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Course 9: Brain and Cognitive Sciences |
![]() | | | 9.00-9.499 | | | 9.50-9.999 plus Thesis, UROP | | | ![]() |
9.00 Introduction to Psychological Science
![]() ![]() ![]() Prereq: None Units: 4-0-8 Lecture: TR2-3.30 (32-123) Recitation: W10 (46-1015) or W4 (46-1015) or W EVE (7 PM) (46-1015) or R12 (46-3037) or R4 (46-1015) or R EVE (7 PM) (46-1015) or F10 (46-1015) or F11 (46-1015) or F1 (46-3037) or F2 (46-3037) or R4 (46-3037) ![]() A survey of the scientific study of human nature, including how the mind works, and how the brain supports the mind. Topics include the mental and neural bases of perception, emotion, learning, memory, cognition, child development, personality, psychopathology, and social interaction. Consideration of how such knowledge relates to debates about nature and nurture, free will, consciousness, human differences, self, and society. J. D. Gabrieli No required or recommended textbooks 9.01 Introduction to Neuroscience
![]() ![]() ![]() Prereq: None Units: 4-0-8 ![]() 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, learning and memory, and diseases of the brain. M. Bear 9.011 Systems Neuroscience Core I
![]() ![]() Prereq: Permission of instructor Units: 6-0-12 ![]() Survey of brain and behavioral studies. Examines principles underlying the structure and function of the nervous system, with a focus on systems approaches. Topics include development of the nervous system and its connections, sensory systems of the brain, the motor system, higher cortical functions, and behavioral and cellular analyses of learning and memory. Preference to first-year graduate students in BCS. R. Desimone, E. K. Miller 9.012 Cognitive Science
![]() ![]() Prereq: Permission of instructor Units: 6-0-12 Lecture: TR1-4 (46-4199) ![]() Intensive survey of cognitive science. Topics include visual perception, language, memory, cognitive architecture, learning, reasoning, decision-making, and cognitive development. Topics covered from behavioral, computational, and neural perspectives. E. Gibson, P. Sinha, J. Tenenbaum No textbook information available 9.013[J] Molecular and Cellular Neuroscience Core II
![]() ![]() (Same subject as 7.68[J]) Prereq: Permission of instructor Units: 3-0-9 Lecture: MW1-2.30 (46-4062) ![]() Survey and primary literature review of major areas in molecular and cellular neurobiology. Covers genetic neurotrophin signaling, adult neurogenesis, G-protein coupled receptor signaling, glia function, epigenetics, neuronal and homeostatic plasticity, neuromodulators of circuit function, and neurological/psychiatric disease mechanisms. Includes lectures and exams, and involves presentation and discussion of primary literature. 9.015 recommended, though the core subjects can be taken in any sequence. G. Feng, L.-H. Tsai No textbook information available 9.014 Quantitative Methods and Computational Models in Neurosciences
![]() ![]() Prereq: None Units: 3-1-8 ![]() Provides theoretical background and practical skills needed to analyze and model neurobiological observations at the molecular, systems and cognitive levels. Develops an intuitive understanding of mathematical tools and computational techniques which students apply to analyze, visualize and model research data using MATLAB programming. Topics include linear systems and operations, dimensionality reduction (e.g., PCA), Bayesian approaches, descriptive and generative models, classification and clustering, and dynamical systems. Limited to 18; priority to current BCS Graduate students. M. Jazayeri, A. Rebei 9.015[J] Molecular and Cellular Neuroscience Core I
![]() ![]() (Same subject as 7.65[J]) Prereq: None Units: 3-0-9 ![]() Survey and primary literature review of selected major topic areas in molecular and cellular neurobiology. Covers nervous system development, axonal pathfinding, synapse formation and function, synaptic plasticity, ion channels and receptors, cellular neurophysiology, glial cells, sensory transduction, and relevant examples in human disease. Includes lectures and weekly paper write-ups, together with student presentations and discussion of primary literature. A final two-page research write-up is also due at the end of the term. J. T. Littleton, M. Sheng, B. Weissbourd 9.016[J] Introduction to Sound, Speech, and Hearing
![]() ![]() Not offered regularly; consult department (Same subject as HST.714[J]) Prereq: (6.3000 and 8.03) or permission of instructor Units: 4-0-8 ![]() Introduces students to the acoustics, anatomy, physiology, and mechanics related to speech and hearing. Focuses on how humans generate and perceive speech. Topics related to speech, explored through applications and challenges involving acoustics, speech recognition, and speech disorders, include acoustic theory of speech production, basic digital speech processing, control mechanisms of speech production and basic elements of speech and voice perception. Topics related to hearing include acoustics and mechanics of the outer ear, middle ear, and cochlea, how pathologies affect their function, and methods for clinical diagnosis. Surgical treatments and medical devices such as hearing aids, bone conduction devices, and implants are also covered. S. Ghosh, H. Nakajima, S. Puria 9.017 Systems Neuroscience Core II
