Printer Friendly Page

Spring 2005

First day of classes: Pitt January 5, 2005; CMU January 10, 2005.

Core courses:
Computational Neuroscience Methods
Computational Models of Neural Systems,
Intro to Parallel Distributed Processing,
Neurophysiology
Systems Neurobiology

Note:  students in the CNBC graduate training program automatically have instructor permission to attend any of these core courses, but cross-registration procedures may apply.


CMU Biological Sciences

03-315 Introduction to Magnetic Resonance Imaging in Neuroscience: 9 units

  • Instructor: Eric Ahrens
  • Date/Time: Tue & Thu 3:00 PM- 4:20 PM
  • Location: Mellon Institute 448
  • Prerequisites: Biology 03-121 (modern biology) and Mathematics 21-117 or 21-121 or 21-122, or permission of the instructor.

The course is designed to introduce students to the fundamental principles of magnetic resonance imaging (MRI) and its application in neuroscience. MRI is emerging as the preeminent method to obtain structural and functional information about the living human brain. This methodology has helped to revolutionize neuroscience and the study of human cognition. The specific topics covered in this course will include: introduction to spin gymnastics, survey of imaging methods, structural brain mapping, functional MRI (fMRI), and MR spectroscopy (MRS). Approximately, one third of the course will be devoted to introductory concepts of magnetic resonance, another third to the discussion of MRI methods, and the remaining third will cover a broad range of neuroscience applications. Guest lectures will be incorporated into the course from neuroscientists and psychologists who use MRI in their own research.

 

03-761 Neural Plasticity in Sensory and Motor Systems: 9 units

  • Instructors: Alison Barth, Nathan Urban, Justin Crowley
  • Date/Time: Mon 2:30 PM - 4:20 PM
  • Location: Mellon Institute 191
  • Prerequisites: Biology 03-360
  • Special Permission Required

Neural plasticity underlies the capacity of the central nervous system to encode new information, develop new abilities and adapt to the environment. Plasticity is required for learning and is modulated during development and by disorders of the brain. Recent advances in experimental methodology have led to new insights on the biological mechanisms underlying neural plasticity. The topics if the papers chosen for review will center on recent experimental and theoretical studies of topics such as synaptic plasticity, developmental and activity-dependent changes in sensory and motor maps.


CMU Computer Science

15-385/685  Computer Vision: 9/12 units

  • Instructor: Tai Sing Lee
  • Date/Time: Tue & Thu 3:00 PM - 4:20 PM
  • Location: Wean Hall 5403
  • Prerequisites: 15-113 and (18-202 or 21-241)

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, but biological and psychological perspectives will also be considered. Topics covered include image formation and representation, multi-scale analysis, segmentation, contour and region analysis, reconstruction of depth based on stereo, texture shading and motion, and analysis and recognition of objects and scenes using statistical and model-based techniques.

 

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

  • Instructor: C Guestrin
  • Date/Time: Mon & Wed 1:30 PM - 2:50 PM
  • Location: Wean Hall 7500

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

 

15-833 Computational Models of Neural Systems: 12 units

[CNBC Core Course]

  • Instructor: David Touretzky
  • Date/Time: Mon & Wed 4:30 PM to 5:50 PM
  • Location: Wean Hall 4615A

This course is an in-depth study of information processing in real neural systems from a computer science perspective. We will examine several brain areas where processing is sufficiently well understood that it can be discussed in terms of specific representations and algorithms. We will focus primarily on computer models of these systems, after establishing the necessary anatomical, physiological, and psychophysical context. There will be some neuroscience tutorial lectures for those with no prior background in this area.


CMU Psychology

 

85-712/412 Cognitive Modeling: 9 units

  • Instructor: John Anderson
  • Date/Time: Tue & Thu 10:30 AM -11:50 AM
  • Location: Baker Hall 340A
  • Prerequisites: Special permission required, contact instructor.

This course will be concerned with modeling of cognition. We will use a high-level modeling language to simulate a range of cognitive tasks from the literature on attention, memory, problem solving and skill acquisition. Students will end the course developing a model for a phenomenon of their choosing. The course grade will be determined by a series of assignments involving developing cognitive models and by a written exam.

 

85-714/414 Cognitive Neuropsychology: 9 units

  • Instructor: Marlene Behrmann
  • Date/Time: Mon & Wed 1:30 PM - 2:50 PM
  • Location: Baker Hall 340A
  • Prerequisites: Special permission required, contact instructor.

This course will review what has been learned of the neural bases of cognition through studies of brain-damaged patients as well as newer techniques such as brain stimulation mapping, regional metabolic and blood flow imaging, and attempt to relate these clinical and physiological data to theories of the mind cast in information-processing terms. The course will be organized into units corresponding to the traditionally-defined subfields of cognitive psychology such as perception, memory and language. In each area, we will ask: To what extent do the neurological phenomena make contact with the available cognitive theories? When they do, what are their implications for these theories (i.e., Can we confirm or disconfirm particular cognitive theories using neurological data?)? When they do not, what does this tell us about the parses of the mind imposed by the theories and methodologies of cognitive psychology and neuropsychology?

