[Eeglablist] bad channel rejection - kurtosis - threshold limits default 5

[Makoto Miyakoshi]

Dear Ida,

> I didn't pay much attention to it assuming
> that the default settings are the most common ones.

Not necessarily so. These parameters depend on your data quality.

> - Why is 5 default value for the max threshold limits? I read explanation of
> the function jointprob() where it says that the threshold is expressed in
> standard deviation of the mean.

Start with 5 and see the results. If it catches too many epochs, then
increase the value. I would use 8-10.

> - What would be the easiest way to calculate the standard deviation of the
> mean of my dataset and would that result be the threshold that is
> appropriate to my dataset?

Adjust them so that the sum of epochs suggested by your rejection
methods ends up with around 10 % of the data.

> - Are there situation when it is better to use Kurtosis rather than the
> probability measure and the other way around?

You should see what type of artifacts are picked up by what methods.
Generally, kurtosis is too sensitive to outliers. The probability
measure sometimes picks up large alpha. Both have problems, so don't
completely rely on them. Use them mildly.

I would recommend that you simply threshold the data by amplitude
first (+/- 150-200 microvolt, for example) to exclude undoubtedly
wrong epochs due to loose channel etc (select up to 1% of data- but be
careful not to catch eye blinks), then apply probability method
(select up to 3-5% of data). You may think the data is not clean yet,
but apply ICA anyway, and do rejections on IC activities to select
another up to 5% of epochs if you want.

See also Delorme et al. 2007 NeuroImage for epoch rejection using
EEGLAB tools. This is an excellent guide for you.

My general impression is that people spend too much time on data
cleaning (especially psychologists; I've seen this because I'm a
psychologist). ICA decomposition is in many cases more robust than you
think. If you want to prove it, try ICA with rejection rate of 5%,
10%, and 15%. I'll bet you don't see much (or even any) difference in
IC topos and spectra as long as you recorded the data in an ordinary
laboratory environment. So don't be too nervous.

Makoto

2013/2/9 ida miokovic <ida.miokovic at gmail.com>:
> Dear eeglab list,
>
> after performing some analysis on the eeg dataset I have, I noticed that in
> "Bad channels rejection" step I used Kurtosis measure, normalize measure
> checked and the max threshold limits remained set on 5 (by the default). At
> the time of performing this step, I didn't pay much attention to it assuming
> that the default settings are the most common ones. Now, when explaining to
> the detail each step of my analysis, I'm stuck here.
>
> - Why is 5 default value for the max threshold limits? I read explanation of
> the function jointprob() where it says that the threshold is expressed in
> standard deviation of the mean.
>
> - What would be the easiest way to calculate the standard deviation of the
> mean of my dataset and would that result be the threshold that is
> appropriate to my dataset?
>
> - Are there situation when it is better to use Kurtosis rather than the
> probability measure and the other way around?
>
> Thank you very much for your help and I apologize in advance if you find
> these questions too simple...
>
> 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