The MIT School of Science has announced eight postdocs and research scientists as recipients of the 2022 Infinite Expansion Award.
The award, formerly known as the Infinite Kilometer Award, was created in 2012 to highlight extraordinary members of the MIT science community. The awardees are nominated not only for their research, but for going above and beyond in mentoring junior colleagues, participating in educational programs, and contributing to their departments, labs, and research centers, the school, and the Institute.
The 2022 School of Science Infinite Expansion winners are:
Héctor de Jesús-Cortés, a postdoc in the Picower Institute for Learning and Memory, nominated by professor and Department of Brain and Cognitive Sciences (BCS) head Michale Fee, professor and McGovern Institute for Brain Research Director Robert Desimone, professor and Picower Institute Director Li-Huei Tsai, professor and associate BCS head Laura Schulz, associate professor and associate BCS head Joshua McDermott, and professor and BCS Postdoc Officer Mark Bear for his “awe-inspiring commitment of time and energy to research, outreach, education, mentorship, and community;”
Harold Erbin, a postdoc in the Laboratory for Nuclear Science’s Institute for Artificial Intelligence and Fundamental Interactions (IAIFI), nominated by professor and IAIFI Director Jesse Thaler, associate professor and IAIFI Deputy Director Mike Williams, and associate professor and IAIFI Early Career and Equity Committee Chair Tracy Slatyer for “provid[ing] exemplary service on the IAIFI Early Career and Equity Committee” and being “actively involved in many other IAIFI community building efforts;”
Megan Hill, a postdoc in the Department of Chemistry, nominated by Professor Jeremiah Johnson for being an “outstanding scientist” who has “also made exceptional contributions to our community through her mentorship activities and participation in Women in Chemistry;”
Xingcheng Lin, a postdoc in the Department of Chemistry, nominated by Associate Professor Bin Zhang for being “very talented, extremely hardworking, and genuinely enthusiastic about science;”
Alexandra Pike, a postdoc in the Department of Biology, nominated by Professor Stephen Bell for “not only excel[ing] in the laboratory” but also being “an exemplary citizen in the biology department, contributing to teaching, community, and to improving diversity, equity, and inclusion in the department;”
Jakob Voigts, a research scientist in the McGovern Institute for Brain Research, nominated by Associate Professor Mark Harnett and his laboratory for “contribut[ing] to the growth and development of the lab and its members in numerous and irreplaceable ways.”
Winners are honored with a monetary award and will be celebrated with family, friends, and nominators at a later date, along with recipients of the Infinite Mile Award.
The human brain is finely tuned not only to recognize particular sounds, but also to determine which direction they came from. By comparing differences in sounds that reach the right and left ear, the brain can estimate the location of a barking dog, wailing fire engine, or approaching car.
MIT neuroscientists have now developed a computer model that can also perform that complex task. The model, which consists of several convolutional neural networks, not only performs the task as well as humans do, it also struggles in the same ways that humans do.
“We now have a model that can actually localize sounds in the real world,” says Josh McDermott, an associate professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research. “And when we treated the model like a human experimental participant and simulated this large set of experiments that people had tested humans on in the past, what we found over and over again is it the model recapitulates the results that you see in humans.”
Findings from the new study also suggest that humans’ ability to perceive location is adapted to the specific challenges of our environment, says McDermott, who is also a member of MIT’s Center for Brains, Minds, and Machines.
McDermott is the senior author of the paper, which appears today in Nature Human Behavior. The paper’s lead author is MIT graduate student Andrew Francl.
Modeling localization
When we hear a sound such as a train whistle, the sound waves reach our right and left ears at slightly different times and intensities, depending on what direction the sound is coming from. Parts of the midbrain are specialized to compare these slight differences to help estimate what direction the sound came from, a task also known as localization.
This task becomes markedly more difficult under real-world conditions — where the environment produces echoes and many sounds are heard at once.
Scientists have long sought to build computer models that can perform the same kind of calculations that the brain uses to localize sounds. These models sometimes work well in idealized settings with no background noise, but never in real-world environments, with their noises and echoes.
To develop a more sophisticated model of localization, the MIT team turned to convolutional neural networks. This kind of computer modeling has been used extensively to model the human visual system, and more recently, McDermott and other scientists have begun applying it to audition as well.
Convolutional neural networks can be designed with many different architectures, so to help them find the ones that would work best for localization, the MIT team used a supercomputer that allowed them to train and test about 1,500 different models. That search identified 10 that seemed the best-suited for localization, which the researchers further trained and used for all of their subsequent studies.
To train the models, the researchers created a virtual world in which they can control the size of the room and the reflection properties of the walls of the room. All of the sounds fed to the models originated from somewhere in one of these virtual rooms. The set of more than 400 training sounds included human voices, animal sounds, machine sounds such as car engines, and natural sounds such as thunder.
