Personal pursuits

This story originally appeared in the Fall 2022 issue of BrainScan.

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Many neuroscientists were drawn to their careers out of curiosity and wonder. Their deep desire to understand how the brain works drew them into the lab and keeps them coming back, digging deeper and exploring more each day. But for some, the work is more personal.

Several McGovern faculty say they entered their field because someone in their lives was dealing with a brain disorder that they wanted to better understand. They are committed to unraveling the basic biology of those conditions, knowing that knowledge is essential to guide the development of better treatments.

The distance from basic research to clinical progress is shortening, and many young neuroscientists hope not just to deepen scientific understanding of the brain, but to have direct impact on the lives of patients. Some want to know why people they love are suffering from neurological disorders or mental illness; others seek to understand the ways in which their own brains work differently than others. But above all, they want better treatments for people affected by such disorders.

Seeking answers

That’s true for Kian Caplan, a graduate student in MIT’s Department of Brain and Cognitive Sciences who was diagnosed with Tourette syndrome around age 13. At the time, learning that the repetitive, uncontrollable movements and vocal tics he had been making for most of his life were caused by a neurological disorder was something of a relief. But it didn’t take long for Caplan to realize his diagnosis came with few answers.

Graduate student Kian Caplan studies the brain circuits associated with Tourette syndrome and obsessive-compulsive disorder in Guoping Feng and Fan Wang’s labs at the McGovern Institute. Photo: Steph Stevens

Tourette syndrome has been estimated to occur in about six of every 1,000 children, but its neurobiology remains poorly understood.

“The doctors couldn’t really explain why I can’t control the movements and sounds I make,” he says. “They couldn’t really explain why my symptoms wax and wane, or why the tics I have aren’t always the same.”

That lack of understanding is not just frustrating for curious kids like Caplan. It means that researchers have been unable to develop treatments that target the root cause of Tourette syndrome. Drugs that dampen signaling in parts of the brain that control movement can help suppress tics, but not without significant side effects. Caplan has tried those drugs. For him, he says, “they’re not worth the suppression.”

Advised by Fan Wang and McGovern Associate Director Guoping Feng, Caplan is looking for answers. A mouse model of obsessive-compulsive disorder developed in Feng’s lab was recently found to exhibit repetitive movements similar to those of people with Tourette syndrome, and Caplan is working to characterize those tic-like movements. He will use the mouse model to examine the brain circuits underlying the two conditions, which often co-occur in people. Broadly, researchers think Tourette syndrome arises due to dysregulation of cortico-striatal-thalamo-cortical circuits, which connect distant parts of the brain to control movement. Caplan and Wang suspect that the brainstem — a structure found where the brain connects to the spinal cord, known for organizing motor movement into different modules — is probably involved, too.

Wang’s research group studies the brainstem’s role in movement, but she says that like most researchers, she hadn’t considered its role in Tourette syndrome until Caplan joined her lab. That’s one reason Caplan, who has long been a mentor and advocate for students with neurodevelopmental disorders, thinks neuroscience needs more neurodiversity.

“I think we need more representation in basic science research by the people who actually live with those conditions,” he says. Their experiences can lead to insights that may be inaccessible to others, he says, but significant barriers in academia often prevent this kind of representation. Caplan wants to see institutions make systemic changes to ensure that neurodiverse and otherwise minority individuals are able to thrive in academia. “I’m not an exception,” he says, “there should be more people like me here, but the present system makes that incredibly difficult.”

Overcoming adversity

Like Caplan, Lace Riggs faced significant challenges in her pursuit to study the brain. She grew up in Southern California’s Inland Empire, where issues of social disparity, chronic stress, drug addiction, and mental illness were a part of everyday life.

Postdoctoral fellow Lace Riggs studies the origins of neurodevelopmental conditions in Guoping Feng’s lab at the McGovern Institute. Photo: Lace Riggs

“Living in severe poverty and relying on government assistance without access to adequate education and resources led everyone I know and love to suffer tremendously, myself included,” says Riggs, a postdoctoral fellow in the Feng lab.

“There are not a lot of people like me who make it to this stage,” says Riggs, who has lost friends and family members to addiction, mental illness, and suicide. “There’s a reason for that,” she adds. “It’s really, really difficult to get through the educational system and to overcome socioeconomic barriers.”

Today, Riggs is investigating the origins of neurodevelopmental conditions, hoping to pave the way to better treatments for brain disorders by uncovering the molecular changes that alter the structure and function of neural circuits.

Riggs says that the adversities she faced early in life offered valuable insights in the pursuit of these goals. She first became interested in the brain because she wanted to understand how our experiences have a lasting impact on who we are — including in ways that leave people vulnerable to psychiatric problems.

“While the need for more effective treatments led me to become interested in psychiatry, my fascination with the brain’s unique ability to adapt is what led me to neuroscience,” says Riggs.

After finishing high school, Riggs attended California State University in San Bernardino and became the only member of her family to attend university or attempt a four-year degree. Today, she spends her days working with mice that carry mutations linked to autism or ADHD in humans, studying the animals’ behavior and monitoring their neural activity. She expects that aberrant neural circuit activity in these conditions may also contribute to mood disorders, whose origins are harder to tease apart because they often arise when genetic and environmental factors intersect. Ultimately, Riggs says, she wants to understand how our genes dictate whether an experience will alter neural signaling and impact mental health in a long-lasting way.

Riggs uses patch clamp electrophysiology to record the strength of inhibitory and excitatory synaptic input onto individual neurons (white arrow) in an animal model of autism. Image: Lace Riggs

“If we understand how these long-lasting synaptic changes come about, then we might be able to leverage these mechanisms to develop new and more effective treatments.”

While the turmoil of her childhood is in the past, Riggs says it is not forgotten — in part, because of its lasting effects on her own mental health.  She talks openly about her ongoing struggle with social anxiety and complex post-traumatic stress disorder because she is passionate about dismantling the stigma surrounding these conditions. “It’s something I have to deal with every day,” Riggs says. That means coping with symptoms like difficulty concentrating, hypervigilance, and heightened sensitivity to stress. “It’s like a constant hum in the background of my life, it never stops,” she says.

