Author: MIT News

Polina Anikeeva and Feng Zhang awarded 2018 Vilcek Prize

Anne Trafton |

Polina Anikeeva, the Class of 1942 Associate Professor in the Department of Materials Science and Engineering and associate director of the Research Laboratory of Electronics, and Feng Zhang, the James and Patricia Poitras ’63 Professor in Neuroscience at the McGovern Institute, have each been awarded a 2018 Vilcek Prize for Creative Promise in Biomedical Science. Awarded annually by the Vilcek Foundation, the $50,000 prizes recognize younger immigrants who have demonstrated exceptional promise early in their careers.

“The Vilcek Prizes were established in appreciation of the immigrants who chose to dedicate their vision and talent to bettering American society,” says Rick Kinsel, president of the Vilcek Foundation. “This year’s prizewinners honor and continue that legacy with works of astounding, revolutionary importance.”

Polina Anikeeva, who was born in the former Soviet Union, earned her PhD in materials science and engineering at MIT in 2009 and now runs her own bioelectronics lab in the same department focused on the development of materials and devices that enable recording and manipulation of signaling processes within the nervous system. The Vilcek Foundation recognizes Anikeeva for “fashioning ingenious solutions to long-standing challenges in biomedical engineering” including the design of therapeutic devices for conditions such as Parkinson’s disease and spinal cord injury.

Feng Zhang, who is also a core member of the Broad Institute and an associate professor in the departments of Brain and Cognitive Sciences and Biological Engineering, is being recognized for his role in advancing optogenetics (a method for controlling brain activity with light) and developing molecular tools to edit the genome. Thanks to his leadership in inventing precise and efficient gene-editing technologies using CRISPR, Zhang’s work has resulted in a “growing array of applications, such as uncovering the genetic underpinnings of diseases, ushering in gene therapies to cure heritable diseases, and improving agriculture.” Zhang’s family immigrated to the United States from China when he was 11 years of age.

Anikeeva and Zhang will be among eight Vilcek prizewinners honored at an awards gala in New York City in April 2018.

The Vilcek Foundation was established in 2000 by Jan and Marica Vilcek, immigrants from the former Czechoslovakia. The mission of the foundation, to honor the contributions of immigrants to the United States and to foster appreciation of the arts and sciences, was inspired by the couple’s respective careers in biomedical science and art history, as well as their personal experiences and appreciation of the opportunities they received as newcomers to this country.

Institute launches the MIT Intelligence Quest

Anne Trafton |

MIT today announced the launch of the MIT Intelligence Quest, an initiative to discover the foundations of human intelligence and drive the development of technological tools that can positively influence virtually every aspect of society.

The announcement was first made in a letter MIT President L. Rafael Reif sent to the Institute community.

At a time of rapid advances in intelligence research across many disciplines, the Intelligence Quest will encourage researchers to investigate the societal implications of their work as they pursue hard problems lying beyond the current horizon of what is known.

Some of these advances may be foundational in nature, involving new insight into human intelligence, and new methods to allow machines to learn effectively. Others may be practical tools for use in a wide array of research endeavors, such as disease diagnosis, drug discovery, materials and manufacturing design, automated systems, synthetic biology, and finance.

“Today we set out to answer two big questions, says President Reif. “How does human intelligence work, in engineering terms? And how can we use that deep grasp of human intelligence to build wiser and more useful machines, to the benefit of society?”

MIT Intelligence Quest: The Core and The Bridge

MIT is poised to lead this work through two linked entities within MIT Intelligence Quest. One of them, “The Core,” will advance the science and engineering of both human and machine intelligence. A key output of this work will be machine-learning algorithms. At the same time, MIT Intelligence Quest seeks to advance our understanding of human intelligence by using insights from computer science.

The second entity, “The Bridge” will be dedicated to the application of MIT discoveries in natural and artificial intelligence to all disciplines, and it will host state-of-the-art tools from industry and research labs worldwide.

The Bridge will provide a variety of assets to the MIT community, including intelligence technologies, platforms, and infrastructure; education for students, faculty, and staff about AI tools; rich and unique data sets; technical support; and specialized hardware.

Along with developing and advancing the technologies of intelligence, MIT Intelligence Quest researchers will also investigate the societal and ethical implications of advanced analytical and predictive tools. There are already active projects and groups at the Institute investigating autonomous systems, media and information quality, labor markets and the work of the future, innovation and the digital economy, and the role of AI in the legal system.

In all its activities, MIT Intelligence Quest is intended to take advantage of — and strengthen — the Institute’s culture of collaboration. MIT Intelligence Quest will connect and amplify existing excellence across labs and centers already engaged in intelligence research. It will also establish shared, central spaces conducive to group work, and its resources will directly support research.

“Our quest is meant to power world-changing possibilities,” says Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. Chandrakasan, in collaboration with Provost Martin Schmidt and all four of MIT’s other school deans, has led the development and establishment of MIT Intelligence Quest.

“We imagine preventing deaths from cancer by using deep learning for early detection and personalized treatment,” Chandrakasan continues. “We imagine artificial intelligence in sync with, complementing, and assisting our own intelligence. And we imagine every scientist and engineer having access to human-intelligence-inspired algorithms that open new avenues of discovery in their fields. Researchers across our campus want to push the boundaries of what’s possible.”

Engaging energetically with partners

In order to power MIT Intelligence Quest and achieve results that are consistent with its ambitions, the Institute will raise financial support through corporate sponsorship and philanthropic giving.

MIT Intelligence Quest will build on the model that was established with the MIT–IBM Watson AI Lab, which was announced in September 2017. MIT researchers will collaborate with each other and with industry on challenges that range in scale from the very broad to the very specific.

“In the short time since we began our collaboration with IBM, the lab has garnered tremendous interest inside and outside MIT, and it will be a vital part of MIT Intelligence Quest,” says President Reif.

