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A voice for change — in Spanish

by Jennifer Michalowski |

Jessica Chomik-Morales had a bicultural childhood. She was born in Boca Raton, Florida, where her parents had come seeking a better education for their daughter than she would have access to in Paraguay. But when she wasn’t in school, Chomik-Morales was back in that small, South American country with her family. One of the consequences of growing up in two cultures was an early interest in human behavior. “I was always in observer mode,” Chomik-Morales says, recalling how she would tune in to the nuances of social interactions in order to adapt and fit in.

Today, that fascination with human behavior is driving Chomik-Morales as she works with MIT professor of cognitive science Laura Schulz and Walter A. Rosenblith Professor of Cognitive Neuroscience and McGovern Institute for Brain Research investigator Nancy Kanwisher as a post-baccalaureate research scholar, using functional brain imaging to investigate how the brain recognizes and understands causal relationships. Since arriving at MIT last fall, she’s worked with study volunteers to collect functional MRI (fMRI) scans and used computational approaches to interpret the images. She’s also refined her own goals for the future.

Jessica Chomik-Morales (right) with postdoctoral associate Héctor De Jesús-Cortés. Photo: Steph Stevens

She plans to pursue a career in clinical neuropsychology, which will merge her curiosity about the biological basis of behavior with a strong desire to work directly with people. “I’d love to see what kind of questions I could answer about the neural mechanisms driving outlier behavior using fMRI coupled with cognitive assessment,” she says. And she’s confident that her experience in MIT’s two-year post-baccalaureate program will help her get there. “It’s given me the tools I need, and the techniques and methods and good scientific practice,” she says. “I’m learning that all here. And I think it’s going to make me a more successful scientist in grad school.”

The road to MIT

Chomik-Morales’s path to MIT was not a straightforward trajectory through the U.S. school system. When her mom, and later her dad, were unable to return to the U.S., she started eight grade in the capital city of Asunción. It did not go well. She spent nearly every afternoon in the principal’s office, and soon her father was encouraging her to return to the United States. “You are an American,” he told her. “You have a right to the educational system there.”

Back in Florida, Chomik-Morales became a dedicated student, even while she worked assorted jobs and shuffled between the homes of families who were willing to host her. “I had to grow up,” she says. “My parents are sacrificing everything just so I can have a chance to be somebody. People don’t get out of Paraguay often, because there aren’t opportunities and it’s a very poor country. I was given an opportunity, and if I waste that, then that is disrespect not only to my parents, but to my lineage, to my country.”

As she graduated from high school and went on to earn a degree in cognitive neuroscience at Florida Atlantic University, Chomik-Morales found herself experiencing things that were completely foreign to her family. Though she spoke daily with her mom via WhatsApp, it was hard to share what she was learning in school or what she was doing in the lab. And while they celebrated her academic achievements, Chomik-Morales knew they didn’t really understand them. “Neither of my parents went to college,” she says. “My mom told me that she never thought twice about learning about neuroscience. She had this misconception that it was something that she would never be able to digest.”

Chomik-Morales believes that the wonders of neuroscience are for everybody. But she also knows that Spanish speakers like her mom have few opportunities to hear the kinds of accessible, engaging stories that might draw them in. So she’s working to change that. With support from the McGovern Institute, the National Science Foundation funded Science and Technology Center for Brains, Minds, and Machines, Chomik-Morales is hosting and producing a weekly podcast called “Mi Última Neurona” (“My Last Neuron”), which brings conversations with neuroscientists to Spanish speakers around the world.

Listeners hear how researchers at MIT and other institutions are exploring big concepts like consciousness and neurodegeneration, and learn about the approaches they use to study the brain in humans, animals, and computational models. Chomik-Morales wants listeners to get to know neuroscientists on a personal level too, so she talks with her guests about their career paths, their lives outside the lab, and often, their experiences as immigrants in the United States.

After recording an interview with Chomik-Morales that delved into science, art, and the educational system in his home country of Peru, postdoc Arturo Deza thinks “Mi Última Neurona” has the potential to inspire Spanish speakers in Latin America, as well immigrants in other countries. “Even if you’re not a scientist, it’s really going to captivate you and you’re going to get something out of it,” he says. To that point, Chomik-Morales’s mother has quickly become an enthusiastic listener, and even begun seeking out resources to learn more about the brain on her own.

Chomik-Morales hopes the stories her guests share on “Mi Última Neurona” will inspire a future generation of Hispanic neuroscientists. She also wants listeners to know that a career in science doesn’t have to mean leaving their country behind. “Gain whatever you need to gain from outside, and then, if it’s what you desire, you’re able to go back and help your own community,” she says. With “Mi Última Neurona,” she adds, she feels she is giving back to her roots.

How do illusions trick the brain?

by Dana Boebinger | Jarrod Hicks |

As part of our Ask the Brain series, Jarrod Hicks, a graduate student in Josh McDermott‘s lab and Dana Boebinger, a postdoctoral researcher at the University of Rochester (and former graduate student in Josh McDermott’s lab), answer the question, “How do illusions trick the brain?”

