Research Area: Systems Neuroscience

​neural circuits, attention, brain disorders, executive function, sensory processing, behavior, timing, plasticity, learning, memory, emotion, habits

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.

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.

Controlling our internal world

by Sabbi Lall |

Olympic skaters can launch, perform multiple aerial turns, and land gracefully, anticipating imperfections and reacting quickly to correct course. To make such elegant movements, the brain must have an internal model of the body to control, predict, and make almost instantaneous adjustments to motor commands. So-called “internal models” are a fundamental concept in engineering and have long been suggested to underlie control of movement by the brain, but what about processes that occur in the absence of movement, such as contemplation, anticipation, planning?

Using a novel combination of task design, data analysis, and modeling, MIT neuroscientist Mehrdad Jazayeri and colleagues now provide compelling evidence that the core elements of an internal model also control purely mental processes in a study published in Nature Neuroscience.

“During my thesis I realized that I’m interested, not so much in how our senses react to sensory inputs, but instead in how my internal model of the world helps me make sense of those inputs,”says Jazayeri, the Robert A. Swanson Career Development Professor of Life Sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

Indeed, understanding the building blocks exerting control of such mental processes could help to paint a better picture of disruptions in mental disorders, such as schizophrenia.

Internal models for mental processes

Scientists working on the motor system have long theorized that the brain overcomes noisy and slow signals using an accurate internal model of the body. This internal model serves three critical functions: it provides motor to control movement, simulates upcoming movement to overcome delays, and uses feedback to make real-time adjustments.

“The framework that we currently use to think about how the brain controls our actions is one that we have borrowed from robotics: we use controllers, simulators, and sensory measurements to control machines and train operators,” explains Reza Shadmehr, a professor at the Johns Hopkins School of Medicine who was not involved with the study. “That framework has largely influenced how we imagine our brain controlling our movements.”

Jazazyeri and colleagues wondered whether the same framework might explain the control principles governing mental states in the absence of any movement.

“When we’re simply sitting, thoughts and images run through our heads and, fundamental to intellect, we can control them,” explains lead author Seth Egger, a former postdoctoral associate in the Jazayeri lab and now at Duke University.

“We wanted to find out what’s happening between our ears when we are engaged in thinking,” says Egger.

Imagine, for example, a sign language interpreter keeping up with a fast speaker. To track speech accurately, the translator continuously anticipates where the speech is going, rapidly adjusting when the actual words deviate from the prediction. The interpreter could be using an internal model to anticipate upcoming words, and use feedback to make adjustments on the fly.

1-2-3…Go

Hypothesizing about how the components of an internal model function in scenarios such as translation is one thing. Cleanly measuring and proving the existence of these elements is much more complicated as the activity of the controller, simulator, and feedback are intertwined. To tackle this problem, Jazayeri and colleagues devised a clever task with primate models in which the controller, simulator, and feedback act at distinct times.

In this task, called “1-2-3-Go,” the animal sees three consecutive flashes (1, 2, and 3) that form a regular beat, and learns to make an eye movement (Go) when they anticipate the 4th flash should occur. During the task, researchers measured neural activity in a region of the frontal cortex they had previously linked to the timing of movement.

Jazayeri and colleagues had clear predictions about when the controller would act (between the third flash and “Go”) and when feedback would be engaged (with each flash of light). The key surprise came when researchers saw evidence for the simulator anticipating the third flash. This unexpected neural activity has dynamics that resemble the controller, but was not associated with a response. In other words, the researchers uncovered a covert plan that functions as the simulator, thus uncovering all three elements of an internal model for a mental process, the planning and anticipation of “Go” in the “1-2-3-Go” sequence.

“Jazayeri’s work is important because it demonstrates how to study mental simulation in animals,” explains Shadmehr, “and where in the brain that simulation is taking place.”

Having found how and where to measure an internal model in action, Jazayeri and colleagues now plan to ask whether these control strategies can explain how primates effortlessly generalize their knowledge from one behavioral context to another. For example, how does an interpreter rapidly adjust when someone with widely different speech habits takes the podium? This line of investigation promises to shed light on high-level mental capacities of the primate brain that simpler animals seem to lack, that go awry in mental disorders, and that designers of artificial intelligence systems so fondly seek.

