Try, try again? Study says no

When it comes to learning languages, adults and children have different strengths. Adults excel at absorbing the vocabulary needed to navigate a grocery store or order food in a restaurant, but children have an uncanny ability to pick up on subtle nuances of language that often elude adults. Within months of living in a foreign country, a young child may speak a second language like a native speaker.

Brain structure plays an important role in this “sensitive period” for learning language, which is believed to end around adolescence. The young brain is equipped with neural circuits that can analyze sounds and build a coherent set of rules for constructing words and sentences out of those sounds. Once these language structures are established, it’s difficult to build another one for a new language.

In a new study, a team of neuroscientists and psychologists led by Amy Finn, a postdoc at MIT’s McGovern Institute for Brain Research, has found evidence for another factor that contributes to adults’ language difficulties: When learning certain elements of language, adults’ more highly developed cognitive skills actually get in the way. The researchers discovered that the harder adults tried to learn an artificial language, the worse they were at deciphering the language’s morphology — the structure and deployment of linguistic units such as root words, suffixes, and prefixes.

“We found that effort helps you in most situations, for things like figuring out what the units of language that you need to know are, and basic ordering of elements. But when trying to learn morphology, at least in this artificial language we created, it’s actually worse when you try,” Finn says.

Finn and colleagues from the University of California at Santa Barbara, Stanford University, and the University of British Columbia describe their findings in the July 21 issue of PLoS One. Carla Hudson Kam, an associate professor of linguistics at British Columbia, is the paper’s senior author.

Too much brainpower

Linguists have known for decades that children are skilled at absorbing certain tricky elements of language, such as irregular past participles (examples of which, in English, include “gone” and “been”) or complicated verb tenses like the subjunctive.

“Children will ultimately perform better than adults in terms of their command of the grammar and the structural components of language — some of the more idiosyncratic, difficult-to-articulate aspects of language that even most native speakers don’t have conscious awareness of,” Finn says.

In 1990, linguist Elissa Newport hypothesized that adults have trouble learning those nuances because they try to analyze too much information at once. Adults have a much more highly developed prefrontal cortex than children, and they tend to throw all of that brainpower at learning a second language. This high-powered processing may actually interfere with certain elements of learning language.

“It’s an idea that’s been around for a long time, but there hasn’t been any data that experimentally show that it’s true,” Finn says.

Finn and her colleagues designed an experiment to test whether exerting more effort would help or hinder success. First, they created nine nonsense words, each with two syllables. Each word fell into one of three categories (A, B, and C), defined by the order of consonant and vowel sounds.

Study subjects listened to the artificial language for about 10 minutes. One group of subjects was told not to overanalyze what they heard, but not to tune it out either. To help them not overthink the language, they were given the option of completing a puzzle or coloring while they listened. The other group was told to try to identify the words they were hearing.

Each group heard the same recording, which was a series of three-word sequences — first a word from category A, then one from category B, then category C — with no pauses between words. Previous studies have shown that adults, babies, and even monkeys can parse this kind of information into word units, a task known as word segmentation.

Subjects from both groups were successful at word segmentation, although the group that tried harder performed a little better. Both groups also performed well in a task called word ordering, which required subjects to choose between a correct word sequence (ABC) and an incorrect sequence (such as ACB) of words they had previously heard.

The final test measured skill in identifying the language’s morphology. The researchers played a three-word sequence that included a word the subjects had not heard before, but which fit into one of the three categories. When asked to judge whether this new word was in the correct location, the subjects who had been asked to pay closer attention to the original word stream performed much worse than those who had listened more passively.

Turning off effort

The findings support a theory of language acquisition that suggests that some parts of language are learned through procedural memory, while others are learned through declarative memory. Under this theory, declarative memory, which stores knowledge and facts, would be more useful for learning vocabulary and certain rules of grammar. Procedural memory, which guides tasks we perform without conscious awareness of how we learned them, would be more useful for learning subtle rules related to language morphology.

“It’s likely to be the procedural memory system that’s really important for learning these difficult morphological aspects of language. In fact, when you use the declarative memory system, it doesn’t help you, it harms you,” Finn says.

