Author: MIT News

Scientists find neurons that process language on different timescales

by Anne Trafton |

Using functional magnetic resonance imaging (fMRI), neuroscientists have identified several regions of the brain that are responsible for processing language. However, discovering the specific functions of neurons in those regions has proven difficult because fMRI, which measures changes in blood flow, doesn’t have high enough resolution to reveal what small populations of neurons are doing.

Now, using a more precise technique that involves recording electrical activity directly from the brain, MIT neuroscientists have identified different clusters of neurons that appear to process different amounts of linguistic context. These “temporal windows” range from just one word up to about six words.

The temporal windows may reflect different functions for each population, the researchers say. Populations with shorter windows may analyze the meanings of individual words, while those with longer windows may interpret more complex meanings created when words are strung together.

“This is the first time we see clear heterogeneity within the language network,” says Evelina Fedorenko, an associate professor of neuroscience at MIT. “Across dozens of fMRI experiments, these brain areas all seem to do the same thing, but it’s a large, distributed network, so there’s got to be some structure there. This is the first clear demonstration that there is structure, but the different neural populations are spatially interleaved so we can’t see these distinctions with fMRI.”

Fedorenko, who is also a member of MIT’s McGovern Institute for Brain Research, is the senior author of the study, which appears today in Nature Human Behavior. MIT postdoc Tamar Regev and Harvard University graduate student Colton Casto are the lead authors of the paper.

Temporal windows

Functional MRI, which has helped scientists learn a great deal about the roles of different parts of the brain, works by measuring changes in blood flow in the brain. These measurements act as a proxy of neural activity during a particular task. However, each “voxel,” or three-dimensional chunk, of an fMRI image represents hundreds of thousands to millions of neurons and sums up activity across about two seconds, so it can’t reveal fine-grained detail about what those neurons are doing.

One way to get more detailed information about neural function is to record electrical activity using electrodes implanted in the brain. These data are hard to come by because this procedure is done only in patients who are already undergoing surgery for a neurological condition such as severe epilepsy.

“It can take a few years to get enough data for a task because these patients are relatively rare, and in a given patient electrodes are implanted in idiosyncratic locations based on clinical needs, so it takes a while to assemble a dataset with sufficient coverage of some target part of the cortex. But these data, of course, are the best kind of data we can get from human brains: You know exactly where you are spatially and you have very fine-grained temporal information,” Fedorenko says.

In a 2016 study, Fedorenko reported using this approach to study the language processing regions of six people. Electrical activity was recorded while the participants read four different types of language stimuli: complete sentences, lists of words, lists of non-words, and “jabberwocky” sentences — sentences that have grammatical structure but are made of nonsense words.

Those data showed that in some neural populations in language processing regions, activity would gradually build up over a period of several words, when the participants were reading sentences. However, this did not happen when they read lists of words, lists of nonwords, of Jabberwocky sentences.

In the new study, Regev and Casto went back to those data and analyzed the temporal response profiles in greater detail. In their original dataset, they had recordings of electrical activity from 177 language-responsive electrodes across the six patients. Conservative estimates suggest that each electrode represents an average of activity from about 200,000 neurons. They also obtained new data from a second set of 16 patients, which included recordings from another 362 language-responsive electrodes.

When the researchers analyzed these data, they found that in some of the neural populations, activity would fluctuate up and down with each word. In others, however, activity would build up over multiple words before falling again, and yet others would show a steady buildup of neural activity over longer spans of words.

By comparing their data with predictions made by a computational model that the researchers designed to process stimuli with different temporal windows, the researchers found that neural populations from language processing areas could be divided into three clusters. These clusters represent temporal windows of either one, four, or six words.

“It really looks like these neural populations integrate information across different timescales along the sentence,” Regev says.

Processing words and meaning

These differences in temporal window size would have been impossible to see using fMRI, the researchers say.

“At the resolution of fMRI, we don’t see much heterogeneity within language-responsive regions. If you localize in individual participants the voxels in their brain that are most responsive to language, you find that their responses to sentences, word lists, jabberwocky sentences and non-word lists are highly similar,” Casto says.

The researchers were also able to determine the anatomical locations where these clusters were found. Neural populations with the shortest temporal window were found predominantly in the posterior temporal lobe, though some were also found in the frontal or anterior temporal lobes. Neural populations from the two other clusters, with longer temporal windows, were spread more evenly throughout the temporal and frontal lobes.

Fedorenko’s lab now plans to study whether these timescales correspond to different functions. One possibility is that the shortest timescale populations may be processing the meanings of a single word, while those with longer timescales interpret the meanings represented by multiple words.

“We already know that in the language network, there is sensitivity to how words go together and to the meanings of individual words,” Regev says. “So that could potentially map to what we’re finding, where the longest timescale is sensitive to things like syntax or relationships between words, and maybe the shortest timescale is more sensitive to features of single words or parts of them.”

The research was funded by the Zuckerman-CHE STEM Leadership Program, the Poitras Center for Psychiatric Disorders Research, the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University, the U.S. National Institutes of Health, an American Epilepsy Society Research and Training Fellowship, the McDonnell Center for Systems Neuroscience, Fondazione Neurone, the McGovern Institute, MIT’s Department of Brain and Cognitive Sciences, and the Simons Center for the Social Brain.

Three MIT professors named 2024 Vannevar Bush Fellows

by School of Science |

The U.S. Department of Defense (DoD) has announced three MIT professors among the members of the 2024 class of the Vannevar Bush Faculty Fellowship (VBFF). The fellowship is the DoD’s flagship single-investigator award for research, inviting the nation’s most talented researchers to pursue ambitious ideas that defy conventional boundaries.

