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Differences between deep neural networks and human perception

by Kenneth Blum |

When your mother calls your name, you know it’s her voice — no matter the volume, even over a poor cell phone connection. And when you see her face, you know it’s hers — if she is far away, if the lighting is poor, or if you are on a bad FaceTime call. This robustness to variation is a hallmark of human perception. On the other hand, we are susceptible to illusions: We might fail to distinguish between sounds or images that are, in fact, different. Scientists have explained many of these illusions, but we lack a full understanding of the invariances in our auditory and visual systems.

Deep neural networks also have performed speech recognition and image classification tasks with impressive robustness to variations in the auditory or visual stimuli. But are the invariances learned by these models similar to the invariances learned by human perceptual systems? A group of MIT researchers has discovered that they are different. They presented their findings yesterday at the 2019 Conference on Neural Information Processing Systems.

The researchers made a novel generalization of a classical concept: “metamers” — physically distinct stimuli that generate the same perceptual effect. The most famous examples of metamer stimuli arise because most people have three different types of cones in their retinae, which are responsible for color vision. The perceived color of any single wavelength of light can be matched exactly by a particular combination of three lights of different colors — for example, red, green, and blue lights. Nineteenth-century scientists inferred from this observation that humans have three different types of bright-light detectors in our eyes. This is the basis for electronic color displays on all of the screens we stare at every day. Another example in the visual system is that when we fix our gaze on an object, we may perceive surrounding visual scenes that differ at the periphery as identical. In the auditory domain, something analogous can be observed. For example, the “textural” sound of two swarms of insects might be indistinguishable, despite differing in the acoustic details that compose them, because they have similar aggregate statistical properties. In each case, the metamers provide insight into the mechanisms of perception, and constrain models of the human visual or auditory systems.

In the current work, the researchers randomly chose natural images and sound clips of spoken words from standard databases, and then synthesized sounds and images so that deep neural networks would sort them into the same classes as their natural counterparts. That is, they generated physically distinct stimuli that are classified identically by models, rather than by humans. This is a new way to think about metamers, generalizing the concept to swap the role of computer models for human perceivers. They therefore called these synthesized stimuli “model metamers” of the paired natural stimuli. The researchers then tested whether humans could identify the words and images.

“Participants heard a short segment of speech and had to identify from a list of words which word was in the middle of the clip. For the natural audio this task is easy, but for many of the model metamers humans had a hard time recognizing the sound,” explains first-author Jenelle Feather, a graduate student in the MIT Department of Brain and Cognitive Sciences (BCS) and a member of the Center for Brains, Minds, and Machines (CBMM). That is, humans would not put the synthetic stimuli in the same class as the spoken word “bird” or the image of a bird. In fact, model metamers generated to match the responses of the deepest layers of the model were generally unrecognizable as words or images by human subjects.

Josh McDermott, associate professor in BCS and investigator in CBMM, makes the following case: “The basic logic is that if we have a good model of human perception, say of speech recognition, then if we pick two sounds that the model says are the same and present these two sounds to a human listener, that human should also say that the two sounds are the same. If the human listener instead perceives the stimuli to be different, this is a clear indication that the representations in our model do not match those of human perception.”

Joining Feather and McDermott on the paper are Alex Durango, a post-baccalaureate student, and Ray Gonzalez, a research assistant, both in BCS.

There is another type of failure of deep networks that has received a lot of attention in the media: adversarial examples (see, for example, “Why did my classifier just mistake a turtle for a rifle?“). These are stimuli that appear similar to humans but are misclassified by a model network (by design — they are constructed to be misclassified). They are complementary to the stimuli generated by Feather’s group, which sound or appear different to humans but are designed to be co-classified by the model network. The vulnerabilities of model networks exposed to adversarial attacks are well-known — face-recognition software might mistake identities; automated vehicles might not recognize pedestrians.

The importance of this work lies in improving models of perception beyond deep networks. Although the standard adversarial examples indicate differences between deep networks and human perceptual systems, the new stimuli generated by the McDermott group arguably represent a more fundamental model failure — they show that generic examples of stimuli classified as the same by a deep network produce wildly different percepts for humans.

The team also figured out ways to modify the model networks to yield metamers that were more plausible sounds and images to humans. As McDermott says, “This gives us hope that we may be able to eventually develop models that pass the metamer test and better capture human invariances.”