Still unresolved is the question of whether adults can overcome this language-learning obstacle. Finn says she does not have a good answer yet but she is now testing the effects of “turning off” the adult prefrontal cortex using a technique called transcranial magnetic stimulation. Other interventions she plans to study include distracting the prefrontal cortex by forcing it to perform other tasks while language is heard, and treating subjects with drugs that impair activity in that brain region.

The research was funded by the National Institute of Child Health and Human Development and the National Science Foundation.

When good people do bad things

When people get together in groups, unusual things can happen — both good and bad. Groups create important social institutions that an individual could not achieve alone, but there can be a darker side to such alliances: Belonging to a group makes people more likely to harm others outside the group.

“Although humans exhibit strong preferences for equity and moral prohibitions against harm in many contexts, people’s priorities change when there is an ‘us’ and a ‘them,’” says Rebecca Saxe, an associate professor of cognitive neuroscience at MIT. “A group of people will often engage in actions that are contrary to the private moral standards of each individual in that group, sweeping otherwise decent individuals into ‘mobs’ that commit looting, vandalism, even physical brutality.”

Several factors play into this transformation. When people are in a group, they feel more anonymous, and less likely to be caught doing something wrong. They may also feel a diminished sense of personal responsibility for collective actions.

Saxe and colleagues recently studied a third factor that cognitive scientists believe may be involved in this group dynamic: the hypothesis that when people are in groups, they “lose touch” with their own morals and beliefs, and become more likely to do things that they would normally believe are wrong.

In a study that recently went online in the journal NeuroImage, the researchers measured brain activity in a part of the brain involved in thinking about oneself. They found that in some people, this activity was reduced when the subjects participated in a competition as part of a group, compared with when they competed as individuals. Those people were more likely to harm their competitors than people who did not exhibit this decreased brain activity.

“This process alone does not account for intergroup conflict: Groups also promote anonymity, diminish personal responsibility, and encourage reframing harmful actions as ‘necessary for the greater good.’ Still, these results suggest that at least in some cases, explicitly reflecting on one’s own personal moral standards may help to attenuate the influence of ‘mob mentality,’” says Mina Cikara, a former MIT postdoc and lead author of the NeuroImage paper.

Group dynamics

Cikara, who is now an assistant professor at Carnegie Mellon University, started this research project after experiencing the consequences of a “mob mentality”: During a visit to Yankee Stadium, her husband was ceaselessly heckled by Yankees fans for wearing a Red Sox cap. “What I decided to do was take the hat from him, thinking I would be a lesser target by virtue of the fact that I was a woman,” Cikara says. “I was so wrong. I have never been called names like that in my entire life.”

The harassment, which continued throughout the trip back to Manhattan, provoked a strong reaction in Cikara, who isn’t even a Red Sox fan.

“It was a really amazing experience because what I realized was I had gone from being an individual to being seen as a member of ‘Red Sox Nation.’ And the way that people responded to me, and the way I felt myself responding back, had changed, by virtue of this visual cue — the baseball hat,” she says. “Once you start feeling attacked on behalf of your group, however arbitrary, it changes your psychology.”

Cikara, then a third-year graduate student at Princeton University, started to investigate the neural mechanisms behind the group dynamics that produce bad behavior. In the new study, done at MIT, Cikara, Saxe (who is also an associate member of MIT’s McGovern Institute for Brain Research), former Harvard University graduate student Anna Jenkins, and former MIT lab manager Nicholas Dufour focused on a part of the brain called the medial prefrontal cortex. When someone is reflecting on himself or herself, this part of the brain lights up in functional magnetic resonance imaging (fMRI) brain scans.

A couple of weeks before the study participants came in for the experiment, the researchers surveyed each of them about their social-media habits, as well as their moral beliefs and behavior. This allowed the researchers to create individualized statements for each subject that were true for that person — for example, “I have stolen food from shared refrigerators” or “I always apologize after bumping into someone.”

When the subjects arrived at the lab, their brains were scanned as they played a game once on their own and once as part of a team. The purpose of the game was to press a button if they saw a statement related to social media, such as “I have more than 600 Facebook friends.”

The subjects also saw their personalized moral statements mixed in with sentences about social media. Brain scans revealed that when subjects were playing for themselves, the medial prefrontal cortex lit up much more when they read moral statements about themselves than statements about others, consistent with previous findings. However, during the team competition, some people showed a much smaller difference in medial prefrontal cortex activation when they saw the moral statements about themselves compared to those about other people.

