Context tree selection for functional data

2016/02/01 by Aline Duarte, Ricardo Fraiman, Duarte, A. +7 · 2 citations
Computer Science · #Data Management and Algorithms #Data Mining Algorithms and Applications #FOS: Biological sciences #Neurons and Cognition (q-bio.NC) #Time Series Analysis and Forecasting

paper · pdf · doi:10.48550/arxiv.1602.00579

openalex publication_date 2016/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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 driven by chains with memory of variable length. It leads to a new experimental protocol in which sequences of auditory stimuli generated by a stochastic chain are presented to volunteers while electroencephalographic (EEG) data is recorded from their scalp. A new statistical model selection procedure for functional data is introduced and proved to be consistent. Applied to samples of EEG data collected using our experimental protocol it produces results supporting the conjecture that the brain effectively identifies the structure of the chain generating the sequence of stimuli.

Citations

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