“Model metamers demonstrate a significant failure of present-day neural networks to match the invariances in the human visual and auditory systems,” says Feather, “We hope that this work will provide a useful behavioral measuring stick to improve model representations and create better models of human sensory systems.”

Brain science in the Bolivian rainforest

by Julie Pryor |

Malinda McPherson headshot
Graduate student Malinda McPherson. Photo: Caitlin Cunningham

Malinda McPherson is a graduate student in Josh McDermott‘s lab, studying how people hear pitch (how high or low a sound is) in both speech and music.

To test the extent to which human audition varies across cultures, McPherson travels with the McDermott lab to Bolivia to study the Tsimane’ — a native Amazonian society with minimal exposure to Western culture.

Their most recent study, published in the journal Current Biology, found a striking variation in perception of musical pitch across cultures.

In this Q&A, we ask McPherson what motivates her research and to describe some of the challenges she has experienced working in the Bolivian rainforest. 

What are you working on now?

Right now, I’m particularly excited about a project that involves working with children; we are trying to better understand how the ability to hear pitch develops with age and experience. Difficulty hearing pitch is one of the first issues that most people with poor or corrected hearing find discouraging, so in addition to simply being an interesting basic component of audition, understanding how pitch perception develops may be useful in engineering assistive hearing devices.

How has your personal background inspired your research?

I’ve been an avid violist for over twenty years and still perform with the Chamber Music Society at MIT. When I was an undergraduate and deciding between a career as a professional musician and a career in science, I found a way to merge the two by working as a research assistant in a lab studying musical creativity. I worked in that lab for three years and was completely hooked. My musical training has definitely helped me design a few experiments!

What was your most challenging experience in Bolivia?  Most rewarding?

The most challenging aspect of our fieldwork in Bolivia is sustaining our intensity over a period of 4-5 weeks.  Every moment is precious, and the pace of work is both exhilarating and exhausting. Despite the long hours of work and travel (by canoe or by truck over very bumpy roads), it is an incredible privilege to meet with and to learn from the Tsimane’. I’ve been picking up some Tsimane’ phrases from the translators with whom we work, and can now have basic conversations with participants and make kids laugh, so that’s a lot of fun. A few children I met my first year greeted me by name when we went back this past year. That was a very special moment!

Translator Manuel Roca Moye (left) with Malinda McPherson and Josh McDermott in a fully loaded canoe. Photo: McDermott lab

What single scientific question do you hope to answer?

I’d be curious to figure out the overlaps and distinctions between how we perceive music versus speech, but I think one of the best aspects of science is that many of the important future questions haven’t been thought of yet!

Single neurons can encode distinct landmarks

by Sabbi Lall |

The organization of many neurons wired together in a complex circuit gives the brain its ability to perform powerful calculations. Work from the Harnett lab recently showed that even single neurons can process more information than previously thought, representing distinct variables at the subcellular level during behavior.

McGovern Investigator Mark Harnett and postdoc Jakob Voigts conducted an extremely delicate and intricate imaging experiment on different parts of the same neuron in the mouse retinosplenial cortex during 2-D navigation. Their set up allowed 2-photon imaging of neuronal sub-compartments during free 2-D navigation with head rotation, the latter being important to follow neural activity during naturalistic, complex behavior.

Recording computation by subcompartments in neurons.

 

In the work, published recently in Neuron, the authors used Ca2+-imaging to show that the soma in a single neuron was consistently active when mice were at particular landmarks as they navigated in an arena. The dendrites (tree-like antennas that receive input from other neurons) of exactly the same neuron were robustly active independent of the soma at distinct positions and orientations in the arena. This strongly suggests that the dendrites encode distinct information compared to their parent soma, in this case spatial variables during navigation, laying the foundation for studying sub-cellular processes during complex behaviors.

 

Shrinking CRISPR tools

by Sabbi Lall |

Before CRISPR gene-editing tools can be used to treat brain disorders, scientists must find safe ways to deliver the tools to the brain. One promising method involves harnessing viruses that are benign, and replacing non-essential genetic cargo with therapeutic CRISPR tools. But there is limited room for additional tools in a vector already stuffed with essential gear.

Squeezing all the tools that are needed to edit the genome into a single delivery vector is a challenge. Soumya Kannan is addressing this capacity problem in Feng Zhang’s lab with fellow graduate student Han Altae-Tran, by developing smaller CRISPR tools that can be more easily packaged into viral vectors for delivery. She is focused on RNA editors, members of the Cas13 family that can fix small mutations in RNA without making changes to the genome itself.

