A New Method for Generating Realistic Null Data Exploiting Underlying Graph Structure with Application to EEG
E. Pirondini, A. Vybornova, M. Coscia, and D. Van De Ville
Technological and computational advances are making available large amounts of high-dimensional and rich-structured biomedical data, including brain images and signals. Acknowledging the network structure in our analyses opens a multitude of avenues in investigating “systems level” properties. For instance, computational neuroscience has boosted the interest in modeling and analyzing large datasets using concepts normally applied in networks and graph theories.