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New neuron type discovered only in primate brains

by Stephanie M. McPherson |

Neuropsychiatric illnesses like schizophrenia and autism are a complex interplay of brain chemicals, environment, and genetics that requires careful study to understand the root causes. Scientists have traditionally relied on samples taken from mice and non-human primates to study how these diseases develop. But the question has lingered: are the brains of these subjects similar enough to humans to yield useful insights?

Now work from the Broad Institute of MIT and Harvard and the McGovern Institute for Brain Research is pointing towards an answer. In a study published in Nature, researchers from the Broad’s Stanley Center for Psychiatric Research report several key differences in the brains of ferrets, mice, nonhuman primates, and humans, all focused on a type of neuron called interneurons. Most surprisingly, the team found a new type of interneuron only in primates, located in a part of the brain called the striatum, which is associated with Huntington’s disease and potentially schizophrenia.

The findings could help accelerate research into causes of and treatments for neuropsychiatric illnesses, by helping scientists choose the lab model that best mimics features of the human brain that may be involved in these diseases.

“The data from this work will inform the study of human brain disorders because it helps us think about which features of the human brain can be studied in mice, which features require higher organisms such as marmosets, and why mouse models often don’t reflect the effects of the corresponding mutations in human,” said Steven McCarroll, senior author of the study, director of genetics at the Stanley Center, and a professor of genetics at Harvard Medical School.

“Dysfunctions of interneurons have been strongly linked to several brain disorders including autism spectrum disorder and schizophrenia,” said Guoping Feng, co-author of the study, director of model systems and neurobiology at the Stanley Center, and professor of neuroscience at MIT’s McGovern Institute for Brain Research. “These data further demonstrate the unique importance of non-human primate models in understanding neurobiological mechanisms of brain disorders and in developing and testing therapeutic approaches.”

Enter the interneuron

Interneurons form key nodes within neural circuitry in the brain, and help regulate neuronal activity by releasing the neurotransmitter GABA, which inhibits the firing of other neurons.

Fenna Krienen, a postdoctoral fellow in the McCarroll Lab and first author on the Nature paper, and her colleagues wanted to track the natural history of interneurons.

“We wanted to gain an understanding of the evolutionary trajectory of the cell types that make up the brain,” said Krienen. “And then we went about acquiring samples from species that could inform this understanding of evolutionary divergence between humans and the models that so often stand in for humans in neuroscience studies.”

One of the tools the researchers used was Drop-seq, a high-throughput single nucleus RNA sequencing technique developed by McCarroll’s lab, to classify the roles and locations of more than 184,000 telencephalic interneurons in the brains of ferrets, humans, macaques, marmosets, and mice. Using tissue from frozen samples, the team isolated the nuclei of interneurons from the cortex, the hippocampus, and the striatum, and profiled the RNA from the cells.

The researchers thought that because interneurons are found in all vertebrates, the cells would be relatively static from species to species.

“But with these sensitive measurements and a lot of data from the various species, we got a different picture about how lively interneurons are, in terms of the ways that evolution has tweaked their programs or their populations from one species to the next,” said Krienen.

She and her collaborators identified four main differences in interneurons between the species they studied: the cells change their proportions across brain regions, alter the programs they use to link up with other neurons, and can migrate to different regions of the brain.

But most strikingly, the scientists discovered that primates have a novel interneuron not found in other species. The interneuron is located in the striatum—the brain structure responsible for cognition, reward, and coordinated movements that has existed as far back on the evolutionary tree as ancient primitive fish. The researchers were amazed to find the new neuron type made up a third of all interneurons in the striatum.

“Although we expected the big innovations in human and primate brains to be in the cerebral cortex, which we tend to associate with human intelligence, it was in fact in the venerable striatum that Fenna uncovered the most dramatic cellular innovation in the primate brain,” said McCarroll. “This cell type had never been discovered before, because mice have nothing like it.”

“The question of what provides the “human advantage” in cognitive abilities is one of the fundamental issues neurobiologists have endeavored to answer,” said Gordon Fishell, group leader at the Stanley Center, a professor of neurobiology at Harvard Medical School, and a collaborator on the study. “These findings turn on end the question of ‘how do we build better brains?’. It seems at least part of the answer stems from creating a new list of parts.”

A better understanding of how these inhibitory neurons vary between humans and lab models will provide researchers with new tools for investigating various brain disorders. Next, the researchers will build on this work to determine the specific functions of each type of interneuron.

“In studying neurodevelopmental disorders, you would like to be convinced that your model is an appropriate one for really complex social behaviors,” Krienen said. “And the major overarching theme of the study was that primates in general seem to be very similar to one another in all of those interneuron innovations.”

Support for this work was provided in part by the Broad Institute’s Stanley Center for Psychiatric Research and the NIH Brain Initiative, the Dean’s Innovation Award (Harvard Medical School), the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, the Poitras Center for Psychiatric Disorders Research at MIT, the McGovern Institute for Brain Research at MIT, and the National Institute of Neurological Disorders and Stroke.

20 Years of Discovery

by Robert Desimone |

 

McGovern Institute Director Robert Desimone.

