Brain’s language center has multiple roles

A century and a half ago, French physician Pierre Paul Broca found that patients with damage to part of the brain’s frontal lobe were unable to speak more than a few words. Later dubbed Broca’s area, this region is believed to be critical for speech production and some aspects of language comprehension.

However, in recent years neuroscientists have observed activity in Broca’s area when people perform cognitive tasks that have nothing to do with language, such as solving math problems or holding information in working memory. Those findings have stimulated debate over whether Broca’s area is specific to language or plays a more general role in cognition.

A new study from MIT may help resolve this longstanding question. The researchers, led by Nancy Kanwisher, the Walter A. Rosenblith Professor of Cognitive Neuroscience, found that Broca’s area actually consists of two distinct subunits. One of these focuses selectively on language processing, while the other is part of a brainwide network that appears to act as a central processing unit for general cognitive functions.

“I think we’ve shown pretty convincingly that there are two distinct bits that we should not be treating as a single region, and perhaps we shouldn’t even be talking about “Broca’s area” because it’s not a functional unit,” says Evelina Fedorenko, a research scientist in Kanwisher’s lab and lead author of the new study, which recently appeared in the journal Current Biology.

Kanwisher and Fedorenko are members of MIT’s Department of Brain and Cognitive Sciences and the McGovern Institute for Brain Research. John Duncan, a professor of neuroscience at the Cognition and Brain Sciences Unit of the Medical Research Council in the United Kingdom, is also an author of the paper.

A general role

Broca’s area is located in the left inferior frontal cortex, above and behind the left eye. For this study, the researchers set out to pinpoint the functions of distinct sections of Broca’s area by scanning subjects with functional magnetic resonance imaging (fMRI) as they performed a variety of cognitive tasks.

To locate language-selective areas, the researchers asked subjects to read either meaningful sentences or sequences of nonwords. A subset of Broca’s area lit up much more when the subjects processed meaningful sentences than when they had to interpret nonwords.

The researchers then measured brain activity as the subjects performed easy and difficult versions of general cognitive tasks, such as doing a math problem or holding a set of locations in memory. Parts of Broca’s area lit up during the more demanding versions of those tasks. Critically, however, these regions were spatially distinct from the regions involved in the language task.

These data allowed the researchers to map, for each subject, two distinct regions of Broca’s area — one selectively involved in language, the other involved in responding to many demanding cognitive tasks. The general region surrounds the language region, but the exact shapes and locations of the borders between the two vary from person to person.

The general-function region of Broca’s area appears to be part of a larger network sometimes called the multiple demand network, which is active when the brain is tackling a challenging task that requires a great deal of focus. This network is distributed across frontal and parietal lobes in both hemispheres of the brain, and all of its components appear to communicate with one another. The language-selective section of Broca’s area also appears to be part of a larger network devoted to language processing, spread throughout the brain’s left hemisphere.

Mapping functions

The findings provide evidence that Broca’s area should not be considered to have uniform functionality, says Peter Hagoort, a professor of cognitive neuroscience at Radboud University Nijmegen in the Netherlands. Hagoort, who was not involved in this study, adds that more work is needed to determine whether the language-selective areas might also be involved in any other aspects of cognitive function. “For instance, the language-selective region might play a role in the perception of music, which was not tested in the current study,” he says.

The researchers are now trying to determine how the components of the language network and the multiple demand network communicate internally, and how the two networks communicate with each other. They also hope to further investigate the functions of the two components of Broca’s area.

“In future studies, we should examine those subregions separately and try to characterize them in terms of their contribution to various language processes and other cognitive processes,” Fedorenko says.

The team is also working with scientists at Massachusetts General Hospital to study patients with a form of neurodegeneration that gradually causes loss of the ability to speak and understand language. This disorder, known as primary progressive aphasia, appears to selectively target the language-selective network, including the language component of Broca’s area.

The research was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the Ellison Medical Foundation and the U.K. Medical Research Council.

Brain Scan Cover Image: Spring 2012

To win at cards, players must understand the beliefs and intentions of their opponents, an ability known as “Theory of Mind.” Rebecca Saxe studies the brain mechanisms that underlie this quintessentially human ability.