Domitilla Del Vecchio, professor of mechanical engineering and the Grover M. Hermann Professor in Health Sciences & Technology; Mehrdad Jazayeri, professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research; and Themistoklis Sapsis, the William I. Koch Professor of Mechanical Engineering and director of the Center for Ocean Engineering are among the 11 university scientists and engineers chosen for this year’s fellowship class. They join an elite group of approximately 50 fellows from previous class years.

“The Vannevar Bush Faculty Fellowship is more than a prestigious program,” said Bindu Nair, director of the Basic Research Office in the Office of the Under Secretary of Defense for Research and Engineering, in a press release. “It’s a beacon for tenured faculty embarking on groundbreaking ‘blue sky’ research.”

Research topics

Each fellow receives up to $3 million over a five-year term to pursue cutting-edge projects. Research topics in this year’s class span a range of disciplines, including materials science, cognitive neuroscience, quantum information sciences, and applied mathematics. While pursuing individual research endeavors, Fellows also leverage the unique opportunity to collaborate directly with DoD laboratories, fostering a valuable exchange of knowledge and expertise.

Del Vecchio, whose research interests include control and dynamical systems theory and systems and synthetic biology, will investigate the molecular underpinnings of analog epigenetic cell memory, then use what they learn to “establish unprecedented engineering capabilities for creating self-organizing and reconfigurable multicellular systems with graded cell fates.”

“With this fellowship, we will be able to explore the limits to which we can leverage analog memory to create multicellular systems that autonomously organize in permanent, but reprogrammable, gradients of cell fates and can be used for creating next-generation tissues and organoids with dramatically increased sophistication,” she says, honored to have been selected.

Jazayeri wants to understand how the brain gives rise to cognitive and emotional intelligence. The engineering systems being built today lack the hallmarks of human intelligence, explains Jazayeri. They neither learn quickly nor generalize their knowledge flexibly. They don’t feel emotions or have emotional intelligence.

Jazayeri plans to use the VBFF award to integrate ideas from cognitive science, neuroscience, and machine learning with experimental data in humans, animals, and computer models to develop a computational understanding of cognitive and emotional intelligence.

“I’m honored and humbled to be selected and excited to tackle some of the most challenging questions at the intersection of neuroscience and AI,” he says.

“I am humbled to be included in such a select group,” echoes Sapsis, who will use the grant to research new algorithms and theory designed for the efficient computation of extreme event probabilities and precursors, and for the design of mitigation strategies in complex dynamical systems.

Examples of Sapsis’s work include risk quantification for extreme events in human-made systems; climate events, such as heat waves, and their effect on interconnected systems like food supply chains; and also “mission-critical algorithmic problems such as search and path planning operations for extreme anomalies,” he explains.

VBFF impact

Named for Vannevar Bush PhD 1916, an influential inventor, engineer, former professor, and dean of the School of Engineering at MIT, the highly competitive fellowship, formerly known as the National Security Science and Engineering Faculty Fellowship, aims to advance transformative, university-based fundamental research. Bush served as the director of the U.S. Office of Scientific Research and Development, and organized and led American science and technology during World War II.

“The outcomes of VBFF-funded research have transformed entire disciplines, birthed novel fields, and challenged established theories and perspectives,” said Nair. “By contributing their insights to DoD leadership and engaging with the broader national security community, they enrich collective understanding and help the United States leap ahead in global technology competition.”

Four MIT faculty named 2024 HHMI Investigators

Anne Trafton |

The Howard Hughes Medical Institute (HHMI) today announced its 2024 investigators, four of whom hail from the School of Science at MIT: Steven Flavell, Mary Gehring, Mehrad Jazayeri, and Gene-Wei Li.

Four others with MIT ties were also honored: Jonathan Abraham, graduate of the Harvard/MIT MD-PhD Program; Dmitriy Aronov PhD ’10; Vijay Sankaran, graduate of the Harvard/MIT MD-PhD Program; and Steven McCarroll, institute member of the Broad Institute of MIT and Harvard.

Every three years, HHMI selects roughly two dozen new investigators who have significantly impacted their chosen disciplines to receive a substantial and completely discretionary grant. This funding can be reviewed and renewed indefinitely. The award, which totals roughly $11 million per investigator over the next seven years, enables scientists to continue working at their current institution, paying their full salary while providing financial support for researchers to be flexible enough to go wherever their scientific inquiries take them.

Of the almost 1,000 applicants this year, 26 investigators were selected for their ability to push the boundaries of science and for their efforts to create highly inclusive and collaborative research environments.

“When scientists create environments in which others can thrive, we all benefit,” says HHMI president Erin O’Shea. “These newest HHMI Investigators are extraordinary, not only because of their outstanding research endeavors but also because they mentor and empower the next generation of scientists to work alongside them at the cutting edge.”

Steven Flavell

Steven Flavell, associate professor of brain and cognitive sciences and investigator in the Picower Institute for Learning and Memory, seeks to uncover the neural mechanisms that generate the internal states of the brain, for example, different motivational and arousal states. Working in the model organism, the C. elegans worm, the lab has used genetic, systems, and computational approaches to relate neural activity across the brain to precise features of the animal’s behavior. In addition, they have mapped out the anatomical and functional organization of the serotonin system, mapping out how it modulates the internal state of C. elegans. As a newly named HHMI Investigator, Flavell will pursue research that he hopes will build a foundational understanding of how internal states arise and influence behavior in nervous systems in general. The work will employ brain-wide neural recordings, computational modeling, expansive research on neuromodulatory system organization, and studies of how the synaptic wiring of the nervous system constrains an animal’s ability to generate different internal states.

