[FieldTrip] Smoothing before permutation test

David Groppe david.m.groppe at gmail.com
Wed Nov 2 18:33:01 CET 2016

Smoothing a time-frequency matrix is just as valid.
I would apply the smoothing to whatever it is you are plugging into the
permutation test as an independent observation (in your case it sounds like
trial averages).

On Wed, Nov 2, 2016 at 1:02 PM, Ramirez Pasos, <Ramirez_U at ukw.de> wrote:

> Thank you David for your response! Just to be clear: by "smoothing" I'm
> not referring to the smoothing performed when using the
> ft_frequencyanalysis multitaper method, but some kind of spatial smoothing
> on the time-frequency matrix obtained via ft_frequencyanalysis - so that
> according to your suggestion, I would smooth each trial, then average
> trials for each subject/condition, and finally use these for statistical
> evaluation?  Is there a reason why smoothing each trial might be preferable
> to smoothing each subject's trial average?
> Thank you so much in advance,
> Uri
> ________________________________
> Von: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]"
> im Auftrag von "David Groppe [david.m.groppe at gmail.com]
> Gesendet: Mittwoch, 2. November 2016 14:43
> An: FieldTrip discussion list
> Betreff: Re: [FieldTrip] Smoothing before permutation test
> Since permutation tests exploit correlations between variables to increase
> sensitivity, smoothing each trial will increase your sensitivity.
>     cheers,
>         -David
> On Wed, Nov 2, 2016 at 6:41 AM, Ramirez Pasos, <Ramirez_U at ukw.de<mailto:
> Ramirez_U at ukw.de>> wrote:
> 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
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