Mehrdad Jazayeri to join McGovern Institute faculty

We are pleased to announce the appointment of Mehrdad Jazayeri as an Investigator at the McGovern Institute for Brain Research. He will join the institute in January 2013, with a faculty appointment as assistant professor in MIT’s Department of Brain and Cognitive Sciences.

Complex behaviors rely on a combination of sensory evidence, prior experience and knowledge about potential costs and benefits. Jazayeri’s research is focused on the neural mechanisms that enable the brain to integrate these internal and external cues and to produce flexible goal-directed behavior.

In his dissertation work with J. Anthony Movshon at New York University, Jazayeri asked how the brain uses unreliable sensory signals to make probabilistic inferences. His work led to a simple computational scheme that explained how information in visual cortical maps is used for a variety of visual perceptual tasks. Later, as a Helen Hay Whitney postdoctoral fellow, he began to investigate the role of prior experience on perception. Working in the laboratory of Michael Shadlen at the University of Washington, he used a simple timing task to show that humans exploit their prior experience of temporal regularities to make better estimates of time intervals. Using a rigorous mathematical framework — Bayesian estimation — this work provided a detailed model for quantifying how measurements, prior expectations and internal goals influence timing behavior.

Jazayeri then turned to monkey electrophysiology to study how neurons process timing information and how they combine sensory cues with prior experience. For this work, he taught monkeys to reproduce time intervals, as if keeping the beat in music. The animals were provided with beats 1 and 2 and were rewarded for producing a third beat at the correct time. By recording from sensorimotor neurons in the parietal cortex during this task, Jazayeri showed that the pattern of activity is very different during the measurement and production phases of the task, even though the interval is the same.  Moreover, he found that the response dynamics of parietal neurons were shaped not only by the immediate time cues but also by the intervals monkeys had encountered in preceding trials.

Building on his previous work, Jazayeri will pursue two long-term research themes at MIT. One line of research will examine how brain circuits measure and produce time, an ability that is crucial for mental capacities such as learning causes and effects, “intuitive physics,” and sequencing thoughts and actions. The other line of research will exploit timing tasks to understand the neural basis of sensorimotor integration, a key component of cognitive functions such as deliberation and probabilistic reasoning.

Understanding complex behaviors such as flexible timing or sensorimotor integration requires methods for manipulating the activity of specific structures and circuits within the brain. Optogenetics, the ability to control brain activity using light, has emerged as a powerful tool for such studies. In a recent collaboration with Greg Horwitz at the Univeristy of Washington, Jazayeri reported the first successful application of optogenetics to evoke a behavioral response in primates. Motivated by this proof-of-principle experiment, Jazayeri plans to combine the traditional tools of psychophysics and electrophysiology with optogenetic manipulations to characterize the circuits that control timing and sensorimotor integration in the primate brain.

Originally from Iran, Jazayeri obtained his B.Sc in Electrical Engineering from Sharif University of Technology in Tehran. He received his PhD from New York University, where he studied with J. Anthony Movshon, winning the Dean’s award for the most outstanding dissertation in the university.  After graduating, he was awarded a Helen Hay Whitney fellowship to join the laboratory of Michael Shadlen at the University of Washington, where he has been since 2007.

Martha Constantine-Paton wins lifetime achievement award

Constantine-Paton, a leading figure in the field of developmental neuroscience, has been awarded the Society for Neuroscience’s Mika Salpeter Lifetime Achievement Award.

The award recognizes individuals with outstanding career achievements in neuroscience who have also actively promoted the professional advancement of women in neuroscience. Constantine-Paton will be recognized for her achievements during the Society for Neuroscience’s annual meeting this October.

Over the past 30 years, Constantine-Paton has established a reputation as a leading figure in the field of developmental neuroscience. In particular, her pioneering work on NMDA receptor-dependent plasticity laid the groundwork for our current understanding of how the brain becomes correctly wired in response to activity and experience.

She has also mentored many students and postdocs, among them several prominent women scientists, and she is very active in promoting the career development of her junior colleagues.

