[Eeglablist] artifact rejection for abnormal trends

[Arnaud Delorme]

Dear Josh,

if you perform a linear fit, for instance using the Matlab regress function, the function computes the R-square statistics. This is the square of the correlation coefficient. For more information, see

http://en.wikipedia.org/wiki/Coefficient_of_determination

Thanks,

Arno

On Aug 23, 2012, at 8:12 AM, Makoto Miyakoshi wrote:

> Dear Arno,
> 
> I don't understand it either. Maybe it requires more explanation.
> Would you help us please?
> 
> Makoto
> 
> 2012/8/22 Joshua Hartshorne <jkhartshorne at gmail.com>:
>> I am using ICA to correct for blinks. Prior to running ICA, I am doing a bit
>> of minimal data-cleaning so that my ICA is reasonably good. I rejected and
>> replaced bad channels (kurtosis, threshold=4) and then am rejecting epochs
>> based on an abnormal linear trend of greater than 150 (which I realize is
>> quite generous).
>> 
>> What I don't entirely understand is the minR option that one has to set for
>> the abnormal trend detection. The documentation says, cryptically, that it's
>> the "minimal linear regression R-square value to allow in the data". What
>> are we regressing? Is this mV against time? That is, is this a measure of
>> how linear the trend is (1 = perfectly linear during the epoch)?
>> 
>> Thank you. Josh Hartshorne
>> 
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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
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