[Eeglablist] (no subject)

[Makoto Miyakoshi]

Dear Valeio,

> -What is the most easier way to interpret the attached plot (localize
component),i.e., what is the meaning of the plot components.

There may be some event at around 500ms. However, the event may not be in
synch with the window length. I noticed in your ERPimage there is
trial-by-trial shift of latency.

> -Is localize component plot basically related to the attached file
(Component ERP image) or to the attached file (Component maps In 2-D) or to
the attached file (component spectra and maps)?

Since you have only a few number of channels, it is inappropriate to
perform DIPFIT! Just show scalp topos and don't use dipfit (or you'll
mislead readers). I wanted to judge the decomposition quality from the
scalp topo distribution but too few number of channels. From the time
series, I thought the data quality is not very good (if the ERPimage shows
IC activity).

Makoto

On Sat, Sep 19, 2015 at 11:13 AM, valerio jus <valeriojus at gmail.com> wrote:

> Hi all,
>
> -What is the most easier way to interpret the attached plot (localize
> component),i.e., what is the meaning of the plot components. Please not
> that, I obtainment this plot form Tools > Locate dipoles using DIPFIT >
> Plot component dipoles.
>
>
> -Is localize component plot basically related to the attached file
> (Component ERP image) or to the attached file (Component maps In 2-D) or to
> the attached file (component spectra and maps)?
>
> Thanks a lot.
>
> Valerio​
>  Localizing components.png
> <https://drive.google.com/file/d/0Byt9XStqEMdIWWZVYkROd1llbG8/view?usp=drive_web>
> ​​
>  component spectra and maps.png
> <https://drive.google.com/file/d/0Byt9XStqEMdINkRyNmVWXzJqN2s/view?usp=drive_web>
> ​​
>  Component maps In 2-D.png
> <https://drive.google.com/file/d/0Byt9XStqEMdIcVQ4THhmRE8zOUk/view?usp=drive_web>
> ​​
>  Component ERP image.png
> <https://drive.google.com/file/d/0Byt9XStqEMdISEgyWF95VTBwV00/view?usp=drive_web>
> ​
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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