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Graduate student Jarrod Hicks studies how the brain processes sound. Photo: M.E. Megan Hicks

Imagine you’re a detective. Your job is to visit a crime scene, observe some evidence, and figure out what happened. However, there are often multiple stories that could have produced the evidence you observe. Thus, to solve the crime, you can’t just rely on the evidence in front of you – you have to use your knowledge about the world to make your best guess about the most likely sequence of events. For example, if you discover cat hair at the crime scene, your prior knowledge about the world tells you it’s unlikely that a cat is the culprit. Instead, a more likely explanation is that the culprit might have a pet cat.

Although it might not seem like it, this kind of detective work is what your brain is doing all the time. As your senses send information to your brain about the world around you, your brain plays the role of detective, piecing together each bit of information to figure out what is happening in the world. The information from your senses usually paints a pretty good picture of things, but sometimes when this information is incomplete or unclear, your brain is left to fill in the missing pieces with its best guess of what should be there. This means that what you experience isn’t actually what’s out there in the world, but rather what your brain thinks is out there. The consequence of this is that your perception of the world can depend on your experience and assumptions.

Optical illusions

Optical illusions are a great way of showing how our expectations and assumptions affect what we perceive. For example, look at the squares labeled “A” and “B” in the image below.

Checkershadow illusion. Image: Edward H. Adelson

Is one of them lighter than the other? Although most people would agree that the square labeled “B” is much lighter than the one labeled “A,” the two squares are actually the exact same color. You perceive the squares differently because your brain knows, from experience, that shadows tend to make things appear darker than what they actually are. So, despite the squares being physically identical, your brain thinks “B” should be lighter.

Auditory illusions

Tricks of perception are not limited to optical illusions. There are also several dramatic examples of how our expectations influence what we hear. For example, listen to the mystery sound below. What do you hear?

Mystery sound

Because you’ve probably never heard a sound quite like this before, your brain has very little idea about what to expect. So, although you clearly hear something, it might be very difficult to make out exactly what that something is. This mystery sound is something called sine-wave speech, and what you’re hearing is essentially a very degraded sound of someone speaking.

Now listen to a “clean” version of this speech in the audio clip below:

Clean speech

You probably hear a person saying, “the floor was quite slippery.” Now listen to the mystery sound above again. After listening to the original audio, your brain has a strong expectation about what you should hear when you listen to the mystery sound again. Even though you’re hearing the exact same mystery sound as before, you experience it completely differently. (Audio clips courtesy of University of Sussex).

 

Dana Boebinger describes the science of illusions in this McGovern Minute.

Subjective perceptions

These illusions have been specifically designed by scientists to fool your brain and reveal principles of perception. However, there are plenty of real-life situations in which your perceptions strongly depend on expectations and assumptions. For example, imagine you’re watching TV when someone begins to speak to you from another room. Because the noise from the TV makes it difficult to hear the person speaking, your brain might have to fill in the gaps to understand what’s being said. In this case, different expectations about what is being said could cause you to hear completely different things.

Which phrase do you hear?

Listen to the clip below to hear a repeating loop of speech. As the sound plays, try to listen for one of the phrases listed in teal below.

Because the audio is somewhat ambiguous, the phrase you perceive depends on which phrase you listen for. So even though it’s the exact same audio each time, you can perceive something totally different! (Note: the original audio recording is from a football game in which the fans were chanting, “that is embarrassing!”)

Illusions like the ones above are great reminders of how subjective our perceptions can be. In order to make sense of the messy information coming in from our senses, our brains are constantly trying to fill in the blanks and with its best guess of what’s out there. Because of this guesswork, our perceptions depend on our experiences, leading each of us to perceive and interact with the world in a way that’s uniquely ours.

Jarrod Hicks is a PhD candidate in the Department of Brain and Cognitive Sciences at MIT working with Josh McDermott in the Laboratory for Computational Audition. He studies sound segregation, a key aspect of real-world hearing in which a sound source of interest is estimated amid a mixture of competing sources. He is broadly interested in teaching/outreach, psychophysics, computational approaches to represent stimulus spaces, and neural coding of high-level sensory representations.

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Do you have a question for The Brain? Ask it here.

Lindsay Case and Guangyu Robert Yang named 2022 Searle Scholars

Anne Trafton |

MIT cell biologist Lindsay Case and computational neuroscientist Guangyu Robert Yang have been named 2022 Searle Scholars, an award given annually to 15 outstanding U.S. assistant professors who have high potential for ongoing innovative research contributions in medicine, chemistry, or the biological sciences.

Case is an assistant professor of biology, while Yang is an assistant professor of brain and cognitive sciences and electrical engineering and computer science, and an associate investigator at the McGovern Institute for Brain Research. They will each receive $300,000 in flexible funding to support their high-risk, high-reward work over the next three years.

Lindsay Case

Case arrived at MIT in 2021, after completing a postdoc at the University of Texas Southwestern Medical Center in the lab of Michael Rosen. Prior to that, she earned her PhD from the University of North Carolina at Chapel Hill, working in the lab of Clare Waterman at the National Heart Lung and Blood Institute.

Situated in MIT’s Building 68, Case’s lab studies how molecules within cells organize themselves, and how such organization begets cellular function. Oftentimes, molecules will assemble at the cell’s plasma membrane — a complex signaling platform where hundreds of receptors sense information from outside the cell and initiate cellular changes in response. Through her experiments, Case has found that molecules at the plasma membrane can undergo a process known as phase separation, condensing to form liquid-like droplets.

