[Eeglablist] Re: question about sampling rate in eeglab
arno at sccn.ucsd.edu
Fri Jul 29 07:52:23 PDT 2005
Stefan Scherbaum wrote:
>I have a question about converting sampling rates in EEGlab, hoping
>that you can help me:
>I recorded a file with 1000 Hz and an analog filter onset at 250 Hz.
>Later, I downsampled the data with Brain Vision Analyzer to 250 Hz,
>using a softare filter at 112.5 Hz with 24db damping. This was done to
>make the import into EEGLab easier.
>To check the results of the downsampling, I imported one channel of
>the original data to EEGlab and downsampled it to 250 Hz after
>filtering at 112.5 Hz.
>Comparing this channel with the channel converted with BVA (and
>imported to EEGLab), I realized differences that I can not explain and
>that I hope you might possibly have an explanation for.
>1. The length of the data converted by eeglab (724581) is not 1/4 of
>the original length (2898320) - the BVA file has exactly 1/4 of the
I created a dataset with 2898320 data points, filtered and resampled the
data and obtained exactly 724580 data points. For the difference in data
points, my simpliest explanation would be that the sampling rate
imported in EEGLAB (1000 Hz) is not a round number (1000.0001 Hz for
instance). This number may be rounded in some graphic interfaces. You
can check that by typing EEG.srate. If this is not the case, then I
cannot explain this discrepency since I do not observe it.
>2. There are differences in the curves - I attached a screenshot
>(timescale 0.25): channel 1 is the channel converted by EEGLab (-1
>points), channel 2 is the data converted by BVA and channel 3 shows
The two datasets may look slightly different because different filters
have been used. I do not know which filter BVA uses but it is probably
not linear (24 dB damping seems beyond the capabilities of a linear
filter). You may try using the IIR non-linear filter plugin in EEGLAB
and see if the result is closer to what is returned by BVA.
>Do you have an idea about all this? I am a little bit confused which
>data I should use for further analysis - do you have an idea how to
>choose the right dataset to continue?
As far as which dataset you should use, I think using either dataset is
fine as long as you do not forget to mention which filter type you used
(and which software).
>Thank you very much!
* Arnaud Delorme <http://www.sccn.ucsd.edu/%7Earno>, Ph.D.* , SCCN,
UCSD, San Diego, USA
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