Protocol to decode representations from EEG data with intermixed signals using temporal signal decomposition and multivariate pattern-analysis
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
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).
Details
Original language | English |
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Article number | 101399 |
Journal | STAR Protocols |
Volume | 3 |
Issue number | 2 |
Publication status | Published - 17 Jun 2022 |
Peer-reviewed | Yes |
External IDs
PubMed | 35677605 |
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ORCID | /0000-0002-2989-9561/work/160952439 |
ORCID | /0000-0002-9069-7803/work/160953290 |
Keywords
ASJC Scopus subject areas
Keywords
- Behavior, Bioinformatics, Cognitive Neuroscience, Neuroscience