DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES
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DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES DEPARTMENT OF BRAIN AND COGNITIVE behavior, departmental researchers are working to develop theories of vision, motor control, neural circuitry, and language within an SCIENCES experimental framework. The study of mind, brain, and behavior has grown in recent years In cognitive science, human experimentation is combined with with unprecedented speed. New avenues of approach, opened by formal and computational analyses to understand complex developments in the biological and computer sciences, raise the intelligent processes such as language, reasoning, memory, and hope that human beings, having achieved considerable mastery over visual information processing. There are applications in the elds of the world around them, may also come closer to an understanding education, articial intelligence, human-machine interaction, and in of themselves. The goal of the Department of Brain and Cognitive the treatment of language, cognitive, and other disorders. Sciences is to answer fundamental questions concerning intelligent Subelds in cognitive science include psycholinguistics, comprising processes and brain organization. To this end, the department sentence and word processing, language acquisition, and aphasia; focuses on four themes: molecular and cellular neuroscience, visual cognition, including reading, imagery, attention, and systems neuroscience, cognitive science, and computation. Several perception of complex patterns such as faces, objects, and scenes; members of the department's faculty are aliated with two major spatial cognition; memory; and the nature and development research centers: the Picower Institute for Learning and Memory and of concepts. Another key eld is the study of perception— the McGovern Institute for Brain Research. developmental and processing approaches focus on human and Research in cellular neuroscience deals with the biology of neurons, machine vision, and how visual images are encoded, stored, emphasizing the special properties of these cells as encoders, and retrieved, with current topics that include motion analysis, transmitters, and processors of information. Departmental stereopsis, perceptual organization, and perceptual similarity. Other researchers apply techniques of contemporary molecular and research includes functional brain imaging in normal subjects as cellular biology to problems of neuronal development, structure, and well as studies of neurologically impaired patients in an attempt to function, resulting in a new understanding of the underlying basic understand brain mechanisms underlying normal human sensation, components of the nervous system and their interactions. These perception, cognition, action, and aect. studies have profound clinical implications, in part by generating a framework for the treatment of neurological and psychiatric disorders. Primary areas of interest include the development and Undergraduate Study plasticity of neuronal morphology and connectivity, the cellular and molecular bases of behavior in simple neuronal circuits, Bachelor of Science in Brain and Cognitive Sciences (Course 9) neurochemistry, and cellular physiology. Brain science and cognitive science are complementary and interactive in their research objectives. Both approaches examine In the area of systems neuroscience, departmental investigators perception, performance, and intervening processes in humans and use a number of new approaches ranging from computation through animals. Central issues in the discipline include the interpretation electrophysiology to biophysics. Of major interest are the visual of sensory experience; the reception, manipulation, storage, and and motor systems where the scientic goals are to understand retrieval of information within the nervous system; and the planning transduction and encoding of sensory stimuli into nerve messages, and execution of motor activity. Higher-level functions include organization and development of sensorimotor systems, processing the development of formal and informal reasoning skills; and the of sensorimotor information, and the sensorimotor performance of structure, acquisition, use, and internal representation of human organisms. Also of major interest is neuromodulatory regulation, language. where the scientic goal is to understand the eects of rewarding or stressful environments on brain circuits. The Bachelor of Science in Brain and Cognitive Sciences (http:// catalog.mit.edu/degree-charts/brain-cognitive-sciences-course-9) In computation and cognitive science, particularly strong prepares students to pursue advanced degrees or careers in articial interactions exist between the Department of Brain and Cognitive intelligence, machine learning, neuroscience, medicine, cognitive Sciences, the Computer Science and Articial Intelligence science, psychology, linguistics, philosophy, education research and Laboratory, and the Center for Biological and Computational technology, and human-machine interaction. Learning, providing new intellectual approaches in areas including vision and motor control, and biological and computer learning. Methods of inquiry in the brain and cognitive sciences are drawn Computational theories are developed and tested within the from molecular, cellular, and systems neuroscience; cognitive and framework of neurophysiological, psychological, and other perceptual psychology; computer science and articial intelligence; experimental approaches. In the study of vision and motor control, linguistics; philosophy of language and mind; and mathematics. complementary experimental work includes single-cell and multiple- The undergraduate program is designed to provide instruction in cell neurophysiological recording as well as functional brain imaging. the relevant aspects of these various disciplines. The program is In the area of learning, which is seen as central to intelligent administered by an Undergraduate Ocer and an Undergraduate Department of Brain and Cognitive Sciences | 3
