To avoid any a priori bias with respect to choosing time windows and localization for ERP analyses, which allows for vast number of comparisons, a multivariate statistical tool called partial least squares (PLS) was used (McIntosh et al., 1996; Lobaugh et al., 2001; Krishnan et al., 2011). All ERP data is submitted to PLS by importing microvolts for every ms from stimulus presentation to 450 ms for each electrode. This is done for all participants and conditions. Singular value decomposition (SVD) identifies a set of latent variables (LVs), that correspond to the strongest ERP patterns in the data based on our experimental contrast/conditions (match vs. mismatch). An LV explains how much of the covariance was explained by our experimental contrast. To visualize the LVs, the salience is computed and represented as design scores and salience maps. Design scores code the effects of the LV between −1 and 1 (see top part of Figure 2) and salience plots show where this effect is present spatiotemporally (bottom part od Figure 2). In the salience maps, the dots show for which electrodes and temporal windows the LV is explaining the covariance. Thus, the relation between the experimental design contrasts (represented by the LV) and the spatiotemporal pattern of ERP amplitude changes is represented by the electrode saliences in Figure 2. The estimate of obtaining a singular value by chance (similar to a p-value) was computed by 1,000 permutations. The reliability of electrode saliences at each time point was assessed by 200 bootstrap re-samplings, which applies random sampling with replacement. For examples of how PLS can be applied to EEG data, see Lobaugh et al., 2001; Hay et al., 2002; Düzel et al., 2003; Itier et al., 2004; Grundy and Shedden, 2014 and for an example for speech production ERP data see, Christoffels et al. (2016). For more detailed explanation of applications and formulas see McIntosh and Lobaugh (2004). In short, PLS analyses allowed us to narrow the time windows and locations of experimental effects in order to perform conventional ERP statistics.