English

NetGrowth_AQ_thesis

Advancing in biological comprehension and technology allows for more complex in vitro experiments. C. Villard’s group at Ipgg in Paris [Renault, 2015], as well as other authors [Smirnov, 2014], performs studies on the environmental interaction of growth cones with different substrates and mechanical confinements; the results of such studies are relevant for medical application as for fundamental understanding of growth cone inner mechanisms. On the other side the investigation for the neuronal code bring researchers to study the spontaneous activity in vitro, shading the light on the bursting phenomenon and it’s spatial properties [Orlandi et al., 2013]. To reproduce such dynamics a useful tool as NEST can be used, a powerful open-source simulator reproducing neuronal activity with eligible complexity. However any tool is available to reconstruct the network morphology or topology with a biological hint. The Neurophysics group at Diderot try to collect theories and results from biophysics and biologists to fit them up in an efficient neuronal growth simulator, NetGrowth. The simulator is built up with the idea of modularity, letting the researcher to choose the complexity level of

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