The researchers also ensured the model started with the same information provided by human ears. The outer ear, or pinna, has many folds that reflect sound, altering the frequencies that enter the ear, and these reflections vary depending on where the sound comes from. The researchers simulated this effect by running each sound through a specialized mathematical function before it went into the computer model.
“This allows us to give the model the same kind of information that a person would have,” Francl says.
After training the models, the researchers tested them in a real-world environment. They placed a mannequin with microphones in its ears in an actual room and played sounds from different directions, then fed those recordings into the models. The models performed very similarly to humans when asked to localize these sounds.
“Although the model was trained in a virtual world, when we evaluated it, it could localize sounds in the real world,” Francl says.
Similar patterns
The researchers then subjected the models to a series of tests that scientists have used in the past to study humans’ localization abilities.
In addition to analyzing the difference in arrival time at the right and left ears, the human brain also bases its location judgments on differences in the intensity of sound that reaches each ear. Previous studies have shown that the success of both of these strategies varies depending on the frequency of the incoming sound. In the new study, the MIT team found that the models showed this same pattern of sensitivity to frequency.
“The model seems to use timing and level differences between the two ears in the same way that people do, in a way that’s frequency-dependent,” McDermott says.
The researchers also showed that when they made localization tasks more difficult, by adding multiple sound sources played at the same time, the computer models’ performance declined in a way that closely mimicked human failure patterns under the same circumstances.
“As you add more and more sources, you get a specific pattern of decline in humans’ ability to accurately judge the number of sources present, and their ability to localize those sources,” Francl says. “Humans seem to be limited to localizing about three sources at once, and when we ran the same test on the model, we saw a really similar pattern of behavior.”
Because the researchers used a virtual world to train their models, they were also able to explore what happens when their model learned to localize in different types of unnatural conditions. The researchers trained one set of models in a virtual world with no echoes, and another in a world where there was never more than one sound heard at a time. In a third, the models were only exposed to sounds with narrow frequency ranges, instead of naturally occurring sounds.
When the models trained in these unnatural worlds were evaluated on the same battery of behavioral tests, the models deviated from human behavior, and the ways in which they failed varied depending on the type of environment they had been trained in. These results support the idea that the localization abilities of the human brain are adapted to the environments in which humans evolved, the researchers say.
The researchers are now applying this type of modeling to other aspects of audition, such as pitch perception and speech recognition, and believe it could also be used to understand other cognitive phenomena, such as the limits on what a person can pay attention to or remember, McDermott says.
The research was funded by the National Science Foundation and the National Institute on Deafness and Other Communication Disorders.
Five MIT faculty members have been elected as fellows of the American Association for the Advancement of Science (AAAS).
The 2021 class of AAAS Fellows includes 564 scientists, engineers, and innovators spanning 24 scientific disciplines who are being recognized for their scientifically and socially distinguished achievements.
Mircea Dincă is the W. M. Keck Professor of Energy in the Department of Chemistry. His group’s research focuses on addressing challenges related to the storage and consumption of energy, and global environmental concerns. Central to these efforts are the synthesis of novel organic-inorganic hybrid materials and the manipulation of their electrochemical and photophysical properties, with a current emphasis on porous materials and extended one-dimensional van der Waals materials.
Guoping Feng is the James W. and Patricia T. Poitras Professor of Neuroscience in the Department of Brain and Cognitive Sciences, associate director of MIT’s McGovern Institute for Brain Research, director of Model Systems and Neurobiology at the Stanley Center for Psychiatric Research, and an institute member of the Broad Institute of MIT and Harvard. His research is devoted to understanding the development and function of synapses in the brain and how synaptic dysfunction may contribute to neurodevelopmental and psychiatric disorders. By understanding the molecular, cellular, and circuitry mechanisms of these disorders, Feng hopes his work will eventually lead to the development of new and effective treatments for the millions of people suffering from these devastating diseases.
David Shoemaker is a senior research scientist with the MIT Kavli Institute for Astrophysics and Space Research. His work is focused on gravitational-wave observation and includes developing technologies for the detectors (LIGO, LISA), developing proposals for new instruments (Cosmic Explorer), managing the teams to build them and the consortia which exploit the data (LIGO Scientific Collaboration, LISA Consortium), and supporting the overall growth of the field (Gravitational-Wave International Committee).
Ian Hunter is the Hatsopoulos Professor of Mechanical Engineering and runs the Bioinstrumentation Lab at MIT. His main areas of research are instrumentation, microrobotics, medical devices, and biomimetic materials. Over the years he and his students have developed many instruments and devices including: confocal laser microscopes, scanning tunneling electron microscopes, miniature mass spectrometers, new forms of Raman spectroscopy, needle-free drug delivery technologies, nano- and micro-robots, microsurgical robots, robotic endoscopes, high-performance Lorentz force motors, and microarray technologies for massively parallel chemical and biological assays.