![]() ![]() Not offered regularly; consult department Prereq: 18.06 or (9.011 and 9.014) Units: 2-2-8 ![]() Covers systems and computational neuroscience topics relevant to understanding how animal brains solve a wide range of cognitive tasks. Focuses on experimental approaches in systems neuroscience (behavioral design, parametric stimulus control, recording techniques) and theory-driven analyses (dynamical systems, control theory, Bayesian theory), both at the level of behavioral and neural data. Also focuses on regional organization (cortex, thalamus, basal ganglia, midbrain, and cerebellum), along with traditional divisions in systems neuroscience: sensory systems, motor systems, and associative systems. Staff 9.021[J] Cellular Neurophysiology and Computing
![]() ![]() ![]() (Same subject as 2.794[J], 6.4812[J], 20.470[J], HST.541[J]) (Subject meets with 2.791[J], 6.4810[J], 9.21[J], 20.370[J]) Prereq: (Physics II (GIR), 18.03, and (2.005, 6.2000, 6.3000, 10.301, or 20.110)) or permission of instructor Units: 5-2-5 ![]() ![]() Integrated overview of the biophysics of cells from prokaryotes to neurons, with a focus on mass transport and electrical signal generation across cell membrane. First third of course focuses on mass transport through membranes: diffusion, osmosis, chemically mediated, and active transport. Second third focuses on electrical properties of cells: ion transport to action potential generation and propagation in electrically excitable cells. Synaptic transmission. Electrical properties interpreted via kinetic and molecular properties of single voltage-gated ion channels. Final third focuses on biophysics of synaptic transmission and introduction to neural computing. Laboratory and computer exercises illustrate the concepts. Students taking graduate version complete different assignments. Staff 9.07 Statistics for Brain and Cognitive Science
![]() ![]() Prereq: 6.100B Units: 4-0-8 ![]() Provides students with the basic tools for analyzing experimental data, properly interpreting statistical reports in the literature, and reasoning under uncertain situations. Topics organized around three key theories: probability, statistical, and the linear model. Probability theory covers axioms of probability, discrete and continuous probability models, law of large numbers, and the Central Limit Theorem. Statistical theory covers estimation, likelihood theory, Bayesian methods, bootstrap and other Monte Carlo methods, as well as hypothesis testing, confidence intervals, elementary design of experiments principles and goodness-of-fit. The linear model theory covers the simple regression model and the analysis of variance. Places equal emphasis on theory, data analyses, and simulation studies. E. Brown 9.073[J] Statistics for Neuroscience Research
![]() ![]() ![]() (Same subject as HST.460[J]) Prereq: Permission of instructor Units: 3-0-9 ![]() A survey of statistical methods for neuroscience research. Core topics include introductions to the theory of point processes, the generalized linear model, Monte Carlo methods, Bayesian methods, multivariate methods, time-series analysis, spectral analysis and state-space modeling. Emphasis on developing a firm conceptual understanding of the statistical paradigm and statistical methods primarily through analyses of actual experimental data. E. N. Brown 9.09[J] Cellular and Molecular Neurobiology
![]() ![]() (Same subject as 7.29[J]) Prereq: 7.05 or 9.01 Units: 4-0-8 Lecture: MW1-2.30 (46-3310) Recitation: F12 (46-3310) +final ![]() Introduction to the structure and function of the nervous system. Emphasizes the cellular properties of neurons and other excitable cells. Includes the structure and biophysical properties of excitable cells, synaptic transmission, neurochemistry, neurodevelopment, integration of information in simple systems, and detection and information coding during sensory transduction. T. Littleton, S. Prescott Textbooks (Spring 2025) 9.110[J] Nonlinear Control
![]() ![]() (Same subject as 2.152[J]) Prereq: 2.151, 6.7100, 16.31, or permission of instructor Units: 3-0-9 Lecture: TR1-2.30 (5-234) ![]() Introduction to nonlinear control and estimation in physical and biological systems. Nonlinear stability theory, Lyapunov analysis, Barbalat's lemma. Feedback linearization, differential flatness, internal dynamics. Sliding surfaces. Adaptive nonlinear control and estimation. Multiresolution bases, nonlinear system identification. Contraction analysis, differential stability theory. Nonlinear observers. Asynchronous distributed computation and learning. Concurrent synchronization, polyrhythms. Monotone nonlinear systems. Emphasizes application to physical systems (robots, aircraft, spacecraft, underwater vehicles, reaction-diffusion processes, machine vision, oscillators, internet), machine learning, computational neuroscience, and systems biology. Includes term projects. J. Slotine Textbooks (Spring 2025) 9.12 Experimental Molecular Neurobiology
