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:
Koch
CNS/SS/Psy/Bi 102 ab
Brains, Minds, and Society
9 units (3-0-6)
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second, third terms
Prerequisites: Bi/CNS 150 and CNS/Bi/Ph/CS 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.
Instructors:
Adolphs, Camerer, Koch, Rangel
CNS/SS/Psy 110 abc
Cognitive Neuroscience Tools
5 units (1
|
5-0-3
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.
Instructor:
Rangel
CNS/Bi/Psy 120
The Neuronal Basis of Consciousness
9 units (4-0-5)
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third term
What are the correlates of consciousness in the brain? The course provides a framework for beginning to address this question using a reductionist point of view. It focuses on the neurophysiology of the primate visual system, but also discusses alternative approaches more suitable for work with rodents. Topics to be covered include the anatomy and physiology of the primate's visual system (striate and extrastriate cortical areas, dorsal/ventral distinction, visual-frontal connections), iconic and working memory, selective visual attention, visual illusions, clinical studies (neglect, blind sight, split-brain, agnosia), direct stimulation of the brain, delay and trace associative conditioning, conscious and unconscious olfactory processing, and philosophical approaches to consciousness.
Instructor:
Koch
Psy/CNS 130
Introduction to Human Memory
9 units (3-0-6)
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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 2009-10.
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 2009-10.
Bi/CNS/Psy 133
Neurobiology and Evolution of Emotion: Do Flies Have Feelings?
9 units (3-0-6)
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third term
Prerequisites: Bi/CNS 150 or instructor's permission. Recommended Bi 156 and SS/Psy/Bi/CNS 140.
Fundamental issues in emotion research at multiple levels of experimental analysis, and in species ranging from humans to mice to flies. Psychological theories and data from studies in humans will be presented to clarify the relationship between emotional behavior, affect, feelings, and moods, which in turn will form the basis for exploring whether and how different animal models can be used to investigate the neural circuit and molecular bases of emotion. Can genetically tractable model organisms such as flies show "emotional behavior," or have "feelings"? What have we learned from animal models about the neural circuit and genetic bases of emotional behavior, and how does it relate to what we know from human studies? Disorders of emotion will also be discussed, including affective disorders in humans, and their potential animal models.
Instructors:
Anderson, Adolphs
SS/Psy/Bi/CNS 140
Social Neuroscience
9 units (3-0-6)
|
third term
Prerequisites: Bi/CNS 150 recommended.
This course will survey the neural basis of social behavior, drawing on both theoretical and empirical approaches. Recent findings from cognitive neuroscience will be discussed, with an emphasis on data from humans. Topics will include motivation, emotion, theory of mind, social perception, and simulation. Not offered 2009-10.
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.
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.
Instructor:
Perona
Bi/CNS 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, Kennedy, Lester
CS/CNS/EE 154
Artificial Intelligence
9 units (3-3-3)
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first term
Prerequisites: Ma 2 b or equivalent; and CS 1 or equivalent.
How can we build systems that perform well in unknown 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, logic 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, and will provide hands-on experience in a course project. Not offered in 2009-10.
Instructor:
Krause
CS/CNS/EE 155
Probabilistic Graphical Models
9 units (3-3-3)
|
first term
Prerequisites: background in algorithms and statistics (CS/CNS/EE 154 or CS/CNS/EE 156 a or instructor's permission).
Many real-world problems in AI, computer vision, robotics, computer systems, computational neuroscience, computational biology, and natural language processing require one to reason about highly uncertain, structured data, and draw global insight from local observations. Probabilistic graphical models allow addressing these challenges in a unified framework. These models generalize approaches such as hidden Markov models and Kalman filters, factor analysis, and Markov random fields. In this course, we will study the problem of learning such models from data, performing inference (both exact and approximate), and using these models for making decisions. The techniques draw from statistics, algorithms, and discrete and convex optimization. The course will be heavily research oriented, covering current developments such as probabilistic relational models, models for naturally combining logical and probabilistic inference, and nonparametric Bayesian methods.
Instructor:
Krause
CS/CNS/EE 156 ab
Learning Systems
9 units (3-0-6)
|
first, second 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 157
Comparative Nervous Systems
9 units (2-3-4)
|
third term
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. Given in alternate years; not offered 2009-10.
Instructor:
Allman
Bi/CNS 158
Vertebrate Evolution
9 units (3-0-6)
|
third term
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. Given in alternate years; offered 2009-10.
