Picower Institute

Subterms

    Latest story

    138 Shares159 Views

    Creating new skills and new connections with MIT’s Quantitative Methods Workshop

    by

    Starting on New Year’s Day, when many people were still clinging to holiday revelry, scores of students and faculty members from about a dozen partner universities instead flipped open their laptops for MIT’s Quantitative Methods Workshop, a jam-packed, weeklong introduction to how computational and mathematical techniques can be applied to neuroscience and biology research. But don’t think of QMW as a “crash course.” Instead the program’s purpose is to help elevate each participant’s scientific outlook, both through the skills and concepts it imparts and the community it creates.

    “It broadens their horizons, it shows them significant applications they’ve never thought of, and introduces them to people whom as researchers they will come to know and perhaps collaborate with one day,” says Susan L. Epstein, a Hunter College computer science professor and education coordinator of MIT’s Center for Brains, Minds, and Machines, which hosts the program with the departments of Biology and Brain and Cognitive Sciences and The Picower Institute for Learning and Memory. “It is a model of interdisciplinary scholarship.”

    This year 83 undergraduates and faculty members from institutions that primarily serve groups underrepresented in STEM fields took part in the QMW, says organizer Mandana Sassanfar, senior lecturer and director of diversity and science outreach across the four hosting MIT entities. Since the workshop launched in 2010, it has engaged more than 1,000 participants, of whom more than 170 have gone on to participate in MIT Summer Research Programs (such as MSRP-BIO), and 39 have come to MIT for graduate school.

    Individual goals, shared experience

    Undergraduates and faculty in various STEM disciplines often come to QMW to gain an understanding of, or expand their expertise in, computational and mathematical data analysis. Computer science- and statistics-minded participants come to learn more about how such techniques can be applied in life sciences fields. In lectures; in hands-on labs where they used the computer programming language Python to process, analyze, and visualize data; and in less formal settings such as tours and lunches with MIT faculty, participants worked and learned together, and informed each other’s perspectives.

    Brain and Cognitive Sciences Professor Nancy Kanwisher delivers a lecture in MIT’s Building 46 on functional brain imaging to QMW participants.

    Photo: Mandana Sassanfar

    Previous item
    Next item

    And regardless of their field of study, participants made connections with each other and with the MIT students and faculty who taught and spoke over the course of the week.

    Hunter College computer science sophomore Vlad Vostrikov says that while he has already worked with machine learning and other programming concepts, he was interested to “branch out” by seeing how they are used to analyze scientific datasets. He also valued the chance to learn the experiences of the graduate students who teach QMW’s hands-on labs.

    “This was a good way to explore computational biology and neuroscience,” Vostrikov says. “I also really enjoy hearing from the people who teach us. It’s interesting to hear where they come from and what they are doing.”

    Jariatu Kargbo, a biology and chemistry sophomore at University of Maryland Baltimore County, says when she first learned of the QMW she wasn’t sure it was for her. It seemed very computation-focused. But her advisor Holly Willoughby encouraged Kargbo to attend to learn about how programming could be useful in future research — currently she is taking part in research on the retina at UMBC. More than that, Kargbo also realized it would be a good opportunity to make connections at MIT in advance of perhaps applying for MSRP this summer.

    “I thought this would be a great way to meet up with faculty and see what the environment is like here because I’ve never been to MIT before,” Kargbo says. “It’s always good to meet other people in your field and grow your network.”

    QMW is not just for students. It’s also for their professors, who said they can gain valuable professional education for their research and teaching.

    Fayuan Wen, an assistant professor of biology at Howard University, is no stranger to computational biology, having performed big data genetic analyses of sickle cell disease (SCD). But she’s mostly worked with the R programming language and QMW’s focus is on Python. As she looks ahead to projects in which she wants analyze genomic data to help predict disease outcomes in SCD and HIV, she says a QMW session delivered by biology graduate student Hannah Jacobs was perfectly on point.

    “This workshop has the skills I want to have,” Wen says.

    Moreover, Wen says she is looking to start a machine-learning class in the Howard biology department and was inspired by some of the teaching materials she encountered at QMW — for example, online curriculum modules developed by Taylor Baum, an MIT graduate student in electrical engineering and computer science and Picower Institute labs, and Paloma Sánchez-Jáuregui, a coordinator who works with Sassanfar.

