Symposium highlights scale of mental health crisis and novel methods of diagnosis and treatment

Digital technologies, such as smartphones and machine learning, have revolutionized education. At the McGovern Institute for Brain Research’s 2024 Spring Symposium, “Transformational Strategies in Mental Health,” experts from across the sciences — including psychiatry, psychology, neuroscience, computer science, and others — agreed that these technologies could also play a significant role in advancing the diagnosis and treatment of mental health disorders and neurological conditions.

Co-hosted by the McGovern Institute, MIT Open Learning, McClean Hospital, the Poitras Center for Psychiatric Disorders Research at MIT, and the Wellcome Trust, the symposium raised the alarm about the rise in mental health challenges and showcased the potential for novel diagnostic and treatment methods.

“We have to do something together as a community of scientists and partners of all kinds to make a difference.” – John Gabrieli

John Gabrieli, the Grover Hermann Professor of Health Sciences and Technology at MIT, kicked off the symposium with a call for an effort on par with the Manhattan Project, which in the 1940s saw leading scientists collaborate to do what seemed impossible. While the challenge of mental health is quite different, Gabrieli stressed, the complexity and urgency of the issue are similar. In his later talk, “How can science serve psychiatry to enhance mental health?,” he noted a 35 percent rise in teen suicide deaths between 1999 and 2000 and, between 2007 and 2015, a 100 percent increase in emergency room visits for youths ages 5 to 18 who experienced a suicide attempt or suicidal ideation.

“We have no moral ambiguity, but all of us speaking today are having this meeting in part because we feel this urgency,” said Gabrieli, who is also a professor of brain and cognitive sciences, the director of the Integrated Learning Initiative (MITili) at MIT Open Learning, and a member of the McGovern Institute. “We have to do something together as a community of scientists and partners of all kinds to make a difference.”

An urgent problem

In 2021, U.S. Surgeon General Vivek Murthy issued an advisory on the increase in mental health challenges in youth; in 2023, he issued another, warning of the effects of social media on youth mental health. At the symposium, Susan Whitfield-Gabrieli, a research affiliate at the McGovern Institute and a professor of psychology and director of the Biomedical Imaging Center at Northeastern University, cited these recent advisories, saying they underscore the need to “innovate new methods of intervention.”

Other symposium speakers also highlighted evidence of growing mental health challenges for youth and adolescents. Christian Webb, associate professor of psychology at Harvard Medical School, stated that by the end of adolescence, 15-20 percent of teens will have experienced at least one episode of clinical depression, with girls facing the highest risk. Most teens who experience depression receive no treatment, he added.

Adults who experience mental health challenges need new interventions, too. John Krystal, the Robert L. McNeil Jr. Professor of Translational Research and chair of the Department of Psychiatry at Yale University School of Medicine, pointed to the limited efficacy of antidepressants, which typically take about two months to have an effect on the patient. Patients with treatment-resistant depression face a 75 percent likelihood of relapse within a year of starting antidepressants. Treatments for other mental health disorders, including bipolar and psychotic disorders, have serious side effects that can deter patients from adherence, said Virginie-Anne Chouinard, director of research at McLean OnTrackTM, a program for first episode psychosis at McLean Hospital.

New treatments, new technologies

Emerging technologies, including smartphone technology and artificial intelligence, are key to the interventions that symposium speakers shared.

In a talk on AI and the brain, Dina Katabi, the Thuan and Nicole Pham Professor of Electrical Engineering and Computer Science at MIT, discussed novel ways to detect Parkinson’s and Alzheimer’s, among other diseases. Early-stage research involved developing devices that can analyze how movement within a space impacts the surrounding electromagnetic field, as well as how wireless signals can detect breathing and sleep stages.

“I realize this may sound like la-la land,” Katabi said. “But it’s not! This device is used today by real patients, enabled by a revolution in neural networks and AI.”

Parkinson’s disease often cannot be diagnosed until significant impairment has already occurred. In a set of studies, Katabi’s team collected data on nocturnal breathing and trained a custom neural network to detect occurrences of Parkinson’s. They found the network was over 90 percent accurate in its detection. Next, the team used AI to analyze two sets of breathing data collected from patients at a six-year interval. Could their custom neural network identify patients who did not have a Parkinson’s diagnosis on the first visit, but subsequently received one? The answer was largely yes: Machine learning identified 75 percent of patients who would go on to receive a diagnosis.

Detecting high-risk patients at an early stage could make a substantial difference for intervention and treatment. Similarly, research by Jordan Smoller, professor of psychiatry at Harvard Medical School and director of the Center for Precision Psychiatry at Massachusetts General Hospital, demonstrated that AI-aided suicide risk prediction model could detect 45 percent of suicide attempts or deaths with 90 percent specificity, about two to three years in advance.

Other presentations, including a series of lightning talks, shared new and emerging treatments, such as the use of ketamine to treat depression; the use of smartphones, including daily text surveys and mindfulness apps, in treating depression in adolescents; metabolic interventions for psychotic disorders; the use of machine learning to detect impairment from THC intoxication; and family-focused treatment, rather than individual therapy, for youth depression.

Advancing understanding

The frequency and severity of adverse mental health events for children, adolescents, and adults demonstrate the necessity of funding for mental health research — and the open sharing of these findings.

Niall Boyce, head of mental health field building at the Wellcome Trust — a global charitable foundation dedicated to using science to solve urgent health challenges — outlined the foundation’s funding philosophy of supporting research that is “collaborative, coherent, and focused” and centers on “What is most important to those most affected?” Wellcome research managers Anum Farid and Tayla McCloud stressed the importance of projects that involve people with lived experience of mental health challenges and “blue sky thinking” that takes risks and can advance understanding in innovative ways. Wellcome requires that all published research resulting from its funding be open and accessible in order to maximize their benefits.

Whether through therapeutic models, pharmaceutical treatments, or machine learning, symposium speakers agreed that transformative approaches to mental health call for collaboration and innovation.