 

85-719/419 Introduction to Parallel Distributed Processing: 9 units

[CNBC Core Course]

  • Instructor: David Plaut
  • Date/Time: Tue & Thu 1:30 PM- 2:50 PM
  • Location: Baker Hall 340A
  • Prerequisites: Special permission required, contact instructor.
  • Course home page: http://www.cnbc.cmu.edu/~plaut/85-419/

This course will provide an overview of parallel-distributed processing models of aspects of perception, memory, language, knowledge representation, and learning. The course will consist of lectures describing the theory behind the models as well as their implementation, and students will get hands-on experience running existing simulation models on workstations.

 

85-721/421 Language & Thought: 9 units

  • Instructor: Brian MacWhinney
  • Date/Time: Mon & Wed 10:30 AM - 11:50 AM
  • Location: Baker Hall 336B
  • Prerequisites: Special permission required, contact instructor.

This course allows the student to explore ways in which the mind shapes language and language shapes the mind. Why are humans the only species with a full linguistic system? Some of the questions to be explored are: What kinds of mental abilities allow the child to learn language? What are the cognitive abilities needed to support the production and comprehension of sentences in real time? How do these abilities differ between people? Are there universal limits on the ways in which languages differ? Where do these limitations come from cognition in general or the specific language facility? Why is it so hard to learn a second language? Are there important links between language change and cultural change that point to links between language and culture?

 

85-729/429 Cognitive Brain Imaging: 9 units

  • Instructor: Marcel Just
  • Date/Time: Wed 7:00 PM - 8:50 PM
  • Location: Baker Hall 336B
  • Prerequisites: 85211 or 85213 or 85411 or 85412 or 85414 or 85419. Special permission required, contact instructor.

This seminar will examine how the brain executes higher level cognitive processes, such as problem-solving, language comprehension, and visual thinking. The topic will be addressed by examining 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 perform what function, but also how the activity of different parts of the brain are organized to 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, visual thinking. Several different technologies for measuring brain activity (e.g. PET and functional MRI and also some PET imaging) 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. Graduate Students Only.

 

85-795 Applications of Cognitive and Perceptual Psychology: 9 units

  • Instructor: R Klatzky
  • Date/Time: Tue & Thu 9:00 AM - 10:20 AM
  • Location: Baker Hall 336B
  • Prerequisites: 85211 or 85310 or 85370
  • Special permission required, contact instructor.

The famous psychologist George Miller once said that Psychology should "give itself away." The goal of this course is to look at cases where we have done so -- or at least tried. The course focuses on applications that are sufficiently advanced as to have made an impact outside of the research field per se. That impact can take the form of a product, a change in practice, or a legal statute. The application should have a theoretical base, as contrasted, say, with pure measurement research as in ergonomics. Examples of applications are virtual reality (in vision, hearing, and touch), cognitive tutors based on models of cognitive processing, phonologically based reading programs, latent semantic analysis applications to writing assessment, and measurses of consumers' implicit attitudes. The course will use a case-study approach that considers a set of applications in detail, while building a genera l understanding of what it means to move research into the applied setting. The questions to be considered include: What makes a body of theoretically based research applicable? What is the pathway from laboratory to practice? What are the barriers - economic, legal, entrenched belief or practice? The format will emphasize analysis and discussion by students.


CMU Robotics

16-721 Advanced Robot Perception: 12 units

  • Instructor: S Narasimhan
  • Days/Times: Tue & Thu 10:30 AM - 11:20 AM
  • Location: Newell Simon Hall 3002

The goal of this course is to come up to speed with current research in computer vision. The course includes introductory lectures for each topics and presentations/implementations by students based on recent publications in major computer vision conferences and journals. The list of papers and topics is updated every year.

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


16-725 Methods in Medical Image Analysis: 12 units

  • Instructor: George Stetten, Yanxi Liu, Jonas August
  • Date/Time: Tue & Thu, 3:00 - 4:20pm
  • Location:Wean Hall 4601
  • Prerequisites: Permission of the instructor, knowledge of C++, vector calculus and basic probability.

The fundamentals of computational medical image analysis will be explored, leading to current research in applying geometry and statistics to segmentation, registration, visualization, and image understanding. Student will develop practical experience through projects using the National Library of Medicine Insight Toolkit (ITK), a new software library developed by a consortium of institutions including CMU. In addition to image analysis, the course will describe the major medical imaging modalities and include interaction with practicing radiologists at UPMC.