Brain region linked to altered social interactions in autism model

by Sabbi Lall |

Although psychiatric disorders can be linked to particular genes, the brain regions and mechanisms underlying particular disorders are not well-understood. Mutations or deletions of the SHANK3 gene are strongly associated with autism spectrum disorder (ASD) and a related rare disorder called Phelan-McDermid syndrome. Mice with SHANK3 mutations also display some of the traits associated with autism, including avoidance of social interactions, but the brain regions responsible for this behavior have not been identified.

A new study by neuroscientists at MIT and colleagues in China provides clues to the neural circuits underlying social deficits associated with ASD. The paper, published in Nature Neuroscience, found that structural and functional impairments in the anterior cingulate cortex (ACC) of SHANK3 mutant mice are linked to altered social interactions.

“Neurobiological mechanisms of social deficits are very complex and involve many brain regions, even in a mouse model,” explains Guoping Feng, the James W. and Patricia T. Poitras Professor at MIT and one of the senior authors of the study. “These findings add another piece of the puzzle to mapping the neural circuits responsible for this social deficit in ASD models.”

The Nature Neuroscience paper is the result of a collaboration between Feng, who is also an investigator at MIT’s McGovern Institute and a senior scientist in the Broad Institute’s Stanley Center for Psychiatric Research, and Wenting Wang and Shengxi Wu at the Fourth Military Medical University, Xi’an, China.

A number of brain regions have been implicated in social interactions, including the prefrontal cortex (PFC) and its projections to brain regions including the nucleus accumbens and habenula, but these studies failed to definitively link the PFC to altered social interactions seen in SHANK3 knockout mice.

In the new study, the authors instead focused on the ACC, a brain region noted for its role in social functions in humans and animal models. The ACC is also known to play a role in fundamental cognitive processes, including cost-benefit calculation, motivation, and decision making.

In mice lacking SHANK3, the researchers found structural and functional disruptions at the synapses, or connections, between excitatory neurons in the ACC. The researchers went on to show that the loss of SHANK3 in excitatory ACC neurons alone was enough to disrupt communication between these neurons and led to unusually reduced activity of these neurons during behavioral tasks reflecting social interaction.

Having implicated these ACC neurons in social preferences and interactions in SHANK3 knockout mice, the authors then tested whether activating these same neurons could rescue these behaviors. Using optogenetics and specfic drugs, the researchers activated the ACC neurons and found improved social behavior in the SHANK3 mutant mice.

“Next, we are planning to explore brain regions downstream of the ACC that modulate social behavior in normal mice and models of autism,” explains Wenting Wang, co-corresponding author on the study. “This will help us to better understand the neural mechanisms of social behavior, as well as social deficits in neurodevelopmental disorders.”

Previous clinical studies reported that anatomical structures in the ACC were altered and/or dysfunctional in people with ASD, an initial indication that the findings from SHANK3 mice may also hold true in these individuals.

The research was funded, in part, by the Natural Science Foundation of China. Guoping Feng was supported by NIMH grant no. MH097104, the  Poitras Center for Psychiatric Disorders Research at the McGovern Institute at MIT, and the Hock E. Tan and K. Lisa Yang Center for Autism Research at the McGovern Institute at MIT.

Ed Boyden receives 2019 Warren Alpert Prize

by Sabbi Lall |

The 2019 Warren Alpert Foundation Prize has been awarded to four scientists, including Ed Boyden, for pioneering work that launched the field of optogenetics, a technique that uses light-sensitive channels and pumps to control the activity of neurons in the brain with a flick of a switch. He receives the prize alongside Karl Deisseroth, Peter Hegemann, and Gero Miesenböck, as outlined by The Warren Alpert Foundation in their announcement.

Harnessing light and genetics, the approach illuminates and modulates the activity of neurons, enables study of brain function and behavior, and helps reveal activity patterns that can overcome brain diseases.

Boyden’s work was key to envisioning and developing optogenetics, now a core method in neuroscience. The method allows brain circuits linked to complex behavioral processes, such as those involved in decision-making, feeding, and sleep, to be unraveled in genetic models. It is also helping to elucidate the mechanisms underlying neuropsychiatric disorders, and has the potential to inspire new strategies to overcome brain disorders.

