Revisiting reinforcement learning

MIT Institute Professor Ann Graybiel. Photo: Justin Knight

Dopamine is a powerful signal in the brain, influencing our moods, motivations, movements, and more. The neurotransmitter is crucial for reward-based learning, a function that may be disrupted in a number of psychiatric conditions, from mood disorders to addiction. Now, researchers led by Ann Graybiel, an investigator at MIT’s McGovern Institute, have found surprising patterns of dopamine signaling that suggest neuroscientists may need to refine their model of how reinforcement learning occurs in the brain. The team’s findings were published October 14, 2024, in the journal Nature Communications.

Dopamine plays a critical role in teaching people and other animals about the cues and behaviors that portend both positive and negative outcomes; the classic example of this type of learning is the dog that Ivan Pavlov trained to anticipate food at the sound of bell. Graybiel explains that according to the standard model of reinforcement learning, when an animal is exposed to a cue paired with a reward, dopamine-producing cells initially fire in response to the reward. As animals learn the association between the cue and the reward, the timing of dopamine release shifts, so it becomes associated with the cue instead of the reward itself.

But with new tools enabling more detailed analyses of when and where dopamine is released in the brain, Graybiel’s team is finding that this model doesn’t completely hold up. The group started picking up clues that the field’s model of reinforcement learning was incomplete more than ten years ago, when Mark Howe, a graduate student in the lab, noticed that the dopamine signals associated with reward were released not in a sudden burst the moment a reward was obtained, but instead before that, building gradually as a rat got closer to its treat. Dopamine might actually be communicating to the rest of the brain the proximity of the reward, they reasoned. “That didn’t fit at all with the standard, canonical model,” Graybiel says.

Dopamine dynamics

As other neuroscientists considered how a model of reinforcement learning could take those findings into account, Graybiel and postdoctoral researcher Min Jung Kim decided it was time to take a closer look at dopamine dynamics.

“We thought, let’s go back to the most basic kind of experiment and start all over again,” Graybiel says.

That meant using sensitive new dopamine sensors to track the neurotransmitter’s release in the brains of mice as they learned to associated a blue light with a satisfying sip of water. The team focused its attention on the striatum, a region within the brain’s basal ganglia, where neurons use dopamine to influence neural circuits involved in a variety of processes, including reward-based learning.

The researchers found that the timing of dopamine release varied in different parts of the striatum. But nowhere did Graybiel’s team find a transition in dopamine release timing from the time of the reward to the time to the cue—the key transition predicted by the standard model of reinforcement learning model.

In the team’s simplest experiments, where every time a mouse saw a light it was paired with a reward, the lateral part of the striatum reliably released dopamine when animals were given their water. This strong response to the reward never diminished, even as the mice learned to expect the reward when they saw a light. In the medial part of the striatum, in contrast, dopamine was never released at the time of the reward. Cells there always fired when a mouse saw the light, even early in the learning process. This was puzzling, Graybiel says, because at the beginning of learning, dopamine would have been predicted to respond to the reward itself.

The patterns of dopamine release became even more unexpected when Graybiel’s team introduced a second light into its experimental setup. The new light, in a different position than the first, did not signal a reward. Mice watched as either light was given as the cue, one at a time, with water accompanying only the original cue.

In these experiments, when the mice saw the reward-associated light, dopamine release went up in the centromedial striatum and surprisingly, stayed up until the reward was delivered. In the lateral part of the region, dopamine also involved a sustained period where signaling plateaued.

Graybiel says she was surprised to see how much dopamine responses changed when the experimenters introduce the second light. The responses to the rewarded light were different when the other light could be shown in other trials, even though the mice saw only one light at a time. “There must be a cognitive aspect to this that comes into play,” she says. “The brain wants to hold onto the information that the cue has come on for a while.” Cells in the striatum seem to achieve this through the sustained dopamine release that continued during the brief delay between the light and the reward in the team’s experiments. Indeed, Graybiel said, while this kind of sustained dopamine release has not previously been linked to reinforcement learning, it is reminiscent of sustained signaling that has been tied to working memory in other parts of the brain.

Reinforcement learning, reconsidered

Ultimately, Graybiel says, “many of our results didn’t fit reinforcement learning models as traditionally—and by now canonically—considered.” That suggests neuroscientists’ understanding of this process will need to evolve as part of the field’s deepening understanding of the brain. “But this is just one step to help us all refine our understanding and to have reformulations of the models of how basal ganglia influence movement and thought and emotion. These reformulations will have to include surprises about the reinforcement learning system vis-á-vis these plateaus, but they could possibly give us insight into how a single experience can linger in this reinforcement-related part of our brains,” she says.

This study was funded by the National Institutes of Health, the William N. & Bernice E. Bumpus Foundation, the Saks Kavanaugh Foundation, the CHDI Foundation, Joan and Jim Schattinger, and Lisa Yang.

