Probability waves: pattern-based p-value correction in mass univariate analysis between two event-related potential waves.

BackgroundMethods for p-value correction are criticized for either increasing Type II error or improperly reducing Type I error. This problem is worse when dealing with hundreds or thousands of paired comparisons between waves or images which are performed point-to-point. This text considers patterns in probability vectors resulting from multiple point-to-point comparisons between two ERP waves (mass univariate analysis) to correct p-values. These patterns (probability waves) mirror ERP waveshapes and might be indicators of consistency in statistical differences. New methodIn order to compute and analyze these patterns, we convoluted the decimal logarithm of the probability vector (p) using a Gaussian vector with size compatible to the ERP periods observed. For verify consistency of this method, we also calculated mean amplitudes of late ERPs from Pz (P300 wave) and O1 electrodes in two samples, respectively of typical and ADHD subjects. Resultsthe present method reduces the range of p-values that did not show covariance with neighbors (that is, that are likely random differences, type I errors), while preserving the amplitude of probability waves, in accordance to difference between respective mean amplitudes. Comparison with existing methodsthe positive-FDR resulted in a different profile of corrected p-values, which is not consistent with expected results or differences between mean amplitudes of the analyzed ERPs. Conclusionthe present new method seems to be biological and statistically more suitable to correct p-values in mass univariate analysis of ERP waves.