Fundamentals of Topographic Analyses of Event-Related Potentials

Electroencephalography (EEG) marked its centennial in 2024 and remains a major workhorse in clinical, basic, and applied research alike. This is partially attributable to EEG’s accessibility and cost-efficiency as well as the fact that EEG non-invasively measures the electric fields of the brain. Innovations in EEG over the past century have largely been either in terms of improving data acquisition or data analysis. On the one hand, the hardware for EEG recording allows for more electrodes from more efficient electronics and well as more user-friendly hardware. On the other hand, advancements in signal processing allow researchers to use EEG to provide both temporal and spatial information about brain (dys)function. However, that EEG is so widespread also makes the method susceptible to practices that may hinder scientific advancement by adding confusion rather than clarity in the acquisition, analysis, and interpretation of EEG data. This chapter offers readers an accessible overview of these considerations as well as a guide to these analyses that provide reference-independent measurements of response strength and response topography and therefore circumvent statistical and interpretational caveats of canonical ERP analysis methods. The analyses overviewed here can, in most instances, be extended to the analysis of spontaneous EEG, as well as spectrally-deconvolved signals both when recorded at the scalp and intracranially in humans and animal models alike. The versatility and accessibility of EEG, in combination with advances in signal processing, allow for this ‘old dog’ of human neuroscience to still deliver new tricks and innovations.