Bootstrap significance of low SNR evoked response.
In order to obtain adequate signal to noise ratio (SNR), stimulus-evoked brain signals are averaged over a large number of trials. However, in certain applications, e.g. fetal magnetoencephalography (MEG), this approach fails due to underlying conditions (inherently small signals, non-stationary/poorly characterized signals, or limited number of trials). The resulting low SNR makes it difficult to reliably identify a response by visual examination of the averaged time course, even after pre-processing to attenuate interference. The purpose of this work was to devise an intuitive statistical significance test for low SNR situations, based on non-parametric bootstrap resampling. We compared a two-parameter measure of p-value and statistical power with a bootstrap equal means test and a traditional rank test using fetal MEG data collected with a light flash stimulus. We found that the two-parameter measure generally agreed with established measures, while p-value alone was overly optimistic. In an extension of our approach, we compared methods to estimate the background noise. A method based on surrogate averages resulted in the most robust estimate. In summary we have developed a flexible and intuitively satisfying bootstrap-based significance measure incorporating appropriate noise estimation.
Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. mccubbin@telus.net <mccubbin@telus.net>
J
J
McCubbin
T
T
Yee
J
J
Vrba
S E
SE
Robinson
P
P
Murphy
H
H
Eswaran
H
H
Preissl
D001921:Brain / Q000196:embryology* / Q000502:physiology*; D001931:Brain Mapping; D003198:Computer Simulation; D005072:Evoked Potentials, Auditory / Q000502:physiology*; D005333:Fetus; D006801:Humans; D015225:Magnetoencephalography; D008954:Models, Biological; D009010:Monte Carlo Method; D009622:Noise; D013997:Time Factors