    Tiziana Ligorio, a Hunter College computer science doctoral lecturer who together with Epstein teaches a deep machine-learning class at the City University of New York campus, felt similarly. Rather than require a bunch of prerequisites that might drive students away from the class, Ligorio was looking to QMW’s intense but introductory curriculum as a resource for designing a more inclusive way of getting students ready for the class.

    Instructive interactions

    Each day runs from 9 a.m. to 5 p.m., including morning and afternoon lectures and hands-on sessions. Class topics ranged from statistical data analysis and machine learning to brain-computer interfaces, brain imaging, signal processing of neural activity data, and cryogenic electron microscopy.

    “This workshop could not happen without dedicated instructors — grad students, postdocs, and faculty — who volunteer to give lectures, design and teach hands-on computer labs, and meet with students during the very first week of January,” Saassanfar says.

    MIT assistant professor of biology Brady Weissbourd (center) converses with QMW student participants during a lunch break.

    Photo: Mandana Sassanfar

    Previous item
    Next item

    The sessions surround student lunches with MIT faculty members. For example, at midday Jan. 2, assistant professor of biology Brady Weissbourd, an investigator in the Picower Institute, sat down with seven students in one of Building 46’s curved sofas to field questions about his neuroscience research in jellyfish and how he uses quantitative techniques as part of that work. He also described what it’s like to be a professor, and other topics that came to the students’ minds.

    Then the participants all crossed Vassar Street to Building 26’s Room 152, where they formed different but similarly sized groups for the hands-on lab “Machine learning applications to studying the brain,” taught by Baum. She guided the class through Python exercises she developed illustrating “supervised” and “unsupervised” forms of machine learning, including how the latter method can be used to discern what a person is seeing based on magnetic readings of brain activity.

    As students worked through the exercises, tablemates helped each other by supplementing Baum’s instruction. Ligorio, Vostrikov, and Kayla Blincow, assistant professor of biology at the University of the Virgin Islands, for instance, all leapt to their feet to help at their tables.

    Hunter College lecturer of computer science Tiziana Ligorio (standing) explains a Python programming concept to students at her table during a workshop session.

    Photo: David Orenstein

    Previous item
    Next item

    At the end of the class, when Baum asked students what they had learned, they offered a litany of new knowledge. Survey data that Sassanfar and Sánchez-Jáuregui use to anonymously track QMW outcomes, revealed many more such attestations of the value of the sessions. With a prompt asking how one might apply what they’ve learned, one respondent wrote: “Pursue a research career or endeavor in which I apply the concepts of computer science and neuroscience together.”

    Enduring connections

    While some new QMW attendees might only be able to speculate about how they’ll apply their new skills and relationships, Luis Miguel de Jesús Astacio could testify to how attending QMW as an undergraduate back in 2014 figured into a career where he is now a faculty member in physics at the University of Puerto Rico Rio Piedras Campus. After QMW, he returned to MIT that summer as a student in the lab of neuroscientist and Picower Professor Susumu Tonegawa. He came back again in 2016 to the lab of physicist and Francis Friedman Professor Mehran Kardar. What’s endured for the decade has been his connection to Sassanfar. So while he was once a student at QMW, this year he was back with a cohort of undergraduates as a faculty member.

    Michael Aldarondo-Jeffries, director of academic advancement programs at the University of Central Florida, seconded the value of the networking that takes place at QMW. He has brought students for a decade, including four this year. What he’s observed is that as students come together in settings like QMW or UCF’s McNair program, which helps to prepare students for graduate school, they become inspired about a potential future as researchers.

    “The thing that stands out is just the community that’s formed,” he says. “For many of the students, it’s the first time that they’re in a group that understands what they’re moving toward. They don’t have to explain why they’re excited to read papers on a Friday night.”