John E. Kelly III, IBM senior vice president for cognitive solutions and research, says, “To take on the world’s greatest challenges and seize its biggest opportunities, we need to rapidly advance both AI technology and our understanding of human intelligence. Building on decades of collaboration — including our extensive joint MIT–IBM Watson AI Lab — IBM and MIT will together shape a new agenda for intelligence research and its applications. We are proud to be a cornerstone of this expanded initiative.”

MIT will seek to establish additional entities within MIT Intelligence Quest, in partnership with corporate and philanthropic organizations.

Why MIT

MIT has been on the frontier of intelligence research since the 1950s, when pioneers Marvin Minsky and John McCarthy helped establish the field of artificial intelligence.

MIT now has over 200 principal investigators whose research bears directly on intelligence. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the MIT Department of Brain and Cognitive Sciences (BCS) — along with the McGovern Institute for Brain Research and the Picower Institute for Learning and Memory — collaborate on a range of projects. MIT is also home to the National Science Foundation–funded center for Brains, Minds and Machines (CBMM) — the only national center of its kind.

Four years ago, MIT launched the Institute for Data, Systems, and Society (IDSS) with a mission promoting data science, particularly in the context of social systems. It is  anticipated that faculty and students from IDSS will play a critical role in this initiative.

Faculty from across the Institute will participate in the initiative, including researchers in the Media Lab, the Operations Research Center, the Sloan School of Management, the School of Architecture and Planning, and the School of Humanities, Arts, and Social Sciences.

“Our quest will amount to a journey taken together by all five schools at MIT,” says Provost Schmidt. “Success will rest on a shared sense of purpose and a mix of contributions from a wide variety of disciplines. I’m excited by the new thinking we can help unlock.”

At the heart of MIT Intelligence Quest will be collaboration among researchers in human and artificial intelligence.

“To revolutionize the field of artificial intelligence, we should continue to look to the roots of intelligence: the brain,” says James DiCarlo, department head and Peter de Florez Professor of Neuroscience in the Department of Brain and Cognitive Sciences. “By working with engineers and artificial intelligence researchers, human intelligence researchers can build models of the brain systems that produce intelligent behavior. The time is now, as model building at the scale of those brain systems is now possible. Discovering how the brain works in the language of engineers will not only lead to transformative AI — it will also illuminate entirely new ways to repair, educate, and augment our own minds.”

Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT, and director of CSAIL, agrees. MIT researchers, she says, “have contributed pioneering and visionary solutions for intelligence since the beginning of the field, and are excited to make big leaps to understand human intelligence and to engineer significantly more capable intelligent machines. Understanding intelligence will give us the knowledge to understand ourselves and to create machines that will support us with cognitive and physical work.”

David Siegel, who earned a PhD in computer science at MIT in 1991 pursuing research at MIT’s Artificial Intelligence Laboratory, and who is a member of the MIT Corporation and an advisor to the MIT Center for Brains, Minds, and Machines, has been integral to the vision and formation of MIT Intelligence Quest and will continue to help shape the effort. “Understanding human intelligence is one of the greatest scientific challenges,” he says, “one that helps us understand who we are while meaningfully advancing the field of artificial intelligence.” Siegel is co-chairman and a founder of Two Sigma Investments, LP.

The fruits of research

MIT Intelligence Quest will thus provide a platform for long-term research, encouraging the foundational advances of the future. At the same time, MIT professors and researchers may develop technologies with near-term value, leading to new kinds of collaborations with existing companies — and to new companies.

Some such entrepreneurial efforts could be supported by The Engine, an Institute initiative launched in October 2016 to support startup companies pursuing particularly ambitious goals.

Other innovations stemming from MIT Intelligence Quest could be absorbed into the innovation ecosystem surrounding the Institute — in Kendall Square, Cambridge, and the Boston metropolitan area. MIT is located in close proximity to a world-leading nexus of biotechnology and medical-device research and development, as well as a cluster of leading-edge technology firms that study and deploy machine intelligence.

MIT also has roots in centers of innovation elsewhere in the United States and around the world, through faculty research projects, institutional and industry collaborations, and the activities and leadership of its alumni. MIT Intelligence Quest will seek to connect to innovative companies and individuals who share MIT’s passion for work in intelligence.

Eric Schmidt, former executive chairman of Alphabet, has helped MIT form the vision for MIT Intelligence Quest. “Imagine the good that can be done by putting novel machine-learning tools in the hands of those who can make great use of them,” he says. “MIT Intelligence Quest can become a fount of exciting new capabilities.”

“I am thrilled by today’s news,” says President Reif. “Drawing on MIT’s deep strengths and signature values, culture, and history, MIT Intelligence Quest promises to make important contributions to understanding the nature of intelligence, and to harnessing it to make a better world.”

“MIT is placing a bet,” he says, “on the central importance of intelligence research to meeting the needs of humanity.”

Ultrathin needle can deliver drugs directly to the brain

Anne Trafton |

MIT researchers have devised a miniaturized system that can deliver tiny quantities of medicine to brain regions as small as 1 cubic millimeter. This type of targeted dosing could make it possible to treat diseases that affect very specific brain circuits, without interfering with the normal function of the rest of the brain, the researchers say.

Using this device, which consists of several tubes contained within a needle about as thin as a human hair, the researchers can deliver one or more drugs deep within the brain, with very precise control over how much drug is given and where it goes. In a study of rats, they found that they could deliver targeted doses of a drug that affects the animals’ motor function.

“We can infuse very small amounts of multiple drugs compared to what we can do intravenously or orally, and also manipulate behavioral changes through drug infusion,” says Canan Dagdeviren, the LG Electronics Career Development Assistant Professor of Media Arts and Sciences and the lead author of the paper, which appears in the Jan. 24 issue of Science Translational Medicine.

