Using Coherence-based spectro-spatial filters for stimulus features prediction from electro-corticographic recordings.

ABSTRACT: The traditional approach in neuroscience relies on encoding models where brain responses are related to different stimuli in order to establish dependencies. In decoding tasks, on the contrary, brain responses are used to predict the stimuli, and traditionally, the signals are assumed stationary within trials, which is rarely the case for natural stimuli. We hypothesize that a decoding model assuming each experimental trial as a realization of a random process more likely reflects the statistical properties of the undergoing process compared to the assumption of stationarity. Here, we propose a Coherence-based spectro-spatial filter that allows for reconstructing stimulus features from brain signal's features. The proposed method extracts common patterns between features of the brain signa

SUBMITTER: Delgado Saa J 

PROVIDER: S-EPMC7203138 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature