Network Theorizing: From Molecules to Societies
Cognitive Science 200
Winter, 2016

Meeting for Enrolled Students: Fridays, 2:00-2:55

Lecture to which UCSD community is invited: 3:00 to 4:30

Both in Cognitive Science Building, Room 003

Professor: William Bechtel Office Hours: Wednesday, 3:30-4:50
Office: HSS 8076 Email: bechtel@ucsd.edu
Telephone: 822-4461 Wiki site: http://mechanism.ucsd.edu:8080/Networks

Description

Network theorizing is playing a major role in a wide range of disciplines, from cell and molecular biology to the social sciences. This course will explore the various roles network theorizing is playing across this range of disciplines, with the goals of discovering whether there are common principles and how different disciplines might gain from the insights developed in the others.

Cog Sci. 200 is structured around a series of lectures. These lectures are open to the entire UCSD communiity, but they are invited for the course and students in the course are encouraged to be active in the discussions at the lectures. As preparation for the lectures, we will meet for an hour before the lecture and discuss papers relevant to the topic of the lecture.

Overview of Schedule

Date

Speaker

Topic of Talk

Readings
January 8
No lecture: Class goes until 4:30
William Bechtel, Philosophy, UCSD Basics of network analysis 1. Watts, D., & Strogratz, S. (1998). Collective dynamics of small worlds. Nature, 393, 440-442.
2. Barabási, A.-L., & Bonabeau, E. (2003). Scale-free networks. Scientific American, 50-59.
3. Alon, U. (2007). Network motifs: Theory and experimental approaches. Nature Reviews Genetics, 8, 450-461.
January 15 Trey Ideker, UCSD Department of Medicine and Biomolecular networks 1. Hofree, M., Shen, J. P., Carter, H., Gross, A., & Ideker, T. (2013). Network-based stratification of tumor mutations. Nature Methods, 10, 1108-1115.
2. Dutkowski, J., Kramer, M., Surma, M. A., Balakrishnan, R., Cherry, J. M., Krogan, N. J., & Ideker, T. (2013). A gene ontology inferred from molecular networks. Nat Biotechnol, 31, 38-45.
January 22 Hannah Carter, UCSD, Department of Medicine Disease networks 1. Engin, H. B., Hofree, M., & Carter, H. (2015). Identifying mutation specific cancer pathways using a structurally resolved protein interaction network. Pac Symp Biocomput, 84-95.
January 29 Gary Cottrell, Computer Science and Engineering, UCSD Artificial neural networks

1. McClelland, J. L., & Rumelhart, D. E. (1981). An Interactive Activation Model of Context Effects in Letter Perception: Part I. An Account of Basic Findings. Psychological Review, 88, 375-407.
2. Dailey, M. N., Cottrell, G. W., Padgett, C., & Adolphs, R. (2002). EMPATH: A neural network that categorizes facial expressions. Journal of Cognitive Neuroscience, 14, 1158-1173.

February 5 Lev Tsimring, BioCircuits Institute, UCSD Synthetic gene networks 1. Ahmad S. Khalil & James J. Collins. Synthetic biology: applications come of age. Nature Reviews Genetics 11, 367-379 (May 2010).
2. Adrian L. Slusarczyk, Allen Lin & Ron Weiss. Foundations for the design and implementation of synthetic genetic circuits. Nature Reviews Genetics 13, 406-420 (June 2012).
3. Tal Danino, Octavio Mondrag├│n-Palomino, Lev Tsimring & Jeff Hasty. A synchronized quorum of genetic clocks. Nature 463, 326-330 (21 January 2010).
February 12 Andrea Chiba, Cognitive Science and Neurosciences, UCSD Brain networks 1. Chiba, A. A., & Quinn, K. L. (2008). Basal forebrain and memory. In H. Eichenbaum (Ed.), Memory systems (Vol. 3 of Learning and memory: A comprehensive reference, pp. 281-302). Oxford: Elsevier.
February 19 Bradley Voytek, Cognitive Science, UCSD Coordinated oscillations in brain networks

1. Buzsaki, G., & Draguhn, A. (2004). Neuronal Oscillations in Cortical Networks. Science, 304, 1926-1929.
2. Fries, P. (2005). A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends in Cognitive Sciences, 9, 474-480.
3. Voytek, B., Kayser, A. S., Badre, D., Fegen, D., Chang, E. F., Crone, N. E., Parvizi, J., Knight, R. T., & D'Esposito, M. (2015). Oscillatory dynamics coordinating human frontal networks in support of goal maintenance. Nature Neuroscience, 18, 1318-1324

February 26 No meeting    
March 4 Noa Pinter-Wollman, BioCircuits Institute, UCSD Agent networks 1. Pinter-Wollman, N., Wollman, R., Guetz, A., Holmes, S., & Gordon, D. M. (2011). The effect of individual variation on the structure and function of interaction networks in harvester ants. J R Soc Interface, 8, 1562-1573.
2. Pinter-Wollman, N., Hobson, E. A., Smith, J. E., Edelman, A. J., Shizuka, D., de Silva, S., Waters, J. S., Prager, S. D., Sasaki, T., Wittemyer, G., Fewell, J., & McDonald, D. B. (2014). The dynamics of animal social networks: analytical, conceptual, and theoretical advances. Behavioral Ecology, 25, 242-255.
3. Pinter-Wollman, N. (2015). Nest architecture shapes the collective behaviour of harvester ants. Biol Lett, 11.
March 11 Massimo Franceschetti, Electrical and Computer Engineering, UCSD Social networks

1. Coviello, L., Fowler, J. H., & Franceschetti, M. (2014). Words on the Web: Noninvasive Detection of Emotional Contagion in Online Social Networks. Proceedings of the Ieee, 102, 1911-1921.
2. Coviello, L., & Franceschetti, M. (2015). An instance of distributed social computation: the multi-agent group membership problem. Control of Network Systems, IEEE Transactions on, PP, 1-

Course Requirements and Evaluation

This course should be taken for S/U grade only. If there is some reason you need a letter grade, you must tell me at the outset and get my approval. Note: If you are taking the course for a letter grade, the research paper is not optional.

Students are required to:

  1. Attend all class sessions, both the class-only meeting from 2:00 to 2:55 and the lecture from 3:00 to 4:30 and complete the readings assigned before each meeting. This is a necessary conditions and absences require a good justification and must be approved.
  2. For each week, prepare a 1-2 page essay responding to the assigned readings. This paper should be posted on the course wiki site ()http://mechanism.ucsd.edu:8080/Networks) by Wednesday at 5pm. In these essays you will be expected to engage one of the readings in a critical fashion. The goal is not to summarize the paper since everyone will have read the paper. Rather do one or more of the following or something similar: (1) identify ideas that you find novel and exciting, (2) show a way in which the claims or arguments of the paper might be questioned, or (3) shows some important implications or applications of the ideas in the paper. (60% of grade if S/U; 30% if letter grade)
  3. For each week, read and post a comment on the course wiki site on at least two other students' essays before class and participate in the discussion in class (40% of grade if S/U; 20% if letter grade)
  4. Write a paper (approximately 5,000 words) that addresses the use of network theorizing in at least one discipline. This paper should clearly draw upon and make use of the readings and lectures in this course, but it should advance a specific thesis and develop original arguments for that thesis. Due March 13, Noon. (50% if letter grade) For those taking the course S/U, this paper is optional and it or a shorter version (to be negotiated) could be used to make up for missed or poor work on one of the weekly assignments.