“We believe this tiny microfabricated device could have tremendous impact in understanding brain diseases, as well as providing new ways of delivering biopharmaceuticals and performing biosensing in the brain,” says Robert Langer, the David H. Koch Institute Professor at MIT and one of the paper’s senior authors.

Michael Cima, the David H. Koch Professor of Engineering in the Department of Materials Science and Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research, is also a senior author of the paper.

Targeted action

Drugs used to treat brain disorders often interact with brain chemicals called neurotransmitters or the cell receptors that interact with neurotransmitters. Examples include l-dopa, a dopamine precursor used to treat Parkinson’s disease, and Prozac, used to boost serotonin levels in patients with depression. However, these drugs can have side effects because they act throughout the brain.

“One of the problems with central nervous system drugs is that they’re not specific, and if you’re taking them orally they go everywhere. The only way we can limit the exposure is to just deliver to a cubic millimeter of the brain, and in order to do that, you have to have extremely small cannulas,” Cima says.

The MIT team set out to develop a miniaturized cannula (a thin tube used to deliver medicine) that could target very small areas. Using microfabrication techniques, the researchers constructed tubes with diameters of about 30 micrometers and lengths up to 10 centimeters. These tubes are contained within a stainless steel needle with a diameter of about 150 microns. “The device is very stable and robust, and you can place it anywhere that you are interested,” Dagdeviren says.

The researchers connected the cannulas to small pumps that can be implanted under the skin. Using these pumps, the researchers showed that they could deliver tiny doses (hundreds of nanoliters) into the brains of rats. In one experiment, they delivered a drug called muscimol to a brain region called the substantia nigra, which is located deep within the brain and helps to control movement.

Previous studies have shown that muscimol induces symptoms similar to those seen in Parkinson’s disease. The researchers were able to generate those effects, which include stimulating the rats to continually turn in a clockwise direction, using their miniaturized delivery needle. They also showed that they could halt the Parkinsonian behavior by delivering a dose of saline through a different channel, to wash the drug away.

“Since the device can be customizable, in the future we can have different channels for different chemicals, or for light, to target tumors or neurological disorders such as Parkinson’s disease or Alzheimer’s,” Dagdeviren says.

This device could also make it easier to deliver potential new treatments for behavioral neurological disorders such as addiction or obsessive compulsive disorder, which may be caused by specific disruptions in how different parts of the brain communicate with each other.

“Even if scientists and clinicians can identify a therapeutic molecule to treat neural disorders, there remains the formidable problem of how to delivery the therapy to the right cells — those most affected in the disorder. Because the brain is so structurally complex, new accurate ways to deliver drugs or related therapeutic agents locally are urgently needed,” says Ann Graybiel, an MIT Institute Professor and a member of MIT’s McGovern Institute for Brain Research, who is also an author of the paper.

Measuring drug response

The researchers also showed that they could incorporate an electrode into the tip of the cannula, which can be used to monitor how neurons’ electrical activity changes after drug treatment. They are now working on adapting the device so it can also be used to measure chemical or mechanical changes that occur in the brain following drug treatment.

The cannulas can be fabricated in nearly any length or thickness, making it possible to adapt them for use in brains of different sizes, including the human brain, the researchers say.

“This study provides proof-of-concept experiments, in large animal models, that a small, miniaturized device can be safely implanted in the brain and provide miniaturized control of the electrical activity and function of single neurons or small groups of neurons. The impact of this could be significant in focal diseases of the brain, such as Parkinson’s disease,” says Antonio Chiocca, neurosurgeon-in-chief and chairman of the Department of Neurosurgery at Brigham and Women’s Hospital, who was not involved in the research.

The research was funded by the National Institutes of Health and the National Institute of Biomedical Imaging and Bioengineering.

School of Science Infinite Kilometer Awards for 2017

Anne Trafton |

The MIT School of Science has announced the 2017 winners of the Infinite Kilometer Award. The Infinite Kilometer Award was established in 2012 to highlight and reward the extraordinary — but often underrecognized — work of the school’s research staff and postdocs.

Recipients of the award are exceptional contributors to their research programs. In many cases, they are also deeply committed to their local or global MIT community, and are frequently involved in mentoring and advising their junior colleagues, participating in the school’s educational programs, making contributions to the MIT Postdoctoral Association, or contributing to some other facet of the MIT community.

In addition to a monetary award, honorees and their colleagues, friends, and family are invited to a celebratory lunch in May.

The 2017 Infinite Kilometer winners are:

Rodrigo Garcia, McGovern Institute for Brain Research;

Lydia Herzel, Department of Biology;

Yutaro Iiyama, Laboratory for Nuclear Science;

Kendrick Jones, Picower Institute for Learning and Memory;

Matthew Musgrave, Laboratory for Nuclear Science;

Cody Siciliano, Picower Institute for Learning and Memory;

Peter Sudmant, Department of Biology;

Ashley Watson, Picower Institute for Learning and Memory;

The School of Science is also currently accepting nominations for its Infinite Mile Awards. Nominations are due by Feb. 16 and all School of Science employees are eligible. Infinite Mile Awards will be presented with the Infinite Kilometer Awards this spring.

How the brain keeps time

Anne Trafton |

Timing is critical for playing a musical instrument, swinging a baseball bat, and many other activities. Neuroscientists have come up with several models of how the brain achieves its exquisite control over timing, the most prominent being that there is a centralized clock, or pacemaker, somewhere in the brain that keeps time for the entire brain.

However, a new study from MIT researchers provides evidence for an alternative timekeeping system that relies on the neurons responsible for producing a specific action. Depending on the time interval required, these neurons compress or stretch out the steps they take to generate the behavior at a specific time.

“What we found is that it’s a very active process. The brain is not passively waiting for a clock to reach a particular point,” says Mehrdad Jazayeri, the Robert A. Swanson Career Development Professor of Life Sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

MIT postdoc Jing Wang and former postdoc Devika Narain are the lead authors of the paper, which appears in the Dec. 4 issue of Nature Neuroscience. Graduate student Eghbal Hosseini is also an author of the paper.