“The limitation is that RNA editors are large. At this point though, we know that editing works, we understand the mechanism by which it works, and there’s feasible packaging in AAV. We’re now trying to shrink systems such as RESCUE and REPAIR so that they fit into the packaging for delivery.”

One of many avenues the Zhang lab has taken to tool-finding in the past is to explore biodiversity for new versions of tools, and this is an approach that intrigues Soumya.

“Metagenomics projects are literally sequencing life from the Antarctic ice cores to hot sea vents. It fascinates me that the CRISPR tools of ancient organisms and those that live in extreme conditions.”

Researchers continue to search these troves of sequencing data for new tools.

 

Two CRISPR scientists on the future of gene editing

by Sabbi Lall |

As part of our Ask the Brain series, Martin Wienisch and Jonathan Wilde of the Feng lab look into the crystal ball to predict the future of CRISPR tech.

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Where will CRISPR be in five years?

Jonathan: We’ll definitely have more efficient, more precise, and safer editing tools. An immediate impact on human health may be closer than we think through more nutritious and resilient crops. Also, I think we will have more viable tools available for repairing disease-causing mutations in the brain, which is something that the field is really lacking right now.

Martin: And we can use these technologies with new disease models to help us understand brain disorders such as Huntington’s disease.

Jonathan: There are also incredible tools being discovered in nature: exotic CRISPR systems from newly discovered bacteria and viruses. We could use these to attack disease-causing bacteria.

Martin: We would then be using CRISPR systems for the reason they evolved. Also improved gene drives, CRISPR-systems that can wipe out disease-carrying organisms such as mosquitoes, could impact human health in that time frame.

What will move gene therapy forward?

Martin: A breakthrough on delivery. That’s when therapy will exponentially move forward. Therapy will be tailored to different diseases and disorders, depending on relevant cell types or the location of mutations for example.

Jonathan: Also panning biodiversity even faster: we’ve only looked at one small part of the tree of life for tools. Sequencing and computational advances can help: a future where we collect and analyze genomes in the wild using portable sequencers and laptops can only quicken the pace of new discoveries.

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

CRISPR: From toolkit to therapy

by Sabbi Lall |

Think of the human body as a community of cells with specialized roles. Each cell carries the same blueprint, an array of genes comprising the genome, but different cell types have unique functions — immune cells fight invading bacteria, while neurons transmit information.

But when something goes awry, the specialization of these cells becomes a challenge for treatment. For example, neurons lack active cell repair systems required for promising gene editing techniques like CRISPR.

Can current gene editing tools be modified to work in neurons? Can we reach neurons without impacting healthy cells nearby? McGovern Institute researchers are trying to answer these questions by developing gene editing tools and delivery systems that can target — and repair — faulty brain cells.

Expanding the toolkit

Feng Zhang with folded arms in lab
McGovern Investigator Feng Zhang in his lab.

Natural CRISPR systems help bacteria fend off would-be attackers. Our first glimpse of the impact of such systems was the use of CRISPR-Cas9 to edit human cells.

“Harnessing Cas9 was a major game-changer in the life sciences,” explains Feng Zhang, an investigator at the McGovern Institute and the James and Patricia Poitras Professor of Neuroscience at MIT. “But Cas9 is just one flavor of one kind of bacterial defense system — there is a treasure trove of natural systems that may have enormous potential, just waiting to be unlocked.”

By finding and optimizing new molecular tools, the Zhang lab and others have developed CRISPR tools that can now potentially target neurons and fix diverse mutation types, bringing gene therapy within reach.

Precise in space and time

A single letter change to a gene can be devastating. These genes may function only briefly during development, so a temporary “fix” during this window could be beneficial. For such cases, the Zhang lab and others have engineered tools that target short-lived RNAs. These molecules act as messengers, carrying information from DNA to be converted into functional factors in the cell.

“RNA editing is powerful from an ethical and safety standpoint,” explains Soumya Kannan, a graduate student in the Zhang lab working on these tools. “By targeting RNA molecules, which are only present for a short time, we can avoid permanent changes to the genetic material, and we can make these changes in any type of cell.”

