The importance of objectively comprehending the different relationships among the differently specialized brain structures assumes a relevant role in the Neuroscience. In this regard, my research aims at concisely construing the complex functional networks of the brain by using theoretical graph approaches. 

The body of techniques related to graph theory is strongly wide-scope and applies to networks at different scale. This advance has the merit to uniform the treatment of the cerebral connectivity patterns even if the methodologies employed for their estimation could be so different. 

My research field (Brain Network Analysis) is inserted within the activity of the Neuroelectrical Imaging and Brain Computer Interfacing laboratory at the Scientific Institute for Research, Hospitalization and Health Care "Fondazione S.Lucia". The core of the laboratory is represented by the merging of bioengineering and clinical neurophysiology expertises on four main themes:

1. High Resolution EEG, concerning the development of advanced processing methods of electroencephalographic (EEG) signals related to the solution of the linear inverse problem to non-invasively estimate the cortical functional activities.

2. Functional Brain Connectivity, dedicated to the implementation of multivariate autoregressive models (MVAR) for the estimation of causality networks among the activities of different cortical areas in the frequency domain.

3. Brain Network Analysis, devoted to the extraction of relevant features from complex graphs allowing for the generation and testing of particular hypotheses on the physiologic nature of the functional networks estimated from high resolution EEG recordings.

4. Brain Computer Interface, the implementation of a real-time EEG-based brain computer interface (BCI) to investigate the use of this type of BCI as an aid to enhance (or even to allow) the functional independence of persons with different degrees of motor disability.