[Eeglablist] epoch baseline removal experience?

Sun May 13 06:40:47 PDT 2012

Dear Makeig,

I still feel quite confused about your post.Please forgive me for my
ignorance as a newbie in ICA.
My questions can be outlined as follows:
1)Why should we first remove major artifacts and then filter the data?Can
we invert these two procedures?
2)ICA should be conducted in epoched data or continuous data?If both are
ok,which is better?For continuous data often contains large amounts of
artifacts,which happens during the interval of each trial in experiment,I
think it may be better to do ICA on epoched data.
3)Why should baseline removal be done after ICA?I really don't understand
the reason under this practice.
4)Why longer epochs are more enjoyable for ICA?
5)Are there some indicators which can  used to identify if the result of
ICA are good enough to make inference?
Sorry for the long question list and wish for your reply.

2012/5/13 Matthew Stief <ms2272 at cornell.edu>

> Hi Scott,
>
> Thanks for this. If you're going to baseline-zero epochs after ICA, then
> what's the point of baselining the whole dataset before epoching? Just to
> have an additional kind of high pass filter?  You're saying that doing this
> AND a ~1Hz high-pass filter would be better for the ICA than just doing the
> high-pass filter, right? I thought that the advantage of doing the
> whole-epoch baseline (and thus also i assume this whole dataset baseline
> removal), was that it ameliorated problems of low frequency drift for the
> ICA without suffering from the attenuation of large later components caused
> by an aggressive high pass filter. So I was thinking of it as an
> alternative to high pass filtering, not an addition to it. In my current
> data processing strategy I've gone for not baseline removing before ICA at
> all, and just relying on an aggressive 2 Hz high-pass filter (all I care
> about is the P1), and then doing a baseline removal for epochs after the
> ICA. But you're saying doing this big baseline removal and a high pass
> produces superior results, right?
>
> Also, I wasn't sure from your e-mail whether you thought the whole dataset
> baseline removal should occur before or after filtering. I've been doing
> major artifact removal after filtering because it makes bad patches easier
> to see, but i'd be happy to do it this way if it creates a better ICA
> decomposition to do this kind of total baseline removal.
>
> Thank you!
>
> -Matthew
>
>
>
> On Fri, May 11, 2012 at 11:09 PM, Scott Makeig <smakeig at gmail.com> wrote:
>
>> Even whole-epoch baseline removal is not ideal.  It is better to
>> zero-baseline the data after major artifact-period removal but before
>> epoching (and, typically, high-pass filtering above ~1 Hz). Only then
>> extract epochs for ICA decomposition (IF you do not want to decompose the
>> continuous data -- our more typical procedure). After ICA decomposition,
>> data epochs can be individually baseline-zeroed without affecting the ICA
>> account of them.
>>
>> Scott
>>
>> On Fri, May 11, 2012 at 12:31 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>wrote:
>>
>>> Dear Ida and Scott,
>>>
>>> > As I understood, the purpose of Baseline Removal is for me/us to have
>>> > better insight when event in observed epoch happened, so the value
>>> around
>>> > corresponding marker is expected to be zero. Right?
>>>
>>> That sounds right, although I may not understand you perfectly.
>>> ERP show up usually after the event (unless it is expectation-related
>>> nature), so it makes sense to set the baseline period before stimulus
>>> onset during which brain activity is supposed to be neutral, and
>>> whatever ERP can be compared against it.
>>>
>>> > I have one more question regarding this - does it matter if I Remove
>>> > Baseline for example (-1000ms to 0ms) if I have epoch that is longer
>>> (-4
>>> > secs to 4 secs)? I read in Q&A list Arno's answer regarding similar
>>> question
>>> > where he said that ICA can be unstable if the epochs baseline is too
>>> short,
>>> > so he suggests longer baselines (i.e 1 sec).
