[FieldTrip] Nonparametric statistical testing of phase coherence

Eric Maris e.maris at psych.ru.nl
Thu Apr 11 12:09:26 CEST 2013


If I were a reviewer, I would object against such a procedure (because you
are mixing up units-of-observation; see Maris, Psychophysiology, 2012).
But I know people have done in the early days of fMRI analysis
(concatenating the data of the multiple subjects; called a level-1
analysis in that community), but this has sparked a lot of criticisms.

 

Eric Maris

 

From: Ana Navarro Cebrian [mailto:sabato45 at hotmail.com] 
Sent: donderdag 11 april 2013 6:08
To: FieldTrip discussion list
Subject: Re: [FieldTrip] Nonparametric statistical testing of phase
coherence

 

Thank you, Eric. Would then make sense to add all the trials (from all
subjects) from condition1 in one set, and all the trials (from all
subjects) from condition2 in a second set, and run this Montecarlo
simulation (the same way I was talking about to compare) those two
conditions?

Thanks again,

Ana


 

 

 

  _____  

From: e.maris at psych.ru.nl
To: fieldtrip at science.ru.nl
Date: Wed, 10 Apr 2013 09:21:28 +0200
Subject: Re: [FieldTrip] Nonparametric statistical testing of phase
coherence

Hi Ana,

 

Yes, this is correct.

 

Eric Maris

 

From: Ana Navarro Cebrian [mailto:sabato45 at hotmail.com] 
Sent: dinsdag 9 april 2013 19:57
To: FieldTrip discussion list
Subject: Re: [FieldTrip] Nonparametric statistical testing of phase
coherence

 

Hi Maris,

thank you for your response.

I think my question wasn't clear. Let me rephrase it. I'd like to apply
the 

montecarlo approach that you explain in Maris et al., because I have

two conditions (errors vs correct responses) with a huge difference in the
number 

of trials. In this case, I understand that I have to apply the montercarlo
simulation

across trials to find out whether condition 1 is different from condition
2 independently 

of their different number of trials.

If that's correct, my question is, do I get a p-value from this procedure?


If so, after performing the same analysis for each subject independently, 

I'll end up with a p-value for each subject. Is that correct?

 

I'm sorry if I'm not understanding something basic.

I really appreciate your help.

Ana 

 


 

 

 

  _____  

From: e.maris at psych.ru.nl
To: fieldtrip at science.ru.nl
Date: Tue, 9 Apr 2013 12:09:03 +0200
Subject: Re: [FieldTrip] Nonparametric statistical testing of phase
coherence

Hi Ana,

 

To compare coherence between conditions across subjects (instead of
trials), you need a different statfun: depsamplesT (for a within-subjects
design; subjects have participated in all conditions) or indepsamplesT
(for a between-subjects design; subjects have participated in only one
condition). Typically, this type of test is performed using power as the
dependent variable, but exactly the same test is used for comparing
coherence in a multiple-subject study. However, you will have to specify
the cfg.parameter field when calling ft_freqstatistics such that it points
to the data field that contains your coherence data (importantly, for a
given reference channel).

 

Good luck,

 

Eric Maris 

 

From: Ana Navarro Cebrian [mailto:sabato45 at hotmail.com] 
Sent: vrijdag 5 april 2013 23:56
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] Nonparametric statistical testing of phase coherence

 


Hello everybody,

I'd like to use the test proposed in Maris et al., 2007 (that I believe is
implemented in statistics_montecarlo.m?). 

I'm calculating the difference in phase coherence between two conditions.
The problem is that one condition has much less trials than the other, so
I imagine the Montecarlo simulation would need to be across trials, in
which case, I'd end up with a p-value for each individual subject, right?
I'm not sure then how to apply this across subjects. The Maris et al.
paper is very clear, but it only explains single subject analysis. 

I hope that makes any sense. I appreciate any help.

Thanks,

Ana 

 


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