Pat and Lore McGovern founded the McGovern Institute 20 years ago with a dual mission – to understand the brain, and to apply that knowledge to help the many people affected by brain disorders. Some of the amazing developments of the past 20 years, such as CRISPR, may seem entirely unexpected and “out of the blue.” But they were all built on a foundation of basic research spanning many years. With the incredible foundation we are building right now, I feel we are poised for many more “unexpected” discoveries in the years ahead.

I predict that in 20 years, we will have quantitative models of brain function that will not only explain how the brain gives rise to at least some aspects of our mind, but will also give us a new mechanistic understanding of brain disorders. This, in turn, will lead to new types of therapies, in what I imagine to be a post-pharmaceutical era of the future. I have no doubt that these same brain models will inspire new educational approaches for our children, and will be incorporated into whatever replaces my automobile, and iPhone, in 2040. I encourage you to read some other predictions from our faculty.

Our cutting-edge work depends not only on our stellar line up of faculty, but the more than 400 postdocs, graduate students, undergraduates, summer students, and staff who make up our community.

For this reason, I am particularly delighted to share with you McGovern’s rising stars — 20 young scientists from each of our labs — who represent the next generation of neuroscience.

And finally, we remain deeply indebted to our supporters for funding our research, including ongoing support from the Patrick J. McGovern Foundation. In recent years, more than 40% of our annual research funding has come from private individuals and foundations. This support enables critical seed funding for new research projects, the development of new technologies, our new research into autism and psychiatric disorders, and fellowships for young scientists just starting their careers. Our annual fund supporters have made possible more than 42 graduate fellowships, and you can read about some of these fellows on our website.

I hope that as you visit our website and read the pages of our special anniversary issue of Brain Scan, you will feel as optimistic as I do about our future.

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

Tool developed in Graybiel lab reveals new clues about Parkinson’s disease

by Jennifer Michalowski |

As the brain processes information, electrical charges zip through its circuits and neurotransmitters pass molecular messages from cell to cell. Both forms of communication are vital, but because they are usually studied separately, little is known about how they work together to control our actions, regulate mood, and perform the other functions of a healthy brain.

Neuroscientists in Ann Graybiel’s laboratory at MIT’s McGovern Institute are taking a closer look at the relationship between these electrical and chemical signals. “Considering electrical signals side by side with chemical signals is really important to understand how the brain works,” says Helen Schwerdt, a postdoctoral researcher in Graybiel’s lab. Understanding that relationship is also crucial for developing better ways to diagnose and treat nervous system disorders and mental illness, she says, noting that the drugs used to treat these conditions typically aim to modulate the brain’s chemical signaling, yet studies of brain activity are more likely to focus on electrical signals, which are easier to measure.

Schwerdt and colleagues in Graybiel’s lab have developed new tools so that chemical and electrical signals can, for the first time, be measured simultaneously in the brains of primates. In a study published September 25, 2020, in Science Advances, they used those tools to reveal an unexpectedly complex relationship between two types of signals that are disrupted in patients with Parkinson’s disease—dopamine signaling and coordinated waves of electrical activity known as beta-band oscillations.

Complicated relationship

Graybiel’s team focused its attention on beta-band activity and dopamine signaling because studies of patients with Parkinson’s disease had suggested a straightforward inverse relationship between the two. The tremors, slowness of movement, and other symptoms associated with the disease develop and progress as the brain’s production of the neurotransmitter dopamine declines, and at the same time, beta-band oscillations surge to abnormal levels. Beta-band oscillations are normally observed in parts of the brain that control movement when a person is paying attention or planning to move. It’s not clear what they do or why they are disrupted in patients with Parkinson’s disease. But because patients’ symptoms tend to be worst when beta activity is high—and because beta activity can be measured in real time with sensors placed on the scalp or with a deep-brain stimulation device that has been implanted for treatment, researchers have been hopeful that it might be useful for monitoring the disease’s progression and patients’ response to treatment. In fact, clinical trials are already underway to explore the effectiveness of modulating deep-brain stimulation treatment based on beta activity.

When Schwerdt and colleagues examined these two types of signals in the brains of rhesus macaques, they discovered that the relationship between beta activity and dopamine is more complicated than previously thought.

Their new tools allowed them to simultaneously monitor both signals with extraordinary precision, targeting specific parts of the striatum—a region deep within the brain involved in controlling movement, where dopamine is particularly abundant—and taking measurements on the millisecond time scale to capture neurons’ rapid-fire communications.

They took these measurements as the monkeys performed a simple task, directing their gaze in a particular direction in anticipation of a reward. This allowed the researchers to track chemical and electrical signaling during the active, motivated movement of the animals’ eyes. They found that beta activity did increase as dopamine signaling declined—but only in certain parts of the striatum and during certain tasks. The reward value of a task, an animal’s past experiences, and the particular movement the animal performed all impacted the relationship between the two types of signals.

