Actiview acquisition software

EEG and electromyographic (EMG) activity were recorded using active surface electrodes (BioSemi, The Netherlands) and ActiView acquisition software (version 6.05). EEG was measured using 64 pin electrodes plugged into a headcap (BioSemi) that ensured positioning in accordance with the 10/20 layout system. EMG was recorded from four pairs of electrodes placed on left lower leg muscles (interelectrode distance ~ 1.5 cm) after preparation of the skin with shaving, abrasion, and cleaning with alcohol. Pairs of EMG electrodes were positioned over the proximal (TA_prox) and distal (TA_dist) ends of the anterior tibial muscle (mean distance between electrode pairs ~ 12 cm) and over the center of the medial gastrocnemius (MG) and soleus (SOL) muscles. As per the BioSemi system design, signals were recorded in reference to a common mode sense active electrode, while a driven right leg electrode was used to cancel signals measured at the common mode sense electrode. Analog signals were sampled at 2048 Hz, and offset was contained to ±25 μV.

The experiment took place in a dark, sound-proof, electrically-shielded room. The participants sat comfortably on a chair facing the stimulus screen and were asked to avoid any movements or eye-blinks during the trials. Frequent breaks and continual monitoring of the participants appeared to successfully ensure their on-going comfort and continued attention. The continuous EEG signals were recorded using the 64-electrode ActiveTwo system (BioSemi, Amsterdam, Netherlands) with Actiview acquisition software (BioSemi, Netherlands). Impedance of each electrode was maintained below 5 kΩ for the duration of each experiment. The signal was digitized at 512 Hz with a pass band from 0.01 to 100 Hz. Horizontal and vertical electro-oculograms were recorded using separate electrodes placed above and below the right eye and at the outer canthi of both eyes. The precise stimulus markers were recorded by the Biosemi system.

The electroencephalography (EEG) data were collected at a sampling rate of 2048 Hz using the BioSemi ActiveTwo system and ActiView acquisition software (BioSemi, Netherlands) from 16 electrodes. In all, 7 external electrodes were used: 4 for monitoring horizontal and vertical eye movement, 2 for mastoid recordings and 1 for nose recording. Offline data analysis was carried out in MATLAB (The Math Works Inc., Natick, Massachusetts, USA) using the EEGLAB toolbox (Delorme and Makeig, 2004 (link)). The continuous EEG data were first resampled to 256 Hz and band-pass filtered at 0.5–30 Hz. The BioSemi enables referencing the data for online EEG display without actually referencing the data. Referencing is accomplished offline; in this study, the signals were referenced offline to the nose channel. To identify and remove eye artifacts, independent component analysis (ICA; Jung et al., 2000 (link)) was carried out. The EEG data were then segmented into epochs from −100 to 900 ms with a time window of 100 ms for the baseline correction. ERPs were time-locked to the word onset. Artifact rejection was set to remove activation exceeding ±100 μV at any channel. The grand average was computed per stimulus type for all participants, and deviant-minus-standard subtractions were calculated for the deviants.