“I urge all of us to strive, not only to make scientific discoveries to move the field forward,” says Riggs, “but to improve the accessibility of this career to those whose lived experiences are required to truly accomplish that goal.”

Studies of autism tend to exclude women, researchers find

In recent years, researchers who study autism have made an effort to include more women and girls in their studies. However, despite these efforts, most studies of autism consistently enroll small numbers of female subjects or exclude them altogether, according to a new study from MIT.

The researchers found that a screening test commonly used to determine eligibility for studies of autism consistently winnows out a much higher percentage of women than men, creating a “leaky pipeline” that results in severe underrepresentation of women in studies of autism.

This lack of representation makes it more difficult to develop useful interventions or provide accurate diagnoses for girls and women, the researchers say.

“I think the findings favor having a more inclusive approach and widening the lens to end up being less biased in terms of who participates in research,” says John Gabrieli, the Grover Hermann Professor of Health Sciences and Technology and a professor of brain and cognitive sciences at MIT. “The more we understand autism in men and women and nonbinary individuals, the better services and more accurate diagnoses we can provide.”

Gabrieli, who is also a member of MIT’s McGovern Institute for Brain Research, is the senior author of the study, which appears in the journal Autism Research. Anila D’Mello, a former MIT postdoc who is now an assistant professor at the University of Texas Southwestern, is the lead author of the paper. MIT Technical Associate Isabelle Frosch, Research Coordinator Cindy Li, and Research Specialist Annie Cardinaux are also authors of the paper.

Gabrieli lab researchers Annie Cardinaux (left), Anila D’Mello (center), Cindy Li (right), and Isabelle Frosch (not pictured) have
uncovered sex biases in ASD research. Photo: Steph Stevens

Screening out females

Autism spectrum disorders are diagnosed based on observation of traits such as repetitive behaviors and difficulty with language and social interaction. Doctors may use a variety of screening tests to help them make a diagnosis, but these screens are not required.

For research studies of autism, it is routine to use a screening test called the Autism Diagnostic Observation Schedule (ADOS) to determine eligibility for the study. This test, which assesses social interaction, communication, play, and repetitive behaviors, provides a quantitative score in each category, and only participants who reach certain scores qualify for inclusion in studies.

While doing a study exploring how quickly the brains of autistic adults adapt to novel events in the environment, scientists in Gabrieli’s lab began to notice that the ADOS appeared to have unequal effects on male and female participation in research. As the study progressed, D’Mello noticed some significant brain differences between the male and female subjects in the study.

To investigate these differences further, D’Mello tried to find more female participants using an MIT database of autistic adults who have expressed interest in participating in research studies. However, when she sorted through the subjects, she found that only about half of the women in the database had met the ADOS cutoff scores typically required for inclusion in autism studies, compared to 80 percent of the males.

“We realized then that there’s a discrepancy and that the ADOS is essentially screening out who eventually participated in research,” D’Mello says. “We were really surprised at how many males we retained and how many females we lost to the ADOS.”

To see if this phenomenon was more widespread, the researchers looked at six publicly available datasets, which include more than 40,000 adults who have been diagnosed as autistic. For some of these datasets, participants were screened with ADOS to determine their eligibility to participate in studies, while for others, a “community diagnosis” — diagnosis from a doctor or other health care provider — was sufficient.

The researchers found that in datasets that required ADOS screening for eligibility, the ratio of male to female participants ended up being around 8:1, while in those that required only a community diagnosis the ratios ranged from about 2:1 to 1:1.

Previous studies have found differences between behavioral patterns in autistic men and women, but the ADOS test was originally developed using a largely male sample, which may explain why it often excludes women from research studies, D’Mello says.

“There were few females in the sample that was used to create this assessment, so it might be that it’s not great at picking up the female phenotype, which may differ in certain ways — primarily in domains like social communication,” she says.

Effects of exclusion

Failure to include more women and girls in studies of autism may contribute to shortcomings in the definitions of the disorder, the researchers say.

“The way we think about it is that the field evolved perhaps an implicit bias in how autism is defined, and it was driven disproportionately by analysis of males, and recruitment of males, and so on,” Gabrieli says. “So, the definition doesn’t fit as well, on average, with the different expression of autism that seems to be more common in females.”

This implicit bias has led to documented difficulties in receiving a diagnosis for girls and women, even when their symptoms are the same as those presented by autistic boys and men.

“Many females might be missed altogether in terms of diagnoses, and then our study shows that in the research setting, what is already a small pool gets whittled down at a much larger rate than that of males,” D’Mello says.

Excluding girls and women from this kind of research study can lead to treatments that don’t work as well for them, and it contributes to the perception that autism doesn’t affect women as much as men.

“The goal is that research should directly inform treatment, therapies, and public perception,” D’Mello says. “If the research is saying that there aren’t females with autism, or that the brain basis of autism only looks like the patterns established in males, then you’re not really helping females as much as you could be, and you’re not really getting at the truth of what the disorder might be.”

The researchers now plan to further explore some of the gender and sex-based differences that appear in autism, and how they arise. They also plan to expand the gender categories that they include. In the current study, the surveys that each participant filled out asked them to choose male or female, but the researchers have updated their questionnaire to include nonbinary and transgender options.

The research was funded by the Hock E. Tan and K. Lisa Yang Center for Autism Research, the Simons Center for the Social Brain at MIT, and the National Institutes of Mental Health.

Artificial neural networks model face processing in autism

Many of us easily recognize emotions expressed in others’ faces. A smile may mean happiness, while a frown may indicate anger. Autistic people often have a more difficult time with this task. It’s unclear why. But new research, published today in The Journal of Neuroscience, sheds light on the inner workings of the brain to suggest an answer. And it does so using a tool that opens new pathways to modeling the computation in our heads: artificial intelligence.