“Martha’s research contributions have been extremely influential within her field, and her influence has also been felt through her exemplary record of mentoring and service,” says McGovern Institute director Robert Desimone. “Martha’s career indeed represents a lifetime of achievement and I cannot imagine a more deserving recipient for this honor.”

Predicting how patients respond to therapy

Social anxiety is usually treated with either cognitive behavioral therapy or medications. However, it is currently impossible to predict which treatment will work best for a particular patient. The team of researchers from MIT, Boston University (BU) and Massachusetts General Hospital (MGH) found that the effectiveness of therapy could be predicted by measuring patients’ brain activity as they looked at photos of faces, before the therapy sessions began.

The findings, published this week in the Archives of General Psychiatry, may help doctors more accurately choose treatments for social anxiety disorder, which is estimated to affect around 15 million people in the United States.

“Our vision is that some of these measures might direct individuals to treatments that are more likely to work for them,” says John Gabrieli, the Grover M. Hermann Professor of Brain and Cognitive Sciences at MIT, a member of the McGovern Institute for Brain Research and senior author of the paper.

Lead authors of the paper are MIT postdoc Oliver Doehrmann and Satrajit Ghosh, a research scientist in the McGovern Institute.

Choosing treatments

Sufferers of social anxiety disorder experience intense fear in social situations, interfering with their ability to function in daily life. Cognitive behavioral therapy aims to change the thought and behavior patterns that lead to anxiety. For social anxiety disorder patients, that might include learning to reverse the belief that others are watching or judging them.

The new paper is part of a larger study that MGH and BU recently ran on cognitive behavioral therapy for social anxiety, led by Mark Pollack, director of the Center for Anxiety and Traumatic Stress Disorders at MGH, and Stefan Hofmann, director of the Social Anxiety Program at BU.

“This was a chance to ask if these brain measures, taken before treatment, would be informative in ways above and beyond what physicians can measure now, and determine who would be responsive to this treatment,” Gabrieli says.

Currently doctors might choose a treatment based on factors such as ease of taking pills versus going to therapy, the possibility of drug side effects, or what the patients’ insurance will cover. “From a science perspective there’s very little evidence about which treatment is optimal for a person,” Gabrieli says.

The researchers used functional magnetic resonance imaging (fMRI) to image the brains of patients before and after treatment. There have been many imaging studies showing brain differences between healthy people and patients with neuropsychiatric disorders, but so far imaging has not been established as a way to predict patient response to particular treatments.

Measuring brain activity

In the new study, the researchers measured differences in brain activity as patients looked at images of angry or neutral faces. After 12 weeks of cognitive behavioral therapy, patients’ social anxiety levels were tested. The researchers found that patients who had shown a greater difference in activity in high-level visual processing areas during the face-response task showed the most improvement after therapy.

The findings are an important step towards improving doctors’ ability to choose the right treatment for psychiatric disorders, says Greg Siegle, associate professor of psychiatry at the University of Pittsburgh. “It’s really critical that somebody do this work, and they did it very well,” says Siegle, who was not part of the research team. “It moves the field forward, and brings psychology into more of a rigorous science, using neuroscience to distinguish between clinical cases that at first appear homogeneous.”

Gabrieli says it’s unclear why activity in brain regions involved with visual processing would be a good predictor of treatment outcome. One possibility is that patients who benefited more were those whose brains were already adept at segregating different types of experiences, Gabrieli says.

The researchers are now planning a follow-up study to investigate whether brain scans can predict differences in response between cognitive behavioral therapy and drug treatment.

“Right now, all by itself, we’re just giving somebody encouraging or discouraging news about the likely outcome of therapy,” Gabrieli says. “The really valuable thing would be if it turns out to be differentially sensitive to different treatment choices.”

The research was funded by the Poitras Center for Affective Disorders Research and the National Institute of Mental Health.

Stroke disrupts how brain controls muscle synergies

The simple act of picking up a pencil requires the coordination of dozens of muscles: The eyes and head must turn toward the object as the hand reaches forward and the fingers grasp it. To make this job more manageable, the brain’s motor cortex has implemented a system of shortcuts. Instead of controlling each muscle independently, the cortex is believed to activate muscles in groups, known as “muscle synergies.” These synergies can be combined in different ways to achieve a wide range of movements.

