[Eeglablist] SASICA 1.3.1 now available

[Maximilien Chaumon]

Dear Iman,

I have little experience with resting state EEG, but here's my hunch: clean
neural components should have the same properties as with epoched data.
Namely, a smooth/dipolar topography (dipolar fits explaining a lot of
variance is a good indicator), relatively large amplitude (i.e. they should
be ranked among the first components), they could also have a peak at a
physiological frequency (alpha, beta...) and should generally rank low on
the artefact measures returned by SASICA.
SASICA is designed to spot specific artifactual components, so it is a bit
of a reverse use you want to make of it.
In the paper here
<https://github.com/dnacombo/SASICA/blob/master/Chaumon_et_al_JNM_2015.pdf> he
examples of Figure 3 G-I are atypical neural components that are likely to
be mistaken for ocular ones. More stereotypical neural components are shown
on Figure 2.

Hope this helps
Max

Le jeu. 21 juil. 2016 à 18:17, Iman Mohammad-Rezazadeh <
irezazadeh at ucdavis.edu> a écrit :

> My question is how your method can separate btw neural and non neural
> components (such as one in Fig 3G) *in resting state EEG (* if there is
> no event related activity)?
>
>
>
> *From:* Maximilien Chaumon [mailto:maximilien.chaumon at gmail.com]
> *Sent:* Wednesday, July 20, 2016 11:49 PM
> *To:* Iman Mohammad-Rezazadeh <irezazadeh at UCDAVIS.EDU>;
> eeglablist at sccn.ucsd.edu
> *Cc:* Rob Coben <drcoben at gmail.com>
> *Subject:* Re: [Eeglablist] SASICA 1.3.1 now available
>
>
>
> Hi Iman,
>
>
>
> Thanks for your note. What is your question?
>
>
>
>
>
> Le mer. 20 juil. 2016 à 19:32, Iman Mohammad-Rezazadeh <
> irezazadeh at ucdavis.edu> a écrit :
>
> Hi Max,
>
> It is great.
>
> I have a question about the toolbox and its application on continuous EEG
> processing , especially during resting. Examples in your published paper
> are based on ERP experiments however if we don’t have any sign on ERP
> components in the temporal activity I wonder how your algorithm/toolbox can
> differentiate btw neural and non-neural for something like Fig 3 G.  For
> example, In your paper it is obvious that for the above figure, you have
> got a early positive and late negative ERP components.
>
>
>
> Best,
>
> Iman
>
> *-------------------------------------------------------------*
>
> *Iman M.Rezazadeh, Ph.D*
>
> Semel Intitute, UCLA , Los Angeles
>
> & Center for Mind and Brain, UC DAVIS, Davis
>
>
>
>
>
>
>
> *From:* eeglablist-bounces at sccn.ucsd.edu [mailto:
> eeglablist-bounces at sccn.ucsd.edu] *On Behalf Of *Maximilien Chaumon
> *Sent:* Tuesday, July 19, 2016 4:15 AM
> *To:* eeglablist at sccn.ucsd.edu
> *Subject:* [Eeglablist] SASICA 1.3.1 now available
>
>
>
> Dear all,
>
> A new version of SASICA, the EEGLAB extension for ICA component selection
> is available in the extension repository of EEGLAB (File > Manage
> Extensions > data processing extensions), or directly from github
> <https://github.com/dnacombo/SASICA/archive/master.zip>.
>
> The associated paper can be downloaded here
> <https://github.com/dnacombo/SASICA/blob/master/Chaumon_et_al_JNM_2015.pdf>
> .
>
>
>
> New features:
>
> Bug fixes and improved usability.
>
>
>
> Note: on a new install, first entering SASICA('resetprefs') in the command
> window is recommended.
>
> Enjoy!
> Max
>
>
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