Brain Disorder: Anxiety

Brain biomarkers predict mood and attention symptoms

by Sabbi Lall |

Mood and attentional disorders amongst teens are an increasing concern, for parents, society, and for peers. A recent Pew research center survey found conditions such as depression and anxiety to be the number one concern that young students had about their friends, ranking above drugs or bullying.

“We’re seeing an epidemic in teen anxiety and depression,” explains McGovern Research Affiliate Susan Whitfield-Gabrieli.

“Scientists are finding a huge increase in suicide ideation and attempts, something that hit home for me as a mother of teens. Emergency rooms in hospitals now have guards posted outside doors of these teenagers that attempted suicide—this is a pressing issue,” explains Whitfield-Gabrieli who is also director of the Northeastern University Biomedical Imaging Center and a member of the Poitras Center for Psychiatric Disorders Research.

Finding new methods for discovering early biomarkers for risk of psychiatric disorders would allow early interventions and avoid reaching points of crisis such as suicide ideation or attempts. In research published recently in JAMA Psychiatry, Whitfield-Gabrieli and colleagues found that signatures predicting future development of depression and attentional symptoms can be detected in children as young as seven years old.

Long-term view

While previous work had suggested that there may be biomarkers that predict development of mood and attentional disorders, identifying early biomarkers prior to an onset of illness requires following a cohort of pre-teens from a young age, and monitoring them across years. This effort to have a proactive, rather than reactive, approach to the development of symptoms associated with mental disorders is exactly the route Whitfield-Gabrieli and colleagues took.

“One of the exciting aspects of this study is that the cohort is not pre-selected for already having symptoms of psychiatric disorders themselves or even in their family,” explained Whitfield-Gabrieli. “It’s an unbiased cohort that we followed over time.”

McGovern research affiliate Susan Whitfield-Gabrieli has discovered early brain biomarkers linked to psychiatric disorders.

In some past studies, children were pre-selected, for example a major depressive disorder diagnosis in the parents, but Whitfield-Gabrieli and colleagues, Silvia Bunge from Berkeley and Laurie Cutting from Vanderbilt, recruited a range of children without preconditions, and examined them at age 7, then again 4 years later. The researchers examined resting state functional connectivity, and compared this to scores on the child behavioral checklist (CBCL), allowing them to relate differences in the brain to a standardized analysis of behavior that can be linked to psychiatric disorders. The CBCL is used both in research and in the clinic and his highly predictive of disorders including ADHD, so that changes in the brain could be related to changes in a widely used clinical scoring system.

“Over the four years, some people got worse, some got better, and some stayed the same according the CBCL. We could relate this directly to differences in brain networks, and could identify at age 7 who would get worse,” explained Whitfield-Gabrieli.

Brain network changes

The authors analyzed differences in resting state network connectivity, regions across the brain that rise and fall in activity level together, as visualized using fMRI. Reduced connectivity between these regions may allow us to get a handle on reduced “top-down” control of neural circuits. The dorsolateral prefrontal region is linked to executive function, external attention, and emotional control. Increased connection with the medial prefrontal cortex is known to be present in attention deficit hyperactivity disorder (ADHD), while a reduced connection to a different brain region, the sgACC, is seen in major depressive disorder. The question remained as to whether these changes can be seen prior to the onset of diagnosable attentional or mood disorders.

Whitfield-Gabrieli and colleagues found that these resting state networks varied in the brains of children that would later develop anxiety/depression and ADHD symptoms. Weaker scores in connectivity between the dorsolateral and medial prefrontal cortical regions tended to be seen in children whose attention scores went on to improve. Analysis of the resting state networks above could differentiate those who would have typical attentional behavior by age 11 versus those that went on to develop ADHD.

Whitfield-Gabrieli has replicated this finding in an independent sample of children and she is continuing to expand the analysis and check the results, as well as follow this cohort into the future. Should changes in resting state networks be a consistent biomarker, the next step is to initiate interventions prior to the point of crisis.

“We’ve recently been able to use mindfulness interventions, and show these reduce self-perceived stress and amygdala activation in response to fear, and we are also testing the effect of exercise interventions,” explained Whitfield-Gabrieli. “The hope is that by using predictive biomarkers we can augment children’s lifestyles with healthy interventions that can prevent risk converting to a psychiatric disorder.”