Evelyn N. Wang is the Ford Professor of Engineering and head of the Department of Mechanical Engineering. Her research program combines fundamental studies of micro/nanoscale heat and mass transport processes with the development of novel engineered structures to create innovative solutions in thermal management, energy, and water harvesting systems. Her work in thermophotovoltaics was named to Technology Review’s lists of Biggest Clean Energy Advances, in 2016, and Ten Breakthrough Technologies, in 2017, and to the Department of Energy Frontiers Research Center’s Ten of Ten awards. Her work extracting water from air has won her the title of 2017 Foreign Policy’s Global ReThinker and the 2018 Eighth Prince Sultan bin Abdulaziz International Prize for Water.
MIT neuroscientist and McGovern Investigator Nancy Kanwisher. Photo: Jussi Puikkonen/KNAW
The National Academy of Sciences (NAS) has announced today that Nancy Kanwisher, the Walter A. Rosenblith Professor of Cognitive Neuroscience in MIT’s Department of Brain and Cognitive Sciences, has received the 2022 NAS Award in the Neurosciences for her “pioneering research into the functional organization of the human brain.” The $25,000 prize, established by the Fidia Research Foundation, is presented every three years to recognize “extraordinary contributions to the neuroscience fields.”
“I am deeply honored to receive this award from the NAS,” says Kanwisher, who is also an investigator in MIT’s McGovern Institute and a member of the Center for Brains, Minds and Machines. “It has been a profound privilege, and a total blast, to watch the human brain in action as these data began to reveal an initial picture of the organization of the human mind. But the biggest joy has been the opportunity to work with the incredible group of talented young scientists who actually did the work that this award recognizes.”
A window into the mind
Kanwisher is best known for her landmark insights into how humans recognize and process faces. Psychology had long-suggested that recognizing a face might be distinct from general object recognition. But Kanwisher galvanized the field in 1997 with her seminal discovery that the human brain contains a small region specialized to respond only to faces. The region, which Kanwisher termed the fusiform face area (FFA), became activated when subjects viewed images of faces in an MRI scanner, but not when they looked at scrambled faces or control stimuli.
Since her 1997 discovery (now the most highly cited manuscript in its area), Kanwisher and her students have applied similar methods to find brain specializations for the recognition of scenes, the mental states of others, language, and music. Taken together, her research provides a compelling glimpse into the architecture of the brain, and, ultimately, what makes us human.
“Nancy’s work over the past two decades has argued that many aspects of human cognition are supported by specialized neural circuitry, a conclusion that stands in contrast to our subjective sense of a singular mental experience,” says McGovern Institute Director Robert Desimone. “She has made profound contributions to the psychological and cognitive sciences and I am delighted that the National Academy of Sciences has recognized her outstanding achievements.”
One-in-a-million mentor
Beyond the lab, Kanwisher has a reputation as a tireless communicator and mentor who is actively engaged in the policy implications of brain research. The statistics speak for themselves: her 2014 TED talk, “A Neural portrait of the human mind” has been viewed over a million times online and her introductory MIT OCW course on the human brain has generated more than nine million views on YouTube.
Nancy Kanwisher works with researchers from her lab in MIT’s Martinos Imaging Center. Photo: Kris Brewer
Kanwisher also has an exceptional track record in training women scientists who have gone on to successful independent research careers, in many cases becoming prominent figures in their own right.
“Nancy is the one-in-a-million mentor, who is always skeptical of your ideas and your arguments, but immensely confident of your worth,” says Rebecca Saxe, John W. Jarve (1978) Professor of Brain and Cognitive Sciences, investigator at the McGovern Institute, and associate dean of MIT’s School of Science. Saxe was a graduate student in Kanwisher’s lab where she earned her PhD in cognitive neuroscience in 2003. “She has such authentic curiosity,” Saxe adds. “It’s infectious and sustaining. Working with Nancy was a constant reminder of why I wanted to be a scientist.”
The NAS will present Kanwisher with the award during its annual meeting on May 1, 2022 in Washington, DC. The event will be webcast live. Kanwisher plans to direct her prize funds to the non-profit organization Malengo, established by a former student and which provides quality undergraduate education to individuals who would otherwise not be able to afford it.
Learning to navigate social relationships is a skill that is critical for surviving in human societies. For babies and young children, that means learning who they can count on to take care of them.
MIT neuroscientists have now identified a specific signal that young children and even babies use to determine whether two people have a strong relationship and a mutual obligation to help each other: whether those two people kiss, share food, or have other interactions that involve sharing saliva.
In a new study, the researchers showed that babies expect people who share saliva to come to one another’s aid when one person is in distress, much more so than when people share toys or interact in other ways that do not involve saliva exchange. The findings suggest that babies can use these cues to try to figure out who around them is most likely to offer help, the researchers say.
“Babies don’t know in advance which relationships are the close and morally obligating ones, so they have to have some way of learning this by looking at what happens around them,” says Rebecca Saxe, the John W. Jarve Professor of Brain and Cognitive Sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the new study.
