Profile Category: Faculty

McGovern Institute faculty lead labs conducting groundbreaking research linked to the central mission of the institution. They also hold appointments in one or more academic departments at MIT.

Mehrdad Jazayeri

Neurobiology of Mental Computations

How does the brain give rise to the mind? How do neurons, circuits, and synapses in the brain encode knowledge about objects, events, and other structural and causal relationships in the environment? Research in Mehrdad Jazayeri’s lab brings together ideas from cognitive science, neuroscience, and machine learning with experimental data in humans, animals, and computer models to develop a computational understanding of how the brain create internal representations, or models, of the external world.

Michale Fee

Song Circuits

Michale Fee studies how the brain learns and generates complex sequential behaviors, focusing 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.

Guoping Feng

Listening to Synapses

Guoping Feng is interested in how synapses — the connections between neurons — contribute to neurodevelopmental and psychiatric diseases, including autism spectrum disorder (ASD) and schizophrenia. He leads research that uses molecular genetics combined with behavioral and electrophysiological methods to study the components of the synapse.

Feng is perhaps best known for pioneering a gene-based therapy that could reverse a severe form of autism that is caused by a single mutation in the SHANK3 gene. After genetically engineering the SHANK3 mutation in animal models using CRISPR-based technology, Feng’s gene-correction therapy greatly reduced SHANK3 symptoms, restoring the animals’ cognitive, behavioral, and motor functions.

Additionally, the lab has leveraged genetic technologies to help map the cellular diversity in the brain—a valuable tool in neuroscience research. Through understanding the molecular, cellular, and circuit changes underlying brain diseases and disorders, the Feng lab hopes to eventually inform new and more effective treatments for neurodevelopmental and psychiatric disorders.

Nancy Kanwisher

Architecture of the Mind

What is the nature of the human mind? Philosophers have debated this question for centuries, but Nancy Kanwisher approaches this question empirically, using brain imaging to look for components of the human mind that reside in particular regions of the brain. Her lab has identified cortical regions that are selectively engaged in the perception of faces, places, and bodies, and other regions specialized for uniquely human functions including the music, language, and thinking about other people’s thoughts. More recently, her lab has begun using artificial neural networks to unpack these findings and examine why, from a computational standpoint, the brain exhibits functional specification in the first place.

Ann Graybiel

Probing the Deep Brain

Ann Graybiel studies the basal ganglia, forebrain structures that are profoundly important for normal brain function. Dysfunction in these regions is implicated in neurologic and neuropsychiatric disorders ranging from Parkinson’s disease and Huntington’s disease to obsessive-compulsive disorder, anxiety and depression, and addiction. Graybiel’s laboratory is uncovering circuits underlying both the neural deficits related to these disorders, as well as the role that the basal ganglia play in guiding normal learning, motivation, and behavior.

Tomaso Poggio

Engineering Intelligence

Tomaso Poggio is one of the founders of computational neuroscience. He pioneered a model of the fly’s visual system as well as of human stereovision. His research has always been interdisciplinary, bridging brains and computers. It is now focused on the mathematics of deep learning and on the computational neuroscience of the visual cortex. Poggio also introduced using an approach called regularization theory to computational vision, made key contributions to the biophysics of computation and to learning theory, and developed an influential model of recognition in the visual cortex. Research in the Poggio lab is guided by the belief that understanding learning is at the heart of understanding both biological and artificial intelligence. Learning is therefore the route to understanding how the human brain works and for making intelligent machines.

John Gabrieli

Images of Mind

John Gabrieli’s goal is to understand the organization of memory, thought, and emotion in the human brain. In collaboration with clinical colleagues, Gabrieli uses brain imaging to better understand, diagnose, and select treatments for neurological and psychiatric diseases.

A major focus of the Gabrieli lab is the neural basis of learning in children. His team found structural differences in the brains of young children who are at risk for reading difficulties, even before they start learning to read. By studying these differences in children, Gabrieli hopes to identify ways to improve learning in the classroom and inform effective educational policies and practices.

Gabrieli is also interested in using the tools of neuroscience to personalize medicine. His team showed that brain scans can identify children who are vulnerable to depression before symptoms even appear, opening the possibility of earlier interventions to prevent episodes of depression. Brain scans may also help help predict which individuals with social anxiety disorder are most likely to benefit from a particular therapeutic intervention. Gabrieli’s team continues to explore the role of neuroimaging in other brain disorders, including schizophrenia, addiction, and bipolar disorder.

His team also studies a range of other research topics, including new strategies to cope with emotional stress, the benefits of mindfulness for academic performance and mental health, and the value of embracing neurodiversity to better understand autism.

Mark Harnett

Listening to Neurons

Mark Harnett studies how the biophysical features of individual neurons, including ion channels, receptors, and membrane electrical properties, endow neural circuits with the ability to process information and perform the complex computations that underlie behavior. As part of this work, the Harnett lab was the first to describe the physiological properties of human dendrites, the elaborate tree-like structures through which neurons receive the vast majority of their synaptic inputs. Harnett also examines how computations are instantiated in neural circuits to produce complex behaviors such as spatial navigation.

Virtual Tour of Harnett Lab

Martha Constantine-Paton

Developing Connections

Martha Constantine-Paton studied the formation and modification of synapses – the interconnections between neurons – in order to understand how experience shapes the wiring of the brain. By studying individual neurons in the visual system of developing animals, she showed that a class of molecules known as NMDA receptors plays an essential role in setting the strengths of synapses. NMDA receptors are thought to underlie many aspects of learning throughout life. Constantine-Paton also examined the role these receptors play in developmental disorders that have their origins in early life.

Robert Desimone

Paying Attention

Our brains are constantly bombarded with sensory information. The ability to distinguish relevant information from irrelevant distractions is a critical skill, one that is impaired in many brain disorders. By studying the visual system of humans and animals, Robert Desimone has shown that when we attend to something specific, neurons in certain brain regions fire in unison – like a chorus rising above the noise – allowing the relevant information to be “heard” more efficiently by other regions of the brain.