Flexible control

One of the earliest models of timing control, known as the clock accumulator model, suggested that the brain has an internal clock or pacemaker that keeps time for the rest of the brain. A later variation of this model suggested that instead of using a central pacemaker, the brain measures time by tracking the synchronization between different brain wave frequencies.

Although these clock models are intuitively appealing, Jazayeri says, “they don’t match well with what the brain does.”

No one has found evidence for a centralized clock, and Jazayeri and others wondered if parts of the brain that control behaviors that require precise timing might perform the timing function themselves. “People now question why would the brain want to spend the time and energy to generate a clock when it’s not always needed. For certain behaviors you need to do timing, so perhaps the parts of the brain that subserve these functions can also do timing,” he says.

To explore this possibility, the researchers recorded neuron activity from three brain regions in animals as they performed a task at two different time intervals — 850 milliseconds or 1,500 milliseconds.

The researchers found a complicated pattern of neural activity during these intervals. Some neurons fired faster, some fired slower, and some that had been oscillating began to oscillate faster or slower. However, the researchers’ key discovery was that no matter the neurons’ response, the rate at which they adjusted their activity depended on the time interval required.

At any point in time, a collection of neurons is in a particular “neural state,” which changes over time as each individual neuron alters its activity in a different way. To execute a particular behavior, the entire system must reach a defined end state. The researchers found that the neurons always traveled the same trajectory from their initial state to this end state, no matter the interval. The only thing that changed was the rate at which the neurons traveled this trajectory.

When the interval required was longer, this trajectory was “stretched,” meaning the neurons took more time to evolve to the final state. When the interval was shorter, the trajectory was compressed.

“What we found is that the brain doesn’t change the trajectory when the interval changes, it just changes the speed with which it goes from the initial internal state to the final state,” Jazayeri says.

Dean Buonomano, a professor of behavioral neuroscience at the University of California at Los Angeles, says that the study “provides beautiful evidence that timing is a distributed process in the brain — that is, there is no single master clock.”

“This work also supports the notion that the brain does not tell time using a clock-like mechanism, but rather relies on the dynamics inherent to neural circuits, and that as these dynamics increase and decrease in speed, animals move more quickly or slowly,” adds Buonomano, who was not involved in the research.

Neural networks

The researchers focused their study on a brain loop that connects three regions: the dorsomedial frontal cortex, the caudate, and the thalamus. They found this distinctive neural pattern in the dorsomedial frontal cortex, which is involved in many cognitive processes, and the caudate, which is involved in motor control, inhibition, and some types of learning. However, in the thalamus, which relays motor and sensory signals, they found a different pattern: Instead of altering the speed of their trajectory, many of the neurons simply increased or decreased their firing rate, depending on the interval required.

Jazayeri says this finding is consistent with the possibility that the thalamus is instructing the cortex on how to adjust its activity to generate a certain interval.

The researchers also created a computer model to help them further understand this phenomenon. They began with a model of hundreds of neurons connected together in random ways, and then trained it to perform the same interval-producing task they had used to train animals, offering no guidance on how the model should perform the task.

They found that these neural networks ended up using the same strategy that they observed in the animal brain data. A key discovery was that this strategy only works if some of the neurons have nonlinear activity — that is, the strength of their output doesn’t constantly increase as their input increases. Instead, as they receive more input, their output increases at a slower rate.

Jazayeri now hopes to explore further how the brain generates the neural patterns seen during varying time intervals, and also how our expectations influence our ability to produce different intervals.

The research was funded by the Rubicon Grant from the Netherlands Scientific Organization, the National Institutes of Health, the Sloan Foundation, the Klingenstein Foundation, the Simons Foundation, the Center for Sensorimotor Neural Engineering, and the McGovern Institute.

How badly do you want something? Babies can tell

Anne Trafton |

Babies as young as 10 months can assess how much someone values a particular goal by observing how hard they are willing to work to achieve it, according to a new study from MIT and Harvard University.

This ability requires integrating information about both the costs of obtaining a goal and the benefit gained by the person seeking it, suggesting that babies acquire very early an intuition about how people make decisions.

“Infants are far from experiencing the world as a ‘blooming, buzzing confusion,’” says lead author Shari Liu, referring to a description by philosopher and psychologist William James about a baby’s first experience of the world. “They interpret people’s actions in terms of hidden variables, including the effort [people] expend in producing those actions, and also the value of the goals those actions achieve.”

“This study is an important step in trying to understand the roots of common-sense understanding of other people’s actions. It shows quite strikingly that in some sense, the basic math that is at the heart of how economists think about rational choice is very intuitive to babies who don’t know math, don’t speak, and can barely understand a few words,” says Josh Tenenbaum, a professor in MIT’s Department of Brain and Cognitive Sciences, a core member of the joint MIT-Harvard Center for Brains, Minds and Machines (CBMM), and one of the paper’s authors.

Tenenbaum helped to direct the research team along with Elizabeth Spelke, a professor of psychology at Harvard University and CBMM core member, in whose lab the research was conducted. Liu, the paper’s lead author, is a graduate student at Harvard. CBMM postdoc Tomer Ullman is also an author of the paper, which appears in the Nov. 23 online edition of Science.

Calculating value

Previous research has shown that adults and older children can infer someone’s motivations by observing how much effort that person exerts toward obtaining a goal.

The Harvard/MIT team wanted to learn more about how and when this ability develops. Babies expect people to be consistent in their preferences and to be efficient in how they achieve their goals, previous studies have found. The question posed in this study was whether babies can combine what they know about a person’s goal and the effort required to obtain it, to calculate the value of that goal.