Benefits of mindfulness for middle schoolers

by Anne Trafton |

Two new studies from investigators at the McGovern Institute at MIT suggest that mindfulness — the practice of focusing one’s awareness on the present moment — can enhance academic performance and mental health in middle schoolers. The researchers found that more mindfulness correlates with better academic performance, fewer suspensions from school, and less stress.

“By definition, mindfulness is the ability to focus attention on the present moment, as opposed to being distracted by external things or internal thoughts. If you’re focused on the teacher in front of you, or the homework in front of you, that should be good for learning,” says John Gabrieli, the Grover M. Hermann Professor in Health Sciences and Technology, a professor of brain and cognitive sciences, and a member of MIT’s McGovern Institute for Brain Research.

The researchers also showed, for the first time, that mindfulness training can alter brain activity in students. Sixth-graders who received mindfulness training not only reported feeling less stressed, but their brain scans revealed reduced activation of the amygdala, a brain region that processes fear and other emotions, when they viewed images of fearful faces.

“Mindfulness is like going to the gym. If you go for a month, that’s good, but if you stop going, the effects won’t last,” Gabrieli says. “It’s a form of mental exercise that needs to be sustained.”

Together, the findings suggest that offering mindfulness training in schools could benefit many students, says Gabrieli, who is the senior author of both studies.

“We think there is a reasonable possibility that mindfulness training would be beneficial for children as part of the daily curriculum in their classroom,” he says. “What’s also appealing about mindfulness is that there are pretty well-established ways of teaching it.”

In the moment

Both studies were performed at charter schools in Boston. In one of the papers, which appears today in the journal Behavioral Neuroscience, the MIT team studied about 100 sixth-graders. Half of the students received mindfulness training every day for eight weeks, while the other half took a coding class. The mindfulness exercises were designed to encourage students to pay attention to their breath, and to focus on the present moment rather than thoughts of the past or the future.

Students who received the mindfulness training reported that their stress levels went down after the training, while the students in the control group did not. Students in the mindfulness training group also reported fewer negative feelings, such as sadness or anger, after the training.

About 40 of the students also participated in brain imaging studies before and after the training. The researchers measured activity in the amygdala as the students looked at pictures of faces expressing different emotions.

At the beginning of the study, before any training, students who reported higher stress levels showed more amygdala activity when they saw fearful faces. This is consistent with previous research showing that the amygdala can be overactive in people who experience more stress, leading them to have stronger negative reactions to adverse events.

“There’s a lot of evidence that an overly strong amygdala response to negative things is associated with high stress in early childhood and risk for depression,” Gabrieli says.

After the mindfulness training, students showed a smaller amygdala response when they saw the fearful faces, consistent with their reports that they felt less stressed. This suggests that mindfulness training could potentially help prevent or mitigate mood disorders linked with higher stress levels, the researchers say.

Richard Davidson, a professor of psychology and psychiatry at the University of Wisconsin, says that the findings suggest there could be great benefit to implementing mindfulness training in middle schools.

“This is really one of the very first rigorous studies with children of that age to demonstrate behavioral and neural benefits of a simple mindfulness training,” says Davidson, who was not involved in the study.

Evaluating mindfulness

In the other paper, which appeared in the journal Mind, Brain, and Education in June, the researchers did not perform any mindfulness training but used a questionnaire to evaluate mindfulness in more than 2,000 students in grades 5-8. The questionnaire was based on the Mindfulness Attention Awareness Scale, which is often used in mindfulness studies on adults. Participants are asked to rate how strongly they agree with statements such as “I rush through activities without being really attentive to them.”

The researchers compared the questionnaire results with students’ grades, their scores on statewide standardized tests, their attendance rates, and the number of times they had been suspended from school. Students who showed more mindfulness tended to have better grades and test scores, as well as fewer absences and suspensions.

“People had not asked that question in any quantitative sense at all, as to whether a more mindful child is more likely to fare better in school,” Gabrieli says. “This is the first paper that says there is a relationship between the two.”

The researchers now plan to do a full school-year study, with a larger group of students across many schools, to examine the longer-term effects of mindfulness training. Shorter programs like the two-month training used in the Behavioral Neuroscience study would most likely not have a lasting impact, Gabrieli says.

“Mindfulness is like going to the gym. If you go for a month, that’s good, but if you stop going, the effects won’t last,” he says. “It’s a form of mental exercise that needs to be sustained.”