As a Searle Scholar, Case is investigating the role that phase separation plays in regulating a specific class of signaling molecules called kinases. Her team will take a multidisciplinary approach to probe what happens when kinases phase separate into signaling clusters, and what cellular changes occur as a result. Because phase separation is emerging as a promising new target for small molecule therapies, this work will help identify kinases that are strong candidates for new therapeutic interventions to treat diseases such as cancer.

“I am honored to be recognized by the Searle Scholars Program, and thrilled to join such an incredible community of scientists,” Case says. “This support will enable my group to broaden our research efforts and take our preliminary findings in exciting new directions. I look forward to better understanding how phase separation impacts cellular function.”

Guangyu Robert Yang

Before coming to MIT in 2021, Yang trained in physics at Peking University, obtained a PhD in computational neuroscience at New York University with Xiao-Jing Wang, and further trained as a postdoc at the Center for Theoretical Neuroscience of Columbia University, as an intern at Google Brain, and as a junior fellow at the Simons Society of Fellows.

His research team at MIT, the MetaConscious Group, develops models of mental functions by incorporating multiple interacting modules. They are designing pipelines to process and compare large-scale experimental datasets that span modalities ranging from behavioral data to neural activity data to molecular data. These datasets are then be integrated to train individual computational modules based on the experimental tasks that were evaluated such as vision, memory, or movement.

Ultimately, Yang seeks to combine these modules into a “network of networks” that models higher-level brain functions such as the ability to flexibly and rapidly learn a variety of tasks. Such integrative models are rare because, until recently, it was not possible to acquire data that spans modalities and brain regions in real time as animals perform tasks. The time is finally right for integrative network models. Computational models that incorporate such multisystem, multilevel datasets will allow scientists to make new predictions about the neural basis of cognition and open a window to a mathematical understanding the mind.

“This is a new research direction for me, and I think for the field too. It comes with many exciting opportunities as well as challenges. Having this recognition from the Searle Scholars program really gives me extra courage to take on the uncertainties and challenges,” says Yang.

Since 1981, 647 scientists have been named Searle Scholars. Including this year, the program has awarded more than $147 million. Eighty-five Searle Scholars have been inducted into the National Academy of Sciences. Twenty scholars have been recognized with a MacArthur Fellowship, known as the “genius grant,” and two Searle Scholars have been awarded the Nobel Prize in Chemistry. The Searle Scholars Program is funded through the Searle Funds at The Chicago Community Trust and administered by Kinship Foundation.

A brain circuit in the thalamus helps us hold information in mind

Anne Trafton |

As people age, their working memory often declines, making it more difficult to perform everyday tasks. One key brain region linked to this type of memory is the anterior thalamus, which is primarily involved in spatial memory — memory of our surroundings and how to navigate them.

In a study of mice, MIT researchers have identified a circuit in the anterior thalamus that is necessary for remembering how to navigate a maze. The researchers also found that this circuit is weakened in older mice, but enhancing its activity greatly improves their ability to run the maze correctly.

This region could offer a promising target for treatments that could help reverse memory loss in older people, without affecting other parts of the brain, the researchers say.

“By understanding how the thalamus controls cortical output, hopefully we could find more specific and druggable targets in this area, instead of generally modulating the prefrontal cortex, which has many different functions,” says Guoping Feng, the James W. and Patricia T. Poitras Professor in Brain and Cognitive Sciences at MIT, a member of the Broad Institute of Harvard and MIT, and the associate director of the McGovern Institute for Brain Research at MIT.

Feng is the senior author of the study, which appears today in the Proceedings of the National Academy of Sciences. Dheeraj Roy, a NIH K99 Awardee and a McGovern Fellow at the Broad Institute, and Ying Zhang, a J. Douglas Tan Postdoctoral Fellow at the McGovern Institute, are the lead authors of the paper.

Spatial memory

The thalamus, a small structure located near the center of the brain, contributes to working memory and many other executive functions, such as planning and attention. Feng’s lab has recently been investigating a region of the thalamus known as the anterior thalamus, which has important roles in memory and spatial navigation.

Previous studies in mice have shown that damage to the anterior thalamus leads to impairments in spatial working memory. In humans, studies have revealed age-related decline in anterior thalamus activity, which is correlated with lower performance on spatial memory tasks.

The anterior thalamus is divided into three sections: ventral, dorsal, and medial. In a study published last year, Feng, Roy and Zhang studied the role of the anterodorsal (AD) thalamus and anteroventral (AV) thalamus in memory formation. They found that the AD thalamus is involved in creating mental maps of physical spaces, while the AV thalamus helps the brain to distinguish these memories from other memories of similar spaces.

In their new study, the researchers wanted to look more deeply at the AV thalamus, exploring its role in a spatial working memory task. To do that, they trained mice to run a simple T-shaped maze. At the beginning of each trial, the mice ran until they reached the T. One arm was blocked off, forcing them to run down the other arm. Then, the mice were placed in the maze again, with both arms open. The mice were rewarded if they chose the opposite arm from the first run. This meant that in order to make the correct decision, they had to remember which way they had turned on the previous run.