Researchers have primarily suggested two brain areas where the differences might lie. A region on the side of the primate (including human) brain called the inferior temporal (IT) cortex contributes to facial recognition. Meanwhile, a deeper region called the amygdala receives input from the IT cortex and other sources and helps process emotions.

Kohitij Kar, a research scientist in the lab of MIT Professor James DiCarlo, hoped to zero in on the answer. (DiCarlo, the Peter de Florez Professor in the Department of Brain and Cognitive Sciences, is a member of the McGovern Institute for Brain Research and director of MIT’s Quest for Intelligence.)

Kar began by looking at data provided by two other researchers: Shuo Wang, at Washington University in St. Louis, and Ralph Adolphs, at the California Institute of Technology. In one experiment, they showed images of faces to autistic adults and to neurotypical controls. The images had been generated by software to vary on a spectrum from fearful to happy, and the participants judged, quickly, whether the faces depicted happiness. Compared with controls, autistic adults required higher levels of happiness in the faces to report them as happy.

Modeling the brain

Kar, who is also a member of the Center for Brains, Minds and Machines, trained an artificial neural network, a complex mathematical function inspired by the brain’s architecture, to perform the same task. The network contained layers of units that roughly resemble biological neurons that process visual information. These layers process information as it passes from an input image to a final judgment indicating the probability that the face is happy. Kar found that the network’s behavior more closely matched the neurotypical controls than it did the autistic adults.

The network also served two more interesting functions. First, Kar could dissect it. He stripped off layers and retested its performance, measuring the difference between how well it matched controls and how well it matched autistic adults. This difference was greatest when the output was based on the last network layer. Previous work has shown that this layer in some ways mimics the IT cortex, which sits near the end of the primate brain’s ventral visual processing pipeline. Kar’s results implicate the IT cortex in differentiating neurotypical controls from autistic adults.

The other function is that the network can be used to select images that might be more efficient in autism diagnoses. If the difference between how closely the network matches neurotypical controls versus autistic adults is greater when judging one set of images versus another set of images, the first set could be used in the clinic to detect autistic behavioral traits. “These are promising results,” Kar says. Better models of the brain will come along, “but oftentimes in the clinic, we don’t need to wait for the absolute best product.”

Next, Kar evaluated the role of the amygdala. Again, he used data from Wang and colleagues. They had used electrodes to record the activity of neurons in the amygdala of people undergoing surgery for epilepsy as they performed the face task. The team found that they could predict a person’s judgment based on these neurons’ activity. Kar re-analyzed the data, this time controlling for the ability of the IT-cortex-like network layer to predict whether a face truly was happy. Now, the amygdala provided very little information of its own. Kar concludes that the IT cortex is the driving force behind the amygdala’s role in judging facial emotion.

Noisy networks

Finally, Kar trained separate neural networks to match the judgments of neurotypical controls and autistic adults. He looked at the strengths or “weights” of the connections between the final layers and the decision nodes. The weights in the network matching autistic adults, both the positive or “excitatory” and negative or “inhibitory” weights, were weaker than in the network matching neurotypical controls. This suggests that sensory neural connections in autistic adults might be noisy or inefficient.

To further test the noise hypothesis, which is popular in the field, Kar added various levels of fluctuation to the activity of the final layer in the network modeling autistic adults. Within a certain range, added noise greatly increased the similarity between its performance and that of the autistic adults. Adding noise to the control network did much less to improve its similarity to the control participants. This further suggest that sensory perception in autistic people may be the result of a so-called “noisy” brain.

Computational power

Looking forward, Kar sees several uses for computational models of visual processing. They can be further prodded, providing hypotheses that researchers might test in animal models. “I think facial emotion recognition is just the tip of the iceberg,” Kar says. They can also be used to select or even generate diagnostic content. Artificial intelligence could be used to generate content like movies and educational materials that optimally engages autistic children and adults. One might even tweak facial and other relevant pixels in what autistic people see in augmented reality goggles, work that Kar plans to pursue in the future.

Ultimately, Kar says, the work helps to validate the usefulness of computational models, especially image-processing neural networks. They formalize hypotheses and make them testable. Does one model or another better match behavioral data? “Even if these models are very far off from brains, they are falsifiable, rather than people just making up stories,” he says. “To me, that’s a more powerful version of science.”

Circuit that focuses attention brings in wide array of inputs

In a new brain-wide circuit tracing study, scientists at MIT’s Picower Institute for Learning and Memory focused selective attention on a circuit that governs, fittingly enough, selective attention. The comprehensive maps they produced illustrate how broadly the mammalian brain incorporates and integrates information to focus its sensory resources on its goals.

Working in mice, the team traced thousands of inputs into the circuit, a communication loop between the anterior cingulate cortex (ACC) and the lateral posterior (LP) thalamus. In primates the LP is called the pulvinar. Studies in humans and nonhuman primates have indicated that the byplay of these two regions is critical for brain functions like being able to focus on an object of interest in a crowded scene, says study co-lead author Yi Ning Leow, a graduate student in the lab of senior author Mriganka Sur, the Newton Professor in MIT’s Department of Brain and Cognitive Sciences. Research has implicated dysfunction in the circuit in attention-affecting disorders such as autism and attention deficit/hyperactivity disorder.

The new study in the Journal of Comparative Neurology extends what’s known about the circuit by detailing it in mice, Leow says, importantly showing that the mouse circuit is closely analogous to the primate version even if the LP is proportionately smaller and less evolved than the pulvinar.

“In these rodent models we were able to find very similar circuits,” Leow says. “So we can possibly study these higher-order functions in mice as well. We have a lot more genetic tools in mice so we are better able to look at this circuit.”