Multi-modal systems allow subsecond recording of chemical and electrical neural signals in the form of dopamine molecular concentrations and beta-band local field potentials (beta LFPs), respectively. Online measurements of dopamine and beta LFP (time-dependent traces displayed in box on right) were made in the primate striatum (caudate nucleus and putamen colored in green and purple, respectively, in the left brain image) as the animal was performing a task in which eye movements were made to cues displayed on the left (purple event marker line) and right (green event) of a screen in order to receive large or small amounts of food reward (red and blue events). Dopamine and beta LFP neural signals are centrally implicated in Parkinson’s disease and other brain disorders. Image: Helen Schwerdt

“What we expected is there in the overall view, but if we just look at a different level of resolution, all of a sudden the rules don’t hold,” says Graybiel, who is also an MIT Institute Professor. “It doesn’t destroy the likelihood that one would want to have a treatment related to this presumed opposite relationship, but it does say there’s something more here that we haven’t known about.”

The researchers say it’s important to investigate this more nuanced relationship between dopamine signaling and beta activity, and that understanding it more deeply might lead to better treatments for patients with Parkinson’s disease and related disorders. While they plan to continue to examine how the two types of signals relate to one another across different parts of the brain and under different behavioral conditions, they hope that other teams will also take advantage of the tools they have developed. “As these methods in neuroscience become more and more precise and dazzling in their power, we’re bound to discover new things,” says Graybiel.

This study was supported by the National Institute of Biomedical Imaging and Bioengineering, the National Institute of Neurological Disorders and Stroke, the Army Research Office, the Saks Kavanaugh Foundation, the National Science Foundation, Kristin R. Pressman and Jessica J. Pourian ’13 Fund, and Robert Buxton.

Robert Desimone to receive Goldman-Rakic Prize

by Julie Pryor |

Robert Desimone, the Doris and Don Berkey Professor in Brain and Cognitive Sciences at MIT, has been named a winner of this year’s Goldman-Rakic Prize for Outstanding Achievement in Cognitive Neuroscience Research. The award, given annually by the Brain and Behavior Research Foundation, is named in recognition of former Yale University neuroscientist Patricia Goldman-Rakic.

Desimone, who is also the director of the McGovern Institute for Brain Research, studies the brain mechanisms underlying attention, and most recently he has been studying animal models for brain disorders.

Desimone will deliver his prize lecture at the 2020 Annual International Mental Health Research Virtual Symposium on October 30, 2020.

Rapid test for Covid-19 shows improved sensitivity

by Anne Trafton |

Since the start of the Covid-19 pandemic, researchers at MIT and the Broad Institute of MIT and Harvard, along with their collaborators at the University of Washington, Fred Hutchinson Cancer Research Center, Brigham and Women’s Hospital, and the Ragon Institute, have been working on a CRISPR-based diagnostic for Covid-19 that can produce results in 30 minutes to an hour, with similar accuracy as the standard PCR diagnostics now used.

The new test, known as STOPCovid, is still in the research stage but, in principle, could be made cheaply enough that people could test themselves every day. In a study appearing today in the New England Journal of Medicine, the researchers showed that on a set of patient samples, their test detected 93 percent of the positive cases as determined by PCR tests for Covid-19.

“We need rapid testing to become part of the fabric of this situation so that people can test themselves every day, which will slow down outbreak,” says Omar Abudayyeh, an MIT McGovern Fellow working on the diagnostic.

Abudayyah is one of the senior authors of the study, along with Jonathan Gootenberg, a McGovern Fellow, and Feng Zhang, a core member of the Broad Institute, investigator at the MIT McGovern Institute and Howard Hughes Medical Institute, and the James and Patricia Poitras ’63 Professor of Neuroscience at MIT. The first authors of the paper are MIT biological engineering graduate students Julia Joung and Alim Ladha in the Zhang lab.

A streamlined test

Zhang’s laboratory began collaborating with the Abudayyeh and Gootenberg laboratory to work on the Covid-19 diagnostic soon after the SARS-CoV-2 outbreak began. They focused on making an assay, called STOPCovid, that was simple to carry out and did not require any specialized laboratory equipment. Such a test, they hoped, would be amenable to future use in point-of-care settings, such as doctors’ offices, pharmacies, nursing homes, and schools.

“We developed STOPCovid so that everything could be done in a single step,” Joung says. “A single step means the test can be potentially performed by nonexperts outside of laboratory settings.”

In the new version of STOPCovid reported today, the researchers incorporated a process to concentrate the viral genetic material in a patient sample by adding magnetic beads that attract RNA, eliminating the need for expensive purification kits that are time-intensive and can be in short supply due to high demand. This concentration step boosted the test’s sensitivity so that it now approaches that of PCR.

“Once we got the viral genomes onto the beads, we found that that could get us to very high levels of sensitivity,” Gootenberg says.

Working with collaborators Keith Jerome at Fred Hutchinson Cancer Research Center and Alex Greninger at the University of Washington, the researchers tested STOPCovid on 402 patient samples — 202 positive and 200 negative — and found that the new test detected 93 percent of the positive cases as determined by the standard CDC PCR test.

“Seeing STOPCovid working on actual patient samples was really gratifying,” Ladha says.

They also showed, working with Ann Woolley and Deb Hung at Brigham and Women’s Hospital, that the STOPCovid test works on samples taken using the less invasive anterior nares swab. They are now testing it with saliva samples, which could make at-home tests even easier to perform. The researchers are continuing to develop the test with the hope of delivering it to end users to help fight the COVID-19 pandemic.