“Understanding mental health requires us to understand the unbelievable diversity of humans,” Gabrieli said. “We have to use all the tools we have now to develop new treatments that will work for people for whom our conventional treatments don’t.”

Nancy Kanwisher Shares 2024 Kavli Prize in Neuroscience

The Norwegian Academy of Science and Letters today announced the 2024 Kavli Prize Laureates in the fields of astrophysics, nanoscience, and neuroscience. The 2024 Kavli Prize in Neuroscience honors Nancy Kanwisher, the Walter A. Rosenblith Professor of Cognitive Neuroscience at MIT and an investigator at the McGovern Institute, along with UC Berkeley neurobiologist Doris Tsao, and Rockefeller University neuroscientist Winrich Freiwald for their discovery of a highly localized and specialized system for representation of faces in human and non-human primate neocortex. The neuroscience laureates will share $1 million USD.

“Kanwisher, Freiwald, and Tsao together discovered a localized and specialized neocortical system for face recognition,” says Kristine Walhovd, Chair of the Kavli Neuroscience Committee. “Their outstanding research will ultimately further our understanding of recognition not only of faces, but objects and scenes.”

Overcoming failure

As a graduate student at MIT in the early days of functional brain imaging, Kanwisher was fascinated by the potential of the emerging technology to answer a suite of questions about the human mind. But a lack of brain imaging resources and a series of failed experiments led Kanwisher consider leaving the field for good. She credits her advisor, MIT Professor of Psychology Molly Potter, for supporting her through this challenging time and for teaching her how to make powerful inferences about the inner workings of the mind from behavioral data alone.

After receiving her PhD from MIT, Kanwisher spent a year studying nuclear strategy with a MacArthur Foundation Fellowship in Peace and International Security, but eventually returned to science by accepting a faculty position at Harvard University where she could use the latest brain imaging technology to pursue the scientific questions that had always fascinated her.

Zeroing in on faces

Recognizing faces is important for social interaction in many animals. Previous work in human psychology and animal research had suggested the existence of a functionally specialized system for face recognition, but this system had not clearly been identified with brain imaging technology. It is here that Kanwisher saw her opportunity.

Using a new method at the time, called functional magnetic resonance imaging or fMRI, Kanwisher’s team scanned people while they looked at faces and while they looked at objects, and searched for brain regions that responded more to one than the other. They found a small patch of neocortex, now called the fusiform face area (FFA), that is dedicated specifically to the task of face recognition. She found individual differences in the location of this area and devised an analysis technique to effectively localize specialized functional regions in the brain. This technique is now widely used and applied to domains beyond the face recognition system. Notably, Kanwisher’s first FFA paper was co-authored with Josh McDermott, who was an undergrad at Harvard University at the time, and is now an associate investigator at the McGovern Institute and holds a faculty position alongside Kanwisher in MIT’s Department of Brain and Cognitive Sciences.

A group of five scientists standing and smiling in front of a whiteboard.
The Kanwisher lab at Harvard University circa 1996. From left to right: Nancy Kanwisher, Josh McDermott (then an undergrad), Marvin Chun (postdoc), Ewa Wojciulik (postdoc), and Jody Culham (grad student). Photo: Nancy Kanwisher

From humans to monkeys

Inspired by Kanwisher´s findings, Winrich Freiwald and Doris Tsao together used fMRI to localize similar face patches in macaque monkeys. They mapped out six distinct brain regions, known as the face patch system, including these regions’ functional specialization and how they are connected. By recording the activity of individual brain cells, they revealed how cells in some face patches specialize in faces with particular views.

Tsao proceeded to identify how the face patches work together to identify a face, through a specific code that enables single cells to identify faces by assembling information of facial features. For example, some cells respond to the presence of hair, others to the distance between the eyes. Freiwald uncovered that a separate brain region, called the temporal pole, accelerates our recognition of familiar faces, and that some cells are selectively responsive to familiar faces.

“It was a special thrill for me when Doris and Winrich found face patches in monkeys using fMRI,” says Kanwisher, whose lab at MIT’s McGovern Institute has gone on to uncover many other regions of the human brain that engage in specific aspects of perception and cognition. “They are scientific heroes to me, and it is a thrill to receive the Kavli Prize in neuroscience jointly with them.”

“Nancy and her students have identified neocortical subregions that differentially engage in the perception of faces, places, music and even what others think,” says McGovern Institute Director Robert Desimone. “We are delighted that her groundbreaking work into the functional organization of the human brain is being honored this year with the Kavli Prize.”

Together, the laureates, with their work on neocortical specialization for face recognition, have provided basic principles of neural organization which will further our understanding of how we perceive the world around us.

About the Kavli Prize

The Kavli Prize is a partnership among The Norwegian Academy of Science and Letters, The Norwegian Ministry of Education and Research, and The Kavli Foundation (USA). The Kavli Prize honors scientists for breakthroughs in astrophysics, nanoscience and neuroscience that transform our understanding of the big, the small and the complex. Three one-million-dollar prizes are awarded every other year in each of the three fields. The Norwegian Academy of Science and Letters selects the laureates based on recommendations from three independent prize committees whose members are nominated by The Chinese Academy of Sciences, The French Academy of Sciences, The Max Planck Society of Germany, The U.S. National Academy of Sciences, and The Royal Society, UK.

Honoring a visionary

Today marks the 10th anniversary of the passing of Pat McGovern, an extraordinary visionary and philanthropist whose legacy continues to inspire and impact the world. As the founder of International Data Group (IDG)—a premier information technology organization—McGovern was not just a pioneering figure in the technology media world, but also a passionate advocate for using technology for the greater good.

Under McGovern’s leadership, IDG became a global powerhouse, launching iconic publications such as Computerworld, Macworld, and PCWorld. His foresight also led to the creation of IDG Ventures, a network of venture funds around the world, including the notable IDG Capital in Beijing.