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES Administrator, consulting as necessary with faculty members from 9.18[J] Developmental Neurobiology these disciplines who also serve as advisors to majors, helping 9.19 Computational Psycholinguistics them select a coherent set of subjects from within the requirements, 9.21[J] Cellular Neurophysiology and including a research requirement. Members of the faculty are Computing available to guide the research. 9.26[J] Principles and Applications The Brain and Cognitive Sciences (BCS) major incorporates of Genetic Engineering for programming and computational skills to meet the increasing Biotechnology and Neuroscience demands for those skills in both graduate school and the workforce. 9.35 Perception The major oers a tiered system of subjects with enough flexibility 9.49 Neural Circuits for Cognition to allow multiple avenues through the Brain and Cognitive Sciences 9.53 Emergent Computations Within curriculum, meeting the divergent goals of BCS students. Individual Distributed Neural Circuits guidance regarding career goals is available from faculty and from 9.66[J] Computational Cognitive Science Career Advising and Professional Development. 9.85 Infant and Early Childhood Cognition Bachelor of Science in Computation and Cognition (Course 6-9) Tier 3 Subjects The Department of Electrical Engineering and Computer Science 9.24 Disorders and Diseases of the (http://catalog.mit.edu/schools/engineering/electrical-engineering- Nervous System computer-science) and the Department of Brain and Cognitive 9.28 Current Topics in Developmental Sciences (p. 3) oer a joint curriculum leading to a Bachelor Neurobiology of Science in Computation and Cognition (http://catalog.mit.edu/ 9.32 Genes, Circuits, and Behavior degree-charts/computation-cognition-6-9) that focuses on the 9.42 The Brain and Its Interface with the emerging eld of computational and engineering approaches to Body brain science, cognition, and machine intelligence. The curriculum provides flexibility to accommodate students with a wide diversity 9.46 Neuroscience of Morality of interests in this area—from biologically inspired approaches to Total Units 72 articial intelligence to reverse engineering circuits in the brain. This joint program prepares students for careers that include advanced applications of articial intelligence and machine Graduate Study learning, as well as further graduate study in systems and cognitive neuroscience. Students in the program are full members of both The Department of Brain and Cognitive Sciences oers programs of departments, with an academic advisor from the Department of Brain study leading to the doctoral degree in neuroscience or cognitive and Cognitive Sciences. science. Areas of research specialization include cellular and molecular neuroscience, systems neuroscience, computation, and Inquiries cognitive science. The graduate programs are designed to prepare students to pursue careers in research, teaching, or industry. Information about this program is available from the Brain and Cognitive Sciences Academic Oce, Room 46-2005, 617-253-7403. Doctor of Philosophy in Brain and Cognitive Sciences Fields The doctor of philosophy in brain and cognitive sciences elds Minor in Brain and Cognitive Sciences (http://catalog.mit.edu/schools/science/#degreesandprogramstext) The Minor in Brain and Cognitive Sciences consists of six subjects (the PhD program) is normally completed in approximately six years arranged in two levels of study, intended to provide students breadth of full-time work, including summers. Institute requirements for in the eld as a whole and some depth in an area of specialization. the PhD are given in the section on General Degree Requirements (http://catalog.mit.edu/mit/graduate-education/general-degree- Core Subjects requirements). Formal coursework for the departmental program 9.00 Introduction to Psychological Science 12 (http://catalog.mit.edu/degree-charts/phd-brain-cognitive- 9.01 Introduction to Neuroscience 12 sciences), described below, is intended to prepare the student to 9.40 Introduction to Neural Computation 12 pass the general examinations and do original thesis research. The Specialized Subjects written general examinations will be due in August of the second Select any combination of three subjects from Tier 2 36 year. and/or Tier 3 of the undergraduate degree program: All students start with rst-year intensive core subjects that provide Tier 2 Subjects an introduction to brain and cognitive studies from the viewpoint 9.09[J] Cellular and Molecular Neurobiology of systems neuroscience, molecular and cellular neuroscience, 9.13 The Human Brain cognition, and computation. Incoming graduate students are 4 | Department of Brain and Cognitive Sciences
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES required to take at least two of these subjects but encouraged to take all within the rst two years of study. Further coursework will Financial Support be diversied to give each individual the appropriate background for Financial assistance is provided to qualied applicants in the form research in his or her own area. of traineeships, research assistantships, teaching assistantships, and a limited number of fellowships, subject to availability of Coursework in cellular and molecular neuroscience emphasizes the funds. Prospective students are encouraged to apply for individual current genetic, molecular, and cellular approaches to biological fellowships such as those sponsored by the National Science systems that are necessary to generate advances in neuroscience. Foundation and the National Defense Science and Engineering Training in systems neuroscience covers neuroanatomy, Graduate Fellowship Program to cover all or part of the cost of their neurophysiology, and neurotransmitter chemistry, concentrating education. The department's nancial resources for non-US citizens on the major sensory, motor, memory, and executive systems in are limited; international students are strongly encouraged to seek the vertebrate brain. Specic ties to molecular neurobiology or nancial assistance for all or part of the cost of their education from computation may be emphasized, depending upon the research non-MIT sources. interests of the student. Inquiries Coursework for students in computation is intended to give both For additional information regarding teaching and research an understanding of empirical approaches to the study of the brain programs, contact the Academic Administrator, Department of Brain and animal behavior and a theoretical background for analyzing and Cognitive Sciences, Room 46-2005, 617-253-5741, or visit the computational aspects of biological information processing. department's website (http://web.mit.edu/bcs). Candidates studying cognitive science take coursework covering such topics as language processing, language acquisition, cognitive Faculty and Teaching Sta development, natural computation, neural networks, connectionist models, and visual information processing. Students also choose Michale S. Fee, PhD seminars and coursework in linguistics, philosophy, logic, Glen V. (1946) and Phyllis F. Dorflinger Professor mathematics, or computer science, depending on the individual Professor of Neuroscience student's research program. Head, Department of Brain and Cognitive Sciences Graduate students begin a research apprenticeship immediately Laura E. Schulz, PhD upon arrival with lab rotations in the rst year. To familiarize new Professor of Cognitive Science students with the research being conducted in the department, the Associate Head, Department of Brain and Cognitive Sciences department hosts a series of talks in September by faculty whose Josh McDermott, PhD labs are open for rotations. Students typically choose their rst Associate Professor of Cognitive Science rotation by October 1. Laboratory rotations allow students to get to Associate Head, Department of Brain and Cognitive Sciences know several dierent labs; learn concepts and techniques, and select a laboratory in which they will