Research Area: Systems Neuroscience

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

Ila Fiete

Neural Coding and Dynamics

Ila Fiete builds tools and mathematical models to expand our knowledge of the brain’s computations. Specifically, her lab focuses on how the brain develops and reshapes its neural connections to perform high-level computations, like those involved in memory and learning. The Fiete lab applies cutting-edge theoretical and quantitative methods—wielding the vast capabilities of computational models, informed by mathematics, machine learning, and physics—digging deeper into how the brain represents and manipulates information. Through these strategies, Fiete hopes to shed new light onto the neural ensembles behind learning, integration of new information, inference-making, and spatial navigation.

Her lab’s findings are pushing the frontiers of neuroscience—while advancing the utility of computational tools in this space—and are building a more robust understanding of complex brain processes.

Alan Jasanoff

Next Generation Brain Imaging

One of the greatest challenges of modern neuroscience is to relate high-level operations of the brain and mind to well-defined biological processes that arise from molecules and cells. The Jasanoff lab is creating a suite of experimental approaches designed to achieve this by permitting brain-wide dynamics of neural signaling and plasticity to be imaged for the first time, with molecular specificity. These potentially transformative approaches use novel probes detectable by magnetic resonance imaging (MRI) and other noninvasive readouts. The probes afford qualitatively new ways to study healthy and pathological aspects of integrated brain function in mechanistically-informative detail, in animals and possibly also people.

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.

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.

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

Ian Wickersham

Making Connections

Ian Wickersham develops genetic tools that provide more powerful and precise ways to study the organization of the brain. His lab invents techniques for targeting neurons based on their synaptic connectivity and gene expression patterns in order to cause them to express genes that allow the neurons to be studied and controlled by neuroscientists and clinicians. The goal of Wickersham’s work is to provide neuroscience with more effective ways of studying the brain, and potentially to provide clinical neurology with more effective ways of treating disorders of the brain.

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.

James DiCarlo

Rapid Recognition

DiCarlo’s research goal is to reverse engineer the brain mechanisms that underlie human visual intelligence. He and his collaborators have revealed how population image transformations carried out by a deep stack of interconnected neocortical brain areas — called the primate ventral visual stream — are effortlessly able to extract object identity from visual images. His team uses a combination of large-scale neurophysiology, brain imaging, direct neural perturbation methods, and machine learning methods to build and test neurally-mechanistic computational models of the ventral visual stream and its support of cognition and behavior. Such an engineering-based understanding is likely to lead to new artificial vision and artificial intelligence approaches, new brain-machine interfaces to restore or augment lost senses, and a new foundation to ameliorate disorders of the mind.