The use of ERP methodology involves numerous degrees of freedom. To ensure the reliability and replicability of ERP research output, it is therefore crucial that researchers avoid practises (all too common to the field) prone to result in erroneous effects, and ensure that their reporting is complete and replicable. To support researchers to do so, numerous efforts have been made to improve how people use ERP as a methodology, and ensure that reporting of data acquisition, pre-processing, analyses, and results are standardised. Such tools, frameworks, and guidance harbour the potential to substantially increase replicability and reliability in the field, and tackle the ongoing replication crisis.

These resources provide us with an invaluable opportunity to substantially improve standards in ERP research and reporting. As the field continues to expand, the implementation of these guidelines and recommendations in ERP study design, data collection, analysis, and reporting is crucial to ensure the reliability and validity of scientific developments. However, despite the longstanding availability of such resources, their use (and adherence to their guidance) is scarce (see, for example. common under-reporting of methodological detail; infrequent use of sample size calculations).

The literature cited within these pages serves as a repository for resources that can guide every stage of your ERP research through design, data acquisition, pre-processing, and reporting to ensure that the research you produce make a valuable contribution to the field.

NB. It goes without saying that the first resource for any ERP researcher in the making is An Introduction to the Event-Related Potential Technique by Steve Luck. If finances are of concern (which, of course, for most students it is) consider the first edition, which contains much of the useful content and can be sourced second-hand for quite a bit less.