“It is truly an honor to be included among the extremely distinguished list of winners of the Alpert Award,” says Boyden, the Y. Eva Tan Professor in Neurotechnology at the McGovern Institute, MIT. “To me personally, it is exciting to see the relatively new field of neurotechnology recognized. The brain implements our thoughts and feelings. It makes us who we are. This mysteries and challenge requires new technologies to make the brain understandable and repairable. It is a great honor that our technology of optogenetics is being thus recognized.”

While they were students, Boyden, and fellow awardee Karl Deisseroth, brainstormed about how microbial opsins could be used to mediate optical control of neural activity. In mid-2004, the pair collaborated to show that microbial opsins can be used to optically control neural activity. Upon launching his lab at MIT, Boyden’s team developed the first optogenetic silencing tool, the first effective optogenetic silencing in live mammals, noninvasive optogenetic silencing, and single-cell optogenetic control.

“The discoveries made by this year’s four honorees have fundamentally changed the landscape of neuroscience,” said George Q. Daley, dean of Harvard Medical School. “Their work has enabled scientists to see, understand and manipulate neurons, providing the foundation for understanding the ultimate enigma—the human brain.”

Beyond optogenetics, Boyden has pioneered transformative technologies that image, record, and manipulate complex systems, including expansion microscopy, robotic patch clamping, and even shrinking objects to the nanoscale. He was elected this year to the ranks of the National Academy of Sciences, and selected as an HHMI Investigator. Boyden has received numerous awards for this work, including the 2018 Gairdner International Prize and the 2016 Breakthrough Prize in Life Sciences.

The Warren Alpert Foundation, in association with Harvard Medical School, honors scientists whose work has improved the understanding, prevention, treatment or cure of human disease. Prize recipients are selected by the foundation’s scientific advisory board, which is composed of distinguished biomedical scientists and chaired by the dean of Harvard Medical School. The honorees will share a $500,000 prize and will be recognized at a daylong symposium on Oct. 3 at Harvard Medical School.

Ed Boyden holds the titles of Investigator, McGovern Institute; Y. Eva Tan Professor in Neurotechnology at MIT; Leader, Synthetic Neurobiology Group, Media Lab; Associate Professor, Biological Engineering, Brain and Cognitive Sciences, Media Lab; Co-Director, MIT Center for Neurobiological Engineering; Member, MIT Center for Environmental Health Sciences, Computational and Systems Biology Initiative, and Koch Institute.

How expectation influences perception

by Anne Trafton |

For decades, research has shown that our perception of the world is influenced by our expectations. These expectations, also called “prior beliefs,” help us make sense of what we are perceiving in the present, based on similar past experiences. Consider, for instance, how a shadow on a patient’s X-ray image, easily missed by a less experienced intern, jumps out at a seasoned physician. The physician’s prior experience helps her arrive at the most probable interpretation of a weak signal.

The process of combining prior knowledge with uncertain evidence is known as Bayesian integration and is believed to widely impact our perceptions, thoughts, and actions. Now, MIT neuroscientists have discovered distinctive brain signals that encode these prior beliefs. They have also found how the brain uses these signals to make judicious decisions in the face of uncertainty.

“How these beliefs come to influence brain activity and bias our perceptions was the question we wanted to answer,” says Mehrdad Jazayeri, the Robert A. Swanson Career Development Professor of Life Sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

The researchers trained animals to perform a timing task in which they had to reproduce different time intervals. Performing this task is challenging because our sense of time is imperfect and can go too fast or too slow. However, when intervals are consistently within a fixed range, the best strategy is to bias responses toward the middle of the range. This is exactly what animals did. Moreover, recording from neurons in the frontal cortex revealed a simple mechanism for Bayesian integration: Prior experience warped the representation of time in the brain so that patterns of neural activity associated with different intervals were biased toward those that were within the expected range.

MIT postdoc Hansem Sohn, former postdoc Devika Narain, and graduate student Nicolas Meirhaeghe are the lead authors of the study, which appears in the July 15 issue of Neuron.

