CPSC 644-600 Cortical Networks:
Spring 2007

Syllabus

NEWS: 5/8/07, 12:40PM (Tue)
Read-Only Bulletin Board.: 3/19/07, 01:21PM (Mon)

Page last modified: 2/27/07, 01:59PM Tuesday.

General Information Resources Reading List Weekly Schedule Lecture Notes Course Material

I. General Information

Instructor:

Dr. Yoonsuck Choe
Email: choe(a)tamu.edu
Office: HRBB 322B
Phone: 845-5466
Office hours: 3pm-4pm, MWF

TA: N/A

Prerequisite/Restrictions:

CPSC 420, 625, 636, or 633 (or equivalent) and graduate classification; or consent of instructor.

Lectures:

MWF 1:50--2:20pm HRBB 126.

Introduction:

From the course catalog: The architecture of the mammalian cerebral cortex; its modular organization and its network for distributed and parallel processing; cortical networks in perception and memory; neuronal microstructure and dynamical simulation of cortical networks; the cortical network as a proven paradigm for the design of cognitive machines.

About this semester: This course will provide necessary background for modeling the structure (anatomy), function (physiology), and growth (development) of neurons, neuronal circuits, and neuronal networks. Various computational concepts, techniques, and tools necessary for modeling neural systems will be introduced. A selected set of latest papers in the field of computational neuroscience and neuroinformatics will be surveyed.

Textbook:

Administrative Trivia:

  1. Computer accounts: if you do not have a unix account, ask for one on the CS web page.
  2. Programming languages permitted: C/C++, Java, or Matlab (or octave), and must be executable on CS unix hosts or any windows system in the departmental lab.

Topics to be covered:

See the Weekly Schedule section for more details.

Grading:

  1. Quiz (one or two): 10%
  2. Paper commentaries (6 to 7, each one paragraph long): 30%
  3. Programming assignments/exercises (about 3): 10% each = 30%
  4. Term project: proposal, presentation, final report 40%
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 Integrity Statement:

AGGIE HONOR CODE: An Aggie does not lie, cheat, or steal or tolerate those who do.

Upon accepting admission to Texas A&M University, a student immediately assumes a commitment to uphold the Honor Code, to accept responsibility for learning, and to follow the philosophy and rules of the Honor System. Students will be required to state their commitment on examinations, research papers, and other academic work. Ignorance of the rules does not exclude any member of the TAMU community from the requirements or the processes of the Honor System.

For additional information please visit: http://www.tamu.edu/aggiehonor/

Local Course Policy:

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 Cain Hall or call 845-1637.

Resources:

  1. Research resources page
  2. 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

Week
Date
Topic
Reading
Assignments
Notices and Dues
Notes
1 1/15 MLK Day (Holiday)        
1 1/17 No class Class canceled due to the weather      
1 1/19 Introduction Course overview     slide01.pdf
2 1/22 Introduction Essential terminology and neuroanatomy     slide02.pdf
2 1/24 Neuron: Physiology Shepherd: Chapter 2     slide03.pdf
2 1/26 Neuron: Computational models Dayan and Abbott: Chapter 5, Appendix A.4     slide04.pdf
3 1/29 Neuron: Computational models Dayan and Abbott: Chapter 5, Appendix A.4   Quiz slide05.pdf
3 1/31 Neuron: Computational models Dayan and Abbott: Chapter 5, Appendix A.4     slide05.pdf
3 2/2 Thalamus Shepherd: Chapter 8     slide06.pdf
slide07.pdf
4 2/5 Thalamus Model Choe (2004) [PDF]     slide08.pdf
4 2/7 Thalamus Model Choe (2004) [PDF]     slide08.pdf
4 2/9 Neuron: Plasticity Dayan and Abbott: Chapter 8     slide09.pdf
5 2/12 Neuron: Plasticity Dayan and Abbott: Chapter 8     slide09.pdf
5 2/14 Neural Encoding Dayan and Abbott: Chapter 1     slide10.pdf
5 2/16 Neural Encoding Dayan and Abbott: Chapter 1     slide10.pdf
6 2/19 Visual System: Computation Miikkulainen et al. [eBook]: Chapter 1,2,3     slide11.pdf
6 2/21 Visual System: Development Miikkulainen et al.: Chapters 4 and 5     slide11.pdf
6 2/23 Visual System: Development Miikkulainen et al.: Chapters 4 and 5     slide11.pdf
7 2/26 Delay Compensation Lim and Choe (2006) [PDF]     slide12.pdf
7 2/28 Neocortex Shepherd: Chapter 12; Douglas and Martin (2004) [PDF]     slide13.pdf
7 3/2 Basal Ganglia Shepherd: Chapter 9     slide14.pdf
8 3/5 Motor System: Decoding Internal State Choe and Smith (2006) [PDF]   Homework 1 due slide15.pdf
8 3/7 Motor System: Decoding Internal State Choe and Smith (2006) [PDF]     slide15.pdf
8 3/9 Computational Tools Showcase Topographica, xppaut, octave, SIDA, neuroevolution     slide16.pdf
9 3/12 Spring break        
9 3/14 Spring break        
9 3/16 Spring break        
10 3/19 Motor System: RF Development Reto Wyss et al. (2006) [PDF]     slide17.pdf
10 3/21 Motor System: Response Tuning Emilio Salinas (2006) [PDF]     slide18.pdf
10 3/23 Motor System: RF Development Floreano et al. (2005) [PDF]     slide19.pdf
11 3/26 Natural Images: Response Statistics and Salience Choe and Sarma (2006) [PDF]     slide20.pdf
11 3/28 Natural Images: Statistical Structure Xiuwen Liu and DeLiang Wang (2002) [PDF] Homework 2 announced   slide21.pdf
11 3/30 Neuron Morphology De Schutter: Chapter 6 and 7     slide22.pdf
12 4/2 Neuron Morphology De Schutter: Chapter 6 and 7     slide22.pdf
12 4/4 Neuron Morphology: Statistical Description Ascoli et al. (2001) [PDF]     slide23.pdf
12 4/6 No class Reading day   Homework 2 due (3pm, HRBB 322B)  
13 4/9 Network Analysis: Complexity Sporns and Tononi (2002) [PDF]; Sporns et al. (2004) [PDF]     slide24.pdf
13 4/11 Guest Lecture Helga Kocurek will present Nicholas Humphrey's book A History of the Mind, Harper Collins, 1992      
13 4/13 No class Trip      
14 4/16 Network Analysis: Shortest Path Kaiser and Hilgetag (2006) [PDF]     slide25.pdf
14 4/18 Network Analysis: Dynamics Thiel et al. (2003) [PDF]     slide26.pdf
14 4/20 Network Analysis: Dynamics Thiel et al. (2003) [PDF]     slide26.pdf
15 4/23 Systems Neuroscience Van Hemmen and Sejnowski: Chapters 1, 13, and 19     slide27.pdf
15 4/25 Dynamics Heinz Von Foerster     slide28.pdf
15 4/27 Virtual Guest Lecture Cognitive Science Society's Virtual Colloquim Series: Andy Clark, on Embodiment and Ecological Control (view at home)      
16 4/30 Project Presentation        
165/1Project presentation and Course wrapup  


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