The research was funded by the Walton Family Foundation, the Poitras Center for Psychiatric Disorders Research at the McGovern Institute for Brain Research, and the National Council of Science and Technology of Mexico. Camila Caballero ’13, now a graduate student at Yale University, is the lead author of the Mind, Brain, and Education study. Caballero and MIT postdoc Clemens Bauer are lead authors of the Behavioral Neuroscience study. Additional collaborators were from the Harvard Graduate School of Education, Transforming Education, Boston Collegiate Charter School, and Calmer Choice.

Ann Graybiel

Probing the Deep Brain

Ann Graybiel studies the basal ganglia, forebrain structures that are profoundly important for normal brain function. Dysfunction in these regions is implicated in neurologic and neuropsychiatric disorders ranging from Parkinson’s disease and Huntington’s disease to obsessive-compulsive disorder, anxiety and depression, and addiction. Graybiel’s laboratory is uncovering circuits underlying both the neural deficits related to these disorders, as well as the role that the basal ganglia play in guiding normal learning, motivation, and behavior.

John Gabrieli

Images of Mind

John Gabrieli’s goal is to understand the organization of memory, thought, and emotion in the human brain. In collaboration with clinical colleagues, Gabrieli uses brain imaging to better understand, diagnose, and select treatments for neurological and psychiatric diseases.

A major focus of the Gabrieli lab is the neural basis of learning in children. His team found structural differences in the brains of young children who are at risk for reading difficulties, even before they start learning to read. By studying these differences in children, Gabrieli hopes to identify ways to improve learning in the classroom and inform effective educational policies and practices.

Gabrieli is also interested in using the tools of neuroscience to personalize medicine. His team showed that brain scans can identify children who are vulnerable to depression before symptoms even appear, opening the possibility of earlier interventions to prevent episodes of depression. Brain scans may also help help predict which individuals with social anxiety disorder are most likely to benefit from a particular therapeutic intervention. Gabrieli’s team continues to explore the role of neuroimaging in other brain disorders, including schizophrenia, addiction, and bipolar disorder.

His team also studies a range of other research topics, including new strategies to cope with emotional stress, the benefits of mindfulness for academic performance and mental health, and the value of embracing neurodiversity to better understand autism.

What is CRISPR?

by The Brain |

CRISPR (which stands for Clustered Regularly Interspaced Short Palindromic Repeats) is not actually a single entity, but shorthand for a set of bacterial systems that are found with a hallmarked arrangement in the bacterial genome.

When CRISPR is mentioned, most people are likely thinking of CRISPR-Cas9, now widely known for its capacity to be re-deployed to target sequences of interest in eukaryotic cells, including human cells. Cas9 can be programmed to target specific stretches of DNA, but other enzymes have since been discovered that are able to edit DNA, including Cpf1 and Cas12b. Other CRISPR enzymes, Cas13 family members, can be programmed to target RNA and even edit and change its sequence.

The common theme that makes CRISPR enzymes so powerful, is that scientists can supply them with a guide RNA for a chosen sequence. Since the guide RNA can pair very specifically with DNA, or for Cas13 family members, RNA, researchers can basically provide a given CRISPR enzyme with a way of homing in on any sequence of interest. Once a CRISPR protein finds its target, it can be used to edit that sequence, perhaps removing a disease-associated mutation.

In addition, CRISPR proteins have been engineered to modulate gene expression and even signal the presence of particular sequences, as in the case of the Cas13-based diagnostic, SHERLOCK.

Do you have a question for The Brain? Ask it here.

Satrajit Ghosh

Personalized Medicine

A fundamental problem in psychiatry is that there are no biological markers for diagnosing mental illness or for indicating how best to treat it. Treatment decisions are based entirely on symptoms, and doctors and their patients will typically try one treatment, then if it does not work, try another, and perhaps another. Satrajit Ghosh hopes to change this picture, and his research suggests that individual brain scans and speaking patterns can hold valuable information for guiding psychiatrists and patients. His research group develops novel analytic platforms that use such information to create robust, predictive models around human health. Current areas include depression, suicide, anxiety disorders, autism, Parkinson’s disease, and brain tumors.

Neuroscientists get at the roots of pessimism

Anne Trafton |

Many patients with neuropsychiatric disorders such as anxiety or depression experience negative moods that lead them to focus on the possible downside of a given situation more than the potential benefit.

MIT neuroscientists have now pinpointed a brain region that can generate this type of pessimistic mood. In tests in animals, they showed that stimulating this region, known as the caudate nucleus, induced animals to make more negative decisions: They gave far more weight to the anticipated drawback of a situation than its benefit, compared to when the region was not stimulated. This pessimistic decision-making could continue through the day after the original stimulation.

