Research Area: Cellular & Molecular Neuroscience

​synapses, vesicles, electrophysiology, protein complexes, signaling, small molecules, disease-linked genes, dendrites, cell death, brain disorders, neurodevelopment

Ten years of bigger samples, better views

by Jennifer Michalowski |

Nearly 150 years ago, scientists began to imagine how information might flow through the brain based on the shapes of neurons they had seen under the microscopes of the time. With today’s imaging technologies, scientists can zoom in much further, seeing the tiny synapses through which neurons communicate with one another and even the molecules the cells use to relay their messages. These inside views can spark new ideas about how healthy brains work and reveal important changes that contribute to disease.

McGovern Institute Investigator Edward Boyden. Photo: Justin Knight

This sharper view of biology is not just about the advances that have made microscopes more powerful than ever before. Using methodology developed in the lab of McGovern investigator Edward Boyden, researchers around the world are imaging samples that have been swollen to as much as 20 times their original size so their finest features can be seen more clearly.

“It’s a very different way to do microscopy,” says Boyden, who is also a Howard Hughes Medical Institute investigator and a member of the Yang Tan Collective at MIT. “In contrast to the last 300 years of bioimaging, where you use a lens to magnify an image of light from an object, we physically magnify objects themselves.” Once a tissue is expanded, Boyden says, researchers can see more even with widely available, conventional microscopy hardware.

Boyden’s team introduced this approach, which they named expansion microscopy (ExM), in 2015. Since then, they have been refining the method and adding to its capabilities, while researchers at MIT and beyond deploy it to learn about life on the smallest of scales.

“It’s spreading very rapidly throughout biology and medicine,” Boyden says. “It’s being applied to kidney disease, the fruit fly brain, plant seeds, the microbiome, Alzheimer’s disease, viruses, and more.”

Origins of ExM 

To develop expansion microscopy, Boyden and his team turned to hydrogels: a material with remarkable water-absorbing properties that had already been put to practical use: it’s layered inside disposable diapers to keep babies dry. Boyden’s lab hypothesized that hydrogels could retain their structure while they absorbed hundreds of times their original weight in water, expanding the space between their chemical components as they swell.

After some experimentation, Boyden’s team settled on four key steps to enlarging tissue samples for better imaging. First, the tissue must be infused with a hydrogel. Components of the tissue, biomolecules, are anchored to the gel’s web-like matrix, linking them directly to the molecules that make up the gel. Then the tissue is chemically softened and water is added. As the hydrogel absorbs the water, it swells and the tissue expands, growing evenly so the relative positions of its components are preserved.

Boyden and graduate students Fei Chen and Paul Tillberg’s first report on expansion microscopy was published in the journal Science in 2015. In it, the team demonstrated that by spreading apart molecules that had been crowded inside cells, features that would have blurred together under a standard light microscope became separate and distinct. Light microscopes can discriminate between objects that are separated by about 300 nanometers—a limit imposed by the laws of physics. With expansion microscopy, Boyden’s group reported an effective resolution of about 70 nanometers, for a four-fold expansion.

Boyden says this is a level of clarity that biologists need. “Biology is fundamentally, in the end, a nanoscale science,” he says. “Biomolecules are nanoscale, and the interactions between biomolecules are over nanoscale distances. Many of the most important problems in biology and medicine involve nanoscale questions.” Several kinds of sophisticated microscopes, each with their own advantages and disadvantages, can bring this kind of detail to light. But those methods are costly and require specialized skills, making them inaccessible for most researchers. “Expansion microscopy democratizes nanoimaging,” Boyden says. “Now anybody can go look at the building blocks of life and how they relate to each other.”

Empowering scientists

Since Boyden’s team introduced expansion microscopy in 2015, research groups around the world have published hundreds of papers reporting on discoveries they have made using expansion microscopy. For neuroscientists, the technique has lit up the intricacies of elaborate neural circuits, exposed how particular proteins organize themselves at and across synapses to facilitate communication between neurons, and uncovered changes associated with aging and disease.

It has been equally empowering for studies beyond the brain. Sabrina Absalon uses expansion microscopy every week in her lab at Indiana University School of Medicine to study the malaria parasite, a single-celled organism packed with specialized structures that enable it to infect and live inside its hosts. The parasite is so small, most of those structures can’t be seen with ordinary light microscopy. “So as a cell biologist, I’m losing the biggest tool to infer protein function, organelle architecture, morphology, linked to function, and all those things–which is my eye,” she says. With expansion, she can not only see the organelles inside a malaria parasite, she can watch them assemble and follow what happens to them when the parasite divides. Understanding those processes, she says, could help drug developers find new ways to interfere with the parasite’s life cycle.

Longitudinally opened mosquito midguts prepared using MoTissU-ExM. Image: Sabrina Absalon

Absalon adds that the accessibility of expansion microscopy is particularly important in the field of parasitology, where a lot of research is happening in parts of the world where resources are limited. Workshops and training programs in Africa, South America, and Asia are ensuring the technology reaches scientists whose communities are directly impacted by malaria and other parasites. “Now they can get super-resolution imaging without very fancy equipment,” Absalon says.

Always Improving

Since 2015, Boyden’s interdisciplinary lab group has found a variety of creative ways to improve expansion microscopy and use it in new ways. Their standard technique today enables better labeling, bigger expansion factors, and higher resolution imaging. Cellular features less than 20 nanometers from one another can now be separated enough to appear distinct under a light microscope.

They’ve also adapted their protocols to work with a range of important sample types, from entire roundworms (popular among neuroscientists, developmental biologists, and other researchers) to clinical samples. In the latter regard, they’ve shown that expansion can help reveal subtle signs of disease, which could enable earlier or less costly diagnoses.

Originally, the group optimized its protocol for visualizing proteins inside cells, by labeling proteins of interest and anchoring them to the hydrogel prior to expansion. With a new way of processing samples, users can now restain their expanded samples with new labels for multiple rounds of imaging, so they can pinpoint the positions of dozens of different proteins in the same tissue. That means researchers can visualize how molecules are organized with respect to one another and how they might interact, or survey large sets of proteins to see, for example, what changes with disease.

Synaptic proteins and their associations to neuronal processes in the mouse primary somatosensory cortex imaged using expansion microscopy. Image: Boyden lab

But better views of proteins were just the beginning for expansion microscopy. “We want to see everything,” Boyden says. “We’d love to see every biomolecule there is, with precision down to atomic scale.” They’re not there yet—but with new probes and modified procedures, it’s now possible to see not just proteins, but also RNA and lipids in expanded tissue samples.