Four from MIT named 2025 Rhodes Scholars

Yiming Chen ’24, Wilhem Hector, Anushka Nair, and David Oluigbo have been selected as 2025 Rhodes Scholars and will begin fully funded postgraduate studies at Oxford University in the U.K. next fall. In addition to MIT’s two U.S. Rhodes winners, Ouigbo and Nair, two affiliates were awarded international Rhodes Scholarships: Chen for Rhodes’ China constituency and Hector for the Global Rhodes Scholarship. Hector is the first Haitian citizen to be named a Rhodes Scholar.

The scholars were supported by Associate Dean Kim Benard and the Distinguished Fellowships team in Career Advising and Professional Development. They received additional mentorship and guidance from the Presidential Committee on Distinguished Fellowships.

“It is profoundly inspiring to work with our amazing students, who have accomplished so much at MIT and, at the same time, thought deeply about how they can have an impact in solving the world’s major challenges,” says Professor Nancy Kanwisher who co-chairs the committee along with Professor Tom Levenson. “These students have worked hard to develop and articulate their vision and to learn to communicate it to others with passion, clarity, and confidence. We are thrilled but not surprised to see so many of them recognized this year as finalists and as winners.

Yiming Chen ’24

Yiming Chen, from Beijing, China, and the Washington area, was named one of four Rhodes China Scholars on Sept 28. At Oxford, she will pursue graduate studies in engineering science, working toward her ongoing goal of advancing AI safety and reliability in clinical workflows.

Chen graduated from MIT in 2024 with a BS in mathematics and computer science and an MEng in computer science. She worked on several projects involving machine learning for health care, and focused her master’s research on medical imaging in the Medical Vision Group of the Computer Science and Artificial Intelligence Laboratory (CSAIL).

Collaborating with IBM Research, Chen developed a neural framework for clinical-grade lumen segmentation in intravascular ultrasound and presented her findings at the MICCAI Machine Learning in Medical Imaging conference. Additionally, she worked at Cleanlab, an MIT-founded startup, creating an open-source library to ensure the integrity of image datasets used in vision tasks.

Chen was a teaching assistant in the MIT math and electrical engineering and computer science departments, and received a teaching excellence award. She taught high school students at the Hampshire College Summer Studies in Math and was selected to participate in MISTI Global Teaching Labs in Italy.

Having studied the guzheng, a traditional Chinese instrument, since age 4, Chen served as president of the MIT Chinese Music Ensemble, explored Eastern and Western music synergies with the MIT Chamber Music Society, and performed at the United Nations. On campus, she was also active with Asymptones a capella, MIT Ring Committee, Ribotones, Figure Skating Club, and the Undergraduate Association Innovation Committee.

Wilhem Hector

Wilhem Hector, a senior from Port-au-Prince, Haiti, majoring in mechanical engineering, was awarded a Global Rhodes Scholarship on Nov 1. The first Haitian national to be named a Rhodes Scholar, Hector will pursue at Oxford a master’s in energy systems followed by a master’s in education, focusing on digital and social change. His long-term goals are twofold: pioneering Haiti’s renewable energy infrastructure and expanding hands-on opportunities in the country‘s national curriculum.

Hector developed his passion for energy through his research in the MIT Howland Lab, where he investigated the uncertainty of wind power production during active yaw control. He also helped launch the MIT Renewable Energy Clinic through his work on the sources of opposition to energy projects in the U.S. Beyond his research, Hector had notable contributions as an intern at Radia Inc. and DTU Wind Energy Systems, where he helped develop computational wind farm modeling and simulation techniques.

Outside of MIT, he leads the Hector Foundation, a nonprofit providing educational opportunities to young people in Haiti. He has raised over $80,000 in the past five years to finance their initiatives, including the construction of Project Manus, Haiti’s first open-use engineering makerspace. Hector’s service endeavors have been supported by the MIT PKG Center, which awarded him the Davis Peace Prize, the PKG Fellowship for Social Impact, and the PKG Award for Public Service.

Hector co-chairs both the Student Events Board and the Class of 2025 Senior Ball Committee and has served as the social chair for Chocolate City and the African Students Association.

Anushka Nair

Anushka Nair, from Portland, Oregon, will graduate next spring with BS and MEng degrees in computer science and engineering with concentrations in economics and AI. She plans to pursue a DPhil in social data science at the Oxford Internet Institute. Nair aims to develop ethical AI technologies that address pressing societal challenges, beginning with combating misinformation.

For her master’s thesis under Professor David Rand, Nair is developing LLM-powered fact-checking tools to detect nuanced misinformation beyond human or automated capabilities. She also researches human-AI co-reasoning at the MIT Center for Collective Intelligence with Professor Thomas Malone. Previously, she conducted research on autonomous vehicle navigation at Stanford’s AI and Robotics Lab, energy microgrid load balancing at MIT’s Institute for Data, Systems, and Society, and worked with Professor Esther Duflo in economics.

