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- W4256160930 abstract "In this report, I propose an analytical approach based on k means clustering to identify functionally relevant spectral microstates in EEG data. As a proof of principle, the analysis is applied to an EEG data set in which participants performed a continuous arithmetic task. In order to assess the functional relevance of the identified ‘spectral microstates’, their occurrence are compared to inter-individual differences in arithmetic task performance." @default.
- W4256160930 created "2022-05-12" @default.
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- W4256160930 date "2019-12-08" @default.
- W4256160930 modified "2023-10-16" @default.
- W4256160930 title "Capturing EEG Spectral Microstates Through K Means Clustering" @default.
- W4256160930 doi "https://doi.org/10.31219/osf.io/uqykr" @default.
- W4256160930 hasPublicationYear "2019" @default.
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