Exploring the specificity of the relationship between cortical network function and biological simulation parameters.

by David Gomez-Cabrero (Clinical Gene Networks, Karolinska Institutet)

Friday 11 Jun 2010, 10:00 → 11:00 Europe/Stockholm

RB35

We present a computational strategy to explore parameter space for the case of large-scale biological neural network simulations. We focus on a specific neural function, visuo-spatial working memory, and we construct a biological neural network that mimics the cortical network. The strategy is divided in two steps. In the first step parameter space is explored in order to find sets of parameters such that the network sustains persistent activity; to this end, we design several evaluation functions that quantify this ability and weigh them in a proper way. The second step analyses the sets of parameters found by exploring and typifying the different areas of solutions. We found that solutions can be classified in terms of characteristics, behaviour and space regions.