Beyond his remarkable business acumen, McGovern, with his wife, Lore, co-founded the McGovern Institute for Brain Research at MIT in 2000. This institute has been at the forefront of neuroscience research, contributing to groundbreaking advancements in perception, attention, memory, and artificial intelligence (AI), as well as discoveries with direct translational impact, such as CRISPR technology. CRISPR discoveries made at the McGovern Institute are now licensed for the first clinical application of genome editing in sickle cell disease.

Pat McGovern’s commitment to bettering humanity is further evidenced by the Patrick J. McGovern Foundation, which works in partnership with public, private, and social institutions to drive progress on our most pressing challenges through the use of artificial intelligence, data science, and key emerging technologies.

Remembering Pat McGovern

On this solemn anniversary, we reflect on Pat McGovern’s enduring influence through the words of those who knew him best.

Lore Harp McGovern
Co-founder and board member of the McGovern Institute for Brain Research

“Technology was Pat’s medium, the platform on which he built his amazing company 60 years ago. But it was people who truly motivated Pat, and he empowered and encouraged them to reach for the stars. He lived by the motto, ‘let’s try it,’ and believed that nothing was out bounds. His goal was to help create a more just and peaceful world, and establishing the McGovern Institute was our way to give back meaningfully to this world. I know he would be so proud of what has been achieved and what is yet to come.”

Robert Desimone
Director of the McGovern Institute for Brain Research

“Pat McGovern had a vision for an international community of scientists and students drawn together to collaborate on understanding the brain.  This vision has been realized in the McGovern Institute, and we are now seeing the profound advances in our understanding of the brain and even clinical applications that Pat predicted would follow.”

Hugo Shong
Chairman of IDG Capital

“Pat’s impact on technology, science and research is immeasurable. A man of tremendous vision, he grew IDG out of Massachusetts and made it into one of the world’s most recognized brands in its space, forging partnerships and winning friends wherever he went. He applied that very same vision and energy to the McGovern Institute and the Patrick J. McGovern Foundation, in support of their impressive and necessary causes. I know he would be extremely proud of what both organizations have achieved thus far, and particularly how their work has broken technological frontiers and bettered the lives of millions.”

Vilas Dhar
President of the Patrick J. McGovern Foundation

“Patrick J. McGovern was more than a tech mogul; he was a visionary who believed in the power of information to empower people and improve societies. His work has had a profound effect on public policy and education, laying the groundwork for a more informed and connected world and guiding our work to ensure that artificial intelligence is used to sustain a human-centered world that creates economic and social opportunity for all.  On a personal level, Pat’s leadership was characterized by a genuine care for his employees and a belief in their potential. He created a culture of curiosity, encouraging humanity to explore, innovate, and dream big. His spirit lives on in every philanthropic activity we undertake.”

Genevieve Juillard
CEO of IDG 

The legacy of Pat McGovern is felt not just in Boston, but around the world—by the thousands of IDG customers and by people like me who have the privilege to work at IDG, 60 years after he founded it. His innovative spirit and unwavering commitment to excellence continue to inspire and guide us.”

Sudhir Sethi
Founder and Chairman of Chiratae Ventures (formally IDG Ventures)

“Pat McGovern was a visionary who foresaw the potential of technology in India and nurtured the ecosystem as an active participant. Pat enabled a launchpad for Chiratae Ventures, empowering our journey to become the leading home-grown venture capital fund in India today. Pat is a role model to entrepreneurs worldwide, and we honor his legacy with our annual ‘Chiratae Ventures Patrick J. McGovern Awards’ that celebrate courage and the spirit of entrepreneurship.”

Marc Benioff
Founder and CEO of Salesforce
wrote in the book “Future Forward that “Pat McGovern was a gift to us all, a trailblazing visionary who showed an entire generation of entrepreneurs what it means to be a principle-based leader and how to lead with higher values.”

Pat McGovern’s memory lives on not just in the institutions and innovations he fostered, but in the countless lives he touched and transformed. Today, we celebrate a man who saw the future and helped us all move towards it with hope and determination.

Simons Center’s collaborative approach propels autism research, at MIT and beyond

The secret to the success of MIT’s Simons Center for the Social Brain is in the name. With a founding philosophy of “collaboration and community” that has supported scores of scientists across more than a dozen Boston-area research institutions, the SCSB advances research by being inherently social.

SCSB’s mission is “to understand the neural mechanisms underlying social cognition and behavior and to translate this knowledge into better diagnosis and treatment of autism spectrum disorders.” When Director Mriganka Sur founded the center in 2012 in partnership with the Simons Foundation Autism Research Initiative (SFARI) of Jim and Marilyn Simons, he envisioned a different way to achieve urgently needed research progress than the traditional approach of funding isolated projects in individual labs. Sur wanted SCSB’s contribution to go beyond papers, though it has generated about 350 and counting. He sought the creation of a sustained, engaged autism research community at MIT and beyond.

“When you have a really big problem that spans so many issues  a clinical presentation, a gene, and everything in between  you have to grapple with multiple scales of inquiry,” says Sur, the Newton Professor of Neuroscience in MIT’s Department of Brain and Cognitive Sciences (BCS) and The Picower Institute for Learning and Memory. “This cannot be solved by one person or one lab. We need to span multiple labs and multiple ways of thinking. That was our vision.”

In parallel with a rich calendar of public colloquia, lunches, and special events, SCSB catalyzes multiperspective, multiscale research collaborations in two programmatic ways. Targeted projects fund multidisciplinary teams of scientists with complementary expertise to collectively tackle a pressing scientific question. Meanwhile, the center supports postdoctoral Simons Fellows with not one, but two mentors, ensuring a further cross-pollination of ideas and methods.

Complementary collaboration

In 11 years, SCSB has funded nine targeted projects. Each one, by design, involves a deep and multifaceted exploration of a major question with both fundamental importance and clinical relevance. The first project, back in 2013, for example, marshaled three labs spanning BCS, the Department of Biology, and The Whitehead Institute for Biomedical Research to advance understanding of how mutation of the Shank3 gene leads to the pathophysiology of Phelan-McDermid Syndrome by working across scales ranging from individual neural connections to whole neurons to circuits and behavior.

