[FieldTrip] time-frequeny analysis task vs resting

Lorena Santamaria Covarrubias lorenalsc at hotmail.com
Mon Dec 12 06:47:57 CET 2016

Hi Matt,

Thank you for you reply Matt.

I am working with ECoG. The tasks that participants have to perform is movements of hand and tongue, indicated by a visual stimuli.

Five repetitions each motor task followed by a fixation cross on the screen and then the next motor task, in a random order.

Resting state were recorded prior to the motor tasks during 5 minutes were participants has to look to a fixation cross and not perform any movement.

If you need any other information please let me know.

Thank you.

De: fieldtrip-bounces at science.ru.nl <fieldtrip-bounces at science.ru.nl> en nombre de Matt Gerhold <matt.gerhold at gmail.com>
Enviado: lunes, 12 de diciembre de 2016 5:26
Para: FieldTrip discussion list
Asunto: Re: [FieldTrip] time-frequeny analysis task vs resting

What do your tasks entail? Can you provide more specific details regarding your experimental design? That will help clarify what the best analytical work-flow will be in your case.


On Mon, Dec 12, 2016 at 3:37 AM, Lorena Santamaria Covarrubias <lorenalsc at hotmail.com<mailto:lorenalsc at hotmail.com>> wrote:

Good morning,

I am new in this topic and I have a basic question about baseline correction (ft_freqbaseline) when I am trying to study the time frequency analysis of task versus resting period.

I have two data-sets, one with the tasks information, 64 channels x 1s epoch x 100 trials (50 trials task1 and 50 trials task2)  and then 5 minutes of continuous recording for resting state.

I obtained the power spectrum for both tasks:

cfg              = [];
cfg.output = 'pow';
cfg.method  = 'tfr';
cfg.foi          =  8:1:130;
cfg.toi          =  0.3:0.01:1.3;
cfg.keeptrials   = 'no';

cfg.trials = find(epoch_data.trialinfo == 1);
Task1Spec= ft_freqanalysis(cfg,epoch_data);

cfg.trials = find(epoch_data.trialinfo == 2);
Task2Spec = ft_freqanalysis(cfg,epoch_data);

But now I don't know how to do the baseline correction with the 5 minutes continuous data to can compare the power spectrum of both tasks in relation to the resting state.

Maybe I missing something pretty basic, apologies in advance for it if this is the case.

Any suggestions will be appreciated.


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