, either as blood flows in the case of fMRI, or as brainwaves in the case of EEG.” Fox goes on to conclude that the compelled use of brain imaging techniques would “deprive individuals of control over their thoughts” and be a violation of the Fifth Amendment.

But there is an alternative view as well, under which the Fifth Amendment protects only testimonial communication, leaving the unexpressed thoughts in a suspect’s head potentially open to government discovery, technology permitting. In a recent law review article titled “A Modest Defense of Mind Reading,” Kiel Brennan-Marquez writes that “at least some mind-reading devices almost certainly would not” elicit “communicative acts” by the suspect, “making their use permissible under the Fifth Amendment.” Brennan-Marquez acknowledges that compelled mind-reading would raise privacy concerns, but argues that those should be addressed by the Fourth Amendment, which prohibits unreasonable searches and seizures.

That doesn’t seem right. It would make little sense to provide constitutional protection to a suspected bank robber’s refusal to answer a detective’s question if the thoughts preceding the refusal—e.g., “since I’m guilty, I’d better not answer this question”—are left unprotected. Stated another way, the right to remain silent would be meaningless if not accompanied by protection for the thinking required to exercise it.

And if that weren’t enough, concluding that compelled brain scans don’t violate the Fifth Amendment would raise another problem as well: In a future that might include mature mind-reading technology, it would leave the Fourth Amendment as the last barrier protecting our thoughts from unwanted discovery. That, in turn, would raise the possibility that the government could get a search warrant for our thoughts. It’s a chilling prospect, and one that we should hope never comes to pass.

Patience reaps rewards

Brain imaging shows how prolonged treatment of a behavioral disorder restores a normal response to rewards

Attention-deficit/hyperactivity disorder (ADHD) is characterized by abnormal behavioral traits such as inattention, impulsivity and hyperactivity. It is also associated with impaired processing of reward in the brain, meaning that patients need much greater rewards to become motivated. One of the common treatments for ADHD, methylphenidate (MPH), is known to improve reward processing in the short term, but the long-term effects have remained unclear.

Kei Mizuno from the RIKEN Center for Life Science Technologies, in collaboration with colleagues from several other Japanese research institutions, has now demonstrated that prolonged treatment with MPH brings about stable changes in brain activity that improve reward processing with a commensurate improvement in ADHD symptoms.

ADHD is thought to affect up to 5% of children worldwide, and about half of those will go on to experience symptoms of the disorder into adulthood. MPH treats the disorder by increasing the levels of the brain chemical dopamine, which is involved in reward processing.

To understand the effect of MPH on ADHD symptoms and specifically reward processing over the longer term, the researchers studied the reward response behavior of ADHD and healthy patients—all children or adolescents—before and after treatment with osmotic release oral system (OROS) MPH. They used functional magnetic resonance imaging (fMRI) to measure brain activity during a task that saw participants rewarded with payment, but in two different scenarios: a high and a low monetary reward condition.

“In the high monetary reward condition, participants earned higher than the expected reward; whereas in the low monetary condition, participants earned an average reward that was consistently lower than expected,” says Mizuno.

The brain images showed that before treatment with OROS-MPH, ADHD patients had lower than normal sensitivity to reward, as demonstrated by their abnormally low brain activity in two parts of the brain associated with reward processing—the nucleus accumbens and the thalamus—during testing under the low monetary reward scenario.

However, after three months of treatment with OROS-MPH, there was no difference in the activity of these brain areas in ADHD patients compared with the healthy controls under any of the reward conditions. Their sensitivity to reward had returned to normal, and the patients’ other ADHD symptoms also showed improvement.

Mizuno says that this study goes further than previous work. “We knew that acute MPH treatment improves reward processing in ADHD,” he explains. “Now we’ve revealed that decreased reward sensitivity and ADHD symptoms are improved by treatment for three months.”

Researchers Identify Emotions Based on Brain Activity

For the first time, scientists at Carnegie Mellon University have identified which emotion a person is experiencing based on brain activity.

