[Eeglablist] ICA and dipfit: high residual variance

[John Fredy Ochoa Gómez .]

Dear Giovanni, and your topographies seem dipolar? seem neuronal? If you
have bad topographies you will have high residual variance

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135

Best,

On Wed, Sep 21, 2016 at 7:30 AM, Giovanni Vecchiato <
giovanni.vecchiato at gmail.com> wrote:

> Dear all,
>
>
>
> I’m performing an ICA followed by a dipole source localization (DIPFIT)
> and I’m not satisfied by the outcome of the analysis because it returns too
> high values of residual variance (RV%).
>
>
>
> Here the details of the EEG signal acquisition and processing (eeglab
> v13.6.5b):
>
>
>
> 1.    Data acquisition with EGI (srate = 500 Hz; 129 channel):
>
> a.    two blocks of an execution task (EX) + two blocks of motor imagery
> task (IM) (overall, around 17 minutes of recording)
>
>
>
> 2.    Signal processing
>
> a.    PREP pipeline with line frequency removed = [50 100 150 200]; the
> other parameters are the default ones
>
> b.    high pass filtering @ 0.1 Hz
>
> c.    data segmentation in EX and IM conditions ([-1, 6] seconds), 40
> trials per condition
>
> d.    PCA on the IM dataset (35 trials remained after trial rejection)
>
> e.    Extended ICA with 27 PCs to retain (which explain the 99% of the
> variance)
>
> f.     DIPFIT analysis using the MNI template and manual co-registration
> (the actual EGI channel positions are correctly loaded) returning an
> average residual variance of (0.5 +/- 0.2) which values seem too high to be
> taken into account for a following analysis of ICs.
>
>
>
> I have tried several modification to the above processing chain (e.g. low
> pass filtering @ 45 Hz; ICA on a larger number of PCs and on a larger
> number of trials (80); ICA performed with AMICA; ICA performed with Brain
> Vision Analyzer – Extended ICA) but with no improvement of the results. I
> have also tried on different datasets and tasks with the same results.
>
>
>
> Do you all have any suggestion to achieve lower DIPFIT residual variance
> which are plausible from the neurophysiological point of view?
>
> I can also share a sample dataset if you consider it useful.
>
>
>
> Thanks in advance,
>
> Best,
>
> Giovanni
>
>
>
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-- 
John Ochoa
Docente de Bioingeniería
Universidad de Antioquia
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