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The brain’s language network is more extensive than previously thought

Anne Trafton |

For decades, neuroscientists have known that specific regions in the brain’s left hemisphere are responsible for processing language. However, a new study from MIT shows that language processing also occurs in many other parts of the brain.

Using functional magnetic resonance imaging (fMRI) data from more than 700 people, the researchers identified 17 additional regions of the brain that appear to play a role in language. These regions are scattered across the brain, including parts of the cerebellum, hippocampus, and cerebral cortex, and they make up about 5 percent of the total volume of the adult brain — about the size of a large strawberry.

“Even though there are all these distant components, it’s pretty restricted in terms of volume. You don’t need that much of the brain to do language,” says Evelina Fedorenko, an MIT associate professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

Exactly how these regions contribute to language processing is still to be discovered, although the researchers have made some progress toward determining the functions of the cerebellar regions that they identified.

A group of smiling researchers stand in front of a wall of windows.
The authors of the Journal of Neuroscience manuscript pictured together, from left to right: Benjamin Lipkin, Colton Casto, Evelilna Fedorenko, Agata Wolna, Aaron Wright, and Sam Hutchinson. Photo: Alexandra Sokhina

MIT postdoc Agata Wolna is the lead author of the paper, which appears today in the Journal of Neuroscience. Other authors include Aaron Wright, a K. Lisa Yang Post-Baccalaureate Research Scholar at MIT; Colton Casto, a graduate student at Harvard University; Samuel Hutchinson, a graduate student at MIT; and Benjamin Lipkin PhD ’26.

Tracking language

The brain’s language processing centers include Broca’s area, first discovered in the 1800s, plus additional regions in the left frontal and temporal lobes of the brain. Scientists have found that some of the corresponding areas of the right hemisphere also contribute to processing language, especially the social-emotional components of language.

There have also been hints that other parts of the brain might be involved in language processing. Early in her career, Fedorenko’s language studies often showed active brain regions outside of the canonical language centers, but she says she was discouraged from including them in her papers.

“When we initially started looking at language, in the first couple of papers, I tried to be comprehensive and include anything that seemed consistent across participants, and there was a huge amount of resistance,” she says.

“People would say things like, ‘Well, we know those are not language areas, so please focus on the language areas.’”

In the new study, she and Wolna wanted to revisit those brain scans and see if they could systematically identify language regions outside of the standard language-processing areas.

To do that, they analyzed data from 772 people who had been scanned in Fedorenko’s lab since 2013. Each of these participants underwent a task known as a language localizer, which is used to determine the location of language processing areas for each subject.

During the test, participants read or listen to sentences as well as sequences of nonwords. For each person, the researchers measure the difference in strength of response when reading real sentences or nonsense sequences. The brain areas that work harder during the sentence condition are considered to be doing something relevant to language, especially if they respond while both reading and listening to sentences.

“It’s a very simple paradigm that lets you identify this core language system in individual brains,” Wolna says.

When searching for language areas, the researchers usually use a relatively strict statistical threshold. In this study, they relaxed the threshold and also used some targeted searches in subcortical areas, in hopes of finding all areas that may contribute to language processing. “We always see this frontal temporal network, but there’s quite a lot of evidence that there are other regions that are also critical for language processing,” Wolna says. “By using a laxer threshold and zooming in on areas with weak MRI signal, we tried to maximize the chances of finding small and weakly responsive regions outside of this left frontal temporal system.”

A widespread network

For about 490 of the participants, the researchers also had data on how their brain responded during a spatial working memory task — remembering the locations of flashing squares on a grid. This task engages a brain network called the multiple demand system, which does not overlap with the core language areas.

This task allowed the researchers to ask whether any of the newly identified language-sensitive regions specifically respond to language and not more general cognitive processes.

Of the 17 new language sites that were revealed by this study, five are located in the cerebellum, which is mainly involved in coordinating the body’s movement. In a study published earlier this year, researchers led by Casto found that three of those cerebellar regions also became engaged during some nonlinguistic cognitive tasks, which was also seen in the new study.

“Those areas that respond to both language and some other tasks could be really interesting and important because they may be doing something like integrating information from different cortical systems,” Fedorenko says.

They also found language-selective regions in the medial frontal cortex, the bottom surface of the left temporal lobe, the hippocampus, and the amygdala. The researchers now plan to further study how these brain regions might contribute to language processing.

A graphic illustrating the established language regions of the brain (red) alongside the new, extended language regions discovered by Fedorenko’s team (blue). Image: Agata Wolna

“We can now test some ideas from past work, and also more rigorously characterize these regions across different kinds of language manipulations, and different kinds of non-linguistic tasks, to try to understand what it is that they’re doing,” Fedorenko says.

The research was funded by the Simons Center for the Social Brain at MIT, the McGovern Institute, MIT’s Department of Brain and Cognitive Sciences, and the MIT Siegel Family Quest for Intelligence.

 

 

Two McGovern faculty appointed to named professorships at MIT

by Julie Pryor |

MIT has appointed McGovern faculty members Sven Dorkenwald and Josh McDermott to named professorships that will provide additional support for their “outstanding research and educational careers.” Named professorships at MIT are prestigious endowed faculty chairs that provide crucial financial support for both junior faculty and senior scholars, enabling them to pursue bold research and global challenges.

Dorkenwald, who recently joined MIT as an assistant professor of brain and cognitive sciences and an investigator at the McGovern Institute, has been selected to hold the  Silverman (1968) Family Career Development Professorship for a three-year term beginning July 1, 2026. A trailblazer in the field of computational neuroscience, Dorkenwald reconstructs maps of neuronal circuits to investigate how they support complex computations. He is recognized for his leadership in connectomics—an emerging discipline focused on reconstructing and analyzing neural circuitry at unprecedented scale and detail. Jeffrey Silverman ’68 is a life member emeritus of the MIT Corporation. His generous gift to the institute empowers early career professors to pursue high-risk research. 