To answer that question, the researchers showed 10-month-old infants animated videos in which an “agent,” a cartoon character shaped like a bouncing ball, tries to reach a certain goal (another cartoon character). In one of the videos, the agent has to leap over walls of varying height to reach the goal. First, the babies saw the agent jump over a low wall and then refuse to jump over a medium-height wall. Next, the agent jumped over the medium-height wall to reach a different goal, but refused to jump over a high wall to reach that goal.

The babies were then shown a scene in which the agent could choose between the two goals, with no obstacles in the way. An adult or older child would assume the agent would choose the second goal, because the agent had worked harder to reach that goal in the video seen earlier. The researchers found that 10-month-olds also reached this conclusion: When the agent was shown choosing the first goal, infants looked at the scene longer, indicating that they were surprised by that outcome. (Length of looking time is commonly used to measure surprise in studies of infants.)

The researchers found the same results when babies watched the agents perform the same set of actions with two different types of effort: climbing ramps of varying incline and jumping across gaps of varying width.

“Across our experiments, we found that babies looked longer when the agent chose the thing it had exerted less effort for, showing that they infer the amount of value that agents place on goals from the amount of effort that they take toward these goals,” Liu says.

The findings suggest that infants are able to calculate how much another person values something based on how much effort they put into getting it.

“This paper is not the first to suggest that idea, but its novelty is that it shows this is true in much younger babies than anyone has seen. These are preverbal babies, who themselves are not actively doing very much, yet they appear to understand other people’s actions in this sophisticated, quantitative way,” says Tenenbaum, who is also affiliated with MIT’s Computer Science and Artificial Intelligence Laboratory.

Studies of infants can reveal deep commonalities in the ways that we think throughout our lives, suggests Spelke. “Abstract, interrelated concepts like cost and value — concepts at the center both of our intuitive psychology and of utility theory in philosophy and economics — may originate in an early-emerging system by which infants understand other people’s actions,” she says.

The study shows, for the first time, that “preverbal infants can look at the world like economists,” says Gergely Csibra, a professor of cognitive science at Central European University in Hungary. “They do not simply calculate the costs and benefits of others’ actions (this had been demonstrated before), but relate these terms onto each other. In other words, they apply the well-known logic that all of us rely on when we try to assess someone’s preferences: The harder she tries to achieve something, the more valuable is the expected reward to her when she succeeds.”

Modeling intelligence

Over the past 10 years, scientists have developed computer models that come close to replicating how adults and older children incorporate different types of input to infer other people’s goals, intentions, and beliefs. For this study, the researchers built on that work, especially work by Julian Jara-Ettinger PhD ’16, who studied similar questions in preschool-age children. The researchers developed a computer model that can predict what 10-month-old babies would infer about an agent’s goals after observing the agent’s actions. This new model also posits an ability to calculate “work” (or total force applied over a distance) as a measure of the cost of actions, which the researchers believe babies are able to do on some intuitive level.

“Babies of this age seem to understand basic ideas of Newtonian mechanics, before they can talk and before they can count,” Tenenbaum says. “They’re putting together an understanding of forces, including things like gravity, and they also have some understanding of the usefulness of a goal to another person.”

Building this type of model is an important step toward developing artificial intelligence that replicates human behavior more accurately, the researchers say.

“We have to recognize that we’re very far from building AI systems that have anything like the common sense even of a 10-month-old,” Tenenbaum says. “But if we can understand in engineering terms the intuitive theories that even these young infants seem to have, that hopefully would be the basis for building machines that have more human-like intelligence.”

Still unanswered are the questions of exactly how and when these intuitive abilities arise in babies.

“Do infants start with a completely blank slate, and somehow they’re able to build up this sophisticated machinery? Or do they start with some rudimentary understanding of goals and beliefs, and then build up the sophisticated machinery? Or is it all just built in?” Ullman says.

The researchers hope that studies of even younger babies, perhaps as young as 3 months old, and computational models of learning intuitive theories that the team is also developing, may help to shed light on these questions.

This project was funded by the National Science Foundation through the Center for Brains, Minds, and Machines, which is based at MIT’s McGovern Institute for Brain Research and led by MIT and Harvard.

Stress can lead to risky decisions

Anne Trafton |

Making decisions is not always easy, especially when choosing between two options that have both positive and negative elements, such as deciding between a job with a high salary but long hours, and a lower-paying job that allows for more leisure time.

MIT neuroscientists have now discovered that making decisions in this type of situation, known as a cost-benefit conflict, is dramatically affected by chronic stress. In a study of mice, they found that stressed animals were far likelier to choose high-risk, high-payoff options.

The researchers also found that impairments of a specific brain circuit underlie this abnormal decision making, and they showed that they could restore normal behavior by manipulating this circuit. If a method for tuning this circuit in humans were developed, it could help patients with disorders such as depression, addiction, and anxiety, which often feature poor decision-making.

“One exciting thing is that by doing this very basic science, we found a microcircuit of neurons in the striatum that we could manipulate to reverse the effects of stress on this type of decision making. This to us is extremely promising, but we are aware that so far these experiments are in rats and mice,” says Ann Graybiel, an Institute Professor at MIT and member of the McGovern Institute for Brain Research.

Graybiel is the senior author of the paper, which appears in Cell on Nov. 16. The paper’s lead author is Alexander Friedman, a McGovern Institute research scientist.

Hard decisions

In 2015, Graybiel, Friedman, and their colleagues first identified the brain circuit involved in decision making that involves cost-benefit conflict. The circuit begins in the medial prefrontal cortex, which is responsible for mood control, and extends into clusters of neurons called striosomes, which are located in the striatum, a region associated with habit formation, motivation, and reward reinforcement.

In that study, the researchers trained rodents to run a maze in which they had to choose between one option that included highly concentrated chocolate milk, which they like, along with bright light, which they don’t like, and an option with dimmer light but weaker chocolate milk. By inhibiting the connection between cortical neurons and striosomes, using a technique known as optogenetics, they found that they could transform the rodents’ preference for lower-risk, lower-payoff choices to a preference for bigger payoffs despite their bigger costs.