complete their dissertation Professors research. Students complete three rotations during the rst year; an Edward H. Adelson, PhD optional fourth rotation is also available during spring or summer John and Dorothy Wilson Professor of Vision Science term but must be approved by the rotation coordinator. Students Professor of Brain and Cognitive Sciences must submit a brief rotation proposal at the start of each rotation, and a brief summary upon completion of each rotation. Polina Olegovna Anikeeva, PhD Matoula S. Salapatas Professor of Materials Science and Engineering At the end of the rst year, an advisory committee of two to four Professor of Materials Science and Engineering faculty members is formed. This committee monitors progress and, Professor of Brain and Cognitive Sciences with membership changing as necessary, evolves into the thesis committee. Thesis research normally requires 24-48 months of full- Mark Bear, PhD time activity aer the qualifying examinations have been passed. It Picower Professor of Neuroscience is expected that the research embodied in the PhD dissertation be (On sabbatical, fall) original and signicant work, publishable in scientic journals. Upon successful completion of all program requirements, the student will be awarded the PhD in the corresponding eld of brain and cognitive sciences. Department of Brain and Cognitive Sciences | 5
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES Edward S. Boyden III, PhD Roger Levy, PhD Y. Eva Tan Professor in Neurotechnology Professor of Brain and Cognitive Sciences Professor of Brain and Cognitive Sciences Professor of Media Arts and Sciences J. Troy Littleton, MD, PhD Professor of Biological Engineering Menicon Professor in Neuroscience (On sabbatical, fall) Professor of Biology Professor of Brain and Cognitive Sciences Emery N. Brown, MD, PhD Edward Hood Taplin Professor of Medical Engineering Earl K. Miller, PhD Warren M. Zapol Professor of Anaesthesia, HMS Picower Professor Professor of Computational Neuroscience Professor of Neuroscience Member, Institute for Data, Systems, and Society Elly Nedivi, PhD Core Faculty, Institute for Medical Engineering and Science William R. (1964) and Linda R. Young Professorship Robert Desimone, PhD Professor of Neuroscience Doris and Don Berkey Professor Professor of Biology Professor of Neuroscience Tomaso A. Poggio, PhD James DiCarlo, MD, PhD Eugene McDermott Professor in the Brain Sciences and Human Peter deFlorez Professor of Neuroscience Behavior Guoping Feng, PhD Drazen Prelec, PhD James W. (1963) and Patricia T. Poitras Professor Digital Equipment Corp. Leaders for Global Operations Professor of Professor of Neuroscience Management Professor of Management Science Ila Fiete, PhD Professor of Economics Professor of Computational Neuroscience Professor of Brain and Cognitive Sciences John D. E. Gabrieli, PhD Alexander Rakhlin, PhD Grover Hermann Professor of Health Sciences and Technology Professor of Brain and Cognitive Sciences Professor of Cognitive Neuroscience Member, Institute for Data, Systems, and Society Core Faculty, Institute for Medical Engineering and Science David Rand, PhD Edward A. Gibson, PhD Erwin H. Schell Professor Professor of Cognitive Science Professor of Marketing Professor of Brain and Cognitive Sciences Ann M. Graybiel, PhD Member, Institute for Data, Systems, and Society Institute Professor Professor of Brain and Cognitive Sciences Rebecca R. Saxe, PhD John W. Jarve (1978) Professor of Cognitive Science Susan Hockeld, PhD Professor of Neuroscience Morgan Hwa-Tze Sheng, PhD President Emerita Professor of Brain and Cognitive Sciences Neville Hogan, PhD Pawan Sinha, PhD Sun Jae Professor in Mechanical Engineering Professor of Vision and Computational Neuroscience Professor of Brain and Cognitive Sciences (On sabbatical, spring) Alan P. Jasano, PhD Jean-Jacques E. Slotine, PhD Professor of Biological Engineering Professor of Mechanical Engineering Professor of Nuclear Science and Engineering Professor of Information Sciences Professor of Brain and Cognitive Sciences Member, Institute for Data, Systems, and Society Nancy Kanwisher, PhD Mriganka Sur, PhD Walter A. Rosenblith Professor Paul E. (1965) and Lilah Newton Professor Professor of Cognitive Neuroscience Professor of Neuroscience 6 | Department of Brain and Cognitive Sciences
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES Joshua B. Tenenbaum, PhD Guangyu Robert Yang, PhD Professor of Cognitive Science and Computation Assistant Professor of Brain and Cognitive Sciences Assistant Professor of Electrical Engineering and Computer Science Susumu Tonegawa, PhD Picower Professor Adjunct Professors Professor of Biology Tari Sharot, PhD Professor of Neuroscience Adjunct Professor of Brain and Cognitive Sciences Li-Huei Tsai, PhD Picower Professor Senior Lecturers Professor of Neuroscience Thomas Byrne, PhD Senior Lecturer in Brain and Cognitive Sciences Fan Wang, PhD Professor of Brain and Cognitive Sciences Laura Frawley, PhD Senior Lecturer in Brain and Cognitive Sciences Matthew A. Wilson, PhD Sherman Fairchild Professor Lecturers Professor of Neuroscience Aida Khan, PhD Professor of Biology Lecturer in Brain and Cognitive Sciences Feng Zhang, PhD James and Patricia Poitras (1963) Professor of Neuroscience Research Sta Professor of Biological Engineering (On sabbatical, spring) Principal Research Scientists Vikash Kumar Mansinghka, PhD Associate Professors Principal Research Scientist of Brain and Cognitive Sciences Gloria Choi, PhD Ruth Rosenholtz, PhD Mark Hyman Jr Career Development Associate Professor Principal Research Scientist of Brain and Cognitive Sciences Associate Professor of Neuroscience Kwanghun Chung, PhD Research Scientists Associate Professor of Chemical Engineering Andrew Bolton, PhD Associate Professor of Brain and Cognitive Sciences Research Scientist of Brain and Cognitive Sciences Core Faculty, Institute for Medical Engineering and Science Christopher Cueva, PhD Evelina Fedorenko, PhD Research Scientist of Brain and Cognitive Sciences Associate Professor of Brain and Cognitive Neurosciences Cameron Freer, PhD Steven Flavell, PhD Research Scientist of Brain and Cognitive Sciences Associate Professor of Brain and Cognitive Sciences Michal Fux, PhD Mark Thomas Harnett, PhD Research Scientist of Brain and Cognitive Sciences Associate Professor of Neuroscience Sharon Gilad-Gutnick, PhD Myriam Heiman, PhD Research Scientist of Brain and Cognitive Sciences Associate Professor of Neuroscience Melissa Kline Struhl, PhD Mehrdad Jazayeri, PhD Research Scientist of Brain and Cognitive Sciences Associate Professor of Neuroscience Laureline Logiaco, PhD Research Scientist of Brain and Cognitive Sciences Assistant Professors Nidhi Seethapathi, PhD Max Siegel, PhD Assistant Professor of Brain and Cognitive Sciences Research Scientist of Brain and Cognitive Sciences Assistant Professor of Electrical Engineering and Computer Science Kevin A. Smith, PhD Research Scientist of Brain and Cognitive Sciences Department of Brain and Cognitive Sciences | 7