>>>
>>> Although I don't know what Arno meant in that specific context, I
>>> guess he was probably referring to the finding reported by Groppe,
>>> Makeig, and Kutas (2009). In the paper, the authors reports
>>> whole-epoch baseline produced better ICA results compared to short
>>> pre-stimulus baseline. Therefore, for ICA purpose, it's even better to
>>> use an entire epoch for a baseline. The authors says 'It is not clear
>>> what causes this difference.' in the paper (pp.1208), though I heard
>>> Scott say a brief explanation. What do you think, Scott?
>>>
>>> Makoto
>>>
>>>
>>>
>>> 2012/5/10 ida miokovic <ida.miokovic at gmail.com>:
>>> > Dear Makoto,
>>> >
>>> > thank you for your answer, it cleared the doubts in my head regarding
>>> this
>>> > =). As I understood, the purpose of Baseline Removal is for me/us to
>>> have
>>> > better insight when event in observed epoch happened, so the value
>>> around
>>> > corresponding marker is expected to be zero. Right?
>>> >
>>> > I have one more question regarding this - does it matter if I Remove
>>> > Baseline for example (-1000ms to 0ms) if I have epoch that is longer
>>> (-4
>>> > secs to 4 secs)? I read in Q&A list Arno's answer regarding similar
>>> question
>>> > where he said that ICA can be unstable if the epochs baseline is too
>>> short,
>>> > so he suggests longer baselines (i.e 1 sec).
>>> >
>>> > Thanks,
>>> >
>>> > Ida
>>> >
>>> >
>>> > On Thu, May 10, 2012 at 9:45 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu
>>> >
>>> > wrote:
>>> >>
>>> >> Dear Ida,
>>> >>
>>> >> The consequence would be that you may not have near-zero potential
>>> >> at/around time zero (and this time zero which should be an onset of
>>> >> whatever event). Usually people want to reset their data to zero
>>> >> microvolt at/around time zero, so they subtract mean of short time
>>> >> period immediately before it (for example, -200 ms to 0 ms as a
>>> >> baseline period). Am I answering to your question? If not, let me
>>> >> know.
>>> >>
>>> >> Makoto
>>> >>
>>> >> 2012/5/10 ida miokovic <ida.miokovic at gmail.com>:
>>> >> > Hello everyone,
>>> >> >
>>> >> > Since I do not have experience in eeg signal processing, I am
>>> asking you
>>> >> > for
>>> >> > the opinion regarding epoch baseline removal (a window for this
>>> pops up
>>> >> > after I do the data epoching). Epochs I am extracting are quite
>>> long: -4
>>> >> > secs before and 4 secs after Marker of my interest.
>>> >> >
>>> >> > Why is following suggested in tutorial:
>>> >> >
>>> >> > "Using the mean value in the pre-stimulus period (the pop_rmbase()
>>> >> > default)
>>> >> > is effective for many datasets, if the goal of the analysis is to
>>> define
>>> >> > transformations that occur in the data following the time-locking
>>> >> > events."
>>> >> >
>>> >> > What are the consequences if I leave the fields in pop up window
>>> (Epoch
>>> >> > Baseline Removal) empty and therefore have the whole epoch used as a
>>> >> > baseline?
>>> >> >
>>> >> > Thank you in advance,
>>> >> >
>>> >> > All the best,
>>> >> >
>>> >> > Ida
>>> >> >
>>> >> >
>>> >> >
>>> >> >
>>> >> >
>>> >> >
>>> >> > _______________________________________________
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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
>>>
>>
>>
>>
>> --
>> Scott Makeig, Research Scientist and Director, Swartz Center for
>> Computational Neuroscience, Institute for Neural Computation; Prof. of
>> Neurosciences (Adj.), University of California San Diego, La Jolla CA
>> 92093-0559, http://sccn.ucsd.edu/~scott
>>
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>
>
>
> --
> _________________________________________________________________
> Matthew Stief
> Human Development | Sex & Gender Lab | Cornell University
> http://www.human.cornell.edu/HD/sexgender
>
>
> Heterosexuality isn't normal, it's just common.
> -Dorothy Parker
>
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-- 
Yuan-Fang Chao
School of Psychology
SouthWest University
Beibei,Chongqing,China
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