Soumya Kannan in the lab
Graduate student Soumya Kannan is developing smaller CRISPR tools that can be more easily packaged into viral vectors for delivery. Photo: Caitlin Cunningham

Zhang’s team has developed twin RNA-editing tools, REPAIR and RESCUE, which can fix single RNA bases by bringing together a base editor with the CRISPR protein Cas13. These RNA-editing tools can be used in neurons because they do not rely on cellular machinery to make the targeted changes. They also have the potential to tackle a wide array of diseases in other tissue types.

CAST addition

If a gene is severely disrupted, more radical help may be needed: insertion of a normal gene. For this situation, Zhang’s lab recently identified CRISPR-associated transposases (CASTs) from cyanobacteria. CASTs combine Cas12k, which is targeted by a guide RNA to a precise genome location, with an enzyme that can insert gene-sized pieces of DNA.

“With traditional CRISPR you can make simple changes, similar to changing a few letters or words in a Word document. The new system can ‘copy and paste’ entire genes.” – Alim Ladha

Transposases were originally identified as enzymes that help rogue genes “jump” from one place to another in the genome. CAST uses a similar activity to insert entire genes self-sufficiently without help from the target cell so, like REPAIR and RESCUE, it can potentially be used in neurons.

“Our initial work was to fully characterize how this new system works, and test whether it can actually insert genes,” explains Alim Ladha, a graduate fellow in the Tan-Yang Center for Autism Research, who worked on CAST with Jonathan Strecker, a postdoctoral fellow in the Zhang lab.

The goal is now to use CAST to precisely target neurons and other specific cell types affected by disease.

Toward delivery

As the gene-editing toolbox expands, McGovern labs are working on precise delivery systems.Adeno-associated virus (AAV) is an FDA-approved virus for delivering genes, but has limited room to carry the necessary cargo — CRISPR machinery plus templates — to fix genes.

To tackle this problem, McGovern Investigators Guoping Feng and Feng Zhang are working on reducing the cargo needed for therapy. In addition, the Zhang, Gootenberg and Abudayyeh labs are working on methods to precisely deliver the therapeutic packages to neurons, such as new tissue-specific viruses that can carry bigger payloads. Finally, entirely new modalities for delivery are being explored in the effort to develop gene therapy to a point where it can be safely delivered to patients.

“Cas9 has been a very useful tool for the life sciences,” says Zhang. “And it’ll be exciting to see continued progress with the broadening toolkit and delivery systems, as we make further progress toward safe gene therapies.

Controlling attention with brain waves

Anne Trafton |

Having trouble paying attention? MIT neuroscientists may have a solution for you: Turn down your alpha brain waves. In a new study, the researchers found that people can enhance their attention by controlling their own alpha brain waves based on neurofeedback they receive as they perform a particular task.

The study found that when subjects learned to suppress alpha waves in one hemisphere of their parietal cortex, they were able to pay better attention to objects that appeared on the opposite side of their visual field. This is the first time that this cause-and-effect relationship has been seen, and it suggests that it may be possible for people to learn to improve their attention through neurofeedback.

Desimone lab study shows that people can boost attention by manipulating their own alpha brain waves with neurofeedback training.

“There’s a lot of interest in using neurofeedback to try to help people with various brain disorders and behavioral problems,” says Robert Desimone, director of MIT’s McGovern Institute for Brain Research. “It’s a completely noninvasive way of controlling and testing the role of different types of brain activity.”

It’s unknown how long these effects might last and whether this kind of control could be achieved with other types of brain waves, such as beta waves, which are linked to Parkinson’s disease. The researchers are now planning additional studies of whether this type of neurofeedback training might help people suffering from attentional or other neurological disorders.

Desimone is the senior author of the paper, which appears in Neuron on Dec. 4. McGovern Institute postdoc Yasaman Bagherzadeh is the lead author of the study. Daniel Baldauf, a former McGovern Institute research scientist, and Dimitrios Pantazis, a McGovern Institute principal research scientist, are also authors of the paper.

Alpha and attention

There are billions of neurons in the brain, and their combined electrical signals generate oscillations known as brain waves. Alpha waves, which oscillate in the frequency of 8 to 12 hertz, are believed to play a role in filtering out distracting sensory information.

Previous studies have shown a strong correlation between attention and alpha brain waves, particularly in the parietal cortex. In humans and in animal studies, a decrease in alpha waves has been linked to enhanced attention. However, it was unclear if alpha waves control attention or are just a byproduct of some other process that governs attention, Desimone says.

To test whether alpha waves actually regulate attention, the researchers designed an experiment in which people were given real-time feedback on their alpha waves as they performed a task. Subjects were asked to look at a grating pattern in the center of a screen, and told to use mental effort to increase the contrast of the pattern as they looked at it, making it more visible.

