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Fall 2002 First day of classes for CMU & Pitt: Monday, August 26, 2002. Core courses: Cognitive Neuroscience,
CMU Computer Science 15-681 Machine Learning Fall: 12 units (undergraduate version)
Machine Learning is concerned with computer programs that automatically improve their performance through experience (e.g., programs that learn to spot high-risk medical patients, recognize human faces, detect credit card fraud, and drive autonomous robots). This course covers the theory and practical algorithms for machine learning from a variety of perspectives. We cover topics such as datamining, decision tree learning, neural network learning, statistical learning methods, genetic algorithms, Bayesian learning methods, explanation-based learning, and reinforcement learning. The course covers theoretical concepts such as inductive bias, the PAC learning framework, minimum description length principle, and Occam's Razor. Short programming assignments include hands-on experiments with various learning algorithms. Typical assignments include neural network learning for face recognition, and decision tree learning from databases of credit records. Prerequisite: 15-212, or permission of the instructor.
15-781 Machine Learning: 12 units (graduate version)
Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers the theory and practice of machine learning from a variety of perspectives. We cover topics such as learning decision trees, neural network learning, statistical learning methods, genetic algorithms, Bayesian learning methods, explanation-based learning, and reinforcement learning. The course covers theoretical concepts such as inductive bias, the PAC and Mistake-bound learning frameworks, minimum description length principle, and Occam's Razor. Programming assignments include hands-on experiments with various learning algorithms. Typical assignments include neural network learning for face recognition, and decision tree learning from databases of credit records. CMU Mechanical Engineering 24-779 Section A, Special Topics in Controls: Human Systems and Control: 9 or 12 units
This course covers the mechanisms of human motor systems and control, using arm movements as an example. The course starts with the anatomy of muscles, sensors, spinal cords, and brains; then functional analyses of these system components will follow. After system analysis, all components are integrated to study feedback control dynamics. Using physiological studies such as psychophysical and lesion experiments, this course covers classical and modern theories of how the nervous system may control movements. Advanced topics include adaptation, representation, coordinate systems, cognitive involvement, and rehabilitation techniques for motor-impaired patients. A project / presentation is required to take the course for 12 units. Prerequisites: 21-241, 21-260, 24-451, or permission of the instructor. CMU Robotics 16-720 Section A, Computer Vision: 12 units
Description: This course deals with the science and engineering of computer vision, that is, the analysis of patterns in visual images of the world with the goal of reconstructing and understanding the objects and processes in the world that are producing them. The emphasis is on physical, mathematical, and information processing aspects of vision. Topics covered include image formation and representation, camera geometry and calibration, multi-scale analysis, segmentation, contour and region analysis, energy-based techniques, reconstruction of based on stereo, shading and motion, 3-D surface representation and projection, and analysis and recognition of objects and scenes using statistical and model-based techniques. The material is based on a recent graduate-level textbook augmented with research papers, as appropriate. The course involves considerable Matlab programming exercises. CMU Psychology 85-713 Human Information Processing and Artificial Intelligence: 9 units
Reading is a composite of very complex cognitive skills. It is also an area in which there has been rapid progress in understanding the process, its acquisition, and the sources of difficulty and disability. This course examines research and theories on sentence and text comprehension, word recogni-tion, individual differences in reading ability, dyslexia, writing systems, eye fixations, perception, instructional methods, and speed reading. 85-729 Cognitive Brain Imaging: 9 units
This seminar will examine how the brain executes higher level cognitive processes, such as problem-solving, language comprehension, and visual thinking. The class will examine what recent brain imaging studies can tell us about these various kinds of thinking. This new scientific approach has the potential of providing important information about how the brain thinks, indicating not only what parts of the brain perform what function, but also how the activities of different parts of the brain are organized to jointly perform some thinking task, and how various neurological diseases (e.g. aphasia, Alzheimer's) affect brain activity. A variety of different types of thinking will be examined, including short-term working memory storage and computation, problem-solving, language comprehension, and visual thinking. Several different technologies for measuring brain activity (e.g. PET and functional MRI) will be considered, attempting to relate brain physiology to cognitive functioning. The course will examine brain imaging in normal subjects and in people with various kinds of brain damage. The course laboratory sessions will use a computer cluster (BH 332P) to visualize and process brain imaging results. The goals of the computer-assisted exercises are: 1. To learn to navigate through a 3-D brain visualization (a computerized graphic representation of some real person’s brain) 2. To learn the statistical procedures used to measure brain activation 3. To learn to relate brain activation to an approximate location in the brain 4. To learn the results of specific experiments, in terms of the brain locations of activation during the performance of certain tasks 85-765 Cognitive Neuroscience: 9 units [CNBC core course]
This course will cover fundamental findings and approaches in cognitive neuroscience, with the goal of providing an overview of the field at an advanced level. Topics will include high-level vision, spatial cognition, working memory, long-term memory, learning, language, executive control, and emotion. Each topic will be approached from a variety of methodological directions, for example, computational modeling, cognitive assessment in brain-damaged humans, non-invasive brain monitoring in humans, and single-neuron recording in animals. Lectures will alternate with sessions in seminar format. Prerequisite: Permission of Instructor (Graduate standing or undergraduates must have strong prior background in at least one relevant discipline, and permission of instructor. 85-782 Consciousness and Cognition: 9 units
This course will examine the relationship between cognition and consciousness. One particular focus will be on the issue of how complex the processes that are largely unconsciously controlled may be and another is on the interaction of conscious and non-conscious processes in the control of cognition. We will also very briefly examine relevant ideas about consciousness that arise in other fields such as philosophy of mind and physics. The major topics to be included will be drawn from: the experience and functionality of consciousness, neuroscience approaches to consciousness, perceptual and attentional work on consciousness, cognition in altered states of consciousness (in particular, dreaming), implicit memory, and the proceduralization of higher level cognitive processes. The course will consist of our reading and discussing primary research literature from the above areas. There will be a number of short written assignments based on the weekly reading and a term paper. GRADUATE STUDENTS ONLY.
