Bayesian analysis
We supplemented frequentist analysis with Bayesian analysis, which can confirm the probably of the null hypothesis being true given the data (PH0|D) (Dienes, 2014). This allows us to statistically confirm that ERP amplitudes are similar in two conditions. We used conventional Bayes factor parameters of 1/3 and 3. For Bayesian t tests, we used the default Cauchy prior (with r-scale of 0.707). For Bayesian ANOVA, we report BF include. This involves parameter estimation and is not completely consistent between re-runs, so we avoid overinterpretation of borderline values. Bayesian analyses were run in open source JASP software (JASP Team, 2022).