MIT postdoc Ashley Thomas is the lead author of the study, which appears today in Science. Brandon Woo, a Harvard University graduate student; Daniel Nettle, a professor of behavioral science at Newcastle University; and Elizabeth Spelke, a professor of psychology at Harvard, are also authors of the paper.
Sharing saliva
In human societies, people typically distinguish between “thick” and “thin” relationships. Thick relationships, usually found between family members, feature strong levels of attachment, obligation, and mutual responsiveness. Anthropologists have also observed that people in thick relationships are more willing to share bodily fluids such as saliva.
“That inspired both the question of whether infants distinguish between those types of relationships, and whether saliva sharing might be a really good cue they could use to recognize them,” Thomas says.
To study those questions, the researchers observed toddlers (16.5 to 18.5 months) and babies (8.5 to 10 months) as they watched interactions between human actors and puppets. In the first set of experiments, a puppet shared an orange with one actor, then tossed a ball back and forth with a different actor.
After the children watched these initial interactions, the researchers observed the children’s reactions when the puppet showed distress while sitting between the two actors. Based on an earlier study of nonhuman primates, the researchers hypothesized that babies would look first at the person whom they expected to help. That study showed that when baby monkeys cry, other members of the troop look to the baby’s parents, as if expecting them to step in.
The MIT team found that the children were more likely to look toward the actor who had shared food with the puppet, not the one who had shared a toy, when the puppet was in distress.
In a second set of experiments, designed to focus more specifically on saliva, the actor either placed her finger in her mouth and then into the mouth of the puppet, or placed her finger on her forehead and then onto the forehead of the puppet. Later, when the actor expressed distress while standing between the two puppets, children watching the video were more likely to look toward the puppet with whom she had shared saliva.
Social cues
The findings suggest that saliva sharing is likely an important cue that helps infants to learn about their own social relationships and those of people around them, the researchers say.
“The general skill of learning about social relationships is very useful,” Thomas says. “One reason why this distinction between thick and thin might be important for infants in particular, especially human infants, who depend on adults for longer than many other species, is that it might be a good way to figure out who else can provide the support that they depend on to survive.”
The researchers did their first set of studies shortly before Covid-19 lockdowns began, with babies who came to the lab with their families. Later experiments were done over Zoom. The results that the researchers saw were similar before and after the pandemic, confirming that pandemic-related hygiene concerns did not affect the outcome.
“We actually know the results would have been similar if it hadn’t been for the pandemic,” Saxe says. “You might wonder, did kids start to think very differently about sharing saliva when suddenly everybody was talking about hygiene all the time? So, for that question, it’s very useful that we had an initial data set collected before the pandemic.”
Doing the second set of studies on Zoom also allowed the researchers to recruit a much more diverse group of children because the subjects were not limited to families who could come to the lab in Cambridge during normal working hours.
In future work, the researchers hope to perform similar studies with infants in cultures that have different types of family structures. In adult subjects, they plan to use functional magnetic resonance imaging (fMRI) to study what parts of the brain are involved in making saliva-based assessments about social relationships.
The research was funded by the National Institutes of Health; the Patrick J. McGovern Foundation; the Guggenheim Foundation; a Social Sciences and Humanities Research Council Doctoral Fellowship; MIT’s Center for Brains, Minds, and Machines; and the Siegel Foundation.
For people struggling with substance use disorders — and there are about 35 million of them worldwide — treatment options are limited. Even among those who seek help, relapse is common. In the United States, an epidemic of opioid addiction has been declared a public health emergency.
A 2019 survey found that 1.6 million people nationwide had an opioid use disorder, and the crisis has surged since the start of the COVID-19 pandemic. The Centers for Disease Control and Prevention estimates that more than 100,000 people died of drug overdose between April 2020 and April 2021 — nearly 30 percent more overdose deaths than occurred during the same period the previous year.
In the United States, an epidemic of opioid addiction has been declared a public health emergency.
A deeper understanding of what addiction does to the brain and body is urgently needed to pave the way to interventions that reliably release affected individuals from its grip. At the McGovern Institute, researchers are turning their attention to addiction’s driving force: the deep, recurring craving that makes people prioritize drug use over all other wants and needs.
McGovern Institute co-founder, Lore Harp McGovern.
“When you are in that state, then it seems nothing else matters,” says McGovern Investigator Fan Wang. “At that moment, you can discard everything: your relationship, your house, your job, everything. You only want the drug.”
With a new addiction initiative catalyzed by generous gifts from Institute co-founder Lore Harp McGovern and others, McGovern scientists with diverse expertise have come together to begin clarifying the neurobiology that underlies the craving state. They plan to dissect the neural transformations associated with craving at every level — from the drug-induced chemical changes that alter neuronal connections and activity to how these modifications impact signaling brain-wide. Ultimately, the McGovern team hopes not just to understand the craving state, but to find a way to relieve it — for good.