In the new study, the researchers performed a similar experiment without optogenetic manipulations. Instead, they exposed the rodents to a short period of stress every day for two weeks.

Before experiencing stress, normal rats and mice would choose to run toward the maze arm with dimmer light and weaker chocolate milk about half the time. The researchers gradually increased the concentration of chocolate milk found in the dimmer side, and as they did so, the animals began choosing that side more frequently.

However, when chronically stressed rats and mice were put in the same situation, they continued to choose the bright light/better chocolate milk side even as the chocolate milk concentration greatly increased on the dimmer side. This was the same behavior the researchers saw in rodents that had the prefrontal cortex-striosome circuit disrupted optogenetically.

“The result is that the animal ignores the high cost and chooses the high reward,” Friedman says.

The findings help to explain how stress contributes to substance abuse and may worsen mental disorders, says Amy Arnsten, a professor of neuroscience and psychology at the Yale University School of Medicine, who was not involved in the research.

“Stress is ubiquitous, for both humans and animals, and its effects on brain and behavior are of central importance to the understanding of both normal function and neuropsychiatric disease. It is both pernicious and ironic that chronic stress can lead to impulsive action; in many clinical cases, such as drug addiction, impulsivity is likely to worsen patterns of behavior that produce the stress in the first place, inducing a vicious cycle,” Arnsten wrote in a commentary accompanying the Cell paper, co-authored by Daeyeol Lee and Christopher Pittenger of the Yale University School of Medicine.

Circuit dynamics

The researchers believe that this circuit integrates information about the good and bad aspects of possible choices, helping the brain to produce a decision. Normally, when the circuit is turned on, neurons of the prefrontal cortex activate certain neurons called high-firing interneurons, which then suppress striosome activity.

When the animals are stressed, these circuit dynamics shift and the cortical neurons fire too late to inhibit the striosomes, which then become overexcited. This results in abnormal decision making.

“Somehow this prior exposure to chronic stress controls the integration of good and bad,” Graybiel says. “It’s as though the animals had lost their ability to balance excitation and inhibition in order to settle on reasonable behavior.”

Once this shift occurs, it remains in effect for months, the researchers found. However, they were able to restore normal decision making in the stressed mice by using optogenetics to stimulate the high-firing interneurons, thereby suppressing the striosomes. This suggests that the prefronto-striosome circuit remains intact following chronic stress and could potentially be susceptible to manipulations that would restore normal behavior in human patients whose disorders lead to abnormal decision making.

“This state change could be reversible, and it’s possible in the future that you could target these interneurons and restore the excitation-inhibition balance,” Friedman says.

The research was funded by the National Institutes of Health/National Institute for Mental Health, the CHDI Foundation, the Defense Advanced Research Projects Agency and the U.S. Army Research Office, the Bachmann-Strauss Dystonia and Parkinson Foundation, the William N. and Bernice E. Bumpus Foundation, Michael Stiefel, the Saks Kavanaugh Foundation, and John Wasserlein and Lucille Braun.

Next-generation optogenetic molecules control single neurons

Anne Trafton |

Researchers at MIT and Paris Descartes University have developed a new optogenetic technique that sculpts light to target individual cells bearing engineered light-sensitive molecules, so that individual neurons can be precisely stimulated.

Until now, it has been challenging to use optogenetics to target single cells with such precise control over both the timing and location of the activation. This new advance paves the way for studies of how individual cells, and connections among those cells, generate specific behaviors such as initiating a movement or learning a new skill.

“Ideally what you would like to do is play the brain like a piano. You would want to control neurons independently, rather than having them all march in lockstep the way traditional optogenetics works, but which normally the brain doesn’t do,” says Ed Boyden, an associate professor of brain and cognitive sciences and biological engineering at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research.

The new technique relies on a new type of light-sensitive protein that can be embedded in neuron cell bodies, combined with holographic light-shaping that can focus light on a single cell.

Boyden and Valentina Emiliani, a research director at France’s National Center for Scientific Research (CNRS) and director of the Neurophotonics Laboratory at Paris Descartes University, are the senior authors of the study, which appears in the Nov. 13 issue of Nature Neuroscience. The lead authors are MIT postdoc Or Shemesh and CNRS postdocs Dimitrii Tanese and Valeria Zampini.

Precise control

More than 10 years ago, Boyden and his collaborators first pioneered the use of light-sensitive proteins known as microbial opsins to manipulate neuron electrical activity. These opsins can be embedded into the membranes of neurons, and when they are exposed to certain wavelengths of light, they silence or stimulate the cells.

Over the past decade, scientists have used this technique to study how populations of neurons behave during brain tasks such as memory recall or habit formation. Traditionally, many cells are targeted simultaneously because the light shining into the brain strikes a relatively large area. However, as Boyden points out, neurons may have different functions even when they are near each other.

“Two adjacent cells can have completely different neural codes. They can do completely different things, respond to different stimuli, and play different activity patterns during different tasks,” he says.

To achieve independent control of single cells, the researchers combined two new advances: a localized, more powerful opsin and an optimized holographic light-shaping microscope.

For the opsin, the researchers used a protein called CoChR, which the Boyden lab discovered in 2014. They chose this molecule because it generates a very strong electric current in response to light (about 10 times stronger than that produced by channelrhodopsin-2, the first protein used for optogenetics).

They fused CoChR to a small protein that directs the opsin into the cell bodies of neurons and away from axons and dendrites, which extend from the neuron body. This helps to prevent crosstalk between neurons, since light that activates one neuron can also strike axons and dendrites of other neurons that intertwine with the target neuron.

Boyden then worked with Emiliani to combine this approach with a light-stimulation technique that she had previously developed, known as two-photon computer-generated holography (CGH). This can be used to create three-dimensional sculptures of light that envelop a target cell.

