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:
  • References:
  • 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.