Instructor:
Allman
CS/CNS/EE 159
Projects in Machine Learning and AI
9 units (0-0-9)
|
third term
Prerequisites: CS/CNS/EE 154 or CS/CNS/EE 156 b.
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. This course can be combined with CS/CNS/EE 154/155 or with CS/CNS/EE 156 ab to satisfy the project requirement for the CS undergraduate degree. Not offered 2009-10.
Instructor:
Krause
Bi/CNS 162
Cellular and Systems Neuroscience Laboratory
12 units (2-7-3)
|
third term
Prerequisites: Bi 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. Given in alternate years; offered 2009-10.
Instructor:
Wagenaar
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 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.
Instructor:
Shimojo
Bi/CNS 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.
Instructor:
Tsao
CNS/Bi/EE 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; offered 2009-10.
Instructors:
Perona, Shimojo, Koch
CNS/Bi/Ph/CS 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
CNS/CS/EE 188
Topics in Computation and Biological Systems
9 units (3-0-6)
|
second term
Prerequisites: Ma 2 or IST 4.
Advanced topics related to computational methods in biology. Topics might change from year to year. Examples include spectral analysis techniques and their applications in threshold circuits complexity and in computational learning theory. The role of feedback in computation. The logic of computation in gene regulation networks. The class includes a project that has the goal of learning how to understand, criticize, and present the ideas and results in research papers.
Instructor:
Bruck
BE/CS/CNS/Bi 191 ab
Biomolecular Computation
9 units (3-0-6) second term; (2-4-3) third term
|
second, third terms
Prerequisites: ChE/BE 163. Recommended: 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 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; offered 2009-10.
Instructor:
Allman
Bi/CNS 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; not offered 2009-10.
Instructor:
Allman
Bi/CNS 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. Given in alternate years; offered 2009-10.
Instructor:
Anderson
CNS/Bi 221
Computational Neuroscience
9 units (4-0-5)
|
third term
Prerequisites: Bi/CNS 150 or instructor's permission.
Lecture and discussion aimed at understanding computational aspects of information processing within the nervous system. The course will emphasize single neurons and how their biophysical properties relate to neuronal coding, i.e., how information is actually represented in the brain at the level of action potentials. Topics include biophysics of single neurons, signal detection and signal reconstruction, information theory, population coding and temporal coding in sensory systems of invertebrates and in the primate cortex. Students are required to hand in three homework assignments, discuss one set of papers in class, and participate in the debates. Not offered 2009-10.
CNS/Bi 247
Cerebral Cortex
6 units (2-0-4)
|
second term
Prerequisites: Bi/CNS 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; not offered 2009-10.
Instructor:
Andersen
BE/CNS 248
Magnetic Resonance Imaging
9 units (3-1-5)
|
first term
Prerequisites: Undergraduate-level physics, biology, and/or engineering courses recommended; basic quantum mechanics, statistics, and signal processing are helpful.
Physics, engineering, and computational aspects of MRI. Theory, engineering, and practice of MRI for biological and medical applications are covered in detail. Provides technical background necessary for a full understanding of the concepts underpinning the specific uses of MRI for functional brain imaging. Complements CNS/SS 251. Not offered 2009-10.
Bi/CNS 250 b
Topics in Systems Neuroscience
9 units (3-0-6)
|
second 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 (3-1-5)
|
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). Not offered 2009-10.
CNS/SS 252
Experimental Design and Research Methods in Cognitive Neuroscience
9 units (3-0-6)
|
second term
This course will cover the basics of experimental design, research methods, and statistics for use in cognitive neuroscience. It will cover different types of experimental designs commonly used in cognitive neuroscience, including factorial designs, parametric designs, randomized block designs, nested designs, repeated measure designs; the statistics required to analyze such data, including t-tests, linear and multiple regression analyses, analysis of variance, random and fixed effects, all under the rubric of the general linear model, and model-free or "non-parametric" statistics. Undergraduate students may register with instructor's permission. Not offered 2009-10.
CS/CNS/EE 253
Special Topics in Machine Learning
9 units (3-3-3)
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).
Instructor:
Krause
SS/Psy/Bi/CNS 255
Topics in Emotion and Social Cognition
9 units (3-0-6)
|
third term
Prerequisites: SS/Psy/Bi/CNS 140 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.
Instructor:
Adolphs
CNS/Bi 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. Instructor Andersen.
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