The findings could help scientists better understand how some of the crippling effects of depression and anxiety arise, and guide them in developing new treatments.

“We feel we were seeing a proxy for anxiety, or depression, or some mix of the two,” says Ann Graybiel, an MIT Institute Professor, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study, which appears in the Aug. 9 issue of Neuron. “These psychiatric problems are still so very difficult to treat for many individuals suffering from them.”

The paper’s lead authors are McGovern Institute research affiliates Ken-ichi Amemori and Satoko Amemori, who perfected the tasks and have been studying emotion and how it is controlled by the brain. McGovern Institute researcher Daniel Gibson, an expert in data analysis, is also an author of the paper.

Emotional decisions

Graybiel’s laboratory has previously identified a neural circuit that underlies a specific kind of decision-making known as approach-avoidance conflict. These types of decisions, which require weighing options with both positive and negative elements, tend to provoke a great deal of anxiety. Her lab has also shown that chronic stress dramatically affects this kind of decision-making: More stress usually leads animals to choose high-risk, high-payoff options.

In the new study, the researchers wanted to see if they could reproduce an effect that is often seen in people with depression, anxiety, or obsessive-compulsive disorder. These patients tend to engage in ritualistic behaviors designed to combat negative thoughts, and to place more weight on the potential negative outcome of a given situation. This kind of negative thinking, the researchers suspected, could influence approach-avoidance decision-making.

To test this hypothesis, the researchers stimulated the caudate nucleus, a brain region linked to emotional decision-making, with a small electrical current as animals were offered a reward (juice) paired with an unpleasant stimulus (a puff of air to the face). In each trial, the ratio of reward to aversive stimuli was different, and the animals could choose whether to accept or not.

This kind of decision-making requires cost-benefit analysis. If the reward is high enough to balance out the puff of air, the animals will choose to accept it, but when that ratio is too low, they reject it. When the researchers stimulated the caudate nucleus, the cost-benefit calculation became skewed, and the animals began to avoid combinations that they previously would have accepted. This continued even after the stimulation ended, and could also be seen the following day, after which point it gradually disappeared.

This result suggests that the animals began to devalue the reward that they previously wanted, and focused more on the cost of the aversive stimulus. “This state we’ve mimicked has an overestimation of cost relative to benefit,” Graybiel says.

The study provides valuable insight into the role of the basal ganglia (a region that includes the caudate nucleus) in this type of decision-making, says Scott Grafton, a professor of neuroscience at the University of California at Santa Barbara, who was not involved in the research.

“We know that the frontal cortex and the basal ganglia are involved, but the relative contributions of the basal ganglia have not been well understood,” Grafton says. “This is a nice paper because it puts some of the decision-making process in the basal ganglia as well.”

A delicate balance

The researchers also found that brainwave activity in the caudate nucleus was altered when decision-making patterns changed. This change, discovered by Amemori, is in the beta frequency and might serve as a biomarker to monitor whether animals or patients respond to drug treatment, Graybiel says.

Graybiel is now working with psychiatrists at McLean Hospital to study patients who suffer from depression and anxiety, to see if their brains show abnormal activity in the neocortex and caudate nucleus during approach-avoidance decision-making. Magnetic resonance imaging (MRI) studies have shown abnormal activity in two regions of the medial prefrontal cortex that connect with the caudate nucleus.

The caudate nucleus has within it regions that are connected with the limbic system, which regulates mood, and it sends input to motor areas of the brain as well as dopamine-producing regions. Graybiel and Amemori believe that the abnormal activity seen in the caudate nucleus in this study could be somehow disrupting dopamine activity.

“There must be many circuits involved,” she says. “But apparently we are so delicately balanced that just throwing the system off a little bit can rapidly change behavior.”

The research was funded by the National Institutes of Health, the CHDI Foundation, the U.S. Office of Naval Research, the U.S. Army Research Office, MEXT KAKENHI, the Simons Center for the Social Brain, the Naito Foundation, the Uehara Memorial Foundation, Robert Buxton, Amy Sommer, and Judy Goldberg.