As the mice performed the task, the researchers used optogenetics to inhibit activity of either AV or AD neurons during three different parts of the task: the sample phase, which occurs during the first run; the delay phase, while they are waiting for the second run to begin; and the choice phase, when the mice make their decision which way to turn during the second run.

The researchers found that inhibiting AV neurons during the sample or choice phases had no effect on the mice’s performance, but when they suppressed AV activity during the delay phase, which lasted 10 seconds or longer, the mice performed much worse on the task.

This suggests that the AV neurons are most important for keeping information in mind while it is needed for a task. In contrast, inhibiting the AD neurons disrupted performance during the sample phase but had little effect during the delay phase. This finding was consistent with the research team’s earlier study showing that AD neurons are involved in forming memories of a physical space.

“The anterior thalamus in general is a spatial learning region, but the ventral neurons seem to be needed in this maintenance period, during this short delay,” Roy says. “Now we have two subdivisions within the anterior thalamus: one that seems to help with contextual learning and the other that actually helps with holding this information.”

Age-related decline

The researchers then tested the effects of age on this circuit. They found that older mice (14 months) performed worse on the T-maze task and their AV neurons were less excitable. However, when the researchers artificially stimulated those neurons, the mice’s performance on the task dramatically improved.

Another way to enhance performance in this memory task is to stimulate the prefrontal cortex, which also undergoes age-related decline. However, activating the prefrontal cortex also increases measures of anxiety in the mice, the researchers found.

“If we directly activate neurons in medial prefrontal cortex, it will also elicit anxiety-related behavior, but this will not happen during AV activation,” Zhang says. “That is an advantage of activating AV compared to prefrontal cortex.”

If a noninvasive or minimally invasive technology could be used to stimulate those neurons in the human brain, it could offer a way to help prevent age-related memory decline, the researchers say. They are now planning to perform single-cell RNA sequencing of neurons of the anterior thalamus to find genetic signatures that could be used to identify cells that would make the best targets.

The research was funded, in part, by the Stanley Center for Psychiatric Research at the Broad Institute, the Hock E. Tan and K. Lisa Yang Center for Autism Research at MIT, and the James and Patricia Poitras Center for Psychiatric Disorders Research at MIT.

Circuit that focuses attention brings in wide array of inputs

by David Orenstein | Picower Institute |

In a new brain-wide circuit tracing study, scientists at MIT’s Picower Institute for Learning and Memory focused selective attention on a circuit that governs, fittingly enough, selective attention. The comprehensive maps they produced illustrate how broadly the mammalian brain incorporates and integrates information to focus its sensory resources on its goals.

Working in mice, the team traced thousands of inputs into the circuit, a communication loop between the anterior cingulate cortex (ACC) and the lateral posterior (LP) thalamus. In primates the LP is called the pulvinar. Studies in humans and nonhuman primates have indicated that the byplay of these two regions is critical for brain functions like being able to focus on an object of interest in a crowded scene, says study co-lead author Yi Ning Leow, a graduate student in the lab of senior author Mriganka Sur, the Newton Professor in MIT’s Department of Brain and Cognitive Sciences. Research has implicated dysfunction in the circuit in attention-affecting disorders such as autism and attention deficit/hyperactivity disorder.

The new study in the Journal of Comparative Neurology extends what’s known about the circuit by detailing it in mice, Leow says, importantly showing that the mouse circuit is closely analogous to the primate version even if the LP is proportionately smaller and less evolved than the pulvinar.

“In these rodent models we were able to find very similar circuits,” Leow says. “So we can possibly study these higher-order functions in mice as well. We have a lot more genetic tools in mice so we are better able to look at this circuit.”

The study, also co-led by former MIT undergraduate Blake Zhou, therefore provides a detailed roadmap in the experimentally accessible mouse model for understanding how the ACC and LP cooperate to produce selective attention. For instance, now that Leow and Zhou have located all the inputs that are wired into the circuit, Leow is tapping into those feeds to eavesdrop on the information they are carrying. Meanwhile, she is correlating that information flow with behavior.

“This study lays the groundwork for understanding one of the most important, yet most elusive, components of brain function, namely our ability to selectively attend to one thing out of several, as well as switch attention,” Sur says.

Using virally mediated circuit-tracing techniques pioneered by co-author Ian Wickersham, principal research scientist in brain and cognitive sciences and the McGovern Institute for Brain Research at MIT, the team found distinct sources of input for the ACC and the LP. Generally speaking, the detailed study finds that the majority of inputs to the ACC were from frontal cortex areas that typically govern goal-directed planning, and from higher visual areas. The bulk of inputs to the LP, meanwhile, were from deeper regions capable of providing context such as the mouse’s needs, location and spatial cues, information about movement, and general information from a mix of senses.

So even though focusing attention might seem like a matter of controlling the senses, Leow says, the circuit pulls in a lot of other information as well.

“We’re seeing that it’s not just sensory — there are so many inputs that are coming from non-sensory areas as well, both sub-cortically and cortically,” she says. “It seems to be integrating a lot of different aspects that might relate to the behavioral state of the animal at a given time. It provides a way to provide a lot of internal and special context for that sensory information.”

