Bootstrap analysis of the single subject with event related potentials

Neural correlates of cognitive states in event-related potentials (ERPs) serve as markers for related cerebral processes. Although these are usually evaluated in subject groups, the ability to evaluate such markers statistically in single subjects is essential for case studies in neuropsychology. Here we investigated the use of a simple test based on nonparametric bootstrap confidence intervals for this purpose, by evaluating three different ERP phenomena: the face-selectivity of the N170, error-related negativity, and the P3 component in a Posner cueing paradigm. In each case, we compare single-subject analysis with statistical significance determined using bootstrap to conventional group analysis using analysis of variance (ANOVA). We found that the proportion of subjects who show a significant effect at the individual level based on bootstrap varied, being greatest for the N170 and least for the P3. Furthermore, it correlated with significance at the group level. We conclude that the bootstrap methodology can be a viable option for interpreting single-case ERP amplitude effects in the right setting, probably with well-defined stereotyped peaks that show robust differences at the group level, which may be more characteristic of early sensory components than late cognitive effects.