People

Research for patient benefit: MRI physics, MRI safety, image analysis and clinical application of AI

Extraction of morphological networks based on structural MRI, analysing network measures that can help in providing neuroimaging makers for dementia.

My research interests are focused on Complexity issues. In general, the complex systems that I research involve Coupled Dynamical Systems, namely, many non-trivially interacting sub-systems. I try to measure, explain, and/or predict their collective behaviour (for example, the emergence of synchronization or chaotic dynamics) in terms of how they are inter-connected, namely, in terms of the topological features of the underlying network topology (i.e., Graph Theory).

In particular, I am fascinated by Network Neuroscience research, where Complexity challenges abound -- neurons in the brain create a myriad of dynamical behaviours due to their intricate connectivity and complex substrate and our observations can only access these behaviours by indirect measurements. Hence, I am intereseted in questions such as, how do we manage to infer the brain's connectivity from indirect measurements (e.g., EEGs or MRIs)? how do particular diseases (e.g., Alzheimer's disease or chronic depression) affect the brain's connectivity? what data-driven conclusions can we draw from studying different states of consciousness (e.g., REM sleep)? and how can we develop/improve methods (both, in data acquisition and analysis) to increase our unserstanding of these issues?