Labeling lipids, including those that form the membranes surrounding cells, means researchers can now see clear outlines of cells in expanded tissues. With the enhanced resolution afforded by expansion, even the slender projections of neurons can be traced through an image. Typically, researchers have relied on electron microscopy, which generates exquisitely detailed pictures but requires expensive equipment, to map the brain’s circuitry. “Now you can get images that look a lot like electron microscopy images, but on regular old light microscopes—the kind that everybody has access to,” Boyden says.

Boyden says expansion can be powerful in combination with other cutting-edge tools. When expanded samples are used with an ultra-fast imaging method developed by Eric Betzig, an HHMI investigator at the University of California, Berkeley, called lattice light-sheet microscopy, the entire brain of a fruit fly can be imaged at high resolution in just a few days. (See HHMI video below).

And when RNA molecules are anchored within a hydrogel network and then sequenced in place, scientists can see exactly where inside cells the instructions for building specific proteins are positioned, which Boyden’s team demonstrated in a collaboration with Harvard University geneticist George Church and then-MIT-professor Aviv Regev. “Expansion basically upgrades many other technologies’ resolutions,” Boyden says. “You’re doing mass-spec imaging, X-ray imaging, or Raman imaging? Expansion just improved your instrument.”

Expanding Possibilities

Ten years past the first demonstration of expansion microscopy’s power, Boyden and his team are committed to continuing to make expansion microscopy more powerful. “We want to optimize it for different kinds of problems, and making technologies faster, better, and cheaper is always important,” he says. But the future of expansion microscopy will be propelled by innovators outside the Boyden lab, too. “Expansion is not only easy to do, it’s easy to modify—so lots of other people are improving expansion in collaboration with us, or even on their own,” Boyden says.

Boyden points to a group led by Silvio Rizzoli at the University Medical Center Göttingen in Germany that, collaborating with Boyden, has adapted the expansion protocol to discern the physical shapes of proteins. At the Korea Advanced Institute of Science and Technology, researchers led by Jae-Byum Chang, a former postdoctoral researcher in Boyden’s group, have worked out how to expand entire bodies of mouse embryos and young zebrafish, collaborating with Boyden to set the stage for examining developmental processes and long-distance neural connections with a new level of detail. And mapping connections within the brain’s dense neural circuits could become easier with light-microscopy based connectomics, an approach developed by Johann Danzl and colleagues at the Institute of Science and Technology in Austria that takes advantage of both the high resolution and molecular information that expansion microscopy can reveal.

“The beauty of expansion is that it lets you see a biological system down to its smallest building blocks,” Boyden says.

His team is intent on pushing the method to its physical limits, and anticipates new opportunities for discovery as they do. “If you can map the brain or any biological system at the level of individual molecules, you might be able to see how they all work together as a network—how life really operates,” he says.

Seeing more in expansion microscopy

by Jennifer Michalowski |

In biology, seeing can lead to understanding, and researchers in Edward Boyden’s lab at MIT’s McGovern Institute are committed to bringing life into sharper focus. With a pair of new methods, they are expanding the capabilities of expansion microscopy—a high-resolution imaging technique the group introduced in 2015—so researchers everywhere can see more when they look at cells and tissues under a light microscope.

McGovern Institute Investigator Edward Boyden. Photo: Justin Knight

“We want to see everything, so we’re always trying to improve it,” says Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT.  “A snapshot of all life, down to its fundamental building blocks, is really the goal.” Boyden is also a Howard Hughes Medical Institute investigator and a member of the Yang Tan Collective at MIT.

With new ways of staining their samples and processing images, users of expansion microscopy can now see vivid outlines of the shapes of cells in their images and pinpoint the locations of many different proteins inside a single tissue sample with resolution that far exceeds that of conventional light microscopy. These advances, both reported in the journal Nature Communications, enable new ways of tracing the slender projections of neurons and visualizing spatial relationships between molecules that contribute to health and disease.

Expansion microscopy uses a water-absorbing hydrogel to physically expand biological tissues. After a tissue sample has been permeated by the hydrogel, it is hydrated. The hydrogel swells as it absorbs water, preserving the relative locations of molecules in the tissue as it gently pulls them away from one another. As a result, crowded cellular components appear separate and distinct when the expanded tissue is viewed under a light microscope. The approach, which can be performed using standard laboratory equipment, has made super-resolution imaging accessible to most research teams.

Since first developing expansion microscopy, Boyden and his team have continued to enhance the method—increasing its resolution, simplifying the procedure, devising new features, and integrating it with other tools.

Visualizing cell membranes

One of the team’s latest advances is a method called ultrastructural membrane expansion microscopy (umExM), which they described in the February 12 issue of Nature Communications. With it, biologists can use expansion microscopy to visualize the thin membranes that form the boundaries of cells and enclose the organelles inside them. These membranes, built mostly of molecules called lipids, have been notoriously difficult to densely label in intact tissues for imaging with light microscopy. Now, researchers can use umExM to study cellular ultrastructure and organization within tissues.

Tay Shin, a former graduate student in Boyden’s lab and a J. Douglas Tan Fellow in the Tan-Yang Center for Autism Research at MIT, led the development of umExM. “Our goal was very simple at first: Let’s label membranes in intact tissue, much like how an electron microscope uses osmium tetroxide to label membranes to visualize the membranes in tissue,” he says. “It turns out that it’s extremely hard to achieve this.”

The team first needed to design a label that would make the membranes in tissue samples visible under a light microscope. “We almost had to start from scratch,” Shin says. “We really had to think about the fundamental characteristics of the probe that is going to label the plasma membrane, and then think about how to incorporate them into expansion microscopy.” That meant engineering a molecule that would associate with the lipids that make up the membrane and link it to both the hydrogel used to expand the tissue sample and a fluorescent molecule for visibility.

After optimizing the expansion microscopy protocol for membrane visualization and extensively testing and improving potential probes, Shin found success one late night in the lab. He placed an expanded tissue sample on a microscope and saw sharp outlines of cells.

Traceability of umExM. 3D rendering of 20 manually traced and reconstructed myelinated axons in the corpus callosum. Image: Ed Boyden

Because of the high resolution enabled by expansion, the method allowed Boyden’s team to identify even the tiny dendrites that protrude from neurons and clearly see the long extensions of their slender axons. That kind of clarity could help researchers follow individual neurons’ paths within the densely interconnected networks of the brain, the researchers say.