During the task, subjects were scanned using magnetoencephalography (MEG), which reveals brain activity with millisecond precision. The researchers measured alpha levels in both the left and right hemispheres of the parietal cortex and calculated the degree of asymmetry between the two levels. As the asymmetry between the two hemispheres grew, the grating pattern became more visible, offering the participants real-time feedback.

McGovern postdoc Yasaman sits in a magnetoencephalography (MEG) scanner. Photo: Justin Knight

Although subjects were not told anything about what was happening, after about 20 trials (which took about 10 minutes), they were able to increase the contrast of the pattern. The MEG results indicated they had done so by controlling the asymmetry of their alpha waves.

“After the experiment, the subjects said they knew that they were controlling the contrast, but they didn’t know how they did it,” Bagherzadeh says. “We think the basis is conditional learning — whenever you do a behavior and you receive a reward, you’re reinforcing that behavior. People usually don’t have any feedback on their brain activity, but when we provide it to them and reward them, they learn by practicing.”

Although the subjects were not consciously aware of how they were manipulating their brain waves, they were able to do it, and this success translated into enhanced attention on the opposite side of the visual field. As the subjects looked at the pattern in the center of the screen, the researchers flashed dots of light on either side of the screen. The participants had been told to ignore these flashes, but the researchers measured how their visual cortex responded to them.

One group of participants was trained to suppress alpha waves in the left side of the brain, while the other was trained to suppress the right side. In those who had reduced alpha on the left side, their visual cortex showed a larger response to flashes of light on the right side of the screen, while those with reduced alpha on the right side responded more to flashes seen on the left side.

“Alpha manipulation really was controlling people’s attention, even though they didn’t have any clear understanding of how they were doing it,” Desimone says.

Persistent effect

After the neurofeedback training session ended, the researchers asked subjects to perform two additional tasks that involve attention, and found that the enhanced attention persisted. In one experiment, subjects were asked to watch for a grating pattern, similar to what they had seen during the neurofeedback task, to appear. In some of the trials, they were told in advance to pay attention to one side of the visual field, but in others, they were not given any direction.

When the subjects were told to pay attention to one side, that instruction was the dominant factor in where they looked. But if they were not given any cue in advance, they tended to pay more attention to the side that had been favored during their neurofeedback training.

In another task, participants were asked to look at an image such as a natural outdoor scene, urban scene, or computer-generated fractal shape. By tracking subjects’ eye movements, the researchers found that people spent more time looking at the side that their alpha waves had trained them to pay attention to.

“It is promising that the effects did seem to persist afterwards,” says Desimone, though more study is needed to determine how long these effects might last.

The research was funded by the McGovern Institute.

McGovern scientists named STAT Wunderkinds

by Sabbi Lall |

McGovern researchers Sam Rodriques and Jonathan Strecker have been named to the class of 2019 STAT wunderkinds. This group of 22 researchers was selected from a national pool of hundreds of nominees, and aims to recognize trail-blazing scientists that are on the cusp of launching their careers but not yet fully independent.

“We were thrilled to receive this news,” said Robert Desimone, director of the McGovern Institute. “It’s great to see the remarkable progress being made by young scientists in McGovern labs be recognized in this way.”

Finding context

Sam Rodriques works in Ed Boyden’s lab at the McGovern Institute, where he develops new technologies that enable researchers to understand the behaviors of cells within their native spatial and temporal context.

“Psychiatric disease is a huge problem, but only a handful of first-in-class drugs for psychiatric diseases approved since the 1960s,” explains Rodriques, also affiliated with the MIT Media Lab and Broad Institute. “Coming up with novel cures is going to require new ways to generate hypotheses about the biological processes that underpin disease.”

Rodriques also works on several technologies within the Boyden lab, including preserving spatial information in molecular mapping technologies, finding ways of following neural connectivity in the brain, and Implosion Fabrication, or “Imp Fab.” This nanofabrication technology allows objects to be evenly shrunk to the nanoscale and has a wide range of potential applications, including building new miniature devices for examining neural function.

“I was very surprised, not expecting it at all!” explains Rodriques when asked about becoming a STAT Wunderkind, “I’m sure that all of the hundreds of applicants are very accomplished scientists, and so to be chosen like this is really an honor.”