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES Professors Emeriti 9.000 Constructive Criticism of Research in the Brain & Cognitive Sciences Emilio Bizzi, MD, PhD Prereq: Permission of instructor Institute Professor Emeritus G (Fall) Professor Emeritus of Brain and Cognitive Sciences 3-0-3 units Can be repeated for credit. Martha Constantine-Paton, PhD Professor Emerita of Neuroscience Provides training in the constructive analysis, critique, and defense Professor Emerita of Biology of the content of scientic papers in the brain sciences. Instruction provided in analyzing, presenting, constructively reviewing, and Alan V. Hein, PhD defending the scientic claims of cutting-edge primary research Professor Emeritus of Experimental Psychology from all areas of brain sciences: molecular, systems, cognitive, Mary C. Potter, PhD and computation. Training provided by example from the instructor Professor Emerita of Psychology and practice reviewing, critiquing, presenting, and defending. Practice with instructor feedback provided to each student through William G. Quinn, PhD constructively critiquing research and presenting/defending Professor Emeritus of Neurobiology research. Beyond preparing for the weekly class discussion, students Professor Emeritus of Biology are also expected to attend the Brain and Cognitive Sciences colloquium each week to practice critical analysis and constructive Peter H. Schiller, PhD questioning. Open to rst-year graduate students in Course 9. Dorothy W. Poitras Professor Emeritus J. DiCarlo Professor Emeritus of Medical Physiology Gerald Edward Schneider, PhD 9.01 Introduction to Neuroscience Professor Emeritus of Neuroscience Prereq: None U (Fall) Kenneth Wexler, PhD 4-0-8 units. REST Professor Emeritus of Psychology Professor Emeritus of Linguistics Introduction to the mammalian nervous system, with emphasis on the structure and function of the human brain. Topics include the function of nerve cells, sensory systems, control of movement, 9.00 Introduction to Psychological Science learning and memory, and diseases of the brain. Prereq: None M. Bear U (Spring) 4-0-8 units. HASS-S 9.011 Systems Neuroscience Core I Prereq: Permission of instructor A survey of the scientic study of human nature, including how the G (Fall) mind works, and how the brain supports the mind. Topics include the 6-0-12 units mental and neural bases of perception, emotion, learning, memory, cognition, child development, personality, psychopathology, and Survey of brain and behavioral studies. Examines principles social interaction. Consideration of how such knowledge relates to underlying the structure and function of the nervous system, with debates about nature and nurture, free will, consciousness, human a focus on systems approaches. Topics include development of the dierences, self, and society. nervous system and its connections, sensory systems of the brain, J. D. Gabrieli the motor system, higher cortical functions, and behavioral and cellular analyses of learning and memory. Preference to rst-year graduate students in BCS. R. Desimone, E. K. Miller 8 | Department of Brain and Cognitive Sciences
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.012 Cognitive Science 9.015[J] Molecular and Cellular Neuroscience Core I Prereq: Permission of instructor Same subject as 7.65[J] G (Spring) Prereq: None 6-0-12 units G (Fall) 3-0-9 units Intensive survey of cognitive science. Topics include visual perception, language, memory, cognitive architecture, learning, Survey and primary literature review of selected major topic reasoning, decision-making, and cognitive development. Topics areas in molecular and cellular neurobiology. Covers nervous covered from behavioral, computational, and neural perspectives. system development, axonal pathnding, synapse formation and E. Gibson, P. Sinha, J. Tenenbaum function, synaptic plasticity, ion channels and receptors, cellular neurophysiology, glial cells, sensory transduction, and relevant 9.013[J] Molecular and Cellular Neuroscience Core II examples in human disease. Includes lectures and weekly paper Same subject as 7.68[J] write-ups, together with student presentations and discussion of Prereq: Permission of instructor primary literature. A nal two-page research write-up is also due at G (Spring) the end of the term. 3-0-9 units J. T. Littleton, M. Sheng Survey and primary literature review of major areas in molecular 9.016[J] Introduction to Sound, Speech, and Hearing and cellular neurobiology. Covers genetic neurotrophin signaling, Same subject as HST.714[J] adult neurogenesis, G-protein coupled receptor signaling, glia Prereq: (6.3000 and 8.03) or permission of instructor function, epigenetics, neuronal and homeostatic plasticity, G (Fall) neuromodulators of circuit function, and neurological/psychiatric Not oered regularly; consult department disease mechanisms. Includes lectures and exams, and involves 4-0-8 units presentation and discussion of primary literature. 9.015[J] recommended, though the core subjects can be taken in any See description under subject HST.714[J]. sequence. S. S. Ghosh, H. H. Nakajima, S. Puria G. Feng, L.-H. Tsai 9.017 Systems Neuroscience Core II 9.014 Quantitative Methods and Computational Models in Prereq: 18.06 or (9.011 and 9.014) Neurosciences G (Spring) Prereq: None 2-2-8 units G (Fall) 3-1-8 units Covers systems and computational neuroscience topics relevant to understanding how animal brains solve a wide range of cognitive Provides theoretical background and practical skills needed to tasks. Focuses on experimental approaches in systems neuroscience analyze and model neurobiological observations at the molecular, (behavioral design, parametric stimulus control, recording systems and cognitive levels. Develops an intuitive understanding of techniques) and theory-driven analyses (dynamical systems, control mathematical tools and computational techniques which students theory, Bayesian theory), both at the level of behavioral and neural apply to analyze, visualize and model research data using MATLAB data. Also focuses on regional organization (cortex, thalamus, basal programming. Topics include linear systems and operations, ganglia, midbrain, and cerebellum), along with traditional divisions dimensionality reduction (e.g., PCA), Bayesian approaches, in systems neuroscience: sensory systems, motor systems, and descriptive and generative models, classication and clustering, and associative systems. dynamical systems. Limited to 18; priority to current BCS Graduate M. Halassa students. M. Jazayeri, D. Zysman Department of Brain and Cognitive Sciences | 9
