Fall 2005

First day of classes for CMU & Pitt: Monday, August 29, 2005.

Core courses:  Cognitive Neuroscience,
Cellular & Molecular Neurobiology

CMU Computer Science

10-701 Machine Learning: 12 units
(Cross-listed as 15-781 for CS PhD students only.)

• Instructor: Tom Mitchell & Andrew Moore
• Location: Wean Hall 7500
• Days/Times: TR 10:30AM to 11:50AM

Classes will not begin until after the CSD Immigration Course

It is hard to imagine anything more fascinating than automated systems that improve their own performance. The study of learning from data is commercially and scientifically important. This course is designed to give a graduate-level student a thorough grounding in the methodologies, technologies, mathematics and algorithms currently needed by people who do research in learning and data mining or who may need to apply learning or data mining techniques to a target problem. The topics of the course draw from classical statistics, from machine learning, from data mining, from Bayesian statististics and from statistical algorithmics. Students entering the class with a pre-existing working knowledge of probability, statistics and algorithms will be at an advantage, but the class has been designed so that anyone with a strong numerate background can catch up and fully participate. Due to high demand, this class will also be offered in Spring 2005.
Please refer to this link for the most recent schedule updates.

This course is only available to CSD PhD and 5th year MS students. If you are f rom another department you must register under the number 10-701 (CALD). If you have questions send email to diane@cs

15-874 Special Topics: Computational Neuroscience: 12 units
Cross listed as 15-490

• Instructor: Tai Sing Lee
• Location: Porter Hall A20
• Days/Times: TR 1:30PM to 2:50PM

Classes will not begin until after the CSD Immigration Course

An introduction to computational neuroscience, i.e. the application of of computational and mathematical concepts and techniques to the study of the brain. Students will learn the fundamentals of signals and systems, pattern analysis, probability theory and information theories and apply these techniques to study how the real nervous systems computes, communicates and learns at many levels, from synapses to neurons, from neuronal populations to systems. Topics include basic anatomy and physiology of neurons and the mammalian nervous systems, biophysics of single neurons, excitable membranes and cable equation, encoding and decoding of information in single neurons and neuronal ensembles, neural adaptation and learning, signal detection and reconstruction, distributed and hierarchical computations. Concrete examples will be drawn primarily from the visual and the motor systems and studied from both biological and computational perspectives. Students will do a number of Matlab programming and mathematical exercises to consolidate their learning, participate in the analysis of real neuronal data. No prior background in biology is assumed.

Prerequisites: 15-113 and (18-202 or 21-241)

CMU Psychology

85-765 Cognitive Neuroscience [CNBC core course]
Cross-listed as Pitt Neuroscience NROSCI 2005.

• Instructor: Jay McClelland & Carl Olson : 9 units
• Location: Mellon Institute 115
• Days/Times: TR 10:30AM to 11:50AM

  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 vison, 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. Prerequisites: Graduate standing or two upper-level psychology courses from the areas of developmental psychology, cognitive psychology, computational modeling of intelligence, neuropsychology or neuroscience.
  
  Prerequisites: Graduate standing or two upper-level psychology courses from the areas of developmental psychology, cognitive psychology, computational modeling of intelligence, neuropsychology or neuroscience.
  
  Graduate Students Only. Please email Dr. Jay McClelland for permission to enroll at mcclelland@cmu.edu

Perception, broadly defined, is the construction of a representation of the external world for purposes of thinking and acting. Although we often think of perception as the processing of inputs to the sense organs, the world conveyed by the senses is ambiguous, and cognitive and sensory systems interact to interpret it. In this course, we will examine the sensory-level mechanisms involved in perception by various sensory modalities, including vision, audition, and touch. We will learn how sensory coding interacts with top-down processing based on context and prior knowledge and how perception changes with learning and development. We will look at methods of psychophysics, neuroscience, and cognitive psychology. The goals include not only imparting basic knowledge about perception but also providing new insights into everyday experiences.

Graduate Students Only. Please email Dr. Roberta Klatzy to enroll at klatzky@cmu.edu

85-782 Conciousness & Cognition: 9 units

CMU Robotics

16-720 Section A, Computer Vision: 12 units

• Instructor: Martial Hebert
• Location: Doherty Hall A310
• Days/Times: TR 1:30PM - 2:50PM

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.

