| source Caltech (X) |
level |
department Computation and Neural Systems (X) |
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.
Score: 11.717955 Details | Listing | Web page
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.
Score: 11.717955 Details | Listing | Web page
For course description, see Psychology.
Score: 11.717955 Details | Listing | Web page
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 2008–09.
Score: 11.717955 Details | Listing | Web page
For course description, see Biology.
Score: 11.717955 Details | Listing | Web page
For course description, see Social Science.
Score: 11.717955 Details | Listing | Web page
For course description, see Biology.
Score: 11.717955 Details | Listing | Web page
For course description, see Computer Science.
Score: 11.717955 Details | Listing | Web page
For course description, see Biology.
Score: 11.717955 Details | Listing | Web page
For course description, see Biology.
Score: 11.717955 Details | Listing | Web page
For course description, see Computer Science.
Score: 11.717955 Details | Listing | Web page
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. Not offered 2008–09.
Score: 11.717955 Details | Listing | Web page
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. Instructors: Perona, Shimojo, Koch. Given in alternate years; not offered 2008–09.
Score: 11.717955 Details | Listing | Web page
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. Instructors: Perona, Winfree.
Score: 11.717955 Details | Listing | Web page
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. Not offered 2008–09.
Score: 11.717955 Details | Listing | Web page
For course description, see Computer Science.
Score: 11.717955 Details | Listing | Web page
For course description, see Biology.
Score: 11.717955 Details | Listing | Web page
For course description, see Biology.
Score: 11.717955 Details | Listing | Web page
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 2008–09.
Score: 11.717955 Details | Listing | Web page
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. Instructor: Andersen. Given in alternate years; offered 2008–09.
Score: 11.717955 Details | Listing | Web page
For course description, see Bioengineering.
Score: 11.717955 Details | Listing | Web page
For course description, see Biology.
Score: 11.717955 Details | Listing | Web page
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 2008–09.
Score: 11.717955 Details | Listing | Web page
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 2008–09.
Score: 11.717955 Details | Listing | Web page
For course description, see Psychology.
Score: 11.717955 Details | Listing | Web page