A new study from MIT, Harvard Medical School and the San Camillo Hospital in Venice finds that after a stroke, these muscle synergies are activated in altered ways. Furthermore, those disruptions follow specific patterns depending on the severity of the stroke and the amount of time that has passed since the stroke.

The findings, published this week in the Proceedings of the National Academy of Sciences, could lead to improved rehabilitation for stroke patients, as well as a better understanding of how the motor cortex coordinates movements, says Emilio Bizzi, an Institute Professor at MIT and senior author of the paper.

“The cortex is responsible for motor learning and for controlling movement, so we want to understand what’s going on there,” says Bizzi, who is a member of the McGovern Institute for Brain Research at MIT. “How does the cortex translate an idea to move into a series of commands to accomplish a task?”

Coordinated control

One way to explore motor cortical functions is to study how motor patterns are disrupted in stroke patients who suffered damage to the motor areas.

In 2009, Bizzi and his colleagues first identified muscle synergies in the arms of people who had suffered mild strokes by measuring electrical activity in each muscle as the patients moved. Then, by utilizing a specially designed factorization algorithm, the researchers identified characteristic muscle synergies in both the stroke-affected and unaffected arms.

“To control, precisely, each muscle needed for the task would be very hard. What we have proven is that the central nervous system, when it programs the movement, makes use of these modules,” Bizzi says. “Instead of activating simultaneously 50 muscles for a single action, you will combine a few synergies to achieve that goal.”

In the 2009 study, and again in the new paper, the researchers showed that synergies in the affected arms of patients who suffered mild strokes in the cortex are very similar to those seen in their unaffected arms even though the muscle activation patterns are different. This shows that muscle synergies are structured within the spinal cord, and that cortical stroke alters the ability of the brain to activate these synergies in the appropriate combinations.

However, the new study found a much different pattern in patients who suffered more severe strokes. In those patients, synergies in the affected arm merged to form a smaller number of larger synergies. And in a third group of patients, who had suffered their stroke many years earlier, the muscle synergies of the affected arm split into fragments of the synergies seen in the unaffected arm.

This phenomenon, known as fractionation, does not restore the synergies to what they would have looked like before the stroke. “These fractionations appear to be something totally new,” says Vincent Cheung, a research scientist at the McGovern Institute and lead author of the new PNAS paper. “The conjecture would be that these fragments could be a way that the nervous system tries to adapt to the injury, but we have to do further studies to confirm that.”

This is the first time that fractionation of muscle synergies identified by factorization has been seen in chronic stroke patients, says Simon Giszter, a professor of neurobiology and anatomy at Drexel University. “It raises the question of how this occurs and if it’s a compensatory process. If it is, we can use this measurement to study how the recovery process can be accelerated,” says Giszter, who was not involved in this study.

Toward better rehabilitation

The researchers believe that these patterns of synergies, which are determined by both the severity of the deficit and the time since the stroke occurred, could be used as markers to more fully describe individual patients’ impaired status. “In some of the patients, we see a mixture of these patterns. So you can have severe but chronic patients, for instance, who show both merging and fractionation,” Cheung says.

The findings could also help doctors design better rehabilitation programs. The MIT team is now working with several hospitals to establish new therapeutic protocols based on the discovered markers.

About 700,000 people suffer strokes in the United States every year, and many different rehabilitation programs exist to treat them. Choosing one is currently more of an art than a science, Bizzi says. “There is a great deal of need to sharpen current procedures for rehabilitation by turning to principles derived from the most advanced brain research,” he says. “It is very likely that different strategies of rehabilitation will have to be used in patients who have one type of marker versus another.”

The research was funded by the National Institutes of Health and the Italian Ministry of Health.

Thinking about others is not child’s play

When you try to read other people’s thoughts, or guess why they are behaving a certain way, you employ a skill known as theory of mind. This skill, as measured by false-belief tests, takes time to develop: In children, it doesn’t start appearing until the age of 4 or 5.

Several years ago, MIT neuroscientist Rebecca Saxe showed that in adults, theory of mind is seated in a specific brain region known as the right temporo-parietal junction (TPJ). Saxe and colleagues at MIT have now shown how brain activity in the TPJ changes as children learn to reason about others’ thoughts and feelings.