McDermott, a professor of brain and cognitive sciences and an associate investigator at the McGovern Institute, has been selected to hold the Uncas (1923) and Helen Whitaker Professorship for a five-year renewable term beginning July 1, 2026. McDermott’s research operates at the intersection of psychology, neuroscience, and engineering to study how people hear and interpret sound. Groundbreaking discoveries from the McDermott lab are informing new treatments for hearing loss, and paving the way for machine systems that emulate the human ability to recognize and interpret sound. The Uncas (1923) and Helen Whitaker Professorship chair was established in 1980 through a gift from the late Helen Whitaker, the first woman elected to life membership of the MIT Corporation. It is designed to support distinguished faculty whose work spans multiple disciplines to solve complex, real-world problems. 

 

The brain’s internal ruler

by Jennifer Michalowski |

McGovern Investigator Fan Wang. Photo: Caitliin Cunningham

If you are crossing an unfamiliar room in the dark, you may grope around a bit to get a sense of your space.

But for many animals, feeling out a space comes more naturally. A mouse, for instance, can efficiently navigate in the dark just by grazing its whiskers against walls and other obstacles.

Fan Wang, a professor of brain and cognitive sciences and an investigator at the McGovern Institute, has discovered how neurons in a mouse’s brainstem use signals from the animal’s touch-sensitive whiskers to estimate an object’s distance from the face.

Her team’s findings, published online June 25, 2026, in the journal Neuron, unlock key circuitry the brain uses to represent the space immediately surrounding the body.

Mapping space

The circuit the team discovered is part of the brain’s system for creating an egocentric map of space—that is, understanding where things are relative to one’s own body. Neuroscientists know that the brain calls on specialized circuits to understand space in this way, which are different from its system for mapping space using external landmarks.

In their study, Wang and her team explored how the brain maps the space closest to the body, which is known as the peripersonal space. This is the space in which we move, and it is vital that we understand where things are in relationship to our bodies so we can reach, step, avoid hazards, and otherwise interact effectively with our environment.

Wang says mice were an appealing model for investigating how the brain understands objects’ distance within the peripersonal space, because a rodent’s whiskers seem so much like a built-in set of rulers. These whiskers, which vary in length, are swept back and forth as the animals explore their environment. As whiskers bend and vibrate, the mechanical sensations are relayed to the brain by sensory neurons at their base. Those neurons fire more when a whisker bends close to the face than they do in response to contact near the whisker’s tip, communicating information about the proximity of the touch.

Close-up image of a mouse peeking through a hole with whiskers grazing the edge of the hole. Image: Istockphoto

Wang’s team wanted to know if the brain uses these signals to build an internal ruler-like representation of distance more precise than “near” or “far.” To find out, graduate student Wenxi Xiao and research scientist Kyle Severson monitored neural activity in a small sensory-processing region in the brainstem where tactile signals from the whiskers first arrive in the brain. They studied what happened there as mice walked on a treadmill while brushing their whiskers against a wall that passed by at different distances.

Many neurons in the region were sensitive to the whisker bending triggered by the wall. Some behaved similarly to the sensory neurons they were getting their information from, firing more when the wall was closer to the face and thus serving as a proximity-based distance code. But other cells were tuned in to discrete distances, firing only when the distance of the wall the whiskers had touched was within a specific range.

For some neurons, activity peaked when the wall was 23 mm away from the face, near the tips of the longest whiskers. Others responded most when the wall was at intermediate distances.

“Each of these neurons represents a specific distance, and together they span the full range reached by the longest whisker, like tick marks on the ruler,” Wang explains. “We call that the map code.”

The team wanted to know how the brain converts proximity signals from different whiskers into accurate map code of object’s distances from the head. “You cannot just listen to individual whisker neurons, because a contact at the tip of a short whisker would be in the middle of a long whisker. You need a brain circuit to build a unified distance map,” Wang says.

Through computational modeling and by exploring what happened when they manipulated neural signaling in specific ways, Wang’s team showed how distances can be calculated by comparing inputs from different sensory neurons. Their findings suggest that each brainstem neuron that makes up the map code receives both direct excitatory inputs from proximity-sensitive whisker neurons and inhibitory inputs from neurons driven by proximity-dependent whisker touch signals.

“Essentially the inhibitory pathway allows the brainstem to compare two inputs by subtraction,” Wang explains. “If one input signals ‘this is how far it is’ and the other signals ‘this is how far I estimate it to be,’ subtracting one from the other yields an intermediate value. We think it’s a simple and elegant way to transform tactile input into a representation of discrete distance.”

Wang notes that despite their importance, the brain’s body-centered representations of space have so far received little attention from neuroscientists, who know much more about how we understand locations in space relative to landmarks (an allocentric map). She is eager to investigate how the egocentric map code her team discovered is integrated with other brain systems to guide movement, social interactions, and other behavior, and hopes the findings will further exploration from other groups.

The study was funded by grants from the National Institutes of Health.

Would you return a favor? Scientists say it depends on the relationship

by Anne Trafton |

When a friend buys you a cup of coffee, it’s likely that next time, you’ll return the gesture. This type of reciprocal generosity has been well-documented in behavioral economic studies.

However, anthropologists and other social scientists have known for decades that in the context of relationships where one person has more power, status, or influence, reciprocal generosity is usually not the norm.

Researchers at MIT have now experimentally demonstrated, for the first time, that small changes to the relationship context can dramatically change people’s actions and expectations of reciprocal generosity.

During interactions between people of different social status, people tend to expect that generosity will flow one way, and it can be either up or down. It may be that a professor always buys coffee for her students, or that a student always offers to help carry groceries for his resident advisor. Once the precedent is established, it is expected to continue.