![]() ![]() ![]() Prereq: Biology (GIR) and 9.01 Units: 2-4-6 Lecture: T3-5 (46-1015) Lab: F1-5 (46-1024) ![]() Experimental techniques in cellular and molecular neurobiology. Designed for students without previous experience in techniques of cellular and molecular biology. Experimental approaches include DNA manipulation, molecular cloning, protein biochemistry, dissection and culture of brain cells, synaptic protein analysis, immunocytochemistry, and fluorescent microscopy. One lab session plus one paper review session per week. Instruction and practice in written communication provided. Enrollment limited. G. Choi No textbook information available 9.123[J] Neurotechnology in Action
![]() ![]() (Same subject as 20.203[J]) Prereq: Permission of instructor Units: 3-6-3 Lecture: TR2.30-4 (46-4062) ![]() Offers a fast-paced introduction to numerous laboratory methods at the forefront of modern neurobiology. Comprises a sequence of modules focusing on neurotechnologies that are developed and used by MIT research groups. Each module consists of a background lecture and 1-2 days of firsthand laboratory experience. Topics typically include optical imaging, optogenetics, high throughput neurobiology, MRI/fMRI, advanced electrophysiology, viral and genetic tools, and connectomics. E. Boyden, M. Jonas No textbook information available 9.13 The Human Brain
![]() ![]() Prereq: 9.00, 9.01, or permission of instructor Units: 3-0-9 Lecture: MW11-12.30 (46-3002) +final ![]() Surveys the core perceptual and cognitive abilities of the human mind and asks how these are implemented in the brain. Key themes include the functional organization of the cortex, as well as the representations and computations, developmental origins, and degree of functional specificity of particular cortical regions. Emphasizes the methods available in human cognitive neuroscience, and what inferences can and cannot be drawn from each. N. Kanwisher No textbook information available 9.17 Systems Neuroscience Laboratory
![]() ![]() ![]() Prereq: 9.01 or permission of instructor Units: 2-4-6 ![]() Consists of a series of laboratories designed to give students experience with basic techniques for conducting systems neuroscience research. Includes sessions on anatomical, neurophysiological, and data acquisition and analysis techniques, and how these techniques are used to study nervous system function. Involves the use of experimental animals. Assignments include weekly preparation for lab sessions, two major lab reports and a series of basic computer programming tutorials (MATLAB). Instruction and practice in written communication provided. Enrollment limited. Frawley 9.175[J] Robotics
![]() ![]() (Same subject as 2.165[J]) Prereq: 2.151 or permission of instructor Units: 3-0-9 ![]() Introduction to robotics and learning in machines. Kinematics and dynamics of rigid body systems. Adaptive control, system identification, sparse representations. Force control, adaptive visual servoing. Task planning, teleoperation, imitation learning. Navigation. Underactuated systems, approximate optimization and control. Dynamics of learning and optimization in networks. Elements of biological planning and control. Motor primitives, entrainment, active sensing, binding models. Term projects. J-J Slotine 9.18[J] Developmental Neurobiology
![]() ![]() (Same subject as 7.49[J]) (Subject meets with 7.69[J], 9.181[J]) Prereq: 7.03, 7.05, 9.01, or permission of instructor Units: 3-0-9 Lecture: TR2.30-4 (46-3037) Recitation: T4 (46-3037) ![]() Considers molecular control of neural specification, formation of neuronal connections, construction of neural systems, and the contributions of experience to shaping brain structure and function. Topics include: neural induction and pattern formation, cell lineage and fate determination, neuronal migration, axon guidance, synapse formation and stabilization, activity-dependent development and critical periods, development of behavior. Students taking graduate version complete additional readings that will be addressed in their mid-term and final exams. E. Nedivi, S. Prescott Textbooks (Spring 2025) 9.181[J] Developmental Neurobiology