Boyden calls tracing these neural processes “a top priority of our time in brain science.” Such tracing has traditionally relied heavily on electron microscopy, which requires specialized skills and expensive equipment. Shin says that because expansion microscopy uses a standard light microscope, it is far more accessible to laboratories worldwide.

Shin and Boyden point out that users of expansion microscopy can learn even more about their samples when they pair the new ability to reveal lipid membranes with fluorescent labels that show where specific proteins are located. “That’s important, because proteins do a lot of the work of the cell, but you want to know where they are with respect to the cell’s structure,” Boyden says.

One sample, many proteins

To that end, researchers no longer have to choose just a few proteins to see when they use expansion microscopy. With a new method called multiplexed expansion revealing (multiExR), users can now label and see more than 20 different proteins in a single sample. Biologists can use the method to visualize sets of proteins, see how they are organized with respect to one another, and generate new hypotheses about how they might interact.

A key to the new method, reported November 9, 2024, in Nature Communications, is the ability to repeatedly link fluorescently labeled antibodies to specific proteins in an expanded tissue sample, image them, then strip these away and use a new set of antibodies to reveal a new set of proteins. Postdoctoral fellow Jinyoung Kang fine-tuned each step of this process, assuring tissue samples stayed intact and the labeled proteins produced bright signals in each round of imaging.

After capturing many images of a single sample, Boyden’s team faced another challenge: how to ensure those images were in perfect alignment so they could be overlaid with one another, producing a final picture that showed the precise positions of all of the proteins that had been labeled and visualized one by one.

Expansion microscopy lets biologists visualize some of cells’ tiniest features—but to find the same features over and over again during multiple rounds of imaging, Boyden’s team first needed to home in on a larger structure. “These fields of view are really tiny, and you’re trying to find this really tiny field of view in a gel that’s actually become quite large once you’ve expanded it,” explains Margaret Schroeder, a graduate student in Boyden’s lab who, with Kang, led the development of multiExR.

“Here’s one of the most famous receptors in all of neuroscience, hiding out in one of the most famous molecular hallmarks of pathology in neuroscience.” – Ed Boyden

To navigate to the right spot every time, the team decided to label the blood vessels that pass through each tissue sample and use these as a guide. To enable precise alignment, certain fine details also needed to consistently appear in every image; for this, the team labeled several structural proteins. With these reference points and customized imaging processing software, the team was able to integrate all of their images of a sample into one, revealing how proteins that had been visualized separately were arranged relative to one another.

The team used multiExR to look at amyloid plaques—the aberrant protein clusters that notoriously develop in brains affected by Alzheimer’s disease. “We could look inside those amyloid plaques and ask, what’s inside of them? And because we can stain for many different proteins, we could do a high throughput exploration,” Boyden says. The team chose 23 different proteins to view in their images. The approach revealed some surprises, such as the presence of certain neurotransmitter receptors (AMPARs). “Here’s one of the most famous receptors in all of neuroscience, and there it is, hiding out in one of the most famous molecular hallmarks of pathology in neuroscience,” says Boyden. It’s unclear what role, if any, the receptors play in Alzheimer’s disease—but the finding illustrates how the ability to see more inside cells can expose unexpected aspects of biology and raise new questions for research.

Funding for this work came from MIT, Lisa Yang and Y. Eva Tan, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, the US Army, Cancer Research UK, the New York Stem Cell Foundation, the National Institutes of Health, Lore McGovern, Good Ventures, Schmidt Futures. Samsung, MathWorks, the Collamore-Rogers Fellowship, the National Science Foundation, Alana Foundation USA, the Halis Family Foundation, Lester A. Gimpelson, Donald and Glenda Mattes, David B. Emmes, Thomas A. Stocky, Avni U. Shah, Kathleen Octavio, Good Ventures/Open Philanthropy, and the European Union’s Horizon 2020 program.

A cell protector collaborates with a killer

by Jennifer Michalowski |

From early development to old age, cell death is a part of life. Without enough of a critical type of cell death known as apoptosis, animals wind up with too many cells, which can set the stage for cancer or autoimmune disease. But careful control is essential, because when apoptosis eliminates the wrong cells, the effects can be just as dire, helping to drive many kinds of neurodegenerative disease.

Portrait of a scientist
McGovern Investigator Robert Horvitz poses for a photo in his laboratory. Photo: AP Images/Aynsley Floyd

By studying the microscopic roundworm Caenorhabditis elegans—which was honored with its fourth Nobel Prize last month—scientists at MIT’s McGovern Institute have begun to unravel a longstanding mystery about the factors that control apoptosis: how a protein capable of preventing programmed cell death can also promote it. Their study, led by McGovern Investigator Robert Horvitz and reported October 9, 2024, in the journal Science Advances, sheds light on the process of cell death in both health and disease.

“These findings, by graduate student Nolan Tucker and former graduate student, now MIT faculty colleague, Peter Reddien, have revealed that a protein interaction long thought to block apoptosis in C. elegans, likely instead has the opposite effect,” says Horvitz, who shared the 2002 Nobel Prize for discovering and characterizing the genes controlling cell death in C. elegans.

Mechanisms of cell death

Horvitz, Tucker, Reddien and colleagues have provided foundational insights in the field of apoptosis by using C. elegans to analyze the mechanisms that drive apoptosis as well as the mechanisms that determine how cells ensure apoptosis happens when and where it should. Unlike humans and other mammals, which depend on dozens of proteins to control apoptosis, these worms use just a few. And when things go awry, it’s easy to tell: When there’s not enough apoptosis, researchers can see that there are too many cells inside the worms’ translucent bodies. And when there’s too much, the worms lack certain biological functions or, in more extreme cases, can’t reproduce or die during embryonic development.

black and white microscopic image of worms
The nematode worm Caenorhabditis elegans has provided answers to many fundamental questions in biology. Image: Robert Horvitz

Work in the Horvitz lab defined the roles of many of the genes and proteins that control apoptosis in worms. These regulators proved to have counterparts in human cells, and for that reason studies of worms have helped reveal how human cells govern cell death and pointed toward potential targets for treating disease.

A protein’s dual role

Three of C. elegans’ primary regulators of apoptosis actively promote cell death, whereas just one, CED-9, reins in the apoptosis-promoting proteins to keep cells alive. As early as the 1990s, however, Horvitz and colleagues recognized that CED-9 was not exclusively a protector of cells. Their experiments indicated that the protector protein also plays a role in promoting cell death. But while researchers thought they knew how CED-9 protected against apoptosis, its pro-apoptotic role was more puzzling.

