ArticleScientific reports2021
Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Different Factors Determining Motor Execution and Motor Imagery Performance in a Serial Reaction Time Task with Intrinsic Variability.Brain sciences · 2026Article
- Extracting the fingerprints of sequences of random rhythmic auditory stimuli from electrophysiological data.PLoS computational biology · 2025Article
- Probabilistic prediction and context tree identification in the Goalkeeper game.Scientific reports · 2024Article
- Response times are affected by mispredictions in a stochastic game.Scientific reports · 2024Article
- The Neuroscience Experiments System (NES)-A Software Tool to Manage Experimental Data and Its Provenance.Frontiers in neuroinformatics · 2021Article
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Authors and funding
6 authors.
Funding
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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.
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