 

16-899A Machine Perception and Modeling of Human Behavior: 12 units

  • Instructor: Chris Atkeson (CMU), Rich Simpson (Pitt)
  • Date/Time: Thu 3:00 PM - 6:00 PM
  • Location: Porter Hall 225 B

This course will survey methods for monitoring and modeling human behavior, with a focus on assistive applications and applications that improve quality of life. We will cover measurement approaches including instrumenting environments, everyday objects, and wearable devices. We will cover a variety of modeling techniques from psychology, speech recognition and language modeling, graphics, and machine perception.

The course will meet alternately at CMU and at Pitt. The first meeting for CMU students will be Jan 13 in Porter Hall

 


Pitt Mathematics

MATH 3375: Computational Neuroscience Methods CR HRS: 3.0

[CNBC Core Course]

  • Instructors: Bard Ermentrout & Jonathan E Rubin
  • Days/Times: Tue & Thu 9:00 AM - 10:25 AM
  • Location: Thackeray Hall 525

Sampling of topics covered: neuron spiking; firing rates and spike statistics; reverse correlations and receptive fields; neural decoding (discrimination, population decoding, spike train decoding); electrical properties of neurons; single-compartment models; modeling channels and synpatic conductances; the Hodgkin-Huxley model; the cable equation; conductances and morphology; levels of modeling; network models (firint rate models, feedforward and recurrent networks, excitatory-inhibitory networks, stochasic networks); plasticity and learning; supervised and unsupervised learning.

MATH 3950: Nonlinear Dynamic Chaos & Oscill CR HRS: 3.0

  • Instructors: Bard Ermentrout & Jonathan E Rubin
  • Days/Times: Mon & Wed 10:30 AM - 11:50 AM
  • Location: Thackeray Hall 703

This course gives a description of modern techniques for analyzing nonlinear differential equations. It covers topics such as chaos, nonlinear oscillations, bifurcation theory, phase locking and invariant manifold methods. Topics such as averaging, singular perturbation, and equations on tori are also discussed.

 

Pitt Psychology

PSY 2330 Developmental Psych: Cognitive Development CR HRS: 2.0

  • Instructor: Jana Marie Iverson
  • Days/Times: Wed 9:00 AM - 11:45 AM
  • Location: Sennott Square 4117

This course will provide an introduction to central theories and issues in the study of cognitive development in infancy and childhood. The course will cover (a) theoretical frameworks for studying cognitive development, including constructivist, sociocultural, and dynamic systems theories; and (b) specific topics in the study of cognitive development, including perception, memory, language, categorization, and reasoning.

 

PSY 2460 Human Cognition: Learning & Memory CR HRS: 2.0

  • Instructor: Mark Wheeler
  • Days/Times: Thu 2:00 PM - 04:25 PM
  • Location: Learning Research and Development Center

This is a basic half-term module in learning and memory. It offers intensive coverage of the basic theoretical and experimental approaches to learning and memory.


Pitt Neuroscience

NROSCI 2012 Neurophysiology: CR HRS: 3.0

[CNBC Core Course]

  • Instructor: Jon W. Johnson
  • Days/Times: Tue & Thu 11:00 - 12:15pm
  • Location: Langley Hall A224

In this course we will examine the functioning of neurons and synapses, the basic units responsible for fast communication within the nervous system. The course will focus on the elegant use of electrical mechanisms by the nervous system, and on the powerful quantitative approach to scientific investigation that is fundamental to neurophysiology. Topics that will be addressed include: principles of electric current flow exploited by the nervous system; the basis of the resting potential of neurons; the structure and function of voltage-gated and neurotransmitter-gated ion channels; generation and propagation of action potentials; the physiology of fast synaptic communication.

 

NROSCI/MSNBIO 2102 Systems Neurobiology: CR HRS: 6.0

[CNBC Core Course]

  • Instructor: Dan Simons
  • Days/Times: Mon & Wed 9:00 - 10:20am, Fri 9:00 - 10:55am
  • Location: Victoria Hall 116
  • Prerequisites: MSNBIO 2100 OR NROSCI 2100 (Cellular and Molecular Neurobiology), or INTBP 2000 (Foundations in Biomedical Science), or permission of the instructor. A background in basic biology is required. If students have not had college biology courses, they must obtain consent of the instructor to enroll.
  • Dates: 01/05/03 - 04/16/03

This course is a component of the introductory graduate sequence designed to provide an overview of neuroscience. This course provides an introduction to the structure of the mammalian nervous system and to the functional organization of sensory systems, motor systems, regulatory systems, and systems involved in higher brain functions. It is taught primarily in a lecture format with some laboratory work. The course covers in detail the major sensory, motor and behavioral regulatory systems of the brain. The course satisfies the CNBC core requirement in neuroanatomy.

 

NROSCI 3023 Seminar in Cognitive Neuroscience: CR HRS: 1.0 to 3.0

  • Instructors: Carl Olson, Carol Colby, James Mcclelland
  • Location: Mellon Institute
  • Days/Times: By Appointment

    This is a journal club devoted to cognitive neuroscience.