CED-9’s dual role means that mutations in the gene that encode it can impact apoptosis in multiple ways. Most ced-9 mutations interfere with the protein’s ability to protect against cell death and result in excess cell death. Conversely, mutations that abnormally activate ced-9 cause too little cell death, just like mutations that inactivate any of the three killer genes.

An atypical ced-9 mutation, identified by Reddien when he was a PhD student in Horvitz’s lab, hinted at how CED-9 promotes cell death. That mutation altered the part of the CED-9 protein that interacts with the protein CED-4, which is proapoptotic. Since the mutation specifically leads to a reduction in apoptosis, this suggested that CED-9 might need to interact with CED-4 to promote cell death.

The idea was particularly intriguing because researchers had long thought that CED-9’s interaction with CED-4 had exactly the opposite effect: In the canonical model, CED-9 anchors CED-4 to cells’ mitochondria, sequestering the CED-4 killer protein and preventing it from associating with and activating another key killer, the CED-3 protein —thereby preventing apoptosis.

To test the hypothesis that CED-9’s interactions with the killer CED-4 protein enhance apoptosis, the team needed more evidence. So graduate student Nolan Tucker used CRISPR gene editing tools to create more worms with mutations in CED-9, each one targeting a different spot in the CED-4-binding region. Then he examined the worms. “What I saw with this particular class of mutations was extra cells and viability,” he says—clear signs that the altered CED-9 was still protecting against cell death, but could no longer promote it. “Those observations strongly supported the hypothesis that the ability to bind CED-4 is needed for the pro-apoptotic function of CED-9,” Tucker explains. Their observations also suggested that, contrary to earlier thinking, CED-9 doesn’t need to bind with CED-4 to protect against apoptosis.

When he looked inside the cells of the mutant worms, Tucker found additional evidence that these mutations prevented CED-9’s ability to interact with CED-4. When both CED-9 and CED-4 are intact, CED-4 appears associated with cells’ mitochondria. But in the presence of these mutations, CED-4 was instead at the edge of the cell nucleus. CED-9’s ability to bind CED-4 to mitochondria appeared to be necessary to promote apoptosis, not to protect against it.

In wild-type worms CED-4 is localized to mitochondria. However, the introduction of CED-9-CED-4 binding mutations such as ced-4(n6703) or ced-9(n6704), causes CED-4 protein to localize to the outer edge of the nucleus. Image: Nolan Tucker, Robert Horvitz

Looking ahead

While the team’s findings begin to explain a long-unanswered question about one of the primary regulators of apoptosis, they raise new ones, as well. “I think that this main pathway of apoptosis has been seen by a lot of people as more or less settled science. Our findings should change that view,” Tucker says.

The researchers see important parallels between their findings from this study of worms and what’s known about cell death pathways in mammals. The mammalian counterpart to CED-9 is a protein called BCL-2, mutations in which can lead to cancer.  BCL-2, like CED-9, can both promote and protect against apoptosis. As with CED-9, the pro-apoptotic function of BCL-2 has been mysterious. In mammals, too, mitochondria play a key role in activating apoptosis. The Horvitz lab’s discovery opens opportunities to better understand how apoptosis is regulated not only in worms but also in humans, and how dysregulation of apoptosis in humans can lead to such disorders as cancer, autoimmune disease and neurodegeneration.

Brain pathways that control dopamine release may influence motor control

Anne Trafton |

Within the human brain, movement is coordinated by a brain region called the striatum, which sends instructions to motor neurons in the brain. Those instructions are conveyed by two pathways, one that initiates movement (“go”) and one that suppresses it (“no-go”).

In a new study, MIT researchers have discovered an additional two pathways that arise in the striatum and appear to modulate the effects of the go and no-go pathways. These newly discovered pathways connect to dopamine-producing neurons in the brain — one stimulates dopamine release and the other inhibits it.

By controlling the amount of dopamine in the brain via clusters of neurons known as striosomes, these pathways appear to modify the instructions given by the go and no-go pathways. They may be especially involved in influencing decisions that have a strong emotional component, the researchers say.

“Among all the regions of the striatum, the striosomes alone turned out to be able to project to the dopamine-containing neurons, which we think has something to do with motivation, mood, and controlling movement,” says Ann Graybiel, an MIT Institute Professor, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the new study.

Iakovos Lazaridis, a research scientist at the McGovern Institute, is the lead author of the paper, which appears today in the journal Current Biology.

New pathways

Graybiel has spent much of her career studying the striatum, a structure located deep within the brain that is involved in learning and decision-making, as well as control of movement.

Within the striatum, neurons are arranged in a labyrinth-like structure that includes striosomes, which Graybiel discovered in the 1970s. The classical go and no-go pathways arise from neurons that surround the striosomes, which are known collectively as the matrix. The matrix cells that give rise to these pathways receive input from sensory processing regions such as the visual cortex and auditory cortex. Then, they send go or no-go commands to neurons in the motor cortex.

However, the function of the striosomes, which are not part of those pathways, remained unknown. For many years, researchers in Graybiel’s lab have been trying to solve that mystery.

Their previous work revealed that striosomes receive much of their input from parts of the brain that process emotion. Within striosomes, there are two major types of neurons, classified as D1 and D2. In a 2015 study, Graybiel found that one of these cell types, D1, sends input to the substantia nigra, which is the brain’s major dopamine-producing center.

It took much longer to trace the output of the other set, D2 neurons. In the new Current Biology study, the researchers discovered that those neurons also eventually project to the substantia nigra, but first they connect to a set of neurons in the globus palladus, which inhibits dopamine output. This pathway, an indirect connection to the substantia nigra, reduces the brain’s dopamine output and inhibits movement.

The researchers also confirmed their earlier finding that the pathway arising from D1 striosomes connects directly to the substantia nigra, stimulating dopamine release and initiating movement.

“In the striosomes, we’ve found what is probably a mimic of the classical go/no-go pathways,” Graybiel says. “They’re like classic motor go/no-go pathways, but they don’t go to the motor output neurons of the basal ganglia. Instead, they go to the dopamine cells, which are so important to movement and motivation.”

Emotional decisions

The findings suggest that the classical model of how the striatum controls movement needs to be modified to include the role of these newly identified pathways. The researchers now hope to test their hypothesis that input related to motivation and emotion, which enters the striosomes from the cortex and the limbic system, influences dopamine levels in a way that can encourage or discourage action.

That dopamine release may be especially relevant for actions that induce anxiety or stress. In their 2015 study, Graybiel’s lab found that striosomes play a key role in making decisions that provoke high levels of anxiety; in particular, those that are high risk but may also have a big payoff.