The study, also co-led by former MIT undergraduate Blake Zhou, therefore provides a detailed roadmap in the experimentally accessible mouse model for understanding how the ACC and LP cooperate to produce selective attention. For instance, now that Leow and Zhou have located all the inputs that are wired into the circuit, Leow is tapping into those feeds to eavesdrop on the information they are carrying. Meanwhile, she is correlating that information flow with behavior.

“This study lays the groundwork for understanding one of the most important, yet most elusive, components of brain function, namely our ability to selectively attend to one thing out of several, as well as switch attention,” Sur says.

Using virally mediated circuit-tracing techniques pioneered by co-author Ian Wickersham, principal research scientist in brain and cognitive sciences and the McGovern Institute for Brain Research at MIT, the team found distinct sources of input for the ACC and the LP. Generally speaking, the detailed study finds that the majority of inputs to the ACC were from frontal cortex areas that typically govern goal-directed planning, and from higher visual areas. The bulk of inputs to the LP, meanwhile, were from deeper regions capable of providing context such as the mouse’s needs, location and spatial cues, information about movement, and general information from a mix of senses.

So even though focusing attention might seem like a matter of controlling the senses, Leow says, the circuit pulls in a lot of other information as well.

“We’re seeing that it’s not just sensory — there are so many inputs that are coming from non-sensory areas as well, both sub-cortically and cortically,” she says. “It seems to be integrating a lot of different aspects that might relate to the behavioral state of the animal at a given time. It provides a way to provide a lot of internal and special context for that sensory information.”

Given the distinct sets of inputs to each region, the ACC may be tasked with focusing attention on a desired object, while the LP is modulating how the ACC goes about making those computations, accounting for what’s going on both inside and outside the animal. Decoding just what that incoming contextual information is, and what the LP tells the ACC, are the key next steps, Leow says. Another clear set of questions the study raises are what are the circuit’s outputs. In other words, after it integrates all this information, what does it do with it?

The paper’s other authors are Heather Sullivan and Alexandria Barlowe.

A National Science Scholarship, the National Institutes of Health, and the JPB Foundation provided support for the study.

Five MIT faculty elected 2021 AAAS Fellows

Five MIT faculty members have been elected as fellows of the American Association for the Advancement of Science (AAAS).

The 2021 class of AAAS Fellows includes 564 scientists, engineers, and innovators spanning 24 scientific disciplines who are being recognized for their scientifically and socially distinguished achievements.

Mircea Dincă is the W. M. Keck Professor of Energy in the Department of Chemistry. His group’s research focuses on addressing challenges related to the storage and consumption of energy, and global environmental concerns. Central to these efforts are the synthesis of novel organic-inorganic hybrid materials and the manipulation of their electrochemical and photophysical properties, with a current emphasis on porous materials and extended one-dimensional van der Waals materials.

Guoping Feng is the James W. and Patricia T. Poitras Professor of Neuroscience in the Department of Brain and Cognitive Sciences, associate director of MIT’s McGovern Institute for Brain Research, director of Model Systems and Neurobiology at the Stanley Center for Psychiatric Research, and an institute member of the Broad Institute of MIT and Harvard. His research is devoted to understanding the development and function of synapses in the brain and how synaptic dysfunction may contribute to neurodevelopmental and psychiatric disorders. By understanding the molecular, cellular, and circuitry mechanisms of these disorders, Feng hopes his work will eventually lead to the development of new and effective treatments for the millions of people suffering from these devastating diseases.

David Shoemaker is a senior research scientist with the MIT Kavli Institute for Astrophysics and Space Research. His work is focused on gravitational-wave observation and includes developing technologies for the detectors (LIGO, LISA), developing proposals for new instruments (Cosmic Explorer), managing the teams to build them and the consortia which exploit the data (LIGO Scientific Collaboration, LISA Consortium), and supporting the overall growth of the field (Gravitational-Wave International Committee).

Ian Hunter is the Hatsopoulos Professor of Mechanical Engineering and runs the Bioinstrumentation Lab at MIT. His main areas of research are instrumentation, microrobotics, medical devices, and biomimetic materials. Over the years he and his students have developed many instruments and devices including: confocal laser microscopes, scanning tunneling electron microscopes, miniature mass spectrometers, new forms of Raman spectroscopy, needle-free drug delivery technologies, nano- and micro-robots, microsurgical robots, robotic endoscopes, high-performance Lorentz force motors, and microarray technologies for massively parallel chemical and biological assays.

Evelyn N. Wang is the Ford Professor of Engineering and head of the Department of Mechanical Engineering. Her research program combines fundamental studies of micro/nanoscale heat and mass transport processes with the development of novel engineered structures to create innovative solutions in thermal management, energy, and water harvesting systems. Her work in thermophotovoltaics was named to Technology Review’s lists of Biggest Clean Energy Advances, in 2016, and Ten Breakthrough Technologies, in 2017, and to the Department of Energy Frontiers Research Center’s Ten of Ten awards. Her work extracting water from air has won her the title of 2017 Foreign Policy’s Global ReThinker and the 2018 Eighth Prince Sultan bin Abdulaziz International Prize for Water.

Single gene linked to repetitive behaviors, drug addiction

Making and breaking habits is a prime function of the striatum, a large forebrain region that underlies the cerebral cortex. McGovern researchers have identified a particular gene that controls striatal function as well as repetitive behaviors that are linked to drug addiction vulnerability.

To identify genes involved specifically in striatal functions, MIT Institute Professor Ann Graybiel previously identified genes that are preferentially expressed in striatal neurons. One identified gene encodes CalDAG-GEFI (CDGI), a signaling molecule that effects changes inside of cells in response to extracellular signals that are received by receptors on the cell surface. In a paper to be published in the October issue of Neurobiology of Disease and now available online, Graybiel, along with former Research Scientist Jill Crittenden and collaborators James Surmeier and Shenyu Zhai at the Feinman School of Medicine at Northwestern University, show that CDGI is key for controlling behavioral responses to drugs of abuse and underlying neuronal plasticity (cellular changes induced by experience) in the striatum.

