Author: Julie Pryor

3 Questions: On humanizing scientists

by Peter Dizikes | MIT News |

Alan Lightman has spent much of his authorial career writing about scientific discovery, the boundaries of knowledge, and remarkable findings from the world of research. His latest book “The Shape of Wonder,” co-authored with the lauded English astrophysicist Martin Rees and published this month by Penguin Random House, offers both profiles of scientists and an examination of scientific methods, humanizing researchers and making an affirmative case for the value of their work. Lightman is a professor of the practice of the humanities in MIT’s Comparative Media Studies/Writing Program; Rees is a fellow of Trinity College at Cambridge University and the UK’s Astronomer Royal. Lightman talked with MIT News about the new volume.

Q: What is your new book about?

A: The book tries to show who scientists are and how they think. Martin and I wrote it to address several problems. One is mistrust in scientists and their institutions, which is a worldwide problem. We saw this problem illustrated during the pandemic. That mistrust I think is associated with a belief by some people that scientists and their institutions are part of the elite establishment, a belief that is one feature of the populist movement worldwide. In recent years there’s been considerable misinformation about science. And, many people don’t know who scientists are.

Another thing, which is very important, is a lack of understanding about evidence-based critical thinking. When scientists get new data and information, their theories and recommendations change. But this process, part of the scientific method, is not well-understood outside of science. Those are issues we address in the book. We have profiles of a number of scientists and show them as real people, most of whom work for the benefit of society or out of intellectual curiosity, rather than being driven by political or financial interests. We try to humanize scientists while showing how they think.

Q: You profile some well-known figures in the book, as well as some lesser-known scientists. Who are some of the people you feature in it?

A: One person is a young neuroscientist, Lace Riggs, who works at the McGovern Institute for Brain Research at MIT. She grew up in difficult circumstances in southern California, decided to go into science, got a PhD in neuroscience, and works as a postdoc researching the effect of different compounds on the brain and how that might lead to drugs to combat certain mental illnesses. Another very interesting person is Magdalena Lenda, an ecologist in Poland. When she was growing up, her father sold fish for a living, and took her out in the countryside and would identify plants, which got her interested in ecology. She works on stopping invasive species. The intention is to talk about people’s lives and interests, and show them as full people.

While humanizing scientists in the book, we show how critical thinking works in science. By the way, critical thinking is not owned by scientists. Accountants, doctors, and many others use critical thinking. I’ve talked to my car mechanic about what kinds of problems come into the shop. People don’t know what causes the check engine light to go on — the catalytic converter, corroded spark plugs, etc. — so mechanics often start from the simplest and cheapest possibilities and go to the next potential problem, down the list. That’s a perfect example of critical thinking. In science, it is checking your ideas and hypotheses against data, then updating them if needed.

Q: Are there common threads linking together the many scientists you feature in the book?

A: There are common threads, but also no single scientific stereotype. There’s a wide range of personalities in the sciences. But one common thread is that all the scientists I know are passionate about what they’re doing. They’re working for the benefit of society, and out of sheer intellectual curiosity. That links all the people in the book, as well as other scientists I’ve known. I wish more people in America would realize this: Scientists are working for their overall benefit. Science is a great success story. Thanks to scientific advances, since 1900 the expected lifespan in the U.S, has increased from a little more than 45 years to almost 80 years, in just a century, largely due to our ability to combat diseases. What’s more vital than your lifespan?

This book is just a drop in the bucket in terms of what needs to be done. But we all do what we can.

International neuroscience collaboration unveils comprehensive cellular-resolution map of brain activity

by Julie Pryor |

The first comprehensive map of mouse brain activity has been unveiled by a large international collaboration of neuroscientists. Researchers from the International Brain Laboratory (IBL), including McGovern Investigator Ila Fiete, published their findings today in two papers in Nature, revealing insights into how decision-making unfolds across the entire brain in mice at single-cell resolution. This brain-wide activity map challenges the traditional hierarchical view of information processing in the brain and shows that decision-making is distributed across many regions in a highly coordinated way.

“This is the first time anyone has produced a full, brain-wide map of the activity of single neurons during decision-making,” explains Co-Founder of IBL Alexandre Pouget. “The scale is unprecedented as we recorded from over half a million neurons across mice in 12 labs, covering 279 brain areas, which together represent 95% of the mouse brain volume. The decision-making activity, and particularly reward, lit up the brain like a Christmas tree,” adds Pouget, who is also a Group Leader at the University of Geneva.

Brain-wide map showing 75,000 analyzed neurons lighting up during different stages of decision-making. At the beginning of the trial, the activity is quiet. Then it builds up in the visual areas at the back of the brain, followed by a rise in activity spreading across the brain as evidence accumulates towards a decision. Next, motor areas light up as there is movement onset and finally there is a spike in activity everywhere in the brain as the animal is rewarded.

Modeling decision-making

The brain map was made possible by a major international collaboration of neuroscientists from multiple universities, including MIT. Researchers across 12 labs used state-of-the-art silicon electrodes, called Neuropixels probes,  for simultaneous neural recordings to measure brain activity while mice were carrying out a decision-making task.

McGovern Associate Investigator Ila Fiete. Photo: Caitlin Cunningham

“Participating in the International Brain Laboratory has added new ways for our group to contribute to science,” says Fiete, who is also a professor of brain and cognitive sciences director of the K. Lisa Yang ICoN Center at MIT. “Our lab has helped standardize methods to analyze and generate robust conclusions from data. As computational neuroscientists interested in building models of how the brain works, access to brainwide recordings is incredible: the traditional approach of recording from one or a few brain areas limited our ability to build and test theories, resulting in fragmented models. Now we have the delightful but formidable task to make sense of how all parts of the brain coordinate to perform a behavior. Surprisingly, having a full view of the brain leads to simplifications in the models of decision making.”

The labs collected data from mice performing a decision-making task with sensory, motor, and cognitive components. In the task, a mouse sits in front of a screen and a light appears on the left or right side. If the mouse then responds by moving a small wheel in the correct direction, it receives a reward.

In some trials, the light is so faint that the animal must guess which way to turn the wheel, for which it can use prior knowledge: the light tends to appear more frequently on one side for a number of trials, before the high-frequency side switches. Well-trained mice learn to use this information to help them make correct guesses. These challenging trials therefore allowed the researchers to study how prior expectations influence perception and decision-making.