“Ann Graybiel and colleagues have earlier found that the striosome is concerned with inhibiting dopamine neurons. Now they show unexpectedly that another type of striosomal neuron exerts the opposite effect and can signal reward. The striosomes can thus both up- or down-regulate dopamine activity, a very important discovery. Clearly, the regulation of dopamine activity is critical in our everyday life with regard to both movements and mood, to which the striosomes contribute,” says Sten Grillner, a professor of neuroscience at the Karolinska Institute in Sweden, who was not involved in the research.

Another possibility the researchers plan to explore is whether striosomes and matrix cells are arranged in modules that affect motor control of specific parts of the body.

“The next step is trying to isolate some of these modules, and by simultaneously working with cells that belong to the same module, whether they are in the matrix or striosomes, try to pinpoint how the striosomes modulate the underlying function of each of these modules,” Lazaridis says.

They also hope to explore how the striosomal circuits, which project to the same region of the brain that is ravaged by Parkinson’s disease, may influence that disorder.

The research was funded by the National Institutes of Health, the Saks-Kavanaugh Foundation, the William N. and Bernice E. Bumpus Foundation, Jim and Joan Schattinger, the Hock E. Tan and K. Lisa Yang Center for Autism Research, Robert Buxton, the Simons Foundation, the CHDI Foundation, and an Ellen Schapiro and Gerald Axelbaum Investigator BBRF Young Investigator Grant.

Seven with MIT ties elected to National Academy of Medicine for 2024

by Nina Tamburello | Koch Institute |

The National Academy of Medicine recently announced the election of more than 90 members during its annual meeting, including MIT faculty members Matthew Vander Heiden and Fan Wang, along with five MIT alumni.

Election to the National Academy of Medicine (NAM) is considered one of the highest honors in the fields of health and medicine and recognizes individuals who have demonstrated outstanding professional achievement and commitment to service.

Matthew Vander Heiden is the director of the Koch Institute for Integrative Cancer Research at MIT, a Lester Wolfe Professor of Molecular Biology, and a member of the Broad Institute of MIT and Harvard. His research explores how cancer cells reprogram their metabolism to fuel tumor growth and has provided key insights into metabolic pathways that support cancer progression, with implications for developing new therapeutic strategies. The National Academy of Medicine recognized Vander Heiden for his contributions to “the development of approved therapies for cancer and anemia” and his role as a “thought leader in understanding metabolic phenotypes and their relations to disease pathogenesis.”

Vander Heiden earned his MD and PhD from the University of Chicago and completed  his clinical training in internal medicine and medical oncology at the Brigham and Women’s Hospital and the Dana-Farber Cancer Institute. After postdoctoral research at Harvard Medical School, Vander Heiden joined the faculty of the MIT Department of Biology and the Koch Institute in 2010. He is also a practicing oncologist and instructor in medicine at Dana-Farber Cancer Institute and Harvard Medical School.

Fan Wang is a professor of brain and cognitive sciences, an investigator at the McGovern Institute, and director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT.  Wang’s research focuses on the neural circuits governing the bidirectional interactions between the brain and body. She is specifically interested in the circuits that control the sensory and emotional aspects of pain and addiction, as well as the sensory and motor circuits that work together to execute behaviors such as eating, drinking, and moving. The National Academy of Medicine has recognized her body of work for “providing the foundational knowledge to develop new therapies to treat chronic pain and movement disorders.”

Before coming to MIT in 2021, Wang obtained her PhD from Columbia University and received her postdoctoral training at the University of California at San Francisco and Stanford University. She became a faculty member at Duke University in 2003 and was later appointed the Morris N. Broad Professor of Neurobiology. Wang is also a member of the American Academy of Arts and Sciences and she continues to make important contributions to the neural mechanisms underlying general anesthesia, pain perception, and movement control.

MIT alumni who were elected to the NAM for 2024 include:

  • Leemore Dafny PhD ’01 (Economics);
  • David Huang ’85 MS ’89  (Electrical Engineering and Computer Science) PhD ’93 Medical Engineering and Medical Physics);
  • Nola M. Hylton ’79 (Chemical Engineering);
  • Mark R. Prausnitz PhD ’94 (Chemical Engineering); and
  • Konstantina M. Stankovic ’92 (Biology and Physics) PhD ’98 (Speech and Hearing Bioscience and Technology)

Established originally as the Institute of Medicine in 1970 by the National Academy of Sciences, the National Academy of Medicine addresses critical issues in health, science, medicine, and related policy and inspires positive actions across sectors.

“This class of new members represents the most exceptional researchers and leaders in health and medicine, who have made significant breakthroughs, led the response to major public health challenges, and advanced health equity,” said National Academy of Medicine President Victor J. Dzau. “Their expertise will be necessary to supporting NAM’s work to address the pressing health and scientific challenges we face today.”

A new method makes high-resolution imaging more accessible

Anne Trafton |

A classical way to image nanoscale structures in cells is with high-powered, expensive super-resolution microscopes. As an alternative, MIT researchers have developed a way to expand tissue before imaging it — a technique that allows them to achieve nanoscale resolution with a conventional light microscope.

In the newest version of this technique, the researchers have made it possible to expand tissue 20-fold in a single step. This simple, inexpensive method could pave the way for nearly any biology lab to perform nanoscale imaging.

“This democratizes imaging,” says Laura Kiessling, the Novartis Professor of Chemistry at MIT and a member of the Broad Institute of MIT and Harvard and MIT’s Koch Institute for Integrative Cancer Research. “Without this method, if you want to see things with a high resolution, you have to use very expensive microscopes. What this new technique allows you to do is see things that you couldn’t normally see with standard microscopes. It drives down the cost of imaging because you can see nanoscale things without the need for a specialized facility.”

At the resolution achieved by this technique, which is around 20 nanometers, scientists can see organelles inside cells, as well as clusters of proteins.

“Twenty-fold expansion gets you into the realm that biological molecules operate in. The building blocks of life are nanoscale things: biomolecules, genes, and gene products,” says Edward Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT; a professor of biological engineering, media arts and sciences, and brain and cognitive sciences; a Howard Hughes Medical Institute investigator; and a member of MIT’s McGovern Institute for Brain Research and Koch Institute for Integrative Cancer Research.

Boyden and Kiessling are the senior authors of the new study, which appears today in Nature Methods. MIT graduate student Shiwei Wang and Tay Won Shin PhD ’23 are the lead authors of the paper.