“This paper represents years of intensive research, which paid off in the end by identifying a specific cellular signaling cascade for controlling repetitive behaviors and neuronal plasticity,” says Graybiel, who is also an investigator at the McGovern Institute and a professor of brain and cognitive sciences at MIT.

McGovern Investigator Ann Graybiel (right) with former Research Scientist Jill Crittenden. Photo: Justin Knight

Surprise discovery

To understand the essential roles of CDGI, Crittenden first engineered “knockout” mice that lack the gene encoding CDGI. Then the Graybiel team began looking for abnormalities in the CDGI knockout mice that could be tied to the loss of CDGI’s function.

Initially, they noticed that the rodent ear-tag IDs often fell off in the knockout mice, an observation that ultimately led to the surprise discovery by the Graybiel team and others that CDGI is expressed in blood platelets and is responsible for a bleeding disorder in humans, dogs, and other animals. The CDGI knockout mice were otherwise healthy and seemed just like their “wildtype” brothers and sisters, which did not carry the gene mutation. To figure out the role of CDGI in the brain, the Graybiel team would have to scrutinize the mice more closely.

Challenging the striatum

Both the CDGI knockout and wildtype mice were given an extensive set of behavioral and neurological tests and the CDGI mice showed deficits in two tests designed to challenge the striatum.

In one test, mice must find their way through a maze by relying on egocentric (i.e. self-referential) cues, such as their turning right or turning left, and not competing allocentric (i.e. external) cues, such as going toward a bright poster on the wall. Egocentric cues are thought to be processed by the striatum whereas allocentric cues are thought to rely on the hippocampus.

In a second test of striatal function, mice learned various gait patterns to match different patterns of rungs on their running wheel, a task designed to test the mouse’s ability to learn and remember a motor sequence.

The CDGI mice learned both of these striatal tasks more slowly than their wildtype siblings, suggesting that the CDGI mice might perform normally in general tests of behavior because they are able to compensate for striatal deficits by using other brain regions such as the hippocampus to solve standard tasks.

The team then decided to give the mice a completely different type of test that relies on the striatum. Because the striatum is strongly activated by drugs of abuse, which elevate dopamine and drive motor habits, Crittenden and collaborator Morgane Thomsen (now at the University of Copenhagen) looked to see whether the CDGI knockout mice respond normally to amphetamine and cocaine.

Psychomotor stimulants like cocaine and amphetamine normally induce a mixture of hyperactive behaviors such as pacing and focused repetitive behaviors like skin-picking (also called stereotypy or punding in humans). The researchers found however, that the drug-induced behaviors in the CDGI knockout mice were less varied than the normal mice and consisted of abnormally prolonged stereotypy, as though the mice were unable to switch between behaviors. The researchers were able to map the abnormal behavior to CDGI function in the striatum by showing that the same vulnerability to drug-induced stereotypy was observed in mice that were engineered to delete CDGI in the striatum after birth (“conditional knockouts”), but to otherwise have normal CDGI throughout the body.

Controlling cravings

In addition to exhibiting prolonged, repetitive behaviors, the CDGI knockout mice had a vulnerability to self-administer drugs. Although previous research had shown that treatments that activate the M1 acetylcholine receptor can block cocaine self-administration, the team found that this therapy was ineffective in CDGI knockout mice. Knockouts continued to self-administer cocaine (suggesting increased craving for the drug) at the same rate before and after M1 receptor activation treatment, even though the treatment succeeded with their sibling control mice. The researchers concluded that CDGI is critically important for controlling repetitive behaviors and the ability to stop self-administration of addictive stimulants.

mouse brain images
Brain sections from control mice (left) and mice engineered for deletion of the CDGI gene after birth. The expression of CDGI in the striatum (arrows) grows stronger as mice grow from pups to adulthood in control mice, but is gradually lost in the CDGI engineered mice (“conditional knockouts”). Image courtesy of the researchers

To better understand how CDGI is linked to the M1 receptor at the cellular level, the team turned to slice physiologists, scientists who record the electrical activity of neurons in brain slices. Their recordings showed that striatal neurons from CDGI knockouts fail to undergo the normal, expected electrophysiological changes after receiving treatments that target the M1 receptor. In particular, the neurons of the striatum that function broadly to stop ongoing behaviors, did not integrate cellular signals properly and failed to undergo “long-term potentiation,” a type of neuronal plasticity thought to underlie learning.

The new findings suggest that excessive repetitive movements are controlled by M1 receptor signaling through CDGI in indirect pathway neurons of the striatum, a neuronal subtype that degenerates in Huntington’s disease and is affected by dopamine loss and l-DOPA replacement therapy in Parkinson’s disease.

“The M1 acetylcholine receptor is a target for therapeutic drug development in treating cognitive and behavioral problems in multiple disorders, but progress has been severely hampered by off-target side-effects related to the wide-spread expression of the M1 receptor,” Graybiel explains. “Our findings suggest that CDGI offers the possibility for forebrain-specific targeting of M1 receptor signaling cascades that are of interest for blocking pathologically repetitive and unwanted behaviors that are common to numerous brain disorders including Huntington’s disease, drug addiction, autism, and schizophrenia as well as drug-induced dyskinesias. We hope that this work can help therapeutic development for these major health problems.”

This work was funded by the James W. (1963) and Patricia T. Poitras Fund, the William N. & Bernice E. Bumpus Foundation, the Saks Kavanaugh Foundation, the Simons Foundation, and the National Institute of Health.

Some brain disorders exhibit similar circuit malfunctions

Many neurodevelopmental disorders share similar symptoms, such as learning disabilities or attention deficits. A new study from MIT has uncovered a common neural mechanism for a type of cognitive impairment seen in some people with autism and schizophrenia, even though the genetic variations that produce the impairments are different for each condition.

In a study of mice, the researchers found that certain genes that are mutated or missing in some people with those disorders cause similar dysfunctions in a neural circuit in the thalamus. If scientists could develop drugs that target this circuit, they could be used to treat people who have different disorders with common behavioral symptoms, the researchers say.