“I think that it should be possible to define the basis of internal states in C. elegans in concrete terms,” Flavell says. “If we can build a thread of understanding from the molecular architecture of neuromodulatory systems, to changes in brain-wide activity, to state-dependent changes in behavior, then I think we’ll be in a much better place as a field to think about the basis of brain states in more complex animals.”

Mary Gehring

Mary Gehring, professor of biology and core member and David Baltimore Chair in Biomedical Research at the Whitehead Institute for Biomedical Research, studies how plant epigenetics modulates plant growth and development, with a long-term goal of uncovering the essential genetic and epigenetic elements of plant seed biology. Ultimately, the Gehring Lab’s work provides the scientific foundations for engineering alternative modes of seed development and improving plant resiliency at a time when worldwide agriculture is in a uniquely precarious position due to climate changes.

The Gehring Lab uses genetic, genomic, computational, synthetic, and evolutionary approaches to explore heritable traits by investigating repetitive sequences, DNA methylation, and chromatin structure. The lab primarily uses the model plant A. thaliana, a member of the mustard family and the first plant to have its genome sequenced.

“I’m pleased that HHMI has been expanding its support for plant biology, and gratified that our lab will benefit from its generous support,” Gehring says. “The appointment gives us the freedom to step back, take a fresh look at the scientific opportunities before us, and pursue the ones that most interest us. And that’s a very exciting prospect.”

Mehrdad Jazayeri

Mehrdad Jazayeri, a professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research, studies how physiological processes in the brain give rise to the abilities of the mind. Work in the Jazayeri Lab brings together ideas from cognitive science, neuroscience, and machine learning with experimental data in humans, animals, and computer models to develop a computational understanding of how the brain creates internal representations, or models, of the external world.

Before coming to MIT in 2013, Jazayeri received his BS in electrical engineering, majoring in telecommunications, from Sharif University of Technology in Tehran, Iran. He completed his MS in physiology at the University of Toronto and his PhD in neuroscience at New York University.

With his appointment to HHMI, Jazayeri plans to explore how the brain enables rapid learning and flexible behavior — central aspects of intelligence that have been difficult to study using traditional neuroscience approaches.

“This is a recognition of my lab’s past accomplishments and the promise of the exciting research we want to embark on,” he says. “I am looking forward to engaging with this wonderful community and making new friends and colleagues while we elevate our science to the next level.”

Gene-Wei Li

Gene-Wei Li, associate professor of biology, has been working on quantifying the amount of proteins cells produce and how protein synthesis is orchestrated within the cell since opening his lab at MIT in 2015.

Li, whose background is in physics, credits the lab’s findings to the skills and communication among his research team, allowing them to explore the unexpected questions that arise in the lab.

For example, two of his graduate student researchers found that the coordination between transcription and translation fundamentally differs between the model organisms E. coli and B. subtilis. In B. subtilis, the ribosome lags far behind RNA polymerase, a process the lab termed “runaway transcription.” The discovery revealed that this kind of uncoupling between transcription and translation is widespread across many species of bacteria, a study that contradicted the long-standing dogma of molecular biology that the machinery of protein synthesis and RNA polymerase work side-by-side in all bacteria.

The support from HHMI enables Li and his team the flexibility to pursue the basic research that leads to discoveries at their discretion.

“Having this award allows us to be bold and to do things at a scale that wasn’t possible before,” Li says. “The discovery of runaway transcription is a great example. We didn’t have a traditional grant for that.”

License plates of MIT

by Maia Weinstock |

What does your license plate say about you?

In the United States, more than 9 million vehicles carry personalized “vanity” license plates, in which preferred words, digits, or phrases replace an otherwise random assignment of letters and numbers to identify a vehicle. While each state and the District of Columbia maintains its own rules about appropriate selections, creativity reigns when choosing a unique vanity plate. What’s more, the stories behind them can be just as fascinating as the people who use them.

It might not come as a surprise to learn that quite a few MIT community members have participated in such vehicular whimsy. Read on to meet some of them and learn about the nerdy, artsy, techy, and MIT-related plates that color their rides.

A little piece of tech heaven

One of the most recognized vehicles around campus is Samuel Klein’s 1998 Honda Civic. More than just the holder of a vanity plate, it’s an art car — a vehicle that’s been custom-designed as a way to express an artistic idea or theme. Klein’s Civic is covered with hundreds of 5.5-inch floppy disks in various colors, and it sports disks, computer keys, and other techy paraphernalia on the interior. With its double-entendre vanity plate, “DSKDRV” (“disk drive”), the art car initially came into being on the West Coast.

Klein, a longtime affiliate of the MIT Media Lab, MIT Press, and MIT Libraries, first heard about the car from fellow Wikimedian and current MIT librarian Phoebe Ayers. An artistic friend of Ayers’, Lara Wiegand, had designed and decorated the car in Seattle but wanted to find a new owner. Klein was intrigued and decided to fly west to check the Civic out.

“I went out there, spent a whole afternoon seeing how she maintained the car and talking about engineering and mechanisms and the logistics of what’s good and bad,” Klein says. “It had already gone through many iterations.”

Klein quickly decided he was up to the task of becoming the new owner. As he drove the car home across the country, it “got a wide range of really cool responses across different parts of the U.S.”

Back in Massachusetts, Klein made a few adjustments: “We painted the hubcaps, we added racing stripes, we added a new generation of laser-etched glass circuits and, you know, I had my own collection of antiquated technology disks that seemed to fit.”

The vanity plate also required a makeover. In Washington state it was “DISKDRV,” but, Klein says, “we had to shave the license plate a bit because there are fewer letters in Massachusetts.”

