Course 2071.402:

Course 2071.402:
Brain and Computation (2012)

School of Computer Science and Engineering, Seoul National University
Instructor: Prof. Byoung-Tak Zhang
TA: Kwonill Kim (Office : 302-314-1, Tel : 02-880-1847)
Classroom: 83-503
Time: Friday, 09:30~12:30
Objectives:

To understand the principles of information coding and processing in the brain.
To learn mathematical and computational tools for modeling brain function at the neuron and network levels.
To build computational models of learning and memory in the brain networks.

Textbook:

Fundamentals of Computational Neuroscience, Thomas Trappenberg , 2002.

References:

Principles of Neural Science, Eric R. Kandel, J.H. Schwartz, Thomas M. Jessell, 2000
Nature Neuroscience 2000 supplement - Computational Approaches to Brain Function, BI Seminar Link

Evaluation:

Mid-Term exams (45%)
Final exam (45%)
Presence and participation in discussion (10%)

Lecuture Schedule

Title

Lecture Note

1. Introduction
2. Neurons and Conductance-Based Models
3. Spiking Neurons and Response Variability
4. Neurons in a Network
5. Representations and The Neural Code
6. Feed-forward Mapping Networks
Mid-Term Exam (10/26)

7. Associators and Synaptic Plasticity
8. Auto-associative Memory and Network Dynamics
9. Continuous Attractor and Competitive Networks
10. Supervised Learning and Rewards Systems
11. System Level Organization and Coupled Networks
Appendix. History of A.I. & Brainlike Computing
Final Exam (12/07)

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Guiding Questions 1~6

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Guiding Questions 7~10

Lecuture Board

This page is maintained by Kwonill Kim
Last updated: 2012-10-05.