One interpretation of the findings is that keeping track of whose turn it is to do a favor is the exception in social interactions, not the rule. That is, it is extra work that we do when we want to maintain equal relationships.

“In many intimate relationships, hierarchical relationships, or other kinds of role-based relationships, you don’t put in the work of trying to keep track of turns,” says Rebecca Saxe, the John W. Jarve Professor of Brain and Cognitive Sciences, a member of the McGovern Institute for Brain Research, and associate dean of science at MIT. “Under this interpretation, we just follow precedent because following a precedent is easier. We all know what to expect, and we don’t have to keep track of what happened last time.”

Saxe is the senior author of the study, which appears in the journal Open Mind. MIT graduate student Alicia Chen is the paper’s lead author.

Changing expectations

Most experimental studies of generosity have been done in the context of behavioral economics and game theory. In such experiments, people are usually paired with a stranger and asked to play games that require coordination. Such studies have found that people tend to use turn-taking and reciprocity as their default strategies. These scenarios, however, are stripped from any social context that might exist between people in the real world.

Saxe and Chen wanted to see if they could measure the effects of social context by incorporating relationships into the type of experiments used to evaluate people’s expectations regarding generosity.

“Where generosity becomes hard and complicated is when it starts to occur in the context of existing relationships, because it changes the terms of the relationships,” Saxe says. “What’s expected of you is very different within a relationship than outside of one.”

To study these effects, the researchers designed experiments in which participants read stories about different types of interactions. In some of the scenarios, the subjects of the stories were described as having either symmetric or asymmetric relationships. In others, they were given specific social relationships such as aunt-niece or manager-employee.

Each story described interactions that might be seen in typical daily life, such as buying coffee for a co-worker or preparing a meal for one’s family. Participants were then asked to predict what would happen the next time the interaction occurred.

In all of these scenarios, the researchers found that people expected that generous acts would be reciprocated when they occurred between individuals in symmetric relationships such as friends, cousins, or co-workers of equal rank. However, their expectations changed for asymmetric relationships, where each person has a different social status. In those cases, people expected that any precedent that was set would continue in the future.

One possible explanation for this is that reciprocity is not the norm but an exception that only occurs in the interactions between equals or strangers, the researchers say. Many of our interactions are with people with whom we have asymmetric relationship, and to maintain those relationships, it’s simply easier to follow precedent.

“If there’s no need to keep track of our equal status, then in some ways it’s the default to fall back on following precedents,” Saxe says.

Maintaining relationships

The study showed that in asymmetric relationships, generosity could flow in either direction. Once that direction was established, it was expected to continue. For example, after an older brother bought concert tickets for a much younger brother, the study participants expected that the older brother would also buy the tickets for the next concert.

“We found that when people know the relationship is asymmetric, they don’t expect reciprocity; they expect the same action to keep on going,” Chen says. “If the lower-rank person acts generously, people expect that to continue, and if the higher-rank person acts generously, people expect that to continue.”

Following precedents is not only easier, but keeping up these actions may help solidify and define existing relationships. For example, anthropologists have long known that gift-giving helps to construct and maintain social relationships.

“Following a precedent can be a way of actively maintaining relationships and hierarchies, when the asymmetry of the exchange truly reflects the asymmetry of the relationship,” Saxe says.

The researchers are now working on creating computational models that could be used to analyze different factors that people take into account when they’re considering whether someone might reciprocate a generous act. In addition to the factors examined in this study, others could include how much each person will benefit, what type of relationship they’re in, and culturally specific expectations of how people should act in different situations.

“One really powerful thing about these models is that we can build in existing theories, add things to the models, and then compare how much these extra factors, like considerations related to social relationships, matter in terms of explaining what people are doing,” Chen says. “This allows us to quantitatively compare the different theories to each other.”

The research was funded by the Simons Foundation Autism Research Initiative and the Patrick J. McGovern Foundation.

Language development in the brain

by Jennifer Michalowski |

The brain’s capacity to use and understand language expands rapidly in the first years of life, as babies start to make sense of the words they hear and eventually begin to piece together sentences of their own. The language-processing parts of the brain that make this possible continue to evolve in older children, as they expand their vocabularies and learn to use language more flexibly.

Scientists at MIT’s McGovern Institute have captured snapshots of the developing language-processing network in brain scans of hundreds of children and adolescents. Their data, reported on May 16 in the journal Nature Communications, show that the network continues to mature, becoming better integrated and increasingly responsive until around age 16. But they also found that a key feature of the adult language network is established early on: its localization in the left side of the brain.

Language lateralization

It is well known that using language is mostly the job of the left hemisphere. As adults, we call on the language-processing regions there when we read, write, speak, or listen to others talk. But there was some question as to whether this left lateralization is established early in life, or might instead emerge as the language network matures, with both sides of the brain contributing to language in childhood.

To find out, researchers needed to see young brains in action—and several McGovern Institute labs had collected exactly the right kind of data. Groups led by Associate Professor of Brain and Cognitive Sciences Evelina Fedorenko, John Gabrieli, the Grover Hermann Professor of Health Sciences and Technology, and Rebecca Saxe, the John W. Jarve (1978) Professor of Brain and Cognitive Sciences  teamed up to share brain scans from children, adolescents, and adults and compare how their brains responded to language.

In studies aimed at better understanding a variety of cognitive functions and developmental disorders, the three teams had all collected functional MRI data while subjects participated in “language localizer” tasks—an approach the Fedorenko lab developed to map the language-processing network in a person’s brain. By monitoring brain activity with functional MRI as people engage in both language tasks and non-linguistic tasks, researchers can identify parts of the brain that are exclusively dedicated to language processing, whose precise anatomic location varies across individuals.

To activate the language network, the researchers had children listen to stories inside the MRI scanner. Depending on their age, some heard excerpts of Alice in Wonderland, some listened to podcasts and TED talks, and others heard shorter, simpler stories. To watch their brains during a non-linguistic task, the researchers had the children listen to nonsense words.