Today, the car has about 250,000 miles and an Instagram account. “The biggest challenge is just the disks have to be resurfaced, like a lizard, every few years,” says Klein, whose partner, an MIT research scientist, often parks it around campus. “There’s a small collection of love letters for the car. People leave the car notes. It’s very sweet.”

Marking his place in STEM history

Omar Abudayyeh ’12, PhD ’18, a recent McGovern Fellow at the McGovern Institute for Brain Research at MIT who is now an assistant professor at Harvard Medical School, shares an equally riveting story about his vanity plate, “CRISPR,” which adorns his sport utility vehicle.

The plate refers to the genome-editing technique that has revolutionized biological and medical research by enabling rapid changes to genetic material. As an MIT graduate student in the lab of Professor Feng Zhang, a pioneering contributor to CRISPR technologies, Abudayyeh was highly involved in early CRISPR development for DNA and RNA editing. In fact, he and Jonathan Gootenberg ’13, another recent McGovern Fellow and assistant professor at Harvard Medical School who works closely with Abudayyeh, discovered many novel CRISPR enzymes, such as Cas12 and Cas13, and applied these technologies for both gene therapy and CRISPR diagnostics.

So how did Abudayyeh score his vanity plate? It was all due to his attendance at a genome-editing conference in 2022, where another early-stage CRISPR researcher, Samuel Sternberg, showed up in a car with New York “CRISPR” plates. “It became quite a source of discussion at the conference, and at one of the breaks, Sam and his labmates egged us on to get the Massachusetts license plate,” Abudayyeh explains. “I insisted that it must be taken, but I applied anyway, paying the 70 dollars and then receiving a message that I would get a letter eight to 12 weeks later about whether the plate was available or not. I then returned to Boston and forgot about it until a couple months later when, to my surprise, the plate arrived in the mail.”

While Abudayyeh continues his affiliation with the McGovern Institute, he and Gootenberg recently set up a lab at Harvard Medical School as new faculty members. “We have continued to discover new enzymes, such as Cas7-11, that enable new frontiers, such as programmable proteases for RNA sensing and novel therapeutics, and we’ve applied CRISPR technologies for new efforts in gene editing and aging research,” Abudayyeh notes.

As for his license plate, he says, “I’ve seen instances of people posting about it on Twitter or asking about it in Slack channels. A number of times, people have stopped me to say they read the Walter Isaacson book on CRISPR, asking how I was related to it. I would then explain my story — and describe how I’m actually in the book, in the chapters on CRISPR diagnostics.”

Displaying MIT roots, nerd pride

For some, a connection to MIT is all the reason they need to register a vanity plate — or three. Jeffrey Chambers SM ’06, PhD ’14, a graduate of the Department of Aeronautics and Astronautics, shares that he drives with a Virginia license plate touting his “PHD MIT.” Professor of biology Anthony Sinskey ScD ’67 owns several vehicles sporting vanity plates that honor Course 20, which is today the Department of Biological Engineering but has previously been known by Food Technology, Nutrition and Food Science, and Applied Biological Sciences. Sinskey says he has both “MIT 20” and “MIT XX” plates in Massachusetts and New Hampshire.

At least two MIT couples have had dual vanity plates. Says Laura Kiessling ’83, professor of chemistry: “My plate is ‘SLEX.’ This is the abbreviation for a carbohydrate called sialyl Lewis X. It has many roles, including a role in fertilization (sperm-egg binding). It tends to elicit many different reactions from people asking me what it means. Unless they are scientists, I say that my husband [Ron Raines ’80, professor of biology] gave it to me as an inside joke. My husband’s license plate is ‘PROTEIN.’”

Professor of the practice emerita Marcia Bartusiak of MIT Comparative Media Studies/Writing and her husband, Stephen Lowe PhD ’88, previously shared a pair of related license plates. When the couple lived in Virginia, Lowe working as a mathematician on the structure of spiral galaxies and Bartusiak a young science writer focused on astronomy, they had “SPIRAL” and “GALAXY” plates. Now retired in Massachusetts, while they no longer have registered vanity plates, they’ve named their current vehicles “Redshift” and “Blueshift.”

Still other community members have plates that make a nod to their hobbies — such as Department of Earth, Atmospheric and Planetary Sciences and AeroAstro Professor Sara Seager’s “ICANOE” — or else playfully connect with fellow drivers. Julianna Mullen, communications director in the Plasma Science and Fusion Center, says of her “OMGWHY” plate: “It’s just an existential reminder of the importance of scientific inquiry, especially in traffic when someone cuts you off so they can get exactly two car lengths ahead. Oh my God, why did they do it?”

Are you an MIT affiliate with a unique vanity plate? We’d love to see it!

Polina Anikeeva named head of the Department of Materials Science and Engineering

by Mary Beth Gallagher | School of Engineering |

Polina Anikeeva PhD ’09, the Matoula S. Salapatas Professor at MIT, has been named the new head of MIT’s Department of Materials Science and Engineering (DMSE), effective July 1.

“Professor Anikeeva’s passion and dedication as both a researcher and educator, as well as her impressive network of connections across the wider Institute, make her incredibly well suited to lead DMSE,” says Anantha Chandrakasan, chief innovation and strategy officer, dean of engineering, and Vannevar Bush Professor of Electrical Engineering and Computer Science.

In addition to serving as a professor in DMSE, Anikeeva is a professor of brain and cognitive sciences, director of the K. Lisa Yang Brain-Body Center, a member of the McGovern Institute for Brain Research, and associate director of MIT’s Research Laboratory of Electronics.