Ann Graybiel wins 2018 Gruber Neuroscience Prize

Anne Trafton |

Institute Professor Ann Graybiel, a professor in the Department of Brain and Cognitive Sciences and member of MIT’s McGovern Institute for Brain Research, is being recognized by the Gruber Foundation for her work on the structure, organization, and function of the once-mysterious basal ganglia. She was awarded the prize alongside Okihide Hikosaka of the National Institute of Health’s National Eye Institute and Wolfram Schultz of the University of Cambridge in the U.K.

The basal ganglia have long been known to play a role in movement, and the work of Graybiel and others helped to extend their roles to cognition and emotion. Dysfunction in the basal ganglia has been linked to a host of disorders including Parkinson’s disease, Huntington’s disease, obsessive-compulsive disorder and attention-deficit hyperactivity disorder, and to depression and anxiety disorders. Graybiel’s research focuses on the circuits thought to underlie these disorders, and on how these circuits act to help us form habits in everyday life.

“We are delighted that Ann has been honored with the Gruber Neuroscience Prize,” says Robert Desimone, director of the McGovern Institute. “Ann’s work has truly elucidated the complexity and functional importance of these forebrain structures. Her work has driven the field forward in a fundamental fashion, and continues to do so.’

Graybiel’s research focuses broadly on the striatum, a hub in basal ganglia-based circuits that is linked to goal-directed actions and habits. Prior to her work, the striatum was considered to be a primitive forebrain region. Graybiel found that the striatum instead has a complex architecture consisting of specialized zones: striosomes and the surrounding matrix. Her group went on to relate these zones to function, finding that striosomes and matrix differentially influence behavior. Among other important findings, Graybiel has shown that striosomes are focal points in circuits that link mood-related cortical regions with the dopamine-containing neurons of the midbrain, which are implicated in learning and motivation and which undergo degeneration in Parkinson’s disorder and other clinical conditions. She and her group have shown that these regions are activated by drugs of abuse, and that they influence decision-making, including decisions that require weighing of costs and benefits.

Graybiel continues to drive the field forward, finding that striatal neurons spike in an accentuated fashion and ‘bookend’ the beginning and end of behavioral sequences in rodents and primates. This activity pattern suggests that the striatum demarcates useful behavioral sequences such, in the case of rodents, pressing levers or running down mazes to receive a reward. Additionally, she and her group worked on miniaturized tools for chemical sensing and delivery as part of a continued drive toward therapeutic intervention in collaboration with the laboratories of Robert Langer in the Department of Chemical Engineering and Michael Cima, in the Department of Materials Science and Engineering.

“My first thought was of our lab, and how fortunate I am to work with such talented and wonderful people,” says Graybiel.  “I am deeply honored to be recognized by this prestigious award on behalf of our lab.”

The Gruber Foundation’s international prize program recognizes researchers in the areas of cosmology, neuroscience and genetics, and includes a cash award of $500,000 in each field. The medal given to award recipients also outlines the general mission of the foundation, “for the fundamental expansion of human knowledge,” and the prizes specifically honor those whose groundbreaking work fits into this paradigm.

Graybiel, a member of the MIT Class of 1971, has also previously been honored with the National Medal of Science, the Kavli Award, the James R. Killian Faculty Achievement Award at MIT, Woman Leader of Parkinson’s Science award from the Parkinson’s Disease Foundation, and has been recognized by the National Parkinson Foundation for her contributions to the understanding and treatment of Parkinson’s disease. Graybiel is a member of the National Academy of Sciences, the National Academy of Medicine, and the American Academy of Arts and Sciences.

The Gruber Neuroscience Prize will be presented in a ceremony at the annual meeting of the Society for Neuroscience in San Diego this coming November.

Stress can lead to risky decisions

Anne Trafton |

Making decisions is not always easy, especially when choosing between two options that have both positive and negative elements, such as deciding between a job with a high salary but long hours, and a lower-paying job that allows for more leisure time.

MIT neuroscientists have now discovered that making decisions in this type of situation, known as a cost-benefit conflict, is dramatically affected by chronic stress. In a study of mice, they found that stressed animals were far likelier to choose high-risk, high-payoff options.

The researchers also found that impairments of a specific brain circuit underlie this abnormal decision making, and they showed that they could restore normal behavior by manipulating this circuit. If a method for tuning this circuit in humans were developed, it could help patients with disorders such as depression, addiction, and anxiety, which often feature poor decision-making.

“One exciting thing is that by doing this very basic science, we found a microcircuit of neurons in the striatum that we could manipulate to reverse the effects of stress on this type of decision making. This to us is extremely promising, but we are aware that so far these experiments are in rats and mice,” says Ann Graybiel, an Institute Professor at MIT and member of the McGovern Institute for Brain Research.