“The goal is to make this test easy to use and sensitive, so that we can tell whether or not someone is carrying the virus as early as possible,” Zhang says.

The research was funded by the National Institutes of Health, the Swiss National Science Foundation, the Patrick J. McGovern Foundation, the McGovern Institute for Brain Research, the Massachusetts Consortium on Pathogen Readiness Evergrande Covid-19 Response Fund, the Mathers Foundation, the Howard Hughes Medical Institute, the Open Philanthropy Project, J. and P. Poitras, and R. Metcalfe.

 

FULL PAPER AT NEJM

New molecular therapeutics center established at MIT’s McGovern Institute

by Julie Pryor |

More than one million Americans are diagnosed with a chronic brain disorder each year, yet effective treatments for most complex brain disorders are inadequate or even nonexistent.

A major new research effort at MIT’s McGovern Institute aims to change how we treat brain disorders by developing innovative molecular tools that precisely target dysfunctional genetic, molecular, and circuit pathways.

The K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience was established at MIT through a $28 million gift from philanthropist Lisa Yang and MIT alumnus Hock Tan ’75. Yang is a former investment banker who has devoted much of her time to advocacy for individuals with disabilities and autism spectrum disorders. Tan is President and CEO of Broadcom, a global technology infrastructure company. This latest gift brings Yang and Tan’s total philanthropy to MIT to more than $72 million.

Lisa Yang (center) and MIT alumnus Hock Tan ’75 with their daughter Eva (far left) pictured at the opening of the Hock E. Tan and K. Lisa Yang Center for Autism Research in 2017. Photo: Justin Knight

“In the best MIT spirit, Lisa and Hock have always focused their generosity on insights that lead to real impact,” says MIT President L. Rafael Reif. “Scientifically, we stand at a moment when the tools and insights to make progress against major brain disorders are finally within reach. By accelerating the development of promising treatments, the new center opens the door to a hopeful new future for all those who suffer from these disorders and those who love them. I am deeply grateful to Lisa and Hock for making MIT the home of this pivotal research.”

Engineering with precision

Research at the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience will initially focus on three major lines of investigation: genetic engineering using CRISPR tools, delivery of genetic and molecular cargo across the blood-brain barrier, and the translation of basic research into the clinical setting. The center will serve as a hub for researchers with backgrounds ranging from biological engineering and genetics to computer science and medicine.

“Developing the next generation of molecular therapeutics demands collaboration among researchers with diverse backgrounds,” says Robert Desimone, McGovern Institute Director and Doris and Don Berkey Professor of Neuroscience at MIT. “I am confident that the multidisciplinary expertise convened by this center will revolutionize how we improve our health and fight disease in the coming decade. Although our initial focus will be on the brain and its relationship to the body, many of the new therapies could have other health applications.”

There are an estimated 19,000 to 22,000 genes in the human genome and a third of those genes are active in the brain–the highest proportion of genes expressed in any part of the body.

Variations in genetic code have been linked to many complex brain disorders, including depression and Parkinson’s. Emerging genetic technologies, such as the CRISPR gene editing platform pioneered by McGovern Investigator Feng Zhang, hold great potential in both targeting and fixing these errant genes. But the safe and effective delivery of this genetic cargo to the brain remains a challenge.

Researchers within the new Yang-Tan Center will improve and fine-tune CRISPR gene therapies and develop innovative ways of delivering gene therapy cargo into the brain and other organs. In addition, the center will leverage newly developed single cell analysis technologies that are revealing cellular targets for modulating brain functions with unprecedented precision, opening the door for noninvasive neuromodulation as well as the development of medicines. The center will also focus on developing novel engineering approaches to delivering small molecules and proteins from the bloodstream into the brain. Desimone will direct the center and some of the initial research initiatives will be led by Associate Professor of Materials Science and Engineering Polina Anikeeva; Ed Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT; Guoping Feng, the James W. (1963) and Patricia T. Poitras Professor of Brain and Cognitive Sciences at MIT; and Feng Zhang, James and Patricia Poitras Professor of Neuroscience at MIT.

Building a research hub

“My goal in creating this center is to cement the Cambridge and Boston region as the global epicenter of next-generation therapeutics research. The novel ideas I have seen undertaken at MIT’s McGovern Institute and Broad Institute of MIT and Harvard leave no doubt in my mind that major therapeutic breakthroughs for mental illness, neurodegenerative disease, autism and epilepsy are just around the corner,” says Yang.

Center funding will also be earmarked to create the Y. Eva Tan Fellows program, named for Tan and Yang’s daughter Eva, which will support fellowships for young neuroscientists and engineers eager to design revolutionary treatments for human diseases.

“We want to build a strong pipeline for tomorrow’s scientists and neuroengineers,” explains Hock Tan. “We depend on the next generation of bright young minds to help improve the lives of people suffering from chronic illnesses, and I can think of no better place to provide the very best education and training than MIT.”