Ready, set, go

Statisticians have known for centuries that Bayesian integration is the optimal strategy for handling uncertain information. When we are uncertain about something, we automatically rely on our prior experiences to optimize behavior.

“If you can’t quite tell what something is, but from your prior experience you have some expectation of what it ought to be, then you will use that information to guide your judgment,” Jazayeri says. “We do this all the time.”

In this new study, Jazayeri and his team wanted to understand how the brain encodes prior beliefs, and put those beliefs to use in the control of behavior. To that end, the researchers trained animals to reproduce a time interval, using a task called “ready-set-go.” In this task, animals measure the time between two flashes of light (“ready” and “set”) and then generate a “go” signal by making a delayed response after the same amount of time has elapsed.

They trained the animals to perform this task in two contexts. In the “Short” scenario, intervals varied between 480 and 800 milliseconds, and in the “Long” context, intervals were between 800 and 1,200 milliseconds. At the beginning of the task, the animals were given the information about the context (via a visual cue), and therefore knew to expect intervals from either the shorter or longer range.

Jazayeri had previously shown that humans performing this task tend to bias their responses toward the middle of the range. Here, they found that animals do the same. For example, if animals believed the interval would be short, and were given an interval of 800 milliseconds, the interval they produced was a little shorter than 800 milliseconds. Conversely, if they believed it would be longer, and were given the same 800-millisecond interval, they produced an interval a bit longer than 800 milliseconds.

“Trials that were identical in almost every possible way, except the animal’s belief led to different behaviors,” Jazayeri says. “That was compelling experimental evidence that the animal is relying on its own belief.”

Once they had established that the animals relied on their prior beliefs, the researchers set out to find how the brain encodes prior beliefs to guide behavior. They recorded activity from about 1,400 neurons in a region of the frontal cortex, which they have previously shown is involved in timing.

During the “ready-set” epoch, the activity profile of each neuron evolved in its own way, and about 60 percent of the neurons had different activity patterns depending on the context (Short versus Long). To make sense of these signals, the researchers analyzed the evolution of neural activity across the entire population over time, and found that prior beliefs bias behavioral responses by warping the neural representation of time toward the middle of the expected range.

“We have never seen such a concrete example of how the brain uses prior experience to modify the neural dynamics by which it generates sequences of neural activities, to correct for its own imprecision. This is the unique strength of this paper: bringing together perception, neural dynamics, and Bayesian computation into a coherent framework, supported by both theory and measurements of behavior and neural activities,” says Mate Lengyel, a professor of computational neuroscience at Cambridge University, who was not involved in the study.

Embedded knowledge

Researchers believe that prior experiences change the strength of connections between neurons. The strength of these connections, also known as synapses, determines how neurons act upon one another and constrains the patterns of activity that a network of interconnected neurons can generate. The finding that prior experiences warp the patterns of neural activity provides a window onto how experience alters synaptic connections. “The brain seems to embed prior experiences into synaptic connections so that patterns of brain activity are appropriately biased,” Jazayeri says.

As an independent test of these ideas, the researchers developed a computer model consisting of a network of neurons that could perform the same ready-set-go task. Using techniques borrowed from machine learning, they were able to modify the synaptic connections and create a model that behaved like the animals.

These models are extremely valuable as they provide a substrate for the detailed analysis of the underlying mechanisms, a procedure that is known as “reverse-engineering.” Remarkably, reverse-engineering the model revealed that it solved the task the same way the monkeys’ brain did. The model also had a warped representation of time according to prior experience.

The researchers used the computer model to further dissect the underlying mechanisms using perturbation experiments that are currently impossible to do in the brain. Using this approach, they were able to show that unwarping the neural representations removes the bias in the behavior. This important finding validated the critical role of warping in Bayesian integration of prior knowledge.

The researchers now plan to study how the brain builds up and slowly fine-tunes the synaptic connections that encode prior beliefs as an animal is learning to perform the timing task.

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

Mark Harnett receives a 2019 McKnight Scholar Award

Anne Trafton |

McGovern Institute investigator Mark Harnett is one of six young researchers selected to receive a prestigious 2019 McKnight Scholar Award. The award supports his research “studying how dendrites, the antenna-like input structures of neurons, contribute to computation in neural networks.”

