EEG/ERP analysis

EEG/ERP data were analysis with a Linear Mixed-Effects model. As for the case of the data from the naming task, the fixed effect portion of the model included Stage and Training as predictors, while the Random Effect modelled between-subjects variability. The dependent variable was the difference between mismatch and match ERPs calculated in the time window from 300-500 msec post-stimulus onset from the Cz electrode. Data from one subject were excluded from the ERP analysis because of the large number of artefacts.
Results from the stepwise regression showed a main effect of Stage, \(\chi^2\)(2) = 13.96, p = .0027, while neither the Training strategy nor the interaction term were significant, \(\chi^2\)(1) = 0.19, p = .66;  \(\chi^2\)(1) = 0.24, p = .62, respectively. Post hoc comparisons showed a statistically significant increase in the amplitude of the N400 component from pre- to post-training, z = 3.53, p < .01 and from pre-training to follow-up, z = 3.168, p < .012. The increase in the amplitude of the ERP component (averaged across levels of the predictor Training strategy) was retained over the two-weeks follow-up, z = -.38, p = .92.