Graduate Program

Graduate Program

Our department and its graduate program are anchored by the idea that an understanding of how the brain gives rise to the mind requires basic science investigation at multiple empirical scales of analysis (genes, molecules, synapses, neurons, networks of neurons, brain regions, individuals, and groups of individuals), and computational frameworks and models that encapsulate our understanding by formally describing the links between those levels. Currently, BCS experimental efforts are organized around three levels of empirical analysis: cognitive science, the study of behavior to infer the representations and algorithms of the mind; systems neuroscience, the study of the brain structures and circuits that implement those algorithms and representations, and cellular and molecular neuroscience, the study of the mechanisms that control the construction and maintenance of those brain structures and circuits. Crucially, we also apply computational approaches to build the formal links within and between these empirical levels. 

We are committed to training the scientific leaders of the future, and our graduate program is the cornerstone of that commitment.  Our comprehensive, interdisciplinary approach, leadership in the development and deployment of cutting-edge tools, and truly collaborative environment gives graduate students the freedom and ability to shape their research across disciplines to make a large impact today, and to shape their training to broadly prepare them to lead in this rapidly evolving field of the future.

During their first year of study, graduate students rotate through three different laboratories, gaining exposure to the Department’s rich scientific diversity of cutting-edge methods, model systems, and research questions. Typically, by the end of their first year, students select a primary faculty thesis mentor to work with in accomplishing their Ph.D. research.  Students typically complete the Ph.D. program in five to six years. They leave MIT prepared to pursue careers in research, teaching, or industry.  

Our training philosophy is strongly cross-disciplinary, and students are not siloed into single sub-fields.  However, we are conceptually organized into four areas:

 

Cognitive Science

Cognitive science is the scientific study of the human mind. It combines ideas and methods from psychology, computer science, linguistics, philosophy, and neuroscience to illuminate how the mind operates. The broad goal of cognitive science is to characterize the nature of human knowledge – its forms and content – and how that knowledge is used, processed, and acquired. 

This focus area is led by the following faculty members:

Edward AdelsonEmery BrownRobert DesimoneJames DiCarloEvelina FedorenkoIla FieteJohn GabrieliEdward GibsonMichael HalassaMehrdad JazayeriNancy KanwisherRoger LevyJoshua McDermottEarl MillerDrazen PrelecRebecca SaxeLaura SchulzPawan SinhaJoshua TenenbaumShimon UllmanMatthew Wilson

 

Systems Neuroscience

Systems neuroscience is the study of the emergence of abstract representation, memory, learning, and other functions through the interactions of neurons in circuits. Researchers query animal models with diverse experimental tools to examine core cognitive processes and their neural circuit underpinnings. The goal of systems neuroscience is to provide an account of how collective activity in neurons at the level of circuits produces the complex states, plans, and actions, that we call the mind.

This focus area is led by the following faculty members:

Polina AnikeevaMark BearEdward BoydenEmery BrownGloria ChoiKwanghun ChungRobert DesimoneJames DiCarloMichale FeeGuoping FengFiete, IlaSteven FlavellAnn GraybielMichael HalassaMark HarnettAlan JasanoffMehrdad JazayeriEarl MillerMorgan ShengMriganka SurSusumu TonegawaLi-Huei TsaiMatthew WilsonFeng Zhang

 

Cellular and Molecular Neuroscience

Cellular and molecular neuroscience approaches the brain at the level of its most fundamental building-blocks: genes, molecules, cells, and synapses. These components determine how neurons work, how cells are modified and how neurons connect and reconnect for learning and memory. It strives to understand the essential processes and dynamics that control construction and maintenance at the smallest and fastest scales, which are the foundation for brain function at the level of the organism.

This focus area is led by the following faculty members:

Polina AnikeevaMark BearEd BoydenKwanghun ChungFeng, GuopingSteven FlavellAnn GraybielMark HarnettMyriam HeimanTroy LittletonElly Nedivi, Morgan Sheng, Mriganka Sur, Susumu TonegawaLi-Huei TsaiFeng Zhang

 

Computation

Computational approaches seek to develop new analytic, theoretical, and model frameworks for understanding how the brain works.  A key goal is to synthesize disparate strands of experimental discovery from multiple subfields of neuroscience and cognitive science, with the help of mathematical, numerical, and computer-based methods. Computational models seek to answer questions of mechanism (how?), function and efficiency (why?), and arrive at a more complete understanding that bridges neuroscience and cognitive science: A theory of the emergence of mind from brain.

This focus area is led by the following faculty members:

Edward AdelsonEmery BrownDiCarlo, JamesEvelina FedorenkoMichale FeeIla FieteMichael HalassaMark HarnettNeville HoganMehrdad JazayeriNancy KanwisherRoger LevyJoshua McDermottTomaso PoggioAlexander RakhlinRebecca SaxeLaura Schulz, Pawan SinhaJean-Jacques Slotine, Joshua TenenbaumShimon UllmanMatthew Wilson