Course Announcement: Fall 2004
Course Title: Applied System Neuroscience
Gerhard Werner, M.D.
Adj. Professor, BME Unique Number: 12815
Time and Place: M F
9:30-11, ENS 145
The Course addresses conceptual foundations of the Neurobehavioral Sciences, relevant computational models, and applications bridging Neural Science and Engineering.
The following topics will be covered in introductory presentations by
the instructor, and through reading assignments for student
presentations and group discussions: the latter forming the principal
format of the course.
1) Information processing in the NS: Theories
of Neural Coding: Signal Processing, Predictive Coding,
Neurophysics: the Nonlinear Dynamics of Neural Processes
Bayesian Interpretation of Sensory Messages
Processing of Space and Time in the Nervous System
Contributions from Brain Imaging
2) Processing decisions for action:
Perception - Action Coupling (including Kalman Filter)
Reinforcement learning in the NS: Adaptive Critic Engineering
Inverse Dynamics models (including Markovian)
Ecological Robotics , Schema Theory
Course Format: Brief conceptual introductions and
overviews by the instructor, followed by discussion of reading assignments
and problem solving exercises ( within the objectives of the course,
participants also have the opportunity of selecting articles and problems
of their own choice).
Journal publications will be distributed or, if available on line, URL's will be announced in preparation for assigned reading and group discussion.
In addition, the following books are on reserve in the respective libraries . Their purpose is to assist with securing background knowledge, and to enable students to deepen their understanding of issues of special interest to them. I will refer to these sources at the appropriate occasions in the course. These resources are also intended to assist with the design and conduct of individual projects for presentation to the class.
A: Basic Neuroanatomy and Neurophysiology: (Life
D.E. Haines, Fundamental Neuroscience
J.G. Nicholls et al 4th edit. From Neuron to Brain
D. Purves, G.J. Augustine, D. Fitzpatrick, L.C. Katz, A.S. LaMantia,etc. Neuroscience, 2nd edit, 2001.
(notably Ch. 1 & 2 for filling gaps in neurophysiology background knowledge)
B: Nonlinear Dynamics and Systems
S.H. Strogatz: Nonlinear dynamics and chaos.(PMA Library)
P. Berge: order within chaos (PMA Library)
S.H. Zak: Systems and Control <with MATLAB Coded examples (Engin.Libr)
C: Cellular Biophysics (Life Science Librray)
D.Johnston & S.M. Wu: Foundations of cellular Neurrophysiology
T. Fischer Weiss : Cellular Biophysics (with MATLAB sofware for neural and biophysical modeling)
D: Computational modeling of neurons/neural systems: (Life Sciences library)
H.R. Wilson, : Spikes, decisions and actions (with MATLAB software)
L. Abbott & T.J. Sejnowski: Neural Codes and distributed processing.
P. Dayan & L. Abbott: Theoretical neuroscience.
A. Weizenfeld, M.A. Arbib, A. Alexander: The neural Simulation Language (Models and Code)
C. Eliasmith & Anderson: Neural Engineering (with MATLAB software).
Sheu & Choi, Neural information processing and VLSI <presently on order>
E: Neuroimaging (Life Science Library)
J.C. Mazziotta et al: Brain Mapping Handbk : the disorders
R.A. Zimmerman: Neuroimaging : clinical and physical principles
F: Additional Reading:
N. Osaka: Neural basis of consciousness (Life Science Librray)
G.M. Edelman A universe of consciousness : how matter becomes imagination (PCL>
Course Grading: primarliy based on the participation
in group discussion and the oral reports on reading assignments. There
will be one final written examen paper in which the participant is required
to discuss and evaluate an assigned publication in the light
of the criteria explored in the course. Special credits will be given
for individual elective projects on course-related topics.
For information, please contact: email@example.com