Título:
Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data
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Autor:
Hernández, Noslen
Duarte, Aline
Ost, Guilherme
Fraiman, Ricardo
Galves, Antonio
Vargas, Claudia D.
Duarte, Aline
Ost, Guilherme
Fraiman, Ricardo
Galves, Antonio
Vargas, Claudia D.
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Tipo de documento:
Artículo
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Palabras clave:
EEG data
Probabilistic sequences
Auditory stimuli
Probabilistic sequences
Auditory stimuli
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Año de publicación:
2021
Contenido:
Resumen:
Using a new probabilistic approach we model the relationship between sequences of auditory stimuli generated by stochastic chains and the electroencephalographic (EEG) data acquired while 19 participants were exposed to those stimuli. The structure of the chains generating the stimuli are characterized by rooted and labeled trees whose leaves, henceforth called contexts, represent the sequences of past stimuli governing the choice of the next stimulus. A classical conjecture claims that the brain assigns probabilistic models to samples of stimuli. If this is true, then the context tree generating the sequence of stimuli should be encoded in the brain activity. Using an innovative statistical procedure we show that this context tree can effectively be extracted from the EEG data, thus giving support to the classical conjecture.
Descripción:
Existe información adicional en: http://doi.org/10.1038/s41598-021-83119-x
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Editorial:
Springer Nature
EN:
Scientific Reports, 2021, 11: 3520
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Citación:
Hernández, N, Duarte, A, Ost, G [y otros autores]. "Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data". Scientific Reports. [en línea] 2021, 11: 3520. 15 h. DOI: 10.1038/s41598-021-83119-x.
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ISSN:
2045-2322
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Licencia:
Licencia Creative Commons Atribución (CC - By 4.0)
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| 101038s4159802183119x.pdf | — | 4.78 MB | Adobe PDF |