A single expansion

Boyden’s lab invented expansion microscopy in 2015. The technique requires embedding tissue into an absorbent polymer and breaking apart the proteins that normally hold tissue together. When water is added, the gel swells and pulls biomolecules apart from each other.

The original version of this technique, which expanded tissue about fourfold, allowed researchers to obtain images with a resolution of around 70 nanometers. In 2017, Boyden’s lab modified the process to include a second expansion step, achieving an overall 20-fold expansion. This enables even higher resolution, but the process is more complicated.

“We’ve developed several 20-fold expansion technologies in the past, but they require multiple expansion steps,” Boyden says. “If you could do that amount of expansion in a single step, that could simplify things quite a bit.”

With 20-fold expansion, researchers can get down to a resolution of about 20 nanometers, using a conventional light microscope. This allows them see cell structures like microtubules and mitochondria, as well as clusters of proteins.

In the new study, the researchers set out to perform 20-fold expansion with only a single step. This meant that they had to find a gel that was both extremely absorbent and mechanically stable, so that it wouldn’t fall apart when expanded 20-fold.

To achieve that, they used a gel assembled from N,N-dimethylacrylamide (DMAA) and sodium acrylate. Unlike previous expansion gels that rely on adding another molecule to form crosslinks between the polymer strands, this gel forms crosslinks spontaneously and exhibits strong mechanical properties. Such gel components previously had been used in expansion microscopy protocols, but the resulting gels could expand only about tenfold. The MIT team optimized the gel and the polymerization process to make the gel more robust, and to allow for 20-fold expansion.

To further stabilize the gel and enhance its reproducibility, the researchers removed oxygen from the polymer solution prior to gelation, which prevents side reactions that interfere with crosslinking. This step requires running nitrogen gas through the polymer solution, which replaces most of the oxygen in the system.

Once the gel is formed, select bonds in the proteins that hold the tissue together are broken and water is added to make the gel expand. After the expansion is performed, target proteins in tissue can be labeled and imaged.

“This approach may require more sample preparation compared to other super-resolution techniques, but it’s much simpler when it comes to the actual imaging process, especially for 3D imaging,” Shin says. “We document the step-by-step protocol in the manuscript so that readers can go through it easily.”

Imaging tiny structures

Using this technique, the researchers were able to image many tiny structures within brain cells, including structures called synaptic nanocolumns. These are clusters of proteins that are arranged in a specific way at neuronal synapses, allowing neurons to communicate with each other via secretion of neurotransmitters such as dopamine.

In studies of cancer cells, the researchers also imaged microtubules — hollow tubes that help give cells their structure and play important roles in cell division. They were also able to see mitochondria (organelles that generate energy) and even the organization of individual nuclear pore complexes (clusters of proteins that control access to the cell nucleus).

Wang is now using this technique to image carbohydrates known as glycans, which are found on cell surfaces and help control cells’ interactions with their environment. This method could also be used to image tumor cells, allowing scientists to glimpse how proteins are organized within those cells, much more easily than has previously been possible.

The researchers envision that any biology lab should be able to use this technique at a low cost since it relies on standard, off-the-shelf chemicals and common equipment such confocal microscopes and glove bags, which most labs already have or can easily access.

“Our hope is that with this new technology, any conventional biology lab can use this protocol with their existing microscopes, allowing them to approach resolution that can only be achieved with very specialized and costly state-of-the-art microscopes,” Wang says.

The research was funded, in part, by the U.S. National Institutes of Health, an MIT Presidential Graduate Fellowship, U.S. National Science Foundation Graduate Research Fellowship grants, Open Philanthropy, Good Ventures, the Howard Hughes Medical Institute, Lisa Yang, Ashar Aziz, and the European Research Council.

Finding some stability in adaptable brains

by Jennifer Michalowski |

One of the brain’s most celebrated qualities is its adaptability. Changes to neural circuits, whose connections are continually adjusted as we experience and interact with the world, are key to how we learn. But to keep knowledge and memories intact, some parts of the circuitry must be resistant to this constant change.

“Brains have figured out how to navigate this landscape of balancing between stability and flexibility, so that you can have new learning and you can have lifelong memory,” says neuroscientist Mark Harnett, an investigator at MIT’s McGovern Institute.

In the August 27, 2024 of the journal Cell Reports, Harnett and his team show how individual neurons can contribute to both parts of this vital duality. By studying the synapses through which pyramidal neurons in the brain’s sensory cortex communicate, they have learned how the cells preserve their understanding of some of the world’s most fundamental features, while also maintaining the flexibility they need to adapt to a changing world.

McGovern Institute Investigator Mark Harnett. Photo: Adam Glanzman

Visual connections

Pyramidal neurons receive input from other neurons via thousands of connection points. Early in life, these synapses are extremely malleable; their strength can shift as a young animal takes in visual information and learns to interpret it. Most remain adaptable into adulthood, but Harnett’s team discovered that some of the cells’ synapses lose their flexibility when the animals are less than a month old. Having both stable and flexible synapses means these neurons can combine input from different sources to use visual information in flexible ways.

Microscopic image of a mouse brain.
A confocal image of a mouse brain showing dLGN neurons in pink. Image: Courtney Yaeger, Mark Harnett.

Postdoctoral fellow Courtney Yaeger took a close look at these unusually stable synapses, which cluster together along a narrow region of the elaborately branched pyramidal cells. She was interested in the connections through which the cells receive primary visual information, so she traced their connections with neurons in a vision-processing center of the brain’s thalamus called the dorsal lateral geniculate nucleus (dLGN).

The long extensions through which a neuron receives signals from other cells are called dendrites, and they branch of from the main body of the cell into a tree-like structure. Spiny protrusions along the dendrites form the synapses that connect pyramidal neurons to other cells. Yaeger’s experiments showed that connections from the dLGN all led to a defined region of the pyramidal cells—a tight band within what she describes as the trunk of the dendritic tree.

Yaeger found several ways in which synapses in this region— formally known as the apical oblique dendrite domain—differ from other synapses on the same cells. “They’re not actually that far away from each other, but they have completely different properties,” she says.

Stable synapses

In one set of experiments, Yaeger activated synapses on the pyramidal neurons and measured the effect on the cells’ electrical potential. Changes to a neuron’s electrical potential generate the impulses the cells use to communicate with one another. It is common for a synapse’s electrical effects to amplify when synapses nearby are also activated. But when signals were delivered to the apical oblique dendrite domain, each one had the same effect, no matter how many synapses were stimulated. Synapses there don’t interact with one another at all, Harnett says. “They just do what they do. No matter what their neighbors are doing, they all just do kind of the same thing.”