Other past projects have applied similarly integrated, multiscale approaches to topics ranging from how 16p11.2 gene deletion alters the development of brain circuits and cognition to the critical role of the thalamic reticular nucleus in information flow during sleep and wakefulness. Two others produced deep examinations of cognitive functions: how we go from hearing a string of words to understanding a sentence’s intended meaning, and the neural and behavioral correlates of deficits in making predictions about social and sensory stimuli. Yet another project laid the groundwork for developing a new animal model for autism research.

SFARI is especially excited by SCSB’s team science approach, says Kelsey Martin, executive vice president of autism and neuroscience at the Simons Foundation. “I’m delighted by the collaborative spirit of the SCSB,” Martin says. “It’s wonderful to see and learn about the multidisciplinary team-centered collaborations sponsored by the center.”

New projects

In the last year, SCSB has launched three new targeted projects. One team is investigating why many people with autism experience sensory overload and is testing potential interventions to help. The scientists hypothesize that patients experience a deficit in filtering out the mundane stimuli that neurotypical people predict are safe to ignore. Studies suggest the predictive filter relies on relatively low-frequency “alpha/beta” brain rhythms from deep layers of the cortex moderating the higher frequency “gamma” rhythms in superficial layers that process sensory information.

Together, the labs of Charles Nelson, professor of pediatrics at Boston Children’s Hospital (BCH), and BCS faculty members Bob Desimone, the Doris and Don Berkey Professor of Neuroscience at MIT and director of the McGovern Institute, and Earl K. Miller, the Picower Professor, are testing the hypothesis in two different animal models at MIT and in human volunteers at BCH. In the animals they’ll also try out a new real-time feedback system invented in Miller’s lab that can potentially correct the balance of these rhythms in the brain. And in an animal model engineered with a Shank3 mutation, Desimone’s lab will test a gene therapy, too.

“None of us could do all aspects of this project on our own,” says Miller, an investigator in the Picower Institute. “It could only come about because the three of us are working together, using different approaches.”

Right from the start, Desimone says, close collaboration with Nelson’s group at BCH has been essential. To ensure his and Miller’s measurements in the animals and Nelson’s measurements in the humans are as comparable as possible, they have tightly coordinated their research protocols.

“If we hadn’t had this joint grant we would have chosen a completely different, random set of parameters than Chuck, and the results therefore wouldn’t have been comparable. It would be hard to relate them,” says Desimone, who also directs MIT’s McGovern Institute for Brain Research. “This is a project that could not be accomplished by one lab operating in isolation.”

Another targeted project brings together a coalition of seven labs — six based in BCS (professors Evelina Fedorenko, Edward Gibson, Nancy Kanwisher, Roger Levy, Rebecca Saxe, and Joshua Tenenbaum) and one at Dartmouth College (Caroline Robertson) — for a synergistic study of the cognitive, neural, and computational underpinnings of conversational exchanges. The study will integrate the linguistic and non-linguistic aspects of conversational ability in neurotypical adults and children and those with autism.

Fedorenko said the project builds on advances and collaborations from the earlier language Targeted Project she led with Kanwisher.

“Many directions that we started to pursue continue to be active directions in our labs. But most importantly, it was really fun and allowed the PIs [principal investigators] to interact much more than we normally would and to explore exciting interdisciplinary questions,” Fedorenko says. “When Mriganka approached me a few years after the project’s completion asking about a possible new targeted project, I jumped at the opportunity.”

Gibson and Robertson are studying how people align their dialogue, not only in the content and form of their utterances, but using eye contact. Fedorenko and Kanwisher will employ fMRI to discover key components of a conversation network in the cortex. Saxe will examine the development of conversational ability in toddlers using novel MRI techniques. Levy and Tenenbaum will complement these efforts to improve computational models of language processing and conversation.

The newest Targeted Project posits that the immune system can be harnessed to help treat behavioral symptoms of autism. Four labs — three in BCS and one at Harvard Medical School (HMS) — will study mechanisms by which peripheral immune cells can deliver a potentially therapeutic cytokine to the brain. A study by two of the collaborators, MIT associate professor Gloria Choi and HMS associate professor Jun Huh, showed that when IL-17a reaches excitatory neurons in a region of the mouse cortex, it can calm hyperactivity in circuits associated with social and repetitive behavior symptoms. Huh, an immunologist, will examine how IL-17a can get from the periphery to the brain, while Choi will examine how it has its neurological effects. Sur and MIT associate professor Myriam Heiman will conduct studies of cell types that bridge neural circuits with brain circulatory systems.

“It is quite amazing that we have a core of scientists working on very different things coming together to tackle this one common goal,” Choi says. “I really value that.”

Multiple mentors

While SCSB Targeted Projects unify labs around research, the center’s Simons Fellowships unify labs around young researchers, providing not only funding, but a pair of mentors and free-flowing interactions between their labs. Fellows also gain opportunities to inform and inspire their fundamental research by visiting with patients with autism, Sur says.

“The SCSB postdoctoral program serves a critical role in ensuring that a diversity of outstanding scientists are exposed to autism research during their training, providing a pipeline of new talent and creativity for the field,” adds Martin, of the Simons Foundation.

Simons Fellows praise the extra opportunities afforded by additional mentoring. Postdoc Alex Major was a Simons Fellow in Miller’s lab and that of Nancy Kopell, a mathematics professor at Boston University renowned for her modeling of the brain wave phenomena that the Miller lab studies experimentally.

“The dual mentorship structure is a very useful aspect of the fellowship” Major says. “It is both a chance to network with another PI and provides experience in a different neuroscience sub-field.”

Miller says co-mentoring expands the horizons and capabilities of not only the mentees but also the mentors and their labs. “Collaboration is 21st century neuroscience,” Miller says. “Some our studies of the brain have gotten too big and comprehensive to be encapsulated in just one laboratory. Some of these big questions require multiple approaches and multiple techniques.”

Desimone, who recently co-mentored Seng Bum (Michael Yoo) along with BCS and McGovern colleague Mehrdad Jazayeri in a project studying how animals learn from observing others, agrees.

