[Eeglablist] Can i filtering in two different moments?

[Makoto Miyakoshi]

Dear Tiago,

First of all, DO NOT use pop_eegfilt(). Instead, use pop_eegfiltnew(). This
newer version is better.

> My question is: Can filtering at two different times compromise the
reliability of the collected signal? (ie, in addition to the artifact, am i
taking out brain information that compromises the interpretation of the
data?)

Secondly, apply filters only on continuous data. If you apply it on epoched
data, data are windowed near boundaries (i.e. both edges).

If you are interested in an example of preprocessing steps, see this wiki
page.
https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline#Alternatively.2C_cleaning_continuous_data_using_ASR_.2811.2F30.2F2016_updated.29

Makoto



On Mon, Nov 28, 2016 at 8:04 AM, tiago lopes <tiago.lopes56 at yahoo.com>
wrote:

> Hello Dears,
> I am developing an experiment where i try to evaluate the thalamocortical
> dysrhytimia in individuals with chronic pain.
> In order to improve the quality of the collected signal eeg by the removal
> of artifacts, i am filtring in two different moments:
> A) Before dividing into epochs
> B After being divided into epochs
>
> My question is: Can filtering at two different times compromise the
> reliability of the collected signal? (ie, in addition to the artifact, am i
> taking out brain information that compromises the interpretation of the
> data?)
>
> Below is the script used in data processing.
> Thanks a lot for the help.
>
> path ='C:\Users\Tiago Lopes\Documents\MATLAB\Script\REPOUSO E IMG\01 Set
> epochs e ICA (REPOUSO)\';
> epochs ='C:\Users\Tiago Lopes\Documents\MATLAB\Script\REPOUSO E
> IMG\TABELA DE EVENTOS 5000ms.txt';
> name=strcat(path,'*.ASC');
> d=dir(name);
>
> for j=1:length(d)
>     filename = d(j).name;
>     EEG = pop_loadbci( filename, 600 );
>     EEG = pop_select( EEG,'nochannel',{'FOTO'});
>     EEG = pop_select( EEG,'nochannel',{'EMGd' 'EMGm'});
>     EEG = pop_chanedit(EEG, 'lookup','standard-10-5-cap385.elp');
>     EEG = pop_reref( EEG, [] );
>     EEG = pop_eegfilt( EEG, 0.5, 30, [], [0], 0, 0, 'fir1', 0);
>     EEG = pop_importevent( EEG, 'event',epochs,'fields',{'type'
> 'latency'},'skipline',1,'timeunit',0.001);
>     EEG = pop_epoch( EEG, {  }, [-.420 4.580], 'epochinfo', 'yes');
>     EEG = pop_rmbase(EEG,[-300 0]);
>     EEG = pop_eegfilt( EEG, 1.80, 30, [], [0], 0, 0, 'fir1', 0);
>     EEG = pop_epoch( EEG, {  }, [-.420 4.580], 'epochinfo', 'yes');
>     EEG = pop_rmbase(EEG,[-300 0]);
>     EEG = pop_runica(EEG, 'extended',1,'interupt','on');
>     EEG = pop_subcomp( EEG, [1 2], 0);
>     EEG = pop_saveset( EEG, 'filename',d(j).name,'filepath',path);
> end
>
> Att. Tiago Lopes
>



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