Given the distinct sets of inputs to each region, the ACC may be tasked with focusing attention on a desired object, while the LP is modulating how the ACC goes about making those computations, accounting for what’s going on both inside and outside the animal. Decoding just what that incoming contextual information is, and what the LP tells the ACC, are the key next steps, Leow says. Another clear set of questions the study raises are what are the circuit’s outputs. In other words, after it integrates all this information, what does it do with it?

The paper’s other authors are Heather Sullivan and Alexandria Barlowe.

A National Science Scholarship, the National Institutes of Health, and the JPB Foundation provided support for the study.

Approaching human cognition from many angles

by Alli Armijo | MIT News correspondent |

In January, as the Charles River was starting to freeze over, Keith Murray and the other members of MIT’s men’s heavyweight crew team took to erging on the indoor rowing machine. For 80 minutes at a time, Murray endured one of the most grueling workouts of his college experience. To distract himself from the pain, he would talk with his teammates, covering everything from great philosophical ideas to personal coffee preferences.

For Murray, virtually any conversation is an opportunity to explore how people think and why they think in certain ways. Currently a senior double majoring in computation and cognition, and linguistics and philosophy, Murray tries to understand the human experience based on knowledge from all of these fields.

“I’m trying to blend different approaches together to understand the complexities of human cognition,” he says. “For example, from a physiological perspective, the brain is just billions of neurons firing all at once, but this hardly scratches the surface of cognition.”

Murray grew up in Corydon, Indiana, where he attended the Indiana Academy for Science, Mathematics, and Humanities during his junior year of high school. He was exposed to philosophy there, learning the ideas of Plato, Socrates, and Thomas Aquinas, to name a few. When looking at colleges, Murray became interested in MIT because he wanted to learn about human thought processes from different perspectives. “Coming to MIT, I knew I wanted to do something philosophical. But I wanted to also be on the more technical side of things,” he says.

Once on campus, Murray immediately pursued an opportunity through the Undergraduate Research Opportunity Program (UROP) in the Digital Humanities Lab. There he worked with language-processing technology to analyze gendered language in various novels, with the end goal of displaying the data for an online audience. He learned about the basic mathematical models used for analyzing and presenting data online, to study the social implications of linguistic phrases and expressions.

Murray also joined the Concourse learning community, which brought together different perspectives from the humanities, sciences, and math in a weekly seminar. “I was exposed to some excellent examples of how to do interdisciplinary work,” he recalls.

In the summer before his sophomore year, Murray took a position as a researcher in the Harnett Lab, where instead of working with novels, he was working with mice. Alongside postdoc Lucas Fisher, Murray trained mice to do navigational tasks using virtual reality equipment. His goal was to explore neural encoding in navigation, understanding why the mice behaved in certain ways after being shown certain stimuli on the screens. Spending time in the lab, Murray became increasingly interested in neuroscience and the biological components behind human thought processes.

He sought out other neuroscience-related research experiences, which led him to explore a SuperUROP project in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). Working under Professor Nancy Lynch, he designed theoretical models of the retina using machine learning. Murray was excited to apply the techniques he learned in 9.40 (Introduction to Neural Computation) to address complex neurological problems. Murray considers this one of his most challenging research experiences, as the experience was entirely online.

“It was during the pandemic, so I had to learn a lot on my own; I couldn’t exactly do research in a lab. It was a big challenge, but at the end, I learned a lot and ended up getting a publication out of it,” he reflects.

This past semester, Murray has worked in the lab of Professor Ila Fiete in the McGovern Institute for Brain Research, constructing deep-learning models of animals performing navigational tasks. Through this UROP, which builds on his final project from Fiete’s class 9.49 (Neural Circuits for Cognition), Murray has been working to incorporate existing theoretical models of the hippocampus to investigate the intersection between artificial intelligence and neuroscience.

Reflecting on his varied research experiences, Murray says they have shown him new ways to explore the human brain from multiple perspectives, something he finds helpful as he tries to understand the complexity of human behavior.

Outside of his academic pursuits, Murray has continued to row with the crew team, where he walked on his first year. He sees rowing as a way to build up his strength, both physically and mentally. “When I’m doing my class work or I’m thinking about projects, I am using the same mental toughness that I developed during rowing,” he says. “That’s something I learned at MIT, to cultivate the dedication you put toward something. It’s all the same mental toughness whether you apply it to physical activities like rowing, or research projects.”

Looking ahead, Murray hopes to pursue a PhD in neuroscience, looking to find ways to incorporate his love of philosophy and human thought into his cognitive research. “I think there’s a lot more to do with neuroscience, especially with artificial intelligence. There are so many new technological developments happening right now,” he says.

Seven from MIT elected to American Academy of Arts and Sciences for 2022

by MIT News Office |

Seven MIT faculty members are among more than 250 leaders from academia, the arts, industry, public policy, and research elected to the American Academy of Arts and Sciences, the academy announced Thursday.

One of the nation’s most prestigious honorary societies, the academy is also a leading center for independent policy research. Members contribute to academy publications, as well as studies of science and technology policy, energy and global security, social policy and American institutions, the humanities and culture, and education.

