[Eeglablist] A question on semi-automatic detection on continuous data

[Simon-Shlomo Poil]

Hi,

You might also read this page
http://www.nbtwiki.net/doku.php?id=tutorial:automatic_and_semi-automatic_methods_for_eeg_pre-processing#.UGXID1Eldvk
about the FASTER and ADJUST toolboxes, which are integrated in the NBT
toolbox (which is a plugin for EEGlab)

Best regards
Simon



2012/9/26 Tarik S Bel-Bahar <tarikbelbahar at gmail.com>:
> Hello Eve,
>
> Until you find the tools in question in BCIlab,
>
> One way to do this is as follows, let the list know if you have success
> with these simple steps.
>
> 1. Prepare your data (filtering, re-referencing, bad channel dropping,
> etc...)
> up to the point that you are ready to remove "artifactual time periods".
>
> 2. use eeg_regepochs to make a series of "fake" contiguous epochs,
> choosing an epoch size of your choice (.5 or 1 second).
>
> 3. run the epoch rejection tool of choice within eeglab, which will lead
> to the dropping of some subset of the fake epochs from step 2.
>  [you may have to try several different methods,
> and determine what works best for your data]
>
> 4. if you are happy with retained epochs
> run ICA on this newly cleaned set of fake contiguous epochs.
> Note that you need to feed ICA enough data, and preferably
> only periods of time when the cognitive activity in question was occurring.
> for example, don't include the minutes of data when nothing was going on,
> or "in between" your experimental blocks.
>
> 5. Now, if you are happy with the ICA decomposition you get
> apply your ICA decomposition to the continuous file
> just before step 2 above.
>
>
> 6. At this point, you can make your "real" epochs based on
> your true events, and again drop the artifactual epochs.
> (for example, the epochs that have extreme values).
> ...and you should be able to move forward.
>
> 7. Note if you use AMICA from Jason Palmer,
> it is possible for AMICA to discount artifactual periods via the "do_reject"
> flag.
>
>
> Note: almost any method to remove artifactual periods from continuous data
> will necessitate making "windows" within which the artifact detection
> method.
> If you can learn to do it on your own, you could make fake epochs
> via your own scripts, and then rejoin all the remaining epochs.
>
>
>
>
>
>
> On Fri, Sep 21, 2012 at 3:43 PM, alotof eve <alotof_tiger at yahoo.com> wrote:
>>
>>
>> Dear experts,
>>
>> I cannot find the function of semi-automatic detection of artifact for
>> continuous data in BCIlab as Makoto suggested. Any other way to do
>> semi-automatic detection of artifact for continuous data (before segment)
>> off-line?
>>
>> We do ICA but we want to do some artifact detection before it.
>>
>> Many thanks,
>> Duo
>>
>> ----- Forwarded Message -----
>> From: alotof eve <alotof_tiger at yahoo.com>
>> To: "mmiyakoshi at ucsd.edu" <mmiyakoshi at ucsd.edu>
>> Cc: "eeglablist at sccn.ucsd.edu" <eeglablist at sccn.ucsd.edu>
>> Sent: Friday, September 21, 2012 3:39 PM
>> Subject: Re: [Eeglablist] A question on semi-automatic detection on
>> continuous data
>>
>> Dear experts,
>>
>> I cannot find the function of semi-automatic detection of artifact for
>> continuous data in BCIlab as Makoto suggested. Any other way to do
>> semi-automatic detection of artifact for continuous data (before segment)
>> off-line?
>>
>> Many thanks,
>> Duo
>>
>> ________________________________
>> From: Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
>> To: alotof eve <alotof_tiger at yahoo.com>
>> Cc: "eeglablist at sccn.ucsd.edu" <eeglablist at sccn.ucsd.edu>; Christian Kothe
>> <christiankothe at gmail.com>
>> Sent: Thursday, September 20, 2012 7:55 AM
>> Subject: Re: [Eeglablist] A question on semi-automatic detection on
>> continuous data
>>
>> Dear Duo,
>>
>> BCIlab supports it. If you are interested in, please refer to BCIlab wiki.
>> http://sccn.ucsd.edu/wiki/BCILAB
>> I also copy this to the developer of BCIlab, Christian Kothe, for
>> comments.
>>
>> Makoto
>>
>> 2012/9/19 alotof eve <alotof_tiger at yahoo.com>:
>> > Hello, experts,
>> >
>> > I have a question on semi-automatic detection of artifact. I noticed
>> > that
>> > when only the data is segmented, we can use semi-automatic method on
>> > tool
>> > panel. When the data is continuous, the automatic method is invalid. I
>> > am
>> > doing data analysis and I am asked to find a way to do automatic
>> > rejection
>> > on continuous data. I wonder if there is any reason that EEGLab dosen't
>> > offer this function?  Any suggestion on doing semi-automatic detection
>> > on
>> > continous data?
>> >
>> > Thanks,
>> > Duo
>> >
>> > _______________________________________________
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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
>>
>>
>>
>>
>>
>> _______________________________________________
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>
>



-- 
--
Simon-Shlomo Poil

Center of MR-Research
University Children’s Hospital Zurich

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