Welcome to the NICO Reading Group Wiki!
The Northwestern Institute for Complex Systems Reading Group is for graduate students, post-docs, and interested researchers who are doing research or have an interest in complex systems. Complex Systems is an inherently multidisciplinary approach and so this group is open to interested parties in any discipline. This group will meet on a regular basis (typically every 2 weeks) to discuss research papers on a wide variety of topics related to complex systems including but not limited to: agent-based modeling, social networks, nonlinear dynamics, cellular automata, artificial life, global systems, robustness, scaling laws, social dynamics, markets, communication, human language, behavior, biological computation, cognitive neuroscience, and adaptive computation.
Next Meeting
- Tuesday, December 1st, 5-7 PM
- Location: Chambers Hall (Lower level), 600 Foster Street, Evanston
- Topic: Neural Networks
- Readings:
- A. Kepecs, et al. 2002. Spike-timing-dependent plasticity: common themes and divergent vistas, Biol.Cybern. 87, 446–458. http://www.springerlink.com/content/qh0ju6hc19mm070m/fulltext.pdf
- J. C. Reijneveld, et al., 2007. The application of graph theoretical analysis to complex networks in the brain. Clinical Neurophysiology 118 (11): 2317-2331. http://www.sciencedirect.com.turing.library.northwestern.edu/science?_ob=MImg&_imagekey=B6VNP-4PS5KD3-2-J&_cdi=6184&_user=965532&_orig=search&_coverDate=11%2F30%2F2007&_sk=998819988&view=c&wchp=dGLzVtb-zSkzk&md5=49cfdd7b952632e420ab1f1c469957aa&ie=/sdarticle.pdf
- Suggested reading: K. Gurney, 2007. Neural networks for perceptual processing from simulation tools to theories. Phil. Trans. R. Soc. B 362: 339–353. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2323553/pdf/rstb20061962.pdf/?tool=pmcentrez
- FOOD sponsored by NICO
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Topics for upcoming meetings
Upcoming Meetings
Topics: Information Theory, Statistical Regression, Neural Networks, ABMs, Networks, Economics and Networks, Economic Self-Organization, Social Networks, Shannon's Information Theory
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