The Adelson lab works on artificial tactile sensing for robotics. We build novel robot fingers that are soft and sensitive like human fingers, and use them for tasks including manipulation, grasping, and the haptic perception of shape and material properties. We collaborate with researchers in computer vision, robotics, and machine learning in order to build integrated robotic systems.
Polina Anikeeva designs, synthesizes, and fabricates optoelectronic and magnetic devices to advance fundamental understanding and treatment of disorders of the nervous system.
The overarching interest of the Bear lab is in the question of how experience and deprivation modify synaptic connections in the brain. Experience-dependent synaptic plasticity is the physical substrate of memory, sculpts connections during postnatal development to determine the capabilities and limitations of brain functions, is responsible for the reorganization of the brain after damage, and is vulnerable in numerous psychiatric and neurological diseases and contributes to their symptoms.
Emilio Bizzi is an MIT Institute Professor Emeritus and an Emeritus Investigator in the McGovern Institute for Brain Research. He retired from active research in 2017 and is no longer accepting students or research staff.
When active, the Bizzi laboratory elaborated a theoretical and experimental framework that describes the way in which the central nervous system transforms planned movements into muscle activations.
Our group, centered in the MIT McGovern Institute and Howard Hughes Medical Institute, and jointly affiliated with the MIT Department of Biological Engineering and the MIT Department of Media Arts and Sciences, works on inventing and applying new tools for the analysis and engineering of brain circuits. We have been developing molecules, hardware, and methods to activate, silence, record, and analyze neural activity and circuit signaling, throughout brain circuits. We also work on ways to map the molecular structure of the brain.
A primary focus of the research in the Brown laboratory is the development of statistical methods and signal-processing algorithms for neuroscience data analysis, using combinations of likelihood, Bayesian, state-space, time-series and point process approaches. The laboratory is also using a systems neuroscience approach to study how the state of general anesthesia is induced and maintained. The long-term goal of this research is to establish a neurophysiological definition of anesthesia, safer, site-specific anesthetic drugs and to develop better neurophysiologically-based methods for measuring depth of anesthesia.
We use multiple approaches including traditional- and CRISPR-based genome editing, molecular, optogenetic, electrophysiological, and imaging techniques to understand 1) how olfactory stimuli are transformed to behavioral outputs as function of learning and 2) how the immune system modulates neural circuits to shape and guide behavioral outputs.
The Chung laboratory is an interdisciplinary research team devoted to developing and applying novel technologies (e.g. CLARITY) for integrative and comprehensive understanding of large-scale complex biological systems.
Professor Emerita Constantine-Paton retired from active research in 2019 and is no longer accepting students or research staff.
While the lab was active, it studied a phase of synaptogenesis during vertebrate brain development in which the activity patterns of young neurons mediate a competition that allows only highly effective synapses to survive.
Robert Desimone investigates the brain mechanisms that allow us to focus our attention on a specific task while filtering out distractions. Just as our world buzzes with distractions, the neurons in our brain are constantly bombarded with messages. By studying the visual system of humans and animals, Desimone has shown that relevant information is selectively amplified in certain brain regions, while irrelevant information is suppressed.
The research goal of the DiCarlo laboratory is to understand the mechanisms underlying visual object recognition. Specifically, we seek to understand how sensory input is transformed by the brain from an initial representation (essentially a photograph on the retina), to a new, remarkably powerful form of representation -- one that can support our seemingly effortless ability to solve the computationally difficult problem of object recognition.
Fedorenko investigates how people understand and produce language. She uses behavioral and brain imaging (fMRI, ERP, MEG) methods in healthy adults and patients with developmental and acquired brain disorders, as well as intracranial recordings and stimulation in neurosurgical patients, and, more recently, computational modeling.
The Fee lab studies how the brain learns and generates complex sequential behaviors, with a focus on the songbird as a model system. Birdsong is a complex behavior that young birds learn from their fathers and it provides an ideal system to study the neural basis of learned behavior. Because the parts of the bird's brain that control song learning are closely related to human circuits that are disrupted in brain disorders such as Parkinson's and Huntington's disease, Fee hopes the lessons learned from birdsong will provide new clues to the causes and possible treatment of these conditions.
Synapses are fundamental units of neuronal connectivity in the brain. It is at these specialized cell junctions that neurons communicate with one another. Many neuroscientists now look to the synapse for principles of learning and memory, for processes underlying behavior, and for pathological mechanisms of various neurological and psychiatric disorders. The Feng lab's long-term goal is to understand the mechanisms regulating the development and function of synapses and to probe the roles of synaptic and circuitry dysfunction in certain abnormal behaviors and their relevance to psychiatric disorders. There are currently three major aspects of research in the lab.