The study, published in the June 19 issue of PLOS ONE, combines functional magnetic resonance imaging (fMRI) and machine learning to measure brain signals to accurately read emotions in individuals. Led by researchers in CMU’s Dietrich College of Humanities and Social Sciences, the findings illustrate how the brain categorizes feelings, giving researchers the first reliable process to analyze emotions. Until now, research on emotions has been long stymied by the lack of reliable methods to evaluate them, mostly because people are often reluctant to honestly report their feelings. Further complicating matters is that many emotional responses may not be consciously experienced.

Identifying emotions based on neural activity builds on previous discoveries by CMU’s Marcel Just and Tom M. Mitchell, which used similar techniques to create a computational model that identifies individuals’ thoughts of concrete objects, often dubbed “mind reading.”

“This research introduces a new method with potential to identify emotions without relying on people’s ability to self-report,” said Karim Kassam, assistant professor of social and decision sciences and lead author of the study. “It could be used to assess an individual’s emotional response to almost any kind of stimulus, for example, a flag, a brand name or a political candidate.”

One challenge for the research team was find a way to repeatedly and reliably evoke different emotional states from the participants. Traditional approaches, such as showing subjects emotion-inducing film clips, would likely have been unsuccessful because the impact of film clips diminishes with repeated display. The researchers solved the problem by recruiting actors from CMU’s School of Drama.

“Our big breakthrough was my colleague Karim Kassam’s idea of testing actors, who are experienced at cycling through emotional states. We were fortunate, in that respect, that CMU has a superb drama school,” said George Loewenstein, the Herbert A. Simon University Professor of Economics and Psychology.

For the study, 10 actors were scanned at CMU’s Scientific Imaging & Brain Research Center while viewing the words of nine emotions: anger, disgust, envy, fear, happiness, lust, pride, sadness and shame. While inside the fMRI scanner, the actors were instructed to enter each of these emotional states multiple times, in random order.

Another challenge was to ensure that the technique was measuring emotions per se, and not the act of trying to induce an emotion in oneself. To meet this challenge, a second phase of the study presented participants with pictures of neutral and disgusting photos that they had not seen before. The computer model, constructed from using statistical information to analyze the fMRI activation patterns gathered for 18 emotional words, had learned the emotion patterns from self-induced emotions. It was able to correctly identify the emotional content of photos being viewed using the brain activity of the viewers.

To identify emotions within the brain, the researchers first used the participants’ neural activation patterns in early scans to identify the emotions experienced by the same participants in later scans. The computer model achieved a rank accuracy of 0.84. Rank accuracy refers to the percentile rank of the correct emotion in an ordered list of the computer model guesses; random guessing would result in a rank accuracy of 0.50.

Next, the team took the machine learning analysis of the self-induced emotions to guess which emotion the subjects were experiencing when they were exposed to the disgusting photographs.  The computer model achieved a rank accuracy of 0.91. With nine emotions to choose from, the model listed disgust as the most likely emotion 60 percent of the time and as one of its top two guesses 80 percent of the time.

Finally, they applied machine learning analysis of neural activation patterns from all but one of the participants to predict the emotions experienced by the hold-out participant. This answers an important question: If we took a new individual, put them in the scanner and exposed them to an emotional stimulus, how accurately could we identify their emotional reaction? Here, the model achieved a rank accuracy of 0.71, once again well above the chance guessing level of 0.50.

“Despite manifest differences between people’s psychology, different people tend to neurally encode emotions in remarkably similar ways,” noted Amanda Markey, a graduate student in the Department of Social and Decision Sciences.

A surprising finding from the research was that almost equivalent accuracy levels could be achieved even when the computer model made use of activation patterns in only one of a number of different subsections of the human brain.

“This suggests that emotion signatures aren’t limited to specific brain regions, such as the amygdala, but produce characteristic patterns throughout a number of brain regions,” said Vladimir Cherkassky, senior research programmer in the Psychology Department.