“If we can understand the craving state and correct it, or at least relieve a little bit of the pressure,” explains Wang, who will help lead the addiction initiative, “then maybe we can at least give people a chance to use their top-down control to not take the drug.”
The craving cycle
For individuals suffering from substance use disorders, craving fuels a cyclical pattern of escalating drug use. Following the euphoria induced by a drug like heroin or cocaine, depression sets in, accompanied by a drug craving motivated by the desire to relieve that suffering. And as addiction progresses, the peaks and valleys of this cycle dip lower: the pleasant feelings evoked by the drug become weaker, while the negative effects a person experiences in its absence worsen. The craving remains, and increasing use of the drug are required to relieve it.
By the time addiction sets in, the brain has been altered in ways that go beyond a drug’s immediate effects on neural signaling.
These insidious changes leave individuals susceptible to craving — and the vulnerable state endures. Long after the physical effects of withdrawal have subsided, people with substance use disorders can find their craving returns, triggered by exposure to a small amount of the drug, physical or social cues associated with previous drug use, or stress. So researchers will need to determine not only how different parts of the brain interact with one another during craving and how individual cells and the molecules within them are affected by the craving state — but also how things change as addiction develops and progresses.
Circuits, chemistry and connectivity
One clear starting point is the circuitry the brain uses to control motivation. Thanks in part to decades of research in the lab of McGovern Investigator Ann Graybiel, neuroscientists know a great deal about how these circuits learn which actions lead to pleasure and which lead to pain, and how they use that information to establish habits and evaluate the costs and benefits of complex decisions.
Graybiel’s work has shown that drugs of abuse strongly activate dopamine-responsive neurons in a part of the brain called the striatum, whose signals promote habit formation. By increasing the amount of dopamine that neurons release, these drugs motivate users to prioritize repeated drug use over other kinds of rewards, and to choose the drug in spite of pain or other negative effects. Her group continues to investigate the naturally occurring molecules that control these circuits, as well as how they are hijacked by drugs of abuse.
Distribution of opioid receptors targeted by morphine (shown in blue) in two regions in the dorsal striatum and nucleus accumbens of the mouse brain. Image: Ann Graybiel
In Fan Wang’s lab, work investigating the neural circuits that mediate the perception of physical pain has led her team to question the role of emotional pain in craving. As they investigated the source of pain sensations in the brain, they identified neurons in an emotion-regulating center called the central amygdala that appear to suppress physical pain in animals. Now, Wang wants to know whether it might be possible to modulate neurons involved in emotional pain to ameliorate the negative state that provokes drug craving.
These animal studies will be key to identifying the cellular and molecular changes that set the brain up for recurring cravings. And as McGovern scientists begin to investigate what happens in the brains of rodents that have been trained to self-administer addictive drugs like fentanyl or cocaine, they expect to encounter tremendous complexity.
McGovern Associate Investigator Polina Anikeeva, whose lab has pioneered new technologies that will help the team investigate the full spectrum of changes that underlie craving, says it will be important to consider impacts on the brain’s chemistry, firing patterns, and connectivity. To that end, multifunctional research probes developed in her lab will be critical to monitoring and manipulating neural circuits in animal models.
Imaging technology developed by investigator Ed Boyden will also enable nanoscale protein visualization brain-wide. An important goal will be to identify a neural signature of the craving state. With such a signal, researchers can begin to explore how to shut off that craving — possibly by directly modulating neural signaling.
Targeted treatments
“One of the reasons to study craving is because it’s a natural treatment point,” says McGovern Associate Investigator Alan Jasanoff. “And the dominant kind of approaches that people in our team think about are approaches that relate to neural circuits — to the specific connections between brain regions and how those could be changed.” The hope, he explains, is that it might be possible to identify a brain region whose activity is disrupted during the craving state, then use clinical brain stimulation methods to restore normal signaling — within that region, as well as in other connected parts of the brain.
To identify the right targets for such a treatment, it will be crucial to understand how the biology uncovered in laboratory animals reflects what’s happens in people with substance use disorders. Functional imaging in John Gabrieli’s lab can help bridge the gap between clinical and animal research by revealing patterns of brain activity associated with the craving state in both humans and rodents. A new technique developed in Jasanoff’s lab makes it possible to focus on the activity between specific regions of an animal’s brain. “By doing that, we hope to build up integrated models of how information passes around the brain in craving states, and of course also in control states where we’re not experiencing craving,” he explains.
In delving into the biology of the craving state, McGovern scientists are embarking on largely unexplored territory — and they do so with both optimism and urgency. “It’s hard to not appreciate just the size of the problem, and just how devastating addiction is,” says Anikeeva. “At this point, it just seems almost irresponsible to not work on it, especially when we do have the tools and we are interested in the general brain regions that are important for that problem. I would say that there’s almost a civic duty.”
New research from MIT neuroscientists suggest that natural soundscapes have shaped our sense of hearing, optimizing it for the kinds of sounds we most often encounter.