    Or why they are excited to spend a week including New Year’s Day at MIT learning how to apply quantitative methods to life sciences data. More

    More stories

    • 100 Shares119 Views

      in Data Management & Statistics

      Summer research offers a springboard to advanced studies

      by

      Doctoral studies at MIT aren’t a calling for everyone, but they can be for anyone who has had opportunities to discover that science and technology research is their passion and to build the experience and skills to succeed. For Taylor Baum, Josefina Correa Menéndez, and Karla Alejandra Montejo, three graduate students in just one lab of The Picower Institute for Learning and Memory, a pivotal opportunity came via the MIT Summer Research Program in Biology and Neuroscience (MSRP-Bio). When a student finds MSRP-Bio, it helps them find their future in research. 

      In the program, undergraduate STEM majors from outside MIT spend the summer doing full-time research in the departments of Biology, Brain and Cognitive Sciences (BCS), or the Center for Brains, Minds and Machines (CBMM). They gain lab skills, mentoring, preparation for graduate school, and connections that might last a lifetime. Over the last two decades, a total of 215 students from underrepresented minority groups, who are from economically disadvantaged backgrounds, first-generation or nontraditional college students, or students with disabilities have participated in research in BCS or CBMM labs.  

      Like Baum, Correa Menéndez, and Montejo, the vast majority go on to pursue graduate studies, says Diversity and Outreach Coordinator Mandana Sassanfar, who runs the program. For instance, among 91 students who have worked in Picower Institute labs, 81 have completed their undergraduate studies. Of those, 46 enrolled in PhD programs at MIT or other schools such as Cornell, Yale, Stanford, and Princeton universities, and the University of California System. Another 12 have gone to medical school, another seven are in MD/PhD programs, and three have earned master’s degrees. The rest are studying as post-baccalaureates or went straight into the workforce after earning their bachelor’s degree. 

      After participating in the program, Baum, Correa Menéndez, and Montejo each became graduate students in the research group of Emery N. Brown, the Edward Hood Taplin Professor of Computational Neuroscience and Medical Engineering in The Picower Institute and the Institute for Medical Engineering and Science. The lab combines statistical, computational, and experimental neuroscience methods to study how general anesthesia affects the central nervous system to ultimately improve patient care and advance understanding of the brain. Brown says the students have each been doing “off-the-scale” work, in keeping with the excellence he’s seen from MSRP BIO students over the years. For example, on Aug. 10 Baum and Correa Menéndez were honored with MathWorks Fellowships.

      “I think MSRP is fantastic. Mandana does this amazing job of getting students who are quite talented to come to MIT to realize that they can move their game to the next level. They have the capacity to do it. They just need the opportunities,” Brown says. “These students live up to the expectations that you have of them. And now as graduate students, they’re taking on hard problems and they’re solving them.” 

      Paths to PhD studies 

      Pursuing a PhD is hardly a given. Many young students have never considered graduate school or specific fields of study like neuroscience or electrical engineering. But Sassanfar engages students across the country to introduce them to the opportunity MSRP-Bio provides to gain exposure, experience, and mentoring in advanced fields. Every fall, after the program’s students have returned to their undergraduate institutions, she visits schools in places as far flung as Florida, Maryland, Puerto Rico, and Texas and goes to conferences for diverse science communities such as ABRCMS and SACNAS to spread the word. 

      Taylor Baum

      Photo courtesy of Taylor Baum.

      Previous item
      Next item

      When Baum first connected with the program in 2017, she was finding her way at Penn State University. She had been majoring in biology and music composition but had just switched the latter to engineering following a conversation over coffee exposing her to brain-computer interfacing technology, in which detecting brain signals of people with full-body paralysis could improve their quality of life by enabling control of computers or wheelchairs. Baum became enthusiastic about the potential to build similar systems, but as a new engineering student, she struggled to find summer internships and research opportunities. 

      “I got rejected from every single progam except the MIT Center for Brains, Minds and Machines MSRP,” she recalls with a chuckle. 

      Baum thrived in MSRP-Bio, working in Brown’s lab for three successive summers. At each stage, she said, she gained more research skills, experience, and independence. When she graduated, she was sure she wanted to go to graduate school and applied to four of her dream schools. She accepted MIT’s offer to join the Department of Electrical Engineering and Computer Science, where she is co-advised by faculty members there and by Brown. She is now working to develop a system grounded in cardiovascular physiology that can improve blood pressure management. A tool for practicing anesthesiologists, the system automates the dosing of drugs to maintain a patient’s blood pressure at safe levels in the operating room or intensive care unit. 