Harnett examines the biophysical properties of single neurons, ultimately aiming to understand how these relate to the complex computations that underlie behavior. His lab was the first to examine the biophysical properties of human dendrites. The Harnett lab found that human neurons have distinct properties, including increased dendritic compartmentalization that could allow more complex computations within single neurons. His lab recently discovered that such dendritic computations are not rare, or confined to specific behaviors, but are a widespread and general feature of neuronal activity.

“As a young investigator, it is hard to prioritize so many exciting directions and ideas,” explains Harnett. “I really want to thank the McKnight Foundation, both for the support, but also for the hard work the award committee puts into carefully thinking about and giving feedback on proposals. It means a lot to get this type of endorsement from a seriously committed and distinguished committee, and their support gives even stronger impetus to pursue this research direction.”

The McKnight Foundation has supported neuroscience research since 1977, and provides three prominent awards, with the Scholar award aimed at supporting young scientists, and drawing applications from the strongest young neuroscience faculty across the US. William L. McKnight (1887-1979) was an early leader of the 3M Company and had a personal interest in memory and brain diseases. The McKnight Foundation was established with this focus in mind, and the Scholar Award provides $75,000 per year for three years to support cutting edge neuroscience research.

 

McGovern neuroscientists develop a new model for autism

Anne Trafton |

Using the genome-editing system CRISPR, researchers at MIT and in China have engineered macaque monkeys to express a gene mutation linked to autism and other neurodevelopmental disorders in humans. These monkeys show some behavioral traits and brain connectivity patterns similar to those seen in humans with these conditions.

Mouse studies of autism and other neurodevelopmental disorders have yielded drug candidates that have been tested in clinical trials, but none of them have succeeded. Many pharmaceutical companies have given up on testing such drugs because of the poor track record so far.

The new type of model, however, could help scientists to develop better treatment options for some neurodevelopmental disorders, says Guoping Feng, who is the James W. and Patricia Poitras Professor of Neuroscience, a member of MIT’s McGovern Institute for Brain Research, and one of the senior authors of the study.

“Our goal is to generate a model to help us better understand the neural biological mechanism of autism, and ultimately to discover treatment options that will be much more translatable to humans,” says Feng, who is also an institute member of the Broad Institute of MIT and Harvard and a senior scientist in the Broad’s Stanley Center for Psychiatric Research.

“We urgently need new treatment options for autism spectrum disorder, and treatments developed in mice have so far been disappointing. While the mouse research remains very important, we believe that primate genetic models will help us to develop better medicines and possibly even gene therapies for some severe forms of autism,” says Robert Desimone, the director of MIT’s McGovern Institute for Brain Research, the Doris and Don Berkey Professor of Neuroscience, and an author of the paper.

Huihui Zhou of the Shenzhen Institutes of Advanced Technology, Andy Peng Xiang of Sun Yat-Sen University, and Shihua Yang of South China Agricultural University are also senior authors of the study, which appears in the June 12 online edition of Nature. The paper’s lead authors are former MIT postdoc Yang Zhou, MIT research scientist Jitendra Sharma, Broad Institute group leader Rogier Landman, and Qiong Ke of Sun Yat-Sen University. The research team also includes Mriganka Sur, the Paul and Lilah E. Newton Professor in the Department of Brain and Cognitive Sciences and a member of MIT’s Picower Institute for Learning and Memory.

Gene variants

Scientists have identified hundreds of genetic variants associated with autism spectrum disorder, many of which individually confer only a small degree of risk. In this study, the researchers focused on one gene with a strong association, known as SHANK3. In addition to its link with autism, mutations or deletions of SHANK3 can also cause a related rare disorder called Phelan-McDermid Syndrome, whose most common characteristics include intellectual disability, impaired speech and sleep, and repetitive behaviors. The majority of these individuals are also diagnosed with autism spectrum disorder, as many of the symptoms overlap.

The protein encoded by SHANK3 is found in synapses — the junctions between brain cells that allow them to communicate with each other. It is particularly active in a part of the brain called the striatum, which is involved in motor planning, motivation, and habitual behavior. Feng and his colleagues have previously studied mice with Shank3 mutations and found that they show some of the traits associated with autism, including avoidance of social interaction and obsessive, repetitive behavior.