Two rows of seven confocal microscope images of dendrites.
Representative oblique (top) and basal (bottom) dendrites from the same Layer 5 pyramidal neuron imaged across 7 days. Transient spines are labeled with yellow arrowheads the day before disappearance. Image: Courtney Yaeger, Mark Harnett.

The team was also able to visualize the molecular contents of individual synapses. This revealed a surprising lack of a certain kind of neurotransmitter receptor, called NMDA receptors, in the apical oblique dendrites. That was notable because of NMDA receptors’ role in mediating changes in the brain. “Generally when we think about any kind of learning and memory and plasticity, it’s NMDA receptors that do it,” Harnett says. “That is the by far most common substrate of learning and memory in all brains.”

When Yaeger stimulated the apical oblique synapses with electricity, generating patterns of activity that would strengthen most synapses, the team discovered a consequence of the limited presence of NMDA receptors. The synapses’ strength did not change. “There’s no activity-dependent plasticity going on there, as far as we have tested,” Yaeger says.

That makes sense, the researchers say, because the cells’ connections from the thalamus relay primary visual information detected by the eyes. It is through these connections that the brain learns to recognize basic visual features like shapes and lines.

“These synapses are basically a robust, high fidelity readout of this visual information,” Harnett explains. “That’s what they’re conveying, and it’s not context sensitive. So it doesn’t matter how many other synapses are active, they just do exactly what they’re going to do, and you can’t modify them up and down based on activity. So they’re very, very stable.”

“You actually don’t want those to be plastic,” adds Yaeger.

“Can you imagine going to sleep and then forgetting what a vertical line looks like? That would be disastrous.” – Courtney Yaeger

By conducting the same experiments in mice of different ages, the researchers determined that the synapses that connect pyramidal neurons to the thalamus become stable a few weeks after young mice first open their eyes. By that point, Harnett says, they have learned everything they need to learn. On the other hand, if mice spend the first weeks of their lives in the dark, the synapses never stabilize—further evidence that the transition depends on visual experience.

The team’s findings not only help explain how the brain balances flexibility and stability, they could help researchers teach artificial intelligence how to do the same thing. Harnett says artificial neural networks are notoriously bad at this: When an artificial neural network that does something well is trained to do something new, it almost always experiences “catastrophic forgetting” and can no longer perform its original task. Harnett’s team is exploring how they can use what they’ve learned about real brains to overcome this problem in artificial networks.

Harnessing the power of placebo for pain relief

by Jennifer Michalowski |

Placebos are inert treatments, generally not expected to impact biological pathways or improve a person’s physical health. But time and again, some patients report that they feel better after taking a placebo. Increasingly, doctors and scientists are recognizing that rather than dismissing placebos as mere trickery, they may be able to help patients by harnessing their power.

To maximize the impact of the placebo effect and design reliable therapeutic strategies, researchers need a better understanding of how it works. Now, with a new animal model developed by scientists at the McGovern Institute, they will be able to investigate the neural circuits that underlie placebos’ ability to elicit pain relief.

“The brain and body interaction has a lot of potential, in a way that we don’t fully understand,” says McGovern investigator Fan Wang. “I really think there needs to be more of a push to understand placebo effect, in pain and probably in many other conditions. Now we have a strong model to probe the circuit mechanism.”

Context-dependent placebo effect

McGovern Investigator Fan Wang. Photo: Caitliin Cunningham

In the September 5, 2024, issue of the journal Current Biology, Wang and her team report that they have elicited strong placebo pain relief in mice by activating pain-suppressing neurons in the brain while the mice are in a specific environment—thereby teaching the animals that they feel better when they are in that context. Following their training, placing the mice in that environment alone is enough to suppress pain. The team’s experiments, which were funded by the National Institutes of Health, the K. Lisa Yang Brain-Body Center and the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics within MIT’s Yang Tan Collective show that this context-dependent placebo effect relieves both acute and chronic pain.

Context is critical for the placebo effect. While a pill can help a patient feel better when they expect it to, even if it is made only of sugar or starch, it seems to be not just the pill that sets up those expectations, but the entire scenario in which the pill is taken. For example, being in a hospital and interacting with doctors can contribute to a patient’s perception of care, and these social and environmental factors can make a placebo effect more probable.

Postdoctoral fellows Bin Chen and Nitsan Goldstein used visual and textural cues to define a specific place. Then they activated pain-suppressing neurons in the brain while the animals were in this “pain-relief box.” Those pain-suppressing neurons, which Wang’s lab discovered a few years ago, are located in an emotion-processing center of the brain called the central amygdala. By expressing light-sensitive channels in these neurons, the researchers were able to suppress pain with light in the pain-relief box and leave the neurons inactive when mice were in a control box.

Animals learned to prefer the pain-relief box to other environments. And when the researchers tested their response to potentially painful stimuli after they had made that association, they found the mice were less sensitive while they were there. “Just by being in the context that they had associated with pain suppression, we saw that reduced pain—even though we weren’t actually activating those [pain-suppressing] neurons,” Goldstein explains.

Acute and chronic pain relief

Some scientists have been able to elicit placebo pain relief in rodents by treating the animals with morphine, linking environmental cues to the pain suppression caused by the drugs similar to the way Wang’s team did by directly activating pain-suppressing neurons. This drug-based approach works best for setting up expectations of relief for acute pain; its placebo effect is short-lived and mostly ineffective against chronic pain. So Wang, Chen, and Goldstein were particularly pleased to find that their engineered placebo effect was effective for relieving both acute and chronic pain.

In their experiments, animals experiencing a chemotherapy-induced hypersensitivity to touch exhibited a preference for the pain relief box as much as animals who were exposed to a chemical that induces acute pain, days after their initial conditioning. Once there, their chemotherapy-induced pain sensitivity was eliminated; they exhibited no more sensitivity to painful stimuli than they had prior to receiving chemotherapy.

One of the biggest surprises came when the researchers turned their attention back to the pain-suppressing neurons in the central amygdala that they had used to trigger pain relief. They suspected that those neurons might be reactivated when mice returned to the pain-relief box. Instead, they found that after the initial conditioning period, those neurons remained quiet. “These neurons are not reactivated, yet the mice appear to be no longer in pain,” Wang says. “So it suggests this memory of feeling well is transferred somewhere else.”

Goldstein adds that there must be a pain-suppressing neural circuit somewhere that is activated by pain-relief-associated contexts—and the team’s new placebo model sets researchers up to investigate those pathways. A deeper understanding of that circuitry could enable clinicians to deploy the placebo effect—alone or in combination with active treatments—to better manage patients’ pain in the future.