Anikeeva leads the MIT Bioelectronics Group, which focuses on developing magnetic and optoelectronic tools to study neural communication in health and disease. Her team applies magnetic nanomaterials and fiber-based devices to reveal physiological processes underlying brain-organ communication, with particular focus on gut-brain circuits. Their goal is to develop minimally invasive treatments for a range of neurological, psychiatric, and metabolic conditions.

Anikeeva’s research sits at the intersection of materials chemistry, electronics, and neurobiology. By bridging these disciplines, Anikeeva and her team are deepening our understanding and treatment of complex neurological disorders. Her approach has led to the creation of optoelectronic and magnetic devices that can record neural activity and stimulate neurons during behavioral studies.

Throughout her career, Anikeeva has been recognized with numerous awards for her groundbreaking research. Her honors include receiving an NSF CAREER Award, DARPA Young Faculty Award, and the Pioneer Award from the NIH’s High-Risk, High-Reward Research Program. MIT Technology Review named her one of the 35 Innovators Under 35 and the Vilcek Foundation awarded her the Prize for Creative Promise in Biomedical Science.

Her impact extends beyond the laboratory and into the classroom, where her dedication to education has earned her the Junior Bose Teaching Award, the MacVicar Faculty Fellowship, and an MITx Prize for Teaching and Learning in MOOCs. Her entrepreneurial spirit was acknowledged with a $100,000 prize in the inaugural MIT Faculty Founders Initiative Prize Competition, recognizing her pioneering work in neuroprosthetics.

In 2023, Anikeeva co-founded Neurobionics Inc., which develops flexible fibers that can interface with the brain — opening new opportunities for sensing and therapeutics. The team has presented their technologies at MIT delta v Demo Day and won $50,000 worth of lab space at the LabCentral Ignite Golden Ticket pitch competition. Anikeeva serves as the company’s scientific advisor.

Anikeeva earned her bachelor’s degree in physics at St. Petersburg State Polytechnic University in Russia. She continued her education at MIT, where she received her PhD in materials science and engineering. Vladimir Bulović, director of MIT.nano and the Fariborz Maseeh Chair in Emerging Technology, served as Anikeeva’s doctoral advisor. After completing a postdoctoral fellowship at Stanford University, working on devices for optical stimulation and recording of neural activity, Anikeeva returned to MIT as a faculty member in 2011.

Anikeeva succeeds Caroline Ross, the Ford Professor of Engineering, who has served as interim department head since August 2023.

“Thanks to Professor Ross’s steadfast leadership, DMSE has continued to thrive during this period of transition. I’m incredibly grateful for her many contributions and long-standing commitment to strengthening the DMSE community,” adds Chandrakasan.

Study reveals how an anesthesia drug induces unconsciousness

Anne Trafton |

There are many drugs that anesthesiologists can use to induce unconsciousness in patients. Exactly how these drugs cause the brain to lose consciousness has been a longstanding question, but MIT neuroscientists have now answered that question for one commonly used anesthesia drug.

Using a novel technique for analyzing neuron activity, the researchers discovered that the drug propofol induces unconsciousness by disrupting the brain’s normal balance between stability and excitability. The drug causes brain activity to become increasingly unstable, until the brain loses consciousness.

“The brain has to operate on this knife’s edge between excitability and chaos.” – Earl K. Miller

“It’s got to be excitable enough for its neurons to influence one another, but if it gets too excitable, it spins off into chaos. Propofol seems to disrupt the mechanisms that keep the brain in that narrow operating range,” says Earl K. Miller, the Picower Professor of Neuroscience and a member of MIT’s Picower Institute for Learning and Memory.

The new findings, reported today in Neuron, could help researchers develop better tools for monitoring patients as they undergo general anesthesia.

Miller and Ila Fiete, a professor of brain and cognitive sciences, the director of the K. Lisa Yang Integrative Computational Neuroscience Center (ICoN), and a member of MIT’s McGovern Institute for Brain Research, are the senior authors of the new study. MIT graduate student Adam Eisen and MIT postdoc Leo Kozachkov are the lead authors of the paper.

Losing consciousness

Propofol is a drug that binds to GABA receptors in the brain, inhibiting neurons that have those receptors. Other anesthesia drugs act on different types of receptors, and the mechanism for how all of these drugs produce unconsciousness is not fully understood.

Miller, Fiete, and their students hypothesized that propofol, and possibly other anesthesia drugs, interfere with a brain state known as “dynamic stability.” In this state, neurons have enough excitability to respond to new input, but the brain is able to quickly regain control and prevent them from becoming overly excited.

Woman gestures with her hand in front of a glass wall with equations written on it.
Ila Fiete in her lab at the McGovern Institute. Photo: Steph Stevens

Previous studies of how anesthesia drugs affect this balance have found conflicting results: Some suggested that during anesthesia, the brain shifts toward becoming too stable and unresponsive, which leads to loss of consciousness. Others found that the brain becomes too excitable, leading to a chaotic state that results in unconsciousness.

Part of the reason for these conflicting results is that it has been difficult to accurately measure dynamic stability in the brain. Measuring dynamic stability as consciousness is lost would help researchers determine if unconsciousness results from too much stability or too little stability.

In this study, the researchers analyzed electrical recordings made in the brains of animals that received propofol over an hour-long period, during which they gradually lost consciousness. The recordings were made in four areas of the brain that are involved in vision, sound processing, spatial awareness, and executive function.

These recordings covered only a tiny fraction of the brain’s overall activity, so to overcome that, the researchers used a technique called delay embedding. This technique allows researchers to characterize dynamical systems from limited measurements by augmenting each measurement with measurements that were recorded previously.

Using this method, the researchers were able to quantify how the brain responds to sensory inputs, such as sounds, or to spontaneous perturbations of neural activity.