Nair interned in the Executive Office of the Secretary General at the United Nations, where she integrated technology solutions and assisted with launching the High-Level Advisory Body on AI. She also interned in Tesla’s energy sector, contributing to Autobidder, an energy trading tool, and led the launch of a platform for monitoring distributed energy resources and renewable power plants. Her work has earned her recognition as a Social and Ethical Responsibilities of Computing Scholar and a U.S. Presidential Scholar.

Nair has served as President of the MIT Society of Women Engineers and MIT and Harvard Women in AI, spearheading outreach programs to mentor young women in STEM fields. She also served as president of MIT Honors Societies Eta Kappa Nu and Tau Beta Pi.

David Oluigbo

David Oluigbo, from Washington, is a senior majoring in artificial intelligence and decision making and minoring in brain and cognitive sciences. At Oxford, he will undertake an MSc in applied digital health followed by an MSc in modeling for global health. Afterward, Oluigbo plans to attend medical school with the goal of becoming a physician-scientist who researches and applies AI to address medical challenges in low-income countries.

Since his first year at MIT, Oluigbo has conducted neural and brain research with Ev Fedorenko at the McGovern Institute for Brain Research and with Susanna Mierau’s Synapse and Network Development Group at Brigham and Women’s Hospital. His work with Mierau led to several publications and a poster presentation at the Federation of European Societies annual meeting.

In a summer internship at the National Institutes of Health Clinical Center, Oluigbo designed and trained machine-learning models on CT scans for automatic detection of neuroendocrine tumors, leading to first authorship on an International Society for Optics and Photonics conference proceeding paper, which he presented at the 2024 annual meeting. Oluigbo also did a summer internship with the Anyscale Learning for All Laboratory at the MIT Computer Science and Artificial Intelligence Laboratory.

Oluigbo is an EMT and systems administrator officer with MIT-EMS. He is a consultant for Code for Good, a representative on the MIT Schwarzman College of Computing Undergraduate Advisory Group, and holds executive roles with the Undergraduate Association, the MIT Brain and Cognitive Society, and the MIT Running Club.

Illuminating the architecture of the mind

This story also appears in the Winter 2025 issue of BrainScan

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McGovern investigator Nancy Kanwisher and her team have big questions about the nature of the human mind. Energized by Kanwisher’s enthusiasm for finding out how and why the brain works as it does, her team collaborates broadly and embraces various tools of neuroscience. But their core discoveries tend to emerge from pictures of the brain in action. For Kanwisher, the Walter A. Rosenblith Professor of Cognitive Neuroscience at MIT, “there’s nothing like looking inside.”

Kanwisher and her colleagues have scanned the brains of hundreds of volunteers using functional magnetic resonance imaging (fMRI). With each scan, they collect a piece of insight into how the brain is organized.

Male and female researchers sitting in an imaging center with an MRI in the background.
Nancy Kanwisher (right), whose unfaltering support for students and trainees has earned her awards for outstanding teaching and mentorship, is now working with research scientist RT Pramod to find the brain’s “physics network.” Photo: Steph Stevens

Recognizing faces

By visualizing the parts of the brain that get involved in various mental activities — and, importantly, which do not — they’ve discovered that certain parts of the brain specialize in surprisingly specific tasks. Earlier this year Kanwisher was awarded the prestigious Kavli Prize in Neuroscience for the discovery of one of these hyper-specific regions: a small spot within the brain’s neocortex that recognizes faces.

Kanwisher found that this region, which she named the fusiform face area (FFA), is highly sensitive to images of faces and appears to be largely uninterested in other objects. Without the FFA, the brain struggles with facial recognition — an impairment seen in patients who have experienced damage to this part of the brain.

Beyond the FFA

Not everything in the brain is so specialized. Many areas participate in a range of cognitive processes, and even the most specialized modules, like the FFA, must work with other brain regions to process and use information. Plus, Kanwisher and her team have tracked brain activity during many functions without finding regions devoted exclusively to those tasks. (There doesn’t appear to be a part of the brain dedicated to recognizing snakes, for example).

Still, work in the Kanwisher lab demonstrates that as a specialized functional module within the brain, the FFA is not unique. In collaboration with McGovern colleagues Josh McDermott and Evelina Fedorenko, the group has found areas devoted to perceiving music and using language. There’s even a region dedicated to thinking about other people’s thoughts, identified by Rebecca Saxe in work she started as a graduate student in Kanwisher’s lab.

Brain with colored blobs.
Kanwisher’s team has found several hyperspecific regions of the brain, including those dedicated to using language (red-orange), perceiving music (yellow), thinking about other people’s thoughts (blue), recognizing bodies (green), and our intuitive sense of physics (teal). (This is an artistic adaptation of Kanwisher’s data.)

