We therefore used the following method to determine the coordinate for fixation. If, within one set of eight blocks with the same calibration, the difference between median eye position in the different blocks was < 1°, we used the median x-values and y-values Trichostatin A research buy across all blocks as the fixation point coordinates. Otherwise, the eye-tracking data were analysed without this correction. On this filtered data, we removed all trials in which the subjects’ eyes moved by more than 1.75° from the fixation point. Two participants were excluded

because of excessive eye movements. All EEG data analyses were performed in matlab with the fieldtrip toolbox (Oostenveld et al., 2011) as well as custom scripts. The EEG recording was high-pass-filtered with a low cut-off of 0.5 Hz, by the use of fourth-order Chebyshev filters with zero phase-shift. This filter has the advantage BMS 354825 of very high attenuation in the stop band with minimal attenuation in the pass-band (< 0.1 dB). After filtering, bad channels were determined from the statistics of neighboring channels, and interpolated by the use of linear, distance-weighted interpolation. The EEG data were

then referenced to the average. In addition to the deletion of trials on the basis of eye movements, there was also an EEG threshold of ±125 μV. If more than six channels or any of the occipital electrodes of interest exceeded this threshold, the trial was discarded. Otherwise, high-amplitude channels were interpolated by the use of linear, distance-weighted interpolation. Three participants were excluded because of large numbers of trials with EEG artefacts, bringing the total number of participants used in further analysis see more to 14. After removal of artefact trials, an average of 117 trials per condition and participant

remained. Temporal second-order kernels (e.g. Sutter, 2000) representing evoked cortical responses were extracted for each electrode and each of the four stimulus locations, by reverse-correlating the EEG response with the known sequence of pattern reversals. The second-order response takes into account the history of visual stimulation, i.e. whether the current pattern is the same as the one presented one monitor refresh before. Given the findings of previous studies on spatial attention (e.g. Lalor et al., 2007; Kelly et al., 2008; Frey et al., 2010), we expect attentional modulation of the evoked responses during early cortical processing, as represented by responses in the C1 and P1 time-frame. As evoked response kernels represent activity in the early retinotopic cortex, which is very variable across participants (Ales et al., 2010a), the topographical distribution of peak activity was inconsistent across participants. For each stimulus location, we therefore selected two electrodes for each participant by determining mean activity across all four experimental conditions and selecting the two electrodes on the peak of the C1 and P1 topography, respectively.