[FieldTrip] Smoothing before permutation test

[Ramirez Pasos,]

Dear Fieldtrippers,

I have a set of subcortical LFP signals from 8 patients, which I have analyzed with fieldtrip in order to obtain event-related time-frequency plots. Unfortunately, I have only three repetitions for each of my 4 conditions, so there's a lot of noise in the subject-averages of time-frequency data. I'm interested in testing baseline vs activation for each condition as well as comparisons between my 4 conditions (A1A2, A1B1, B1B2, A2B2).

Could anyone tell me their take on smoothing before permuting? Is that a valid procedure with such a small sample size? I've searched for literature discussing smoothing before permuting (mostly the Holmes papers), where much talk of smoothing refers to concepts such as "locally pooled variance" and "pseudo t-statistics," but I don't know how this fits with fieldtrip's cluster statistics functions.

Any thoughts would be greatly appreciated!

U. Ramirez
University of Wuerzburg