New tools for gene editing

Jonathan Strecker is currently a postdoc working in Feng Zhang’s lab, and associated with both the McGovern Institute and Broad Institute. While CRISPR-Cas9 continues to have a profound effect and huge potential for research and biomedical, and agricultural applications, the ability to move entire genes into specific target locations remained out reach.

“Genome editing with CRISPR-Cas enzymes typically involves cutting and disrupting genes, or making certain base edits,” explains Strecker, “however, inserting large pieces of DNA is still hard to accomplish.”

As a postdoctoral researcher in the lab of CRISPR pioneer Feng Zhang, Strecker led research that showed how large sequences could be inserted into a genome at a given location.

“Nature often has interesting solutions to these problems and we were fortunate to identify and characterize a remarkable CRISPR system from cyanobacteria that functions as a programmable transposase.”

Importantly, the system he discovered, called CAST, doesn’t require cellular machinery to insert DNA. This is important as it means that CAST could work in many cell types, including those that have stopped dividing such as neurons, something that is being pursued.

By finding new sources of inspiration, be it nature or art, both Rodriques and Strecker join a stellar line up of young investigators being recognized for creativity and innovation.

 

MIT appoints 14 faculty members to named professorships

Anne Trafton |

The School of Science has announced that 14 of its faculty members have been appointed to named professorships. The faculty members selected for these positions receive additional support to pursue their research and develop their careers.

Riccardo Comin is an assistant professor in the Department of Physics. He has been named a Class of 1947 Career Development Professor. This three-year professorship is granted in recognition of the recipient’s outstanding work in both research and teaching. Comin is interested in condensed matter physics. He uses experimental methods to synthesize new materials, as well as analysis through spectroscopy and scattering to investigate solid state physics. Specifically, the Comin lab attempts to discover and characterize electronic phases of quantum materials. Recently, his lab, in collaboration with colleagues, discovered that weaving a conductive material into a particular pattern known as the “kagome” pattern can result in quantum behavior when electricity is passed through.

Joseph Davis, assistant professor in the Department of Biology, has been named a Whitehead Career Development Professor. He looks at how cells build and deconstruct complex molecular machinery. The work of his lab group relies on biochemistry, biophysics, and structural approaches that include spectrometry and microscopy. A current project investigates the formation of the ribosome, an essential component in all cells. His work has implications for metabolic engineering, drug delivery, and materials science.

Lawrence Guth is now the Claude E. Shannon (1940) Professor of Mathematics. Guth explores harmonic analysis and combinatorics, and he is also interested in metric geometry and identifying connections between geometric inequalities and topology. The subject of metric geometry revolves around being able to estimate measurements, including length, area, volume and distance, and combinatorial geometry is essentially the estimation of the intersection of patters in simple shapes, including lines and circles.

Michael Halassa, an assistant professor in the Department of Brain and Cognitive Sciences, will hold the three-year Class of 1958 Career Development Professorship. His area of interest is brain circuitry. By investigating the networks and connections in the brain, he hopes to understand how they operate — and identify any ways in which they might deviate from normal operations, causing neurological and psychiatric disorders. Several publications from his lab discuss improvements in the treatment of the deleterious symptoms of autism spectrum disorder and schizophrenia, and his latest news provides insights on how the brain filters out distractions, particularly noise. Halassa is an associate investigator at the McGovern Institute for Brain Research and an affiliate member of the Picower Institute for Learning and Memory.

Sebastian Lourido, an assistant professor and the new Latham Family Career Development Professor in the Department of Biology for the next three years, works on treatments for infectious disease by learning about parasitic vulnerabilities. Focusing on human pathogens, Lourido and his lab are interested in what allows parasites to be so widespread and deadly, looking on a molecular level. This includes exploring how calcium regulates eukaryotic cells, which, in turn, affect processes such as muscle contraction and membrane repair, in addition to kinase responses.

Brent Minchew is named a Cecil and Ida Green Career Development Professor for a three-year term. Minchew, a faculty member in the Department of Earth, Atmospheric and Planetary Sciences, studies glaciers using remote sensing methods, such as interferometric synthetic aperture radar. His research into glaciers, including their mechanics, rheology, and interactions with their surrounding environment, extends as far as observing their responses to climate change. His group recently determined that Antarctica, in a worst-case scenario climate projection, would not contribute as much as predicted to rising sea level.

