Dear Haiteng,
2009/7/2 hiten <[log in to unmask]>:
> Dear SPMers:
> Now I am confused about the filtering of M/EEG data.The data was collected
> by VSM CTF275 MEG system,sample at 1200HZ,under incongruent color-words
> STROOP task.The data are preprocessed:
> convert,epoching(-200ms--800ms),aritifacts(1*e-12T).the attached pictures
> has the follwing meanings:
> Pic 1 mean: after aritifact then average signals of all
> 64 trials
> Pic 1mean+2filter: filtering the averaged signals using the
> butterworth bandpass(1-100HZ)
> Pic 1filter+2mean firstly filter(butterworth bandpass(1-100HZ)),then
> average
> Pic 1mean+2wt use my improved wavelet-based de-noising
> algorithm to the averaged signals
>
> 'Mechanisms of evoked and induced responses in MEG/EEG',Olivier David, James
> M. Kilner,* and Karl J. Friston.NeuroImage 31 (2006) 1580 - 1591 clearly
> shows that evoked responses are determinate,time/wave locked. so I have the
> following questions:
> 1.how to set the bandpass width accurately? could somebody give me some
> advice?
>
That depends on your data and on the purpose of your analysis. In
principle you should select the bandpass in such a way that the
activity of interest will be included and noise will be excluded.
> 2.which is the best processing sequences: first average then filter or first
> filter then average? However, no matter Pic1mean+2filter or Pic1filter+2mean
> are deformated comparing to Pic 1 mean ,which I think is not in conformity
> with the actual situation.In my opinion,filtering should be done using a
> zero-phase band-pass filter while spm8 not.
>
In principle both are possible. I'm surprised that there is such a big
difference between the results and it looks like the original data is
distorted too much. SPM does use a zero-phase bandpass filter but
perhaps for such a wide band, you should use 1Hz highpass and 100Hz
lowpass applied sequentially rather than a bandpass. Another
possibility that many people use especially for low-cutoff highpass
filter is to filter continuous data before epoching to avoid edge
artefacts.
> 3.In theory, Pic 1 mean is the evoked respones with additive gaussian noise.
> Pic 1mean+2wt is most similar to Pic 1 mean. So I think Pic 1mean+2wt is
> most closet to the realistic situation. Am I right?
>
It looks quite good but you are not writing just to advertise your
denoising method, are you ;-) ?
Best,
Vladimir
> Any comments would be greatly appreciated. Thanks in advance!
>
> --
> haiteng jiang
> Research Center for Learning Science,
> Southeast University
> Si Pai Lou 2 # , Nanjing, 210096, P.R.China
> Brain Imaging Lab
> Email: [log in to unmask]
>
>
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