Having established these regions’ roles, Kanwisher and her collaborators are now looking at how and why they become so specialized. Meanwhile, the group has also turned its attention to a more complex function that seems to largely take place within a defined network: our intuitive sense of physics.

The brain’s game engine

Early in life, we begin to understand the nature of objects and materials, such as the fact that objects can support but not move through each other. Later, we intuitively understand how it feels to move on a slippery floor, what happens when moving objects collide, and where a tossed ball will fall. “You can’t do anything at all in the world without some understanding of the physics of the world you’re acting on,” Kanwisher says.

Kanwisher says MIT colleague Josh Tenenbaum first sparked her interest in intuitive physical reasoning. Tenenbaum and his students had been arguing that humans understand
the physical world using a simulation system, much like the physics engines that video games use to generate realistic movement and interactions within virtual environments. Kanwisher decided to team up with Tenenbaum to test whether there really is a game engine in the head, and if so, what it computes and represents.

An unstable column of blue and yellow blocks piled on top of a table that is half red, half green.
By asking subjects in an MRI scanner to predict which way this block tower might fall, Kanwisher’s team is zeroing in on the location of the brain’s “physics network.” Image: RT Pramod, Nancy Kanwisher

To find out, Kanwisher and her team have asked volunteers to evaluate various scenarios while in an MRI scanner — some that require physical reasoning and some that do not. They found sizable parts of the brain that participate in physical reasoning tasks but stay quiet during other kinds of thinking.

Research scientist RT Pramod says he was initially skeptical the brain would dedicate special circuitry to the diverse tasks involved in our intuitive sense of physics — but he’s been convinced by the data he’s found. “I see consistent evidence that if you’re reasoning, if you’re thinking, or even if you’re looking at anything sort of “physics-y” about the world, you will see activations in these regions and only in these regions — not anywhere else,” he says.

Pramod’s experiments also show that these regions are called on to make predictions about the physical world. When volunteers watch videos of objects whose trajectories portend a crash — but do not actually depict that crash — it is the physics network that signals what is about to happen. “Only these regions have this information, suggesting that maybe there is some truth to the physics engine hypothesis,” Pramod says.

Kanwisher says she doesn’t expect physical reasoning, which her group has tied to sizable swaths of the brain’s frontal and parietal cortex, to be executed by a module as distinct as the FFA. “It’s not going to be like one hyper-specific region and that’s all that happens there,” she says. “I think ultimately it’s much more interesting than that.”

To figure out what these regions can and cannot do, Kanwisher’s team has broadened the ways in which they ask volunteers to think about physics inside the MRI scanner. So far, Kanwisher says, the group’s tests have focused on rigid objects. But what about soft, squishy ones, or liquids?

A red liquid sloshes inside a clear container.
Kanwisher’s team is exploring whether non-rigid materials, like the liquid in this image, engage the brain’s “physics network” in the same way as rigid objects. Image: Vivian Paulun

Vivian Paulun, a postdoc working jointly with Kanwisher and Tenenbaum, is investigating whether our innate expectations about these kinds of materials occur within the network that they have linked to physical reasoning about rigid objects. Another set of experiments will explore whether we use sounds, like that of a bouncing ball or a screeching car, to predict physics physical events with the same network that interprets visual cues.

Meanwhile, she is also excited about an opportunity to find out what happens when the brain’s physics network is damaged. With collaborators in England, the group plans to find out whether patients in which stroke has affected this part of the brain have specific deficits in physical reasoning.

Probing these questions could reveal fundamental truths about the human mind and intelligence. Pramod points out that it could also help advance artificial intelligence, which so far has been unable to match humans when it comes to physical reasoning. “Inferences that are sort of easy for us are still really difficult for even state-of-the art computer vision,” he says. “If we want to get to a stage where we have really good machine learning algorithms that can interact with the world the way we do, I think we should first understand how the brain does it.”

Neuroscientists create a comprehensive map of the cerebral cortex

By analyzing brain scans taken as people watched movie clips, MIT researchers have created the most comprehensive map yet of the functions of the brain’s cerebral cortex.

Using functional magnetic resonance imaging (fMRI) data, the research team identified 24 networks with different functions, which include processing language, social interactions, visual features, and other types of sensory input.

Many of these networks have been seen before but haven’t been precisely characterized using naturalistic conditions. While the new study mapped networks in subjects watching engaging movies, previous works have used a small number of specific tasks or examined correlations across the brain in subjects who were simply resting.

“There’s an emerging approach in neuroscience to look at brain networks under more naturalistic conditions. This is a new approach that reveals something different from conventional approaches in neuroimaging,” says Robert Desimone, director of MIT’s McGovern Institute for Brain Research. “It’s not going to give us all the answers, but it generates a lot of interesting ideas based on what we see going on in the movies that’s related to these network maps that emerge.”

The researchers hope that their new map will serve as a starting point for further study of what each of these networks is doing in the brain.

