Projects
We use a combination of data analysis, mathematical modeling, and empirical approaches to develop theories and methods for understanding the brain from a network perspective. Our research projects are supported by several national and international funding programs. Our current research is structured along two grand axes:
Network neuroscience
The brain can be modeled as a network of interconnected areas. We address both theoretical and applied questions to better understand the brain structure and function.
Multilayer networks
Brain areas exhibit connectivity across multiple levels and scales. How to analyze and model the resulting complex higher-order topology? [1,2]
Statistical models
Brain networks result from a generating process which is general unknown. How to identify the local connection mechanisms generating brain networks? [3,4]
Network controllability
By interacting with each other brain areas excert a potential controlling power. How to model and leverage this reciprocal influence in brain networks? [5,6]
Brain-computer interfaces
Brain-computer interfaces (BCIs) establish a direct link between the brain and the outworld. We develop new solutions to improve their usability and clinical impact.
Network-based features
Current BCIs neglect the interconnected nature of the brain. We introduce network-based metrics to better decode user's mental intentions. [7,8]
Adaptive classification
BCIs require functional brain reorganization over time. We use network modeling approaches to quantify BCI plasticity and inform adaptive algorithms. [9,10]
Multimodal BCIs
BCI performance critically depends on the efficacy of the experimental setup. We explore innovative solutions aimed to improve the overall user's experience. [11,12]
Key review publications
The complete list of publications can be found here.