“We hear from postdocs all the time that they wish they had two mentors, just in general to get another point of view,” Desimone says. “This is a really good thing and it’s a way for faculty members to learn about what other faculty members and their postdocs are doing.”

Indeed, the Simons Center model suggests that research can be very successful when it’s collaborative and social.

Margaret Livingstone awarded the 2024 Scolnick Prize in Neuroscience

Today the McGovern Institute at MIT announces that the 2024 Edward M. Scolnick Prize in Neuroscience will be awarded to Margaret Livingstone, Takeda Professor of Neurobiology at Harvard Medical School. The Scolnick Prize is awarded annually by the McGovern Institute, for outstanding achievements in neuroscience.

“Margaret Livingstone’s driven curiosity and original experimental approaches have led to fundamental advances in our understanding of visual perception,” says Robert Desimone, director of the McGovern Institute and chair of the selection committee. “In particular, she has made major advances in resolving a long-standing debate over whether the brain domains and neurons that are specifically tuned to detect facial features are present from birth or arise from experience. Her developmental research shows that the cerebral cortex already contains topographic sensory maps at birth but that domain-specific maps, for example to recognize facial-features, require experience and sensory input to develop normally.”

“Margaret Livingstone’s driven curiosity and original experimental approaches have led to fundamental advances in our understanding of visual perception.” — Robert Desimone

Livingstone received a BS from MIT in 1972 and, under the mentorship of Edward Kravitz, a PhD in neurobiology from Harvard University in 1981. Her doctoral research in lobsters showed that the biogenic amines serotonin and octopamine control context-dependent behaviors such as offensive versus defensive postures. She followed up on this discovery as a postdoctoral fellow by researching biogenic amine signaling in learning and memory, with Prof. William Quinn at Princeton University. Using learning and memory mutants created in the fruit fly model she identified defects in dopamine-synthesizing enzymes and calcium-dependent enzymes that produce cAMP. Her results supported the then burgeoning idea that biogenic amines signal through second messengers enable behavioral plasticity.

To test whether biogenic amines also control neuronal function in mammals, Livingstone moved back to Harvard Medical School in 1983 to study the effects of sleep on visual processing with David Hubel, who was studying neuronal activity in the nonhuman primate visual cortex. Over the course of a 20-year collaboration, Livingstone and Hubel showed that the visual system is functionally and anatomically divided into parallel pathways that detect and process the distinct visual features of color, motion, and orientation.

Livingstone quickly rose through the academic ranks at Harvard to be appointed as an instructor and then assistant professor in 1983, associate professor in 1986 and full professor in 1988. With her own laboratory, Livingstone began to explore the organization of face-perception domains in the inferotemporal cortex of nonhuman primates. By combining single-cell recording and fMRI brain imaging data from the same animal, her then graduate student Doris Tsao, in collaboration with Winrich Freiwald, showed that an abundance of individual neurons within the face-recognition domain are tuned to a combination of facial features. These results helped to explain the long-standing question of how individual neurons show such exquisite selectivity to specific faces.

Three images of Mona Lisa, side by side, each with a different filter slightly obscuring the face.
Mona Lisa’s smile has been described as mysterious and fleeting because it seems to disappear when viewers look directly at it. Livingstone showed that Mona Lisa’s smile is more apparent in our peripheral vision than our central (or foveal) vision because our peripheral vision is more sensitive to low spatial frequencies, or shadows and shadings of black and white. These shadows make her lips seem to turn upward into a subtle smile. The three images above show the painting filtered to reveal very low spatial frequency features (left, with the smile more apparent) to high spatial frequency features (right, with the smile being less visible). Image: Margaret Livingstone

In researching face patches, Livingstone became fascinated with the question of whether face-perception domains are present from birth, as many scientists thought at the time. Livingstone and her postdoc Michael Arcaro carried out experiments that showed that the development of face patches requires visual exposure to faces in the early postnatal period. Moreover, they showed that entirely unnatural symbol-specific domains can form in animals that experienced intensive visual exposure to symbols early in development. Thus, experience is both necessary and sufficient for the formation of feature-specific domains in the inferotemporal cortex. Livingtone’s results support a consistent principle for the development of higher-level cortex, from a hard-wired sensory topographic map present at birth to the formation of experience-dependent domains that detect combined, stimulus-specific features.

Livingstone is also known for her scientifically based exploration of the visual arts. Her book “Vision and Art: The Biology of Seeing,” which has sold more than 40,000 copies to date, explores how both the techniques artists use and our anatomy and physiology influence our perception of art. Livingstone has presented this work to audiences around the country, from Pixar Studios, MicroSoft and IBM to The Metropolitan Museum of Art, The National Gallery and The Hirshhorn Museum.

In 2014, Livingstone was awarded the Takeda Professorship of Neurobiology at Harvard Medical School. She was awarded the Mika Salpeter Lifetime Achievement Award from the Society for Neuroscience in 2011, the Grossman Award from the Society of Neurological Surgeons in 2013 and the Roberts Prize for Best Paper in Physics in Medicine and Biology in 2013 and 2016. Livingstone was elected fellow of the American Academy of Arts and Sciences in 2018 and of the National Academy of Science in 2020. She will be awarded the Scolnick Prize in the spring of 2024.

The promise of gene therapy

Portrait of Bob Desimone wearing a suit and tie.
McGovern Institute Director Robert Desimone. Photo: Steph Stevens

As we start 2024, I hope you can join me in celebrating a historic recent advance: the FDA approval of Casgevy, a bold new treatment for devastating sickle cell disease and the world’s first approved CRISPR gene therapy.

Developed by Vertex Pharmaceuticals and CRISPR Therapeutics, we are proud to share that this pioneering therapy licenses the CRISPR discoveries of McGovern scientist and Poitras Professor of Neuroscience Feng Zhang.

It is amazing to think that Feng’s breakthrough work adapting CRISPR-Cas9 for genome editing in eukaryotic cells was published only 11 years ago today in Science.