Elly Nedivi, a professor in the departments of Brain and Cognitive Sciences and Biology, has been named the inaugural William R. (1964) And Linda R. Young Professor. She works on brain plasticity, defined as the brain’s ability to adapt with experience, by identifying genes that play a role in plasticity and their neuronal and synaptic functions. In one of her lab’s recent publications, they suggest that variants of a particular gene may undermine expression or production of a protein, increasing the risk of bipolar disorder. In addition, she collaborates with others at MIT to develop new microscopy tools that allow better analysis of brain connectivity. Nedivi is also a member of the Picower Institute for Learning and Memory.

Andrei Negut has been named a Class of 1947 Career Development Professor for a three-year term. Negut, a member of the Department of Mathematics, fixates on problems in geometric representation theory. This topic requires investigation within algebraic geometry and representation theory simultaneously, with implications for mathematical physics, symplectic geometry, combinatorics and probability theory.

Matĕj Peč, the Victor P. Starr Career Development Professor in the Department of Earth, Atmospheric and Planetary Science until 2021, studies how the movement of the Earth’s tectonic plates affects rocks, mechanically and microstructurally. To investigate such a large-scale topic, he utilizes high-pressure, high-temperature experiments in a lab to simulate the driving forces associated with plate motion, and compares results with natural observations and theoretical modeling. His lab has identified a particular boundary beneath the Earth’s crust where rock properties shift from brittle, like peanut brittle, to viscous, like honey, and determined how that layer accommodates building strain between the two. In his investigations, he also considers the effect on melt generation miles underground.

Kerstin Perez has been named the three-year Class of 1948 Career Development Professor in the Department of Physics. Her research interest is dark matter. She uses novel analytical tools, such as those affixed on a balloon-borne instrument that can carry out processes similar to that of a particle collider (like the Large Hadron Collider) to detect new particle interactions in space with the help of cosmic rays. In another research project, Perez uses a satellite telescope array on Earth to search for X-ray signatures of mysterious particles. Her work requires heavy involvement with collaborative observatories, instruments, and telescopes. Perez is affiliated with the Kavli Institute for Astrophysics and Space Research.

Bjorn Poonen, named a Distinguished Professor of Science in the Department of Mathematics, studies number theory and algebraic geometry. He, his colleagues, and his lab members generate algorithms that can solve polynomial equations with the particular requirement that the solutions be rational numbers. These types of problems can be useful in encoding data. He also helps to determine what is undeterminable, that is exploring the limits of computing.

Daniel Suess, named a Class of 1948 Career Development Professor in the Department of Chemistry, uses molecular chemistry to explain global biogeochemical cycles. In the fields of inorganic and biological chemistry, Suess and his lab look into understanding complex and challenging reactions and clustering of particular chemical elements and their catalysts. Most notably, these reactions include those that are essential to solar fuels. Suess’s efforts to investigate both biological and synthetic systems have broad aims of both improving human health and decreasing environmental impacts.

Alison Wendlandt is the new holder of the five-year Cecil and Ida Green Career Development Professorship. In the Department of Chemistry, the Wendlandt research group focuses on physical organic chemistry and organic and organometallic synthesis to develop reaction catalysts. Her team fixates on designing new catalysts, identifying processes to which these catalysts can be applied, and determining principles that can expand preexisting reactions. Her team’s efforts delve into the fields of synthetic organic chemistry, reaction kinetics, and mechanics.

Julien de Wit, a Department of Earth, Atmospheric and Planetary Sciences assistant professor, has been named a Class of 1954 Career Development Professor. He combines math and science to answer questions about big-picture planetary questions. Using data science, de Wit develops new analytical techniques for mapping exoplanetary atmospheres, studies planet-star interactions of planetary systems, and determines atmospheric and planetary properties of exoplanets from spectroscopic information. He is a member of the scientific team involved in the Search for habitable Planets EClipsing ULtra-cOOl Stars (SPECULOOS) TRANsiting Planets and Planetesimals Small Telescope (TRAPPIST), made up of an international collection of observatories. He is affiliated with the Kavli Institute.

Drug combination reverses hypersensitivity to noise

Anne Trafton |

People with autism often experience hypersensitivity to noise and other sensory input. MIT neuroscientists have now identified two brain circuits that help tune out distracting sensory information, and they have found a way to reverse noise hypersensitivity in mice by boosting the activity of those circuits.

One of the circuits the researchers identified is involved in filtering noise, while the other exerts top-down control by allowing the brain to switch its attention between different sensory inputs.

