CNS 100
Introduction to Computation and Neural Systems
1 unit
|
first term
This course is designed to introduce undergraduate and first-year CNS graduate students to the wide variety of research being undertaken by CNS faculty. Topics from all the CNS research labs are discussed and span the range from biology to engineering. Graded pass/fail.
Instructor:
Perona
CNS/SS/Psy/Bi 102 ab
Brains, Minds, and Society
9 units (3-0-6)
|
second, third terms
Prerequisites: Bi/CNS/NB 150 and CNS/Bi/Ph/CS/NB 187, or instructor's permission.
Introduction to the computations made by the brain during economic and social decision making and their neural substrates. First quarter: Signal detection theory. Unconscious and conscious processing. Emotion and the somatic marker hypothesis. Perceptual decision making. Reinforcement learning. Goal and habit learning. Facial processing in social neuroscience. Second quarter: Optimal Bayesian decision making and prospect theory. Standard and behavioral game theory. Evolution and group decision making. Collective decision making by animals. Exploration. Risk learning. Probabilistic sophistication. Part b not offered 2014-15; part a offered WI term 2014-15.
Instructors:
Adolphs, O'Doherty
Psy/CNS 105 ab
Frontiers in Neuroeconomics
5 units (1.5-0-3.5)
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first term
The new discipline of Neuroeconomics seeks to understand the mechanisms underlying human choice behavior, born out of a confluence of approaches derived from Psychology, Neuroscience and Economics. This seminar will consider a variety of emerging themes in this new field. Some of the topics we will address include the neural bases of reward and motivation, the neural representation of utility and risk, neural systems for inter-temporal choice, goals vs habits, and strategic interactions. We will also spend time evaluating various forms of computational and theoretical models that underpin the field such as reinforcement-learning, Bayesian models and race to barrier models. Each week we will focus on key papers and/or book chapters illustrating the relevant concepts.
Instructor:
O'Doherty
CNS/SS/Psy 110 abc
Cognitive Neuroscience Tools
5 units (1.5-0-3.5)
|
a = third term
This course covers tools and statistical methods used in cognitive neuroscience research. Topics vary from year to year depending on the interests of the students. Recent topics include statistical modeling for fMRI data, experimental design for fMRI, and the preprocessing of fMRI data; part a offered spring term; bc not offered 2014-15.
Psy/CNS 130
Introduction to Human Memory
9 units (3-0-6)
|
second term
The course offers an overview of experimental findings and theoretical issues in the study of human memory. Topics include iconic and echoic memory, working memory, spatial memory, implicit learning and memory; forgetting: facts vs. skills, memory for faces; retrieval: recall vs. recognition, context-dependent memory, semantic memory, spreading activation models and connectionist networks, memory and emotion, infantile amnesia, memory development, and amnesia. Not offered 2014-15.
CNS/Psy/Bi 131
The Psychology of Learning and Motivation
9 units (3-0-6)
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second term
This course will serve as an introduction to basic concepts, findings, and theory from the field of behavioral psychology, covering areas such as principles of classical conditioning, blocking and conditioned inhibition, models of classical conditioning, instrumental conditioning, reinforcement schedules, punishment and avoidance learning. The course will track the development of ideas from the beginnings of behavioral psychology in the early 20th century to contemporary learning theory. Not offered 2014-15.
EE/CNS/CS 148 ab
Selected Topics in Computational Vision
9 units (3-0-6)
|
first, third terms
Prerequisites: undergraduate calculus, linear algebra, geometry, statistics, computer programming. EE 148a is not a prerequisite for EE 148b.
The class will focus on an advanced topic in computational vision: recognition, vision-based navigation, 3-D reconstruction. The class will include a tutorial introduction to the topic, an exploration of relevant recent literature, and a project involving the design, implementation, and testing of a vision system. Part a not offered 2014-15; Part b offered 2014-15.
Instructor:
Perona
Bi/CNS/NB 150
Introduction to Neuroscience
10 units (4-0-6)
|
first term
Prerequisites: Bi 8, 9, or instructors' permission.
General principles of the function and organization of nervous systems, providing both an overview of the subject and a foundation for advanced courses. Topics include the physical and chemical bases for action potentials, synaptic transmission, and sensory transduction; anatomy; development; sensory and motor pathways; memory and learning at the molecular, cellular, and systems level; and the neuroscience of brain diseases.