Incredibly, CRISPR-Cas9 rapidly transitioned from proof-of-concept experiments to an approved treatment in just over a decade.

McGovern scientists are determined to maintain the momentum!

 

Incredibly, CRISPR-Cas9 rapidly transitioned from proof-of-concept experiments to an approved treatment in just over a decade.

Our labs are creating new gene therapies that are already in clinical trials or preparing to enroll patients in trials. For instance, Feng Zhang’s team has developed therapies currently in clinical trials for lymphoblastic leukemia and beta thalassemia, while another McGovern researcher, Guoping Feng, the Poitras Professor of Brain and Cognitive Sciences at MIT, has made advancements that lay the groundwork for a new gene therapy to treat a severe form of autism spectrum disorder. It is expected to enter clinical trials later this year. Moreover, McGovern fellows Omar Abudayyeh and Jonathan Gootenberg created programmable genomic tools that are now licensed for use in monogenic liver diseases and autoimmune disorders.

These exciting innovations stem from your steadfast support of our high-risk, high-reward research. Your generosity is enabling our scientists to pursue basic research in other areas with potential therapeutic applications in the future, such as mechanisms of pain, addiction, the connections between the brain and gut, the workings of memory and attention, and the bi-directional influence of artificial intelligence on brain research. All of this fundamental research is being fueled by major new advances in technology, many of them developed here.

As we enter a new year filled with anticipation following our inaugural gene therapy, I want to express my heartfelt gratitude for your invaluable support in advancing our research programs. Your role in pushing our research to new heights is valued by all faculty, students, and researchers at the McGovern Institute. We can’t wait to share our continued progress with you.

Thank you again for partnering with us to make great scientific achievements possible.

With appreciation and best wishes,

Robert Desimone, PhD
Director, McGovern Institute
Doris and Don Berkey Professor of Neuroscience, MIT

Season’s Greetings from the McGovern Institute

This year’s holiday greeting (video above) was inspired by research conducted in John Gabrieli’s lab, which found that practicing mindfulness reduced children’s stress levels and negative emotions during the pandemic. These findings contribute to a growing body of evidence that practicing mindfulness can change patterns of brain activity associated with emotions and mental health.

Coloring is one form of mindfulness, or focusing awareness on the present. Visit our postcard collection to download and color your own brain-themed postcards and may the spirit of mindfulness bring you peace in the year ahead!

Video credits:
Joseph Laney (illustration)
JR Narrows, Space Lute (sound design)
Jacob Pryor (animation)

A mindful McGovern community

Mindfulness is the practice of maintaining a state of complete awareness of one’s thoughts, emotions, or experiences on a moment-to-moment basis. McGovern researchers have shown that practicing mindfulness reduces anxiety and supports emotional resilience.

In a survey distributed to the McGovern Institute community, 57% of the 74 researchers, faculty, and staff who responded, said that they practice mindfulness as a way to reduce anxiety and stress.

Here are a few of their stories.

Fernanda De La Torre

Portrait of a smiling woman leaning back against a railing.
MIT graduate student Fernanda De La Torre. Photo: Steph Stevens

Fernanda De La Torre is a graduate student in MIT’s Department of Brain and Cognitive Sciences, where she is advised by Josh McDermott.

Originally from Mexico, De La Torre took an unconventional path to her education in the United States, where she completed her undergraduate studies in computer science and math at Kansas State University. In 2019, she came to MIT as a postbaccalaureate student in the lab of Tomaso Poggio where she began working on deep-learning theory, an area of machine learning focused on how artificial neural networks modeled on the brain can learn to recognize patterns and learn.

A recent recipient of the prestigious Paul and Daisy Soros Fellowship for New Americans, De La Torre now studies multisensory integration during speech perception using deep learning models in Josh McDermott’s lab.

What kind of mindfulness do you practice, how often, and why?

Metta meditation is the type of meditation I come back to the most. I practice 2-3 times per week. Sometimes by joining Nikki Mirghafori’s Zoom calls or listening to her and other teachers’ recordings on AudioDharma. I practice because when I observe the patterns of my thoughts, I remember the importance of compassion, including self-compassion. In my experience, I find metta meditation is a wonderful way to cultivate the two: observation and compassion. 

When and why did you start practicing mindfulness?

My first meditation practice was as a first-year post-baccalaureate student here at BCS. Gal Raz (also pictured above) carried a lot of peace and attributed it to meditation; this sparked my curiosity. I started practicing more frequently last summer, after realizing my mental health was not in a good place.

How does mindfulness benefit your research at MIT?

This is hard to answer because I think the benefits of meditation are hard to measure. I find that meditation helps me stay centered and healthy, which can indirectly help the research I do. More directly, some of my initial grad school pursuits were fueled by thoughts during meditation but I ended up feeling that a lot of these concepts are hard to explore using non-philosophical approaches. So I think meditation is mainly a practice that helps my health, my relationships with others, and my relationship with work (this last one I find most challenging and personally unresolved). 

Adam Eisen

MIT graduate student Adam Eisen.

Adam Eisen is a graduate student in MIT’s Department of Brain and Cognitive Sciences, where he is co-advised by Ila Fiete (McGovern Institute) and Earl Miller (Picower Institute).

Eisen completed his undergraduate degree in Applied Mathematics & Computer Engineering at Queen’s University in Toronto, Canada. Prior to joining MIT, Eisen built computer vision algorithms at the solar aerial inspection company Heliolytics and worked on developing machine learning tools to predict disease outcomes from genetics at The Hospital for Sick Children.

Today, in the Fiete and Miller labs, Eisen develops tools for analyzing the flow of neural activity, and applies them to understand changes in neural states (such as from consciousness to anesthetic-induced unconsciousness).

What kind of mindfulness do you practice, how often, and why?

I mostly practice simple sitting meditation centered on awareness of senses and breathing. On a good week, I meditate about 3-5 times. The reason I practice are the benefits to my general experience of living. Whenever I’m in a prolonged period of consistent meditation, I’m shocked by how much more awareness I have about thoughts, feelings and sensations that are arising in my mind throughout the day. I’m also amazed by how much easier it is to watch my mind and body react to the context around me, without slipping into the usual patterns and habits. I also find mindful benefits in doing yoga, running and playing music, but the core is really centered on meditation practice.

