How inappropriate high-pass filters can produce artifactual effects and incorrect conclusions in ERP studies of language and cognition.

Although it is widely known that high-pass filters can reduce the amplitude of slow ERP components, these filters can also introduce artifactual peaks that lead to incorrect conclusions. To demonstrate this and provide evidence about optimal filter settings, we recorded ERPs in a typical language processing paradigm involving syntactic and semantic violations. Unfiltered results showed standard N400 and P600 effects in the semantic and syntactic violation conditions, respectively. However, high-pass filters with cutoffs at 0.3 Hz and above produced artifactual effects of opposite polarity before the true effect. That is, excessive high-pass filtering introduced a significant N400 effect preceding the P600 in the syntactic condition, and a significant P2 effect preceding the N400 in the semantic condition. Thus, inappropriate use of high-pass filters can lead to false conclusions about which components are influenced by a given manipulation. The present results also lead to practical recommendations for high-pass filter settings that maximize statistical power while minimizing filtering artifacts.