Brain-wide results

The first paper, “A brain-wide map of neural activity during complex behaviour,” showed that decision-making signals are surprisingly distributed across the brain, not localized to specific regions. This adds brain-wide evidence to a growing number of studies that challenge the traditional hierarchical model of brain function and emphasizes that there is constant communication across brain areas during decision-making, movement onset, and even reward. This means that neuroscientists will need to take a more holistic, brain-wide approach when studying complex behaviors in future.

Flat maps of the mouse brain showing which areas have significant changes in activity during each of three task intervals. Credit: Michael Schartner & International Brain Laboratory

“The unprecedented breadth of our recordings pulls back the curtain on how the entire brain performs the whole arc of sensory processing, cognitive decision-making, and movement generation,” says Fiete. “Structuring a collaboration that collects a large standardized dataset which single labs could not assemble is a revolutionary new direction for systems neuroscience, initiating the field into the hyper-collaborative mode that has contributed to leaps forward in particle physics and human genetics. Beyond our own conclusions, the dataset and associated technologies, which were released much earlier as part of the IBL mission, have already become a massively used resource for the entire neuroscience community.”

The second paper, “Brain-wide representations of prior information,” showed that prior expectations, our beliefs about what is likely to happen based on our recent experience, are encoded throughout the brain. Surprisingly, these expectations are not only found in cognitive areas, but also brain areas that process sensory information and control actions. For example, expectations are even encoded in early sensory areas such as the thalamus, the brain’s first relay for visual input from the eye. This supports the view that the brain acts as a prediction machine, but with expectations encoded across multiple brain structures playing a central role in guiding behavior responses. These findings could have implications for understanding conditions such as schizophrenia and autism, which are thought to be caused by differences in the way expectations are updated in the brain.

“Much remains to be unpacked: if it is possible to find a signal in a brain area, does it mean that this area is generating the signal, or simply reflecting a signal generated somewhere else? How strongly is our perception of the world is shaped by our expectations? Now we can generate some quantitative answers and begin the next phase experiments to learn about the origins of the expectation signals by intervening to modulate their activity,” says Fiete.

Looking ahead, the team at IBL plan to expand beyond their initial focus on decision-making to explore a broader range of neuroscience questions. With renewed funding in hand, IBL aims to expand its research scope and continue to support large-scale, standardized experiments.

New model of collaborative neuroscience

Officially launched in 2017, IBL introduced a new model of collaboration in neuroscience that uses a standardized set of tools and data processing pipelines shared across multiple labs, enabling the collection of massive datasets while ensuring data alignment and reproducibility. This approach to democratize and accelerate science draws inspiration from large-scale collaborations in physics and biology, such as CERN and the Human Genome Project.

All data from these studies, along with detailed specifications of the tools and protocols used for data collection, are openly accessible to the global scientific community for further analysis and research. Summaries of these resources can be viewed and downloaded on the IBL website under the sections: Data, Tools, Protocols.

This research was supported by grants from Wellcome (209558 and 216324), the Simons Foundation, The National Institutes of Health (NIH U19NS12371601), the National Science Foundation (NSF 1707398), the Gatsby Charitable Foundation (GAT3708), andby the Max Planck Society and the Humboldt Foundation.

 

Searching for self

by Jennifer Michalowski |

This story also appears in the Fall 2025 issue of BrainScan. 

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The question of how we know ourselves might seem the subject of philosophers, but it is just as much a matter of biology. As modern neuroscientists obtain an increasingly sophisticated understanding of how the brain generates emotions, responds to the external world, and learns from experience, some researchers are returning to a central question: How do we know our experiences, emotions, and physical sensations belong to us?

Curiosity about how the brain generates our sense of self has been a driving force for the research of McGovern Investigator Fan Wang. Following that curiosity has drawn Wang into diverse studies, exploring the origins of pain and the mechanisms we use to control our movements.

“We cannot pinpoint a set of active neurons and say that’s the sense of self. That still remains a mystery,” says Wang, who is also a professor of brain and cognitive sciences and co-director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT. But she and other neuroscientists are drilling down into different functions of the brain that together might generate our awareness of ourselves.

Woman wearing blue blazer smiles and gestures off camera with man in white lab coat seated next to her.
McGovern Investigator Fan Wang (right) with research scientist Vincent Prevosto, who studies brain regions implicated in whisker movement. Photo: Steph Stevens

Wang, who teaches the undergraduate course, “Neurobiology of Self,” explains that there are lots of ways to think about our sense of self, which are probably deeply integrated in the brain. Some are mostly about our physical bodies: How do we experience touch? How do we understand
where we are in space, or recognize the boundary between ourselves and rest of the world? Some consider more internal sensations, like how we experience pain or hunger. Emotion is also key to our sense of self: How do we know that anger or joy are our own, and why do these states change the way our bodies feel?

Wang can trace her initial interest in the brain’s sense of self to work she did as a graduate student in Richard Axel’s lab at Columbia University. The lab had identified receptors expressed by sensory neurons in the nose that detect odorous substances. Wang and others discovered the pathways that information about these smells takes to the brain, and how the brain distinguishes one smell from another.

Who is the “knower” of this information? “The answer,” Wang says, “is ‘I’ or ‘me.’ But understanding where I get the sense of self and how that is constructed, is what drives me to do neuroscience.”

Mechanisms of movement

In her lab at the McGovern Institute, Wang is studying how the brain controls the body’s movements, which she sees as closely tied to the awareness of our physical selves. “The reason I think I am in my body is because I can control my movement. I generate the movement. I cannot control your movement,” says Wang. “Volitional movement gives us a sense of agency, and this sense of agency resembles the sense of self.” For the mice that the group studies, one crucial type of movement comes from the whiskers, which the animals depend on as they explore their environments. Wang’s group has traced the neural circuity that controls whiskers’ rhythmic back-and-forth, which is initiated in the brainstem, where many of the body’s most vital functions are controlled. Wang describes the simple circuit as an oscillator, or a self-generated loop.