Those people also turned out to be much more likely to harm members of the competing group during a task performed after the game. Each subject was asked to select photos that would appear with the published study, from a set of four photos apiece of two teammates and two members of the opposing team. The subjects with suppressed medial prefrontal cortex activity chose the least flattering photos of the opposing team members, but not of their own teammates.

“This is a nice way of using neuroimaging to try to get insight into something that behaviorally has been really hard to explore,” says David Rand, an assistant professor of psychology at Yale University who was not involved in the research. “It’s been hard to get a direct handle on the extent to which people within a group are tapping into their own understanding of things versus the group’s understanding.”

Getting lost

The researchers also found that after the game, people with reduced medial prefrontal cortex activity had more difficulty remembering the moral statements they had heard during the game.

“If you need to encode something with regard to the self and that ability is somehow undermined when you’re competing with a group, then you should have poor memory associated with that reduction in medial prefrontal cortex signal, and that’s exactly what we see,” Cikara says.

Cikara hopes to follow up on these findings to investigate what makes some people more likely to become “lost” in a group than others. She is also interested in studying whether people are slower to recognize themselves or pick themselves out of a photo lineup after being absorbed in a group activity.

The research was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the Air Force Office of Scientific Research, and the Packard Foundation.

Inside the adult ADHD brain

About 11 percent of school-age children in the United States have been diagnosed with attention deficit hyperactivity disorder (ADHD). While many of these children eventually “outgrow” the disorder, some carry their difficulties into adulthood: About 10 million American adults are currently diagnosed with ADHD.

In the first study to compare patterns of brain activity in adults who recovered from childhood ADHD and those who did not, MIT neuroscientists have discovered key differences in a brain communication network that is active when the brain is at wakeful rest and not focused on a particular task. The findings offer evidence of a biological basis for adult ADHD and should help to validate the criteria used to diagnose the disorder, according to the researchers.

Diagnoses of adult ADHD have risen dramatically in the past several years, with symptoms similar to those of childhood ADHD: a general inability to focus, reflected in difficulty completing tasks, listening to instructions, or remembering details.

“The psychiatric guidelines for whether a person’s ADHD is persistent or remitted are based on lots of clinical studies and impressions. This new study suggests that there is a real biological boundary between those two sets of patients,” says MIT’s John Gabrieli, the Grover M. Hermann Professor of Health Sciences and Technology, professor of brain and cognitive sciences, and an author of the study, which appears in the June 10 issue of the journal Brain.

Shifting brain patterns

This study focused on 35 adults who were diagnosed with ADHD as children; 13 of them still have the disorder, while the rest have recovered. “This sample really gave us a unique opportunity to ask questions about whether or not the brain basis of ADHD is similar in the remitted-ADHD and persistent-ADHD cohorts,” says Aaron Mattfeld, a postdoc at MIT’s McGovern Institute for Brain Research and the paper’s lead author.

The researchers used a technique called resting-state functional magnetic resonance imaging (fMRI) to study what the brain is doing when a person is not engaged in any particular activity. These patterns reveal which parts of the brain communicate with each other during this type of wakeful rest.

“It’s a different way of using functional brain imaging to investigate brain networks,” says Susan Whitfield-Gabrieli, a research scientist at the McGovern Institute and the senior author of the paper. “Here we have subjects just lying in the scanner. This method reveals the intrinsic functional architecture of the human brain without invoking any specific task.”

In people without ADHD, when the mind is unfocused, there is a distinctive synchrony of activity in brain regions known as the default mode network. Previous studies have shown that in children and adults with ADHD, two major hubs of this network — the posterior cingulate cortex and the medial prefrontal cortex — no longer synchronize.

In the new study, the MIT team showed for the first time that in adults who had been diagnosed with ADHD as children but no longer have it, this normal synchrony pattern is restored. “Their brains now look like those of people who never had ADHD,” Mattfeld says.

“This finding is quite intriguing,” says Francisco Xavier Castellanos, a professor of child and adolescent psychiatry at New York University who was not involved in the research. “If it can be confirmed, this pattern could become a target for potential modification to help patients learn to compensate for the disorder without changing their genetic makeup.”

Lingering problems

However, in another measure of brain synchrony, the researchers found much more similarity between both groups of ADHD patients.

