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 | 3DEPARTMENT 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 SciencesDEPARTMENT 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 | 5DEPARTMENT 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 SciencesDEPARTMENT 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 | 7DEPARTMENT 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 SciencesDEPARTMENT 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 | 9DEPARTMENT 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 SciencesDEPARTMENT 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 | 11DEPARTMENT 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 SciencesDEPARTMENT 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 | 13DEPARTMENT 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 SciencesDEPARTMENT 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 | 15DEPARTMENT 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 SciencesDEPARTMENT 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 | 17You can also read