The findings suggest that the right TPJ becomes more specific to theory of mind as children age, taking on adult patterns of activity over time. The researchers also showed that the more selectively the right TPJ is activated when children listen to stories about other people’s thoughts, the better those children perform in tasks that require theory of mind.

The paper, published in the July 31 online edition of the journal Child Development, lays the groundwork for exploring theory-of-mind impairments in autistic children, says Hyowon Gweon, a graduate student in Saxe’s lab and lead author of the paper.

Given that we know this is what typically developing kids show, the next question to ask is how it compares to autistic children who exhibit marked impairments in their ability to think about other people’s minds,” Gweon says. “Do they show differences from typically developing kids in their neural activity?”

Saxe, an associate professor of brain and cognitive sciences and associate member of MIT’s McGovern Institute for Brain Research, is senior author of the Child Development paper. Other authors are Marina Bedny, a postdoc in Saxe’s lab, and David Dodell-Feder, a graduate student at Harvard University.

Tracking theory of mind

The classic test for theory of mind is the false-belief test, sometimes called the Sally-Anne test. Experimenters often use dolls or puppets to perform a short skit: Sally takes a marble and hides it in her basket, then leaves the room. Anne then removes the marble and puts it in her own box. When Sally returns, the child watching the skit is asked: Where will Sally look for her marble?

Children with well-developed theory of mind realize that Sally will look where she thinks the marble is: her own basket. However, before children develop this skill, they don’t realize that Sally’s beliefs may not correspond to reality. Therefore, they believe she will look for the marble where it actually is, in Anne’s box.

Previous studies have shown that children start making accurate predictions in the false belief test around age 4, but this happens much later, if ever, in autistic children.

In this study, the researchers used functional magnetic resonance imaging (fMRI) to look for a link between the development of theory of mind and changes in neural activity in the TPJ. They studied 20 children, ranging from 5 to 11 years old.

Each child participated in two sets of experiments. First, the child was scanned in the MRI machine as he or she listened to different types of stories. One type focused on people’s mental states, another also focused on people but only on their physical appearances or actions, and a third type of story focused on physical objects.

The researchers measured activity across the brain as the children listened to different stories. By subtracting neural activity as they listen to stories about physical states from activity as they listen to stories about people’s mental states, the researchers can determine which brain regions are exclusive to interpreting people’s mental states.

In younger children, both the left and right TPJ were active in response to stories about people’s mental states, but they were also active when the children listened to stories about people’s appearances or actions. However, in older children, both regions became more specifically tuned to interpreting people’s thoughts and emotions, and were no longer responsive to people’s appearances or actions.

For the second task, done outside of the scanner, the researchers gave children tests similar to the classic Sally-Anne test, as well as harder questions that required making moral judgments, to measure their theory-of-mind abilities. They found that the degree to which activity in the right TPJ was specific to others’ mental states correlated with the children’s performance in theory-of-mind tasks.

Kristin Lagattuta, an associate professor of psychology at the University of California at Davis, says the paper makes an important contribution to understanding how theory of mind develops in older children. “Getting more insight into the neural basis of the behavioral development we’re seeing at these ages is exciting,” says Lagattuta, who was not involved in the research.

In an ongoing study of autistic children undergoing the same type of tests, the researchers hope to learn more about the neural basis of the theory-of-mind impairments seen in autistic children.

“So little is known about differences in neural mechanisms that contribute to these kinds of impairments,” Gweon says. “Understanding the developmental changes in brain regions related to theory of mind is going to be critical to think of measures that can help them in the real world.”

The research was funded by the Ellison Medical Foundation, the Packard Foundation, the John Merck Scholars Program, a National Science Foundation Career Award and an Ewha 21st Century Scholarship.

Video Profile: H. Robert Horvitz

H. Robert Horvitz has devoted much of his career to studying the nematode worm Caenorhabditis elegans. Only 1 mm long and containing fewer than 1000 cells, C. elegans has proved to be remarkably informative for studying many biological problems, including the genetic control of development and behavior and the mechanisms that underlie neurodegenerative disease.