In the normal, awake state, neural activity spikes after any input, then returns to its baseline activity level. However, once propofol dosing began, the brain started taking longer to return to its baseline after these inputs, remaining in an overly excited state. This effect became more and more pronounced until the animals lost consciousness.

This suggests that propofol’s inhibition of neuron activity leads to escalating instability, which causes the brain to lose consciousness, the researchers say.

Better anesthesia control

To see if they could replicate this effect in a computational model, the researchers created a simple neural network. When they increased the inhibition of certain nodes in the network, as propofol does in the brain, network activity became destabilized, similar to the unstable activity the researchers saw in the brains of animals that received propofol.

“We looked at a simple circuit model of interconnected neurons, and when we turned up inhibition in that, we saw a destabilization. So, one of the things we’re suggesting is that an increase in inhibition can generate instability, and that is subsequently tied to loss of consciousness,” Eisen says.

As Fiete explains, “This paradoxical effect, in which boosting inhibition destabilizes the network rather than silencing or stabilizing it, occurs because of disinhibition. When propofol boosts the inhibitory drive, this drive inhibits other inhibitory neurons, and the result is an overall increase in brain activity.”

The researchers suspect that other anesthetic drugs, which act on different types of neurons and receptors, may converge on the same effect through different mechanisms — a possibility that they are now exploring.

If this turns out to be true, it could be helpful to the researchers’ ongoing efforts to develop ways to more precisely control the level of anesthesia that a patient is experiencing. These systems, which Miller is working on with Emery Brown, the Edward Hood Taplin Professor of Medical Engineering at MIT, work by measuring the brain’s dynamics and then adjusting drug dosages accordingly, in real-time.

“If you find common mechanisms at work across different anesthetics, you can make them all safer by tweaking a few knobs, instead of having to develop safety protocols for all the different anesthetics one at a time,” Miller says. “You don’t want a different system for every anesthetic they’re going to use in the operating room. You want one that’ll do it all.”

The researchers also plan to apply their technique for measuring dynamic stability to other brain states, including neuropsychiatric disorders.

“This method is pretty powerful, and I think it’s going to be very exciting to apply it to different brain states, different types of anesthetics, and also other neuropsychiatric conditions like depression and schizophrenia,” Fiete says.

The research was funded by the Office of Naval Research, the National Institute of Mental Health, the National Institute of Neurological Disorders and Stroke, the National Science Foundation Directorate for Computer and Information Science and Engineering, the Simons Center for the Social Brain, the Simons Collaboration on the Global Brain, the JPB Foundation, the McGovern Institute, and the Picower Institute.

A prosthesis driven by the nervous system helps people with amputation walk naturally

Anne Trafton |

State-of-the-art prosthetic limbs can help people with amputations achieve a natural walking gait, but they don’t give the user full neural control over the limb. Instead, they rely on robotic sensors and controllers that move the limb using predefined gait algorithms.

Using a new type of surgical intervention and neuroprosthetic interface, MIT researchers, in collaboration with colleagues from Brigham and Women’s Hospital, have shown that a natural walking gait is achievable using a prosthetic leg fully driven by the body’s own nervous system. The surgical amputation procedure reconnects muscles in the residual limb, which allows patients to receive “proprioceptive” feedback about where their prosthetic limb is in space.

In a study of seven patients who had this surgery, the MIT team found that they were able to walk faster, avoid obstacles, and climb stairs much more naturally than people with a traditional amputation.

“This is the first prosthetic study in history that shows a leg prosthesis under full neural modulation, where a biomimetic gait emerges. No one has been able to show this level of brain control that produces a natural gait, where the human’s nervous system is controlling the movement, not a robotic control algorithm,” says Hugh Herr, a professor of media arts and sciences, co-director of the K. Lisa Yang Center for Bionics at MIT, an associate member of MIT’s McGovern Institute for Brain Research, and the senior author of the new study.

Patients also experienced less pain and less muscle atrophy following this surgery, which is known as the agonist-antagonist myoneural interface (AMI). So far, about 60 patients around the world have received this type of surgery, which can also be done for people with arm amputations.

Hyungeun Song, a postdoc in MIT’s Media Lab, is the lead author of the paper, which appears today in Nature Medicine.

Sensory feedback

Most limb movement is controlled by pairs of muscles that take turns stretching and contracting. During a traditional below-the-knee amputation, the interactions of these paired muscles are disrupted. This makes it very difficult for the nervous system to sense the position of a muscle and how fast it’s contracting — sensory information that is critical for the brain to decide how to move the limb.

People with this kind of amputation may have trouble controlling their prosthetic limb because they can’t accurately sense where the limb is in space. Instead, they rely on robotic controllers built into the prosthetic limb. These limbs also include sensors that can detect and adjust to slopes and obstacles.

To try to help people achieve a natural gait under full nervous system control, Herr and his colleagues began developing the AMI surgery several years ago. Instead of severing natural agonist-antagonist muscle interactions, they connect the two ends of the muscles so that they still dynamically communicate with each other within the residual limb. This surgery can be done during a primary amputation, or the muscles can be reconnected after the initial amputation as part of a revision procedure.

“With the AMI amputation procedure, to the greatest extent possible, we attempt to connect native agonists to native antagonists in a physiological way so that after amputation, a person can move their full phantom limb with physiologic levels of proprioception and range of movement,” Herr says.

In a 2021 study, Herr’s lab found that patients who had this surgery were able to more precisely control the muscles of their amputated limb, and that those muscles produced electrical signals similar to those from their intact limb.

After those encouraging results, the researchers set out to explore whether those electrical signals could generate commands for a prosthetic limb and at the same time give the user feedback about the limb’s position in space. The person wearing the prosthetic limb could then use that proprioceptive feedback to volitionally adjust their gait as needed.