The Fiete group works on the mechanisms underlying memory, integration, error correction, and prediction in the brain, at the circuit level. We use theoretical and computational modeling techniques, and perform quantitative data analysis to tackle mechanistic and function-related questions. Our recent efforts fall right at the nexus of dynamics, coding, and function, as we seek to find how each influences the others.
The goal of the Flavell lab is to understand how neural circuits generate long-lasting behavioral states. By monitoring and manipulating the simple, well-defined nervous system of C. elegans, we aim to identify cellular and circuit mechanisms that organize animal behaviors over seconds, minutes, and hours.
The goal of our lab is to understand principles of brain organization that are consistent across individuals and those that vary across people due to age, personality, and other dimensions of individuality. We study the brain bases of learning, memory, emotion, and motivation, how these develop in children and adolescents, and how these differ in dyslexia, ADHD, autism, depression, and schizophrenia. Our primary methods are brain imaging (functional and structural), and the experimental study of behavior.
Research in the Gibson Lab (a.k.a. TedLab) is aimed at investigating how people learn, represent and process language. In addition, we have recently started to investigate the relationship between language, cognition and culture. We use a variety of methods, including behavioral experiments (e.g., reading and listening studies, lexical priming experiments, dual-task experiments, individual differences studies), statistical modeling and corpus analyses. In collaboration with other labs we also use eye-tracking methods, event-related potentials (ERPs) and functional MRI. Below are the major lines of research and research questions pursued in the lab.
The same brain that can construct language, music and mathematics also lets us develop habits of thought and action. These semi-automatic routines free us to think and attend to the world. But the habit system can also be hijacked by disease and drug exposure. The Graybiel Laboratory focuses on the habit system of the brain and our remarkable ability to switch from conscious activity to nearly non-conscious behavior. The goal of this research is to understand how we make and break habits and how the neurobiology of the habit system is helping to advance understanding of human problems ranging from Parkinson’s disease to obsessive-compulsive spectrum disorders and addiction.
Our work focuses on understanding the role of the thalamus in cognition. While the knowledge about what the cortex does in cognitive processes like attention and executive control has expanded tremendously over the last several decades,our understanding of what the thalamus does is quite limited.
Our laboratory studies how the biophysical features of individual neurons endow neural circuits with powerful processing capabilities, ultimately facilitating the complex computations required to drive adaptive behavior. A principal focus of our work is the role of dendrites, the elaborate tree-like structures where neurons receive the vast majority of afferent input. The spatial arrangement of synaptic contacts on dendrites and the interaction of various biophysical mechanisms enable complex integration of synaptic inputs – our hypothesis is that circuit-level computations are built out of these fundamental operations.
Dr. Heiman’s work seeks to understand the cell type-specific mechanisms responsible for neuronal vulnerability in aging and neurodegenerative diseases, including Huntington’s disease.
The Hockfield laboratory has studied molecular substrates of mammalian development. We identified a family of glycovariants of the extracellular matrix (ECM) proteoglycan, aggrecan, whose expression is regulated by neuronal activity early in an animal's life. Expression of the aggrecan glycoforms is regulated in parallel with critical period events and may play a role in stabilizing mature synaptic relationships.
Hogan's research in the Newman Laboratory emphasizes forceful interaction between the motor control systems of humans and machines (i.e., robots). Recent work pioneered therapeutic neurobotics to promote recovery after brain injury. It provides durable benefits even for chronic-phase stroke survivors, suggesting that with appropriate stimulation neural plasticity may be harnessed even long after injury. Devices to address balance, gait and abnormal lower-limb motor synergies, both in animals and humans, are in development or beginning trials.
A new generation of brain scanning methods will combine the specificity of cellular neuroimaging with the noninvasiveness and coverage of functional magnetic resonance imaging. The Jasanoff Laboratory is developing molecular strategies to help achieve this. We work on the chemistry and biochemistry of novel neuroimaging agents, and our overall goal is to apply the new agents for high-resolution analyses of the neural mechanisms of simple behavior in animals.
The long-term objective of research in my lab is to develop a mathematical framework for understanding the link between the brain and the mind. To tackle this problem, we record and perturb brain signals in animal models while they perform mental computations. We then use normative theories, computational models, and artificial neural networks to understand the building blocks of the mind in terms of the mechanisms and algorithms implemented by the brain.
The Kanwisher lab investigates the functional organization of the brain as a window into the architecture of the human mind. In the past, our lab has discovered a number of cortical regions that are stunningly specialized for specific cognitive tasks such as the perception of faces, places, bodies, and words. Current work is attempting to better characterize the function of each of these regions, to test long-standing but unresolved claims of other cortical specializations (e.g., for language), and to search for new unpredicted specializations using novel clustering methods (in collaboration with Polina Golland).
Roger Levy asks theoretical and applied questions about the processing and acquisition of natural language, with a focus on how linguistic communication resolves uncertainty over a potentially unbounded set of possible signals and meanings.
