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bioRxiv · 10.1101/2023.06.05.543689

The effect of estimation time window length on overlap correction in EEG data

Skukies, R. S.·Ehinger, B.
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Abstract

Regression Event-Related-Potentials (ERPs) with overlap correction (also referred to, as linear deconvolution, or temporal response functions) are becoming more popular for the analysis of Electroencephalography (EEG) data. A common question for the analyst is, how to specify the length of the estimation windows. Long estimation windows might capture all relevant event-related activity, but might introduce artifacts due to overfit, short estimation windows might not overfit, but also might not capture all (overlapping) activity, and thereby introduce bias. Using a systematic simulation approach, we show that longer rather than shorter time windows should be preferred for typical EEG designs. We further provide an interactive app to visualize various design parameters: https://estimationwindow.ccn2023.s-ccs.de

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Skukies, R. S., Ehinger, B.. 2023-06-07. The effect of estimation time window length on overlap correction in EEG data. https://doi.org/10.1101/2023.06.05.543689

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