      More than that, Baum not only is leading an organization advancing STEM education in Puerto Rico, but also is helping to mentor a current MSRP-Bio student in the Brown lab. 

      “MSRP definitely bonds everyone who has participated in it,” Baum says. “If I see anyone who I know participated in MSRP, we could have an immediate conversation. I know that most of us, if we needed help, we’d feel comfortable asking for help from someone from MSRP. With that shared experience, we have a sense of camaraderie, and community.” 

      In fact, a few years ago when a former MSRP-Bio student named Karla Montejo was applying to MIT, Baum provided essential advice and feedback about the application process, Montejo says. Now, as a graduate student, Montejo has become a mentor for the program in her own right, Sassanfar notes. For instance, Montejo serves on program alumni panels that advise new MSRP-Bio students. 

      Karla Alejandra Montejo

      Photo courtesy of Karla Alejandra Montejo.

      Previous item
      Next item

      Montejo’s family immigrated to Miami from Cuba when she was a child. The magnet high school she attended was so new that students were encouraged to help establish the school’s programs. She forged a path into research. 

      “I didn’t even know what research was,” she says. “I wanted to be a doctor, and I thought maybe it would help me on my resume. I thought it would be kind of like shadowing, but no, it was really different. So I got really captured by research when I was in high school.” 

      Despite continuing to pursue research in college at Florida International University, Montejo didn’t get into graduate school on her first attempt because she hadn’t yet learned how to focus her application. But Sassanfar had visited FIU to recruit students and through that relationship Montejo had already gone through MIT’s related Quantitative Methods Workshop (QMW). So Montejo enrolled in MSRP-Bio, working in the CBMM-affiliated lab of Gabriel Kreiman at Boston Children’s Hospital. 

      “I feel like Mandana really helped me out, gave me a break, and the MSRP experience pretty much solidified that I really wanted to come to MIT,” Montejo says. 

      In the QMW, Montejo learned she really liked computational neuroscience, and in Kreiman’s lab she got to try her hand at computational modeling of the cognition involved in making perceptual sense of complex scenes. Montejo realized she wanted to work on more biologically based neuroscience problems. When the summer ended, because she was off the normal graduate school cycle for now, she found a two-year post-baccalaurate program at Mayo Clinic studying the role a brain cell type called astrocytes might have in the Parkinson’s disease treatment deep brain stimulation. 

      When it came time to reapply to graduate schools (with the help of Baum and others in the BCS Application Assistance Program) Montejo applied to MIT and got in, joining the Brown lab. Now she’s working on modeling the role of  metabolic processes in the changing of brain rhythms under anesthesia, taking advantage of how general anesthesia predictably changes brain states. The effects anesthetic drugs have on cell metabolism and the way that ultimately affects levels of consciousness reveals important aspects of how metabolism affects brain circuits and systems. Earlier this month, for instance, Montejo co-led a paper the lab published in The Proceedings of the National Academy of Sciences detailing the neuroscience of a patient’s transition into an especially deep state of unconsciousness called “burst suppression.” 

      Josefina Correa Menendez

      Photo: David Orenstein

      Previous item
      Next item

      A signature of the Brown lab’s work is rigorous statistical analysis and methods, for instance to discern brain arousal states from EEG measures of brain rhythms. A PhD candidate in MIT’s Interdisciplinary Doctoral Program in Statistics, Correa Menéndez is advancing the use of Bayesian hierarchical models for neural data analysis. These statistical models offer a principled way of pooling information across datasets. One of her models can help scientists better understand the way neurons can “spike” with electrical activity when the brain is presented with a stimulus. The other’s power is in discerning critical features such as arousal states of the brain under general anesthesia from electrophysiological recordings. 

      Though she now works with complex equations and computations as a PhD candidate in neuroscience and statistics, Correa Menéndez was mostly interested in music art as a high school student at Academia María Reina in San Juan and then architecture in college at the University of Puerto Rico at Río Piedras. It was discussions at the intersection of epistemology and art during an art theory class that inspired Correa Menéndez to switch her major to biology and to take computer science classes, too. 

