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Bootstrap analysis of the single subject with event related potentials
Ipek Oruç1, Olav Krigolson, Kirsten Dalrymple
1Department of Ophthalmology and Visual Science, University of British Columbia, Vancouver, BC, Canada. ipor@mail.ubc.ca
Cognitive Neuropsychology
|February 2, 2012
Summary
Statistical analysis of event-related potentials (ERPs) in single subjects is crucial for neuropsychology. Nonparametric bootstrap confidence intervals offer a viable method for interpreting individual ERP amplitude effects, particularly for early sensory components.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Psychophysiology
Background:
- Event-related potentials (ERPs) are neural markers of cognitive states.
- Group-level analysis is standard, but single-subject evaluation is vital for neuropsychological case studies.
Purpose of the Study:
- To investigate the utility of nonparametric bootstrap confidence intervals for statistically evaluating ERP markers in single subjects.
- To compare bootstrap-based single-subject analysis with conventional group-level ANOVA.
Main Methods:
- Nonparametric bootstrap confidence intervals were applied to three ERP phenomena: N170 face-selectivity, error-related negativity, and P3 in a Posner cueing paradigm.
- Single-subject significance was determined using bootstrap and compared to group-level ANOVA results.
Main Results:
- The proportion of subjects showing significant individual effects varied across ERP components, highest for N170 and lowest for P3.
- Individual bootstrap significance correlated with group-level significance.
- Bootstrap methodology showed viability for single-case ERP amplitude effects.
Conclusions:
- Bootstrap confidence intervals are a potentially viable method for interpreting single-case ERP amplitude effects.
- This method is most suitable for well-defined, stereotyped peaks with robust group-level differences, characteristic of early sensory components.
