132.650 Cognitive Neural Computation (Spring 2013)
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
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?
References
- 23 Problems in Systems Neuroscience — J. van Hemmen & T. Sejnowski (Eds.) — Oxford University Press — 2006
- How to Create a Mind: The Secret of Human Thought Revealed — R. Kurzweil — Viking — 2012
Grading Policy
| 구분 | 비율 |
|---|---|
| Two Open-book Exams | 60% |
| Presentation & Term Paper | 30% |
| Participation & Discussion | 10% |
Course Schedule
| Week | Date | Topics |
|---|---|---|
| 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 |
| 2 | 3/15 | Arbib, Grossberg & Sejnowski · Kurzweil [2]: The biologically inspired digital neocortex (Ch. 7) & The mind as computer (Ch. 8) |
| 3 | 3/22 | Jeff Hawkins & Tomasso Poggio · Wiskott: How does our visual system achieve shift and size invariance? (Ch. 16) · Abbott: Where Are the Switches on This Thing? (Ch. 21) |
| 4 | 3/29 | Jack Gallant & Itzhak Fried · Crick & Koch: What are the neuronal correlates of consciousness? (Ch. 23) · Sejnowski: What Are the Projective Fields of Cortical Neurons? (Ch. 19) |
| 5 | 4/5 | Earl Miller & Gyorgy Buzsaki · Laurent: Shall we even understand the fly’s brain? (Ch. 1) |
| 6 | 4/12 | Karel Svoboda · van Vreeswijk: What is the neural code? (Ch. 8) · Kenet et al.: Are single neurons soloists or obedient members of a huge orchestra? (Ch. 9) |
| 7 | 4/19 | Poster Presentation 1 |
| 8 | 4/26 | Exam 1 |
| 9 | 5/3 | Stephen Smith & Seth Grant · Gerstner: How can the brain be so fast? (Ch. 7) · Fuster & Edelman · Ramachandran & Hubbard: Synesthesia (Ch. 22) |
| 10 | 5/10 | Clay Reid & Markus Meister · Zucker: Which computation runs in visual cortical columns? (Ch. 11) |
| 11 | 5/17 | Holiday (Buddha’s Birthday) |
| 12 | 5/24 | Tony Bell & Bruno Olshausen · Olshausen & Field: What is the other 85 percent of V1 doing? (Ch. 10) · Carr et al.: Are Neurons Adapted for Specific Computations? (Ch. 12) |
| 13 | 5/31 | Mark Gluck, Geoffrey Hinton & Tom Mitchell · Herz: How Is Time Represented in the Brain? (Ch. 13) · McAlphine & Palmer: How general are neural codes in sensory systems? (Ch. 14) · Iclump: How Does the Hearing System Perform Auditory Scene Analysis? (Ch. 15) |
| 14 | 6/7 | Poster Presentation 2 |
| 15 | 6/14 | Exam 2 |
| 16 | 6/21 | Reviews and Discussion |