Across the data from the three labs, which included children between the ages of four and 16, as well as adults for comparison, the team saw clear developmental changes in the brain’s response to language. “The integration of the system—how well different subregions of the system correlated with each other and worked together during language processing—was stronger in older children as compared to younger children,” says Ola Ozernov-Palchik, a research scientist in Gabrieli’s lab and a research assistant professor at Boston University. The system was also more strongly activated by language in older children, which may reflect their growing comprehension of what they hear.

But strikingly, almost all language processing happened on the left side of the brain, even in the youngest subjects. “From age four on, it seems just as lateralized as in an adult,” Gabrieli says.

Language and developmental disorders

The researchers say this finding has implications for understanding developmental conditions that impact language, including autism and dyslexia. The right side of the brain frequently gets more involved in language processing in people with these conditions than it does in typically developing children. “Almost every single developmental disorder that’s associated with language has a theory that’s related to language lateralization,” Ozernov-Palchik says.

The reason for more bilateral language processing in some disorders is debated. One idea has been that some people might use both sides of their brain for language processing because their brains are less mature. If the right side of the brain processes language early in life, scientists had reasoned, it might simply continue to do so for longer in people with autism or dyslexia than it does in neurotypical individuals. But if most people use the left side of their brains for language even when they are young, the difference can’t be attributed to a developmental delay. Other developmental differences might cause bilateral language processing instead.

The researchers don’t have the full picture yet; they still need to know what parts of the brain process language in children younger than four. Likewise, they would like to know what the brain areas that become the language network are doing in the first months of life, when infants aren’t using language yet. They are eager to find out, both to understand fundamentals of brain development and to shed light on developmental disorders. “I think understanding that normal trajectory is really critical for interpreting what a deviation from that trajectory is,” says Amanda O’Brien, a former graduate student in Gabrieli’s lab who is now a postdoctoral fellow at Harvard.

One reason people thought lateralization might develop gradually is because damage to the left hemisphere of the brain impacts language abilities differently, depending on when it occurs. “If you have damage to the left hemisphere as an adult, you’re very likely to end up with some form of aphasia, at least temporarily,” Fedorenko explains. “But a lot of the time, with early damage to the left hemisphere, you grow up and you’re totally fine. The language can just develop in the right hemisphere.”

Some scientists suspected that the right side of the brain was able to take over language processing in children who suffered early-life brain damage because it was already participating in this function at the time. But the team’s findings suggest the developing brain may be nimbler than that. “Our data tell you that this early plasticity apparently happens in spite of the fact that by age four, we see these very strongly lateralized responses already,” Fedorenko says.

Brighter MRI signals

by Jennifer Michalowski |

When doctors and scientists want to see inside a body, magnetic resonance imaging (MRI) is a powerful tool. MRI can noninvasively capture detailed images of the body’s muscles, organs, and bones. It can monitor blood flow to generate a map of brain activity. And with new sensors developed by bioengineers at MIT, MRI can track the kinds of molecules that make our brains and bodies work.

In the May 13, 2026, issue of the journal Nature Biomedical Engineering, a team led by Alan Jasanoff, the Eugene McDermott Professor in the Brain Sciences and Human Behavior at MIT reports on their new sensors, which can brighten or dim MRI signals in response to specific molecular targets. The probes are designed to amplify the effect that each target molecule has on MRI signal, dramatically improving sensitivity over previous small-molecule sensors. Jasanoff, who is also an associate investigator at the McGovern Institute for Brain Research, says the approach his team used should enable the development of MRI sensors that detect neurotransmitters and other important molecules in the brain.

“We want to be able to measure distinct chemical signals like neurotransmitters, neuropeptides, and metabolites as they fluctuate across the whole brain,” Jasanoff says.

“These chemicals are important ingredients in neural computations, and we want to use the types of probes that we developed to detect these signals dynamically.”

Engineered nanoparticles

Jasanoff explains that researchers have struggled to use MRI to sensitively detect small molecules in the brain because the amount of any given neurochemical is low. Sensors can be designed to change the brightness of an MRI signal in the presence of specific molecules—but it takes a lot of contrast agent to achieve this. If every molecule of contrast agent needs its own target molecule to activate it, low concentrations of the target molecule limit the sensors’ visibility in an MRI scan. “The signal change that you see in the imaging will be very modest,” Jasanoff says. “It won’t let us detect physiological events.”

The Jasanoff team’s new sensors, whose development was led by postdoctoral researcher Sayani Das and graduate student Jacob Cyert Simon, overcome this problem. To generate a greater signal change in response to target molecules, the researchers designed probes in which a single target molecule impacts not one contrast agent, but many.

To achieve this, Das and Simon packaged an MRI contrast agent inside tiny sacs called liposomal nanoparticles. Each nanoparticle is packed with many molecules of gadolinium, a magnetic material that brightens the MRI signal that arises from hydrogen atoms in water. Inside their protective sacs, gadolinium has no effect on MRI signal, unless water molecules can easily get in and out.

Das and Simon built water channels into the walls of their gadolinium-filled nanoparticles, engineering them so that their opening depends on the presence or absence of a target molecule. When the channels open, more water enters and the gadolinium brightens the local MRI signal, lighting up that spot in a scan.

LisNR architecture consisting of an MRI contrast agent (gadoteridol) enclosed in a liposomal membrane (grey) perforated by water permeable pores (orange). Image courtesy of the researchers.

