[FieldTrip] Questions about time frequency analysis of EEG data

[Pelt, S. van (Stan)]

Dear Arti,

My guess is that is has to do with plotting relative change instead of e.g. absolute change. In the individual conditions, you plot relative change to their own baselines, which is in the order of 0.2 or so.
Now when you subtract the 2 conditions, the difference in both baseline and activation epoch is probably small. So when you plot the tfr of this, normalized by the baseline wpoch values of this difference signal, it might blow up the relative change values. You might want to plot just the absolute values of the difference TFR, since it is the difference in the activation window that is most relevant to you (assuming that baseline values are not different between the conditions. Or you could contrast just the activation epochs (e.g., using the tfr of cond1 as ‘baseline’ for cond2), and plot relative change of that.

I’ll illustrate it with some example values to show what I think goes ‘wrong’:

Cond. 1: baseline: 4; activation 6; -> rel.change 0.5 (50% increase)
Cond. 2: baseline 3.9; acitivation 6.3; -> rel change 0.6 (60% increase)
Difference: baseline 0.1; activation 0.3 -> rel change 2.0 (200% increase)

Best,
Stan

--
Stan van Pelt, PhD
Donders Institute for Brain, Cognition and Behaviour
Radboud University
Montessorilaan 3, B.01.34
6525 HR Nijmegen, the Netherlands
tel: +31 24 3616288

From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Arti Abhishek
Sent: woensdag 16 november 2016 5:09
To: FieldTrip discussion list <fieldtrip at science.ru.nl>
Subject: [FieldTrip] Questions about time frequency analysis of EEG data

Dear fieldtrip community,
I am running time frequency analysis on my EEG data and when I subtract the response between conditions, the difference condition has much higher amplitude. Could someone suggest what is wrong here?

Please find the image here:
https://www.dropbox.com/s/kh5uzz8000fmh1b/tfr.pdf?dl=0
and here is my script

cfg                      = [];
cfg.trials              = find(s01_ica_clean_artrel_reref.trialinfo==102);
cfg.channel          = 'EEG';
cfg.method           = 'wavelet';
cfg.width              = 7;
cfg.output             = 'pow';
cfg.foi                  = 2:2:40;
cfg.toi                  = -0.4:0.02:0.5;
s01_cond1           = ft_freqanalysis(cfg, s01_cond1_preprocess);
% difference
cfg=[];
cfg.parameter='powspctrm';
cfg.operation ='x1-x2';
s01_difference     =ft_math(cfg, s01_cond1, s01_cond2);
% plot
cfg                     = [];
cfg.baseline=[-0.4 -0.1];
cfg.zlim=[-0.5 0.5];
cfg.xlim=[-0.4 0.5];
cfg.baselinetype = 'relchange';
cfg.layout              = lay;
cfg.interactive         = 'yes';
cfg.channel={'FZ'};
subplot (1,3,1)
ft_singleplotTFR(cfg, s01_cond1);
title('deviant');
subplot (1,3,2);
ft_singleplotTFR(cfg, s01_cond2);
title('standard');
subplot (1,3,3)
ft_singleplotTFR(cfg, s01_difference);
title('difference');
Thanks,
Arti
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