      When Sassanfar visited Puerto Rico in 2017, a computer science professor (Patricia Ordóñez) suggested that Correa Menéndez apply for a chance to attend the QMW. She did, and that led her to also participate in MSRP-Bio in the lab of Sherman Fairchild Professor Matt Wilson (a faculty member in BCS, CBMM, and the Picower Institute). She joined in the lab’s studies of how spatial memories are represented in the hippocampus and how the brain makes use of those memories to help understand the world around it. With mentoring from then-postdoc Carmen Varela (now a faculty member at Florida State University), the experience not only exposed her to neuroscience, but also helped her gain skills and experience with lab experiments, building research tools, and conducting statistical analyses. She ended up working in the Wilson lab as a research scholar for a year and began her graduate studies in September 2018.  

      Classes she took with Brown as a research scholar inspired her to join his lab as a graduate student. 

      “Taking the classes with Emery and also doing experiments made me aware of the role of statistics in the scientific process: from the interpretation of results to the analysis and the design of experiments,” she says. “More often than not, in science, statistics becomes this sort of afterthought — this ‘annoying’ thing that people need to do to get their paper published. But statistics as a field is actually a lot more than that. It’s a way of thinking about data. Particularly, Bayesian modeling provides a principled inference framework for combining prior knowledge into a hypothesis that you can test with data.” 

      To be sure, no one starts out with such inspiration about scientific scholarship, but MSRP-Bio helps students find that passion for research and the paths that opens up.   More

    • 125 Shares189 Views

      in Data Management & Statistics

      Emery Brown wins a share of 2022 Gruber Neuroscience Prize

      by

      The Gruber Foundation announced on May 17 that Emery N. Brown, the Edward Hood Taplin Professor of Medical Engineering and Computational Neuroscience at MIT, has won the 2022 Gruber Neuroscience Prize along with neurophysicists Laurence Abbott of Columbia University, Terrence Sejnowski of the Salk Institute for Biological Studies, and Haim Sompolinsky of the Hebrew University of Jerusalem.

      The foundation says it honored the four recipients for their influential contributions to the fields of computational and theoretical neuroscience. As datasets have grown ever larger and more complex, these fields have increasingly helped scientists unravel the mysteries of how the brain functions in both health and disease. The prize, which includes a total $500,000 award, will be presented in San Diego, California, on Nov. 13 at the annual meeting of the Society for Neuroscience.

      “These four remarkable scientists have applied their expertise in mathematical and statistical analysis, physics, and machine learning to create theories, mathematical models, and tools that have greatly advanced how we study and understand the brain,” says Joshua Sanes, professor of molecular and cellular biology and founding director of the Center for Brain Science at Harvard University and member of the selection advisory board to the prize. “Their insights and research have not only transformed how experimental neuroscientists do their research, but also are leading to promising new ways of providing clinical care.”

      Brown, who is an investigator in The Picower Institute for Learning and Memory and the Institute for Medical Engineering and Science at MIT, an anesthesiologist at Massachusetts General Hospital, and a professor at Harvard Medical School, says: “It is a pleasant surprise and tremendous honor to be named a co-recipient of the 2022 Gruber Prize in Neuroscience. I am especially honored to share this award with three luminaries in computational and theoretical neuroscience.”

      Brown’s early groundbreaking findings in neuroscience included a novel algorithm that decodes the position of an animal by observing the activity of a small group of place cells in the animal’s brain, a discovery he made while working with fellow Picower Institute investigator Matt Wilson in the 1990s. The resulting state-space algorithm for point processes not only offered much better decoding with fewer neurons than previous approaches, but it also established a new framework for specifying dynamically the relationship between the spike trains (the timing sequence of firing neurons) in the brain and factors from the outside world.

      “One of the basic questions at the time was whether an animal holds a representation of where it is in its mind — in the hippocampus,” Brown says. “We were able to show that it did, and we could show that with only 30 neurons.”

      After introducing this state-space paradigm to neuroscience, Brown went on to refine the original idea and apply it to other dynamic situations — to simultaneously track neural activity and learning, for example, and to define with precision anesthesia-induced loss of consciousness, as well as its subsequent recovery. In the early 2000s, Brown put together a team to specifically study anesthesia’s effects on the brain.