In people without ADHD, when the default mode network is active, another network, called the task positive network, is suppressed. When the brain is performing tasks that require focus, the task positive network takes over and suppresses the default mode network. If this reciprocal relationship degrades, the ability to focus declines.

Both groups of adult ADHD patients, including those who had recovered, showed patterns of simultaneous activation of both networks. This is thought to be a sign of impairment in executive function — the management of cognitive tasks — that is separate from ADHD, but occurs in about half of ADHD patients. All of the ADHD patients in this study performed poorly on tests of executive function. “Once you have executive function problems, they seem to hang in there,” says Gabrieli, who is a member of the McGovern Institute.

The researchers now plan to investigate how ADHD medications influence the brain’s default mode network, in hopes that this might allow them to predict which drugs will work best for individual patients. Currently, about 60 percent of patients respond well to the first drug they receive.

“It’s unknown what’s different about the other 40 percent or so who don’t respond very much,” Gabrieli says. “We’re pretty excited about the possibility that some brain measurement would tell us which child or adult is most likely to benefit from a treatment.”

The research was funded by the Poitras Center for Affective Disorders Research at the McGovern Institute.

Even when test scores go up, some cognitive abilities don’t

To evaluate school quality, states require students to take standardized tests; in many cases, passing those tests is necessary to receive a high-school diploma. These high-stakes tests have also been shown to predict students’ future educational attainment and adult employment and income.

Such tests are designed to measure the knowledge and skills that students have acquired in school — what psychologists call “crystallized intelligence.” However, schools whose students have the highest gains on test scores do not produce similar gains in “fluid intelligence” — the ability to analyze abstract problems and think logically — according to a new study from MIT neuroscientists working with education researchers at Harvard University and Brown University.

In a study of nearly 1,400 eighth-graders in the Boston public school system, the researchers found that some schools have successfully raised their students’ scores on the Massachusetts Comprehensive Assessment System (MCAS). However, those schools had almost no effect on students’ performance on tests of fluid intelligence skills, such as working memory capacity, speed of information processing, and ability to solve abstract problems.

“Our original question was this: If you have a school that’s effectively helping kids from lower socioeconomic environments by moving up their scores and improving their chances to go to college, then are those changes accompanied by gains in additional cognitive skills?” says John Gabrieli, the Grover M. Hermann Professor of Health Sciences and Technology, professor of brain and cognitive sciences, and senior author of a forthcoming Psychological Science paper describing the findings.

Instead, the researchers found that educational practices designed to raise knowledge and boost test scores do not improve fluid intelligence. “It doesn’t seem like you get these skills for free in the way that you might hope, despite learning a lot by being a good student,” says Gabrieli, who is also a member of MIT’s McGovern Institute for Brain Research.

Measuring cognition

This study grew out of a larger effort to find measures beyond standardized tests that can predict long-term success for students. “As we started that study, it struck us that there’s been surprisingly little evaluation of different kinds of cognitive abilities and how they relate to educational outcomes,” Gabrieli says.

The data for the Psychological Science study came from students attending traditional, charter, and exam schools in Boston. Some of those schools have had great success improving their students’ MCAS scores — a boost that studies have found also translates to better performance on the SAT and Advanced Placement tests.

The researchers calculated how much of the variation in MCAS scores was due to the school that students attended. For MCAS scores in English, schools accounted for 24 percent of the variation, and they accounted for 34 percent of the math MCAS variation. However, the schools accounted for very little of the variation in fluid cognitive skills — less than 3 percent for all three skills combined.

In one example of a test of fluid reasoning, students were asked to choose which of six pictures completed the missing pieces of a puzzle — a task requiring integration of information such as shape, pattern, and orientation.

“It’s not always clear what dimensions you have to pay attention to get the problem correct. That’s why we call it fluid, because it’s the application of reasoning skills in novel contexts,” says Amy Finn, an MIT postdoc and lead author of the paper.

Even stronger evidence came from a comparison of about 200 students who had entered a lottery for admittance to a handful of Boston’s oversubscribed charter schools, many of which achieve strong improvement in MCAS scores. The researchers found that students who were randomly selected to attend high-performing charter schools did significantly better on the math MCAS than those who were not chosen, but there was no corresponding increase in fluid intelligence scores.

