Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data

Year: 2021

Type: article

Abstract: 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.

Source: Scientific Reports

DOI: 10.1038/s41598-021-83119-x

Authors: Noslen Hernández, Aline Duarte, Guilherme Ost, Ricardo Fraiman, Antonio Galves, Claudia D. Vargas

Institutions: Universidade de São Paulo, Universidade Federal do Rio de Janeiro, Universidad de la República de Uruguay, Instituto de Biofísica Carlos Chagas Filho

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $1,990

Funders: Fundação de Amparo à Pesquisa do Estado de São Paulo, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Financiadora de Estudos e Projetos, Universidade de São Paulo

OpenAlex ID: W3003575998