The molecular therapeutics center is the second research center established by Yang and Tan at MIT. In 2017, they launched the Hock E. Tan and K. Lisa Yang Center for Autism Research, and, two years later, they created a sister center at Harvard Medical School, with the unique strengths of each institution converging toward a shared goal: understanding the basic biology of autism and how genetic and environmental influences converge to give rise to the condition, then translating those insights into novel treatment approaches.

All tools developed at the molecular therapeutics center will be shared globally with academic and clinical researchers with the goal of bringing one or more novel molecular tools to human clinical trials by 2025.

“We are hopeful that our centers, located in the heart of the Cambridge-Boston biotech ecosystem, will spur further innovation and fuel critical new insights to our understanding of health and disease,” says Yang.

 

School of Science appoints 12 faculty members to named professorships

Anne Trafton |

The School of Science has awarded chaired appointments to 12 faculty members. These faculty, who are members of the departments of Biology; Brain and Cognitive Sciences; Chemistry; Earth, Atmospheric and Planetary Sciences; and Physics, receive additional support to pursue their research and develop their careers.

Kristin Bergmann, an assistant professor in the Department of Earth, Atmospheric and Planetary Sciences, has been named a D. Reid Weedon, Jr. ’41 Career Development Professor. This is a three-year professorship. Bergmann’s research integrates across sedimentology and stratigraphy, geochemistry, and geobiology to reveal aspects of Earth’s ancient environments. She aims to better constrain Earth’s climate record and carbon cycle during the evolution of early eukaryotes, including animals. Most of her efforts involve reconstructing the details of carbonate rocks, which store much of Earth’s carbon, and thus, are an important component of Earth’s climate system over long timescales.

Joseph Checkelscky is an associate professor in the Department of Physics and has been named a Mitsui Career Development Professor in Contemporary Technology, an appointment he will hold until 2023. His research in quantum materials relies on experimental methods at the intersection of physics, chemistry, and nanoscience. This work is aimed toward synthesizing new crystalline systems that manifest their quantum nature on a macroscopic scale. He aims to realize and study these crystalline systems, which can then serve as platforms for next-generation quantum sensors, quantum communication, and quantum computers.

Mircea Dincă, appointed a W. M. Keck Professor of Energy, is a professor in the Department of Chemistry. This appointment has a five-year term. The topic of Dincă’s research falls largely under the umbrella of energy storage and conversion. His interest in applied energy usage involves creating new organic and inorganic materials that can improve the efficiency of energy collection, storage, and generation while decreasing environmental impacts. Recently, he has developed materials for efficient air-conditioning units and been collaborating with Automobili Lamborghini on electric vehicle design.

Matthew Evans has been appointed to a five-year Mathworks Physics Professorship. Evans, a professor in the Department of Physics, focuses on the instruments used to detect gravitational waves. A member of MIT’s Laser Interferometer Gravitational-Wave Observatory (LIGO) research group, he engineers ways to fine-tune the detection capabilities of the massive ground-based facilities that are being used to identify collisions between black holes and stars in deep space. By removing thermal and quantum limitations, he can increase the sensitivity of the device’s measurements and, thus, its scope of exploration. Evans is also a member of the MIT Kavli Institute for Astrophysics and Space Research.

Evelina Fedorenko is an associate professor in the Department of Brain and Cognitive Sciences and has been named a Frederick A. (1971) and Carole J. Middleton Career Development Professor of Neuroscience. Studying how the brain processes language, Fedorenko uses behavioral studies, brain imaging, neurosurgical recording and stimulation, and computational modelling to better grasp language comprehension and production. In her efforts to elucidate how and what parts of the brain support language processing, she evaluates both typical and atypical brains. Fedorenko is also a member of the McGovern Institute for Brain Research.

Ankur Jain is an assistant professor in the Department of Biology and now a Thomas D. and Virginia W. Cabot Career Development Professor. He will hold this career development appointment for a term of three years. Jain studies how cells organize their contents. Within a cell, there are numerous compartments that form due to weak interactions between biomolecules and exist without an enclosing membrane. By analyzing the biochemistry and biophysics of these compartments, Jain deduces the principles of cellular organization and its dysfunction in human disease. Jain is also a member of the Whitehead Institute for Biomedical Research.

Pulin Li, an assistant professor in the Department of Biology and the Eugene Bell Career Development Professor of Tissue Engineering for the next three years, explores genetic circuitry in building and maintain a tissue. In particular, she investigates how communication circuitry between individual cells can extrapolate into multicellular behavior using both natural and synthetically generated tissues, for which she combines the fields of synthetic and systems biology, biophysics, and bioengineering. A stronger understanding of genetic circuitry could allow for progress in medicine involving embryonic development and tissue engineering. Li is a member of the Whitehead Institute for Biomedical Research.

Elizabeth Nolan, appointed an Ivan R. Cottrell Professor of Immunology, investigates innate immunity and infectious disease. The Department of Chemistry professor, who will hold this chaired professorship for five years, combines experimental chemistry and microbiology to learn about human immune responses to, and interactions with, microbial pathogens. This research includes elucidating the fight between host and pathogen for essential metal nutrients and the functions of host-defense peptides and proteins during infection. With this knowledge, Nolan contributes to fundamental understanding of the host’s ability to combat microbial infection, which may provide new strategies to treat infectious disease.