The researchers call their target-responsive sensors liposomal nanoparticle reporters, or LisNRs (pronounced “listeners”). They designed LisNRs that let water in only in the presence of their target molecule. The water channels in these nanoparticles stay blocked until they encounter their target, which can knock aside a channel-blocking bit of protein. Once the channel blocker is displaced, water enters and MRI signal brightens. They also made LisNRs that dim the MRI signal in the presence of the molecule they are designed to detect. These have a channel that stays open until the target molecule comes along and blocks it, keeping water out. Jasanoff lab members Vinay Sharma, Samira Abozeid, and Gregory Thiabaud played key roles in understanding and optimizing these interactions, and collaborators in the laboratory of Masayuki Inoue at the University of Tokyo helped the group engineer channels with higher potency.

In experiments led by postdoctoral researcher Miranda Dawson, Jasanoff’s team used their LisNRs to detect a molecule called biotin in the brains and bodies of living rats, illustrating the probe’s amplifying effects. “We showed that we could detect micromolar-scale levels of biotin with about tenfold greater sensitivity than we would have if we’d used a more conventional, one-to-one type sensing approach,” Jasanoff says. He adds that the team’s modeling suggests that with further development, they may be able to achieve even greater sensitivity gains.

The group showed that the new sensors can be delivered systemically, reaching various organs and spreading throughout the brain. This makes them promising tools for brain-wide imaging, as well as imaging targets in the peripheral nervous system or other tissues.

A next step will be engineering LisNRs that respond to the specific neurochemicals that Jasanoff and his team hope to study. “There are something like 100 neurochemicals in the brain that we’d love to detect in principle,” he says. They’ll start with dopamine and glutamate—two important and relatively abundant molecules that mediate communications between neurons.

This research, including support for postdoctoral fellows and graduate students involved in the work, was funded in part by Lore Harp McGovern, Yang Tan Collective at MIT, K. Lisa Yang Brain-Body Center at MIT, Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, and K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT.

Powerful shrinking technique could enable devices that compute with light

Anne Trafton |

Using a new technique that can create vacancies at any site across a material and then shrink it to about 1/2,000 of its original volume, MIT researchers have designed nanotechnology devices that could be used for optical computing and other applications involving the manipulation of visible light.

The new fabrication technique, known as “implosion carving,” allows researchers to imprint features throughout a hydrogel using photopatterning. If patterned with a resolution of about 800 nanometers, these features can then be shrunk to less than 100 nanometers.

Because that resolution is smaller than the wavelength of light, the devices can bend light in specific ways that allow them to perform optical computations.

Animation of block resembling three skyscrapers spinning in mid air.
MIT engineers created this photonic device by laser-patterning a hydrogel and then shrinking it to 1/2000 of its original volume.

“In order to enable nanophotonic applications in visible light, we need to make nanostructures with feature sizes with a resolution less than 100 nanometers. Only in that way can we precisely create the structure that can manipulate visible light,” says Quansan Yang, a former MIT postdoc, now an assistant professor at the University of Washington, and one of the lead authors of the new study.

In their paper, the researchers demonstrated a photonic device that can perform a simple digit-classification task, but future versions could be used for high-speed imaging and information processing, they say.

Gaojie Yang, a former MIT postdoc, is the co-lead author of the paper, which appears today in Nature Photonics. The paper’s senior authors are Peter So, director of the MIT Laser Biomedical Research Center (LBCR) and an MIT professor of biological engineering and mechanical engineering, and Edward Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT and a professor of biological engineering, media arts and sciences, and brain and cognitive sciences. Boyden is also a Howard Hughes Medical Institute investigator and a member of MIT’s McGovern Institute for Brain Research, the Yang Tan Collective, and Koch Institute for Integrative Cancer Research.

Nanoscale feature sizes

Photonic devices, which transmit and manipulate light, hold potential for use as optical computer chips that could offer an energy-efficient alternative to semiconductor chips. However, existing techniques for creating 3D photonic devices haven’t yet achieved the 100-nanometer resolution that is needed to channel visible light, which has wavelengths between 380 and 750 nanometers.

Using an additive manufacturing technique called two-photon lithography, researchers can use light to create 3D nanoscale features, but with a resolution larger than 100 nanometers. Another technique, known as electron-beam lithography, can be used to etch smaller-resolution features onto a silicon chip, but it doesn’t generate 3D structures.

To make 3D devices with the necessary feature size, the researchers extended the concept of “implosion fabrication,” which Boyden’s lab developed in 2018, to create a new variant called “implosion carving.” In implosion carving, a laser creates vacancies — tiny voids where the hydrogel material has been removed — at precisely targeted locations. These vacancies exhibit different optical properties than the surrounding hydrogel. The hydrogel is then shrunk to bring the patterned features down to the nanoscale.

The carving process begins with immersing the hydrogel in a photosensitizing dye. Then, the researchers use a laser to excite the photosensitizer at specific places in the gel, which in turn generates reactive oxygen species that cut the bonds holding the hydrogel together. This creates a vacancy in that spot.

Once the desired vacancy pattern has been carved into the hydrogel, the researchers shrink it using a two-step process. First, they soak it in a solution containing ions, which causes it to shrink about tenfold in each dimension. To shrink it a little more, and to remove the watery solution, the hydrogel then undergoes a process called supercritical drying, which can remove liquid from a gel without damaging it.

At the end of the process, the hydrogel has been shrunk more than tenfold in each dimension, leading to a 2,000-fold reduction in volume.

Computing with light

To demonstrate the versatility of this technique, the researchers used it to create several 3D shapes, including a helix and a structure inspired by a butterfly wing. Some of these structures are too thin, and have too high an aspect ratio, to be stably created using conventional two-photon lithography.

The researchers also created a device that could perform a simple calculation known as digit classification, a task that is traditionally used to test the performance of neural networks. During this task, the device was presented with a digit, such as 1 or 5, and had to light up a specific location to indicate which number was detected.

To achieve this, the researchers patterned vacancies throughout the device so that it would act like a neural network. The pattern of vacancies would diffract input light as it passed through many layers of patterned hydrogel, so that the output light was determined by the shape of the digit that was entered into the system.