A maximum projection image showing tracked whiskers on the mouse muzzle. The right (control) side shows the back-and-forth rhythmic sweeping of the whiskers, while the experimental side where the whisking oscillator neurons are silenced, the whiskers move very little. Image: Wang Lab

Once it’s started, “the movement can go on unless some other signals stop it,” she says. The movement the circuit generates is simple but voluntary, and can be fine-tuned based on the sensory feedback the whiskers relay back to the brain. They’ve also been investigating how mice move the larynx to generate the squeaks and calls they use to communicate. These intentional movements must be coordinated with the ongoing cycles of respiration since we produce normal sounds only during expiration. Wang’s team has found neurons in the brainstem that generate vocalization-specific movements, and also discovered how respiration-controlling neural circuits can override them, ensuring that breathing is prioritized.

Wang says understanding the circuitry that controls these simple movements sets the stage for figuring out how the brain modifies activity in those circuits to create more complex, intentional movements. “That brings me closer to understanding where this volition is generated — and closer to this sense of self,” she says.

Emotional pain

Still, she knows that volitional movements — even those generated in response to perceptions of the environment — do not, on their own, define a sense of self. As a counterexample, she looks to self-driving cars: “There’s sensory information coming into the central computer, which then generates a motor output — where to drive, where to turn, where to stop. But none of us think a Waymo taxi has a sense of self.”

Wang says when she pondered the ways in which AI-powered cars lack a sense of self, she began thinking about emotions and pain. “If the self-driving Waymo crashes, it will not feel pain,” she says. “But if we hurt ourselves, we will feel pain. And we will hate that, and then we’ll learn.” So her lab is also exploring how the nervous system generates pain perception, including the emotional response that it evokes.

Ensembles of neurons in the amygdala activated by general anesthesia. Image: Fan Wang

In both humans and mice, pain causes emotional suffering that can be recognized and measured through changes in body functions like heart rate and blood pressure. With funding from the K. Lisa Yang Brain-Body Center at MIT, Wang’s lab is carefully tracking these involuntary, or autonomic, functions to gain a more complete understanding of pain’s emotional impact. This approach has helped clarify the role of pain-suppressing neurons in the brain’s amygdala — an important emotion-processing center — that Wang’s team discovered in 2020. When researchers selectively activate those cells in mice, the animals’ behavior makes it clear that the neurons are suppressing pain. Now, the group has learned that activating these neurons suppresses the autonomic response to pain.

Wang says there’s hope that modulating pain’s emotional response might be a way to treat chronic pain in patients. She explains that some patients with damage to another one of the brain’s emotional centers, the cingulate cortex, feel painful stimuli, but experience them as merely intense sensations. That suggests that it might be possible to modulate the emotional response to pain to eliminate patients’ suffering, without blocking the protective information that pain can provide.

The team has also been focusing on another set of anesthesia-activated neurons, which they have found suppress anxiety. When anxiety-suppressing neurons are activated in mice, the animals’ heart rates slow and they become more willing to explore bright, open spaces. Another anxiety-associated measure — heart rate variability — increases. Wang explains that this change is particularly significant: “If you have persistent low heart rate variability, especially in veterans, that is a very good predictor for anxiety developing into depression in the future,” she says.

The team’s findings, which suggest that changes in autonomic functions may themselves relieve anxiety, point toward potential new targets for anti-anxiety therapies. And by highlighting the connection between emotion and bodily responses, they offer more clues about our sense of self. “These neurons are now changing some high-level concept about anxiety,” Wang points out.

That link between emotion and body seems to Wang to be key to the sense of self. The big questions remain unanswered, but that simply stokes her curiosity. “I can be aware of my bodily responses: I am aware of ‘I am anxious’ or ‘I am in pain.’ I can see the pathways from which stimuli go into these nervous systems and come back down to the body and control the response. But I still don’t know who is the person — the knower,” she says. “I haven’t found it, so I’m going to keep looking.”

New gift expands mental illness studies at Poitras Center for Psychiatric Disorders Research

by Julie Pryor |

One in every eight people—970 million globally—live with mental illness, according to the World Health Organization, with depression and anxiety being the most common mental health conditions worldwide. Existing therapies for complex psychiatric disorders like depression, anxiety, and schizophrenia have limitations, and federal funding to address these shortcomings is growing increasingly uncertain.

Jim and Pat Poitras
James and Patricia Poitras at an event co-hosted by the McGovern Institute and Autism Speaks. Photo: Justin Knight

Patricia and James Poitras ’63 have committed $8 million to the Poitras Center for Psychiatric Disorders Research to launch pioneering research initiatives aimed at uncovering the brain basis of major mental illness and accelerating the development of novel treatments.

“Federal funding rarely supports the kind of bold, early-stage research that has the potential to transform our understanding of psychiatric illness. Pat and I want to help fill that gap—giving researchers the freedom to follow their most promising leads, even when the path forward isn’t guaranteed,” says James Poitras, who is chair of the McGovern Institute Board.

Their latest gift builds upon their legacy of philanthropic support for psychiatric disorders research at MIT, which now exceeds $46 million.

“With deep gratitude for Jim and Pat’s visionary support, we are eager to launch a bold set of studies aimed at unraveling the neural and cognitive underpinnings of major mental illnesses,” says Robert Desimone, director of the McGovern Institute, home to the Poitras Center. “Together, these projects represent a powerful step toward transforming how we understand and treat mental illness.”

A legacy of support

Soon after joining the McGovern Institute Leadership Board in 2006, the Poitrases made a $20 million commitment to establish the Poitras Center for Psychiatric Disorders Research at MIT. The center’s goal, to improve human health by addressing the root causes of complex psychiatric disorders, is deeply personal to them both.

“We had decided many years ago that our philanthropic efforts would be directed towards psychiatric research. We could not have imagined then that this perfect synergy between research at MIT’s McGovern Institute and our own philanthropic goals would develop,” recalls Patricia.

The center supports research at the McGovern Institute and collaborative projects with institutions such as the Broad Institute, McLean Hospital, Mass General Brigham and other clinical research centers. Since its establishment in 2007, the center has enabled advances in psychiatric research including the development of a machine learning “risk calculator” for bipolar disorder, the use of brain imaging to predict treatment outcomes for anxiety, and studies demonstrating that mindfulness can improve mental health in adolescents.