The researchers showed that restoring the function of both circuits worked much better than treating either circuit alone. This demonstrates the benefits of mapping and targeting multiple circuits involved in neurological disorders, says Michael Halassa, an assistant professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research.

“We think this work has the potential to transform how we think about neurological and psychiatric disorders, [so that we see them] as a combination of circuit deficits,” says Halassa, the senior author of the study. “The way we should approach these brain disorders is to map, to the best of our ability, what combination of deficits are there, and then go after that combination.”

MIT postdoc Miho Nakajima and research scientist L. Ian Schmitt are the lead authors of the paper, which appears in Neuron on Oct. 21. Guoping Feng, the James W. and Patricia Poitras Professor of Neuroscience and a member of the McGovern Institute, is also an author of the paper.

Hypersensitivity

Many gene variants have been linked with autism, but most patients have very few, if any, of those variants. One of those genes is ptchd1, which is mutated in about 1 percent of people with autism. In a 2016 study, Halassa and Feng found that during development this gene is primarily expressed in a part of the thalamus called the thalamic reticular nucleus (TRN).

That study revealed that neurons of the TRN help the brain to adjust to changes in sensory input, such as noise level or brightness. In mice with ptchd1 missing, TRN neurons fire too fast, and they can’t adjust when noise levels change. This prevents the TRN from performing its usual sensory filtering function, Halassa says.

“Neurons that are there to filter out noise, or adjust the overall level of activity, are not adapting. Without the ability to fine-tune the overall level of activity, you can get overwhelmed very easily,” he says.

In the 2016 study, the researchers also found that they could restore some of the mice’s noise filtering ability by treating them with a drug called EBIO that activates neurons’ potassium channels. EBIO has harmful cardiac side effects so likely could not be used in human patients, but other drugs that boost TRN activity may have a similar beneficial effect on hypersensitivity, Halassa says.

In the new Neuron paper, the researchers delved more deeply into the effects of ptchd1, which is also expressed in the prefrontal cortex. To explore whether the prefrontal cortex might play a role in the animals’ hypersensitivity, the researchers used a task in which mice have to distinguish between three different tones, presented with varying amounts of background noise.

Normal mice can learn to use a cue that alerts them whenever the noise level is going to be higher, improving their overall performance on the task. A similar phenomenon is seen in humans, who can adjust better to noisier environments when they have some advance warning, Halassa says. However, mice with the ptchd1 mutation were unable to use these cues to improve their performance, even when their TRN deficit was treated with EBIO.

This suggested that another brain circuit must be playing a role in the animals’ ability to filter out distracting noise. To test the possibility that this circuit is located in the prefrontal cortex, the researchers recorded from neurons in that region while mice lacking ptch1 performed the task. They found that neuronal activity died out much faster in these mice than in the prefrontal cortex of normal mice. That led the researchers to test another drug, known as modafinil, which is FDA-approved to treat narcolepsy and is sometimes prescribed to improve memory and attention.

The researchers found that when they treated mice missing ptchd1 with both modafinil and EBIO, their hypersensitivity disappeared, and their performance on the task was the same as that of normal mice.

Targeting circuits

This successful reversal of symptoms suggests that the mice missing ptchd1 experience a combination of circuit deficits that each contribute differently to noise hypersensitivity. One circuit filters noise, while the other helps to control noise filtering based on external cues. Ptch1 mutations affect both circuits, in different ways that can be treated with different drugs.

Both of those circuits could also be affected by other genetic mutations that have been linked to autism and other neurological disorders, Halassa says. Targeting those circuits, rather than specific genetic mutations, may offer a more effective way to treat such disorders, he says.

“These circuits are important for moving things around the brain — sensory information, cognitive information, working memory,” he says. “We’re trying to reverse-engineer circuit operations in the service of figuring out what to do about a real human disease.”

He now plans to study circuit-level disturbances that arise in schizophrenia. That disorder affects circuits involving cognitive processes such as inference — the ability to draw conclusions from available information.

The research was funded by the Simons Center for the Social Brain at MIT, the Stanley Center for Psychiatric Research at the Broad Institute, the McGovern Institute for Brain Research at MIT, the Pew Foundation, the Human Frontiers Science Program, the National Institutes of Health, the James and Patricia Poitras Center for Psychiatric Disorders Research at MIT, a Japan Society for the Promotion of Science Fellowship, and a National Alliance for the Research of Schizophrenia and Depression Young Investigator Award.