Instructors:
Adolphs, Lester
Bi/CNS/NB 153
Brain Circuits
9 units (3-0-6)
|
second term
Prerequisites: Bi/CNS/NB 150 or equivalent.
What functions arise when many thousands of neurons combine in a densely connected circuit? Though the operations of neural circuits lie at the very heart of brain science, our textbooks have little to say on the topic. Through an alternation of lecture and discussion this course explores the empirical observations in this field and the analytical approaches needed to make sense of them. We begin with a foray into sensory and motor systems, consider what basic functions they need to accomplish, and examine what neural circuits are involved. Next we explore whether the circuit motifs encountered are also found in central brain areas, with an emphasis on sensory-motor integration and learning. Finally we discuss design principles for neural circuits and what constraints have shaped their structure and function in the course of evolution. Given in alternate years; offered 2014-15.
Instructor:
Meister
CS/CNS/EE/NB 154
Artificial Intelligence
9 units (3-3-3)
|
first term
Prerequisites: Ma 2 b or equivalent, and CS 1 or equivalent.
How can we build systems that perform well in unk nown environments and unforeseen situations? How can we develop systems that exhibit "intelligent" behavior, without prescribing explicit rules? How can we build systems that learn from experience in order to improve their performance? We will study core modeling techniques and algorithms from statistics, optimization, planning, and control and study applications in areas such as sensor networks, robotics, and the Internet. The course is designed for upper-level undergraduate and graduate students. Not offered 2014-15.
CS/CNS/EE 155
Machine Learning Data Mining
9 units (3-3-3)
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second term
Prerequisites: background in algorithms and statistics (CS/CNS/EE/NB 154 or CS/CNS/EE 156 a or instructor's permission).
This course will cover popular methods in machine learning and data mining, with an emphasis on developing a working understanding of how to apply these methods in practice. This course will also cover core foundational concepts underpinning and motivating modern machine learning and data mining approaches. This course will be research-oriented, and will cover recent research developments.
Instructor:
Yue
CS/CNS/EE 156 ab
Learning Systems
9 units (3-0-6)
|
first, third terms
Prerequisites: Ma 2 and CS 2, or equivalent.
Introduction to the theory, algorithms, and applications of automated learning. How much information is needed to learn a task, how much computation is involved, and how it can be accomplished. Special emphasis will be given to unifying the different approaches to the subject coming from statistics, function approximation, optimization, pattern recognition, and neural networks.
Instructor:
Abu-Mostafa
Bi/CNS/NB 157
Comparative Nervous Systems
9 units (2-3-4)
|
third term
Prerequisites: instructor's permission.
An introduction to the comparative study of the gross and microscopic structure of nervous systems. Emphasis on the vertebrate nervous system; also, the highly developed central nervous systems found in arthropods and cephalopods. Variation in nervous system structure with function and with behavioral and ecological specializations and the evolution of the vertebrate brain. Letter grades only. Given in alternate years; offered 2014-15.
Instructor:
Allman
Bi/CNS 158
Vertebrate Evolution
9 units (3-0-6)
|
third term
Prerequisites: Bi 1, Bi 8, or instructor's permission.
An integrative approach to the study of vertebrate evolution combining comparative anatomical, behavioral, embryological, genetic, paleontological, and physiological findings. Special emphasis will be given to: (1) the modification of developmental programs in evolution; (2) homeostatic systems for temperature regulation; (3) changes in the life cycle governing longevity and death; (4) the evolution of brain and behavior. Letter grades only. Given in alternate years; not offered 2014-15.
Instructor:
Allman
CS/CNS/EE 159
Projects in Machine Learning and AI
9 units (0-0-9)
|
third term
Prerequisites: Two terms from the "Learning & Vision" project sequence.
Students are expected to execute a substantial project in AI and/or machine learning, write up a report describing their work, and make a presentation. Not offered 2014-15.
Bi/CNS/NB 162
Cellular and Systems Neuroscience Laboratory
12 units (2-7-3)
|
third term
Prerequisites: Bi/CNS/NB 150 or instructor's permission.