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.021[J] Cellular Neurophysiology and Computing 9.09[J] Cellular and Molecular Neurobiology Same subject as 2.794[J], 6.4812[J], 20.470[J], HST.541[J] Same subject as 7.29[J] Subject meets with 2.791[J], 6.4810[J], 9.21[J], 20.370[J] Prereq: 7.05 or 9.01 Prereq: (Physics II (GIR), 18.03, and (2.005, 6.2000, 6.3000, 10.301, U (Spring) or 20.110[J])) or permission of instructor 4-0-8 units G (Spring) 5-2-5 units See description under subject 7.29[J]. T. Littleton, S. Prescott See description under subject 6.4812[J]. J. Han, T. Heldt 9.110[J] Nonlinear Control Same subject as 2.152[J] 9.07 Statistics for Brain and Cognitive Science Prereq: 2.151, 6.7100[J], 16.31, or permission of instructor Prereq: 6.100B G (Spring) U (Fall) 3-0-9 units 4-0-8 units See description under subject 2.152[J]. Provides students with the basic tools for analyzing experimental J.-J. E. Slotine data, properly interpreting statistical reports in the literature, and reasoning under uncertain situations. Topics organized 9.12 Experimental Molecular Neurobiology around three key theories: probability, statistical, and the linear Prereq: Biology (GIR) and 9.01 model. Probability theory covers axioms of probability, discrete U (Spring) and continuous probability models, law of large numbers, and 2-4-6 units. Institute LAB the Central Limit Theorem. Statistical theory covers estimation, likelihood theory, Bayesian methods, bootstrap and other Monte Experimental techniques in cellular and molecular neurobiology. Carlo methods, as well as hypothesis testing, condence intervals, Designed for students without previous experience in techniques elementary design of experiments principles and goodness-of-t. of cellular and molecular biology. Experimental approaches include The linear model theory covers the simple regression model and DNA manipulation, molecular cloning, protein biochemistry, the analysis of variance. Places equal emphasis on theory, data dissection and culture of brain cells, synaptic protein analysis, analyses, and simulation studies. immunocytochemistry, and fluorescent microscopy. One lab session E. N. Brown plus one paper review session per week. Instruction and practice in written communication provided. Enrollment limited. 9.073[J] Statistics for Neuroscience Research G. Choi Same subject as HST.460[J] Prereq: Permission of instructor 9.123[J] Neurotechnology in Action G (Spring) Same subject as 20.203[J] 3-0-9 units Prereq: Permission of instructor G (Spring) A survey of statistical methods for neuroscience research. Core 3-6-3 units topics include introductions to the theory of point processes, the generalized linear model, Monte Carlo methods, Bayesian methods, Oers a fast-paced introduction to numerous laboratory methods multivariate methods, time-series analysis, spectral analysis and at the forefront of modern neurobiology. Comprises a sequence of state-space modeling. Emphasis on developing a rm conceptual modules focusing on neurotechnologies that are developed and understanding of the statistical paradigm and statistical methods used by MIT research groups. Each module consists of a background primarily through analyses of actual experimental data. lecture and 1-2 days of rsthand laboratory experience. Topics E. N. Brown typically include optical imaging, optogenetics, high throughput neurobiology, MRI/fMRI, advanced electrophysiology, viral and genetic tools, and connectomics. A. Jasano 10 | Department of Brain and Cognitive Sciences
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.13 The Human Brain 9.18[J] Developmental Neurobiology Prereq: 9.00, 9.01, or permission of instructor Same subject as 7.49[J] U (Spring) Subject meets with 7.69[J], 9.181[J] 3-0-9 units Prereq: 7.03, 7.05, 9.01, or permission of instructor U (Spring) Surveys the core perceptual and cognitive abilities of the human 3-0-9 units mind and asks how these are implemented in the brain. Key themes include the functional organization of the cortex, as well as the Considers molecular control of neural specication, formation of representations and computations, developmental origins, and neuronal connections, construction of neural systems, and the degree of functional specicity of particular cortical regions. contributions of experience to shaping brain structure and function. Emphasizes the methods available in human cognitive neuroscience, Topics include: neural induction and pattern formation, cell lineage and what inferences can and cannot be drawn from each. and fate determination, neuronal migration, axon guidance, synapse N. Kanwisher formation and stabilization, activity-dependent development and critical periods, development of behavior. Students taking graduate 9.17 Systems Neuroscience Laboratory version complete additional readings that will be addressed in their Prereq: 9.01 or permission of instructor mid-term and nal exams. U (Fall) E. Nedivi, M. Heiman 2-4-6 units. Institute LAB 9.181[J] Developmental Neurobiology Consists of a series of laboratories designed to give students Same subject as 7.69[J] experience with basic techniques for conducting systems Subject meets with 7.49[J], 9.18[J] neuroscience research. Includes sessions on anatomical, Prereq: 9.011 or permission of instructor neurophysiological, and data acquisition and analysis techniques, G (Spring) and how these techniques are used to study nervous system 3-0-9 units function. Involves the use of experimental animals. Assignments include weekly preparation for lab sessions, two major lab reports Considers molecular control of neural specication, formation of and a series of basic computer programming tutorials (MATLAB). neuronal connections, construction of neural systems, and the Instruction and practice in written communication provided. contributions of experience to shaping brain structure and function. Enrollment limited. Topics include: neural induction and pattern formation, cell lineage M. Harnett, S. Flavell and fate determination, neuronal migration, axon guidance, synapse formation and stabilization, activity-dependent development 9.175[J] Robotics and critical periods, development of behavior. In addition to nal Same subject as 2.165[J] exam, analysis and presentation of research papers required for Prereq: 2.151 or permission of instructor nal grade. Students taking graduate version complete additional G (Fall) assignments. Students taking graduate version complete additional 3-0-9 units readings that will be addressed in their mid-term and nal exams. E. Nedivi, M. Heiman See description under subject 2.165[J]. J.-J. E. Slotine, H. Asada Department of Brain and Cognitive Sciences | 11