      Through experimental research and mathematical modeling, Brown and his team showed that the altered arousal states produced by the main classes of anesthesia medications can be characterized by analyzing the oscillatory patterns observed in the EEG along with the locations of their molecular targets, and the anatomy and physiology of the neural circuits that connect those locations. He has established, including in recent papers with Picower Professor Earl K. Miller, that a principal way in which anesthetics produce unconsciousness is by producing oscillations that impair how different brain regions communicate with each other.

      The result of Brown’s research has been a new paradigm for brain monitoring during general anesthesia for surgery, one that allows an anesthesiologist to dose the patient based on EEG readouts (neural oscillations) of the patient’s anesthetic state rather than purely on vital sign responses. This pioneering approach promises to revolutionize how anesthesia medications are delivered to patients, and also shed light on other altered states of arousal such as sleep and coma.

      To advance that vision, Brown recently discussed how he is working to develop a new research center at MIT and MGH to further integrate anesthesiology with neuroscience research. The Brain Arousal State Control Innovation Center, he said, would not only advance anesthesiology care but also harness insights gained from anesthesiology research to improve other aspects of clinical neuroscience.

      “By demonstrating that physics and mathematics can make an enormous contribution to neuroscience, doctors Abbott, Brown, Sejnowski, and Sompolinsky have inspired an entire new generation of physicists and other quantitative scientists to follow in their footsteps,” says Frances Jensen, professor and chair of the Department of Neurology and co-director of the Penn Medicine Translational Neuroscience Center within the Perelman School of Medicine at the University of Pennsylvania, and chair of the Selection Advisory Board to the prize. “The ramifications for neuroscience have been broad and profound. It is a great pleasure to be honoring each of them with this prestigious award.”

      This report was adapted from materials provided by the Gruber Foundation. More

    • 163 Shares129 Views

      in Data Management & Statistics

      Emery Brown earns American Institute for Medical and Biological Engineering Pierre Galletti Award

      by

      The American Institute for Medical and Biological Engineering has awarded its highest honor this year to Emery N. Brown, the Edward Hood Taplin Professor of Computational Neuroscience and Health Sciences and Technology in The Picower Institute for Learning and Memory and the Institute for Medical Engineering and Science at MIT.

      Brown, who is also an anesthesiologist at Massachusetts General Hospital and the Warren M. Zapol Professor at Harvard Medical School, received the 2022 Pierre M. Galletti Award during the national organization’s Annual Event held on March 25.

      For decades, Brown’s lab has uniquely unified three fields: neuroscience, statistics, and anesthesiology. He is renowned for the development of statistical methods and signal-processing algorithms to enable and improve analysis of neural activity measurements. The work has had numerous applications including studies of learning and memory, brain-computer interfaces, and systems neuroscience. He has also pioneered investigations of how general anesthetic drugs work in the brain to induce and maintain simultaneous but reversible states of unconsciousness, amnesia, immobility, and analgesia. Building on these improvements in fundamental understanding, his lab engineers systems to improve monitoring of patient state and anesthetic dosing during surgery. Optimizing doses of general anesthetic drugs can improve patient care in many ways, including by minimizing side effects such as post-operative delirium and by improving post-operative pain management.

      AIMBE said Brown earned the award in recognition of his “significant contributions to neuroscience data analysis and for characterizing the neurophysiology of anesthesia-induced unconsciousness and demonstrating how it can be reliably monitored in real time using electroencephalogram recordings.”

      Brown, who is also a faculty member in MIT’s Department of Brain and Cognitive Sciences, is now working to develop a research center at MIT dedicated to taking neuroscience-based approaches to advance anesthesiology.