Leigh “Wiki” Royden is now a Cecil and Ida Green Professor of Geology and Geophysics. The five-year appointment supports her research on the large-scale dynamics and tectonics of the Earth as a professor in the Department of Earth, Atmospheric and Planetary Sciences. Fundamental to geoscience, the tectonics of regional and global systems are closely linked, particularly through the subduction of the plates into the mantle. Royden’s research adds to our understanding a of the structure and dynamics of the crust and the upper portion of the mantle through observation, theory and modeling. This progress has profound implications for global natural events, like mountain building and continental break-up.

Phiala Shanahan has been appointed a Class of 1957 Career Development Professor for three years. Shanahan is an assistant professor in the Department of Physics, where she specializes in theoretical and nuclear physics. Shanahan’s research uses supercomputers to provide insight into the structure of protons and nuclei in terms of their quark and gluon constituents. Her work also informs searches for new physics beyond the current Standard Model, such dark matter. She is a member of the MIT Center for Theoretical Physics.

Xiao Wang, an assistant professor, has also been named a new Thomas D. and Virginia W. Cabot Professor. In the Department of Chemistry, Wang designs and produces novel methods and tools for analyzing the brain. Integrating chemistry, biophysics, and genomics, her work provides higher-resolution imaging and sampling to explain how the brain functions across molecular to system-wide scales. Wang is also a core member of the Broad Institute of MIT and Harvard.

Bin Zhang has been appointed a Pfizer Inc-Gerald Laubach Career Development Professor for a three-year term. Zhang, an assistant professor in the Department of Chemistry, hopes to connect the framework of the human genome sequence with its various functions on various time and spatial scales. By developing theoretical and computational approaches to categorize information about dynamics, organization, and complexity of the genome, he aims to build a quantitative, predictive modelling tool. This tool could even produce 3D representations of details happening at a microscopic level within the body.

How general anesthesia reduces pain

by Sabbi Lall |

General anesthesia is medication that suppresses pain and renders patients unconscious during surgery, but whether pain suppression is simply a side effect of loss of consciousness has been unclear. Fan Wang and colleagues have now identified the circuits linked to pain suppression under anesthesia in mouse models, showing that this effect is separable from the unconscious state itself.

“Existing literature suggests that the brain may contain a switch that can turn off pain perception,” explains Fan Wang, a professor at Duke University and lead author of the study. “I had always wanted to find this switch, and it occurred to me that general anesthetics may activate this switch to produce analgesia.”

Wang, who will join the McGovern Institute in January 2021, set out to test this idea with her student, Thuy Hua, and postdoc, Bin Chen.

Pain suppressor

Loss of pain, or analgesia, is an important property of anesthetics that helps to make surgical and invasive medical procedures humane and bearable. In spite of their long use in the medical world, there is still very little understanding of how anesthetics work. It has generally been assumed that a side effect of loss of consciousness is analgesia, but several recent observations have brought this idea into question, and suggest that changes in consciousness might be separable from pain suppression.

A key clue that analgesia is separable from general anesthesia comes from the accounts of patients that regain consciousness during surgery. After surgery, these patients can recount conversations between staff or events that occurred in the operating room, despite not feeling any pain. In addition, some general anesthetics, such as ketamine, can be deployed at low concentrations for pain suppression without loss of consciousness.

Following up on these leads, Wang and colleagues set out to uncover which neural circuits might be involved in suppressing pain during exposure to general anesthetics. Using CANE, a procedure developed by Wang that can detect which neurons activate in response to an event, Wang discovered a new population of GABAergic neurons activated by general anesthetic in the mouse central amygdala.

These neurons become activated in response to different anesthetics, including ketamine, dexmedetomidine, and isoflurane. Using optogenetics to manipulate the activity state of these neurons, Wang and her lab found that they led to marked changes in behavioral responses to painful stimuli.

“The first time we used optogenetics to turn on these cells, a mouse that was in the middle of taking care of an injury simply stopped and started walked around with no sign of pain,” Wang explains.

Specifically, activating these cells blocks pain in multiple models and tests, whereas inhibiting these neurons rendered mice aversive to gentle touch — suggesting that they are involved in a newly uncovered central pain circuit.

The study has implications for both anesthesia and pain. It shows that general anesthetics have complex, multi-faceted effects and that the brain may contain a central pain suppression system.

“We want to figure out how diverse general anesthetics activate these neurons,” explains Wang. “That way we can find compounds that can specifically activate these pain-suppressing neurons without sedation. We’re now also testing whether placebo analgesia works by activating these same central neurons.”

The study also has implications for addiction as it may point to an alternative system for central pain suppression that could be a target of drugs that do not have the devastating side effects of opioids.

Fan Wang joins the McGovern Institute

by Sabbi Lall |

The McGovern Institute is pleased to announce that Fan Wang, currently a Professor at Duke University, will be joining its team of investigators in 2021. Wang is well-known for her work on sensory perception, pain, and behavior. She takes a broad, and very practical approach to these questions, knowing that sensory perception has broad implications for biomedicine when it comes to pain management, addiction, anesthesia, and hypersensitivity.