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.19 Computational Psycholinguistics 9.24 Disorders and Diseases of the Nervous System Subject meets with 9.190 Prereq: (7.29[J] and 9.01) or permission of instructor Prereq: (6.100B and (6.3700, 9.40, or 24.900)) or permission of U (Spring) instructor 3-0-9 units U (Fall) 4-0-8 units Topics examined include regional functional anatomy of the CNS; brain systems and circuits; neurodevelopmental disorders Introduces computational approaches to natural language including autism; neuropsychiatric disorders such as schizophrenia; processing and acquisition by humans and machines, combining neurodegenerative diseases such as Parkinson's and Alzheimer's; symbolic and probabilistic modeling techniques. Covers models autoimmune disorders such as multiple sclerosis; gliomas. Emphasis such as n-grams, nite state automata, and context-free and on diseases for which a molecular mechanism is understood. mildly context-sensitive grammars, for analyzing phonology, Diagnostic criteria, clinical and pathological ndings, genetics, morphology, syntax, semantics, pragmatics, and larger document model systems, pathophysiology, and treatment are discussed for structure. Applications range from accurate document classication individual disorders and diseases. Limited to 18. and sentence parsing by machine to modeling human language M. Sur acquisition and real-time understanding. Covers both theory and contemporary computational tools and datasets. Students taking 9.26[J] Principles and Applications of Genetic Engineering for graduate version complete additional assignments. Biotechnology and Neuroscience R. P. Levy Same subject as 20.205[J] Prereq: Biology (GIR) 9.190 Computational Psycholinguistics Acad Year 2023-2024: Not oered Subject meets with 9.19 Acad Year 2024-2025: U (Spring) Prereq: (6.100B and (6.3702, 9.40, or 24.900)) or permission of 3-0-9 units instructor G (Fall) Covers principles underlying current and future genetic engineering 4-0-8 units approaches, ranging from single cellular organisms to whole animals. Focuses on development and invention of technologies Introduces computational approaches to natural language for engineering biological systems at the genomic level, and processing and acquisition by humans and machines, combining applications of engineered biological systems for medical and symbolic and probabilistic modeling techniques. Covers models biotechnological needs, with particular emphasis on genetic such as n-grams, nite state automata, and context-free and manipulation of the nervous system. Design projects by students. mildly context-sensitive grammars, for analyzing phonology, F. Zhang morphology, syntax, semantics, pragmatics, and larger document structure. Applications range from accurate document classication 9.271[J] Pioneering Technologies for Interrogating Complex and sentence parsing by machine to modeling human language Biological Systems acquisition and real-time understanding. Covers both theory and Same subject as 10.562[J], HST.562[J] contemporary computational tools and datasets. Students taking Prereq: None graduate version complete additional assignments. G (Spring) R. P. Levy 3-0-9 units 9.21[J] Cellular Neurophysiology and Computing See description under subject HST.562[J]. Limited to 15. Same subject as 2.791[J], 6.4810[J], 20.370[J] K. Chung Subject meets with 2.794[J], 6.4812[J], 9.021[J], 20.470[J], HST.541[J] Prereq: (Physics II (GIR), 18.03, and (2.005, 6.2000, 6.3000, 10.301, or 20.110[J])) or permission of instructor U (Spring) 5-2-5 units See description under subject 6.4810[J]. Preference to juniors and seniors. J. Han, T. Heldt 12 | Department of Brain and Cognitive Sciences
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.272[J] Topics in Neural Signal Processing 9.301[J] Neural Plasticity in Learning and Memory Same subject as HST.576[J] Same subject as 7.98[J] Prereq: Permission of instructor Prereq: Permission of instructor G (Spring) G (Spring) 3-0-9 units 3-0-6 units Presents signal processing and statistical methods used to study Examination of the role of neural plasticity during learning neural systems and analyze neurophysiological data. Topics include and memory of invertebrates and mammals. Detailed critical state-space modeling formulated using the Bayesian Chapman- analysis of the current literature of molecular, cellular, genetic, Kolmogorov system, theory of point processes, EM algorithm, electrophysiological, and behavioral studies. Student-directed Bayesian and sequential Monte Carlo methods. Applications include presentations and discussions of original papers supplemented dynamic analyses of neural encoding, neural spike train decoding, by introductory lectures. Juniors and seniors require instructor's studies of neural receptive eld plasticity, algorithms for neural permission. prosthetic control, EEG and MEG source localization. Students should S. Tonegawa know introductory probability theory and statistics. E. N. Brown 9.32 Genes, Circuits, and Behavior Prereq: 7.29[J], 9.16, 9.18[J], or permission of instructor 9.28 Current Topics in Developmental Neurobiology U (Spring) Prereq: None. Coreq: 9.18[J] 3-0-9 units U (Spring) Not oered regularly; consult department Focuses on understanding molecular and cellular mechanisms of 1-0-8 units circuitry development, function and plasticity, and their relevance to normal and abnormal behaviors/psychiatric disorders. Highlights Considers recent advances in the eld of developmental cutting-edge technologies for neuroscience research. Students build neurobiology based on primary research articles that address professional skills through presentations and critical evaluation of molecular control of neural specication, formation of neuronal original research papers. connections, construction of neural systems, and the contributions G. Feng of experience to shaping brain structure and function. Also considers new techniques and methodologies as applied to the eld. Students 9.34[J] Biomechanics and Neural Control of Movement critically analyze articles and prepare concise and informative Same subject as 2.183[J] presentations based on their content. Instruction and practice Subject meets with 2.184 in written and oral communication provided. Requires class Prereq: 2.004 or permission of instructor participation, practice sessions, and presentations. G (Spring) E. Nedivi 3-0-9 units 9.285[J] Audition: Neural Mechanisms, Perception and Cognition See description under subject 2.183[J]. Same subject as HST.723[J] N. Hogan Prereq: Permission of instructor G (Spring) 9.35 Perception 6-0-6 units Prereq: 9.01 or permission of instructor U (Spring) See description under subject HST.723[J]. 4-0-8 units J. McDermott, D. Polley, B. Delgutte, M. C. Brown Studies how the senses work and how physical stimuli are transformed into signals in the nervous system. Examines how the brain uses those signals to make inferences about the world, and uses illusions and demonstrations to gain insight into those inferences. Emphasizes audition and vision, with some discussion of touch, taste, and smell. Provides experience with psychophysical methods. J. McDermott Department of Brain and Cognitive Sciences | 13