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.

Five MIT faculty elected to the National Academy of Sciences for 2024

by School of Science, MIT |

The National Academy of Sciences has elected 120 members and 24 international members, including five faculty members from MIT. Guoping Feng, Piotr Indyk, Daniel J. Kleitman, Daniela Rus, and Senthil Todadri were elected in recognition of their “distinguished and continuing achievements in original research.” Membership to the National Academy of Sciences is one of the highest honors a scientist can receive in their career.

Among the new members added this year are also nine MIT alumni, including Zvi Bern ’82; Harold Hwang ’93, SM ’93; Leonard Kleinrock SM ’59, PhD ’63; Jeffrey C. Lagarias ’71, SM ’72, PhD ’74; Ann Pearson PhD ’00; Robin Pemantle PhD ’88; Jonas C. Peters PhD ’98; Lynn Talley PhD ’82; and Peter T. Wolczanski ’76. Those elected this year bring the total number of active members to 2,617, with 537 international members.

The National Academy of Sciences is a private, nonprofit institution that was established under a congressional charter signed by President Abraham Lincoln in 1863. It recognizes achievement in science by election to membership, and — with the National Academy of Engineering and the National Academy of Medicine — provides science, engineering, and health policy advice to the federal government and other organizations.

Guoping Feng

Guoping Feng is the James W. (1963) and Patricia T. Poitras Professor in the Department of Brain and Cognitive Sciences. He is also associate director and investigator in the McGovern Institute for Brain Research, a member of the Broad Institute of MIT and Harvard, and director of the Hock E. Tan and K. Lisa Yang Center for Autism Research.

His research focuses on understanding the molecular mechanisms that regulate the development and function of synapses, the places in the brain where neurons connect and communicate. He’s interested in how defects in the synapses can contribute to psychiatric and neurodevelopmental disorders. By understanding the fundamental mechanisms behind these disorders, he’s producing foundational knowledge that may guide the development of new treatments for conditions like obsessive-compulsive disorder and schizophrenia.

Feng received his medical training at Zhejiang University Medical School in Hangzhou, China, and his PhD in molecular genetics from the State University of New York at Buffalo. He did his postdoctoral training at Washington University at St. Louis and was on the faculty at Duke University School of Medicine before coming to MIT in 2010. He is a member of the American Academy of Arts and Sciences, a fellow of the American Association for the Advancement of Science, and was elected to the National Academy of Medicine in 2023.

Piotr Indyk

Piotr Indyk is the Thomas D. and Virginia W. Cabot Professor of Electrical Engineering and Computer Science. He received his magister degree from the University of Warsaw and his PhD from Stanford University before coming to MIT in 2000.

Indyk’s research focuses on building efficient, sublinear, and streaming algorithms. He’s developed, for example, algorithms that can use limited time and space to navigate massive data streams, that can separate signals into individual frequencies faster than other methods, and can address the “nearest neighbor” problem by finding highly similar data points without needing to scan an entire database. His work has applications on everything from machine learning to data mining.

He has been named a Simons Investigator and a fellow of the Association for Computer Machinery. In 2023, he was elected to the American Academy of Arts and Sciences.

Daniel J. Kleitman

Daniel Kleitman, a professor emeritus of applied mathematics, has been at MIT since 1966. He received his undergraduate degree from Cornell University and his master’s and PhD in physics from Harvard University before doing postdoctoral work at Harvard and the Niels Bohr Institute in Copenhagen, Denmark.

Kleitman’s research interests include operations research, genomics, graph theory, and combinatorics, the area of math concerned with counting. He was actually a professor of physics at Brandeis University before changing his field to math, encouraged by the prolific mathematician Paul Erdős. In fact, Kleitman has the rare distinction of having an Erdős number of just one. The number is a measure of the “collaborative distance” between a mathematician and Erdős in terms of authorship of papers, and studies have shown that leading mathematicians have particularly low numbers.

He’s a member of the American Academy of Arts and Sciences and has made important contributions to the MIT community throughout his career. He was head of the Department of Mathematics and served on a number of committees, including the Applied Mathematics Committee. He also helped create web-based technology and an online textbook for several of the department’s core undergraduate courses. He was even a math advisor for the MIT-based film “Good Will Hunting.”

Daniela Rus

Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science, is the director of the Computer Science and Artificial Intelligence Laboratory (CSAIL). She also serves as director of the Toyota-CSAIL Joint Research Center.

Her research on robotics, artificial intelligence, and data science is geared toward understanding the science and engineering of autonomy. Her ultimate goal is to create a future where machines are seamlessly integrated into daily life to support people with cognitive and physical tasks, and deployed in way that ensures they benefit humanity. She’s working to increase the ability of machines to reason, learn, and adapt to complex tasks in human-centered environments with applications for agriculture, manufacturing, medicine, construction, and other industries. She’s also interested in creating new tools for designing and fabricating robots and in improving the interfaces between robots and people, and she’s done collaborative projects at the intersection of technology and artistic performance.

Rus received her undergraduate degree from the University of Iowa and her PhD in computer science from Cornell University. She was a professor of computer science at Dartmouth College before coming to MIT in 2004. She is part of the Class of 2002 MacArthur Fellows; was elected to the National Academy of Engineering and the American Academy of Arts and Sciences; and is a fellow of the Association for Computer Machinery, the Institute of Electrical and Electronics Engineers, and the Association for the Advancement of Artificial Intelligence.

Senthil Todadri

Senthil Todadri, a professor of physics, came to MIT in 2001. He received his undergraduate degree from the Indian Institute of Technology in Kanpur and his PhD from Yale University before working as a postdoc at the Kavli Institute for Theoretical Physics in Santa Barbara, California.

Todadri’s research focuses on condensed matter theory. He’s interested in novel phases and phase transitions of quantum matter that expand beyond existing paradigms. Combining modeling experiments and abstract methods, he’s working to develop a theoretical framework for describing the physics of these systems. Much of that work involves understanding the phenomena that arise because of impurities or strong interactions between electrons in solids that don’t conform with conventional physical theories. He also pioneered the theory of deconfined quantum criticality, which describes a class of phase transitions, and he discovered the dualities of quantum field theories in two dimensional superconducting states, which has important applications to many problems in the field.

Todadri has been named a Simons Investigator, a Sloan Research Fellow, and a fellow of the American Physical Society. In 2023, he was elected to the American Academy of Arts and Sciences