Graybiel is the senior author of the paper, which appears in Cell on Nov. 16. The paper’s lead author is Alexander Friedman, a McGovern Institute research scientist.

Hard decisions

In 2015, Graybiel, Friedman, and their colleagues first identified the brain circuit involved in decision making that involves cost-benefit conflict. The circuit begins in the medial prefrontal cortex, which is responsible for mood control, and extends into clusters of neurons called striosomes, which are located in the striatum, a region associated with habit formation, motivation, and reward reinforcement.

In that study, the researchers trained rodents to run a maze in which they had to choose between one option that included highly concentrated chocolate milk, which they like, along with bright light, which they don’t like, and an option with dimmer light but weaker chocolate milk. By inhibiting the connection between cortical neurons and striosomes, using a technique known as optogenetics, they found that they could transform the rodents’ preference for lower-risk, lower-payoff choices to a preference for bigger payoffs despite their bigger costs.

In the new study, the researchers performed a similar experiment without optogenetic manipulations. Instead, they exposed the rodents to a short period of stress every day for two weeks.

Before experiencing stress, normal rats and mice would choose to run toward the maze arm with dimmer light and weaker chocolate milk about half the time. The researchers gradually increased the concentration of chocolate milk found in the dimmer side, and as they did so, the animals began choosing that side more frequently.

However, when chronically stressed rats and mice were put in the same situation, they continued to choose the bright light/better chocolate milk side even as the chocolate milk concentration greatly increased on the dimmer side. This was the same behavior the researchers saw in rodents that had the prefrontal cortex-striosome circuit disrupted optogenetically.

“The result is that the animal ignores the high cost and chooses the high reward,” Friedman says.

The findings help to explain how stress contributes to substance abuse and may worsen mental disorders, says Amy Arnsten, a professor of neuroscience and psychology at the Yale University School of Medicine, who was not involved in the research.

“Stress is ubiquitous, for both humans and animals, and its effects on brain and behavior are of central importance to the understanding of both normal function and neuropsychiatric disease. It is both pernicious and ironic that chronic stress can lead to impulsive action; in many clinical cases, such as drug addiction, impulsivity is likely to worsen patterns of behavior that produce the stress in the first place, inducing a vicious cycle,” Arnsten wrote in a commentary accompanying the Cell paper, co-authored by Daeyeol Lee and Christopher Pittenger of the Yale University School of Medicine.

Circuit dynamics

The researchers believe that this circuit integrates information about the good and bad aspects of possible choices, helping the brain to produce a decision. Normally, when the circuit is turned on, neurons of the prefrontal cortex activate certain neurons called high-firing interneurons, which then suppress striosome activity.

When the animals are stressed, these circuit dynamics shift and the cortical neurons fire too late to inhibit the striosomes, which then become overexcited. This results in abnormal decision making.

“Somehow this prior exposure to chronic stress controls the integration of good and bad,” Graybiel says. “It’s as though the animals had lost their ability to balance excitation and inhibition in order to settle on reasonable behavior.”

Once this shift occurs, it remains in effect for months, the researchers found. However, they were able to restore normal decision making in the stressed mice by using optogenetics to stimulate the high-firing interneurons, thereby suppressing the striosomes. This suggests that the prefronto-striosome circuit remains intact following chronic stress and could potentially be susceptible to manipulations that would restore normal behavior in human patients whose disorders lead to abnormal decision making.

“This state change could be reversible, and it’s possible in the future that you could target these interneurons and restore the excitation-inhibition balance,” Friedman says.

The research was funded by the National Institutes of Health/National Institute for Mental Health, the CHDI Foundation, the Defense Advanced Research Projects Agency and the U.S. Army Research Office, the Bachmann-Strauss Dystonia and Parkinson Foundation, the William N. and Bernice E. Bumpus Foundation, Michael Stiefel, the Saks Kavanaugh Foundation, and John Wasserlein and Lucille Braun.

Rethinking mental illness treatment

by Elizabeth Dougherty |

McGovern researchers are finding neural markers that could help improve treatment for psychiatric patients.

Ten years ago, Jim and Pat Poitras committed $20M to the McGovern Institute to establish the Poitras Center for Affective Disorders Research. The Poitras family had been longtime supporters of MIT, and because they had seen mental illness in their own family, they decided to support an ambitious new program at the McGovern Institute, with the goal of understanding the fundamental biological basis of depression, bipolar disorder, schizophrenia and other major psychiatric disorders.