Desimone and John Duncan, a program leader in the MRC Cognition and Brain Sciences Unit at Cambridge University, are the senior authors of the study, which appears today in Neuron. Reza Rajimehr, a research scientist in the McGovern Institute and a former graduate student at Cambridge University, is the lead author of the paper.

Precise mapping

The cerebral cortex of the brain contains regions devoted to processing different types of sensory information, including visual and auditory input. Over the past few decades, scientists have identified many networks that are involved in this kind of processing, often using fMRI to measure brain activity as subjects perform a single task such as looking at faces.

In other studies, researchers have scanned people’s brains as they do nothing, or let their minds wander. From those studies, researchers have identified networks such as the default mode network, a network of areas that is active during internally focused activities such as daydreaming.

“Up to now, most studies of networks were based on doing functional MRI in the resting-state condition. Based on those studies, we know some main networks in the cortex. Each of them is responsible for a specific cognitive function, and they have been highly influential in the neuroimaging field,” Rajimehr says.

However, during the resting state, many parts of the cortex may not be active at all. To gain a more comprehensive picture of what all these regions are doing, the MIT team analyzed data recorded while subjects performed a more natural task: watching a movie.

“By using a rich stimulus like a movie, we can drive many regions of the cortex very efficiently. For example, sensory regions will be active to process different features of the movie, and high-level areas will be active to extract semantic information and contextual information,” Rajimehr says. “By activating the brain in this way, now we can distinguish different areas or different networks based on their activation patterns.”

The data for this study was generated as part of the Human Connectome Project. Using a 7-Tesla MRI scanner, which offers higher resolution than a typical MRI scanner, brain activity was imaged in 176 people as they watched one hour of movie clips showing a variety of scenes.

The MIT team used a machine-learning algorithm to analyze the activity patterns of each brain region, allowing them to identify 24 networks with different activity patterns and functions.

Some of these networks are located in sensory areas such as the visual cortex or auditory cortex, as expected for regions with specific sensory functions. Other areas respond to features such as actions, language, or social interactions. Many of these networks have been seen before, but this technique offers more precise definition of where the networks are located, the researchers say.

“Different regions are competing with each other for processing specific features, so when you map each function in isolation, you may get a slightly larger network because it is not getting constrained by other processes,” Rajimehr says. “But here, because all the areas are considered together, we are able to define more precise boundaries between different networks.”

The researchers also identified networks that hadn’t been seen before, including one in the prefrontal cortex, which appears to be highly responsive to visual scenes. This network was most active in response to pictures of scenes within the movie frames.

Executive control networks

Three of the networks found in this study are involved in “executive control,” and were most active during transitions between different clips. The researchers also observed that these control networks appear to have a “push-pull” relationship with networks that process specific features such as faces or actions. When networks specific to a particular feature were very active, the executive control networks were mostly quiet, and vice versa.

“Whenever the activations in domain-specific areas are high, it looks like there is no need for the engagement of these high-level networks,” Rajimehr says. “But in situations where perhaps there is some ambiguity and complexity in the stimulus, and there is a need for the involvement of the executive control networks, then we see that these networks become highly active.”

Using a movie-watching paradigm, the researchers are now studying some of the networks they identified in more detail, to identify subregions involved in particular tasks. For example, within the social processing network, they have found regions that are specific to processing social information about faces and bodies. In a new network that analyzes visual scenes, they have identified regions involved in processing memory of places.

“This kind of experiment is really about generating hypotheses for how the cerebral cortex is functionally organized. Networks that emerge during movie watching now need to be followed up with more specific experiments to test the hypotheses. It’s giving us a new view into the operation of the entire cortex during a more naturalistic task than just sitting at rest,” Desimone says.

The research was funded by the McGovern Institute, the Cognitive Science and Technology Council of Iran, the MRC Cognition and Brain Sciences Unit at the University of Cambridge, and a Cambridge Trust scholarship.

A cell protector collaborates with a killer

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.

Adults’ brain activity appears unchanged after a year of medical use of cannabis

In a study of adults who use cannabis because they are seeking relief from pain, depression, anxiety, or insomnia, scientists at MIT and Harvard found no changes in brain activity after one year of self-directed use. The study, reported September 18, 2024, in JAMA Network Open, is among the first to investigate how the real-world ways people use cannabis to treat medical symptoms might impact the brain in lasting ways.

While some studies have linked chronic cannabis use to changes in the brain’s structure and function, outcomes vary depending, in part, on how and when people use the substance. People who begin using cannabis during adolescence, while the brain is still developing, may be particularly vulnerable to brain changes. The potency of the products they use and how often they use them matter, too.

Participants in the research, who obtained medical cannabis cards at the outset of the study, tended to choose lower potency products and use them less than daily. This may be why the researchers’ analysis—which focused on the brain activity associated with three kinds of cognitive processes—showed no changes after a year of use.