However, the researchers say their study is not about comparing charter schools and district schools. Rather, the study showed that while schools of both types varied in their impact on test scores, they did not vary in their impact on fluid cognitive skills.

“What’s nice about this study is it seems to narrow down the possibilities of what educational interventions are achieving,” says Daniel Willingham, a professor of psychology at the University of Virginia who was not part of the research team. “We’re usually primarily concerned with outcomes in schools, but the underlying mechanisms are also important.”

The researchers plan to continue tracking these students, who are now in 10th grade, to see how their academic performance and other life outcomes evolve. They have also begun to participate in a new study of high school seniors to track how their standardized test scores and cognitive abilities influence their rates of college attendance and graduation.

Implications for education

Gabrieli notes that the study should not be interpreted as critical of schools that are improving their students’ MCAS scores. “It’s valuable to push up the crystallized abilities, because if you can do more math, if you can read a paragraph and answer comprehension questions, all those things are positive,” he says.

He hopes that the findings will encourage educational policymakers to consider adding practices that enhance cognitive skills. Although many studies have shown that students’ fluid cognitive skills predict their academic performance, such skills are seldom explicitly taught.

“Schools can improve crystallized abilities, and now it might be a priority to see if there are some methods for enhancing the fluid ones as well,” Gabrieli says.

Some studies have found that educational programs that focus on improving memory, attention, executive function, and inductive reasoning can boost fluid intelligence, but there is still much disagreement over what programs are consistently effective.

The research was a collaboration with the Center for Education Policy Research at Harvard University, Transforming Education, and Brown University, and was funded by the Bill and Melinda Gates Foundation and the National Institutes of Health.

Brain scans may help diagnose dyslexia

About 10 percent of the U.S. population suffers from dyslexia, a condition that makes learning to read difficult. Dyslexia is usually diagnosed around second grade, but the results of a new study from MIT could help identify those children before they even begin reading, so they can be given extra help earlier.

The study, done with researchers at Boston Children’s Hospital, found a correlation between poor pre-reading skills in kindergartners and the size of a brain structure that connects two language-processing areas.

Previous studies have shown that in adults with poor reading skills, this structure, known as the arcuate fasciculus, is smaller and less organized than in adults who read normally. However, it was unknown if these differences cause reading difficulties or result from lack of reading experience.

“We were very interested in looking at children prior to reading instruction and whether you would see these kinds of differences,” says John Gabrieli, the Grover M. Hermann Professor of Health Sciences and Technology, professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research.

Gabrieli and Nadine Gaab, an assistant professor of pediatrics at Boston Children’s Hospital, are the senior authors of a paper describing the results in the Aug. 14 issue of the Journal of Neuroscience. Lead authors of the paper are MIT postdocs Zeynep Saygin and Elizabeth Norton.

The path to reading

The new study is part of a larger effort involving approximately 1,000 children at schools throughout Massachusetts and Rhode Island. At the beginning of kindergarten, children whose parents give permission to participate are assessed for pre-reading skills, such as being able to put words together from sounds.

“From that, we’re able to provide — at the beginning of kindergarten — a snapshot of how that child’s pre-reading abilities look relative to others in their classroom or other peers, which is a real benefit to the child’s parents and teachers,” Norton says.

The researchers then invite a subset of the children to come to MIT for brain imaging. The Journal of Neuroscience study included 40 children who had their brains scanned using a technique known as diffusion-weighted imaging, which is based on magnetic resonance imaging (MRI).

This type of imaging reveals the size and organization of the brain’s white matter — bundles of nerves that carry information between brain regions. The researchers focused on three white-matter tracts associated with reading skill, all located on the left side of the brain: the arcuate fasciculus, the inferior longitudinal fasciculus (ILF) and the superior longitudinal fasciculus (SLF).

When comparing the brain scans and the results of several different types of pre-reading tests, the researchers found a correlation between the size and organization of the arcuate fasciculus and performance on tests of phonological awareness — the ability to identify and manipulate the sounds of language.

Phonological awareness can be measured by testing how well children can segment sounds, identify them in isolation, and rearrange them to make new words. Strong phonological skills have previously been linked with ease of learning to read. “The first step in reading is to match the printed letters with the sounds of letters that you know exist in the world,” Norton says.