“This is a purely optical system that effectively performs optical computing,” So says.

“One of the very attractive features of this technology is that you can manipulate the property of the material at every tiny location,” says Dushan Wadduwage, an assistant professor at Old Dominion University and former MIT postdoc, who is also an author of the paper. “You have millions of different locations that you need to decide the property of, and that turns into a really interesting design problem where we can use deep-learning algorithms to find designs over these millions of parameters and come up with parts that go into optical systems in new ways.”

The researchers now plan to use the same principles to build optical devices that could classify cells based on their state as they flow through a microfluidic device. This could help identify rare cells such as circulating tumor cells in a blood sample, they say.

This approach could also enable the creation of high-throughput imaging techniques for applications such as analyzing tissue samples from biopsies or surgical specimens. And, if adapted to work with other materials such as hydrophobic polymers, it could also be used to create channels within 3D nanofluidic devices.

Other authors of the paper include Gaojie Yang, Takahiro Nambara, Hiroyuki Kusaka, Yuichiro Kunai, Alex Matlock, Corban Swain, Brett Pryor, Yannick Salamin, Daniel Oran, Hasindu Kariyawasam, Ramith Hettiarachchi, and Marin Soljacic.

The research was funded, in part, by the MIT-Fujikura Partnership Fund, the U.S. Army Research Office through the Institute for Soldier Nanotechnologies at MIT, Lisa Yang and Y. Eva Tan, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, and the U.S. National Institutes of Health.

MIT Scientists Sven Dorkenwald and Whitney Henry named 2026 Searle Scholars

by Julie Pryor |

MIT scientists Sven Dorkenwald and Whitney Henry have been named 2026 Searle Scholars, an award given annually to 15 exceptional early-career researchers in the fields of biomedical sciences and chemistry. Chosen by a scientific advisory board, Searle Scholars are considered among the most creative young researchers pursuing high-risk/high-reward research. The Searle Scholars Program is funded through the Searle Funds at The Chicago Community Trust and administered by Kinship Foundation.

Dorkenwald is an assistant professor of brain and cognitive sciences and an investigator at the McGovern Institute for Brain Research. Henry is the Robert A. Swanson (1969) Career Development Professor of Life Sciences and an intramural faculty member at the Koch Institute for Integrative Cancer Research. They will each receive $450,000 in flexible funding to support their work over the next three years.

Sven Dorkenwald

Sven Dorkenwald is a computational neuroscientist investigating the organizational principles of neuronal circuits. The synaptic connectivity of neurons, their connectome, is fundamental to how networks of neurons function. Dorkenwald develops computational and collaborative tools to map, analyze, and interpret synapse-resolution connectomes. His work has led to large connectomic reconstructions of the fruit fly brain and parts of mammalian brains. He uses these connectomes to investigate the architecture of neuronal circuits and how their structure supports complex computations.

“As I establish my new lab, the Searle Scholars Award will help us launch ambitious projects and set our long-term scientific direction,” said Dorkenwald. “I am deeply grateful for the support from the Kinship Foundation and look forward to interacting with this amazing cohort of Searle Scholars.”

Dorkenwald joined the faculty of MIT in 2026 as an assistant professor in the Department of Brain and Cognitive Sciences and an investigator at the McGovern Institute. He earned a BS in physics and an MS in computer engineering from the University of Heidelberg, followed by a PhD in computer science and neuroscience at Princeton University in 2023 under the mentorship of Sebastian Seung and Mala Murthy. Dorkenwald completed his postdoctoral training as a Shanahan Research Fellow at the Allen Institute and the University of Washington, while serving as a Visiting Faculty Researcher at Google Research.

Whitney Henry

Whitney Henry investigates the potential of ferroptosis, an iron-dependent form of cell death, for developing novel therapies that target subpopulations of cancer cells that are highly metastatic, therapy-resistant, and therefore critical instigators of tumor relapse. Her research is focused on uncovering the molecular factors influencing ferroptosis susceptibility, investigating its effects on the tumor microenvironment, and developing innovative methods to manipulate ferroptosis resistance in living organisms, drawing from functional genomics, metabolomics, bioengineering, and a range of in vitro and in vivo models.

“I am incredibly grateful to the Kinship Foundation for supporting our research and giving us the freedom to ask bold, curiosity-driven scientific questions,” said Henry. “This support allows us to pursue ambitious ideas, take creative risks, and embark on new research directions.”

Henry joined the MIT faculty in 2024 as an assistant professor in the Department of Biology and a member of the Koch Institute, and is currently an HHMI Freeman Hrabowski Scholar. She received her bachelor’s degree in biology with a minor in chemistry from Grambling State University and her PhD from Harvard University. Following her doctoral studies, she worked in the lab of Robert Weinberg at the Whitehead Institute and was supported by fellowships from the Jane Coffin Childs Memorial Fund for Medical Research and the Ludwig Center at MIT.

Michale Fee and Fan Wang Elected to the National Academy of Sciences

by Julie Pryor |

Michale Fee, the Glen V. and Phyllis F. Dorflinger Professor of Neuroscience and head of the Department of Brain and Cognitive Sciences, and Fan Wang, a professor of brain and cognitive sciences, have been elected to join the National Academy of Sciences (NAS). Fee and Wang, who are also investigators at the McGovern Institute for Brain Research, were elected by current NAS members in recognition of their “distinguished and continuing achievements in original research.”

The NAS is a private, nonprofit institution that was established under a congressional charter signed by President Abraham Lincoln in 1863. It recognizes achievement in science by election to membership, and — with the National Academy of Engineering and the National Academy of Medicine — provides science, engineering, and health policy advice to the federal government and other organizations. This year, the NAS elected 120 members and 25 international members, including six MIT faculty, bringing the total number of active members to 2,705.

