This document is divided in three parts: In Part I, "Technical information", we specify the justification of the study, the state of the art, the scope of the research and the required specifications. In Part II, "Complex networks and noise in neuroscience: an introduction", we introduce the basic neuroscience concepts to understand the work of this project, explaining, for example, the types of models used to represent neural networks. We explain what is a neuron and which considerations we have in mind to simplify its behavior considering that they are perturbed by noise. Furthermore, complex networks and mathematical concepts to characterize them and to analyze them will be exposed. And, finally, we explain the stochastic resonance phenomenon, in which we will focus our dynamical study, and its advantages. In Part III, "Numerical methods and results", we describe the main characteristics of the program developed to do the calculations and we expose all the results obtained, for small to large networks. To conclude the project, we finish with the conclusions and further work. In the last part, the Appendices, we provide the source code of the program developed and the study costs.