Those elected from MIT this year are:

  • Alberto Abadie, professor of economics and associate director of the Institute for Data, Systems, and Society
  • Regina Barzilay, the School of Engineering Distinguished Professor for AI and Health
  • Roman Bezrukavnikov, professor of mathematics
  • Michale S. Fee, the Glen V. and Phyllis F. Dorflinger Professor and head of the Department of Brain and Cognitive Sciences
  • Dina Katabi, the Thuan and Nicole Pham Professor
  • Ronald T. Raines, the Roger and Georges Firmenich Professor of Natural Products Chemistry
  • Rebecca R. Saxe, the John W. Jarve Professor of Brain and Cognitive Sciences

“We are celebrating a depth of achievements in a breadth of areas,” says David Oxtoby, president of the American Academy. “These individuals excel in ways that excite us and inspire us at a time when recognizing excellence, commending expertise, and working toward the common good is absolutely essential to realizing a better future.”

Since its founding in 1780, the academy has elected leading thinkers from each generation, including George Washington and Benjamin Franklin in the 18th century, Maria Mitchell and Daniel Webster in the 19th century, and Toni Morrison and Albert Einstein in the 20th century. The current membership includes more than 250 Nobel and Pulitzer Prize winners.

Aging Brain Initiative awards fund five new ideas to study, fight neurodegeneration

Anne Trafton |

Neurodegenerative diseases are defined by an increasingly widespread and debilitating death of nervous system cells, but they also share other grim characteristics: Their cause is rarely discernible and they have all eluded cures. To spur fresh, promising approaches and to encourage new experts and expertise to join the field, MIT’s Aging Brain Initiative (ABI) this month awarded five seed grants after a competition among labs across the Institute.

Founded in 2015 by nine MIT faculty members, the ABI promotes research, symposia, and related activities to advance fundamental insights that can lead to clinical progress against neurodegenerative conditions, such as Alzheimer’s disease, with an age-related onset. With an emphasis on spurring research at an early stage before it is established enough to earn more traditional funding, the ABI derives support from philanthropic gifts.

“Solving the mysteries of how health declines in the aging brain and turning that knowledge into effective tools, treatments, and technologies is of the utmost urgency given the millions of people around the world who suffer with no meaningful treatment options,” says ABI director and co-founder Li-Huei Tsai, the Picower Professor of Neuroscience in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences. “We were very pleased that many groups across MIT were eager to contribute their expertise and creativity to that goal. From here, five teams will be able to begin testing their innovative ideas and the impact they could have.”

To address the clinical challenge of accurately assessing cognitive decline during Alzheimer’s disease progression and healthy aging, a team led by Thomas Heldt, associate professor of electrical and biomedical engineering in the Department of Electrical Engineering and Computer Science (EECS) and the Institute for Medical Engineering and Science, proposes to use artificial intelligence tools to bring diagnostics based on eye movements during cognitive tasks to everyday consumer electronics such as smartphones and tablets. By moving these capabilities to common at-home platforms, the team, which also includes EECS Associate Professor Vivian Sze, hopes to increase monitoring beyond what can only be intermittently achieved with high-end specialized equipment and dedicated staffing in specialists’ offices. The team will pilot their technology in a small study at Boston Medical Center in collaboration with neurosurgeon James Holsapple.

Institute Professor Ann Graybiel’s lab in the Department of Brain and Cognitive Sciences (BCS) and the McGovern Institute for Brain Research will test the hypothesis that mutations on a specific gene may lead to the early emergence of Alzheimer’s disease (AD) pathology in the striatum. That’s a a brain region crucial for motivation and movement that is directly and severely impacted by other neurodegenerative disorders including Parkinson’s and Huntington’s diseases, but that has largely been unstudied in Alzheimer’s. By editing the mutations into normal and AD-modeling mice, Research Scientist Ayano Matsushima and Graybiel hope to determine whether and how pathology, such as the accumulation of amyloid proteins, may result. Determining that could provide new insight into the progression of disease and introduce a new biomarker in a region that virtually all other studies have overlooked.

Numerous recent studies have highlighted a potential role for immune inflammation in Alzheimer’s disease. A team led by Gloria Choi, the Mark Hyman Jr. Associate Professor in BCS and The Picower Institute for Learning and Memory, will track one potential source of such activity by determining whether the brain’s meninges, which envelop the brain, becomes a means for immune cells activated by gut bacteria to circulate near the brain, where they may release signaling molecules that promote Alzheimer’s pathology. Working in mice, Choi’s lab will test whether such activity is prone to increase in Alzheimer’s and whether it contributes to disease.

A collaboration led by Peter Dedon, the Singapore Professor in MIT’s Department of Biological Engineering, will explore whether Alzheimer’s pathology is driven by dysregulation of transfer RNAs (tRNAs) and the dozens of natural tRNA modifications in the epitranscriptome, which play a key role in the process by which proteins are assembled based on genetic instructions. With Benjamin Wolozin of Boston University, Sherif Rashad of Tohoku University in Japan, and Thomas Begley of the State University of New York at Albany, Dedon will assess how the tRNA pool and epitranscriptome may differ in Alzheimer’s model mice and whether genetic instructions mistranslated because of tRNA dysregulation play a role in Alzheimer’s disease.

