Neural Correlates of Processing Syntax in Music and ... - PubMan

Electroencephalography and Event-Related Potentials 90
Figure 7-2 Schematic overview of recording and processing an EEG. Data (right-top) are recorded from
several positions at the scalp (left-middle). Data are pre-processed (e.g., filtered, rejected).
Finally, trials of the experimental conditions were averaged, resulting in event-related potentials
(left-bottom). Different conditions are indicated by different colors of the ERPs and
their respective trigger marks in the EEG.
Filtering: The basic idea of filtering EEG data is to remove frequency components that
are regarded to represent noise. Filter may be either high-pass (removing low frequency
components; e.g., electrode drifts), low-pass (removing high frequency components;
e.g., muscle tension), or a combination of high- and low-pass filters (i.e., band-pass or
band-stop filter). Filter design involves finding a good compromise between reduction
of extraneous and the preservation of as much as possible from the fidelity of the brain
waves that should be observed.
Removing ICA components: Basically, an ICA separates EEG activity into a number of
distinct temporally maximally independent components (that may reflect either particular
brain processes or artefacts; Bell & Sejnowski, 1996; Makeig, Jung, Bell, Ghahremani,
& Sejnowski, 1997). Particular components that are regarded to reflect noise are
rejected. This decision may be based on the scalp distribution of the component, on its
frequency spectrum, or on the time course of the components activity (e.g., its coincidence
with an eye-blink artefact in the EEG data).
Rejecting artefact-loaden trials: Rejecting denotes the exclusion of trials on the basis of
particular, mostly statistical, criteria (e.g., if the amplitudes within that trial exceed a