A laboratory-based introduction to experimental methods used for electrophysiological studies of the central nervous system. Through the term, students investigate the physiological response properties of neurons in insect and mammalian brains, using extra- and intracellular recording techniques. Students are instructed in all aspects of experimental procedures, including proper surgical techniques, electrode fabrication, stimulus presentation, and computer-based data analysis. Graded pass/fail.
Instructor:
Staff
Bi/CNS/NB 164
Tools of Neurobiology
9 units (3-0-6)
|
second term
Prerequisites: Bi/CNS/NB 150 or equivalent.
Offers a broad survey of methods and approaches to understanding in modern neurobiology. The focus is on understanding the tools of the discipline, and their use will be illustrated with current research results. Topics include: molecular genetics, disease models, transgenic and knock-in technology, virus tools, tracing methods, gene profiling, light and electron microscopy, optogenetics, optical and electrical recording, neural coding, quantitative behavior, modeling and theory.
Instructor:
Meister
CS/CNS 171
Introduction to Computer Graphics Laboratory
12 units (3-6-3)
|
first term
Prerequisites: Ma 2 and extensive programming experience.
This course introduces the basic ideas behind computer graphics and its fundamental algorithms. Topics include graphics input and output, the graphics pipeline, sampling and image manipulation, three-dimensional transformations and interactive modeling, basics of physically based modeling and animation, simple shading models and their hardware implementation, and fundamental algorithms of scientific visualization. Students will be required to perform significant implementations.
Instructor:
Barr
CS/CNS 174
Computer Graphics Projects
12 units (3-6-3)
|
third term
Prerequisites: Ma 2 and CS/CNS 171 or instructor's permission.
This laboratory class offers students an opportunity for independent work covering recent computer graphics research. In coordination with the instructor, students select a computer graphics modeling, rendering, interaction, or related algorithm and implement it. Students are required to present their work in class and discuss the results of their implementation and any possible improvements to the basic methods. May be repeated for credit with instructor's permission.
Instructor:
Barr
CNS/Bi/SS/Psy/NB 176
Cognition
12 units (6-0-6)
|
third term
The cornerstone of current progress in understanding the mind, the brain, and the relationship between the two is the study of human and animal cognition. This course will provide an in-depth survey and analysis of behavioral observations, theoretical accounts, computational models, patient data, electrophysiological studies, and brain-imaging results on mental capacities such as attention, memory, emotion, object representation, language, and cognitive development. Offered 2014-15.
Instructor:
Shimojo
Bi/CNS/NB 184
The Primate Visual System
9 units (3-1-5)
|
third term
This class focuses on the primate visual system, investigating it from an experimental, psychophysical, and computational perspective. The course will focus on two essential problems: 3-D vision and object recognition. Topics include parallel processing pathways, functional specialization, prosopagnosia, object detection and identification, invariance, stereopsis, surface perception, scene perception, navigation, visual memory, multidimensional readout, signal detection theory, oscillations, and synchrony. It will examine how a visual stimulus is represented starting in the retina, and ending in the frontal lobe, with a special emphasis placed on mechanisms for high-level vision in the parietal and temporal lobes. The course will include a lab component in which students design and analyze their own fMRI experiment. Given in alternate years; offered 2014-15.
Instructor:
Tsao
Bi/CNS/NB 185
Large Scale Brain Networks
6 units (2-0-4)
|
third term
This class will focus on understanding what is known about the large-scale organization of the brain, focusing on the mammalian brain. What large scale brain networks exist and what are their principles of function? How is information flexibly routed from one area to another? What is the function of thalamocortical loops? We will examine large scale networks revealed by anatomical tracing, functional connectivity studies, and mRNA expression analyses, and explore the brain circuits mediating complex behaviors such as attention, memory, sleep, multisensory integration, decision making, and object vision. While each of these topics could cover an entire course in itself, our focus will be on understanding the master plan--how the components of each of these systems are put together and function as a whole. A key question we will delve into, from both a biological and a theoretical perspective, is: how is information flexibly routed from one brain area to another? We will discuss the communication through coherence hypothesis, small world networks, and sparse coding. Given in alternate years, not offered 2014-15.
