DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES

Page created by Donna Holt
 
CONTINUE READING
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, articial 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
                                                                         Subelds 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 aliated 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 aect.
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 scientic 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 scientic goal is to understand the eects 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 articial
interactions exist between the Department of Brain and Cognitive         intelligence, machine learning, neuroscience, medicine, cognitive
Sciences, the Computer Science and Articial 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 articial 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 Ocer 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 oers 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) oer 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
articial intelligence to reverse engineering circuits in the brain.
This joint program prepares students for careers that include
advanced applications of articial 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 oers 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 Oce, 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 diversied to give each individual the appropriate background for   Financial assistance is provided to qualied 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. Specic 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 dierent 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 aer 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 signicant work, publishable in scientic 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 Hockeld, 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 scientic papers in the brain sciences. Instruction
                                                                      provided in analyzing, presenting, constructively reviewing, and
Alan V. Hein, PhD
                                                                      defending the scientic 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 scientic 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
dierences, 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 pathnding, 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 oered 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, classication 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, condence 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,        Oers 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 specication, formation of
representations and computations, developmental origins, and         neuronal connections, construction of neural systems, and the
degree of functional specicity 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 specication, 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 classication        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 oered
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 classication        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 oered 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 specication, 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 articial neural
                                                                           network language models dier 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 articial neural
Self" from external environment; the neural circuits that enable us        network language models dier 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 oered 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 dierent 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
dierential 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 oered 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 scientic 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 neuroscientic 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 scientic 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].
scientic 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 oered 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 scientic 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 dier across individuals and cultures, and how
term. Other assignments include peer editing and reading/critiquing     they are aected 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 oered                                         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 ocer. 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 classication.
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 scientic 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 coecient. 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 scientic 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
You can also read