[Eeglablist] MATLAB for EEGLAB

Fri Feb 17 17:41:47 PST 2017

Dear Devvarta,

I agree with Stephen. Signal processing and Statistics is good to have.
When you perform channel warping, I think it needs optimization toolbox as
well.

Makoto

On Wed, Feb 8, 2017 at 5:43 PM, Dr Devvarta Kumar <devvarta.k at nimhans.ac.in>
wrote:

> Hi
>
> I am buying MATLAB for running EEGLAB. Please let me know whether only
> basic MATLAB is to be procured or any toolbox is also required to run
> EEGLAB?
>
> Best wishes
>
> Devvarta Kumar
>
>
> ----- Original Message -----
> From: Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> Date: Sunday, January 22, 2017 1:21 pm
> Subject: Re: [Eeglablist] ICA question
> To: "Ahmad, Jumana" <jumana.ahmad at kcl.ac.uk>
> Cc: "eeglablist at sccn.ucsd.edu" <eeglablist at sccn.ucsd.edu>
>
> > Dear Jumana,
> >
> > > For data rank reasons, I interpolated and average referenced after
> ICA, using runica. When re-referencing I deleted the ICA activation matrix
> and the ICA weights, because of course I now have interpolated channels
> which do not have ICA weights associated with them.
> >
> > Average referencing is just to subtract a fixed value from all
> channels/ICs, so I thought it is harmless. You don't need to delete
> ICA-calculated items.
> >
> > > I only wanted to do ICA for eye blink rejection, and it worked
> perfectly and I did not have any ICA corruption (trade offs or rank
> deficiency). I compared the data before and after ICA and the level of
> noise was the same.
> >
> > Do you mean that if you don't reject ICA-calculated items, it destroys
> data? I'm interested in testing it. It's more likely it does not happen. If
> you say you reject channels after ICA, it's more likely to result in more
> complicated situation, depending on the path you follow using EEGLAB.
> >
> > By the way what do you mean trade-off?
> >
> > > I am working with an extremely large dataset and do not ideally want
> to re-do these steps, especially because I am mainly working with raw
> channel ERP data.
> >
> > It's a good opportunity for you to start using batch code. If you
> follow my instructions in my wiki pages, 100-200 datasets are nothing. I
> created a STUDY with nearly 1,000 datasets with no problem, so I can
> guarantee up to 1,000. If you eventually want to go back to channels, then
> after ICA selections using std_selectICsByCluster(), perform channel
> statistics. In this case, I think interpolation will definitely help you
> because it'll eliminate missing value problems reasonably.
> >
> > > this time on the Chanel data where ICA blink components have been
> removed
> >
> > Even if you run ICA on IC-rejected clean data, you won't obtain cleaner
> data. What happens is that you'll get exactly the same decomposition. Try
> it with one subject to see it.
> >
> > > Identify noisy channels
> > > Run ICA on clean channels
> > > Interpolate electrodes to give the same 60 electrodes per person
> > > Average reference to the 60 electrodes
> > > Compute ERPs on channel data
> > > Then re-run ICA, and do any further analysis on component data.
> >
> > Yeah it works. Most likely, the last ICA will produce the same results
> except post average-reference components show zero-mean scalp topos.
> >
> > Makoto
> >
> >
> >
> >
> > On Fri, Jan 13, 2017 at 6:20 AM, Ahmad, Jumana <jumana.ahmad at kcl.ac.uk>
> wrote:
>
>> > Dear EEGlab.
>>
>> > For data rank reasons, I interpolated and average referenced after
>> ICA, using runica. When re-referencing I deleted the ICA activation matrix
>> and the ICA weights, because of course I now have interpolated channels
>> which do not have ICA weights associated with them.
>>
>> >
>>
>> > I only wanted to do ICA for eye blink rejection, and it worked
>> perfectly and I did not have any ICA corruption (trade offs or rank
>> deficiency). I compared the data before and after ICA and the level of
>> noise was the same.
>>
>> >
>>
>> > I am working with an extremely large dataset and do not ideally want
>> to re-do these steps, especially because I am mainly working with raw
>> channel ERP data.
>>
>> >
>>
>> > However, for future analysis, if I did want to work with component
>> data, could I re-run ICA for a second time, this time on the Chanel data
>> where ICA blink components have been removed, and where the interpolated
>> electrodes and the new reference implemented (this data should already be
>> clean from blinks etc).
>>
>> >
>>
>> > Overal this would look like:
>>
>> >
>>
>> > Identify noisy channels
>>
>> > Run ICA on clean channels
>>
>> > Interpolate electrodes to give the same 60 electrodes per person
>>
>> > Average reference to the 60 electrodes
>>
>> > Compute ERPs on channel data
>>
>> > Then re-run ICA, and do any further analysis on component data.
>>
>> >
>>
>> >
>>
>> > Please let me know if you can see any issues with this. I very much
>> appreciate any advice.
>>
>> > Best wishes,
>>
>> > Jumana
>>
>> >
>>
>> *> ------------------------------> ------------*
>> *> Jumana Ahmad*
>> > Post-Doctoral Research Worker in Cognitive Neuroscience
>> *> EU-AIMS Longitudinal European Autism Project (LEAP) & SynaG Study*
>> > Room M1.26.Department of Forensic and Neurodevelopmental Sciences (PO
>> 23) | Institute of Psychiatry, Psychology & Neuroscience | King’s College
>> London | 16 De Crespigny Park | London SE5 8AF
>> >
>> *> Phone:* 0207 848 5359| *Email:* jumana.ahmad at kcl.> ac.uk | *Website:*
>> www.eu-aims.> eu <http://www.eu-aims.eu/> | *Facebook:* www.facebook.>
>> com/euaims <http://www.facebook.com/euaims>
>> >
>>
>> >
>> > ______________________________> _________________
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> >
> >
> >
> > --
> > Makoto Miyakoshi
> > Swartz Center for Computational Neuroscience
> > Institute for Neural Computation, University of California San Diego
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>
> =============================================
> Devvarta Kumar, Ph.D.
>
> Additional Professor
> Department of Clinical Psychology
> M. V. Govindaswamy Building
> National Institute of Mental Health and Neurosciences,
> Hosur Road,
> Bangalore,
> Karnataka-560029
> India
>
> Ph: +91-80-26995188 <+91%2080%202699%205188>
> http://www.nimhans.ac.in/users/dr-devvarta-kumar
>
>

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