The researchers also tested the children on two other skills that have been shown to predict reading ability — rapid naming, which is the ability to name a series of familiar objects as quickly as you can, and the ability to name letters. They did not find any correlation between these skills and the size or organization of the white-matter structures scanned in this study.

Early intervention

The left arcuate fasciculus connects Broca’s area, which is involved in speech production, and Wernicke’s area, which is involved in understanding written and spoken language. A larger and more organized arcuate fasciculus could aid in communication between those two regions, the researchers say.

Gabrieli points out that the structural differences found in the study don’t necessarily reflect genetic differences; environmental influences could also be involved. “At the moment when the children arrive at kindergarten, which is approximately when we scan them, we don’t know what factors lead to these brain differences,” he says.

The researchers plan to follow three waves of children as they progress to second grade and evaluate whether the brain measures they have identified predict poor reading skills.

“We don’t know yet how it plays out over time, and that’s the big question: Can we, through a combination of behavioral and brain measures, get a lot more accurate at seeing who will become a dyslexic child, with the hope that that would motivate aggressive interventions that would help these children right from the start, instead of waiting for them to fail?” Gabrieli says.

For at least some dyslexic children, offering extra training in phonological skills can help them improve their reading skills later on, studies have shown.

The research was funded by the National Institutes of Health, the Poitras Center for Affective Disorders Research, the Ellison Medical Foundation and the Halis Family Foundation.

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.

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.

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.

Faces have a special place in the brain

Are you tempted to trade in last year’s digital camera for a newer model with even more megapixels? Researchers who make images of the human brain have the same obsession with increasing their pixel count, which increases the sharpness (or “spatial resolution”) of their images. And improvements in spatial resolution are happening as fast in brain imaging research as they are in digital camera technology.

Nancy Kanwisher, Rebecca Frye Schwarzlose and Christopher Baker at the McGovern Institute for Brain Research at MIT are now using their higher-resolution scans to produce much more detailed images of the brain than were possible just a couple years ago. Just as “hi-def” TV shows clearer views of a football game, these finely grained images are providing new answers to some very old questions in brain research.

One such question hinges on whether the brain is comprised of highly specialized parts, each optimized to conduct a single, very specific function. Or is it instead a general-purpose device that handles many tasks but specializes in none?

Using the higher-resolution scans, the Kanwisher team now provides some of the strongest evidence ever reported for extreme specialization. Their study appeared in the Nov. 23 issue of the Journal of Neuroscience.

The study focuses on face recognition, long considered an example of brain specialization. In the 1990s, researchers including Kanwisher identified a region known as the fusiform face area (FFA) as a potential brain center for face recognition. They pointed to evidence from brain-imaging experiments, and to the fact that people with damage to this brain region cannot recognize faces, even those of their family and closest friends.

However, more recent brain-imaging experiments have challenged this claimed specialization by showing that this region also responds strongly when people see images of bodies and body parts, not just faces. The new study now answers this challenge and supports the original specialization theory.

Schwarzlose suspected that the strong response of the face area to both faces and bodies might result from the blurring together of two distinct but neighboring brain regions that are too close together to distinguish at standard scanning resolutions.

To test this idea, Schwarzlose and her colleagues increased the resolution of their images (like increasing the megapixels on a digital camera) ten-fold to get sharper images of brain function. Indeed, at this higher resolution they could clearly distinguish two neighboring regions. One was primarily active when people saw faces (not bodies), and the other when people saw bodies (not faces).

This finding supports the original claim that the face area is in fact dedicated exclusively to face processing. The results further demonstrate a similar degree of specialization for the new “body region” next door.

The team’s new discovery highlights the importance of improved spatial resolution in studying the structure of the human brain. Just as a higher megapixel digital camera can show greater detail, new brain imaging methods are revealing the finer-grained structure of the human brain. Schwarzlose and her colleagues plan to use the new scanning methods to look for even finer levels of organization within the newly distinguished face and body areas. They also want to figure out how and why the brain regions for faces and bodies land next to each other in the first place.

Kanwisher is the Ellen Swallow Richards Professor of Cognitive Neuroscience. Her colleagues on this work are Schwarzlose, a graduate student in brain and cognitive sciences, and Baker, a postdoctoral researcher in the department.

The research was supported by the National Institutes of Health, the National Center for Research Resources, the Mind Institute, and the National Science Foundation’s Graduate Research Fellowship Program.