A scientist speaks at a podium with an image of DNA on the wall behind him.
Feng Zhang, the James and Patricia Poitras Professor of Neuroscience at MIT, delivers a lecture at the Poitras Center’s 10th anniversary celebration in 2017. Photo: Justin Knight

For the past decade, the Poitrases have also fueled breakthroughs in McGovern Investigator Feng Zhang’s lab, backing the invention of powerful CRISPR systems and other molecular tools that are transforming biology and medicine. Their support has enabled the Zhang team to engineer new delivery vehicles for gene therapy, including vehicles capable of carrying genetic payloads that were once out of reach. The lab has also advanced innovative RNA-guided gene engineering tools such as NovaIscB, published in Nature Biotechnology in May 2025. These revolutionary genome editing and delivery technologies hold promise for the next generation of therapies needed for serious psychiatric illness.

In addition to fueling research in the center, the Poitras family has gifted two endowed professorships—the James and Patricia Poitras Professor of Neuroscience at MIT, currently held by Feng Zhang, and the James W. (1963) and Patricia T. Poitras Professor of Brain and Cognitive Sciences at MIT, held by Guoping Feng—and an annual postdoctoral fellowship at the McGovern Institute.

New initiatives at the Poitras Center

The Poitras family’s latest commitment to the Poitras Center will launch an ambitious set of new projects that bring together neuroscientists, clinicians, and computational experts to probe underpinnings of complex psychiatric disorders including schizophrenia, anxiety, and depression. These efforts reflect the center’s core mission: to speed scientific discovery and therapeutic innovation in the field of psychiatric brain disorders research.

McGovern cognitive neuroscientists Evelina Fedorenko PhD ‘07 and Nancy Kanwisher ’80, PhD ’86, the Walter A. Rosenblith Professor of Cognitive Neuroscience—in collaboration with psychiatrist Ann Shinn of McLean Hospital—will explore how altered inner speech and reasoning contribute to the symptoms of schizophrenia. They will collect functional MRI data from individuals diagnosed with schizophrenia and matched controls as they perform reasoning tasks. The goal is to identify the brain activity patterns that underlie impaired reasoning in schizophrenia, a core cognitive disruption in the disorder.

Three women wearing name tags smile for hte camera.
Patricia Poitras (center) with McGovern Investigators Nancy Kanwisher ’80, PhD ’86 (left) and Martha Constantine-Paton (right) at the Poitras Center’s 10th anniversary celebration in 2017. Photo: Justin Knight

A complementary line of investigation will focus on the role of inner speech—the “voice in our head” that shapes thought and self-awareness. The team will conduct a large-scale online behavioral study of neurotypical individuals to analyze how inner speech characteristics correlate with schizophrenia-spectrum traits. This will be followed by neuroimaging work comparing brain architecture among individuals with strong or weak inner voices and people with schizophrenia, with the aim of discovering neural markers linked to self-talk and disrupted cognition.

A different project led by McGovern neuroscientist Mark Harnett and 2024–2026 Poitras Center Postdoctoral Fellow Cynthia Rais focuses on how ketamine—an increasingly used antidepressant—alters brain circuits to produce rapid and sustained improvements in mood. Despite its clinical success, ketamine’s mechanisms of action remain poorly understood. The Harnett lab is using sophisticated tools to track how ketamine affects synaptic communication and large-scale brain network dynamics, particularly in models of treatment-resistant depression. By mapping these changes at both the cellular and systems levels, the team hopes to reveal how ketamine lifts mood so quickly—and inform the development of safer, longer-lasting antidepressants.

Guoping Feng is leveraging a new animal model of depression to uncover the brain circuits that drive major depressive disorder. The new animal model provides a powerful system for studying the intricacies of mood regulation. Feng’s team is using state-of-the-art molecular tools to identify the specific genes and cell types involved in this circuit, with the goal of developing targeted treatments that can fine-tune these emotional pathways.

“This is one of the most promising models we have for understanding depression at a mechanistic level,” says Feng, who is also associate director of the McGovern Institute. “It gives us a clear target for future therapies.”

Another novel approach to treating mood disorders comes from the lab of James DiCarlo, the Peter de Florez Professor of Neuroscience at MIT, who is exploring the brain’s visual-emotional interface as a therapeutic tool for anxiety. The amygdala, a key emotional center in the brain, is heavily influenced by visual input. DiCarlo’s lab is using advanced computational models to design visual scenes that may subtly shift emotional processing in the brain—essentially using sight to regulate mood. Unlike traditional therapies, this strategy could offer a noninvasive, drug-free option for individuals suffering from anxiety.

Together, these projects exemplify the kind of interdisciplinary, high-impact research that the Poitras Center was established to support.

“Mental illness affects not just individuals, but entire families who often struggle in silence and uncertainty,” adds Patricia. “Our hope is that Poitras Center scientists will continue to make important advancements and spark novel treatments for complex mental health disorders and most of all, give families living with these conditions a renewed sense of hope for the future.”

Learning from punishment

by Jennifer Michalowski |

From toddlers’ timeouts to criminals’ prison sentences, punishment reinforces social norms, making it known that an offender has done something unacceptable. At least, that is usually the intent—but the strategy can backfire. When a punishment is perceived as too harsh, observers can be left with the impression that an authority figure is motivated by something other than justice.

It can be hard to predict what people will take away from a particular punishment, because everyone makes their own inferences not just about the acceptability of the act that led to the punishment, but also the legitimacy of the authority who imposed it. A new computational model developed by scientists at MIT’s McGovern Institute makes sense of these complicated cognitive processes, recreating the ways people learn from punishment and revealing how their reasoning is shaped by their prior beliefs.

Their work, reported August 4 in the journal PNAS, explains how a single punishment can send different messages to different people and even strengthen the opposing viewpoints of groups who hold different opinions about authorities or social norms.

Modeling punishment

“The key intuition in this model is the fact that you have to be evaluating simultaneously both the norm to be learned and the authority who’s punishing,” says McGovern Investigator and John W. Jarve Professor of Brain and Cognitive Sciences Rebecca Saxe, who led the research. “One really important consequence of that is even where nobody disagrees about the facts—everybody knows what action happened, who punished it, and what they did to punish it—different observers of the same situation could come to different conclusions.”

