In this talk, our primary goal is to identify classes of models used by the brain to encode the statistical regularities of the environment. We seek to retrieve statistical regularities of the stimuli sequence from data recorded from the brain. Then, we propose a hierarchical clustering procedure, based on a Kolmogorov-Smirnov-type goodness-of-fit test, to clusters in the same group EEG dataset with the same law, and on different groups with different distributions. We test our method in artificial and real datasets exhibiting promising results.
By Risto Ilmoniemi
By William Lytton
By Claudia Vargas
By Daniel Fraiman
By Oswaldo Baffa Filho
By Leonardo Cohen
By Yves Frégnac
By Maria Elisa Pimentel Piemonte , Rafael Bassi Stern
By Fabrizia Mealli
By Sylvain Le Corff
By Ronnie Pavlov
By Tamara Kucherenko