When and why did you start practicing mindfulness?

I’ve been interested in mindfulness and meditation since undergrad as a path to investigating the nature of mind and thought – an interest which also led me into my PhD. I started practicing meditation more seriously at the start of the pandemic to get more first hand experience with what I had been learning about. I find meditation is one of those things where knowledge and theory can support the practice, but without the experiential component it’s very hard to really start to build an understanding of the core concepts at play.

How does mindfulness benefit your research at MIT?

Mindfulness has definitely informed the kinds of things I’m interested in studying and the questions I’d like to ask – largely in relation to the nature of conscious awareness and the flow of thoughts. Outside of that, I’d like to think that mindfulness benefits my general well-being and spiritual balance, which enables me to do better research.

 

Sugandha Sharma

Woman clasping hands in a yoga pose, looking directly into the camera.
MIT graduate student Sugandha Sharma. Photo: Steph Stevens

Sugandha (Su) Sharma is a graduate student in MIT’s Department of Brain and Cognitive Sciences (BCS), where she is co-advised by Ila Fiete (McGovern Institute) and Josh Tenenbaum (BCS).

Prior to joining MIT, she studied theoretical neuroscience at the University of Waterloo where she built neural models of context dependent decision making in the prefrontal cortex and spiking neuron models of bayesian inference, based on online learning of priors from life experience.

Today, in the Fiete and Tenenbaum labs, she studies the computational and theoretical principles underlying cognition and intelligence in the human brain.  She is currently exploring the coding principles in the hippocampal circuits implicated in spatial navigation, and their role in cognitive computations like structure learning and relational reasoning.

When did you start practicing mindfulness?

When I first learned to meditate, I was challenged to practice it every day for at least 3 months in a row. I took up the challenge, and by the end of it, the results were profound. My whole perspective towards life changed. It made me more empathetic — I could step in other people’s shoes and be mindful of their situations and feelings;  my focus shifted from myself to the big picture — it made me realize how insignificant my life was on the grand scale of the universe, and how it was worthless to be caught up in small things that I was usually worrying about. It somehow also brought selflessness to me. This experience hooked me to meditation and mindfulness for life!

What kind of mindfulness do you practice and why?

I practice mindfulness because it brings awareness. It helps me to be aware of myself, my thoughts, my actions, and my surroundings at each moment in my life, thus helping me stay in and enjoy the present moment. Awareness is of utmost importance since an aware mind always does the right thing. Imagine that you are angry, in that moment you have lost awareness of yourself. The moment you become aware of yourself; anger goes away. This is why sometimes counting helps to combat anger. If you start counting, that gives you time to think and become aware of yourself and your actions.

Meditating — sitting with my eyes closed and just observing (being aware of) my thoughts — is a yogic technique that helps me clear the noise in my mind and calm it down making it easier for me to be mindful not only while meditating, but also in general after I am done meditating. Over time, the thoughts vanish, and the mind becomes blank (noiseless). For this reason, practicing meditation regularly makes it easier for me to be mindful all the time.

An added advantage of yoga and meditation is that it helps combat stress by relaxing the mind and body. Many people don’t know what to do when they are stressed, but I am grateful to have this toolkit of yoga and meditation to deal with stressful situations in my life. They help me calm my mind in stressful situations and ensure that instead of reacting to a situation, I instead act mindfully and appropriately to make it right.

K. Lisa Yang Postbaccalaureate Program names new scholars

Funded by philanthropist Lisa Yang, the K. Lisa Yang Postbaccalaureate Scholar Program provides two years of paid laboratory experience, mentorship, and education to recent college graduates from backgrounds underrepresented in neuroscience. This year, two young researchers in McGovern Institute labs, Joseph Itiat and Sam Merrow, are the recipients of the Yang postbac program.

Itiat moved to the United States from Nigeria in 2019 to pursue a degree in psychology and cognitive neuroscience at Temple University. Today, he is a Yang postbac in John Gabrieli’s lab studying the relationship between learning and value processes and their influence on future-oriented decision-making. Ultimately, Itiat hopes to develop models that map the underlying mechanisms driving these processes.

“Being African, with limited research experience and little representation in the domain of neuroscience research,” Itiat says, “I chose to pursue a postbaccalaureate
research program to prepare me for a top graduate school and a career in cognitive neuroscience.”

Merrow first fell in love with science while working at the Barrow Neurological Institute in Arizona during high school. After graduating from Simmons University in Boston, Massachusetts, Merrow joined Guoping Feng’s lab as a Yang postbac to pursue research on glial cells and brain disorders. “As a queer, nonbinary, LatinX person, I have not met anyone like me in my field, nor have I had role models that hold a similar identity to myself,” says Merrow.

“My dream is to one day become a professor, where I will be able to show others that science is for anyone.”

Previous Yang postbacs include Alex Negron, Zoe Pearce, Ajani Stewart, and Maya Taliaferro.

What does the future hold for generative AI?

Speaking at the “Generative AI: Shaping the Future” symposium on Nov. 28, the kickoff event of MIT’s Generative AI Week, keynote speaker and iRobot co-founder Rodney Brooks warned attendees against uncritically overestimating the capabilities of this emerging technology, which underpins increasingly powerful tools like OpenAI’s ChatGPT and Google’s Bard.

“Hype leads to hubris, and hubris leads to conceit, and conceit leads to failure,” cautioned Brooks, who is also a professor emeritus at MIT, a former director of the Computer Science and Artificial Intelligence Laboratory (CSAIL), and founder of Robust.AI.

“No one technology has ever surpassed everything else,” he added.

The symposium, which drew hundreds of attendees from academia and industry to the Institute’s Kresge Auditorium, was laced with messages of hope about the opportunities generative AI offers for making the world a better place, including through art and creativity, interspersed with cautionary tales about what could go wrong if these AI tools are not developed responsibly.

