Pre-processing & analysis #

Perhaps the second major time investment in any ERP study is the preprocessing that must occur subsequent to data acquisition, before you can even begin to analyse or interpret your data. However, this is where degrees of experimenter freedom increase substantially, resulting in practices that are either intentionally or unintentionally less than ideal. In addition to this, the analyses you choose (and how you choose them) require considerable thought. Below, I have outlined just a few considerations.

The problem of multiple implicit comparisons #

One of the most widely accepted/practiced techniques in ERP data analysis (but importantly, one that is also widely accepted to be flawed) is the selection of time windows and electrodes in order to calculate mean/peak amplitude by looking at where an effect seems to happen. This might seem like an intuitive process, but the implications for the validity of any results that follow from it are considerable. For an excellent paper on See this article by Luck and Gaspelin (2017)

Preprocessing & publication #

Keil, A., Debener, S., Gratton, G., Junghöfer, M., Kappenman, E. S., Luck, S. J., … & Yee, C. M. (2014). Committee report: publication guidelines and recommendations for studies using electroencephalography and magnetoencephalography. Psychophysiology, 51(1), 1-21

Filtering (and what inappropriate filtering can do to your data) #

Tanner, D., Morgan‐Short, K., & Luck, S. J. (2015). How inappropriate high‐pass filters can produce artifactual effects and incorrect conclusions in ERP studies of language and cognition. Psychophysiology, 52(8), 997-1009.