With her seed grant, Ritu Raman, the d’Arbeloff Assistant Professor of Mechanical Engineering, is launching an investigation of possible disruption of intercellular messages in amyotrophic lateral sclerosis (ALS), a terminal condition in which motor neuron causes loss of muscle control. Equipped with a new tool to finely sample interstitial fluid within tissues, Raman’s team will be able to monitor and compare cell-cell signaling in models of the junction between nerve and muscle. These models will be engineered from stem cells derived from patients with ALS. By studying biochemical signaling at the junction the lab hopes to discover new targets that could be therapeutically modified.

Major support for the seed grants, which provide each lab with $100,000, came from generous gifts by David Emmes SM ’76; Kathleen SM ’77, PhD ’86 and Miguel Octavio; the Estate of Margaret A. Ridge-Pappis, wife of the late James Pappis ScD ’59; the Marc Haas Foundation; and the family of former MIT President Paul Gray ’54, SM ’55, ScD ‘60, with additional funding from many annual fund donors to the Aging Brain Initiative Fund.

What words can convey

by Jennifer Michalowski |

From search engines to voice assistants, computers are getting better at understanding what we mean. That’s thanks to language processing programs that make sense of a staggering number of words, without ever being told explicitly what those words mean. Such programs infer meaning instead through statistics—and a new study reveals that this computational approach can assign many kinds of information to a single word, just like the human brain.

The study, published April 14, 2022, in the journal Nature Human Behavior, was co-led by Gabriel Grand, a graduate student at MIT’s Computer Science and Artificial Intelligence Laboratory, and Idan Blank, an assistant professor at the University of California, Los Angeles, and supervised by McGovern Investigator Ev Fedorenko, a cognitive neuroscientist who studies how the human brain uses and understands language, and Francisco Pereira at the National Institute of Mental Health. Fedorenko says the rich knowledge her team was able to find within computational language models demonstrates just how much can be learned about the world through language alone.

Early language models

The research team began its analysis of statistics-based language processing models in 2015, when the approach was new. Such models derive meaning by analyzing how often pairs of words co-occur in texts and using those relationships to assess the similarities of words’ meanings. For example, such a program might conclude that “bread” and “apple” are more similar to one another than they are to “notebook,” because “bread” and “apple” are often found in proximity to words like “eat” or “snack,” whereas “notebook” is not.

The models were clearly good at measuring words’ overall similarity to one another. But most words carry many kinds of information, and their similarities depend on which qualities are being evaluated. “Humans can come up with all these different mental scales to help organize their understanding of words,” explains Grand, a former undergraduate researcher in the Fedorenko lab. For examples, he says, “dolphins and alligators might be similar in size, but one is much more dangerous than the other.”

Grand and Idan Blank, who was then a graduate student at the McGovern Institute, wanted to know whether the models captured that same nuance. And if they did, how was the information organized?

To learn how the information in such a model stacked up to humans’ understanding of words, the team first asked human volunteers to score words along many different scales: Were the concepts those words conveyed big or small, safe or dangerous, wet or dry? Then, having mapped where people position different words along these scales, they looked to see whether language processing models did the same.

Grand explains that distributional semantic models use co-occurrence statistics to organize words into a huge, multidimensional matrix. The more similar words are to one another, the closer they are within that space. The dimensions of the space are vast, and there is no inherent meaning built into its structure. “In these word embeddings, there are hundreds of dimensions, and we have no idea what any dimension means,” he says. “We’re really trying to peer into this black box and say, ‘is there structure in here?’”

Word-vectors in the category ‘animals’ (blue circles) are orthogonally projected (light-blue lines) onto the feature subspace for ‘size’ (red line), defined as the vector difference between large−→−− and small−→−− (red circles). The three dimensions in this figure are arbitrary and were chosen via principal component analysis to enhance visualization (the original GloVe word embedding has 300 dimensions, and projection happens in that space). Image: Fedorenko lab

Specifically, they asked whether the semantic scales they had asked their volunteers use were represented in the model. So they looked to see where words in the space lined up along vectors defined by the extremes of those scales. Where did dolphins and tigers fall on line from “big” to “small,” for example? And were they closer together along that line than they were on a line representing danger (“safe” to “dangerous”)?

Across more than 50 sets of world categories and semantic scales, they found that the model had organized words very much like the human volunteers. Dolphins and tigers were judged to be similar in terms of size, but far apart on scales measuring danger or wetness. The model had organized the words in a way that represented many kinds of meaning—and it had done so based entirely on the words’ co-occurrences.

That, Fedorenko says, tells us something about the power of language. “The fact that we can recover so much of this rich semantic information from just these simple word co-occurrence statistics suggests that this is one very powerful source of learning about things that you may not even have direct perceptual experience with.”

Three from MIT awarded 2022 Paul and Daisy Soros Fellowships for New Americans

by Julia Mongo | Office of Distinguished Fellowships |

MIT graduate student Fernanda De La Torre, alumna Trang Luu ’18, SM ’20, and senior Syamantak Payra are recipients of the 2022 Paul and Daisy Soros Fellowships for New Americans.