“For most older adults, occasional cannabis will not dramatically affect brain activation,” says Harvard neuroscientist Jodi Gilman, who led the study. “However, there are some individuals who may be vulnerable to negative effects of cannabis on cognitive function, particularly those using higher potency products more frequently.”

Gilman cautions that in another study of the same medical cannabis users, her team found that the drug failed to alleviate patients’ pain, depression, or anxiety. “So it didn’t help their symptoms—but it wasn’t associated with significant changes in brain activation,” she says. She also cautioned that some adults in the study did develop problems with cannabis use, including cannabis use disorder.

Medical cannabis programs are currently established in 38 U.S. states and Washington, D.C., increasing access to a substance that many people hope might help them relieve distressing medical symptoms. But little is known about how this type of cannabis use affects neural circuits in the brain. “Cannabis has been legalized through ballot initiatives and by legislatures. Dispensary cannabis has not been tested through large, randomized, double-blind clinical trials,” Gilman says. With McGovern Principal Research Scientist Satrajit Ghosh and MD-PhD student Debbie Burdinski, she set out to see what neuroimaging data would reveal about the impacts of this type of cannabis use.

Participants in their study were all adults seeking relief from depression, anxiety, pain, or insomnia who, prior to obtaining their medical cannabis cards, had never used cannabis at high frequencies. The researchers wanted their study to reflect the ways people really use cannabis, so participants were free choose which types of products they used, as well as how much and how often. “We told people, “Get what you want, use it you as you wish, and we’re going to look at how it may affect the brain,” Gilman explains.

Participants reported using a variety of products, but generally, they tended to choose low-potency products. Their frequency of use also varied, from less than once a month to once or more each day. Fewer than 20 percent of participants were daily users.

At the start of the study and again one year later, the research team used functional MRI scans to watch what happened in the brain while participants used three key cognitive skills: working memory, inhibitory control, and reward processing. The activity revealed on the scans showed the researchers which parts of the brain were working to perform these tasks.

Alterations in activity patterns could indicate changes in brains function. But in the 54 participants who underwent both brain scans, Gilman, Ghosh, and Burdinski found that after one year of cannabis use, brain activity during these three cognitive tasks was unchanged. Burdinski notes that many facets of cognition were not followed in the study, so some changes to brain activity could have occurred without being evident in the team’s data.

The researchers acknowledge that their study cohort, whose members were mostly female, middle-aged, and well educated, was less diverse than the population of people who use cannabis for medical symptoms. In fact, Gilman says, groups that are most vulnerable to negative consequences of cannabis may not have been well represented in the study, and it’s possible that a study of a different subgroup would have found different results.

Ghosh points out that there is still a lot to learn about the impact of cannabis, and larger studies are needed to understand its effects on the brain, including how it impacts different populations. For some individuals, he stresses, its use can have severe, debilitating effects, including symptoms of psychosis, delusions, or cannabinoid hyperemesis syndrome.

Larger studies are needed to understand cannabis’s effects on the brain and how it impacts different populations, Ghosh says. “Science can help us understand how we should be thinking about the impact of various substances or various interventions on the brain, instead of just anecdotal considerations of how they work,” he says. “Maybe there are people for whom there are changes. Now we can start teasing apart those details.”

Brains, fashion, alien life, and more: Highlights from the Cambridge Science Festival

What is it like to give birth on Mars? Can bioengineer TikTok stars win at the video game “Super Smash Brothers” while also answering questions about science? How do sheep, mouse, and human brains compare? These questions and others were asked last month when more than 50,000 visitors from across Cambridge, Massachusetts, and Greater Boston participated in the MIT Museum’s annual Cambridge Science Festival, a week-long celebration dedicated to creativity, ingenuity, and innovation. Running Monday, Sept. 23 through Sunday, Sept. 29, the 2024 edition was the largest in its history, with a dizzyingly diverse program spanning more than 300 events presented in more than 75 different venues, all free and open to the public.

Presented in partnership with the City of Cambridge and more than 250 collaborators across Greater Boston, this year’s festival comprised a wide range of interactive programs for adults, children, and families, including workshops, demos, keynote lectures, walking tours, professional networking opportunities, and expert panels. Aimed at scientists and non-scientists alike, the festival also collaborated with several local schools to offer visits from an astronaut for middle- and high-school students.

With support from dozens of local organizations, the festival was the first iteration to happen under the new leadership of Michael John Gorman, who was appointed director of the MIT Museum in January and began his position in July.

“A science festival like this has an incredible ability to unite a diverse array of people and ideas, while also showcasing Cambridge as an internationally recognized leader in science, technology, engineering, and math,” says Gorman. “I’m thrilled to have joined an institution that values producing events that foster such a strong sense of community, and was so excited to see the enthusiastic response from the tens of thousands of people who showed up and made the festival such a success.”