Instructor:
Tsao
CNS/Bi/EE/CS 186
Vision: From Computational Theory to Neuronal Mechanisms
12 units (4-4-4)
|
second term
Lecture, laboratory, and project course aimed at understanding visual information processing, in both machines and the mammalian visual system. The course will emphasize an interdisciplinary approach aimed at understanding vision at several levels: computational theory, algorithms, psychophysics, and hardware (i.e., neuroanatomy and neurophysiology of the mammalian visual system). The course will focus on early vision processes, in particular motion analysis, binocular stereo, brightness, color and texture analysis, visual attention and boundary detection. Students will be required to hand in approximately three homework assignments as well as complete one project integrating aspects of mathematical analysis, modeling, physiology, psychophysics, and engineering. Given in alternate years; not offered 2014-15.
CNS/Bi/Ph/CS/NB 187
Neural Computation
9 units (3-0-6)
|
first term
Prerequisites: familiarity with digital circuits, probability theory, linear algebra, and differential equations. Programming will be required.
This course investigates computation by neurons. Of primary concern are models of neural computation and their neurological substrate, as well as the physics of collective computation. Thus, neurobiology is used as a motivating factor to introduce the relevant algorithms. Topics include rate-code neural networks, their differential equations, and equivalent circuits; stochastic models and their energy functions; associative memory; supervised and unsupervised learning; development; spike-based computing; single-cell computation; error and noise tolerance.
Instructor:
Perona
BE/CS/CNS/Bi 191 ab
Biomolecular Computation
9 units (3-0-6 a), (2-4-3 b)
|
second, third terms
Prerequisites: none. Recommended: ChE/BE 163, CS 21, CS 129 ab, or equivalent.
This course investigates computation by molecular systems, emphasizing models of computation based on the underlying physics, chemistry, and organization of biological cells. We will explore programmability, complexity, simulation of and reasoning about abstract models of chemical reaction networks, molecular folding, molecular self-assembly, and molecular motors, with an emphasis on universal architectures for computation, control, and construction within molecular systems. If time permits, we will also discuss biological example systems such as signal transduction, genetic regulatory networks, and the cytoskeleton; physical limits of computation, reversibility, reliability, and the role of noise, DNA-based computers and DNA nanotechnology. Part a develops fundamental results; part b is a reading and research course: classic and current papers will be discussed, and students will do projects on current research topics.
Instructor:
Winfree
Bi/CNS/NB 195
Mathematics in Biology
9 units (3-0-6)
|
second term
Prerequisites: Multi-variable calculus.
This course develops the mathematical methods needed for a quantitative understanding of biological phenomena, including data analysis, formulation of simple models, and the framing of quantitative questions. Topics include: probability and stochastic processes, linear algebra and transforms, dynamical systems, MATLAB programming. Given in alternate years; not offered 2014-15.
Instructor:
Meister
Bi/CNS/NB 216
Behavior of Mammals
6 units (2-0-4)
|
first term
A course of lectures, readings, and discussions focused on the genetic, physiological, and ecological bases of behavior in mammals. A basic knowledge of neuroanatomy and neurophysiology is desirable. Given in alternate years; not offered 2014-15.
Instructor:
Allman
Bi/CNS/NB 217
Central Mechanisms in Perception
6 units (2-0-4)
|
first term
Reading and discussions of behavioral and electrophysiological studies of the systems for the processing of sensory information in the brain. Given in alternate years; offered 2014-15.
Instructor:
Allman
Bi/CNS/NB 220
Genetic Dissection of Neural Circuit Function
6 units (2-0-4)
|
second term
This advanced course will discuss the emerging science of neural "circuit breaking" through the application of molecular genetic tools. These include optogenetic and pharmacogenetic manipulations of neuronal activity, genetically based tracing of neuronal connectivity, and genetically based indicators of neuronal activity. Both viral and transgenic approaches will be covered, and examples will be drawn from both the invertebrate and vertebrate literature. Interested students who have little or no familiarity with molecular biology will be supplied with the necessary background information. Lectures and student presentations from the current literature.
Instructor:
Anderson
Bi/CNS/BE/NB 230
Optogenetic Methods in Experimental Neuroscience
9 units (3-1-5)
|
third term
Prerequisites: Graduate standing or Bi/CNS/NB 150 and instructor permission.