For example, she says, a child who is sent to timeout after biting a sibling might interpret the event differently than the parent. One might see the punishment as proportional and important, teaching the child not to bite. But if the biting, to the toddler, seemed a reasonable tactic in the midst of a squabble, the punishment might be seen as unfair, and the lesson will be lost.

People draw on their own knowledge and opinions when they evaluate these situations—but to study how the brain interprets punishment, Saxe and graduate student Setayesh Radkani wanted to take those personal ideas out of the equation. They needed a clear understanding of the beliefs that people held when they observed a punishment, so they could learn how different kinds of information altered their perceptions. So Radkani set up scenarios in imaginary villages where authorities punished individuals for actions that had no obvious analog in the real world.

Woman in red sweater smiling to camera
Graduate student Setayesh Radkani uses tools from psychology, cognitive neuroscience and machine learning to understand the social and moral mind. Photo: Caitlin Cunningham

Participants observed these scenarios in a series of experiments, with different information offered in each one. In some cases, for example, participants were told that the person being punished was either an ally or competitor of the authority, whereas in other cases, the authority’s possible bias was left ambiguous.

“That gives us a really controlled setup to vary prior beliefs,” Radkani explains. “We could ask what people learn from observing punitive decisions with different severities, in response to acts that vary in their level of wrongness, by authorities that vary in their level of different motives.”

For each scenario, participants were asked to evaluate four factors: how much the authority figure cared about justice; the selfishness of the authority; the authority’s bias for or against the individual being punished; and the wrongness of the punished act. The research team asked these questions when participants were first introduced to the hypothetical society, then tracked how their responses changed after they observed the punishment. Across the scenarios, participants’ initial beliefs about the authority and the wrongness of the act shaped the extent to which those beliefs shifted after they observed the punishment.

Radkani was able to replicate these nuanced interpretations using a cognitive model framed around an idea that Saxe’s team has long used to think about how people interpret the actions of others. That is, to make inferences about others’ intentions and beliefs, we assume that people choose actions that they expect will help them achieve their goals.

To apply that concept to the punishment scenarios, Radkani developed a model that evaluates the meaning of a punishment (an action aimed at achieving a goal of the authority) by considering the harm associated with that punishment; its costs or benefits to the authority; and its proportionality to the violation. By assessing these factors, along with prior beliefs about the authority and the punished act, the model was able to predict people’s responses to the hypothetical punishment scenarios, supporting the idea that people use a similar mental model. “You need to have them consider those things, or you can’t make sense of how people understand punishment when they observe it,” Saxe says.

Even though the team designed their experiments to preclude preconceived ideas about the people and actions in their imaginary villages, not everyone drew the same conclusions from the punishments they observed. Saxe’s group found that participants’ general attitudes toward authority influenced their interpretation of events. Those with more authoritarian attitudes—assessed through a standard survey—tended to judge punished acts as more wrong and authorities as more motivated by justice than other observers.

“If we differ from other people, there’s a knee-jerk tendency to say, ‘either they have different evidence from us, or they’re crazy,’” Saxe says. Instead, she says, “It’s part of the way humans think about each other’s actions.”

“When a group of people who start out with different prior beliefs get shared evidence, they will not end up necessarily with shared beliefs. That’s true even if everybody is behaving rationally,” says Saxe.

This way of thinking also means that the same action can simultaneously strengthen opposing viewpoints. The Saxe lab’s modeling and experiments showed that when those viewpoints shape individuals’ interpretations of future punishments, the groups’ opinions will continue to diverge. For instance, a punishment that seems too harsh to a group who suspects an authority is biased can make that group even more skeptical of the authority’s future actions. Meanwhile, people who see the same punishment as fair and the authority as just will be more likely to conclude that the authority figure’s future actions are also just. “You will get a vicious cycle of polarization, staying and actually spreading to new things,” says Radkani.

The researchers say their findings point toward strategies for communicating social norms through punishment. “It is exactly sensible in our model to do everything you can to make your action look like it’s coming out of a place of care for the long-term outcome of this individual, and that it’s proportional to the norm violation they did,” Saxe says. “That is your best shot at getting a punishment interpreted pedagogically, rather than as evidence that you’re a bully.”

Nevertheless, she says that won’t always be enough. “If the beliefs are strong the other way, it’s very hard to punish and still sustain a belief that you were motivated by justice.”

This study was funded, in part, by the Patrick J McGovern Foundation.

How the brain distinguishes oozing fluids from solid objects

Anne Trafton |

Imagine a ball bouncing down a flight of stairs. Now think about a cascade of water flowing down those same stairs. The ball and the water behave very differently, and it turns out that your brain has different regions for processing visual information about each type of physical matter.

In a new study, MIT neuroscientists have identified parts of the brain’s visual cortex that respond preferentially when you look at “things” — that is, rigid or deformable objects like a bouncing ball. Other brain regions are more activated when looking at “stuff” — liquids or granular substances such as sand.

This distinction, which has never been seen in the brain before, may help the brain plan how to interact with different kinds of physical materials, the researchers say.

“When you’re looking at some fluid or gooey stuff, you engage with it in different way than you do with a rigid object. With a rigid object, you might pick it up or grasp it, whereas with fluid or gooey stuff, you probably are going to have to use a tool to deal with it,” says Nancy Kanwisher, the Walter A. Rosenblith Professor of Cognitive Neuroscience; a member of the McGovern Institute for Brain Research and MIT’s Center for Brains, Minds, and Machines; and the senior author of the study.

MIT postdoc Vivian Paulun, who is joining the faculty of the University of Wisconsin at Madison this fall, is the lead author of the paper, which appears today in the journal Current Biology. RT Pramod, an MIT postdoc, and Josh Tenenbaum, an MIT professor of brain and cognitive sciences, are also authors of the study.

Stuff vs. things

Decades of brain imaging studies, including early work by Kanwisher, have revealed regions in the brain’s ventral visual pathway that are involved in recognizing the shapes of 3D objects, including an area called the lateral occipital complex (LOC). A region in the brain’s dorsal visual pathway, known as the frontoparietal physics network (FPN), analyzes the physical properties of materials, such as mass or stability.

Although scientists have learned a great deal about how these pathways respond to different features of objects, the vast majority of these studies have been done with solid objects, or “things.”