Traditional holography is based on reproducing, with light, the shape of a specific object, in the absence of that original object. This is achieved by creating an “interferogram” that contains the information needed to reconstruct an object that was previously illuminated by a reference beam. In computer generated holography, the interferogram is calculated by a computer without the need of any original object. Years ago, Emiliani’s research group demonstrated that combined with two-photon excitation, CGH can be used to refocus laser light to precisely illuminate a cell or a defined group of cells in the brain.

In the new study, by combining this approach with new opsins that cluster in the cell body, the researchers showed they could stimulate individual neurons with not only precise spatial control but also great control over the timing of the stimulation. When they target a specific neuron, it responds consistently every time, with variability that is less than one millisecond, even when the cell is stimulated many times in a row.

“For the first time ever, we can bring the precision of single-cell control toward the natural timescales of neural computation,” Boyden says.

Mapping connections

Using this technique, the researchers were able to stimulate single neurons in brain slices and then measure the responses from cells that are connected to that cell. This paves the way for possible diagramming of the connections of the brain, and analyzing how those connections change in real time as the brain performs a task or learns a new skill.

One possible experiment, Boyden says, would be to stimulate neurons connected to each other to try to figure out if one is controlling the others or if they are all receiving input from a far-off controller.

“It’s an open question,” he says. “Is a given function being driven from afar, or is there a local circuit that governs the dynamics and spells out the exact chain of command within a circuit? If you can catch that chain of command in action and then use this technology to prove that that’s actually a causal link of events, that could help you explain how a sensation, or movement, or decision occurs.”

As a step toward that type of study, the researchers now plan to extend this approach into living animals. They are also working on improving their targeting molecules and developing high-current opsins that can silence neuron activity.

Kirill Volynski, a professor at the Institute of Neurology at University College London, who was not involved in the research, plans to use the new technology in his studies of diseases caused by mutations of proteins involved in synaptic communication between neurons.

“This gives us a very nice tool to study those mutations and those disorders,” Volynski says. “We expect this to enable a major improvement in the specificity of stimulating neurons that have mutated synaptic proteins.”

The research was funded by the National Institutes of Health, France’s National Research Agency, the Simons Foundation for the Social Brain, the Human Frontiers Science Program, John Doerr, the Open Philanthropy Project, the Howard Hughes Medical Institute, and the Defense Advanced Research Projects Agency.

Researchers engineer CRISPR to edit single RNA letters in human cells

Anne Trafton |

The Broad Institute and MIT scientists who first harnessed CRISPR for mammalian genome editing have engineered a new molecular system for efficiently editing RNA in human cells. RNA editing, which can alter gene products without making changes to the genome, has profound potential as a tool for both research and disease treatment.

In a paper published today in Science, senior author Feng Zhang and his team describe the new CRISPR-based system, called RNA Editing for Programmable A to I Replacement, or “REPAIR.” The system can change single RNA nucleotides in mammalian cells in a programmable and precise fashion. REPAIR has the ability to reverse disease-causing mutations at the RNA level, as well as other potential therapeutic and basic science applications.

“The ability to correct disease-causing mutations is one of the primary goals of genome editing,” says Zhang, a core institute member of the Broad Institute, an investigator at the McGovern Institute, and the James and Patricia Poitras ’63 Professor in Neuroscience and associate professor in the departments of Brain and Cognitive Sciences and Biological Engineering at MIT. “So far, we’ve gotten very good at inactivating genes, but actually recovering lost protein function is much more challenging. This new ability to edit RNA opens up more potential opportunities to recover that function and treat many diseases, in almost any kind of cell.”

REPAIR has the ability to target individual RNA letters, or nucleosides, switching adenosines to inosines (read as guanosines by the cell). These letters are involved in single-base changes known to regularly cause disease in humans. In human disease, a mutation from G to A is extremely common; these alterations have been implicated in, for example, cases of focal epilepsy, Duchenne muscular dystrophy, and Parkinson’s disease. REPAIR has the ability to reverse the impact of any pathogenic G-to-A mutation regardless of its surrounding nucleotide sequence, with the potential to operate in any cell type.

Unlike the permanent changes to the genome required for DNA editing, RNA editing offers a safer, more flexible way to make corrections in the cell. “REPAIR can fix mutations without tampering with the genome, and because RNA naturally degrades, it’s a potentially reversible fix,” explains co-first author David Cox, a graduate student in Zhang’s lab.

To create REPAIR, the researchers systematically profiled the CRISPR-Cas13 enzyme family for potential “editor” candidates (unlike Cas9, the Cas13 proteins target and cut RNA). They selected an enzyme from Prevotella bacteria, called PspCas13b, which was the most effective at inactivating RNA. The team engineered a deactivated variant of PspCas13b that still binds to specific stretches of RNA but lacks its “scissor-like” activity, and fused it to a protein called ADAR2, which changes the letters A to I in RNA transcripts.

In REPAIR, the deactivated Cas13b enzyme seeks out a target sequence of RNA, and the ADAR2 element performs the base conversion without cutting the transcript or relying on any of the cell’s native machinery.

The team further modified the editing system to improve its specificity, reducing detectable off-target edits from 18,385 to only 20 in the whole transcriptome. The upgraded incarnation, REPAIRv2, consistently achieved the desired edit in 20 to 40 percent — and up to 51 percent — of a targeted RNA without signs of significant off-target activity. “The success we had engineering this system is encouraging, and there are clear signs REPAIRv2 can be evolved even further for more robust activity while still maintaining specificity,” says Omar Abudayyeh, co-first author and a graduate student in Zhang’s lab. Cox and Abudayyeh are both students in the Harvard-MIT Program in Health Sciences and Technology.

To demonstrate REPAIR’s therapeutic potential, the team synthesized the pathogenic mutations that cause Fanconi anemia and X-linked nephrogenic diabetes insipidus, introduced them into human cells, and successfully corrected these mutations at the RNA level. To push the therapeutic prospects further, the team plans to improve REPAIRv2’s efficiency and to package it into a delivery system appropriate for introducing REPAIRv2 into specific tissues in animal models.

