My interests

Multiscale dynamics of macroscopic networks

I want to understand how the spatial organization of networks changes over time, and how brain regions and even entire networks interact via oscillations. A full description of network dynamics includes (at least) these three components: spatial, temporal, and frequency domain. Neural activity on the macroscopic scale spreads along anatomical connections, which means that the underlying white matter scaffold plays an important role in shaping observed neural activity. How does this relationship between structure and function depend on the time scale and on the nature of the neural signal? These questions are the reason why I work with multimodal approaches, combining MRI and EEG for now, but curious about other techniques as well.

Harmonic modes

The brain can be conceptualized as a graph, where brain regions are the nodes of the graphs and these nodes are connected so brain regions can interact. Once we start thinking of the brain as a graph, we can use tools from other areas of science and engineering. Graph signal processing allows us to analyze our signal as evolving on this graph. Graph signal processing tells us that we can then understand brain activity as a superposition of building blocks, called harmonic modes, which are properties of the graph. Harmonic modes describe brain activity as hierarchical, multiscale, and multidimensional, all concepts that play important roles in neuroscience.

Methods development

Using EEG together with established ideas from connectomics and network neuroscience is still relatively new, and we lack some basic tools to move forward in this direction.