Roberto Carlos Sotero-Diaz
Ph.D. (Doctor of Philosophy)
Research and teaching
My primary research interest is the development and identification of computational models of brain activity (electrical, metabolic and hemodynamic) in order to clarify how the signals we record in Neuroimaging (fMRI, PET, DWMRI) and Electrophysiology (EEG) are generated. My research comprises two complementary approaches: Forward Problem: I develop computational models of the generation of EEG rhythms and fMRI signals, and study how these models can be coupled. Thus, these theoretical biophysical models allow us to study the link between metabolism (glucose and oxygen consumption), cerebral blood flow, electrical activity (postsynaptic potentials and action potentials) and the Blood-oxygenation level dependent (BOLD) response, and the specific role of excitation and inhibition in this coupling. Inverse problem: Here I fit to real data, the models I previously developed. I focus on estimating effective connectivity, and other biophysical parameters. The use of a Bayesian model comparison framework provid us with a tool for selecting the best between different plausible models.
Additionally, I’m interested in the study of the statistical properties of anatomical (using DWMRI data) and functional brain networks (using EEG data). Results from these studies allow us to introduce anatomical and functional constraints in the models. For instance, in the generative EEG and EEG/fMRI models I have proposed, the brain areas were connected using an average anatomical connectivity matrix estimated from DWMRI data.