      “I am extremely honored and grateful to the AIMBE for choosing me to receive the 2022 Galletti Award in recognition of my research deciphering the neuroscience of how anesthetics work,” he says. “I would like to express my gratitude to my collaborators, post-doctoral fellows, students, research assistants, and clinical coordinators who have made this possible.” More

    • 100 Shares99 Views

      in Data Management & Statistics

      Professor Emery Brown has big plans for anesthesiology

      by

      Emery N. Brown — the Edward Hood Taplin Professor of Medical Engineering and of Computational Neuroscience at MIT, an MIT professor of health sciences and technology, an investigator with The Picower Institute for Learning and Memory at MIT, and the Warren M. Zapol Professor of Anaesthesia at Harvard Medical School and Massachusetts General Hospital (MGH) — clearly excels at many roles. Renowned internationally for his anesthesia and neuroscience research, he embodies a unique blend of anesthesiologist, statistician, neuroscientist, educator, and mentor to both students and colleagues. Notably, Brown is one of the most decorated clinician-scientists in the country; he is one of only 25 people — and the first African-American, statistician, and anesthesiologist — to be elected to all three National Academies (Science, Engineering, and Medicine).

      Now, he is handing off one of his many key roles and responsibilities. After almost 10 years, Brown is stepping down as co-director of the Harvard-MIT Program in Health Sciences and Technology (HST). He will turn his energies toward working to develop a new joint center between MIT and MGH that uses the study of anesthesia to design novel approaches to controlling brain states. While a goal of the new center will be to improve anesthesia and intensive care unit management, according to Brown, it will also study related problems such as treating depression, insomnia, and epilepsy, as well as enhancing coma recovery.

      Founded in 1970, HST is one of the oldest interdisciplinary educational programs focused on training the next generation of clinician-scientists and engineers, who learn to translate science, engineering, and medical research into clinical practice, with the aim of improving human health. The MIT Institute for Medical Engineering and Science (IMES), where Brown is associate director, is HST’s home at MIT. Brown was the first HST co-director after the establishment of IMES in 2012; Wolfram Goessling is the Harvard University co-director of HST.

      “Emery has been an exemplary leader for HST during his tenure, and has helped it become a hub for the training of world-class scientists, engineers, and clinicians,” says Anantha Chandrakasan, dean of the MIT School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “I am deeply grateful for his many years of service and wish him well as he moves on to new endeavors.”

      Elazer R. Edelman, director of IMES, calls Brown “a phenom who has been dedicated to our programs for years.”

      “With his thoughtful leadership and understated style, Emery made many contributions to the HST community,” Edelman continues. “On a personal note, this is bittersweet for me, as Emery has been a partner and mentor in my role as IMES director. And while I know that he will always be there for me, as he has been for all of us at IMES and HST, I will miss our late-night calls and midday conferences on matters of import for MIT, IMES, and HST.”

      Brown says “it was an honor and a privilege to co-direct HST with Wolfram.”

      “The students, staff, and faculty are simply amazing,” Brown continues. “Although, now more than 50 years old, HST remains at the vanguard for training PhD and MD students to work at the intersection between engineering, science, and medicine.”

      Goessling also thanks Brown for his leadership: “I truly valued Emery’s partnership and friendship, working together to deepen ties between the MIT and Harvard sides of HST. I am particularly grateful for working with Emery on our combined diversity efforts, leading to the HST Diversity Ambassadors initiative that made HST a better and stronger program.”

      According to Edelman, Brown was instrumental in the transition to new paradigms and relationships with HMS in the context of IMES. In 2014, he led the establishment of clear criteria for HST faculty membership, thereby strengthening the community of faculty experts who train students and provide research opportunities. More recently, he provided guidance through the turmoil of the ongoing Covid-19 pandemic, including the transition to online instruction and the return to the classroom. And Brown has always been a strong supporter of student diversity efforts, serving as an advocate and advisor to HST students.

      Brown holds BA, MA, and PhD degrees from Harvard University, and an MD from Harvard Medical School. He has been recognized with many awards, including the 2020 Swartz Prize in Theoretical and Computational Neuroscience, the 2018 Dickson Prize in Science, and an NIH Director’s Pioneer Award. Brown also served on President Barack Obama’s BRAIN Initiative Working Group. Among his many accomplishments, he has been cited for developing neural signal processing algorithms to characterize how neural systems represent and transmit information, and for unlocking the neurophysiology of how anesthetics produce the states of general anesthesia.

      Edelman says the process is underway to name a successor to Brown as co-director of HST at MIT. More