CMU Statistics 36-749 Experimental Design for Behavioral and Social Sciences: 12 units
Statistical aspects of the design and analysis of planned experiments are studied in this course. A clear statement of the experimental factors will be emphasized. The design aspect will concentrate on choice of models, sample size and order of experimentation. The analysis phase will cover data collection and computation, especially analysis of variance, and will stress the interpretation of results. In addition to weekly lecture, students will attend a computer lab once a week. Prerequisite: 36-202, 36-220, or 36-247 Pitt Mathematics NONE. NROSCI/MSNBIO 2100 Cellular and Molecular Neurobiology: CR HRS: 7.0 [CNBC core course]
This is a required course for students in the Program in Neuroscience, and also satisfies the CNBC core requirement in neurophysiology. The course is very demanding. For this reason, CNBC students not in the Neuroscience program might prefer to take Jon Johnson's undergraduate neurophysiology course in the Spring instead. The regular syllabus will be augmented with half a dozen supplementary lectures specifically for CNBC graduate students. The Cellular and Molecular course covers protein structure and function, gene expression, neuronal development, membrane properties, the action potential, synaptic transmission, and second messenger systems, and synaptic plasticity. It consists of a lecture section and a conference section; students should sign up for both. The conference section is devoted to discussion of papers in the primary literature. NROSCI 2011 Functional Neuroanatomy: CR HRS: 4.0
This course covers the basic structure of the central nervous system from spinal cord to cerebral cortex. The major sensory, motor and integrative neural systems of the human brain are discussed. Based on an understanding of normal neural connections and brain function, the anatomical and physiological basis of various neurological disorders of the nervous system will be explored. Special Enrollment Counseling is required for registration. Students should contact Dr. Sesack for permission to register.
NROSCI 3023 Seminar in Cognitive Neuroscience: CR HRS: 1.0 to 3.0
This is a journal club devoted to cognitive neuroscience.. Pitt Psychology PSY 2005 Statistical Analysis I / Advanced Statistics-UG: CR HRS: 3.0
This course is the first of a two course sequence to provide the knowledge and skills needed to plan and conduct analyses using a uniform framework based on the general linear model. Students will learn techniques to conduct a variety of statistical tests; the appropriate interpretation of results will be emphasized. Topics include descriptive statistics, graphing data, sampling distributions, hypothesis testing (including power, effect sizes, and confidence intervals), T-tests, correlations, multiple regressions, and polynomial regression. Students use SAS for statistical computations.
PSY 2205 Psychopathology: CR HRS: 3.0
The aim of this course is to provide a critical background in research strategies, phenomena, empirical research, and models of adult psychopathology. The course emphasis will be on etiological and pathological research, with both psychological and biological findings to be discussed. Course concentration will be on the major psychopathologies with clinical onset in adulthood, including schizophrenia, affective disorders, anxiety, addictions, and eating disorders. Conceptual and methodological issues that cross diagnostic categories will be stressed. Treatment approaches and differential diagnosis will be covered but not emphasized.
PSY 2400 Human Cognition: Research Methods: CR HRS: 2.0
This course covers experimental research methods including proposing an experiment, literature search, experimental design, programming experiments, simple data analysis, research writing, and oral presentation. Specific research techniques for reaction time, memory and learning methods, protocol analysis, and human subject methods are covered. The course provides students experience with the technical skills for advanced research. The course will require a number of laboratory assignments, execute human experiment, write-up an experiment and an in-class final. PSY 2460 Human Cognition: Learning and Memory: CR HRS: 2.0
PSY 2465 Perception and Attention: CR HRS: 2.0
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