“This study reveals a new circuit mechanism for cognitive impairment and points to a future direction for developing new therapeutics, by dividing patients into specific groups not by their behavioral profile, but by the underlying neurobiological mechanisms,” says Guoping Feng, the James W. and Patricia T. Poitras Professor in Brain and Cognitive Sciences at MIT, a member of the Broad Institute of Harvard and MIT, the associate director of the McGovern Institute for Brain Research at MIT, and the senior author of the new study.

Dheeraj Roy, a Warren Alpert Distinguished Scholar and a McGovern Fellow at the Broad Institute, and Ying Zhang, a postdoc at the McGovern Institute, are the lead authors of the paper, which appears today in Neuron.

Thalamic connections

The thalamus plays a key role in cognitive tasks such as memory formation and learning. Previous studies have shown that many of the gene variants linked to brain disorders such as autism and schizophrenia are highly expressed in the thalamus, suggesting that it may play a role in those disorders.

One such gene is called Ptchd1, which Feng has studied extensively. In boys, loss of this gene, which is carried on the X chromosome, can lead to attention deficits, hyperactivity, aggression, intellectual disability, and autism spectrum disorders.

In a study published in 2016, Feng and his colleagues showed that Ptchd1 exerts many of its effects in a part of the thalamus called the thalamic reticular nucleus (TRN). When the gene is knocked out in the TRN of mice, the mice show attention deficits and hyperactivity. However, that study did not find any role for the TRN in the learning disabilities also seen in people with mutations in Ptchd1.

In the new study, the researchers decided to look elsewhere in the thalamus to try to figure out how Ptchd1 loss might affect learning and memory. Another area they identified that highly expresses Ptchd1 is called the anterodorsal (AD) thalamus, a tiny region that is involved in spatial learning and communicates closely with the hippocampus.

Using novel techniques that allowed them to trace the connections between the AD thalamus and another brain region called the retrosplenial cortex (RSC), the researchers determined a key function of this circuit. They found that in mice, the AD-to-RSC circuit is essential for encoding fearful memories of a chamber in which they received a mild foot shock. It is also necessary for working memory, such as creating mental maps of physical spaces to help in decision-making.

The researchers found that a nearby part of the thalamus called the anteroventral (AV) thalamus also plays a role in this memory formation process: AV-to-RSC communication regulates the specificity of the encoded memory, which helps us distinguish this memory from others of similar nature.

“These experiments showed that two neighboring subdivisions in the thalamus contribute differentially to memory formation, which is not what we expected,” Roy says.

Circuit malfunction

Once the researchers discovered the roles of the AV and AD thalamic regions in memory formation, they began to investigate how this circuit is affected by loss of Ptchd1. When they knocked down expression of Ptchd1 in neurons of the AD thalamus, they found a striking deficit in memory encoding, for both fearful memories and working memory.

The researchers then did the same experiments with a series of four other genes — one that is linked with autism and three linked with schizophrenia. In all of these mice, they found that knocking down gene expression produced the same memory impairments. They also found that each of these knockdowns produced hyperexcitability in neurons of the AD thalamus.

These results are consistent with existing theories that learning occurs through the strengthening of synapses that occurs as a memory is formed, the researchers say.

“The dominant theory in the field is that when an animal is learning, these neurons have to fire more, and that increase correlates with how well you learn,” Zhang says. “Our simple idea was if a neuron fires too high at baseline, you may lack a learning-induced increase.”

The researchers demonstrated that each of the genes they studied affects different ion channels that influence neurons’ firing rates. The overall effect of each mutation is an increase in neuron excitability, which leads to the same circuit-level dysfunction and behavioral symptoms.

The researchers also showed that they could restore normal cognitive function in mice with these genetic mutations by artificially turning down hyperactivity in neurons of the AD thalamus. The approach they used, chemogenetics, is not yet approved for use in humans. However, it may be possible to target this circuit in other ways, the researchers say.

The findings lend support to the idea that grouping diseases by the circuit malfunctions that underlie them may help to identify potential drug targets that could help many patients, Feng says.

“There are so many genetic factors and environmental factors that can contribute to a particular disease, but in the end, it has to cause some type of neuronal change that affects a circuit or a few circuits involved in this behavior,” he says. “From a therapeutic point of view, in such cases you may not want to go after individual molecules because they may be unique to a very small percentage of patients, but at a higher level, at the cellular or circuit level, patients may have more commonalities.”

The research was funded by the Stanley Center at the Broad Institute, the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, the James and Patricia Poitras Center for Psychiatric Disorders Research at MIT, and the National Institutes of Health BRAIN Initiative.

New technique corrects disease-causing mutations

Gene editing, or purposefully changing a gene’s DNA sequence, is a powerful tool for studying how mutations cause disease, and for making changes in an individual’s DNA for therapeutic purposes. A novel method of gene editing that can be used for both purposes has now been developed by a team led by Guoping Feng, the James W. (1963) and Patricia T. Poitras Professor in Brain and Cognitive Sciences at MIT.

“This technical advance can accelerate the production of disease models in animals and, critically, opens up a brand-new methodology for correcting disease-causing mutations,” says Feng, who is also a member of the Broad Institute of Harvard and MIT and the associate director of the McGovern Institute for Brain Research at MIT. The new findings publish online May 26 and in print June 10 in the journal Cell.

Genetic models of disease

A major goal of the Feng lab is to precisely define what goes wrong in neurodevelopmental and neuropsychiatric disorders by engineering animal models that carry the gene mutations that cause these disorders in humans. New models can be generated by injecting embryos with gene editing tools, along with a piece of DNA carrying the desired mutation.

In one such method, the gene editing tool CRISPR is programmed to cut a targeted gene, thereby activating natural DNA mechanisms that “repair” the broken gene with the injected template DNA. The engineered cells are then used to generate offspring capable of passing the genetic change on to further generations, creating a stable genetic line in which the disease, and therapies, are tested.