The class covers the theoretical and practical aspects of optogenetic control and complementary readout methods in molecular, cellular, and systems neuroscience. Topics include opsin design (including natural and artificial sources), delivery (genetic targeting, viral transduction), light activation requirements (power requirements, wavelength, fiberoptics, LEDs), compatible readout modalities (electrophysiology, imaging) and applications to neuronal circuits (case studies based on recent literature). The class offers hands-on lab exposure for opsin delivery to the mammalian brain and recording of brain activity modulated by light.
Instructor:
Gradinaru
CNS/Bi/NB 247
Cerebral Cortex
6 units (2-0-4)
|
second term
Prerequisites: Bi/CNS/NB 150 or equivalent.
A general survey of the structure and function of the cerebral cortex. Topics include cortical anatomy, functional localization, and newer computational approaches to understanding cortical processing operations. Motor cortex, sensory cortex (visual, auditory, and somatosensory cortex), association cortex, and limbic cortex. Emphasis is on using animal models to understand human cortical function and includes correlations between animal studies and human neuropsychological and functional imaging literature. Given in alternate years; offered 2014-15.
Instructor:
Andersen
Bi/CNS/NB 250 c
Topics in Systems Neuroscience
9 units (3-0-6)
|
third term
Prerequisites: graduate standing.
The class focuses on quantitative studies of problems in systems neuroscience. Students will study classical work such as Hodgkin and Huxley's landmark papers on the ionic basis of the action potential, and will move from the study of interacting currents within neurons to the study of systems of interacting neurons. Topics will include lateral inhibition, mechanisms of motion tuning, local learning rules and their consequences for network structure and dynamics, oscillatory dynamics and synchronization across brain circuits, and formation and computational properties of topographic neural maps. The course will combine lectures and discussions, in which students and faculty will examine papers on systems neuroscience, usually combining experimental and theoretical/modeling components.
Instructor:
Siapas
CNS/SS 251
Human Brain Mapping: Theory and Practice
9 units (2-1-6)
|
second term
A course in functional brain imaging. An overview of contemporary brain imaging techniques, usefulness of brain imaging compared to other techniques available to the modern neuroscientist. Review of what is known about the physical and biological bases of the signals being measured. Design and implementation of a brain imaging experiment and analysis of data (with a particular emphasis on fMRI).
Instructor:
O'Doherty
CS/CNS/EE 253
Special Topics in Machine Learning
9 units (3-3-3)
Prerequisites: CS/CNS/EE/NB 154 or CS/CNS/EE 156 a or instructor's permission.
This course is an advanced, research-oriented seminar in machine learning and AI meant for graduate students and advanced undergraduates. The topics covered in the course will vary, but will always come from the cutting edge of machine learning and AI research. Examples of possible topics are active learning and optimized information gathering, AI in distributed systems, computational learning theory, machine learning applications (on the Web, in sensor networks and robotics). Not offered 2014-15.
SS/Psy/Bi/CNS 255
Topics in Emotion and Social Cognition
9 units (3-0-6)
|
third term
Prerequisites: Bi/CNS/NB 150 or instructor's permission.
This course will cover recent findings in the psychology and neurobiology of emotion and social behavior. What role does emotion play in other cognitive processes, such as memory, attention, and decision making? What are the component processes that guide social behavior? To what extent is the processing of social information domain-specific? Readings from the current literature will emphasize functional imaging, psychophysical, and lesion studies in humans. Not offered 2014-15.
CNS/Bi/NB 256
Decision Making
6 units (2-0-4)
|
third term
This special topics course will examine the neural mechanisms of reward, decision making, and reward-based learning. The course covers the anatomy and physiology of reward and action systems. Special emphasis will be placed on the representation of reward expectation; the interplay between reward, motivation, and attention; and the selection of actions. Links between concepts in economics and the neural mechanisms of decision making will be explored. Data from animal and human studies collected using behavioral, neurophysiological, and functional magnetic resonance techniques will be reviewed. Given in alternate years; not offered 2014-15.
CNS/Bi 286 abc
Special Topics in Computation and Neural Systems
Units to be arranged
|
First, second, third terms
Students may register with permission of the responsible faculty member.
Published Date:
July 28, 2022