Textbook Information:
Title: "Computer Vision: A Modern Approach"
Authors: David Forsyth and Jean Ponce
Publisher: Prentice Hall
ISBN: 0-13-085198-1

Prerequisites: 15-385. Some reservations are for Graduate Students in Robotics

 CMU Statistics

36-749 Experimental Design for Behavioral and Social Sciences: 12 units
Cross-listed as 36-309

• Instructor: Howard Seltman
• Location: Lecture - Porter Hall 100, Sections A, B, C, D - Baker Hall 140 C&F
• Days/Times: Lecture TR.12:00PM to 1:20PM. Section A: R/12:00PM to 1:20PM, Section B: R/1:30PM to 2:50PM, Section C: F/12:00PM to 1:20PM and Section D F/1:30 to 2:50 PM

  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.

Pitt Neuroscience

NROSCI 2005 Cognitive Neuroscience CR HRS: 3.0 [CNBC core course]
Cross-listed as CMU 85-765

• Instructor: James McClelland, Carl Olson
• Location: Mellon Institute
• Days/Times: TR 10:30AM to 11:50AM

  This course will cover fundamental findings & approaches in cognitive neuroscience, with the goal of providing an over view 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 emo tion. Each topic will be approached from a variety of meth odological directions, i.e. Computational modeling, cogni tive 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. Prerequisites: Graduate standing or permission of the instructor.

NROSCI 2011 Functional Neuroanatomy: CR HRS: 4.0

• Instructor: Susan Sesack
• Location:  Langley A224
• Days/Times: M.F 9:00A to 9:50A; W 8:00A to 9:50A

This course deals with human neuroanatomy and covers the basic structure of the central nervous system from spinal cord to cerebral cortex. Emphasis is placed on major sys tems and subsystems within the brain, and on their function al significance. The basic structure and morphology of nerve cells will be covered.

Prerequisites: NROSCI 1000 or 1003. Special Enrollment Counseling is required for registration. Students should contact Dr. Sesack for permission to register.

NROSCI/MSNBIO 2100 Cellular and Molecular Neurobiology: CR HRS: 7.0 [CNBC core course]
NROSCI/MSNBIO 2101 Cellular and Molecular Neurobiology Conference: CR HRS: 2.0

• Instructor: Edwin S. Levitan
• Location: BSTWR
• Days/Time: MTHF 9:00A to 10:55A; Conference W 9:00A to 10:55A

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 (2100) and a conference section (2101); students should sign up for both. The conference section is devoted to discussion of papers in the primary literature.

NROSCI 2107 Functional Neuroanatomy: CR HRS: 1.0

• Instructor: Susan Sesack
• Location:  Langley A224
• Days/Times: M.F 9:00A to 9:50A; W 8:00A to 9:50A

This course deals with human neuroanatomy and covers the basic structure of the central nervous system from spinal cord to cerebral cortex. Emphasis is placed on major systems and subsystems within the brain, and on their function al significance. The basic structure and morphology of nerve cells will be covered.

Prerequisites: NROSCI 1000 or 1003. Special Enrollment Counseling is required for registration. Students should contact Dr. Sesack for permission to register.

Pitt Psychology

PSY 2205 Psychopathology: CR HRS: 3.0

• Instructor: Michael Pogue-Geile
• Location:  SENSQ 4401
• Days/Times: TR 2:30P to 3:45P

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.

Prerequisites: Permission of the instructor if not psychology graduate student.

PSY 2400 Human Cognition: Research Methods: CR HRS: 3.0

• Instructor: Walter Schneider
• Location: LDRC
• Days/Times: MW 1:00P to 2:25P

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 2465 Perception and Attention CR HRS: 2.0

• Instructor: Walter Schneider
• Location: LDRC
• Days/Times: MW 3:00PM to 4:55PM

  This is an advanced course on attention. Topics covered include selective attention, vigilance, theories, skill acquisition, automatic processing, and feature search. Physiology of attention, and learning effects. Students read and discuss current research papers in the area and are expected to carry out either an empirial or review research project in the area.