“Nobody has asked how we perceive what we call ‘stuff’ — that is, liquids or sand, honey, water, all sorts of gooey things. And so we decided to study that,” Paulun says.

These gooey materials behave very differently from solids. They flow rather than bounce, and interacting with them usually requires containers and tools such as spoons. The researchers wondered if these physical features might require the brain to devote specialized regions to interpreting them.

To explore how the brain processes these materials, Paulun used a software program designed for visual effects artists to create more than 100 video clips showing different types of things or stuff interacting with the physical environment. In these videos, the materials could be seen sloshing or tumbling inside a transparent box, being dropped onto another object, or bouncing or flowing down a set of stairs.

The researchers used functional magnetic resonance imaging (fMRI) to scan the visual cortex of people as they watched the videos. They found that both the LOC and the FPN respond to “things” and “stuff,” but that each pathway has distinctive subregions that respond more strongly to one or the other.

“Both the ventral and the dorsal visual pathway seem to have this subdivision, with one part responding more strongly to ‘things,’ and the other responding more strongly to ‘stuff,’” Paulun says. “We haven’t seen this before because nobody has asked that before.”

Roland Fleming, a professor of experimental psychology at Justus Liebig University of Geissen, described the findings as a “major breakthrough in the scientific understanding of how our brains represent the physical properties of our surrounding world.”

“We’ve known the distinction exists for a long time psychologically, but this is the first time that it’s been really mapped onto separate cortical structures in the brain. Now we can investigate the different computations that the distinct brain regions use to process and represent objects and materials,” says Fleming, who was not involved in the study.

Physical interactions

The findings suggest that the brain may have different ways of representing these two categories of material, similar to the artificial physics engines that are used to create video game graphics. These engines usually represent a 3D object as a mesh, while fluids are represented as sets of particles that can be rearranged.

“The interesting hypothesis that we can draw from this is that maybe the brain, similar to artificial game engines, has separate computations for representing and simulating ‘stuff’ and ‘things.’ And that would be something to test in the future,” Paulun says.

Portrait of smiling woman wearing a grey sweater.
McGovern Institute postdoc Vivian Paulun, who is joining the faculty of the University of Wisconsin at Madison in the fall of 2025, is the lead author of the “things vs. stuff” paper, which appears today in the journal Current Biology. Photo: Steph Stevens

The researchers also hypothesize that these regions may have developed to help the brain understand important distinctions that allow it to plan how to interact with the physical world. To further explore this possibility, the researchers plan to study whether the areas involved in processing rigid objects are also active when a brain circuit involved in planning to grasp objects is active.

They also hope to look at whether any of the areas within the FPN correlate with the processing of more specific features of materials, such as the viscosity of liquids or the bounciness of objects. And in the LOC, they plan to study how the brain represents changes in the shape of fluids and deformable substances.

The research was funded by the German Research Foundation, the U.S. National Institutes of Health, and a U.S. National Science Foundation grant to the Center for Brains, Minds, and Machines.

 

Adolescents’ willingness to explore is shaped by socioeconomic status

by Jennifer Michalowski |

Exploration is essential to learning—and a new study from scientists at MIT’s McGovern Institute suggests that students may be less willing to explore if they come from a low socioeconomic environment. The study, which focused on adolescents and was published July 9, 2025, in the journal Nature Communications, shows how differences in learning strategies might contribute to socioeconomic-related disparities in academic achievement.

Students with low socioeconomic status (SES)—a measure that takes into account parents’ income levels and educational attainment—tend to lag behind their higher-SES peers academically. Limited resources at home can restrict access to educational tools and experiences, likely contributing to these disparities. But the new study, led by McGovern Institute Investigator John Gabrieli, shows that students from low-SES backgrounds may approach learning differently, too.

“We often think about external factors when we think about socioeconomic differences in learning, but kids’ mindsets and internal factors can also play a role,” says Alexandra Decker, a postdoctoral fellow in Gabrieli’s lab who ran the study. Understanding such differences can help educators develop strategies to reduce disparities and help all students succeed.

The value of exploration

Exploration is a vital part of development, particularly during adolescence. By trying new things and testing limits, children begin to find their way in the world, discovering the subjects and experiences that motivate them. That’s important for obtaining new knowledge, both in and out of school. “There’s a lot of research suggesting that exploration is a really important mechanism that children use for learning,” Decker says. “Exploring their environment really broadly and making mistakes helps them get the feedback that they need for learning,” she says.

Because the outcomes of exploration are unknown, this way of interacting with the world involves risk. “If you try something new, the outcome is uncertain, and it could lead to a bad outcome before things get better. You might lose out, at least in the short term. ” Decker says.

At school, students can explore in a variety of ways, such as by asking questions in class or taking on courses in unfamiliar subjects. Both are opportunities to learn something new, though they may seem less safe than sitting quietly and sticking to more comfortable coursework. Decker points out that this kind of exploration might feel particularly risky when students feel they lack the resources to compensate if things don’t go well.

“If you’re in an environment that’s really enriching, you have resources to compensate for challenges that might be accrued through exploring. If you take a new course and you struggle, you can use your resources to get a tutor and overcome these challenges. Your environment can support exploration and its costs,” she says. “But if you’re in an environment where you don’t have resources to compensate for bad outcomes, you might not take that course that could lead to unknown outcomes.”

Risk-benefit analysis

To investigate the relationship between SES and exploration, Gabrieli’s team had students play a computer game in which they earned points for pumping up balloons as much as possible without popping them. The most successful strategy was to explore the limits early on by pumping the first balloons until they popped, thereby learning when to stop with future balloons. A less exploratory approach could keep all the balloons intact, but earn fewer points over the course of the game.

The students who participated in the study were between the ages of 12 and 14 and came from families with a wide range of SES. Those from lower-SES backgrounds were less likely to explore in the balloon pumping task, resulting in lower outcomes in the game. What’s more, the researchers found a relationship between students’ exploration in the game and their real-world academic performance. Those who explored the least in the balloon-popping game had lower grades than students who explored more. For students at lower-SES levels, reduced exploration also correlated to lower scores on standardized tests of academic skills.

The researchers took a closer look at the data to investigate why some students explored more than others in their game. Their analysis indicated that students who were reluctant to explore were more strongly motivated by avoiding losses than students who had pushed the limits as they pumped their balloons.