![]() ![]() (Same subject as 7.69[J]) (Subject meets with 7.49[J], 9.18[J]) Prereq: 9.011 or permission of instructor Units: 3-0-9 Lecture: TR2.30-4 (46-3037) Recitation: T4 (46-3037) ![]() Considers molecular control of neural specification, formation of neuronal connections, construction of neural systems, and the contributions of experience to shaping brain structure and function. Topics include: neural induction and pattern formation, cell lineage and fate determination, neuronal migration, axon guidance, synapse formation and stabilization, activity-dependent development and critical periods, development of behavior. In addition to final exam, analysis and presentation of research papers required for final grade. Students taking graduate version complete additional assignments. Students taking graduate version complete additional readings that will be addressed in their mid-term and final exams. E. Nedivi, S. Prescott Textbooks (Spring 2025) 9.19 Computational Psycholinguistics
![]() ![]() ![]() (Subject meets with 9.190) Prereq: (6.100B and (6.3700, 9.40, or 24.900)) or permission of instructor Units: 4-0-8 ![]() Introduces computational approaches to natural language processing and acquisition by humans and machines, combining symbolic and probabilistic modeling techniques. Covers models such as n-grams, finite state automata, and context-free and mildly context-sensitive grammars, for analyzing phonology, morphology, syntax, semantics, pragmatics, and larger document structure. Applications range from accurate document classification and sentence parsing by machine to modeling human language acquisition and real-time understanding. Covers both theory and contemporary computational tools and datasets. Students taking graduate version complete additional assignments. Staff 9.190 Computational Psycholinguistics
![]() ![]() ![]() (Subject meets with 9.19) Prereq: (6.100B and (6.3702, 9.40, or 24.900)) or permission of instructor Units: 4-0-8 ![]() Introduces computational approaches to natural language processing and acquisition by humans and machines, combining symbolic and probabilistic modeling techniques. Covers models such as n-grams, finite state automata, and context-free and mildly context-sensitive grammars, for analyzing phonology, morphology, syntax, semantics, pragmatics, and larger document structure. Applications range from accurate document classification and sentence parsing by machine to modeling human language acquisition and real-time understanding. Covers both theory and contemporary computational tools and datasets. Students taking graduate version complete additional assignments. R. P. Levy 9.21[J] Cellular Neurophysiology and Computing
![]() ![]() ![]() (Same subject as 2.791[J], 6.4810[J], 20.370[J]) (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)) or permission of instructor Units: 5-2-5 ![]() ![]() Integrated overview of the biophysics of cells from prokaryotes to neurons, with a focus on mass transport and electrical signal generation across cell membrane. First third of course focuses on mass transport through membranes: diffusion, osmosis, chemically mediated, and active transport. Second third focuses on electrical properties of cells: ion transport to action potential generation and propagation in electrically excitable cells. Synaptic transmission. Electrical properties interpreted via kinetic and molecular properties of single voltage-gated ion channels. Final third focuses on biophysics of synaptic transmission and introduction to neural computing. Laboratory and computer exercises illustrate the concepts. Students taking graduate version complete different assignments. Preference to juniors and seniors. Staff 9.24 Disorders and Diseases of the Nervous System
![]() ![]() Prereq: (7.29 and 9.01) or permission of instructor Units: 3-0-9 Lecture: F1-4 (46-3310) +final ![]() Topics examined include regional functional anatomy of the CNS; brain systems and circuits; neurodevelopmental disorders including autism; neuropsychiatric disorders such as schizophrenia; neurodegenerative diseases such as Parkinson's and Alzheimer's; autoimmune disorders such as multiple sclerosis; gliomas. Emphasis on diseases for which a molecular mechanism is understood. Diagnostic criteria, clinical and pathological findings, genetics, model systems, pathophysiology, and treatment are discussed for individual disorders and diseases. Limited to 18. M. Sur No textbook information available 9.26[J] Principles and Applications of Genetic Engineering for Biotechnology and Neuroscience
![]() ![]() (Same subject as 20.205[J]) Prereq: Biology (GIR) Units: 3-0-9 Lecture: F10-1 (BROAD) ![]() Covers principles underlying current and future genetic engineering approaches, ranging from single cellular organisms to whole animals. Focuses on development and invention of technologies for engineering biological systems at the genomic level, and applications of engineered biological systems for medical and biotechnological needs, with particular emphasis on genetic manipulation of the nervous system. Design projects by students. F. Zhang No textbook information available 9.271[J] Pioneering Technologies for Interrogating Complex Biological Systems