Research in the Littleton lab is aimed at characterizing the mechanisms by which neurons form synaptic connections, how synapses transmit information, and how synapses change during learning and memory. The lab combines molecular biology, protein biochemistry, electrophysiology and neuroimaging approaches with Drosophila genetics to address these questions.
Operating at the intersection of psychology, neuroscience, and engineering, the McDermott lab’s long term goals include understanding the computational principles underlying human hearing, improving devices for assisting those whose hearing is impaired and designing more effective machine systems for recognizing and interpreting sound.
The Miller Laboratory uses experimental and theoretical approaches to study the neural basis of cognition. We investigate how categories, concepts, and rules are learned, mental flexibility, how attention is focused, and, more generally, how the brain coordinates goal-directed thought and action.
The capacity of the brain to modify connections in response to levels of activity is termed plasticity. Plasticity is a prominent feature of brain development, and in the adult underlies learning and memory and adaptive reorganization of sensory maps. The Nedivi lab studies the cellular mechanisms that underlie activity-dependent plasticity in the developing and adult brain through studies of neuronal structural dynamics, identification of the participating genes, and characterization of the proteins they encode.
The Center for Brains, Minds, and Machines (CBMM) aims to create a new field — the Science and Engineering of Intelligence — by bringing together computer scientists, cognitive scientists, and neuroscientists to work in close collaboration. This new field is dedicated to developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding.
Mary Potter is Professor Emerita. She retired from active research in 2015 and is no longer accepting students or research staff.
When the Potter lab was active, its overall goal was to understand the very rapid processes involved in perceiving, comprehending, and remembering meaningful material such as words, sentences, or pictures. We've discovered that the meaning of a pictured scene or written word is understood in a fraction of a second, much faster than the time required for stabilizing even a brief memory of that stimulus -- unless the stimulus fits into the viewer's current mental context, like a word that is part of a sentence.
The Prelec lab studies the psychology and neuroscience of decision-making, favoring problems that involve risky choice, time discounting, self-control and consumer behavior. They also have a longstanding interest in non-verifiable subjective judgments, specifically, in developing methods for eliciting such judgments and for assessing their quality and credibility. Non-verifiable judgments include forecasts of the remote future, historical conjectures, counterfactual hypotheses, and phenomenological 'first-person' reports of internal states.
William "Chip" Quinn is Professor Emeritus. He retired from active research in 2015 and is no longer accepting students or research staff.
When active, thr Quinn lab studied learning. The model system was fruit flies, which can identify a specific chemical odor that they have experienced with electric shock and avoid it. Moreover, they can remember to avoid it for several days. The Quinn lab is investigating the molecular mechanisms underlying learning acquisition and memory storage by inducing and selecting single-gene mutations that affect learning or memory, and by engineering transgenic fly strains that disrupt these processes.
My research is at the interface of Machine Learning and Statistics. I am interested in formalizing the process of learning, in analyzing the learning models, and in deriving and implementing the emerging learning methods. A significant thrust of my research is in developing theoretical and algorithmic tools for online prediction, a learning framework where data arrives in a sequential fashion. My recent interests include understanding neural networks and, more generally, interpolation methods.
Bridging the fields of behavioral economics, cognitive science, and social psychology, David’s research combines behavioral experiments run online and in the field with mathematical and computational models to understand people’s attitudes, beliefs, and choices.
The Rosenholtz lab studies a wide range of topics in visual perception, from early visual encoding, through mid-level perceptual organization, to object and scene recognition. Current interests include efficient encoding in peripheral vision and its implications for performance at virtually all visual tasks, for theories of visual attention, and for late decision-level capacity limits.
The Saxe lab studies Theory of Mind as a case study in the deeper and broader question: how does the brain - an electrical and biological machine - construct abstract thoughts? We use functional neuroimaging, behavioural studies with kids and adults, patient studies, and transcranial magnetic stimulation to study abstract representations in the human brain. In addition to Theory of Mind, our recent research investigates brain development, moral reasoning, causal reasoning, and language.
Peter Schiller is Professor Emeritus. He retired from active research in 2013 and is no longer accepting students or research staff.
When active, the Scholler lab was devoted to the study of the primate visual and oculomotor systems in humans and non-human primates.
Jerry Schneider is Professor Emeritus. He retired from active research in 2017 and is no longer accepting students or research staff.
When active, research in the Schneider lab involved axon regeneration in the central nervous system with functional recovery; special topics in human neuropsychology and perception; and studies of the brains of sea mammals.
MIT Early Childhood Cognition Lab lead investigator Laura Schulz studies learning in early childhood. Her research bridges computational models of cognitive development and behavioral studies in order to understand the origins of inquiry and discovery.