Mark Saddler, graduate fellow of the K. Lisa Yang Integrative Computational Neuroscience Center. Photo: Caitlin Cunningham
In a study reported December 14 in the journal Nature Communications, researchers led by McGovern Institute Associate Investigator Josh McDermott used computational modeling to explore factors that influence how humans hear pitch. Their model’s pitch perception closely resembled that of humans—but only when it was trained using music, voices, or other naturalistic sounds.
Humans’ ability to recognize pitch—essentially, the rate at which a sound repeats—gives melody to music and nuance to spoken language. Although this is arguably the best-studied aspect of human hearing, researchers are still debating which factors determine the properties of pitch perception, and why it is more acute for some types of sounds than others. McDermott, who is also an associate professor in MIT’s Department of Brain and Cognitive Sciences and an investigator with the Center for Brains Minds and Machines (CBMM), is particularly interested in understanding how our nervous system perceives pitch because cochlear implants, which send electrical signals about sound to the brain in people with profound deafness, don’t replicate this aspect of human hearing very well.
“Cochlear implants can do a pretty good job of helping people understand speech, especially if they’re in a quiet environment. But they really don’t reproduce the percept of pitch very well,” says Mark Saddler, a CBMM graduate student who co-led the project and an inaugural graduate fellow of the K. Lisa Yang Integrative Computational Neuroscience Center. “One of the reasons it’s important to understand the detailed basis of pitch perception in people with normal hearing is to try to get better insights into how we would reproduce that artificially in a prosthesis.”
Artificial hearing
Pitch perception begins in the cochlea, the snail-shaped structure in the inner ear where vibrations from sounds are transformed into electrical signals and relayed to the brain via the auditory nerve. The cochlea’s structure and function help determine how and what we hear. And although it hasn’t been possible to test this idea experimentally, McDermott’s team suspected our “auditory diet” might shape our hearing as well.
To explore how both our ears and our environment influence pitch perception, McDermott, Saddler and research assistant Ray Gonzalez built a computer model called a deep neural network. Neural networks are a type of machine learning model widely used in automatic speech recognition and other artificial intelligence applications. Although the structure of an artificial neural network coarsely resembles the connectivity of neurons in the brain, the models used in engineering applications don’t actually hear the same way humans do—so the team developed a new model to reproduce human pitch perception. Their approach combined an artificial neural network with an existing model of the mammalian ear, uniting the power of machine learning with insights from biology. “These new machine learning models are really the first that can be trained to do complex auditory tasks and actually do them well, at human levels of performance,” Saddler explains.
The researchers trained the neural network to estimate pitch by asking it to identify the repetition rate of sounds in a training set. This gave them the flexibility to change the parameters under which pitch perception developed. They could manipulate the types of sound they presented to the model, as well as the properties of the ear that processed those sounds before passing them on to the neural network.
When the model was trained using sounds that are important to humans, like speech and music, it learned to estimate pitch much as humans do. “We very nicely replicated many characteristics of human perception…suggesting that it’s using similar cues from the sounds and the cochlear representation to do the task,” Saddler says.
But when the model was trained using more artificial sounds or in the absence of any background noise, its behavior was very different. For example, Saddler says, “If you optimize for this idealized world where there’s never any competing sources of noise, you can learn a pitch strategy that seems to be very different from that of humans, which suggests that perhaps the human pitch system was really optimized to deal with cases where sometimes noise is obscuring parts of the sound.”
The team also found the timing of nerve signals initiated in the cochlea to be critical to pitch perception. In a healthy cochlea, McDermott explains, nerve cells fire precisely in time with the sound vibrations that reach the inner ear. When the researchers skewed this relationship in their model, so that the timing of nerve signals was less tightly correlated to vibrations produced by incoming sounds, pitch perception deviated from normal human hearing.
McDermott says it will be important to take this into account as researchers work to develop better cochlear implants. “It does very much suggest that for cochlear implants to produce normal pitch perception, there needs to be a way to reproduce the fine-grained timing information in the auditory nerve,” he says. “Right now, they don’t do that, and there are technical challenges to making that happen—but the modeling results really pretty clearly suggest that’s what you’ve got to do.”
by Robert Desimone, McGovern Institute | Nergis Mavalvala, MIT School of Science | Maria T. Zuber, MIT Office of the Vice President for Research |
Following is an open statement in response to “Is MIT’s Research Helping the Chinese Military?”, an opinion essay by Michelle Bethel posted by the Wall Street Journal on Dec. 10, 2021. This statement is jointly from Prof. Robert Desimone, director of the McGovern Institute for Brain Research at MIT, Prof. Nergis Mavalvala, dean of MIT’s School of Science, and Prof. Maria T. Zuber, vice president for research at MIT.
Ms. Bethel is absolutely right that research relationships with institutions in China require the most serious care and consideration. MIT brings a thorough and rigorous approach to these matters.