“Election to the National Academy of Sciences by one’s peers is a great honor for a scientist in the United States,” says McGovern Institute Director Robert Desimone. “Michale and Fan represent the very best of our research community and we are tremendously proud of their accomplishments and this well-deserved recognition.”

Michale Fee’s research explores how the brain learns and generates complex sequential behaviors.  Using the zebra finch as a model system, Fee investigates the neural mechanisms underlying birdsong—a behavior that young birds learn from their fathers through trial and error, much as human infants learn to speak through babbling. His work has revealed that a brain region called the higher vocal center (HVC) functions like an orchestra conductor, precisely controlling the tempo and timing of song production. Other work from his lab has shown how this same circuit helps to store a memory of the father’s song, how baby birds babble in order to practice their song, and how this vocal practice is translated to song learning by listening to themselves sing.

These findings extend far beyond birdsong—the neural circuits controlling birdsong learning are closely related to human brain circuits disrupted in Parkinson’s and Huntington’s disease. Insights from Fee’s research could reveal new clues to the causes and potential treatments of these complex brain disorders.

Fee’s appointment in 2021 as head of the Department of Brain and Cognitive Sciences continues the department’s tradition of being led by scientists whose exemplary work makes MIT a world leader in brain science.

Fan Wang investigates the neural circuits that govern the dynamic interactions between brain and body, exploring how the brain generates sensory perceptions and controls movement. Wang, who is also the co-director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics, uses cutting-edge techniques including optogenetics, in vivo electrophysiology, and in vivo imaging, to make discoveries with profound clinical implications.

By developing innovative tools to study how brain circuits work, Wang discovered distinct populations of neurons activated by anesthesia that can suppress pain without blocking sensation, and can calm anxiety by regulating automatic body functions like heart rate. She also identified the brain circuits controlling rhythmic movements essential for exploration and communication. Together, these findings reveal how emotion, physiology, movement, and consciousness are deeply interconnected.

Wang combines rigorous basic neuroscience with a commitment to translating her discoveries into therapies that relieve human suffering. Her election to the NAS recognizes her contributions to understanding the brain-body connection and therapeutic potential of her groundbreaking research.

The formal induction ceremony for new NAS members, during which they sign the ledger whose first signatory is Abraham Lincoln, will be held at the Academy’s annual meeting in Washington D.C. next spring.

A different reality

by Jennifer Michalowski |

This story also appears in our Spring 2026 BrainScan newsletter.

***

Schizophrenia, a complex and variable psychiatric disorder, changes people’s perceptions of reality. People with schizophrenia may hear, see, or sense things that aren’t there, and they often hold firm to mistaken ideas about the world despite strong evidence to the contrary. As if these changes aren’t disruptive enough, they are usually accompanied by cognitive difficulties and disorganized thinking.

Scientists at the McGovern Institute’s Poitras Center for Psychiatric Disorders Research are looking for clues into the origins of the disorder and its symptoms so they can help guide the development of new treatments. Encouragingly, they are beginning to uncover the brain changes that reshape reality for people with schizophrenia.

Genetic clues

Researchers who want to study the root causes of a disease often turn to genetics for clues—and the genetics of schizophrenia are complicated. Hundreds of different genes seem to shape people’s risk of developing the disorder, most of which nudge risk only slightly. For most people, it seems to be the cumulative effect of these genes and how they intersect with other risk factors, like stress and prenatal complications, that determine who develops schizophrenia and who does not.

Gene variants that substantially impact the risk of schizophrenia are expected to reveal more about the underlying biology of the disorder than genes whose individual impact is minor. But these variants are rare, and it took a massive study to find them. In 2022, scientists at the Broad Institute’s Stanley Center for Psychiatric Research reported that after analyzing the DNA of more than 24,000 people with schizophrenia, they had identified mutations in 10 genes that dramatically increased the risk of the disorder.

“I think this is exciting, because for the first time, you can actually have an animal model based onhuman genetics findings,” says McGovern Institute and Stanley Center Investigator Guoping Feng. “You can put these mutations in animal models to try to understand how this mutation affects brain development, circuit formation, circuit function, and behavior.” Feng is also the James W. (1963) and Patricia T. Poitras Professor of Brain and Cognitive Sciences at MIT.

Woman and man sit at desk looking at brain image on computer screen.
Guoping Feng (right) and his postdoctoral researcher Tinting Zhou (left) examine a mouse brain carrying a genetic mutation associated with schizophrenia. Photo: Steph Stevens

In work supported by the Poitras Center, the Stelling Family Research Fund, and the Yang Tan Collective at MIT, Feng’s lab has engineered three strains of mice that carry ultra-rare schizophrenia-associated mutations. Their first significant findings come from mice with a mutation in a gene called Grin2a. People who inherit a dysfunctional Grin2a gene, which neurons need to detect and respond to a signaling molecule called NMDA, are 20 times more likely to develop schizophrenia than people in whom Grin2a is intact.

Tingting Zhou, a postdoctoral researcher in Feng’s lab, says the team had to think carefully about how to assess mice for schizophrenia-like symptoms. You can’t ask mice about hallucinations or delusions. Instead, Zhou designed an experiment that tested how well mice use new information to update their beliefs about the world—a process that is thought to be impaired in people who experience delusions.

To illustrate how failure to update beliefs can skew someone’s ideas about reality, Zhou describes a situation in which a person watches a stranger reach for something in their pocket, fearing that person intends to harm them. Then, the stranger’s hand emerges with a lollipop. The new information should alleviate concern—but a person with schizophrenia might hold on to their original belief, convinced the lollipop-holding stranger is a threat.

In Zhou’s experiments testing animals’ belief-updating abilities, mice had to keep up with changing information to earn as many treats as possible. Those with the Grin2a mutation were slow to adapt when experimenters adjusted the relative values of their choices. “Once the animal learns something, it’s very hard for them to update the information,” Zhou explains.