![]() ![]() (Same subject as 10.562[J], HST.562[J]) Prereq: None Units: 3-0-9 Lecture: TR11-12.30 (46-6199) ![]() Introduces pioneering technologies in biology and medicine and discusses their underlying biological/molecular/engineering principles. Topics include emerging sample processing technologies, advanced optical imaging modalities, and next-gen molecular phenotyping techniques. Provides practical experience with optical microscopy and 3D phenotyping techniques. Limited to 15. K. Chung No textbook information available 9.272[J] Topics in Neural Signal Processing
![]() ![]() Not offered regularly; consult department (Same subject as HST.576[J]) Prereq: Permission of instructor Units: 3-0-9 ![]() ![]() Presents signal processing and statistical methods used to study neural systems and analyze neurophysiological data. Topics include state-space modeling formulated using the Bayesian Chapman-Kolmogorov system, theory of point processes, EM algorithm, Bayesian and sequential Monte Carlo methods. Applications include dynamic analyses of neural encoding, neural spike train decoding, studies of neural receptive field plasticity, algorithms for neural prosthetic control, EEG and MEG source localization. Students should know introductory probability theory and statistics. E. N. Brown No textbook information available 9.285[J] Audition: Neural Mechanisms, Perception and Cognition
![]() ![]() (Same subject as HST.723[J]) Prereq: Permission of instructor Units: 6-0-6 Begins 1/27. Follows fas schedule. Mee 403a to begin term. 46-5193 to complete term. Lecture: MWF9.30-11.30 (46-5193) ![]() Neural structures and mechanisms mediating the detection, localization and recognition of sounds. General principles are conveyed by theme discussions of auditory masking, sound localization, musical pitch, cochlear implants, cortical plasticity and auditory scene analysis. Follows Harvard FAS calendar. A. Takesian, J. McDermott, D. Polley, D. Mehta No textbook information available 9.301[J] Neural Plasticity in Learning and Memory
![]() ![]() Not offered regularly; consult department (Same subject as 7.98[J]) Prereq: Permission of instructor Units: 3-0-9 ![]() Examination of the role of neural plasticity during learning and memory of invertebrates and mammals. Detailed critical analysis of the current literature of molecular, cellular, genetic, electrophysiological, and behavioral studies. Student-directed presentations and discussions of original papers supplemented by introductory lectures. Juniors and seniors require instructor's permission. Staff 9.32 Genes, Circuits, and Behavior
![]() ![]() Not offered regularly; consult department Prereq: 7.29, 9.16, 9.18, or permission of instructor Units: 3-0-9 ![]() Focuses on understanding molecular and cellular mechanisms of circuitry development, function and plasticity, and their relevance to normal and abnormal behaviors/psychiatric disorders. Highlights cutting-edge technologies for neuroscience research. Students build professional skills through presentations and critical evaluation of original research papers. G. Feng 9.34[J] Biomechanics and Neural Control of Movement
![]() ![]() (Same subject as 2.183[J]) (Subject meets with 2.184) Prereq: 2.004 or permission of instructor Units: 3-0-9 Lecture: TR1-2.30 (1-242) ![]() Presents a quantitative description of how biomechanical and neural factors interact in human sensory-motor behavior. Students survey recent literature on how motor behavior is controlled, comparing biological and robotic approaches to similar tasks. Topics may include a review of relevant neural, muscular and skeletal physiology, neural feedback and "equilibrium-point" theories, co-contraction strategies, impedance control, kinematic redundancy, optimization, intermittency, contact tasks and tool use. Students taking graduate version complete additional assignments. N. Hogan No textbook information available 9.35 Perception
![]() ![]() Prereq: 9.01 or permission of instructor Units: 4-0-8 Lecture: TR2.30-4 (46-3189) Recitation: F11 (46-5313) +final ![]() 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 No required or recommended textbooks 9.357 Current Topics in Perception
![]() ![]() ![]() Prereq: Permission of instructor Units: 2-0-7 Lecture: M3-5 (32-262) ![]() Advanced seminar on issues of current interest in human and machine vision. Topics vary from year to year. Participants discuss current literature as well as their ongoing research. E. H. Adelson No textbook information available 9.36 Neurobiology of Self
![]() ![]() (Subject meets with 9.360) Prereq: 9.01 Units: 3-0-9 ![]() Discusses the neurobiological mechanisms that distinguish "the Self" from external environment; the neural circuits that enable us to know that "the Self" is in pain, or feels hungry, thirsty, and tired; and the neurons and circuits that lead to the emotional and moody Self. Examines brain mechanism that encodes the body schema and the Self in space. This includes the neural computations that 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 9.360 Neurobiology of Self
