Retrieving a Context Tree from EEG Data
1
Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo 05508-090, Brazil
2
Centro de Matemática, Universidad de la República, Uruguay and Instituto Pasteur de Montevideo, Montevideo 11400, Uruguay
3
Instituto de Matemática, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
4
Instituto de Biofísica, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-902, Brazil
*
Author to whom correspondence should be addressed.
Mathematics 2019, 7(5), 427; https://doi.org/10.3390/math7050427
Received: 28 March 2019 / Revised: 30 April 2019 / Accepted: 5 May 2019 / Published: 14 May 2019
(This article belongs to the Special Issue Stochastic Processes in Neuronal Modeling)
It has been repeatedly conjectured that the brain retrieves statistical regularities from stimuli. Here, we present a new statistical approach allowing to address this conjecture. This approach is based on a new class of stochastic processes, namely, sequences of random objects driven by chains with memory of variable length.
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Keywords:
stochastic chains with memory of variable length; sequences of random objects driven by context tree models; stochastic modeling of EEG data
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MDPI and ACS Style
Duarte, A.; Fraiman, R.; Galves, A.; Ost, G.; Vargas, C.D. Retrieving a Context Tree from EEG Data. Mathematics 2019, 7, 427. https://doi.org/10.3390/math7050427
AMA Style
Duarte A, Fraiman R, Galves A, Ost G, Vargas CD. Retrieving a Context Tree from EEG Data. Mathematics. 2019; 7(5):427. https://doi.org/10.3390/math7050427
Chicago/Turabian StyleDuarte, Aline; Fraiman, Ricardo; Galves, Antonio; Ost, Guilherme; Vargas, Claudia D. 2019. "Retrieving a Context Tree from EEG Data" Mathematics 7, no. 5: 427. https://doi.org/10.3390/math7050427
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