[Eeglablist] Comparison STUDY ERSPDATA and ERSPDATA from script

[Makoto Miyakoshi]

Dear Simon,

> the values I get are completely different from when I use the GUI.

> if I want to run a script to get the same results as the ones obtained
with the GUI

But GUI operation does not return numerical data, right? It just shows a
color plot. Judging from this, the difference you found was in
time-frequency plot with unit? Sorry I still don't understand the
differences you are talking about.

The eegh() history can replicate the plot GUI operation makes, right? If it
doese not work, let me know.

Makoto



On Mon, Sep 12, 2016 at 12:28 PM, Simon Recherche <
srigoulotresearch at gmail.com> wrote:

> They differ in everything, they are not similar or there is no obvious
> connection between them.
>
> Maybe I was not clear:
>
> When I use the GUI and compute ersp measures with default parameters, I
> get ERSP values that I can retrieve with commandlines such as  [STUDY
> erspdata ersptimes erspfreqs pgroup pcond pinter] = std_erspplot(STUDY,
> ALLEEG,...)
>
> When I run a script with  pop_newtimef  function (as written in the
> previous email) and same parameters, the values I get are completely
> different from when I use the GUI.
>
>
> My question could be: if I want to run a script to get the same results as
> the ones obtained with the GUI, which function and parameters should I use
> ? I thought it was pop_newtimefunction and the aforementioned parameters
> but it does not seem to be the case.
>
> Thanks for the help,
>
> Simon
>
> On 9 September 2016 at 17:43, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> wrote:
>
>> Dear Simon,
>>
>> Why don't you tell me more about how the results differ? I appreciate
>> your patience.
>>
>> Makoto
>>
>> On Thu, Sep 1, 2016 at 11:07 AM, Simon Recherche <
>> srigoulotresearch at gmail.com> wrote:
>>
>>> Hi all,
>>>
>>> I am trying to compare different methods to get ERSP data from EEGLab.
>>>
>>>
>>> When pre-computing the channel measures for ERSP, I noticed that default
>>> parameters are: 'cycles', [3 0.8], 'nfreqs', 100, 'ntimesout', 200
>>>
>>> I tried to retrieve the same results by adapting Arnaud's script on the
>>> tutorial , for one subject and one electrode so it goes faster (see below).
>>>
>>>
>>> clear all
>>>
>>> clc
>>>
>>>
>>>
>>> subject_list = { 'CA20SD'};
>>>
>>>
>>>
>>> nsubj = length(subject_list); % number of subjects
>>>
>>>
>>>
>>> home_path  = 'D:\EEG_FGX_EEGLab_3\10.ChannelsInterpolated\';
>>>
>>>
>>>
>>>         allersp = zeros([100 200 1 nsubj]);
>>>
>>>         allitc = zeros([ 100 200 1 nsubj]);
>>>
>>>         allpowbase = zeros([ 1 100 1 nsubj]);
>>>
>>>         alltimes = zeros([ 1 200 1 nsubj]);
>>>
>>>         allfreqs = zeros([ 1 100 1 nsubj]);
>>>
>>>
>>>
>>> for subj=1:nsubj
>>>
>>>
>>>
>>>   % Load dataset
>>>
>>>         fprintf('\n\n\n**** %subj: Loading dataset ****\n\n\n',
>>> subject_list{subj});
>>>
>>>         EEG = pop_loadset('filename', [subject_list{subj} '_epochs.set'],
>>> 'filepath', home_path);
>>>
>>>
>>>
>>> % Compute a time-frequency decomposition for every electrode
>>>
>>> for elec = 77
>>>
>>> [ersp,itc,powbase,times,freqs,erspboot,itcboot] = pop_newtimef(EEG, 1,
>>> elec, [EEG.xmin EEG.xmax]*1000, 'cycles', [3 0.8], 'nfreqs', 100,
>>> 'ntimesout', 200, 'plotersp','off', 'plotitc','off');
>>>
>>>
>>>     allersp (:,:,elec,subj) = ersp;
>>>
>>>     allitc (:,:,elec,subj) = itc;
>>>
>>>     allpowbase (:,:,elec,subj) = powbase;
>>>
>>>     alltimes (:,:,elec,subj) = times;
>>>
>>>     allfreqs (:,:,elec,subj) = freqs;
>>>
>>> end;
>>>
>>> end;
>>>
>>>
>>>
>>>
>>>
>>> When I compare the matrix A = ersp(:,:,1,1) with the figure I get with
>>> the STUDY GUI (by selecting the proper channel and subjects), I dont have
>>> the same results.
>>>
>>>
>>> I tried to look at the std_ersp() function to see if other inputs could
>>> help to make calculations similar but I did not find anything.
>>>
>>>
>>>
>>> Thanks again,
>>>
>>>
>>> Simon
>>>
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>>
>>
>>
>> --
>> Makoto Miyakoshi
>> Swartz Center for Computational Neuroscience
>> Institute for Neural Computation, University of California San Diego
>>
>
>


-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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