![]() ![]() (Subject meets with 9.36) Prereq: 9.01 Units: 3-0-9 ![]() Discusses the neurobiological mechanisms that distinguish "the Self" from external environment; the neural circuits that enable us to know that "the Self" is in pain, or feels hungry, thirsty, and tired; and the neurons and circuits that lead to the emotional and moody Self. Examines brain mechanism that encodes the body schema and the Self in space. This includes the neural computations that 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 9.39 Language in the Mind and Brain
![]() ![]() Not offered regularly; consult department (Subject meets with 9.390) Prereq: 9.00, 9.01, or permission of instructor Units: 3-0-9 ![]() ![]() Surveys the core mental abilities — and their neural substrates — that support language, and situates them within the broader landscape of human cognition. Topics explored include: how structured representations are extracted from language; the nature of abstract concepts and how they relate to words; the nature of the brain mechanisms that support language vs. other structured and/or meaningful inputs, like music, mathematical expressions, or pictures; the relationship between language and social cognition; how language is processed in individuals who speak multiple languages; how animal communication systems and artificial neural network language models differ from human language. Draws on evidence from diverse approaches and populations, focusing on cutting-edge research. Students taking graduate version complete additional assignments. Staff 9.390 Language in the Mind and Brain
![]() ![]() Not offered regularly; consult department (Subject meets with 9.39) Prereq: 9.00, 9.01, or permission of instructor Units: 3-0-9 ![]() ![]() Surveys the core mental abilities — and their neural substrates — that support language, and situates them within the broader landscape of human cognition. Topics explored include: how structured representations are extracted from language; the nature of abstract concepts and how they relate to words; the nature of the brain mechanisms that support language vs. other structured and/or meaningful inputs, like music, mathematical expressions, or pictures; the relationship between language and social cognition; how language is processed in individuals who speak multiple languages; how animal communication systems and artificial neural network language models differ from human language. Draws on evidence from diverse approaches and populations, focusing on cutting-edge research. Students taking graduate version complete additional assignments. E. Fedorenko 9.40 Introduction to Neural Computation
![]() ![]() Prereq: (Physics II (GIR), 6.100B, and 9.01) or permission of instructor Units: 4-0-8 Lecture: TR10-12 (46-3189) +final ![]() Introduces quantitative approaches to understanding brain and cognitive functions. Topics include mathematical description of neurons, the response of neurons to sensory stimuli, simple neuronal networks, statistical inference and decision making. Also covers foundational quantitative tools of data analysis in neuroscience: correlation, convolution, spectral analysis, principal components analysis. Mathematical concepts include simple differential equations and linear algebra. J. DiCarlo No required or recommended textbooks 9.401 Tools for Robust Science
![]() ![]() Prereq: None Units: 3-0-9 Lecture: T9-12 (46-3037) ![]() New tools are being developed to improve credibility, facilitate collaboration, accelerate scientific discovery, and expedite translation of results. Students (i) identify obstacles to conducting robust cognitive and neuroscientific research, (ii) practice using current cutting-edge tools designed to overcome these obstacles by improving scientific practices and incentives, and (iii) critically evaluate these tools' potential and limitations. Example tools investigated include shared pre-registration, experimental design, data management plans, meta-data standards, repositories, FAIR code, open-source data processing pipelines, alternatives to scientific paper formats, alternative publishing agreements, citation audits, reformulated incentives for hiring and promotion, and more. R. Saxe No textbook information available 9.41 Research and Communication in Neuroscience and Cognitive Science
![]() ![]() Prereq: 9.URG and permission of instructor Units: 2-12-4 ![]() Emphasizes research and scientific communication. Instruction and practice in written and oral communication provided. Based on results of his/her UROP research, each student creates a full-length paper and a poster as part of an oral presentation at the end of the term. Other assignments include peer editing and reading/critiquing published research papers. Prior to starting class, students must have collected enough data from their UROP research projects to write a paper. Limited to juniors and seniors. M. Wilson 9.42 The Brain and Its Interface with the Body