In the new Nature Medicine study, the MIT team found this sensory feedback did indeed translate into a smooth, near-natural ability to walk and navigate obstacles.

“Because of the AMI neuroprosthetic interface, we were able to boost that neural signaling, preserving as much as we could. This was able to restore a person’s neural capability to continuously and directly control the full gait, across different walking speeds, stairs, slopes, even going over obstacles,” Song says.

A natural gait

For this study, the researchers compared seven people who had the AMI surgery with seven who had traditional below-the-knee amputations. All of the subjects used the same type of bionic limb: a prosthesis with a powered ankle as well as electrodes that can sense electromyography (EMG) signals from the tibialis anterior the gastrocnemius muscles. These signals are fed into a robotic controller that helps the prosthesis calculate how much to bend the ankle, how much torque to apply, or how much power to deliver.

The researchers tested the subjects in several different situations: level-ground walking across a 10-meter pathway, walking up a slope, walking down a ramp, walking up and down stairs, and walking on a level surface while avoiding obstacles.

In all of these tasks, the people with the AMI neuroprosthetic interface were able to walk faster — at about the same rate as people without amputations — and navigate around obstacles more easily. They also showed more natural movements, such as pointing the toes of the prosthesis upward while going up stairs or stepping over an obstacle, and they were better able to coordinate the movements of their prosthetic limb and their intact limb. They were also able to push off the ground with the same amount of force as someone without an amputation.

“With the AMI cohort, we saw natural biomimetic behaviors emerge,” Herr says. “The cohort that didn’t have the AMI, they were able to walk, but the prosthetic movements weren’t natural, and their movements were generally slower.”

These natural behaviors emerged even though the amount of sensory feedback provided by the AMI was less than 20 percent of what would normally be received in people without an amputation.

“One of the main findings here is that a small increase in neural feedback from your amputated limb can restore significant bionic neural controllability, to a point where you allow people to directly neurally control the speed of walking, adapt to different terrain, and avoid obstacles,” Song says.

“This work represents yet another step in us demonstrating what is possible in terms of restoring function in patients who suffer from severe limb injury. It is through collaborative efforts such as this that we are able to make transformational progress in patient care,” says Matthew Carty, a surgeon at Brigham and Women’s Hospital and associate professor at Harvard Medical School, who is also an author of the paper.

Enabling neural control by the person using the limb is a step toward Herr’s lab’s goal of “rebuilding human bodies,” rather than having people rely on ever more sophisticated robotic controllers and sensors — tools that are powerful but do not feel like part of the user’s body.

“The problem with that long-term approach is that the user would never feel embodied with their prosthesis. They would never view the prosthesis as part of their body, part of self,” Herr says. “The approach we’re taking is trying to comprehensively connect the brain of the human to the electromechanics.”

The research was funded by the MIT K. Lisa Yang Center for Bionics and the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

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

by Lauren Rebecca Thacker | MIT Open Learning |

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.”

Just thinking about a location activates mental maps in the brain

Anne Trafton |

As you travel your usual route to work or the grocery store, your brain engages cognitive maps stored in your hippocampus and entorhinal cortex. These maps store information about paths you have taken and locations you have been to before, so you can navigate whenever you go there.

New research from MIT has found that such mental maps also are created and activated when you merely think about sequences of experiences, in the absence of any physical movement or sensory input. In an animal study, the researchers found that the entorhinal cortex harbors a cognitive map of what animals experience while they use a joystick to browse through a sequence of images. These cognitive maps are then activated when thinking about these sequences, even when the images are not visible.

This is the first study to show the cellular basis of mental simulation and imagination in a nonspatial domain through activation of a cognitive map in the entorhinal cortex.

“These cognitive maps are being recruited to perform mental navigation, without any sensory input or motor output. We are able to see a signature of this map presenting itself as the animal is going through these experiences mentally,” says Mehrdad Jazayeri, an associate professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

McGovern Institute Research Scientist Sujaya Neupane is the lead author of the paper, which appears today in Nature. Ila Fiete, a professor of brain and cognitive sciences at MIT, a member of MIT’s McGovern Institute for Brain Research, and director of the K. Lisa Yang Integrative Computational Neuroscience Center, is also an author of the paper.

Mental maps

A great deal of work in animal models and humans has shown that representations of physical locations are stored in the hippocampus, a small seahorse-shaped structure, and the nearby entorhinal cortex. These representations are activated whenever an animal moves through a space that it has been in before, just before it traverses the space, or when it is asleep.

“Most prior studies have focused on how these areas reflect the structures and the details of the environment as an animal moves physically through space,” Jazayeri says. “When an animal moves in a room, its sensory experiences are nicely encoded by the activity of neurons in the hippocampus and entorhinal cortex.”

In the new study, Jazayeri and his colleagues wanted to explore whether these cognitive maps are also built and then used during purely mental run-throughs or imagining of movement through nonspatial domains.

To explore that possibility, the researchers trained animals to use a joystick to trace a path through a sequence of images (“landmarks”) spaced at regular temporal intervals. During the training, the animals were shown only a subset of pairs of images but not all the pairs. Once the animals had learned to navigate through the training pairs, the researchers tested if animals could handle the new pairs they had never seen before.

One possibility is that animals do not learn a cognitive map of the sequence, and instead solve the task using a memorization strategy. If so, they would be expected to struggle with the new pairs. Instead, if the animals were to rely on a cognitive map, they should be able to generalize their knowledge to the new pairs.

