[Eeglablist] FFT vs. PSD

Sebastian Grissmann sebastian.grissmann at lead.uni-tuebingen.de
Fri Oct 24 03:23:41 PDT 2014


Dear Arno,

I just realized that I was getting the same results ('logtrials' 'on'  
or 'off') when I was also saving the single-trial measures for  
single-trials statistics.

Could this be a bug?

Since I was always saving the single-trial measures, I´m now wondering  
if I can assume that I already got the log data (even without  
'logtrials' 'on')?... Or should I rather recompute my results?

Best,
Sebastian

Quoting Sebastian Grissmann <sebastian.grissmann at lead.uni-tuebingen.de>:

> Dear Arno,
>
> No, I was using 'specmode', 'fft', 'nfft', 1024 (to get a finer  
> grained picture) 'logtrials', 'off' (the default)
>
> Thanks for the info! I was assuming (based on the plots) that the  
> log is always computed.
>
> Best,
> Sebastian
>
> Quoting Arnaud Delorme <arno at ucsd.edu>:
>
>> Dear Sebastian,
>>
>> Did you try 'specmode', 'fft', 'logtrials', 'on'?
>> In one case (logtrials off), the function computes the power for  
>> each trials, average power across trials, then compute the log for  
>> display.
>> In the second case (logtrials on), the function computes the log  
>> power for each trial then averages these trials.
>> So it is a matter of when you take the log.
>>
>> It is a matter of taste. Log transformation tend to reduce the  
>> noise, so maybe the second option is better.
>>
>> Arno
>>
>> On Oct 2, 2014, at 10:44 AM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu> wrote:
>>
>>> Dear Sebastian,
>>>
>>> It seems you are asking 'which one is correct' or 'what the  
>>> correct method', but there is no such a thing as 'the only  
>>> solution' here. If you change the computational method, the result  
>>> also changes. As long as your result can be replicated by other  
>>> researchers by using the methods and parameters you describe in  
>>> the paper, and also as long as your reviewer says no to your  
>>> methods and parameters (or don't say anything about them), you are  
>>> fine. You can, and should, choose your methods and parameters and  
>>> you owe full responsibility.
>>>
>>> To conclude, you can choose whichever methods/results you like.  
>>> Just be confident; instead of saying 'which one should I use',  
>>> which is so nice of you, but once you learn both are valid you  
>>> should say 'what's wrong with using this'. I know how you feel  
>>> since my degree is psychology too.
>>>
>>> Makoto
>>>
>>> On Thu, Oct 2, 2014 at 12:37 AM, Sebastian Grissmann  
>>> <sebastian.grissmann at lead.uni-tuebingen.de> wrote:
>>> Hi there,
>>>
>>> I´m a PhD student (who studied Psychology) and currently trying to  
>>> analyze my first EEG dataset. I first started to compute my  
>>> channel spectra ( pop_precomp() ) via a FFT (using the default  
>>> spectopo parameters: ‘specmode’, ‘fft’, ‘logtrials’, ‘off’), but  
>>> when I was later looking at specfreqs (returned from std_specplot)  
>>> I found that my frequency bins were quite broad (>1Hz). Since I  
>>> need a higher frequency resolution for my analysis I tried PSD  
>>> instead of FFT to compute my spectra (spectopo parameters:  
>>> ‘specmode’, ‘psd’, ‘logtrials’, ‘off’). Now I had a very good  
>>> spectral resolution, BUT the spectra looked quite different. For  
>>> example, the alpha peaks were gone (or strongly diminished) in the  
>>> PSD spectra and the statistics also returned very different  
>>> results. I later found out that I can also increase the resolution  
>>> of the FFT via zero-padding (spectopo parameters: ‘specmode’,  
>>> ‘fft’, ‘nfft’, 1024, ‘logtrials’, ‘off’), but the spectra still  
>>> look quite different.
>>>
>>> Here is the link to some figures. The p-value for the statistics  
>>> was always 0.05.
>>>
>>> https://www.dropbox.com/sh/8isx5pwms6ifxuj/AADJO6bmqG0kVPlvTeWCbzALa?dl=0
>>>
>>> I´m using EEGLAB v13.2.1; Sample rate = 250Hz; epoch length =  
>>> 700ms; trials = 59-306; Bandpassfilter = 1-30Hz
>>>
>>> Can anyone help me?… PLEASE…
>>>
>>> Best,
>>> Sebastian
>>>
>>>
>>> Sebastian Grissmann (Mag. rer. nat)
>>> Neuroengineer / PhD student
>>>
>>> LEAD Graduate School
>>> University of Tübingen
>>> Europastrasse 6
>>> 72072 Tübingen
>>> Germany
>>> Phone  +49 7071 29-73604
>>> _______________________________________________
>>> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
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>>>
>>>
>>>
>>> --
>>> Makoto Miyakoshi
>>> Swartz Center for Computational Neuroscience
>>> Institute for Neural Computation, University of California San Diego
>>> _______________________________________________
>>> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
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>>
>>
>
>
>
> Sebastian Grissmann (Mag. rer. nat)
> Neuroengineer / PhD student
>
> LEAD Graduate School
> University of Tübingen
> Europastrasse 6
> 72072 Tübingen
> Germany
> Phone  +49 7071 29-73604
> _______________________________________________
> Eeglablist page: http://sccn.ucsd.edu/eeglab/eeglabmail.html
> To unsubscribe, send an empty email to eeglablist-unsubscribe at sccn.ucsd.edu
> For digest mode, send an email with the subject "set digest mime" to  
> eeglablist-request at sccn.ucsd.edu



Sebastian Grissmann (Mag. rer. nat)
Neuroengineer / PhD student

LEAD Graduate School
University of Tübingen
Europastrasse 6
72072 Tübingen
Germany
Phone  +49 7071 29-73604


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