![]() ![]() Not offered regularly; consult department Prereq: 7.28, 7.29, or permission of instructor Units: 3-0-9 ![]() Covers a range of topics, such as brain-immune system interaction, the gut-brain axis, and bioengineering approaches for studying the brain and its interactions with different organs. Explores how these interactions may be involved in nervous system disease processes. F. Zhang 9.422[J] Principles of Neuroengineering
![]() ![]() (Same subject as 20.452[J], MAS.881[J]) (Subject meets with 20.352) Prereq: Permission of instructor Units: 3-0-9 ![]() Covers how to innovate technologies for brain analysis and engineering, for accelerating the basic understanding of the brain, and leading to new therapeutic insight and inventions. Focuses on using physical, chemical and biological principles to understand technology design criteria governing ability to observe and alter brain structure and function. Topics include optogenetics, noninvasive brain imaging and stimulation, nanotechnologies, stem cells and tissue engineering, and advanced molecular and structural imaging technologies. Includes design projects. Designed for students with engineering maturity who are ready for design. Students taking graduate version complete additional assignments. E. S. Boyden, III 9.455[J] Revolutionary Ventures: How to Invent and Deploy Transformative Technologies
![]() ![]() (Same subject as 15.128[J], 20.454[J], MAS.883[J]) Prereq: Permission of instructor Units: 2-0-7 ![]() Seminar on envisioning and building ideas and organizations to accelerate engineering revolutions. Focuses on emerging technology domains, such as neurotechnology, imaging, cryotechnology, gerontechnology, and bio-and-nano fabrication. Draws on historical examples as well as live case studies of existing or emerging organizations, including labs, institutes, startups, and companies. Goals range from accelerating basic science to developing transformative products or therapeutics. Each class is devoted to a specific area, often with invited speakers, exploring issues from the deeply technical through the strategic. Individually or in small groups, students prototype new ventures aimed at inventing and deploying revolutionary technologies. E. Boyden, J. Bonsen, J. Jacobson 9.48[J] Philosophical Issues in Brain Science
![]() ![]() ![]() ![]() ![]() (Same subject as 24.08[J]) Prereq: None Units: 3-0-9 ![]() An introduction to some central philosophical questions about the mind, specifically those intimately connected with contemporary psychology and neuroscience. Discussions focus on arguments over innate concepts; 'mental images' as pictures in the head; whether color is in the mind or in the world; and whether there can be a science of consciousness. Explains the relevant parts of psychology and neuroscience as the subject proceeds. Staff 9.49 Neural Circuits for Cognition
![]() ![]() (Subject meets with 9.490) Prereq: 9.40, 18.06, or permission of instructor Units: 3-0-9 ![]() Takes a computational approach to examine circuits in the brain that perform elemental cognitive tasks: tasks that are neither directly sensory nor directly motor in function, but are essential to bridging from perception to action. Covers circuits and circuit motifs in the brain that underlie computations like integration, decision-making, spatial navigation, inference, and other cognitive elements. Students study empirical results, build dynamical models of neural circuits, and examine the mathematical theory of representations and computation in such circuits. Considers noise, stability, plasticity, and learning rules for these systems. Students taking graduate version complete additional assignments. I. Fiete 9.490 Neural Circuits for Cognition
![]() ![]() (Subject meets with 9.49) Prereq: 9.40, 18.06, or permission of instructor Units: 3-0-9 ![]() Takes a computational approach to examine circuits in the brain that perform elemental cognitive tasks: tasks that are neither directly sensory nor directly motor in function, but are essential to bridging from perception to action. Covers circuits and circuit motifs in the brain that underlie computations like integration, decision-making, spatial navigation, inference, and other cognitive elements. Students study empirical results, build dynamical models of neural circuits, and examine the mathematical theory of representations and computation in such circuits. Considers noise, stability, plasticity, and learning rules for these systems. Students taking graduate version complete additional assignments. I. Fiete |
![]() | | | 9.00-9.499 | | | 9.50-9.999 plus Thesis, UROP | | | ![]() |