First let us be clear about the work of the MIT McGovern Institute for Brain Research. Of the dozens of research projects currently under way at the McGovern Institute, there is one active research collaboration with China. It involves better identifying and ultimately developing treatments for severe forms of autism or neurological disorders that often render individuals unable to speak and frequently require lifelong care. That project was thoroughly vetted and approved by the U.S. National Institutes of Health in 2019. MIT receives no funding from China for this research, and all findings will be published in peer-reviewed journals, meaning that they are open to medical researchers anywhere in the world. This is the collaboration with the Shenzhen Institute of Advanced Technology that Ms. Bethel referenced in vague terms.
This does not eliminate general concerns about how research may be conducted or used, however. That’s why MIT has strong processes for evaluating and managing the risks of research involving countries, including China, whose behavior affects U.S. national and economic security. Every proposed engagement that involves an organization or funding source from China, once it has been evaluated for compliance with U.S. law and regulation, is further reviewed by committees of senior administrators to consider risks related to national security, economic competitiveness, and civil and human rights. Projects have been variously turned down, modified, or approved under this process.
Ms. Bethel raises important points with respect to U.S.-China relations – but not with respect to the work of the McGovern Institute. We regret that Ms. Bethel felt it necessary to step away from the McGovern, but we respect her views and continue in conversation with her. We note that two other members of the McGovern family, including the McGovern Institute’s co-founder and another daughter, continue to proudly serve on the McGovern board. We are grateful to all three family members.
In a fitting sequel to its entrepreneurship “boot camp” educational lecture series last fall, the MIT Future Founders Initiative has announced the MIT Future Founders Prize Competition, supported by Northpond Ventures, and named the MIT faculty cohort that will participate in this year’s competition. The Future Founders Initiative was established in 2020 to promote female entrepreneurship in biotech.
Despite increasing representation at MIT, female science and engineering faculty found biotech startups at a disproportionately low rate compared with their male colleagues, according to research led by the initiative’s founders, MIT Professor Sangeeta Bhatia, MIT Professor and President Emerita Susan Hockfield, and MIT Amgen Professor of Biology Emerita Nancy Hopkins. In addition to highlighting systemic gender imbalances in the biotech pipeline, the initiative’s founders emphasize that the dearth of female biotech entrepreneurs represents lost opportunities for society as a whole — a bottleneck in the proliferation of publicly accessible medical and technological innovation.
“A very common myth is that representation of women in the pipeline is getting better with time … We can now look at the data … and simply say, ‘that’s not true’,” said Bhatia, who is the John and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science, and a member of MIT’s Koch Institute for Integrative Cancer Research and the Institute for Medical Engineering and Science, in an interview for the March/April 2021 MIT Faculty Newsletter. “We need new solutions. This isn’t just about waiting and being optimistic.”
Inspired by generous funding from Northpond Labs, the research and development-focused affiliate of Northpond Ventures, and by the success of other MIT prize incentive competitions such as the Climate Tech and Energy Prize, the Future Founders Initiative Prize Competition will be structured as a learning cohort in which participants will be supported in commercializing their existing inventions with instruction in market assessments, fundraising, and business capitalization, as well as other programming. The program, which is being run as a partnership between the MIT School of Engineering and the Martin Trust Center for MIT Entrepreneurship, provides hands-on opportunities to learn from industry leaders about their experiences, ranging from licensing technology to creating early startup companies. Bhatia and Kit Hickey, an entrepreneur-in-residence at the Martin Trust Center and senior lecturer at the MIT Sloan School of Management, are co-directors of the program.
“The competition is an extraordinary effort to increase the number of female faculty who translate their research and ideas into real-world applications through entrepreneurship,” says Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. “Our hope is that this likewise serves as an opportunity for participants to gain exposure and experience to the many ways in which they could achieve commercial impact through their research.”
At the end of the program, the cohort members will pitch their ideas to a selection committee composed of MIT faculty, biotech founders, and venture capitalists. The grand prize winner will receive $250,000 in discretionary funds, and two runners-up will receive $100,000. The winners will be announced at a showcase event, at which the entire cohort will present their work. All participants will also receive a $10,000 stipend for participating in the competition.
“The biggest payoff is not identifying the winner of the competition,” says Bhatia. “Really, what we are doing is creating a cohort … and then, at the end, we want to create a lot of visibility for these women and make them ‘top of mind’ in the community.”