Zhou and Feng linked this behavioral difference to abnormally low activity in a part of the brain called the mediodorsal thalamus. The mediodorsal thalamus acts like a switchboard in the brain, routing and coordinating information between different parts of the cortex to support thinking, decision-making, and flexible behavior. Studies with patients have implicated this region in schizophrenia as well, showing that it has fewer cells and is less active in people with the disorder than those without.

A slice of mouse brain dyed purple showing two pink blobs towards the center.
The mediodorsal thalamus (pink) is less active in people with schizophrenia and mouse models of the disease. Image: Guoping Feng, Tingting Zhou

Feng’s lab and others are now looking for belief-updating deficits in other genetic models of schizophrenia. “The goal is to look at whether this is a converging mechanism…then you can start to look at what other [brain] regions are involved,” he says.

In mice with Grin2a mutations, the researchers were able to restore normal belief updating by activating neurons in the mediodorsal thalamus, offering hope that manipulating the same circuitry might benefit patients. “It will not be easy,” Feng says, “but at least you have something you can work on. Previously, it was just very hard to imagine how to develop a new therapeutic for schizophrenia.”

Internal noise

It’s not just the genes associated with schizophrenia that differ across affected individuals. The symptoms of the disorder vary, too. People experience some combination of delusions, hallucinations, disorganized speech, and cognitive problems—but none of these are experienced by everyone with the disorder. This heterogeneity complicates the diagnosis, treatment, and study of schizophrenia. For this reason, some researchers are focusing their efforts on understanding its individual symptoms.

Evelina Fedorenko, a McGovern Investigator and associate professor of brain and cognitive sciences, specializes in understanding how the brain processes speech and language. But recently, her group has teamed up with physician-researcher Ann Shinn at McLean Hospital to begin exploring why some people hear voices when no one is speaking.

About three out of four people with schizophrenia experience auditory hallucinations, which most commonly involve voices.

These hallucinations can be distressing, sometimes involving threatening language or commands to cause harm. Some people with mood disorders or post-traumatic stress disorder also hear them.

Scientist portrait
Tamar Regev was the 2022–2024 Poitras Center Postdoctoral
Fellow in Evelina Fedorenko’s lab. Photo: Steph Stevens

To investigate, Tamar Regev, a research scientist in the Fedorenko lab, asked people who experience auditory hallucinations to listen to different kinds of sounds inside an MRI scanner, then compared how their brains responded versus the brains of people without auditory hallucinations. Her study included participants with schizophrenia and bipolar disorder, both with and without a history of auditory hallucinations, as well as healthy controls.

Inside the scanner, participants listened to three kinds of audio: spoken language, gibberish, and gibberish so scrambled that it barely resembled speech. Regev analyzed how these sounds impacted activity in areas the brain uses to process auditory input at different levels: a part of the auditory cortex that is sensitive to all sounds; a higher-level region within the auditory cortex that usually responds to anything that sounds like speech, even if its content is unclear; and the brain’s language-processing network, which is called on to understand the content of speech, as well as written or signed communications.

Regev found that in people with hallucinations, the part of the brain that usually responds only to language responded to meaningless speech as well. “In this pathway from auditory to speech to language processing, the stimuli that should be filtered out somewhere on the way are now passing to higher stations,” she explains. While auditory hallucinations don’t require external sounds, Fedorenko and Regev propose that the brain’s language areas might be similarly activated by “internal noise” in auditory circuits.

Scrambled language

In people who experience auditory hallucinations, the brain’s language regions respond to sounds that aren’t language–including scrambled meaningless gibberish. Below is a sample gibberish clip used in Fedorenko’s study.

Early identification

McGovern scientists have also used brain imaging to investigate what happens in the brain before people develop clear symptoms of schizophrenia. The disorder is usually diagnosed in adolescence or young adulthood, when patients exhibit the first signs of psychosis—but its origins in the brain likely take root years before that.

“One of the things we’re super interested in is, can you identify people at risk early on, before they have a big problem,” says McGovern Investigator John Gabrieli, whose work is also supported by the Poitras Center and the Stelling Family Research Fund. That might give clinicians an opportunity to intervene and lessen or prevent the disorder’s most devastating effects, he says.

Gabrieli and his colleagues have studied the brains of children who, because they have a parent or sibling with schizophrenia, have an elevated risk of developing the disorder themselves. They found that a system called the default mode network (DMN), which is overactive in adults with schizophrenia, is already working overtime when children in this high-risk group are seven- to 12-years-old.

Gabrieli explains that the DMN is active when people are not actively engaged in an activity or thinking about the external world. “It turns on when you think about your family, your values, your hopes for the future, or important events of your life. It’s almost like a system of who /you are,” he says. Hallucinations and delusions experienced by people with schizophrenia may be associated with overactivity in this network.

MRI images of two brains, one showing an active DMN and the other showing a healthy DMN.
The default mode network (DMN) is a large-scale brain network that is active when a person is not focused on the outside world and the brain is at wakeful rest. The DMN is often over-engaged in adolescents with depression and anxiety, as well as teens at risk for these and other disorders like schizophrenia (left). DMN activation and connectivity can be “tuned” to a healthier state through the practice of mindfulness (right).

“They’re kind of living in their internal world of beliefs, as opposed to the reality that most of us occupy,” Gabrieli explains.

He and his colleagues think overactivity in the DMN might make people vulnerable to schizophrenia—and their data show this atypical activity can be detected many years before the core symptoms of schizophrenia appear. With further validation, children with hyperactivity of the DMN might be candidates for early intervention.

With new and better interventions, the ability to identify people who may be on a path toward schizophrenia will be even more impactful—underscoring the need for continued research on multiple fronts. A recent gift of $8 million to the Poitras Center from Patricia and James Poitras is helping accelerate this work in labs at the McGovern Institute and beyond.