Computational Neuroscience Thursday Research Club

3:00 pm Thursday, HSB G417 followed by tea at 4:00 pm (unless otherwise noted)

2013 Series

3/7 Michael Buice
Allen Institute of Brain Science
Neural Kinetic Theory: From Dynamics to Stochastics
The complexity of the human brain is necessarily reflected in theoretical and computational models. I will describe an approach to the mathematical analysis of neural networks which renders this complexity tractable, the application of many-body techniques to complex neural networks. This approach yields tractable equations for the collective dynamics of the network, as well as the network statistics in the form of “multi-neuron correlation functions.” I will show how the network level correlations, specifically those arising from finite size effects, can impact fundamental dynamical properties such as stability. In addition, it will be seen that network heterogeneity can give rise to an effective stochastic equation obeyed by the individual neurons
4/11 Valentin Dragoi
Department of Neurobiology and Anatomy, University of Texas Houston
Plasticity in population coding in cortical networks
3.30pm, HSB G328
5/2 Daniela Witten
Department of Statistics, University of Washington
5/16 Liam Paninski
Columbia University
Boeing Seminar: Challenges and opportunities in statistical neuroscience
4.00pm, Miller Hall 301
6/13 Stefan Mihalis
Theory Group, Allen Institute for Brain Science

2012 Series

4/5 Research club: Bair lab
4/12 Students invited for pre-talk meeting 2:30 – 3:30 in Guggenheim
Lai-Sang Young gives Boeing Seminar at 4 PM
4/19 Phil Holmes, Princeton University
Host: Eric Shea-Brown (etsb@uw.edu)
4/26 Students invited 2:30 – 3:30 for pre-talk meeting in Guggenheim
Larry Abbott gives Boeing Seminar at 4 PM
Host: Nathan Kutz (kutz@uw.edu)
5/3 Research club: Shadlen lab
5/10 Research club: Rieke lab
5/17 Emilio Salinas, Wake Forest University
Host: Raj Rao (rao@cs.washington.edu)
5/24 Surya Ganguli, Stanford
Host: Eric Shea-Brown (etsb@uw.edu)
5/31 Larry Sorenson, Applied Physics
6/7 Mike Shadlen, UW