“McGovern is a dream place for doing innovative and transformative neuroscience.” – Fan Wang

“I am so thrilled that Fan is coming to the McGovern Institute,” says Robert Desimone, director of the institute and the Doris and Don Berkey Professor of Neuroscience at MIT. “I’ve followed her work for a number of years, and she is making inroads into questions that are relevant to a number of societal problems, such as how we can turn off the perception of chronic pain.”

Wang brings with her a range of techniques developed in her lab, including CANE, which precisely highlights neurons that become activated in response to a stimulus. CANE is highlighting new neuronal subtypes in long-studied brain regions such as the amygdala, and recently elucidated previously undefined neurons in the lateral parabrachial nucleus involved in pain processing.

“I am so excited to join the McGovern Institute,” says Wang. “It is a dream place for doing innovative and transformative neuroscience. McGovern researchers are known for using the most cutting-edge, multi-disciplinary technologies to understand how the brain works. I can’t wait to join the team.”

Wang earned her PhD in 1998 with Richard Axel at Columbia University, subsequently conducting postdoctoral research at Stanford University with Mark Tessier-Lavigne. Wang joined Duke University as a Professor in the Department of Neurobiology in 2003, and was later appointed the Morris N. Broad Distinguished Professor of Neurobiology at Duke University School of Medicine. Wang will join the McGovern Institute as an investigator in January 2021.

National Science Foundation announces MIT-led Institute for Artificial Intelligence and Fundamental Interactions

by Laboratory for Nuclear Science |

The U.S. National Science Foundation (NSF) announced today an investment of more than $100 million to establish five artificial intelligence (AI) institutes, each receiving roughly $20 million over five years. One of these, the NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI), will be led by MIT’s Laboratory for Nuclear Science (LNS) and become the intellectual home of more than 25 physics and AI senior researchers at MIT and Harvard, Northeastern, and Tufts universities.

By merging research in physics and AI, the IAIFI seeks to tackle some of the most challenging problems in physics, including precision calculations of the structure of matter, gravitational-wave detection of merging black holes, and the extraction of new physical laws from noisy data.

“The goal of the IAIFI is to develop the next generation of AI technologies, based on the transformative idea that artificial intelligence can directly incorporate physics intelligence,” says Jesse Thaler, an associate professor of physics at MIT, LNS researcher, and IAIFI director.  “By fusing the ‘deep learning’ revolution with the time-tested strategies of ‘deep thinking’ in physics, we aim to gain a deeper understanding of our universe and of the principles underlying intelligence.”

IAIFI researchers say their approach will enable making groundbreaking physics discoveries, and advance AI more generally, through the development of novel AI approaches that incorporate first principles from fundamental physics.

“Invoking the simple principle of translational symmetry — which in nature gives rise to conservation of momentum — led to dramatic improvements in image recognition,” says Mike Williams, an associate professor of physics at MIT, LNS researcher, and IAIFI deputy director. “We believe incorporating more complex physics principles will revolutionize how AI is used to study fundamental interactions, while simultaneously advancing the foundations of AI.”

In addition, a core element of the IAIFI mission is to transfer their technologies to the broader AI community.

“Recognizing the critical role of AI, NSF is investing in collaborative research and education hubs, such as the NSF IAIFI anchored at MIT, which will bring together academia, industry, and government to unearth profound discoveries and develop new capabilities,” says NSF Director Sethuraman Panchanathan. “Just as prior NSF investments enabled the breakthroughs that have given rise to today’s AI revolution, the awards being announced today will drive discovery and innovation that will sustain American leadership and competitiveness in AI for decades to come.”

Research in AI and fundamental interactions

Fundamental interactions are described by two pillars of modern physics: at short distances by the Standard Model of particle physics, and at long distances by the Lambda Cold Dark Matter model of Big Bang cosmology. Both models are based on physical first principles such as causality and space-time symmetries.  An abundance of experimental evidence supports these theories, but also exposes where they are incomplete, most pressingly that the Standard Model does not explain the nature of dark matter, which plays an essential role in cosmology.

AI has the potential to help answer these questions and others in physics.

For many physics problems, the governing equations that encode the fundamental physical laws are known. However, undertaking key calculations within these frameworks, as is essential to test our understanding of the universe and guide physics discovery, can be computationally demanding or even intractable. IAIFI researchers are developing AI for such first-principles theory studies, which naturally require AI approaches that rigorously encode physics knowledge.

“My group is developing new provably exact algorithms for theoretical nuclear physics,” says Phiala Shanahan, an assistant professor of physics and LNS researcher at MIT. “Our first-principles approach turns out to have applications in other areas of science and even in robotics, leading to exciting collaborations with industry partners.”

Incorporating physics principles into AI could also have a major impact on many experimental applications, such as designing AI methods that are more easily verifiable. IAIFI researchers are working to enhance the scientific potential of various facilities, including the Large Hadron Collider (LHC) and the Laser Interferometer Gravity Wave Observatory (LIGO).