De La Torre, Luu, and Payra are among 30 New Americans selected from a pool of over 1,800 applicants. The fellowship honors the contributions of immigrants and children of immigrants by providing $90,000 in funding for graduate school.

Students interested in applying to the P.D. Soros Fellowship for future years may contact Kim Benard, associate dean of distinguished fellowships in Career Advising and Professional Development.

Fernanda De La Torre

Fernanda De La Torre is a PhD student in the Department of Brain and Cognitive Sciences. With Professor Josh McDermott, she studies how we integrate vision and sound, and with Professor Robert Yang, she develops computational models of imagination.

De La Torre spent her early childhood with her younger sister and grandmother in Guadalajara, Mexico. At age 12, she crossed the Mexican border to reunite with her mother in Kansas City, Missouri. Shortly after, an abusive home environment forced De La Torre to leave her family and support herself throughout her early teens.

Despite her difficult circumstances, De La Torre excelled academically in high school. By winning various scholarships that would discretely take applications from undocumented students, she was able to continue her studies in computer science and mathematics at Kansas State University. There, she became intrigued by the mysteries of the human mind. During college, De La Torre received invaluable mentorship from her former high school principal, Thomas Herrera, who helped her become documented through the Violence Against Women Act. Her college professor, William Hsu, supported her interests in artificial intelligence and encouraged her to pursue a scientific career.

After her undergraduate studies, De La Torre won a post-baccalaureate fellowship from the Department of Brain and Cognitive Sciences at MIT, where she worked with Professor Tomaso Poggio on the theory of deep learning. She then transitioned into the department’s PhD program. Beyond contributing to scientific knowledge, De La Torre plans to use science to create spaces where all people, including those from backgrounds like her own, can innovate and thrive.

She says: “Immigrants face many obstacles, but overcoming them gives us a unique strength: We learn to become resilient, while relying on friends and mentors. These experiences foster both the desire and the ability to pay it forward to our community.”

Trang Luu

Trang Luu graduated from MIT with a BS in mechanical engineering in 2018, and a master of engineering degree in 2020. Her Soros award will support her graduate studies at Harvard University in the MBA/MS engineering sciences program.

Born in Saigon, Vietnam, Luu was 3 when her family immigrated to Houston, Texas. Watching her parents’ efforts to make a living in a land where they did not understand the culture or speak the language well, Luu wanted to alleviate hardship for her family. She took full responsibility for her education and found mentors to help her navigate the American education system. At home, she assisted her family in making and repairing household items, which fueled her excitement for engineering.

As an MIT undergraduate, Luu focused on assistive technology projects, applying her engineering background to solve problems impeding daily living. These projects included a new adaptive socket liner for below-the-knee amputees in Kenya, Ethiopia, and Thailand; a walking stick adapter for wheelchairs; a computer head pointer for patients with limited arm mobility, a safer makeshift cook stove design for street vendors in South Africa; and a quicker method to test new drip irrigation designs. As a graduate student in MIT D-Lab under the direction of Professor Daniel Frey, Luu was awarded a National Science Foundation Graduate Research Fellowship. In her graduate studies, Luu researched methods to improve evaporative cooling devices for off-grid farmers to reduce rapid fruit and vegetable deterioration.

These projects strengthened Luu’s commitment to innovating new technology and devices for people struggling with basic daily tasks. During her senior year, Luu collaborated on developing a working prototype of a wearable device that noninvasively reduces hand tremors associated with Parkinson’s disease or essential tremor. Observing patients’ joy after their tremors stopped compelled Luu and three co-founders to continue developing the device after college. Four years later, Encora Therapeutics has accomplished major milestones, including Breakthrough Device designation by the U.S. Food and Drug Administration.

Syamantak Payra

Hailing from Houston, Texas, Syamantak Payra is a senior majoring in electrical engineering and computer science, with minors in public policy and entrepreneurship and innovation. He will be pursuing a PhD in engineering at Stanford University, with the goal of creating new biomedical devices that can help improve daily life for patients worldwide and enhance health care outcomes for decades to come.

Payra’s parents had emigrated from India, and he grew up immersed in his grandparents’ rich Bengali culture. As a high school student, he conducted projects with NASA engineers at Johnson Space Center, experimented at home with his scientist parents, and competed in spelling bees and science fairs across the United States. Through these avenues and activities, Syamantak not only gained perspectives on bridging gaps between people, but also found passions for language, scientific discovery, and teaching others.

After watching his grandmother struggle with asthma and chronic obstructive pulmonary disease and losing his baby brother to brain cancer, Payra devoted himself to trying to use technology to solve health-care challenges. Payra’s proudest accomplishments include building a robotic leg brace for his paralyzed teacher and conducting free literacy workshops and STEM outreach programs that reached nearly a thousand underprivileged students across the Greater Houston Area.

At MIT, Payra has worked in Professor Yoel Fink’s research laboratory, creating digital sensor fibers that have been woven into intelligent garments that can assist in diagnosing illnesses, and in Professor Joseph Paradiso’s research laboratory, where he contributed to next-generation spacesuit prototypes that better protect astronauts on spacewalks. Payra’s research has been published by multiple scientific journals, and he was inducted into the National Gallery of America’s Young Inventors.