Although CRISPR has accelerated the process of generating such disease models, the process can still take months or years. Reasons for the inefficiency are that many treated cells do not undergo the desired DNA sequence change at all, and the change only occurs on one of the two gene copies (for most genes, each cell contains two versions, one from the father and one from the mother).

In an effort to increase the efficiency of the gene editing process, the Feng lab team initially hypothesized that adding a DNA repair protein called RAD51 to a standard mixture of CRISPR gene editing tools would increase the chances that a cell (in this case a fertilized mouse egg, or one-cell embryo) would undergo the desired genetic change.

As a test case, they measured the rate at which they were able to insert (“knock-in”) a mutation in the gene Chd2 that is associated with autism.  The overall proportion of embryos that were correctly edited remained unchanged, but to their surprise, a significantly higher percentage carried the desired gene edit on both chromosomes. Tests with a different gene yielded the same unexpected outcome.

“Editing of both chromosomes simultaneously is normally very uncommon,” explains postdoctoral fellow Jonathan Wilde.  “The high rate of editing seen with RAD51 was really striking and what started as a simple attempt to make mutant Chd2 mice quickly turned into a much bigger project focused on RAD51 and its applications in genome editing,” said Wilde, who co-authored the Cell paper with research scientist Tomomi Aida.

A molecular copy machine

The Feng lab team next set out to understand the mechanism by which RAD51 enhances gene editing. They hypothesized that RAD51 engages a process called interhomolog repair (IHR), whereby a DNA break on one chromosome is repaired using the second copy of the chromosome (from the other parent) as the template.

To test this, they injected mouse embryos with RAD51 and CRISPR but left out the template DNA. They programmed CRISPR to cut only the gene sequence on one of the chromosomes, and then tested whether it was repaired to match the sequence on the uncut chromosome. For this experiment, they had to use mice in which the sequences on the maternal and paternal chromosomes were different.

They found that control embryos injected with CRISPR alone rarely showed IHR repair. However, addition of RAD51 significantly increased the number of embryos in which the CRISPR-targeted gene was edited to match the uncut chromosome.

“Previous studies of IHR found that it is incredibly inefficient in most cells,” says Wilde. “Our finding that it occurs much more readily in embryonic cells and can be enhanced by RAD51 suggest that a deeper understanding of what makes the embryo permissive to this type of DNA repair could help us design safer and more efficient gene therapies.”

A new way to correct disease-causing mutations          

Standard gene therapy strategies that rely on injecting a corrective piece of DNA to serve as a template for repairing the mutation engage a process called homology-directed repair (HDR).

“HDR-based strategies still suffer from low efficiency and carry the risk of unwanted integration of donor DNA throughout the genome,” explains Feng. “IHR has the potential to overcome these problems because it relies upon natural cellular pathways and the patient’s own normal chromosome for correction of the deleterious mutation.”

Feng’s team went on to identify additional DNA repair-associated proteins that can stimulate IHR, including several that not only promote high levels of IHR, but also repress errors in the DNA repair process. Additional experiments that allowed the team to examine the genomic features of IHR events gave deeper insight into the mechanism of IHR and suggested ways that the technique can be used to make gene therapies safer.

“While there is still a great deal to learn about this new application of IHR, our findings are the foundation for a new gene therapy approach that could help solve some of the big problems with current approaches,” says Aida.

This study was supported by the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, the Poitras Center for Psychiatric Disorders Research at MIT, NIH/NIMH Conte Center Grant (P50 MH094271) and NIH Office of the Director (U24 OD026638).

Individual neurons responsible for complex social reasoning in humans identified

This story is adapted from a January 27, 2021 press release from Massachusetts General Hospital.

The ability to understand others’ hidden thoughts and beliefs is an essential component of human social behavior. Now, neuroscientists have for the first time identified specific neurons critical for social reasoning, a cognitive process that requires individuals to acknowledge and predict others’ hidden beliefs and thoughts.

The findings, published in Nature, open new avenues of study into disorders that affect social behavior, according to the authors.

In the study, a team of Harvard Medical School investigators based at Massachusetts General Hospital and colleagues from MIT took a rare look at how individual neurons represent the beliefs of others. They did so by recording neuron activity in patients undergoing neurosurgery to alleviate symptoms of motor disorders such as Parkinson’s disease.

Theory of mind

The researcher team, which included McGovern scientists Ev Fedorenko and Rebecca Saxe, focused on a complex social cognitive process called “theory of mind.” To illustrate this, let’s say a friend appears to be sad on her birthday. One may infer she is sad because she didn’t get a present or she is upset at growing older.

“When we interact, we must be able to form predictions about another person’s unstated intentions and thoughts,” said senior author Ziv Williams, HMS associate professor of neurosurgery at Mass General. “This ability requires us to paint a mental picture of someone’s beliefs, which involves acknowledging that those beliefs may be different from our own and assessing whether they are true or false.”

This social reasoning process develops during early childhood and is fundamental to successful social behavior. Individuals with autism, schizophrenia, bipolar affective disorder, and traumatic brain injuries are believed to have a deficit of theory-of-mind ability.

For the study, 15 patients agreed to perform brief behavioral tasks before undergoing neurosurgery for placement of deep-brain stimulation for motor disorders. Microelectrodes inserted into the dorsomedial prefrontal cortex recorded the behavior of individual neurons as patients listened to short narratives and answered questions about them.

For example, participants were presented with the following scenario to evaluate how they considered another’s belief of reality: “You and Tom see a jar on the table. After Tom leaves, you move the jar to a cabinet. Where does Tom believe the jar to be?”

Social computation

The participants had to make inferences about another’s beliefs after hearing each story. The experiment did not change the planned surgical approach or alter clinical care.

“Our study provides evidence to support theory of mind by individual neurons,” said study first author Mohsen Jamali, HMS instructor in neurosurgery at Mass General. “Until now, it wasn’t clear whether or how neurons were able to perform these social cognitive computations.”