“The results were unequivocal,” Jazayeri says. “Animals were able to mentally navigate between the new pairs of images from the very first time they were tested. This finding provided strong behavioral evidence for the presence of a cognitive map. But how does the brain establish such a map?”

To address this question, the researchers recorded from single neurons in the entorhinal cortex as the animals performed this task. Neural responses had a striking feature: As the animals used the joystick to navigate between two landmarks, neurons featured distinctive bumps of activity associated with the mental representation of the intervening landmarks.

“The brain goes through these bumps of activity at the expected time when the intervening images would have passed by the animal’s eyes, which they never did,” Jazayeri says. “And the timing between these bumps, critically, was exactly the timing that the animal would have expected to reach each of those, which in this case was 0.65 seconds.”

The researchers also showed that the speed of the mental simulation was related to the animals’ performance on the task: When they were a little late or early in completing the task, their brain activity showed a corresponding change in timing. The researchers also found evidence that the mental representations in the entorhinal cortex don’t encode specific visual features of the images, but rather the ordinal arrangement of the landmarks.

A model of learning

To further explore how these cognitive maps may work, the researchers built a computational model to mimic the brain activity that they found and demonstrate how it could be generated. They used a type of model known as a continuous attractor model, which was originally developed to model how the entorhinal cortex tracks an animal’s position as it moves, based on sensory input.

The researchers customized the model by adding a component that was able to learn the activity patterns generated by sensory input. This model was then able to learn to use those patterns to reconstruct those experiences later, when there was no sensory input.

“The key element that we needed to add is that this system has the capacity to learn bidirectionally by communicating with sensory inputs. Through the associational learning that the model goes through, it will actually recreate those sensory experiences,” Jazayeri says.

The researchers now plan to investigate what happens in the brain if the landmarks are not evenly spaced, or if they’re arranged in a ring. They also hope to record brain activity in the hippocampus and entorhinal cortex as the animals first learn to perform the navigation task.

“Seeing the memory of the structure become crystallized in the mind, and how that leads to the neural activity that emerges, is a really valuable way of asking how learning happens,” Jazayeri says.

The research was funded by the Natural Sciences and Engineering Research Council of Canada, the Québec Research Funds, the National Institutes of Health, and the Paul and Lilah Newton Brain Science Award.

Nancy Kanwisher, Robert Langer, and Sara Seager named Kavli Prize Laureates

Anne Trafton |

MIT faculty members Nancy Kanwisher, Robert Langer, and Sara Seager are among eight researchers worldwide to receive this year’s Kavli Prizes.

A partnership among the Norwegian Academy of Science and Letters, the Norwegian Ministry of Education and Research, and the Kavli Foundation, the Kavli Prizes are awarded every two years to “honor scientists for breakthroughs in astrophysics, nanoscience and neuroscience that transform our understanding of the big, the small and the complex.” The laureates in each field will share $1 million.

Understanding recognition of faces

Nancy Kanwisher, the Walter A Rosenblith Professor of Brain and Cognitive Sciences and McGovern Institute for Brain Research investigator, has been awarded the 2024 Kavli Prize in Neuroscience with Doris Tsao, professor in the Department of Molecular and Cell Biology at the University of California at Berkeley, and Winrich Freiwald, the Denise A. and Eugene W. Chinery Professor at the Rockefeller University.

Kanwisher, Tsao, and Freiwald discovered a specialized system within the brain to recognize faces. Their discoveries have provided basic principles of neural organization and made the starting point for further research on how the processing of visual information is integrated with other cognitive functions.

Kanwisher was the first to prove that a specific area in the human neocortex is dedicated to recognizing faces, now called the fusiform face area. Using functional magnetic resonance imaging, 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.

Integrating nanomaterials for biomedical advances

Robert Langer, the David H. Koch Institute Professor, has been awarded the 2024 Kavli Prize in Nanoscience with Paul Alivisatos, president of the University of Chicago and John D. MacArthur Distinguished Service Professor in the Department of Chemistry, and Chad Mirkin, professor of chemistry at Northwestern University.

Langer, Alivisatos, and Mirkin each revolutionized the field of nanomedicine by demonstrating how engineering at the nano scale can advance biomedical research and application. Their discoveries contributed foundationally to the development of therapeutics, vaccines, bioimaging, and diagnostics.

Langer was the first to develop nanoengineered materials that enabled the controlled release, or regular flow, of drug molecules. This capability has had an immense impact for the treatment of a range of diseases, such as aggressive brain cancer, prostate cancer, and schizophrenia. His work also showed that tiny particles, containing protein antigens, can be used in vaccination, and was instrumental in the development of the delivery of messenger RNA vaccines.

Searching for life beyond Earth

Sara Seager, the Class of 1941 Professor of Planetary Sciences in the Department of Earth, Atmospheric and Planetary Sciences and a professor in the departments of Physics and of Aeronautics and Astronautics, has been awarded the 2024 Kavli Prize in Astrophysics along with David Charbonneau, the Fred Kavli Professor of Astrophysics at Harvard University.

Seager and Charbonneau are recognized for discoveries of exoplanets and the characterization of their atmospheres. They pioneered methods for the detection of atomic species in planetary atmospheres and the measurement of their thermal infrared emission, setting the stage for finding the molecular fingerprints of atmospheres around both giant and rocky planets. Their contributions have been key to the enormous progress seen in the last 20 years in the exploration of myriad exoplanets.

Kanwisher, Langer, and Seager bring the number of all-time MIT faculty recipients of the Kavli Prize to eight. Prior winners include Rainer Weiss in astrophysics (2016), Alan Guth in astrophysics (2014), Mildred Dresselhaus in nanoscience (2012), Ann Graybiel in neuroscience (2012), and Jane Luu in astrophysics (2012).