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.357 Current Topics in Perception 9.39 Language in the Mind and Brain Prereq: Permission of instructor Subject meets with 9.390 G (Spring) Prereq: 9.00, 9.01, or permission of instructor 2-0-7 units U (Spring) Can be repeated for credit. 3-0-9 units Advanced seminar on issues of current interest in human and Surveys the core mental abilities — and their neural substrates machine vision. Topics vary from year to year. Participants discuss — that support language, and situates them within the broader current literature as well as their ongoing research. landscape of human cognition. Topics explored include: how E. H. Adelson structured representations are extracted from language; the nature of abstract concepts and how they relate to words; the nature of 9.36 Neurobiology of Self the brain mechanisms that support language vs. other structured Subject meets with 9.360 and/or meaningful inputs, like music, mathematical expressions, or Prereq: 9.01 pictures; the relationship between language and social cognition; U (Fall) how language is processed in individuals who speak multiple 3-0-9 units languages; how animal communication systems and articial neural network language models dier from human language. Draws on Discusses the neurobiological mechanisms that distinguish "the evidence from diverse approaches and populations, focusing on Self" from external environment; the neural circuits that enable us cutting-edge research. Students taking graduate version complete to know that "the Self" is in pain, or feels hungry, thirsty, and tired; additional assignments. and the neurons and circuits that lead to the emotional and moody E. Fedorenko Self. Examines brain mechanism that encodes the body schema and the Self in space. This includes the neural computations that 9.390 Language in the Mind and Brain allow, for example, the hand to know where the mouth is. Discusses Subject meets with 9.39 the possibility of making robots develop a sense of Self, as well Prereq: 9.00, 9.01, or permission of instructor as disorders and delusions of the Self. Contemporary research — G (Spring) ranging from molecules, cells, circuits, to systems in both animal 3-0-9 units models and humans — explored. Students in the graduate version do additional classwork or projects. Surveys the core mental abilities — and their neural substrates F. Wang — that support language, and situates them within the broader landscape of human cognition. Topics explored include: how 9.360 Neurobiology of Self (New) structured representations are extracted from language; the nature Subject meets with 9.36 of abstract concepts and how they relate to words; the nature of Prereq: 9.01 the brain mechanisms that support language vs. other structured G (Fall) and/or meaningful inputs, like music, mathematical expressions, or 3-0-9 units pictures; the relationship between language and social cognition; how language is processed in individuals who speak multiple Discusses the neurobiological mechanisms that distinguish "the languages; how animal communication systems and articial neural Self" from external environment; the neural circuits that enable us network language models dier from human language. Draws on to know that "the Self" is in pain, or feels hungry, thirsty, and tired; evidence from diverse approaches and populations, focusing on and the neurons and circuits that lead to the emotional and moody cutting-edge research. Students taking graduate version complete Self. Examines brain mechanism that encodes the body schema additional assignments. and the Self in space. This includes the neural computations that E. Fedorenko allow, for example, the hand to know where the mouth is. Discusses the possibility of making robots develop a sense of Self, as well as disorders and delusions of the Self. Contemporary research — ranging from molecules, cells, circuits, to systems in both animal models and humans — explored. Students in the graduate version do additional classwork or projects. F. Wang 14 | Department of Brain and Cognitive Sciences
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.40 Introduction to Neural Computation 9.42 The Brain and Its Interface with the Body Prereq: (Physics II (GIR), 6.100B, and 9.01) or permission of Prereq: 7.28, 7.29[J], or permission of instructor instructor U (Spring) U (Spring) Not oered regularly; consult department 4-0-8 units 3-0-9 units Introduces quantitative approaches to understanding brain and Covers a range of topics, such as brain-immune system interaction, cognitive functions. Topics include mathematical description the gut-brain axis, and bioengineering approaches for studying the of neurons, the response of neurons to sensory stimuli, simple brain and its interactions with dierent organs. Explores how these neuronal networks, statistical inference and decision making. interactions may be involved in nervous system disease processes. Also covers foundational quantitative tools of data analysis in F. Zhang neuroscience: correlation, convolution, spectral analysis, principal components analysis. Mathematical concepts include simple 9.422[J] Principles of Neuroengineering dierential equations and linear algebra. Same subject as 20.452[J], MAS.881[J] M. Fee Subject meets with 20.352 Prereq: Permission of instructor 9.401 Tools for Robust Science G (Fall) Prereq: None Not oered regularly; consult department G (Fall) 3-0-9 units 3-0-9 units See description under subject MAS.881[J]. New tools are being developed to improve credibility, facilitate E. S. Boyden, III collaboration, accelerate scientic discovery, and expedite translation of results. Students (i) identify obstacles to conducting 9.455[J] Revolutionary Ventures: How to Invent and Deploy robust cognitive and neuroscientic research, (ii) practice using Transformative Technologies current cutting-edge tools designed to overcome these obstacles Same subject as 15.128[J], 20.454[J], MAS.883[J] by improving scientic practices and incentives, and (iii) critically Prereq: Permission of instructor evaluate these tools' potential and limitations. Example tools G (Fall) investigated include shared pre-registration, experimental design, 2-0-7 units data management plans, meta-data standards, repositories, FAIR code, open-source data processing pipelines, alternatives to See description under subject MAS.883[J]. scientic paper formats, alternative publishing agreements, citation E. Boyden, J. Bonsen, J. Jacobson audits, reformulated incentives for hiring and promotion, and more. R. Saxe, J.DiCarlo 9.46 Neuroscience of Morality Prereq: 9.00, 9.01, and (9.13 or 9.85) 9.41 Research and Communication in Neuroscience and U (Fall) Cognitive Science Not oered regularly; consult department Prereq: 9.URG and permission of instructor 5-0-7 units. HASS-S U (Fall) Advanced seminar that covers both classic and cutting-edge primary 2-12-4 units literature from psychology and the neuroscience of morality. Emphasizes research and scientic communication. Instruction Addresses questions about how the human brain decides which and practice in written and oral communication provided. Based on actions are morally right or wrong (including neural mechanisms results of his/her UROP research, each student creates a full-length of empathy and self-control), how such brain systems develop paper and a poster as part of an oral presentation at the end of the over childhood and dier across individuals and cultures, and how term. Other assignments include peer editing and reading/critiquing they are aected by brain diseases (such as psychopathy, autism, published research papers. Prior to starting class, students must tumors, or addiction). Instruction and practice in written and oral have collected enough data from their UROP research projects to communication provided. Limited to 24. write a paper. Limited to juniors and seniors. R. Saxe L. Schulz Department of Brain and Cognitive Sciences | 15
