ERP_REJECT performs rejection of outlier trials from ERP studies.
Outlying trials are determined as follows (Citi et al, 2010):
for the set of trials (MxN matrix, M trials of N samples each) the first quartile, q1(j), and third quartile, q3(j), at each sample, j, are found. Then an acceptance "strip" is defined as the time-varying interval [q1(j)−G*D(j), q3(j)+G*D(j)] where D(j)=q3(j)−q1(j). Responses falling outside the acceptance strip for more than a fraction Q of the trial length are rejected. The inputs 'G' and 'Q' default to 1.5 and 0.1, respectively, if not given.
If 'baseline' is not empty, the trials are baseline-corrected before the described procedure is applied. If 'baseline' is a scalar integer, for each trial the value at sample 'baseline' is subtracted from the whole trial; if it is a two-element vector, the average of the samples between baseline(1) and baseline(2) is used instead.
This procedure has been used and described in:
L. Citi, R. Poli, and C. Cinel, "Documenting, modelling and exploiting P300 amplitude changes due to variable target delays in Donchin's speller," Journal of Neural Engineering, vol. 7, p. 056006, Oct. 2010.
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