The study of brain connectivity is a very important and productive subfield of neuroscience that will keep growing in the following years. Large efforts of data analysis from EEG and fMRI data, as well as of modelling brain activity have been accomplished recently. Here, we have identified two fundamental problems that the field is facing in order to develop further. First, a common factor in the current models of cortical networks is their lack of external stimulation, i.e. they only simulate cortical activity that emulates the resting-state. But the brain is responsible for collecting and processing information of the environment, and therefore, its function cannot be understood in the absence of external stimuli. Second, current EEG and fMRI techniques provide an extremely valuable window into the working brain by detecting the degree of activation of brain regions. However, there is currently no framework to understand which are the precise information processes happening at the neuronal level behind the observed activations. Inspired by these questions, we present an interdisciplinary project that aims at establishing grounding work for the future advances in those problems:

1.  We will perform a systematic investigation of the impact of external stimulation in models of cortical networks. The dependence of the emerging collective dynamical phenomena will be studied in terms of the network topology and of the physical properties of the stimuli.
2.  We will develop information theoretical measures to quantify the degrees of segregation and integration caused in the brain by the presence of external stimulation, and
3. We will apply those measures to specifically designed EEG experiments for corroboration.