Cognitive Neural Computation
2013 Spring Graduate Course in Cognitive Science and Brain Science Programs
  • Instructor: Prof. Byoung-Tak Zhang
  • TA: Kwonill Kim
  • Classroom: 014-207-1
  • Time: Friday 10:00-12:30
  • Reference:
    • [1] 23 Problems in Systems Neuroscience, J. van Hemmen and T. Sejnowski (Eds.), Oxford University Press, 2006.
    • [2] How to Create a Mind: The Secret of Human Thought Revealed, R. Kurzweil, Viking, 2012.
  • Evaluation:
    • - Two open-book exams (60%)
    • - Presentation and term paper (30%)
    • - Participation and discussion (10%)
  • Course Description:
    • This course reviews the recent advancements in computational systems neuroscience and discusses the brain-inspired cognitive computing architectures for the next-generation artificial intelligence and machine learning. We address the following questions: How does the mind arise from the brain? How does the brain make sense of the world? How can the brain produce decisions and actions so fast and reliably in constantly changing environments? What principles does the brain use to encode, learn, store, recall, and forget information? How can we use these principles to create a brain-like cognitive computer that learns?
  • Lecture Schedule

    • Week Topics Slides
    Week 1
    (3/8)
    • From cognitive brain science to brain-like computation
    • Brain as a cognitive neural computer
    • Computational vision, language, and motion
    • Lifelong learning with perception-action cycle
    Week 2
    (3/15)
    • Michael Arbib [Keywords] & Stephen Grossberg & Terry Sejnowski
    • Ray Kurzweil [2], The biologically inspired digital neocortex (Ch. 7, 류제환) & The mind as computer (Ch. 8, 류제환)
    Week 3
    (3/22)
    • Jeff Hawkins [Keywords] & Tomasso Poggio
    • Laurenz Wiskott: How does our visual system achieve shift and size invariance? (Ch. 16, 김태준)
    • L. F. Abbott: Where Are the Switches on This Thing? (Ch. 21, 이상우)


    Week 4
    (3/29)
    • Jack Gallant [Keywords] & Itzhak Fried
    • Francis Crick & Christof Koch: What are the neuronal correlates of consciousness? (Ch. 23, 김경민)
    • Terrence J. Sejnowslzi: What Are the Projective Fields of Cortical Neurons? (Ch. 19, 김종규)



    Week 5
    (4/5)
    • Earl Miller & Gyorgy Buzsaki [Keywords]
    • Gilles Laurent: Shall we even understand the fly's brain? (Ch. 1, 천효선)
    Week 6
    (4/12)
    • Karel Svoboda
    • C. van Vreeswijk: What is the neural code? (Ch. 8, 이범진)
    • Tal Kenet et al.: Are single neurons soloists or are they obedient members of a huge orchestra? (Ch. 9, Anwar Sajid)

    Week 7
    (4/19)    		 Layout
    Week 8
    (4/26)
    • Exam 1
    Week 9
    (5/3)
    • Stephen Smith & Seth Grant [Keywords]
    • Wulfram Gerstner: How can the brain be so fast? (Ch. 7, 이충연)
    • Joachin Fuster & Gerald Edelman
    • V. S. Ramachandran & Edward Hubbard: Synesthesia: What does it tell us about the emergence of qualia, metaphor, abstract thought, and language? (Ch. 22, 배수정)

    Week 10
    (5/10)
    • Clay Reid [Keywords] & Markus Meister
    • Steven Zucker: Which computation runs in visual cortical columns? (Ch. 11, 이현민)

    Week 11
    (5/17)
    • Holiday (Buddha's Birthday)
    Week 12
    (5/24)
    • Tony Bell & Bruno Olshausen [Keywords]
    • Bruno Olshausen and David Field: What is the other 85 percent of V1 doing? (Ch. 10, 이상윤)
    • C. E. Carr, S. Iyer, D. Soares, S. IGzlluri, and J. Z. Simon: Are Neurons Adapted for Specific Computations? (Ch. 12, 김진화)



    Week 13
    (5/31)
    • Mark Gluck & Geoffrey Hinton & Tom Mitchell
    • Andreas V. M. Herz: How Is Time Represented in the Brain? (Ch. 13, 이재선)
    • David McAlphine & Alan Palmer: How general are neural codes in sensory systems? (Ch. 14, 유승범)
    • Georg M. Iclump: How Does the Hearing System Perform Auditory Scene Analysis? (Ch. 15, 박예슬)






    Week 14
    (6/7)
    Week 15
    (6/14)
    • Exam 2
    Week 16
    (6/21)
    • Reviews and discussion
    This page is maintained by Kwonill Kim
    Last update: 2013.03.07.