Total variation for the analysis of event-related potentials.

Background: Event-related potential waveforms are often analysed in the time-domain for changes of striking morphological features, like amplitudes or latencies of extrema, at the expense of missing less obvious changes in overall morphology.

New Method: The measure of total variation can capture a variety of changes in curve morphology. We show analytical examples, and the application to two sets of EEG data (n=41, n=19) difficult to analyse with more traditional methods.

Results: Total variation can be used to identify the effects of experimental manipulations on event-related potential waveforms, and can additionally be used to identify the respective time windows by means of hierarchical subdivision of longer signals.

Comparison With Existing Methods: The ANOVA of total variation provided additional insights into effects already hinted at by the ANOVA of global field power in the first experiment, and identified a number of interactions missed by an ANOVA of amplitude as well as a topographic ANOVA in the second one.

Conclusions: The analysis of total variation can be an interesting complement to more traditional analyses, especially when changes are hard to assess with traditional methods, e.g. in the absence of pronounced extrema, or the presence of noise or large interindividual variations of latency.