Generative AI is a term to describe machine-learning models that learn to generate new material that looks like the data they were trained on. These models have exhibited some incredible capabilities, such as the ability to produce human-like creative writing, translate languages, generate functional computer code, or craft realistic images from text prompts.

In her opening remarks to launch the symposium, MIT President Sally Kornbluth highlighted several projects faculty and students have undertaken to use generative AI to make a positive impact in the world. For example, the work of the Axim Collaborative, an online education initiative launched by MIT and Harvard, includes exploring the educational aspects of generative AI to help underserved students.

The Institute also recently announced seed grants for 27 interdisciplinary faculty research projects centered on how AI will transform people’s lives across society.

In hosting Generative AI Week, MIT hopes to not only showcase this type of innovation, but also generate “collaborative collisions” among attendees, Kornbluth said.

Collaboration involving academics, policymakers, and industry will be critical if we are to safely integrate a rapidly evolving technology like generative AI in ways that are humane and help humans solve problems, she told the audience.

“I honestly cannot think of a challenge more closely aligned with MIT’s mission. It is a profound responsibility, but I have every confidence that we can face it, if we face it head on and if we face it as a community,” she said.

While generative AI holds the potential to help solve some of the planet’s most pressing problems, the emergence of these powerful machine learning models has blurred the distinction between science fiction and reality, said CSAIL Director Daniela Rus in her opening remarks. It is no longer a question of whether we can make machines that produce new content, she said, but how we can use these tools to enhance businesses and ensure sustainability. 

“Today, we will discuss the possibility of a future where generative AI does not just exist as a technological marvel, but stands as a source of hope and a force for good,” said Rus, who is also the Andrew and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science.

But before the discussion dove deeply into the capabilities of generative AI, attendees were first asked to ponder their humanity, as MIT Professor Joshua Bennett read an original poem.

Bennett, a professor in the MIT Literature Section and Distinguished Chair of the Humanities, was asked to write a poem about what it means to be human, and drew inspiration from his daughter, who was born three weeks ago.

The poem told of his experiences as a boy watching Star Trek with his father and touched on the importance of passing traditions down to the next generation.

In his keynote remarks, Brooks set out to unpack some of the deep, scientific questions surrounding generative AI, as well as explore what the technology can tell us about ourselves.

To begin, he sought to dispel some of the mystery swirling around generative AI tools like ChatGPT by explaining the basics of how this large language model works. ChatGPT, for instance, generates text one word at a time by determining what the next word should be in the context of what it has already written. While a human might write a story by thinking about entire phrases, ChatGPT only focuses on the next word, Brooks explained.

ChatGPT 3.5 is built on a machine-learning model that has 175 billion parameters and has been exposed to billions of pages of text on the web during training. (The newest iteration, ChatGPT 4, is even larger.) It learns correlations between words in this massive corpus of text and uses this knowledge to propose what word might come next when given a prompt.

The model has demonstrated some incredible capabilities, such as the ability to write a sonnet about robots in the style of Shakespeare’s famous Sonnet 18. During his talk, Brooks showcased the sonnet he asked ChatGPT to write side-by-side with his own sonnet.

But while researchers still don’t fully understand exactly how these models work, Brooks assured the audience that generative AI’s seemingly incredible capabilities are not magic, and it doesn’t mean these models can do anything.

His biggest fears about generative AI don’t revolve around models that could someday surpass human intelligence. Rather, he is most worried about researchers who may throw away decades of excellent work that was nearing a breakthrough, just to jump on shiny new advancements in generative AI; venture capital firms that blindly swarm toward technologies that can yield the highest margins; or the possibility that a whole generation of engineers will forget about other forms of software and AI.

At the end of the day, those who believe generative AI can solve the world’s problems and those who believe it will only generate new problems have at least one thing in common: Both groups tend to overestimate the technology, he said.

“What is the conceit with generative AI? The conceit is that it is somehow going to lead to artificial general intelligence. By itself, it is not,” Brooks said.

Following Brooks’ presentation, a group of MIT faculty spoke about their work using generative AI and participated in a panel discussion about future advances, important but underexplored research topics, and the challenges of AI regulation and policy.

The panel consisted of Jacob Andreas, an associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS) and a member of CSAIL; Antonio Torralba, the Delta Electronics Professor of EECS and a member of CSAIL; Ev Fedorenko, an associate professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research at MIT; and Armando Solar-Lezama, a Distinguished Professor of Computing and associate director of CSAIL. It was moderated by William T. Freeman, the Thomas and Gerd Perkins Professor of EECS and a member of CSAIL.

The panelists discussed several potential future research directions around generative AI, including the possibility of integrating perceptual systems, drawing on human senses like touch and smell, rather than focusing primarily on language and images. The researchers also spoke about the importance of engaging with policymakers and the public to ensure generative AI tools are produced and deployed responsibly.

“One of the big risks with generative AI today is the risk of digital snake oil. There is a big risk of a lot of products going out that claim to do miraculous things but in the long run could be very harmful,” Solar-Lezama said.

The morning session concluded with an excerpt from the 1925 science fiction novel “Metropolis,” read by senior Joy Ma, a physics and theater arts major, followed by a roundtable discussion on the future of generative AI. The discussion included Joshua Tenenbaum, a professor in the Department of Brain and Cognitive Sciences and a member of CSAIL; Dina Katabi, the Thuan and Nicole Pham Professor in EECS and a principal investigator in CSAIL and the MIT Jameel Clinic; and Max Tegmark, professor of physics; and was moderated by Daniela Rus.

One focus of the discussion was the possibility of developing generative AI models that can go beyond what we can do as humans, such as tools that can sense someone’s emotions by using electromagnetic signals to understand how a person’s breathing and heart rate are changing.

But one key to integrating AI like this into the real world safely is to ensure that we can trust it, Tegmark said. If we know an AI tool will meet the specifications we insist on, then “we no longer have to be afraid of building really powerful systems that go out and do things for us in the world,” he said.