The 2024 Cambridge Science Festival was broad in scope, with events ranging from hands-on 3D-printing demos to concerts from the MIT Laptop Ensemble to participatory activities at the MIT Museum’s Maker Hub. This year’s programming also highlighted three carefully curated theme tracks that each encompassed more than 25 associated events:

  1. “For the Win: Games, Puzzles, and the Science of Play” (Thursday) consisted of multiple evening events clustered around Kendall Square.
  2. “Frontiers: A New Era of Space Exploration” (Friday and Saturday) featured programs throughout Boston and was co-curated by The Space Consortium, organizers of Massachusetts Space Week.
  3. “Electric Skin: Wearable Tech and the Future of Fashion” (Saturday) offered both day and evening events at the intersection of science, fabric, and fashion, taking place at The Foundry and co-curated by Boston Fashion Week and Advanced Functional Fabrics of America.

One of the discussions tied to the games-themed “For the Win” track involved artist Jeremy Couillard speaking with MIT Lecturer Mikael Jakobsson about the larger importance of games as a construct for encouraging interpersonal interaction and creating meaningful social spaces. Starting this past summer, the List Visual Arts Center has been the home of Couillard’s first-ever institutional solo exhibition, which centers around “Escape from Lavender Island,” a dystopian third-person, open-world exploration game he released in 2023 on the Steam video-game platform.

For the “Frontiers” space theme, one of the headlining events, “Is Anyone Out There?”, tackled the latest cutting-edge research and theories related to the potential existence of extraterrestrial life. The panel of local astronomers and astrophysicists included Sara Seager, the Class of 1941 Professor of Planetary Science, professor of physics, and professor of aeronautics and astronautics at MIT; Kim Arcand, an expert in astronomic visualization at the Harvard-Smithsonian Center for Astrophysics; and Michael Hecht, a research scientist and associate director of research management at MIT’s Haystack Observatory. The researchers spoke about the tools they and their peers use to try to search for extraterrestrial life, and what discovering life beyond our planet might mean for humanity.

For the “Electric Skin” fashion track, events spanned a range of topics revolving around the role that technology will play in the future of the field, including sold-out workshops where participants learned how to laser-cut and engineer “structural garments.” A panel looking at generative technologies explored how designers are using AI to spur innovation in their companies. Onur Yüce Gün, director of computational design at New Balance, also spoke on a panel with Ziyuan “Zoey” Zhu from IDEO, MIT Media Lab research scientist and architect Behnaz Farahi, and Fiorenzo Omenetto, principal investigator and director of The Tufts Silk Lab and the Frank C. Doble Professor of Engineering at Tufts University and a professor in the Biomedical Engineering Department and in the Department of Physics at Tufts.

Beyond the three themed tracks, the festival comprised an eclectic mix of interactive events and panels. Cambridge Public Library hosted a “Science Story Slam” with high-school students from 10 different states competing for $5,000 in prize money. Entrants shared 5-minute-long stories about their adventures in STEM, with topics ranging from probability to “astro-agriculture.” Judges included several MIT faculty and staff, as well as New York Times national correspondent Kate Zernike.

Elsewhere, the MIT Museum’s Gorman moderated a discussion on AI and democracy that included Audrey Tang, the former minister of digital affairs of Taiwan. The panelists explored how AI tools could combat the polarization of political discourse and increase participation in democratic processes, particularly for marginalized voices. Also in the MIT Museum, the McGovern Institute for Brain Research organized a “Decoding the Brain” event with demos involving real animal brains, while the Broad Institute of MIT and Harvard ran a “Discovery After Dark” event to commemorate the institute’s 20th anniversary. Sunday’s Science Carnival featured more than 100 demos, events, and activities, including the ever-popular “Robot Petting Zoo.”

When it first launched in 2007, the Cambridge Science Festival was by many accounts the first large-scale event of its kind across the entire United States. Similar festivals have since popped up all over the country, including the World Science Festival in New York City, the USA Science and Engineering Festival in Washington, the North Carolina Science Festival in Chapel Hill, and the San Diego Festival of Science and Engineering.

More information about the festival is available online, including opportunities to participate in next year’s events.

Brain pathways that control dopamine release may influence motor control

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

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.”

Model reveals why debunking election misinformation often doesn’t work

When an election result is disputed, people who are skeptical about the outcome may be swayed by figures of authority who come down on one side or the other. Those figures can be independent monitors, political figures, or news organizations. However, these “debunking” efforts don’t always have the desired effect, and in some cases, they can lead people to cling more tightly to their original position.

Neuroscientists and political scientists at MIT and the University of California at Berkeley have now created a computational model that analyzes the factors that help to determine whether debunking efforts will persuade people to change their beliefs about the legitimacy of an election. Their findings suggest that while debunking fails much of the time, it can be successful under the right conditions.