The finding suggests that potential losses might be particularly distressing to lower-SES students, says Gabrieli, who is also the Grover Hermann Professor of Health Sciences and Technology and a professor of brain and cognitive sciences at MIT. Decker adds students from less affluent backgrounds may have found losses to be more consequential than they are for students whose families have more resources, so it makes sense that those students might take greater pains to avoid them.

This is not the first time Gabrieli’s group has found that evidence of differences in the ways students from different socioeconomic backgrounds make decisions. In a brain imaging study published last year, they found that the brains of adolescents from low-SES backgrounds respond less to rewards than the brains of their higher-SES peers. “How you think about the world—in terms of what’s rewarding, risks worth taking or not taking—seems strongly influenced by the environment that you’re growing up in,” he says.

Decker notes that regardless of SES, students in the study were generally more willing to explore when they had experienced more recent successes in the task. This finding, along with what the team learned about how loss aversion curtails exploration, suggest strategies that educators might use to encourage more exploration in the classroom. “Low-stakes opportunities for kids to engage in exploratory risk-taking with positive feedback could go a long way to helping kids feel more comfortable exploring,” Decker says.

 

MIT’s McGovern Institute and Department of Brain and Cognitive Sciences welcome new faculty member Sven Dorkenwald

by Julie Pryor |

The McGovern Institute and the Department of Brain and Cognitive Sciences are pleased to announce the appointment of Sven Dorkenwald as an assistant professor starting in January 2026. A trailblazer in the field of computational neuroscience, Dorkenwald is recognized for his leadership in connectomics—an emerging discipline focused on reconstructing and analyzing neural circuitry at unprecedented scale and detail. 

“We are thrilled to welcome Sven to MIT” says McGovern Institute Director Robert Desimone. “He brings visionary science and a collaborative spirit to a rapidly advancing area of brain and cognitive sciences and his appointment strengthens MIT’s position at the forefront of brain research.” 

Dorkenwald’s research is driven by a bold vision: to develop and apply cutting-edge computational methods that reveal how brain circuits are organized and how they give rise to complex computations. His innovative work has led to transformative advances in the reconstruction of connectomes (detailed neural maps) from nanometer-scale electron microscopy images. He has championed open team science and data sharing and played a central role in producing the first connectome of an entire fruit fly brain—a groundbreaking achievement that is reshaping our understanding of sensory processing and brain circuit function. 

“Sven is a rising leader in computational neuroscience who has already made significant contributions toward advancing our understanding of the brain,” says Michale Fee, the Glen V. and Phyllis F. Dorflinger Professor of Neuroscience, and Department Head of Brain and Cognitive Sciences. “He brings a combination of technical expertise, a collaborative mindset, and a strong commitment to open science that will be invaluable to our department. I’m pleased to welcome him to our community and look forward to the impact he will have.” 

Dorkenwald earned his BS in physics in 2014 and MS in computer engineering in 2017 from the University of Heidelberg, Germany. He began his research in connectomics as an undergraduate in the group of Winfried Denk at the Max Planck Institute for Medical Research and Max Planck Institute of Neurobiology.  Dorkenwald went on to complete his PhD at Princeton University in 2023, where he studied both computer science and neuroscience under the mentorship of Sebastian Seung and Mala Murthy. 

All 139,255 neurons in the brain of an adult fruit fly reconstructed by the FlyWire Consortium, with each neuron uniquely color-coded. Render by Tyler Sloan. Image: Sven Dorkenwald

As a PhD student at Princeton, Dorkenwald spearheaded the FlyWire Consortium, a group of more than 200 scientists, gamers, and proofreaders who combined their skills to create the fruit fly connectome. More than 20 million scientific images of the adult fruit fly brain  were added to an AI model that traced each neuron and synapse in exquisite detail. Members of the consortium then checked the results produced by the AI model and pieced them together into a complete, three-dimensional map. With over 140,000 neurons, it is the most complex brain completely mapped to date. The findings were published in a special issue of Nature in 2024. 

Dorkenwald’s work also played a key role in the MICrONS’ consortium effort to reconstruct a cubic millimeter connectome of the mouse visual cortex. Within the MICrONS effort, he co-lead the development of the software infrastructure, CAVE, that enables scientists to collaboratively edit and analyze large connectomics datasets, including FlyWire’s. The findings of the MICrONS consortium were published in a special issue of Nature in 2025. 

Dorkenwald is currently a Shanahan Fellow at the Allen Institute and the University of Washington. He also serves as a visiting faculty researcher at Google Research, where he has been developing machine learning approaches for the annotation of cell reconstructions as part of the Neuromancer team led by Viren Jain.  

As an investigator at the McGovern Institute and an assistant professor in the department of brain and cognitive sciences at MIT, Dorkenwald  plans to develop computational approaches to overcome challenges in scaling connectomics to whole mammalian brains with the goal of advancing our mechanistic understanding of neuronal circuits and analyzing how they compare across regions and species. 

 

Feng Zhang elected to EMBO membership

by Julie Pryor |

The European Molecular Biology Organization (EMBO), a professional non-profit organization dedicated to promoting international research in life sciences, announced its new members today. Among the 69 new members recognized for their outstanding achievements is Feng Zhang, the James and Patricia Poitras Professor of Neuroscience at MIT and an investigator at the McGovern Institute.

Zhang, who is also a core member of the Broad Institute, a professor of brain and cognitive sciences and biological engineering at MIT, and a Howard Hughes Medical Institute investigator, is a molecular biologist focused on improving human health. He played an integral role in pioneering the use of CRISPR-Cas9 for genome editing in human cells, including working with Stuart Orkin to develop Casgevy, the first CRISPR-based therapeutic approved for clinical use. His team is currently discovering new ways to modify cellular function and activity—including the restoration of diseased, stressed, or aged cells to a more healthful state.

Zhang has been elected to EMBO as an associate member, where he joins a community of more than 2,100 international life scientists that have demonstrated research excellence in their fields.

“A major strength of EMBO lies in the excellence and dedication of its members,” says EMBO Director Fiona Watt. “Science thrives on global collaboration, and the annual election of the new EMBO members and associate members brings fresh energy and inspiration to our community. We are honoured to welcome this remarkable group of scientists to the EMBO Membership. Their ideas and contributions will enrich the organization and help advance the life sciences internationally.”