“Gravitational-wave detectors are among the most sensitive instruments on Earth, but the computational systems used to operate them are mostly based on technology from the previous century,” says Principal Research Scientist Lisa Barsotti of the MIT Kavli Institute for Astrophysics and Space Research. “We have only begun to scratch the surface of what can be done with AI; just enough to see that the IAIFI will be a game-changer.”

The unique features of these physics applications also offer compelling research opportunities in AI more broadly. For example, physics-informed architectures and hardware development could lead to advances in the speed of AI algorithms, and work in statistical physics is providing a theoretical foundation for understanding AI dynamics.

“Physics has inspired many time-tested ideas in machine learning: maximizing entropy, Boltzmann machines, and variational inference, to name a few,” says Pulkit Agrawal, an assistant professor of electrical engineering and computer science at MIT, and researcher in the Computer Science and Artificial Intelligence Laboratory (CSAIL). “We believe that close interaction between physics and AI researchers will be the catalyst that leads to the next generation of machine learning algorithms.”

Cultivating early-career talent

AI technologies are advancing rapidly, making it both important and challenging to train junior researchers at the intersection of physics and AI. The IAIFI aims to recruit and train a talented and diverse group of early-career researchers, including at the postdoc level through its IAIFI Fellows Program.

“By offering our fellows their choice of research problems, and the chance to focus on cutting-edge challenges in physics and AI, we will prepare many talented young scientists to become future leaders in both academia and industry,” says MIT professor of physics Marin Soljacic of the Research Laboratory of Electronics (RLE).

IAIFI researchers hope these fellows will spark interdisciplinary and multi-investigator collaborations, generate new ideas and approaches, translate physics challenges beyond their native domains, and help develop a common language across disciplines. Applications for the inaugural IAIFI fellows are due in mid-October.

Another related effort spearheaded by Thaler, Williams, and Alexander Rakhlin, an associate professor of brain and cognitive science at MIT and researcher in the Institute for Data, Systems, and Society (IDSS), is the development of a new interdisciplinary PhD program in physics, statistics, and data science, a collaborative effort between the Department of Physics and the Statistics and Data Science Center.

“Statistics and data science are among the foundational pillars of AI. Physics joining the interdisciplinary doctoral program will bring forth new ideas and areas of exploration, while fostering a new generation of leaders at the intersection of physics, statistics, and AI,” says Rakhlin.

Education, outreach, and partnerships 

The IAIFI aims to cultivate “human intelligence” by promoting education and outreach. For example, IAIFI members will contribute to establishing a MicroMasters degree program at MIT for students from non-traditional backgrounds.

“We will increase the number of students in both physics and AI from underrepresented groups by providing fellowships for the MicroMasters program,” says Isaac Chuang, professor of physics and electrical engineering, senior associate dean for digital learning, and RLE researcher at MIT. “We also plan on working with undergraduate MIT Summer Research Program students, to introduce them to the tools of physics and AI research that they might not have access to at their home institutions.”

The IAIFI plans to expand its impact via numerous outreach efforts, including a K-12 program in which students are given data from the LHC and LIGO and tasked with rediscovering the Higgs boson and gravitational waves.

“After confirming these recent Nobel Prizes, we can ask the students to find tiny artificial signals embedded in the data using AI and fundamental physics principles,” says assistant professor of physics Phil Harris, an LNS researcher at MIT. “With projects like this, we hope to disseminate knowledge about — and enthusiasm for — physics, AI, and their intersection.”

In addition, the IAIFI will collaborate with industry and government to advance the frontiers of both AI and physics, as well as societal sectors that stand to benefit from AI innovation. IAIFI members already have many active collaborations with industry partners, including DeepMind, Microsoft Research, and Amazon.

“We will tackle two of the greatest mysteries of science: how our universe works and how intelligence works,” says MIT professor of physics Max Tegmark, an MIT Kavli Institute researcher. “Our key strategy is to link them, using physics to improve AI and AI to improve physics. We’re delighted that the NSF is investing the vital seed funding needed to launch this exciting effort.”

Building new connections at MIT and beyond

Leveraging MIT’s culture of collaboration, the IAIFI aims to generate new connections and to strengthen existing ones across MIT and beyond.

Of the 27 current IAIFI senior investigators, 16 are at MIT and members of the LNS, RLE, MIT Kavli Institute, CSAIL, and IDSS. In addition, IAIFI investigators are members of related NSF-supported efforts at MIT, such as the Center for Brains, Minds, and Machines within the McGovern Institute for Brain Research and the MIT-Harvard Center for Ultracold Atoms.

“We expect a lot of creative synergies as we bring physics and computer science together to study AI,” says Bill Freeman, the Thomas and Gerd Perkins Professor of Electrical Engineering and Computer Science and researcher in CSAIL. “I’m excited to work with my physics colleagues on topics that bridge these fields.”

More broadly, the IAIFI aims to make Cambridge, Massachusetts, and the surrounding Boston area a hub for collaborative efforts to advance both physics and AI.

“As we teach in 8.01 and 8.02, part of what makes physics so powerful is that it provides a universal language that can be applied to a wide range of scientific problems,” says Thaler. “Through the IAIFI, we will create a common language that transcends the intellectual borders between physics and AI to facilitate groundbreaking discoveries.”