[Eeglablist] the correct EEG data processing pipeline
Makoto Miyakoshi
mmiyakoshi at ucsd.edu
Fri Oct 19 09:19:31 PDT 2012
Dear Hui-bin,
Yes. ICA can be easily disturbed by low frequency artifact such as
sweating etc. This is why we use 1Hz high-pass, which is very high.
You actually don't need to use this 1Hz high-passed data, because once
you get ICA weight you can use it for 0.1Hz high-passed data, for
example.
Makoto
2012/10/19 Hui-bin Jia <420247417 at qq.com>:
> Dear Makoto,
> Do you mean applying a high-pass filter before ICA will get less
> artifact Independent components?
> Thank you!
>
> Hui-bin
>
>
>
> ------------------ Original ------------------
> From: "mmiyakoshi"<mmiyakoshi at ucsd.edu>;
> Date: Fri, Oct 19, 2012 10:34 PM
> To: "Hui-bin Jia"<420247417 at qq.com>;
> Cc: "eeglablist"<eeglablist at sccn.ucsd.edu>;
> Subject: Re: [Eeglablist] the correct EEG data processing pipeline
>
> Dear Hui-bin,
>
> Applying a high-pass filter helps ICA, so you may want to consider it.
>
> Makoto
>
> 2012/10/18 Hui-bin Jia <420247417 at qq.com>:
>> Hi, everyone
>>
>> I have been studying EEGLAB for about one year. But until now I’m not sure
>> about my EEG data processing pipeline is right or not.
>>
>> My EEG data processing pipeline is:
>>
>> (1) Load EEG data into EEGLAB
>>
>> (2) Read channel locations (Edit > Channel locations)
>>
>> (3) Re-reference
>>
>> (4) Use AAR ( a plugin of EEGLAB) reject EOG and EMG
>>
>> (5) Run ICA and reject artifact components using ADJUST which is also a
>> plugin.
>>
>> (6) Filter the data
>>
>> (7) Extract epochs and Remove baseline
>>
>> (8) Reject epochs (Tools > Reject data epochs)
>>
>> Is my method right?
>>
>> Any reply will be greatly appreciated!
>>
>> THANK YOU!
>>
>> Hui-bin Jia
>>
>>
>>
>>
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>
>
> --
> Makoto Miyakoshi
> JSPS Postdoctral Fellow for Research Abroad
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
--
Makoto Miyakoshi
JSPS Postdoctral Fellow for Research Abroad
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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