The course is designed for students in various disciplines who wish to inform themselves of the current state of Theories on Information Processing in the Nervous system. The course will address  the conceptual foundations of research in the Neurobehavioral Sciences and the reciprocal  relations between Neurosciences and Engineering disciplines.
Some familiarity with basic Principles of Neurophysiology and Neural Network Computation, while helpful, is NOT a prerequisite since the required information will be made available. The course will NOT address molecular Biology of the Nervous System.
        The organizing principles of the course are:
    1) to state (and illustrate) explicitly the problems the Nervous System (and intelligent artifacts) are required to solve as perceptual-cognitive agents in interaction with their environment.
    2) to review and evaluate  the theoretical conceptualizations and known neurophysiological mechanisms proposed to accomplish these tasks. Examples of topics are: the encoding of environmental events in individual Neurons and Neuron Clusters; synchronization of activity and oscillatory phenomena in Neuron Populations; information processing in nonlinear systems and coupled chaotic oscillators.
    The course will apply three teaching approaches:
1: seminar discussion of significant original publications (and WEB references) that highlight the central topics;
( material on more specialized topics in the Neurosciences will be available in a Textbook on the WEB for filling in knowledge gaps in the student's background in computational neuroscience).
2: didactic commentaries on certain topics (to be determined ad hoc to supplement gaps in students' background);
3: elective problem solving exercises tailored to student's background (e. g. computer simulations);
4: demonstrations of computer programs modeling certain aspects of neural information processing.
    Course format: weekly session, three hours each.  Handout material will be provided. In addition, a facility for an ongoing dialog among course participants and instructors will be available on the internet for discussing  issues that may arise in the course of preparing the homework assignments. Students will be expected to prepare each week a brief (one page) statement of their reflections on the assigned reading material, as basis for participation in the group discussions.
    At the end of the course, the students will be able to:
1: critically evaluate knowledge claims in the Neurobehavioral Sciences.
2: reason independently about the implicit and explicit assumptions on which these knowledge claims rest, and to analyze the constraints such assumptions  impose on the generality of conclusion.
3: relate computational Neuroscience to theories of perception and cognition in natural and artifactual systems.
4: apply principles of nonlinear dynamics  to  conceptualizing nervous functions at the system level, and their relevance for designing intelligent artifacts.
    Course Evaluation: At the end of the course, a formal evaluation of the achievement of these objectives will be conducted along two lines: Instructor performance and appropriateness of teaching material for achieving the course objectives.
    Course grading: there will be two exam papers,one half way through the course, the other at its end. In addition, course participation and special projects (if applicable) will receive additional credit.

For questions and inquiries please contact:  gwer1@mail.utexas.edu   or  demaris@ece.utexas.edu