The Selection Committee members for the MIT Future Founders Prize Competition are:
Bill Aulet, professor of the practice in the MIT Sloan School of Management and managing director of the Martin Trust Center for MIT Entrepreneurship
Sangeeta Bhatia, the John and Dorothy Wilson Professor of Electrical Engineering and Computer Science at MIT; a member of MIT’s Koch Institute for Integrative Cancer Research and the Institute for Medical Engineering and Science; and founder of Hepregen, Glympse Bio, and Satellite Bio
Kit Hickey, senior lecturer in the MIT Sloan School of Management and entrepreneur-in-residence at the Martin Trust Center
Susan Hockfield, MIT president emerita and professor of neuroscience
Harvey Lodish, professor of biology and biomedical engineering at MIT and founder of Genzyme, Millennium, and Rubius
Fiona Murray, associate dean for innovation and inclusion in the MIT Sloan School of Management; the William Porter Professor of Entrepreneurship; co-director of the MIT Innovation Initiative; and faculty director of the MIT Legatum Center
Amy Schulman, founding CEO of Lyndra Therapeutics and partner at Polaris Partners
“As an investment firm dedicated to supporting entrepreneurs, we are acutely aware of the limited number of companies founded and led by women in academia. We believe humanity should be benefiting from brilliant ideas and scientific breakthroughs from women in science, which could address many of the world’s most pressing problems. Together with MIT, we are providing an opportunity for women faculty members to enhance their visibility and gain access to the venture capital ecosystem,” says Andrea Jackson, director at Northpond Ventures.
“This first cohort is representative of the unrealized opportunity this program is designed to capture. While it will take a while to build a robust community of connections and role models, I am pleased and confident this program will make entrepreneurship more accessible and inclusive to our community, which will greatly benefit society,” says Susan Hockfield, MIT president emerita.
The MIT Future Founders Prize Competition cohort members were selected from schools across MIT, including the School of Science, the School of Engineering, and Media Lab within the School of Architecture and Planning. They are:
Polina Anikeeva is professor of materials science and engineering and brain and cognitive sciences, an associate member of the McGovern Institute for Brain Research, and the associate director of the Research Laboratory of Electronics. She is particularly interested in advancing the possibility of future neuroprosthetics, through biologically-informed materials synthesis, modeling, and device fabrication. Anikeeva earned her BS in biophysics from St. Petersburg State Polytechnic University and her PhD in materials science and engineering from MIT.
Natalie Artzi is principal research scientist in the Institute of Medical Engineering and Science and an assistant professor in the department of medicine at Brigham and Women’s Hospital. Through the development of smart materials and medical devices, her research seeks to “personalize” medical interventions based on the specific presentation of diseased tissue in a given patient. She earned both her BS and PhD in chemical engineering from the Technion-Israel Institute of Technology.
Laurie A. Boyer is professor of biology and biological engineering in the Department of Biology. By studying how diverse molecular programs cross-talk to regulate the developing heart, she seeks to develop new therapies that can help repair cardiac tissue. She earned her BS in biomedical science from Framingham State University and her PhD from the University of Massachusetts Medical School.
Tal Cohen is associate professor in the departments of Civil and Environmental Engineering and Mechanical Engineering. She wields her understanding of how materials behave when they are pushed to their extremes to tackle engineering challenges in medicine and industry. She earned her BS, MS, and PhD in aerospace engineering from the Technion-Israel Institute of Technology.
Canan Dagdeviren is assistant professor of media arts and sciences and the LG Career Development Professor of Media Arts and Sciences. Her research focus is on creating new sensing, energy harvesting, and actuation devices that can be stretched, wrapped, folded, twisted, and implanted onto the human body while maintaining optimal performance. She earned her BS in physics engineering from Hacettepe University, her MS in materials science and engineering from Sabanci University, and her PhD in materials science and engineering from the University of Illinois at Urbana-Champaign.
Ariel Furst is the Raymond (1921) & Helen St. Laurent Career Development Professor in the Department of Chemical Engineering. Her research addresses challenges in global health and sustainability, utilizing electrochemical methods and biomaterials engineering. She is particularly interested in new technologies that detect and treat disease. Furst earned her BS in chemistry at the University of Chicago and her PhD at Caltech.
Kristin Knouse is assistant professor in the Department of Biology and the Koch Institute for Integrative Cancer Research. She develops tools to investigate the molecular regulation of organ injury and regeneration directly within a living organism with the goal of uncovering novel therapeutic avenues for diverse diseases. She earned her BS in biology from Duke University, her PhD and MD through the Harvard and MIT MD-PhD program.
Elly Nedivi is the William R. (1964) & Linda R. Young Professor of Neuroscience at the Picower Institute for Learning and Memory with joint appointments in the departments of Brain and Cognitive Sciences and Biology. Through her research of neurons, genes, and proteins, Nedivi focuses on elucidating the cellular mechanisms that control plasticity in both the developing and adult brain. She earned her BS in biology from Hebrew University and her PhD in neuroscience from Stanford University.
Ellen Roche is associate professor in the Department of Mechanical Engineering and Institute of Medical Engineering and Science, and the W.M. Keck Career Development Professor in Biomedical Engineering. Borrowing principles and design forms she observes in nature, Roche works to develop implantable therapeutic devices that assist cardiac and other biological function. She earned her bachelor’s degree in biomedical engineering from the National University of Ireland at Galway, her MS in bioengineering from Trinity College Dublin, and her PhD from Harvard University.