A physician and a scientist, Morgan Sheng is author of more than 200 peer-reviewed publications focused on the molecular cellular biology of synapses and synaptic plasticity, and pathogenic mechanisms of neurodegenerative diseases. Sheng’s molecular studies of the structure and function of synapses (the communication junctions between brain cells) while at MGH and MIT have enhanced our understanding of the neural basis of cognitive function and dysfunction, including learning and memory, neurodevelopmental disorders, and dementia. His work has uncovered the form and complexity of protein complexes in the postsynaptic membrane that regulate the remarkable plasticity of neuronal connections.
Using a combination of experimental and computational modeling techniques, research in the Sinha laboratory focuses on understanding how the human brain learns to recognize objects through visual experience and how objects are encoded in memory. The lab's experimental work on these issues involves studying healthy individuals and also those with neurological disorders such as autism. A key initiative of the lab is Project Prakash; this effort seeks to accomplish the twin goals of providing treatment to children with disabilities and also understanding mechanisms of learning and plasticity in the brain.
Professor Slotine is the Director of the Nonlinear Systems Laboratory which studies general mathematical principles of nonlinear system stability, adaptation, and learning, and how they apply to robots and to models of biological control. The lab is particularly interested in how stability and performance constraints shape system architecture, representation, and algorithms in robots, and in whether similar constraints may in some cases lead to similar mechanisms in biological systems. Tools from nonlinear control, such as sliding variables, wave variables, and contraction theory also suggest a number of simple models of physiological motor control, which may help understand the specific roles of hierarchies, motor primitives, and nerve transmission delays.
The Sur laboratory studies the development, plasticity and dynamics of circuits in the cerebral cortex of the brain. The laboratory’s goal is to discover fundamental mechanisms of brain wiring and processing, and how they go awry in brain disorders.
The Tenenbaum laboratory studies the computational basis of human learning and inference. Through a combination of mathematical modeling, computer simulation, and behavioral experiments, we try to uncover the logic behind our everyday inductive leaps: constructing perceptual representations, separating “style” and “content” in perception, learning concepts and words, judging similarity or representativeness, inferring causal connections, noticing coincidences, predicting the future.
The main research interest in the Tonegawa laboratory is to decipher brain mechanisms subserving learning and memory. We seek to understand what happens in the brain when a memory is formed, when a fragile short-term memory is consolidated to a solid long-term memory, and when a memory formed previously is recalled on subsequent occasions. We also seek to understand the role of memory in decision-making, and how various external or internal factors, such as reward, punishment, attention and the subject’s emotional state, affect learning and memory. In summary, we study how the central nervous system in the brain enables our mind, with a focus on learning and memory.
The primary goal of the Tsai laboratory is to elucidate the pathological mechanisms underlying neurological disorders affecting learning and memory. The major research areas include brain aging and Alzheimer’s disease. We are taking a multidisciplinary approach to investigate the molecular, cellular, and circuit basis of neurodegenerative disorders.
My general area of research is the study of vision - including the processing of visual information by the human visual system, and computer vision. The goals of this research are to understand how our own visual system operates, and how to construct artificial systems with visual capabilities including, for example, aids for the visually impaired.
Ken Wexler is Professor Emeritus. He retired from active research in 2016 and is no longer accepting students or research staff.
When active, the Wexler ab/Normal Language Lab sought to understand the nature of the computational system of human language in its many guises. We studied most aspects of linguistic structure, including syntax, semantics, pragmatics and morphology. In pursuing these goals, we took as our primary linguistic data abnormal language, by which we mean nothing more than any system of language that seems to differ from standard adult language for biological reasons, including lack of maturation, difficulties in learning, and genetic variation.
The Wilson laboratory studies the neural processes within the hippocampus and neocortex that enable memories to form and persist over long periods of time. We use a technique that allows us to simultaneously record the activity of hundreds of individual neurons across multiple brain regions in freely behaving animals. When combined with genetic, pharmacological, and behavioral manipulations, these recordings allow us to gain a mechanistic understanding of how animals learn and remember.
Richard Wurtman is Professor Emeritus. He retired from active research in 2011 and is no longer accepting students or research staff.
When active, the goal of the Wurtman laboratory was to discover safe and effective treatments for brain diseases. Over the years, we have used a common basic strategy for doing so: doing fundamental research to identify a previously unsuspected control mechanism involving brain chemistry; confirming that this newly discovered mechanism is at work in the human brain; dentifying a disease in which this mechanism goes awry; developing and testing potential treatments based on these discoveries.
The mammalian brain poses a formidable challenge to the study and treatment of neuropsychiatric diseases – owing to the complex interaction of genetic, epigenetic, and circuit-level mechanisms underlying pathogenesis. Technologies that facilitate functional dissection of distinct brain circuits are necessary for systematic identification of disease origin and therapy. The Zhang laboratory is developing and applying molecular and optical technologies for probing brain function in health and disease. We hope that these new approaches will improve our understanding and treatment of brain diseases.