CPSC 689-603 Computations in Neural and Biological Systems:
Spring 2005


NEWS: 5/10/05, 10:47PM (Tue)
Read-Only Bulletin Board.: 1/6/05, 04:42PM (Thu)

Page last modified: 4/27/05, 02:55PM Wednesday.

General Information Resources Reading List Weekly Schedule Lecture Notes

I. General Information


Dr. Yoonsuck Choe
Email: choe(a)tamu.edu
Office: HRBB 322B
Phone: 845-5466
Office hours: 1-2pm, MWF


CPSC 625, or consent of instructor.


MWF 11:30am-12:20pm HRBB115.


What is the nature of computation in neural and biological systems that enable complex adaptive behavior in organisms? The focus of this course is to address this very question from various different perspectives. Select topics from computational neuroscience, computational vision, and cognitive science (and artificial intelligence) will be reviewed and critiqued. In the first few weeks, basic computational and mathematical preliminaries, as well as neuroscience basics will be covered. Afterwards, a selected collection of current research papers will be discussed. The course is designed to be open-ended to some degree, and a large portion of the time will be dedicated to discussion of the topics.


The goal of this course is to
  1. learn basic computational and mathematical tools for investigating computations in neural and biological systems;
  2. get acquaninted with diverse computational approaches to the understanding of brain function; and
  3. explore how the seemingly disjoint topics can be integrated in a unique synthesis.


Administrative Trivia:

  1. Computer accounts: if you do not have a unix account, ask for one on the CS web page.
  2. We will use Matlab(tm) (there is also an excellent open source clone called GNU/Octave). Matlab is installed on all SunOS machines (and also on the Windows machines -- I've got to check).

Topics to be covered:

See the Weekly Schedule section for more details.


  1. Assignments (30%20%): short programming assignment (10% each).
  2. Paper comments (20%): for the reading assignments each week, a brief (one paragraph) comment/critique must be submitted. Occasionally, the instructor will ask a specific question or ask the student to comment on a particular aspect of the paper.
  3. Paper presentation (10%): each student will study and present a paper from the reading list. The term project may be loosely based on this paper.
  4. Term project (30%): 6-7 page term paper (double spaced) describing the project, and project demo and a presentation (20 minutes + 5 minutes Q/A). The project can either be done individually or as a team of two to three.
  5. Take-home midterm (10%)
Grading will be on the absolute scale. The cutoff for an `A' will be at most 90% of total score, 80% for a `B', 70% for a `C', and 60% for a `D'. However, these cutoffs might be lowered at the end of the semester to accomodate the actual distribution of grades.

Academic Policy:

The TAMU student rules (http://student-rules.tamu.edu/), Part I Rule 20 will be strictly enforced.

Students with Disabilities:

The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact the Department of Student Life: Services for Students with Disabilities in Room 126 of the Koldus Building, or call 845-1637. (The source of this passage is TAMU Phil320 Syllabus.)


  1. Neural Networks: Sharewares and Freewares (Thanks to Subru)
  2. Thalamus slices
  3. Neuroscience Tutorial at The Washington University School of Medicine. (Thanks to Barani)
  4. Research resources page
  5. Ganeral reading list (u: p: ): includes short blurb about how to find, read, and critique others' work. This list is not the course reading list.

