Hidden context tree modeling of EEG data

Author: Antonio Galves.

In this talk a new class of stochastic processes is presented: the Hidden Context Tree Models (HCTM). This class gives a natural framework to mathematically address the neurobiological conjecture about the ability of the brain to identify the structure of a random source. Statistical model selection in a suitable subclass of HCTMs can provide experimental evidence supporting this conjecture. A case study with EEG data will be also presented. This is a joint work with A. Duarte, R. Fraiman, G. Ost and C. Vargas.

Presented at MathStatNeuro Workshop, Laboratoire J. A. Dieudonné, Nice, France, September 10, 2015.



The Research, Innovation and Dissemination Center for Neuromathematics is hosted by the University of São Paulo and funded by FAPESP (São Paulo Research Foundation).


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