I’m giving a computational neuroscience lunch seminar today at Johns Hopkins. I will be talking about my work with Michael Buice, now at the Allen Institute, on how to go beyond mean field theory in neural networks. Technically, I will present our recent work on computing correlations in a network of coupled neurons systematically with a controlled perturbation expansion around the inverse network size. The method uses ideas from kinetic theory with a path integral construction borrowed and adapted by Michael from nonequilibrium statistical mechanics. The talk is similar to the one I gave at MBI in October. Our paper on this topic will appear soon in PLoS Computational Biology. The slides can be found here.
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Scientific Clearing House 
[…] Michael Buice and I have finally published our paper entitled “Dynamic finite size effects in spiking neural networks” in PLoS Computational Biology (link here). Finishing this paper seemed like a Sisyphean ordeal and it is only the first of a series of papers that we hope to eventually publish. This paper outlines a systematic perturbative formalism to compute fluctuations and correlations in a coupled network of a finite but large number of spiking neurons. The formalism borrows heavily from the kinetic theory of plasmas and statistical field theory and is similar to what we used in our previous work on the Kuramoto model (see here and here) and the “Spike model” (see here). Our heuristic paper on path integral methods is here. Some recent talks and summaries can be found here and here. […]
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Hi, I think your site might be having browser compatibility issues.
When I look at your website in Firefox, it looks fine but when opening in Internet Explorer, it has some overlapping.
I just wanted to give you a quick heads up!
Other then that, superb blog!
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Thanks but I think that may be a wordpress problem so I don’t know how to fix it.
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