The gift came at an opportune time, as the field was entering a new phase of discovery, with rapid advances in psychiatric genomics and brain imaging, and with the emergence of new technologies for genome editing and for the development of animal models. Over the past ten years, the Poitras Center has supported work in each of these areas, including Feng Zhang’s work on CRISPR-based genome editing, and Guoping Feng’s work on animal models for autism, schizophrenia and other psychiatric disorders.

This reflects a long-term strategy, says Robert Desimone, director of the McGovern Institute who oversees the Poitras Center. “But we must not lose sight of the overall goal, which is to benefit human patients. Insights from animal models and genomic medicine have the potential to transform the treatments of the future, but we are also interested in the nearer term, and in what we can do right now.”

One area where technology can have a near-term impact is human brain imaging, and in collaboration with clinical researchers at McLean Hospital, Massachusetts General Hospital and other institutions, the Poitras Center has supported an ambitious program to bring human neuroimaging closer to the clinic.

Discovering psychiatry’s crystal ball

A fundamental problem in psychiatry is that there are no biological markers for diagnosing mental illness or for indicating how best to treat it. Treatment decisions are based entirely on symptoms, and doctors and their patients will typically try one treatment, then if it does not work, try another, and perhaps another. The success rates for the first treatments are often less than 50%, and finding what works for an individual patient often means a long and painful process of trial and error.

“Someday, a person will be able to go to a hospital, get a brain scan, charge it to their insurance, and know that it helped the doctor select the best treatment,” says Satra Ghosh.

McGovern research scientist Susan Whitfield-Gabrieli and her colleagues are hoping to change this picture, with the help of brain imaging. Their findings suggest that brain scans can hold valuable information for psychiatrists and their patients. “We need a paradigm shift in how we use imaging. It can be used for more than research,” says Whitfield-Gabrieli, who is a member of McGovern Investigator John Gabrieli’s lab. “It would be a really big boost to be able use it to personalize psychiatric medicine.”

One of Whitfield-Gabrieli’s goals is to find markers that can predict which treatments will work for which patients. Another is to find markers that can predict the likely risk of disease in the future, allowing doctors to intervene before symptoms first develop. All of these markers need further validation before they are ready for the clinic, but they have the potential to meet a dire need to improve treatment for psychiatric disease.

A brain at rest

For Whitfield-Gabrieli, who both collaborates with and is married to Gabrieli, that paradigm shift began when she started to study the resting brain using functional magnetic resonance imaging (fMRI). Most brain imaging studies require the subject to perform a mental task in the scanner, but these are time-consuming and often hard to replicate in a clinical setting.In contrast, resting state imaging requires no task. The subject simply lies in the scanner and lets the mind wander. The patterns of activity can reveal functional connections within the brain, and are reliably consistent from study to study.

Whitfield-Gabrieli thought resting state scanning had the potential to help patients because it is simple and easy to perform.

“Even a 5-minute scan can contain useful information that could help people,” says Satrajit Ghosh, a principal research scientist in the Gabrieli lab who works closely with Whitfield-Gabrieli.

Whitfield-Gabrieli and her clinical collaborator Larry Seidman at Harvard Medical School decided to study resting state activity in patients with schizophrenia. They found a pattern of activity strikingly different from that of typical brains. The patients showed unusually strong activity in a set of interconnected brain regions known as the default mode network, which is typically activated during introspection. It is normally suppressed when a person attends to the outside world, but schizophrenia patients failed to show this suppression.

“The patient isn’t able to toggle between internal processing and external processing the way a typical individual can,” says Whitfield-Gabrieli, whose work is supported by the Poitras Center for Affective Disorders Research.

Since then, the team has observed similar disturbances in the default network in other disorders, including depression, anxiety, bipolar disorder, and ADHD. “We knew we were onto something interesting,” says Whitfield-Gabrieli. “But we kept coming back to the question: how can brain imaging help patients?”

fMRI on patients

Many imaging studies aim to understand the biological basis of disease and ultimately to guide the development of new drugs or other treatments. But this is a long-term goal, and Whitfield-Gabrieli wanted to find ways that brain imaging could have a more immediate impact. So she and Ghosh decided to use fMRI to look at differences among individual patients, and to focus on differences in how they responded to treatment.

