Protocol to decode representations from EEG data with intermixed signals using temporal signal decomposition and multivariate pattern-analysis

The electroencephalogram (EEG) is one of the most widely used techniques in cognitive neuroscience. We present a protocol showing how to combine a temporal signal decomposition approach (RIDE, Residue iteration decomposition) with multivariate pattern analysis (MVPA) to obtain insights into the temporal stability of representations coded in distinct informational fractions of the EEG signal. In this protocol, we describe pre-processing of human EEG data, followed by the set-up and use of MATLAB-based toolboxes for RIDE and MVPA analysis. For complete details on the use and execution of this protocol, please refer to Petruo et al. (2021).