The Center for the Neural Basis of Cognition

Fall 2000 Courses
Fall 2000

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.


15-886 85-411 & 85-711 Section A Cognitive Processes & Problem Solving: 12 units
BEGINS WEEK OF AUGUST 28th

CMU Robotics

16-720 Section A, Computer Vision: 12 units

BEGINS SEPTEMBER 5TH

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: 12 units

This class will review various results in cognitive psychology (attention, perception, memory, problem solving, language) and use of artificial intelligence techniques to simulate cognitive processes. The prerequisites for this course are 15-211 and 85-211. A 3 unit course is taught along with 85-213 which will teach LISP.

85-721 Language and Thought: 9 units

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? Prerequisite: either 85-211 Cognitive Psychology, 80-180 The Nature of Language, or equivalent background.

85-765 Cognitive Neuroscience: 9 units  [CNBC core course]
Cross-listed as Pitt Neuroscience NEUSC 2005.

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.

85-790 Human Learning and Memory: 9 units

This seminar will discuss current topics in human memory as well as go over some of the basic conceptualizations of the functionality of memory and information processing. Most weeks, the instructor will review an aspect of human memory or the literature relevant to the evening's topic. In addition we will discuss one or two journal articles. Students in the course will be responsible for reading all the articles but responsibility for leading the discussion will rotate. The course will require each student to either conduct an experiment relevant to a topic discussed or do a literature review relevant to one of the topics under discussion. Interested students must have taken a basic course in Cognitive Psychology to enroll. Prerequisite: 85-211 OR 85-213.

 CMU Statistics

NONE. But see Spring 2001.

Pitt Mathematics
 

NONE.

Pitt Neuroscience

NROSCI  2001 NEUROPHYSIOLOGY: CR HRS: 4.0 [CNBC Core Course]

This course is a subset of MSNBIO 2100, consisting of just blocks 3-5. Students in the Program in Neuroscience are required to take the full course and should sign up for MSNBIO 2100. CNBC students in other Ph.D. programs can take this subset version, NROSCI 2001, to satisfy the neurophysiology core requirement. However, students are encouraged to at least audit blocks 1-2 of the course if their schedule permits.

The topics covered in this course include the electrophysiological analysis of resting and action potentials, a description of both the pre- and postsynaptic ionic mechanisms involved in synaptic transmission, and an overview of specific examples of how the cellular mechanisms described earlier in the course can be integrated into models of the functioning of small neural networks.

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

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.

Pitt Neurobiology

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

This is a required course for students in the Program in Neuroscience, and also satisfies the CNBC core requirement. CNBC students in other programs can take the subset version, NROSCI 2001 instead.

The course covers protein structure and function, gene expression, neuronal development, membrane properties, the action potential, synaptic transmission, and second messenger systems, and synaptic plasticity.

Pitt Psychology

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 2455 Human Cognition: Language: CR HRS: 2.0

This is a basic half-term module in language processes.  It offers intensive coverage of the basic (adult) psycholinguistic topics such as speech perception, word meaning, and sentence comprehension.
 

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

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.

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