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)
Abstract
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. View Full-TextKeywords:
stochastic chains with memory of variable length; sequences of random objects driven by context tree models; stochastic modeling of EEG data
▼
Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Share & Cite This Article
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.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
Related Articles
Article Metrics
Comments
[Return to top]
Mathematics
EISSN 2227-7390
Published by MDPI AG, Basel, Switzerland
RSS
E-Mail Table of Contents Alert