Although mouse studies can provide a great deal of information on the molecular underpinnings of disease, there are drawbacks to using them to study neurodevelopmental disorders, Feng says. In particular, mice lack the highly developed prefrontal cortex that is the seat of many uniquely primate traits, such as making decisions, sustaining focused attention, and interpreting social cues, which are often affected by brain disorders.

The recent development of the CRISPR genome-editing technique offered a way to engineer gene variants into macaque monkeys, which has previously been very difficult to do. CRISPR consists of a DNA-cutting enzyme called Cas9 and a short RNA sequence that guides the enzyme to a specific area of the genome. It can be used to disrupt genes or to introduce new genetic sequences at a particular location.

Members of the research team based in China, where primate reproductive technology is much more advanced than in the United States, injected the CRISPR components into fertilized macaque eggs, producing embryos that carried the Shank3 mutation.

Researchers at MIT, where much of the data was analyzed, found that the macaques with Shank3 mutations showed behavioral patterns similar to those seen in humans with the mutated gene. They tended to wake up frequently during the night, and they showed repetitive behaviors. They also engaged in fewer social interactions than other macaques.

Magnetic resonance imaging (MRI) scans also revealed similar patterns to humans with autism spectrum disorder. Neurons showed reduced functional connectivity in the striatum as well as the thalamus, which relays sensory and motor signals and is also involved in sleep regulation. Meanwhile, connectivity was strengthened in other regions, including the sensory cortex.

Michael Platt, a professor of neuroscience and psychology at the University of Pennsylvania, says the macaque models should help to overcome some of the limitations of studying neurological disorders in mice, whose behavioral symptoms and underlying neurobiology are often different from those seen in humans.

“Because the macaque model shows a much more complete recapitulation of the human behavioral phenotype, I think we should stand a much greater chance of identifying the degree to which any particular therapy, whether it’s a drug or any other intervention, addresses the core symptoms,” says Platt, who was not involved in the study.

Drug development

Within the next year, the researchers hope to begin testing treatments that may affect autism-related symptoms. They also hope to identify biomarkers, such as the distinctive functional brain connectivity patterns seen in MRI scans, that would help them to evaluate whether drug treatments are having an effect.

A similar approach could also be useful for studying other types of neurological disorders caused by well-characterized genetic mutations, such as Rett Syndrome and Fragile X Syndrome. Fragile X is the most common inherited form of intellectual disability in the world, affecting about 1 in 4,000 males and 1 in 8,000 females. Rett Syndrome, which is more rare and almost exclusively affects girls, produces severe impairments in language and motor skills and can also cause seizures and breathing problems.

“Given the limitations of mouse models, patients really need this kind of advance to bring them hope,” Feng says. “We don’t know whether this will succeed in developing treatments, but we will see in the next few years how this can help us to translate some of the findings from the lab to the clinic.”

The research was funded, in part, by the Shenzhen Overseas Innovation Team Project, the Guangdong Innovative and Entrepreneurial Research Team Program, the National Key R&D Program of China, the External Cooperation Program of the Chinese Academy of Sciences, the Patrick J. McGovern Foundation, the National Natural Science Foundation of China, the Shenzhen Science, Technology Commission, the James and Patricia Poitras Center for Psychiatric Disorders Research at the McGovern Institute at MIT, the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard, and the Hock E. Tan and K. Lisa Yang Center for Autism Research at the McGovern Institute at MIT. The research facilities in China where the primate work was conducted are accredited by AAALAC International, a private, nonprofit organization that promotes the humane treatment of animals in science through voluntary accreditation and assessment programs.

How we tune out distractions

Anne Trafton |

Imagine trying to focus on a friend’s voice at a noisy party, or blocking out the phone conversation of the person sitting next to you on the bus while you try to read. Both of these tasks require your brain to somehow suppress the distracting signal so you can focus on your chosen input.

MIT neuroscientists have now identified a brain circuit that helps us to do just that. The circuit they identified, which is controlled by the prefrontal cortex, filters out unwanted background noise or other distracting sensory stimuli. When this circuit is engaged, the prefrontal cortex selectively suppresses sensory input as it flows into the thalamus, the site where most sensory information enters the brain.

