1.4. EEG acquisition and ERP analysis

VI Vasileios Ioakeimidis
NK Nareg Khachatoorian
CH Corinna Haenschel
TP Thomas A. Papathomas
AF Attila Farkas
MK Marinos Kyriakopoulos
DD Danai Dima
request Request a Protocol
ask Ask a question
Favorite

The EEG signal was recorded using a 64-channel, BrainVision BrainAmp series amplifier (Brain Products, Herrsching, Germany) with a 1000 Hz sampling rate. The data were recorded with respect to FCz electrode reference. Ocular activity was recorded with an electrode placed underneath the left eye. Pre-processing was conducted in BrainVision Analyser (Brain Products, Herrsching, Germany) and the statistical analysis of the ERP was conducted in the Statistical Package for the Social Sciences software (SPSS 23, Armonk, NY: IBM Corp).

Pre-processing steps are described in their order of application. First, all EEG channels were individually inspected for high-frequency noise artefacts and slow drift. Those which were noisy throughout the whole EEG session were topographically interpolated by spherical splines. Subsequently, EEG data were down-sampled to 250 Hz and a high-pass filtered with a cut-off frequency of 0.5 Hz was applied. An automatic ocular correction was performed with the independent component analysis in BrainVision Analyser. Following re-referencing to TP9 and TP10 electrodes, data were segmented from 200 ms prior to 1000 ms after stimulus presentation for each condition. A low-pass filter of 30 Hz was applied followed by automatic artefact rejection which excluded segments with a slope of 100 µV/ms, min–max difference of 200 µV in a 200 ms interval and low activity of 0.5 μV in a 100 ms interval. Baseline correction was applied using the 200 ms interval preceding the stimulus and averaging was performed across each condition (convex, flat, concave). Averaging included all trials per condition (≈48), as opposed to only focussing on accurate-only responses, since concave faces were almost impossible to identify correctly (Table 2). For illustration purposes, a high cut-off filter of 20 Hz was applied to the grand average ERPs in Figure 1 and and22.

Grand average ERP waveforms for 3D normal faces, 3D inverted faces and flat faces in the whole sample (N = 20) in the 20 ROI electrodes.

Grand average ERP difference waves for 3D normal faces minus flat faces and 3D inverted faces minus flat faces in the whole sample (N = 20) in the 20 ROI electrodes.

Do you have any questions about this protocol?

Post your question to gather feedback from the community. We will also invite the authors of this article to respond.

post Post a Question
0 Q&A