INTERESTS: Neuroscience, Biomedical Engineering, Mathematical modeling, Brain Computer Interface.
Electrophysiological tools to assess brain activity.
The development of a wide variety of neuroimaging methods based on Magnetic Resonance Imaging has opened new ways for studying brain organization and functioning with high spatial resolution but it has also made clear that the complex functions of the human brain such as cognition, language, attention and several pathologies are not fully explained by only considering the activation of spatially fixed cerebral structures. Rather we need to consider brain functioning as networks of structures that dynamically interact through electrical signals coded by different frequencies. To thoroughly investigate the dynamics of such networks it is important to also use other techniques such as EEG and MEG, which provide direct measurements of the brain electrical activity with high temporal resolution. In this lecture, we will present classical and novel strategies for the analysis of EEG\MEG data, from statistical measures for detection of the Event Related Brain Dynamics, to methods of dimensionality reduction and the combination of multidimensional analysis with source localization methods. We will describe new approaches for obtaining space-time-frequency characterization of brain electrical activity at the level of neural sources.