[FieldTrip] baseline correction - Cluster Based Permutation Test

[Tara van Viegen]

Hi Eleonora,

A likely explanation of what you describe is that there are baseline
differences between your conditions of interest. You could check this by
running the statistics you used previously on the raw power in the time
window that you select as a baseline (e.g. cfg.latency = [-0.5 -0.1];
cfg.avgovertime = 'yes';). The difference you are observing between your
conditions are then explained by differences that already exist in the
baseline. If you apply a baseline correction you get rid of this effect.

Best,
Tara van Viegen
Senior-RA (aspiring post-doc)
Neuroscience of Attention & Perception Lab
Princeton University
tviegen at princeton.edu

On Mon, Oct 7, 2019 at 12:34 PM eleonora parrotta <eleonora_p at hotmail.it>
wrote:

> Dear Fieldtrippers,
>
> I am performing analysis of EEG data. I have two conditions of interest: A
> and B, and I have performed spectral decomposition with the wavelet method
> to obtain the power (frequencies from 1 to 50 Hz).
>
> I performed a cluster-based permutation test to assess whether there are
> significant power differences between the two conditions of interest in the
> time-interval from the onset of the stimulus to 1 sec after:
>
> %% clusterbased analysis
>
> cfg = [];
>
> cfg.latency = [0 1]; % Time of Interest
>
> cfg.frequency = [8 12]; % Frequency of interest
>
> cfg.channel =  {'PO3', 'P3', 'O1', 'P7','O2','P8','PO4','P4'};
>
> cfg.neighbours = neighbours;
>
> cfg.avgoverfreq = 'yes';
>
> cfg.avgovertime = 'no';
>
> cfg.avgoverchannel = 'no';
>
> cfg.method = 'montecarlo';
>
> cfg.statistic = 'ft_statfun_depsamplesT';
>
> subj = 18;
>
> design = zeros(2,2*subj);
>
> for i = 1:subj
>
>   design(1,i) = i;
>
> end
>
> for i = 1:subj
>
>   design(1,subj+i) = i;
>
> end
>
> design(2,1:subj)= 1;design(2,subj+1:2*subj) = 2;
>
> cfg.design   = design;
>
> cfg.uvar     = 1;
>
> cfg.ivar     = 2;
>
> cfg.correctm         = 'cluster';
>
> cfg.clusteralpha     = 0.05;
>
> cfg.clusterstatistic = 'maxsum';
>
> cfg.minnbchan        = 2;% specifies with which sensors other sensors can
> form clusters
>
> cfg.tail             = 0;
>
> cfg.clustertail      = 0;
>
> cfg.alpha            = 0.05;
>
> cfg.numrandomization = 1000;
>
> [alpha] = ft_freqstatistics(cfg, avg_pred, avg_ran);
>
>
>
> When I perform the cluster-based analysis on raw power I obtain more than
> one negative cluster, with highly significant differences between my two
> condition (p=0.01). The problem is that when I run the cluster-based
> analysis on baseline-corrected power the analysis is not even able to find
> any cluster of electrodes that behave differently in one condition compared
> to the other one (no matter which kind of baseline I applied, I tried with
> both ‘absolute’ and ‘relchange’ and even different time-window).
>
> I am aware of the potential loss of power that can occur when we use
> baseline-correction (http://datacolada.org/39)
>
> At the same time I am not sure how correct is to perform stats on
> non-baseline corrected power, as without applying this procedure drifts and
> offsets potentially present in the signal could affect the statistical
> test, executed on two non-normalized datasets.
>
> I was wondering whether I am not aware of potential ways to specify that a
> baseline-correction has been applied to the data, or if there is a correct
> way of doing it.
>
> So far I couldn’t find any reference that explains it clearly, but if anyone has an explanation I would really appreciate.
>
>
>
> Thanks in advance,
>
>
>
> Eleonora
>
>
>
> _______________________________________________
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> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> https://doi.org/10.1371/journal.pcbi.1002202
>
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