III. Weekly Schedule and Class Notes

Under heavy construction
Notices and Dues
1 1/17 MLK Day (Holiday)      
1 1/19 Introduction       slide01.pdf
1 1/21 Nervous system basics Handouts, and Stevens "The Neuron" in the paper packet     slide02.pdf
2 1/24 Intro wrap up     slide02.pdf
2 1/26 Probability/Bayesian framework Ballard chapter 2; Knill et al. (1996): from the reading list     slide03.pdf
2 1/28 Information theory   Paper commentary #1 assigned   slide04.pdf
3 1/31 Bayesian vs. Info Theory / Self-organization Ballard chapter 2; Bell (1999); Langlois and Garrouste (1997)   Paper commentary #1 due (in class) slide04.pdf
3 2/2 Cognition/ Redundancy/ Learning Langlois and Garrouste (1997)     slide05.pdf
3 2/4 Computationalism Searle (1997; reading list; photocopy TBD) Paper commentary #2 assigned   slide06.pdf
4 2/7 Action and Semantics Choe and Bhamidipati (2004; reading list; Bio-ADIT)     slide07.pdf
4 2/9 Action and Semantics Choe and Bhamidipati (2004; reading list; Bio-ADIT)     slide07.pdf
4 2/11 Eigenbehavior von Foerster (2003; Chapter 11)   Paper commentary #2 due slide08.pdf
5 2/14 Inferring Space from Sensorimotor Dependencies Philipona et al. (2003; reading list) Paper commentary #3 assigned   slide09.pdf
5 2/16 Imitation Arbib (2003; pp606-611; photocopy)     slide10.pdf
5 2/18 Schema theory Arbib (1996; reading list; photocopy)     slide11.pdf
6 2/21 Imitation using Bayesian approach Rao et al. (2004)   Paper commentary #3 due slide12.pdf
6 2/23 Interactive vision Churchland et al. (1994; readling list; photocopy)     slide13.pdf
6 2/25 Dynamical systems Beer (2000; reading list); Ballard chapter 5     slide14.pdf
7 2/28 Thalamus Hill and Tononi (2003; reading list); Guillery and Sherman (2002; reading list)     slide15.pdf
7 3/2 Thalamus and Analogy Choe (2003; reading list; IJCNN pp.1480-1485)     slide16.pdf
7 3/4 Analogy with Binary Spatter Code Kanerva (1998; reading list -- both)     slide17.pdf
8 3/7 Evolutionary Learning Gomez and Miikkulainen (1998; reading list)     slide18.pdf
8 3/9 Time: Neural mechanisms of delay compensation Ask me for a draft paper     slide19.pdf
8 3/11 Time: Flash-lag effect Ask me for a draft paper     slide20.pdf
9 3/14 Spring Break     No class
9 3/16 Spring Break     No class
9 3/18 Spring Break     No class
10 3/21 Rhythm recognition Buisson, J.-C., A rhythm recognition computer program to advocate interactivist perception, Cognitive Science, 28:75-87, 2004 [PDF] (demo)     slide21.pdf
10 3/23 Natural scene statistics Lee and Choe (2003; reading list; IJCNN pp.206-211), Barlow (2001)     slide22.pdf
10 3/25 Reading Day No Class   Miniproject due 11:59pm (use csnet turnin)
11 3/28 Self-organization in the visual cortex Choe and Miikkulainen (Biol. Cyb. 2004)   Midterm 3/29 4pm, room 307 slide23.pdf
11 3/30 Self-organization in the visual cortex Choe and Miikkulainen (Biol. Cyb. 2004)     slide23.pdf
11 4/1 No class   To attend WAM-BAMM'05; Make-up (Out-of-class Midterm 3/29)    
12 4/4 Presentation Hari   4/5: Q-drop
12 4/6 Presentation Marco, David    
12 4/8 Presentation Ji Ryang, (Seungjin)    
13 4/11 Presentation Takao, Jyh-Ming    
13 4/13 Visual illusions Yu and Choe (2004)     slide24.pdf
13 4/15 Alternative essenses of AI Brooks (1998; reading list)     slide25.pdf
14 4/18 3D vs. 2D processing of texture Oh and Choe (2004)     slide27.pdf
14 4/20 Active Vision Granlund (1998)     slide26.pdf
14 4/22 Context-sensitive Clustering Yu, Gutierrez-Osuna, and Choe (2005)     slide28.pdf
15 4/25 Scintillating Grid Illusion Yu and Choe (2004)     slide29.pdf
15 4/27 Andy Clark - Embodiment and Ecological Control Virtual Colloquim at the Cognitive Science Society      
15 4/29 Project presentation David (and potentially Hari)      
165/3Project presentation and Course wrapup  

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