The investigators found that some neurons are specialized and respond only when assessing another’s belief as false, for example. Other neurons encode information to distinguish one person’s beliefs from another’s. Still other neurons create a representation of a specific item, such as a cup or food item, mentioned in the story. Some neurons may multitask and aren’t dedicated solely to social reasoning.

“Each neuron is encoding different bits of information,” Jamali said. “By combining the computations of all the neurons, you get a very detailed representation of the contents of another’s beliefs and an accurate prediction of whether they are true or false.”

Now that scientists understand the basic cellular mechanism that underlies human theory of mind, they have an operational framework to begin investigating disorders in which social behavior is affected, according to Williams.

“Understanding social reasoning is also important to many different fields, such as child development, economics, and sociology, and could help in the development of more effective treatments for conditions such as autism spectrum disorder,” Williams said.

Previous research on the cognitive processes that underlie theory of mind has involved functional MRI studies, where scientists watch which parts of the brain are active as volunteers perform cognitive tasks.

But the imaging studies capture the activity of many thousands of neurons all at once. In contrast, Williams and colleagues recorded the computations of individual neurons. This provided a detailed picture of how neurons encode social information.

“Individual neurons, even within a small area of the brain, are doing very different things, not all of which are involved in social reasoning,” Williams said. “Without delving into the computations of single cells, it’s very hard to build an understanding of the complex cognitive processes underlying human social behavior and how they go awry in mental disorders.”

Adapted from a Mass General news release.

A large-scale tool to investigate the function of autism spectrum disorder genes

Scientists at Harvard University, the Broad Institute of MIT and Harvard, and MIT have developed a technology to investigate the function of many different genes in many different cell types at once, in a living organism. They applied the large-scale method to study dozens of genes that are associated with autism spectrum disorder, identifying how specific cell types in the developing mouse brain are impacted by mutations.

The “Perturb-Seq” method, published in the journal Science, is an efficient way to identify potential biological mechanisms underlying autism spectrum disorder, which is an important first step toward developing treatments for the complex disease. The method is also broadly applicable to other organs, enabling scientists to better understand a wide range of disease and normal processes.

“For many years, genetic studies have identified a multitude of risk genes that are associated with the development of autism spectrum disorder. The challenge in the field has been to make the connection between knowing what the genes are, to understanding how the genes actually affect cells and ultimately behavior,” said co-senior author Paola Arlotta, the Golub Family Professor of Stem Cell and Regenerative Biology at Harvard. “We applied the Perturb-Seq technology to an intact developing organism for the first time, showing the potential of measuring gene function at scale to better understand a complex disorder.”

The study was also led by co-senior authors Aviv Regev, who was a core member of the Broad Institute during the study and is currently Executive Vice President of Genentech Research and Early Development, and Feng Zhang, a core member of the Broad Institute and an investigator at MIT’s McGovern Institute.

To investigate gene function at a large scale, the researchers combined two powerful genomic technologies. They used CRISPR-Cas9 genome editing to make precise changes, or perturbations, in 35 different genes linked to autism spectrum disorder risk. Then, they analyzed changes in the developing mouse brain using single-cell RNA sequencing, which allowed them to see how gene expression changed in over 40,000 individual cells.

By looking at the level of individual cells, the researchers could compare how the risk genes affected different cell types in the cortex — the part of the brain responsible for complex functions including cognition and sensation. They analyzed networks of risk genes together to find common effects.

“We found that both neurons and glia — the non-neuronal cells in the brain — are directly affected by different sets of these risk genes,” said Xin Jin, lead author of the study and a Junior Fellow of the Harvard Society of Fellows. “Genes and molecules don’t generate cognition per se — they need to impact specific cell types in the brain to do so. We are interested in understanding how these different cell types can contribute to the disorder.”

To get a sense of the model’s potential relevance to the disorder in humans, the researchers compared their results to data from post-mortem human brains. In general, they found that in the post-mortem human brains with autism spectrum disorder, some of the key genes with altered expression were also affected in the Perturb-seq data.

“We now have a really rich dataset that allows us to draw insights, and we’re still learning a lot about it every day,” Jin said. “As we move forward with studying disease mechanisms in more depth, we can focus on the cell types that may be really important.”

“The field has been limited by the sheer time and effort that it takes to make one model at a time to test the function of single genes. Now, we have shown the potential of studying gene function in a developing organism in a scalable way, which is an exciting first step to understanding the mechanisms that lead to autism spectrum disorder and other complex psychiatric conditions, and to eventually develop treatments for these devastating conditions,” said Arlotta, who is also an institute member of the Broad Institute and part of the Broad’s Stanley Center for Psychiatric Research. “Our work also paves the way for Perturb-Seq to be applied to organs beyond the brain, to enable scientists to better understand the development or function of different tissue types, as well as pathological conditions.”

“Through genome sequencing efforts, a very large number of genes have been identified that, when mutated, are associated with human diseases. Traditionally, understanding the role of these genes would involve in-depth studies of each gene individually. By developing Perturb-seq for in vivo applications, we can start to screen all of these genes in animal models in a much more efficient manner, enabling us to understand mechanistically how mutations in these genes can lead to disease,” said Zhang, who is also the James and Patricia Poitras Professor of Neuroscience at MIT and a professor of brain and cognitive sciences and biological engineering at MIT.

This study was funded by the Stanley Center for Psychiatric Research at the Broad Institute, the National Institutes of Health, the Brain and Behavior Research Foundation’s NARSAD Young Investigator Grant, Harvard University’s William F. Milton Fund, the Klarman Cell Observatory, the Howard Hughes Medical Institute, a Center for Cell Circuits grant from the National Human Genome Research Institute’s Centers of Excellence in Genomic Science, the New York Stem Cell Foundation, the Mathers Foundation, the Poitras Center for Psychiatric Disorders Research at MIT, the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, and J. and P. Poitras.