“This is a fundamental operation that cleans up all the signals that come in, in a goal-directed way,” says Michael Halassa, an assistant professor of brain and cognitive sciences, a member of MIT’s McGovern Institute for Brain Research, and the senior author of the study.

The researchers are now exploring whether impairments of this circuit may be involved in the hypersensitivity to noise and other stimuli that is often seen in people with autism.

Miho Nakajima, an MIT postdoc, is the lead author of the paper, which appears in the June 12 issue of Neuron. Research scientist L. Ian Schmitt is also an author of the paper.

Shifting attention

Our brains are constantly bombarded with sensory information, and we are able to tune out much of it automatically, without even realizing it. Other distractions that are more intrusive, such as your seatmate’s phone conversation, require a conscious effort to suppress.

In a 2015 paper, Halassa and his colleagues explored how attention can be consciously shifted between different types of sensory input, by training mice to switch their focus between a visual and auditory cue. They found that during this task, mice suppress the competing sensory input, allowing them to focus on the cue that will earn them a reward.

This process appeared to originate in the prefrontal cortex (PFC), which is critical for complex cognitive behavior such as planning and decision-making. The researchers also found that a part of the thalamus that processes vision was inhibited when the animals were focusing on sound cues. However, there are no direct physical connections from the prefrontal cortex to the sensory thalamus, so it was unclear exactly how the PFC was exerting this control, Halassa says.

In the new study, the researchers again trained mice to switch their attention between visual and auditory stimuli, then mapped the brain connections that were involved. They first examined the outputs of the PFC that were essential for this task, by systematically inhibiting PFC projection terminals in every target. This allowed them to discover that the PFC connection to a brain region known as the striatum is necessary to suppress visual input when the animals are paying attention to the auditory cue.

Further mapping revealed that the striatum then sends input to a region called the globus pallidus, which is part of the basal ganglia. The basal ganglia then suppress activity in the part of the thalamus that processes visual information.

Using a similar experimental setup, the researchers also identified a parallel circuit that suppresses auditory input when animals pay attention to the visual cue. In that case, the circuit travels through parts of the striatum and thalamus that are associated with processing sound, rather than vision.

The findings offer some of the first evidence that the basal ganglia, which are known to be critical for planning movement, also play a role in controlling attention, Halassa says.

“What we realized here is that the connection between PFC and sensory processing at this level is mediated through the basal ganglia, and in that sense, the basal ganglia influence control of sensory processing,” he says. “We now have a very clear idea of how the basal ganglia can be involved in purely attentional processes that have nothing to do with motor preparation.”

Noise sensitivity

The researchers also found that the same circuits are employed not only for switching between different types of sensory input such as visual and auditory stimuli, but also for suppressing distracting input within the same sense — for example, blocking out background noise while focusing on one person’s voice.

The team also showed that when the animals are alerted that the task is going to be noisy, their performance actually improves, as they use this circuit to focus their attention.

“This study uses a dazzling array of techniques for neural circuit dissection to identify a distributed pathway, linking the prefrontal cortex to the basal ganglia to the thalamic reticular nucleus, that allows the mouse brain to enhance relevant sensory features and suppress distractors at opportune moments,” says Daniel Polley, an associate professor of otolaryngology at Harvard Medical School, who was not involved in the research. “By paring down the complexities of the sensory stimulus only to its core relevant features in the thalamus — before it reaches the cortex — our cortex can more efficiently encode just the essential features of the sensory world.”

Halassa’s lab is now doing similar experiments in mice that are genetically engineered to develop symptoms similar to those of people with autism. One common feature of autism spectrum disorder is hypersensitivity to noise, which could be caused by impairments of this brain circuit, Halassa says. He is now studying whether boosting the activity of this circuit might reduce sensitivity to noise.

“Controlling noise is something that patients with autism have trouble with all the time,” he says. “Now there are multiple nodes in the pathway that we can start looking at to try to understand this.”

The research was funded by the National Institutes of Mental Health, the National Institute of Neurological Disorders and Stroke, the Simons Foundation, the Alfred P. Sloan Foundation, the Esther A. and Joseph Klingenstein Fund, and the Human Frontier Science Program.