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.48[J] Philosophical Issues in Brain Science 9.50 Research in Brain and Cognitive Sciences Same subject as 24.08[J] Prereq: 9.00 and permission of instructor Prereq: None U (Fall, Spring) Acad Year 2023-2024: Not oered 0-12-0 units Acad Year 2024-2025: U (Fall) Can be repeated for credit. 3-0-9 units. HASS-H; CI-H Laboratory research in brain and cognitive science, using See description under subject 24.08[J]. physiological, anatomical, pharmacological, developmental, E. J. Green behavioral, and computational methods. Each student carries out an experimental study under the direction of a member of the faculty. 9.49 Neural Circuits for Cognition Project must be approved in advance by the faculty supervisor and Subject meets with 9.490 the undergraduate faculty ocer. Written presentation of results is Prereq: 9.40, 18.06, or permission of instructor required. U (Fall) Consult L. Schulz 3-0-9 units 9.520[J] Statistical Learning Theory and Applications Takes a computational approach to examine circuits in the brain that Same subject as 6.7910[J] perform elemental cognitive tasks: tasks that are neither directly Prereq: 6.3700, 6.7900, 18.06, or permission of instructor sensory nor directly motor in function, but are essential to bridging G (Fall) from perception to action. Covers circuits and circuit motifs in the 3-0-9 units brain that underlie computations like integration, decision-making, spatial navigation, inference, and other cognitive elements. Students Covers foundations and recent advances in statistical machine study empirical results, build dynamical models of neural circuits, learning theory, with the dual goals of providing students with and examine the mathematical theory of representations and the theoretical knowledge to use machine learning and preparing computation in such circuits. Considers noise, stability, plasticity, more advanced students to contribute to progress in the eld. The and learning rules for these systems. Students taking graduate content is roughly divided into three parts. The rst part is about version complete additional assignments. classical regularization, margin, stochastic gradient methods, I. Fiete overparametrization, implicit regularization, and stability. The second part is about deep networks: approximation and optimization 9.490 Neural Circuits for Cognition theory plus roots of generalization. The third part is about the Subject meets with 9.49 connections between learning theory and the brain. Occasional talks Prereq: 9.40, 18.06, or permission of instructor by leading researchers on advanced research topics. Emphasis on G (Fall) current research topics. 3-0-9 units T. Poggio, L. Rosasco Takes a computational approach to examine circuits in the brain that 9.521[J] Mathematical Statistics: a Non-Asymptotic Approach perform elemental cognitive tasks: tasks that are neither directly Same subject as 18.656[J], IDS.160[J] sensory nor directly motor in function, but are essential to bridging Prereq: (6.7700[J], 18.06, and 18.6501) or permission of instructor from perception to action. Covers circuits and circuit motifs in the G (Spring) brain that underlie computations like integration, decision-making, 3-0-9 units spatial navigation, inference, and other cognitive elements. Students study empirical results, build dynamical models of neural circuits, Introduces students to modern non-asymptotic statistical analysis. and examine the mathematical theory of representations and Topics include high-dimensional models, nonparametric regression, computation in such circuits. Considers noise, stability, plasticity, covariance estimation, principal component analysis, oracle and learning rules for these systems. Students taking graduate inequalities, prediction and margin analysis for classication. version complete additional assignments. Develops a rigorous probabilistic toolkit, including tail bounds and a I. Fiete basic theory of empirical processes S. Rakhlin, P. Rigollet 16 | Department of Brain and Cognitive Sciences
DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES 9.522 Statistical Reinforcement Learning (9.651) 9.530 Emergent Computations Within Distributed Neural Circuits Prereq: None Subject meets with 9.53 G (Fall) Prereq: 9.40 or permission of instructor 9-0-3 units G (Spring) 4-0-8 units Focuses on sample complexity and algorithms for online learning and decision-making. Prediction of individual sequences, online Addresses the fundamental scientic question of how the human regression, and online density estimation. Multi-armed and brain still outperforms the best computer algorithms in most contextual bandits. Decision-making with structured observations domains of sensory, motor and cognitive function, as well as and the decision-estimation coecient. Frequentist and Bayesian the parallel and distributed nature of neural processing (as approaches. Reinforcement learning: tabular methods and function opposed to the serial organization of computer architectures/ approximation. Behavioral and neural mechanisms of reinforcement algorithms) required to answer it. Explores the biologically plausible learning. computational mechanisms and principles that underlie neural A. Rahklin computing, such as competitive and unsupervised learning rules, attractor networks, self-organizing feature maps, content- 9.53 Emergent Computations Within Distributed Neural Circuits addressable memory, expansion recoding, the stability-plasticity Subject meets with 9.530 dilemma, the role of lateral and top-down feedback in neural Prereq: 9.40 or permission of instructor systems, the role of noise in neural computing. Students taking U (Spring) graduate version complete additional assignments. 4-0-8 units R. Ajemian Addresses the fundamental scientic question of how the human 9.55[J] Consumer Behavior brain still outperforms the best computer algorithms in most Same subject as 15.8471[J] domains of sensory, motor and cognitive function, as well as Prereq: None the parallel and distributed nature of neural processing (as U (Fall) opposed to the serial organization of computer architectures/ 3-0-6 units algorithms) required to answer it. Explores the biologically plausible Credit cannot also be received for 9.550[J], 15.847[J] computational mechanisms and principles that underlie neural computing, such as competitive and unsupervised learning See description under subject 15.8471[J]. rules, attractor networks, self-organizing feature maps, content- D. Rand addressable memory, expansion recoding, the stability-plasticity dilemma, the role of lateral and top-down feedback in neural 9.550[J] Consumer Behavior systems, the role of noise in neural computing. Students taking Same subject as 15.847[J] graduate version complete additional assignments. Prereq: 15.809, 15.814, or permission of instructor R. Ajemian G (Fall) 3-0-6 units Credit cannot also be received for 9.55[J], 15.8471[J] See description under subject 15.847[J]. D. Rand Department of Brain and Cognitive Sciences | 17
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