The 60 new EMBO members in 2025 are based in 18 member states of the EMBC, the intergovernmental organization that funds the main EMBO programs and activities. The nine new EMBO associate members, including Zhang, are based in six countries outside Europe. In total, 29 (42%) of the new members are women and 40 (58%) are men.

The new members will be formally welcomed at the next EMBO Members’ Meeting in Heidelberg, Germany, on 22-24 October 2025.

Rationale engineering generates a compact new tool for gene therapy

by Jennifer Michalowski |

Scientists at the McGovern Institute and the Broad Institute of MIT and Harvard have reengineered a compact RNA-guided enzyme they found in bacteria into an efficient, programmable editor of human DNA. The protein they created, called NovaIscB, can be adapted to make precise changes to the genetic code, modulate the activity of specific genes, or carry out other editing tasks. Because its small size simplifies delivery to cells, NovaIscB’s developers say it is a promising candidate for developing gene therapies to treat or prevent disease.

The study was led by McGovern Institute investigator Feng Zhang, who is also the James and Patricia Poitras Professor of Neuroscience at MIT, a Howard Hughes Medical Institute investigator, and a core member of the Broad Institute. Zhang and his team reported their work today in the journal Nature Biotechnology.

Compact tools

NovaIscB is derived from a bacterial DNA cutter that belongs to a family of proteins called IscBs, which Zhang’s lab discovered in 2021. IscBs are a type of OMEGA system, the evolutionary ancestors to Cas9, which is part of the bacterial CRISPR system that Zhang and others have developed into powerful genome-editing tools. Like Cas9, IscB enzymes cut DNA at sites specified by an RNA guide. By reprogramming that guide, researchers can redirect the enzymes to target sequences of their choosing.

IscBs had caught the team’s attention not only because they share key features of CRISPR’s DNA-cutting Cas9, but also because they are a third of its size. That would be an advantage for potential gene therapies: Compact tools are easier to deliver to cells, and with a small enzyme, researchers would have more flexibility to tinker, potentially adding new functionalities without creating tools that were too bulky for clinical use.

From their initial studies of IscBs, researchers in Zhang’s lab knew that some members of the family could cut DNA targets in human cells. None of the bacterial proteins worked well enough to be deployed therapeutically, however: The team would have to modify an IscB to ensure it could edit targets in human cells efficiently without disturbing the rest of the genome.

To begin that engineering process, Soumya Kannan, a graduate student in Zhang’s lab who is now a junior fellow at the Harvard Society of Fellows, and postdoctoral fellow Shiyou Zhu first searched for an IscB that would make good starting point. They tested nearly 400 different IscB enzymes that can be found in bacteria. Ten were capable of editing DNA in human cells.

Even the most active of those would need to be enhanced to make it a useful genome editing tool. The challenge would be increasing the enzyme’s activity, but only at the sequences specified by its RNA guide. If the enzyme became more active, but indiscriminately so, it would cut DNA in unintended places. “The key is to balance the improvement of both activity and specificity at the same time,” explains Zhu.

Zhu notes that bacterial IscBs are directed to their target sequences by relatively short RNA guides, which makes it difficult to restrict the enzyme’s activity to a specific part of the genome. If an IscB could be engineered to accommodate a longer guide, it would be less likely to act on sequences beyond its intended target.

To optimize IscB for human genome editing, the team leveraged information that graduate student Han Altae-Tran, who is now a postdoctoral fellow at the University of Washington, had learned about the diversity of bacterial IscBs and how they evolved. For instance, the researchers noted that IscBs that worked in human cells included a segment they called REC, which was absent in other IscBs. They suspected the enzyme might need that segment to interact with the DNA in human cells. When they took a closer look at the region, structural modeling suggested that by slightly expanding part of the protein, REC might also enable IscBs to recognize longer RNA guides.

Based on these observations, the team experimented with swapping in parts of REC domains from different IscBs and Cas9s, evaluating how each change impacted the protein’s function. Guided by their understanding of how IscBs and Cas9s interact with both DNA and their RNA guides, the researchers made additional changes, aiming to optimize both efficiency and specificity.

In the end, they generated a protein they called NovaIscB, which was over 100 times more active in human cells than the IscB they had started with and that had demonstrated good specificity for its targets.

Kannan and Zhu constructed and screened hundreds of new IscBs before arriving at NovaIscB—and every change they made to the original protein was strategic. Their efforts were guided by their team’s knowledge of IscBs’ natural evolution as well as predictions of how each alteration would impact the protein’s structure, made using an artificial intelligence tool called AlphaFold2. Compared to traditional methods of introducing random changes into a protein and screening for their effects, this rational engineering approach greatly accelerated the team’s ability to identify a protein with the features they were looking for.

The team demonstrated that NovaIscB is a good scaffold for a variety of genome editing tools. “It biochemically functions very similarly to Cas9, and that makes it easy to port over tools that were already optimized with the Cas9 scaffold,” Kannan says. With different modifications, the researchers used NovaIscB to replace specific letters of the DNA code in human cells and to change the activity of targeted genes.

Importantly, the NovaIscB-based tools are compact enough to be easily packaged inside a single adeno-associated virus (AAV)—the vector most commonly used to safely deliver gene therapy to patients. Because they are bulkier, tools developed using Cas9 can require a more complicated delivery strategy.

Demonstrating NovaIscB’s potential for therapeutic use, Zhang’s team created a tool called OMEGAoff that adds chemical markers to DNA to dial down the activity of specific genes. They programmed OMEGAoff to repress a gene involved in cholesterol regulation, then used AAV to deliver the system to the livers of mice, leading to lasting reductions in cholesterol levels in the animals’ blood.

The team expects that NovaIscB can be used to target genome editing tools to most human genes, and look forward to seeing how other labs deploy the new technology. They also hope others will adopt their evolution-guided approach to rational protein engineering. “Nature has such diversity and its systems have different advantages and disadvantages,” Zhu says. “By learning about that natural diversity, we can make the systems we are trying to engineer better and better.”

This study was funded in part by the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT, Broad Institute Programmable Therapeutics Gift Donors, Pershing Square Foundation, William Ackman, Neri Oxman, the Phillips family, and J. and P. Poitras.