The researchers are also working on additional tools for other types of nucleotide conversions. “There’s immense natural diversity in these enzymes,” says co-first author Jonathan Gootenberg, a graduate student in both Zhang’s lab and the lab of Broad core institute member Aviv Regev. “We’re always looking to harness the power of nature to carry out these changes.”

Zhang, along with the Broad Institute and MIT, plans to share the REPAIR system widely. As with earlier CRISPR tools, the groups will make this technology freely available for academic research via the Zhang lab’s page on the plasmid-sharing website Addgene, through which the Zhang lab has already shared reagents more than 42,000 times with researchers at more than 2,200 labs in 61 countries, accelerating research around the world.

This research was funded, in part, by the National Institutes of Health and the Poitras Center for Affective Disorders Research.

Ten researchers from MIT and Broad receive NIH Director’s Awards

Anne Trafton |

The High-Risk, High-Reward Research (HRHR) program, supported by the National Institutes of Health (NIH) Common Fund, has awarded 86 grants to scientists with unconventional approaches to major challenges in biomedical and behavioral research. Ten of the awardees are affiliated with MIT and the Broad Institute of MIT and Harvard.

The NIH typically supports research projects, not individual scientists, but the HRHR program identifies specific researchers with innovative ideas to address gaps in biomedical research. The program issues four types of awards annually — the Pioneer Award, the New Innovator Award, the Transformative Research Award and the Early Independence Award — to “high-caliber investigators whose ideas stretch the boundaries of our scientific knowledge.”

Four researchers who are affiliated with either MIT or the Broad Institute received this year’s New Innovator Awards, which support “unusually innovative research” from early career investigators. They are:

  • Paul Blainey, an MIT assistant professor of biological engineering and a core member of the Broad Institute, is an expert in microanalysis systems for studies of individual molecules and cells. The award will fund the establishment a new technology that enables advanced readout from living cells.
  • Kevin Esvelt, an associate professor of media arts and sciences at MIT’s Media Lab, invents new ways to study and influence the evolution of ecosystems. Esvelt plans to use the NIH grant to develop powerful “daisy drive” systems for more precise genetic alterations of wild organisms. Such an intervention has the potential to serve as a powerful weapon against malaria, Zika, Lyme disease, and many other infectious diseases.
  • Evan Macosko is an associate member of the Broad Institute who develops molecular techniques to more deeply understand the function of cellular specialization in the nervous system. Macosko’s award will fund a novel technology, Slide-seq, which enables genome-wide expression analysis of brain tissue sections at single-cell resolution.
  • Gabriela Schlau-Cohen, an MIT assistant professor of chemistry, combines tools from chemistry, optics, biology, and microscopy to develop new approaches to study the dynamics of biological systems. Her award will be used to fund the development of a new nanometer-distance assay that directly accesses protein motion with unprecedented spatiotemporal resolution under physiological conditions.

Recipients of the Early Independence Award include three Broad Institute Fellows. The award recognizes “exceptional junior scientists” with an opportunity to skip traditional postdoctoral training and move immediately into independent research positions.

  • Ahmed Badran is a Broad Institute Fellow who studies the function of ribosomes and the control of protein synthesis. Ribosomes are important targets for antibiotics, and the NIH award will support the development of a new technology platform for probing ribosome function within living cells.
  • Fei Chen, a Broad Institute Fellow who is also a research affiliate at MIT’s McGovern Institute for Brain Research, has pioneered novel molecular and microscopy tools to illuminate biological pathways and function. He will use one of these tools, expansion microscopy, to explore the molecular basis of glioblastomas, an aggressive form of brain cancer.
  • Hilary Finucane, a Broad Institute Fellow who recently received her PhD from MIT’s Department of Mathematics, develops computational methods for analyzing biological data. She plans to develop methods to analyze large-scale genomic data to identify disease-relevant cell types and tissues, a necessary first step for understanding molecular mechanisms of disease.

Among the recipients of the NIH’s Pioneer Awards are Kay Tye, an assistant professor of brain and cognitive sciences at MIT and a member of MIT’s Picower Institute for Learning and Memory, and Feng Zhang, the James and Patricia Poitras ’63 Professor in Neuroscience, an associate professor of brain and cognitive sciences and biological engineering at MIT, a core member of the Broad Institute, and an investigator at MIT’s McGovern Institute for Brain Research. Recipients of this award are challenged to pursue “groundbreaking, high-impact approaches to a broad area of biomedical or behavioral science. Tye, who studies the brain mechanisms underlying emotion and behavior, will use her award to look at the neural representation of social homeostasis and social rank. Zhang, who pioneered the gene-editing technology known as CRISPR, plans to develop a suite of tools designed to achieve precise genome surgery for repairing disease-causing changes in DNA.

Ed Boyden, an associate professor of brain and cognitive sciences and biological engineering at MIT, and a member of MIT’s Media Lab and McGovern Institute for Brain Research, is a recipient of the Transformative Research Award. This award promotes “cross-cutting, interdisciplinary approaches that could potentially create or challenge existing paradigms.” Boyden, who develops new strategies for understanding and engineering brain circuits, will use the grant to develop high-speed 3-D imaging of neural activity.

This year, the NIH issued a total of 12 Pioneer Awards, 55 New Innovator Awards, 8 Transformative Research Awards, and 11 Early Independence Awards. The awards total $263 million and represent contributions from the NIH Common Fund; National Institute of General Medical Sciences; National Institute of Mental Health; National Center for Complementary and Integrative Health; and National Institute of Dental and Craniofacial Research.

“I continually point to this program as an example of the creative and revolutionary research NIH supports,” said NIH Director Francis S. Collins. “The quality of the investigators and the impact their research has on the biomedical field is extraordinary.”