The research team also found that while on average the model ranked the correct emotion highest among its guesses, it was best at identifying happiness and least accurate in identifying envy. It rarely confused positive and negative emotions, suggesting that these have distinct neural signatures. And, it was least likely to misidentify lust as any other emotion, suggesting that lust produces a pattern of neural activity that is distinct from all other emotional experiences.

Just, the D.O. Hebb University Professor of Psychology, director of the university’s Center for Cognitive Brain Imaging and leading neuroscientist, explained, “We found that three main organizing factors underpinned the emotion neural signatures, namely the positive or negative valence of the emotion, its intensity — mild or strong, and its sociality — involvement or non-involvement of another person. This is how emotions are organized in the brain.”

In the future, the researchers plan to apply this new identification method to a number of challenging problems in emotion research, including identifying emotions that individuals are actively attempting to suppress and multiple emotions experienced simultaneously, such as the combination of joy and envy one might experience upon hearing about a friend’s good fortune.

Fiber-optic pen helps see inside brains of children with learning disabilities

For less than $100, University of Washington researchers have designed a computer-interfaced drawing pad that helps scientists see inside the brains of children with learning disabilities while they read and write.

The device and research using it to study the brain patterns of children will be presented June 18 at the Organization for Human Brain Mapping meeting in Seattle. A paper describing the tool, developed by the UW’s Center on Human Development and Disability, was published this spring in Sensors, an online open-access journal. “Scientists needed a tool that allows them to see in real time what a person is writing while the scanning is going on in the brain,” said Thomas Lewis, director of the center’s Instrument Development Laboratory. “We knew that fiber optics were an appropriate tool. The question was, how can you use a fiber-optic device to track handwriting?”

To create the system, Lewis and fellow engineers Frederick Reitz and Kelvin Wu hollowed out a ballpoint pen and inserted two optical fibers that connect to a light-tight box in an adjacent control room where the pen’s movement is recorded. They also created a simple wooden square pad to hold a piece of paper printed with continuously varying color gradients. The custom pen and pad allow researchers to record handwriting during functional magnetic resonance imaging, or fMRI, to assess behavior and brain function at the same time.Other researchers have developed fMRI-compatible writing devices, but “I think it does something similar for a tenth of the cost,” Reitz said of the UW system. By using supplies already found in most labs (such as a computer), the rest of the supplies – pen, fiber optics, wooden pad and printed paper – cost less than $100.The device connects to a computer with software that records every aspect of the handwriting, from stroke order to speed, hesitations and liftoffs. Understanding how these physical patterns correlate with a child’s brain patterns can help scientists understand the neural connections involved.

Researchers studied 11- and 14-year-olds with either dyslexia or dysgraphia, a handwriting and letter-processing disorder, as well as children without learning disabilities. Subjects looked at printed directions on a screen while their heads were inside the fMRI scanner. The pen and pad were on a foam pad on their laps.

Subjects were given four-minute blocks of reading and writing tasks. Then they were asked to simply think about writing an essay (they later wrote the essay when not using the fMRI). Just thinking about writing caused many of the same brain responses as actual writing would.

“If you picture yourself writing a letter, there’s a part of the brain that lights up as if you’re writing the letter,” said Todd Richards, professor of radiology and principal investigator of the UW Integrated Brain Imaging Center. “When you imagine yourself writing, it’s almost as if you’re actually writing, minus the motion problems.”

Richards and his staff are just starting to analyze the data they’ve collected from about three dozen subjects, but they have already found some surprising results.

“There are certain centers and neural pathways that we didn’t necessarily expect” to be activated, Richards said. “There are language pathways that are very well known. Then there are other motor pathways that allow you to move your hands. But how it all connects to the hand and motion is still being understood.”

Besides learning disorders, the inexpensive pen and pad also could help researchers study diseases in adults, especially conditions that cause motor control problems, such as stroke, multiple sclerosis and Parkinson’s disease.

“There are several diseases where you cannot move your hand in a smooth way or you’re completely paralyzed,” Richards said. “The beauty is it’s all getting recorded with every stroke, and this device would help us to study these neurological diseases.”