For instance, the model showed that successful debunking is more likely if people are less certain of their original beliefs and if they believe the authority is unbiased or strongly motivated by a desire for accuracy. It also helps when an authority comes out in support of a result that goes against a bias they are perceived to hold: for example, Fox News declaring that Joseph R. Biden had won in Arizona in the 2020 U.S. presidential election.

“When people see an act of debunking, they treat it as a human action and understand it the way they understand human actions — that is, as something somebody did for their own reasons,” says Rebecca Saxe, the John W. Jarve Professor of Brain and Cognitive Sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study. “We’ve used a very simple, general model of how people understand other people’s actions, and found that that’s all you need to describe this complex phenomenon.”

The findings could have implications as the United States prepares for the presidential election taking place on Nov. 5, as they help to reveal the conditions that would be most likely to result in people accepting the election outcome.

MIT graduate student Setayesh Radkani is the lead author of the paper, which appears today in a special election-themed issue of the journal PNAS Nexus. Marika Landau-Wells PhD ’18, a former MIT postdoc who is now an assistant professor of political science at the University of California at Berkeley, is also an author of the study.

Modeling motivation

In their work on election debunking, the MIT team took a novel approach, building on Saxe’s extensive work studying “theory of mind” — how people think about the thoughts and motivations of other people.

As part of her PhD thesis, Radkani has been developing a computational model of the cognitive processes that occur when people see others being punished by an authority. Not everyone interprets punitive actions the same way, depending on their previous beliefs about the action and the authority. Some may see the authority as acting legitimately to punish an act that was wrong, while others may see an authority overreaching to issue an unjust punishment.

Last year, after participating in an MIT workshop on the topic of polarization in societies, Saxe and Radkani had the idea to apply the model to how people react to an authority attempting to sway their political beliefs. They enlisted Landau-Wells, who received her PhD in political science before working as a postdoc in Saxe’s lab, to join their effort, and Landau suggested applying the model to debunking of beliefs regarding the legitimacy of an election result.

The computational model created by Radkani is based on Bayesian inference, which allows the model to continually update its predictions of people’s beliefs as they receive new information. This approach treats debunking as an action that a person undertakes for his or her own reasons. People who observe the authority’s statement then make their own interpretation of why the person said what they did. Based on that interpretation, people may or may not change their own beliefs about the election result.

Additionally, the model does not assume that any beliefs are necessarily incorrect or that any group of people is acting irrationally.

“The only assumption that we made is that there are two groups in the society that differ in their perspectives about a topic: One of them thinks that the election was stolen and the other group doesn’t,” Radkani says. “Other than that, these groups are similar. They share their beliefs about the authority — what the different motives of the authority are and how motivated the authority is by each of those motives.”

The researchers modeled more than 200 different scenarios in which an authority attempts to debunk a belief held by one group regarding the validity of an election outcome.

Each time they ran the model, the researchers altered the certainty levels of each group’s original beliefs, and they also varied the groups’ perceptions of the motivations of the authority. In some cases, groups believed the authority was motivated by promoting accuracy, and in others they did not. The researchers also altered the groups’ perceptions of whether the authority was biased toward a particular viewpoint, and how strongly the groups believed in those perceptions.

Building consensus

In each scenario, the researchers used the model to predict how each group would respond to a series of five statements made by an authority trying to convince them that the election had been legitimate. The researchers found that in most of the scenarios they looked at, beliefs remained polarized and in some cases became even further polarized. This polarization could also extend to new topics unrelated to the original context of the election, the researchers found.

However, under some circumstances, the debunking was successful, and beliefs converged on an accepted outcome. This was more likely to happen when people were initially more uncertain about their original beliefs.

“When people are very, very certain, they become hard to move. So, in essence, a lot of this authority debunking doesn’t matter,” Landau-Wells says. “However, there are a lot of people who are in this uncertain band. They have doubts, but they don’t have firm beliefs. One of the lessons from this paper is that we’re in a space where the model says you can affect people’s beliefs and move them towards true things.”

Another factor that can lead to belief convergence is if people believe that the authority is unbiased and highly motivated by accuracy. Even more persuasive is when an authority makes a claim that goes against their perceived bias — for instance, Republican governors stating that elections in their states had been fair even though the Democratic candidate won.

As the 2024 presidential election approaches, grassroots efforts have been made to train nonpartisan election observers who can vouch for whether an election was legitimate. These types of organizations may be well-positioned to help sway people who might have doubts about the election’s legitimacy, the researchers say.

“They’re trying to train to people to be independent, unbiased, and committed to the truth of the outcome more than anything else. Those are the types of entities that you want. We want them to succeed in being seen as independent. We want them to succeed as being seen as truthful, because in this space of uncertainty, those are the voices that can move people toward an accurate outcome,” Landau-Wells says.

The research was funded, in part, by the Patrick J. McGovern Foundation and the Guggenheim Foundation.