“It gave us something objective to measure,” explains Ghosh. “Someone goes through a treatment, and they either get better or they don’t.” The project also had appeal for Ghosh because it was an opportunity for him to use his expertise in machine learning and other computational tools to build systems-level models of the brain.

For the first study, the team decided to focus on social anxiety disorder (SAD), which is typically treated with either prescription drugs or cognitive behavioral therapy (CBT). Both are moderately effective, but many patients do not respond to the first treatment they try.

The team began with a small study to test whether scans performed before the onset of treatment could predict who would respond best to the treatment. Working with Stefan Hofmann, a clinical psychologist at Boston University, they scanned 38 SAD patients before they began a 12-week course of CBT. At the end of their treatment, the patients were evaluated for clinical improvement, and the researchers examined the scans for patterns of activity that correlated with the improvement. The results were very encouraging; it turned out that predictions based on scan data were 5-fold better than the existing methods based on severity of symptoms at the time of diagnosis.

The researchers then turned to another condition, ADHD, which presents a similar clinical challenge, in that commonly used drugs—such as Adderall or Ritalin—work well, but not for everyone. So the McGovern team began a collaboration with psychiatrist Joseph Biederman, Chief of Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD
at Massachusetts General Hospital, on a similar study, looking for markers of treatment response.

The study is still ongoing, and it will be some time before results emerge, but the researchers are optimistic. “If we could predict who would respond to which treatment and avoid months of trial and error, it would be totally transformative for ADHD,” says Biederman.

Another goal is to predict in advance who is likely to develop a given disease in the future. The researchers have scanned children who have close relatives with schizophrenia or depression, and who are therefore at increased risk of developing these disorders themselves. Surprisingly, the children show patterns of resting state connectivity similar to those of patients.

“I was really intrigued by this,” says Whitfield-Gabrieli. “Even though these children are not sick, they have the same profile as adults who are.”

Whitfield-Gabrieli and Seidman are now expanding their study through a collaboration with clinical researchers at the Shanghai Mental Institute in China, who plan to image and then follow 225 people who are showing early risk signs for schizophrenia. They hope to find markers that predict who will develop the disease and who will not.

“While there are no drugs available to prevent schizophrenia, it may be possible to reduce the risk or severity of the disorder through CBT, or through interventions that reduce stress and improve sleep and well-being,” says Whitfield-Gabrieli. “One likely key to success is early identification of those at highest risk. If we could diagnose early, we could do early interventions
and potentially prevent disorders.”

From association to prediction

The search for predictive markers represents a departure from traditional psychiatric imaging studies, in which a group of patients is compared with a control group of healthy subjects. Studies of this type can reveal average differences between the groups, which may provide clues to the underlying biology of the disease. But they don’t provide information about individual patients, and so they have not been incorporated into clinical practice.

The difference is critical for clinicians, says Biederman. “I treat individuals, not groups. To bring predictive scans to the clinic, we need to be sure the individual scan is informative for the person you are treating.”

To develop these predictions, Whitfield-Gabrieli and Ghosh must first use sophisticated computational methods such as ‘deep learning’ to identify patterns in their data and to build models that relate the patterns to the clinical outcomes. They must then show that these models can generalize beyond the original study population—for example, that predictions based on patients from Boston can be applied to patients from Shanghai. The eventual goal is a model that can analyze a previously unseen brain scan from any individual, and predict with high confidence whether that person will (for example) develop schizophrenia or respond successfully to a particular therapy.

Achieving this will be challenging, because it will require scanning and following large numbers of subjects from diverse demographic groups—thousands of people, not just tens or hundreds
as in most clinical studies. Collaborations with large hospitals, such as the one in Shanghai, can help. Whitfield-Gabrieli has also received funding to collect imaging, clinical, and behavioral
data from over 200 adolescents with depression and anxiety, as part of the National Institutes of Health’s Human Connectome effort. These data, collected in collaboration with clinicians at
McLean Hospital, MGH and Boston University, will be available not only for the Gabrieli team, but for researchers anywhere to analyze. This is important, because no one team or center can
do it alone, says Ghosh. “Data must be collected by many and shared by all.”

The ultimate goal is to study as many patients as possible now so that the tools can help many more later. “Someday, a person will be able to go to a hospital, get a brain scan, charge it to their insurance, and know that it helped the doctor select the best treatment,” says Ghosh. “We’re still far away from that. But that is what we want to work towards.”