[FieldTrip] Kurtosis topography at channel level

[Rui Li]

Dear Frank,

Thanks for your kind reply.

Regards,
Rui.

On Thu, Jul 21, 2016 at 6:48 PM, Frank Neugebauer <
f.neugebauer at uni-muenster.de> wrote:

> Hi Rui,
>
> *Question 1:* why and how does the filter affect the kurtosis?
>
> As kurtosis is not linear, that is
> kurtosis(data+noise)=/=kurtosis(data)+kurtosis(noise), it is a little hard
> to say how exactly changing your data will change the output kurtosis.
> If you filter Gaussian noise the signal should form stronger outlier and
> thus the data should yield higher kurtosis.
> As far as I understand kurtosis, the frequency itself does not directly
> influence the kurtosis output.
>
>
> *Question 2:* Why the kurtosis topographies at channel level from two
> > dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
> > case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4
> (filtered))
> > are not consistent? Because these two datasets are measured from the same
> > patient, the kurtosis topography should be consistent. Do you have any
> idea
> > about this?
>
>
> As far as I understand, epileptic activity is hard to measure because you
> don't know when it will occur and different measurements are not
> inconsistent, but just show different activity at a different time and
> circumstance (such as different sensor noise, interference, but also the
> patient's condition).
> In the introduction to the case they say,
> >> Corticography also showed interictal discharges in the frontal lobe,
> though seizures were of parietal origin. <<. Maybe this is the explanation?
> The kurtosis points to the frontal lobe, too.
>
> I hope this was a little helpful,
> best regards,
> Frank
>
>
> Rui Li wrote on 2016-07-21:
> > Dear FieldTrip users,
>
> > Recently, I am working on the case 1 dataset of epilepsy tutorial. The
> > first patient got the MEG recording from Neuromag and CTF, respectively.
> I
> > encountered some problems when I tried to depict the Kurtosis topography
> > at channel - level.
>
>
> > *Question 1:* why and how does the filter affect the kurtosis?
>
> > Figure 1 and Figure 2 are kurtosis topographies at channel level without
> > band pass filter and with band pass filter, respectively. As we can see,
> > these two figures are very different. Therefore, I am wondering why and
> how
> > does the frequency filter affect the kurtosis?
>
> > The figure 1 is generated by the following program;
>
> > %% preporcessing the channel level data
>
> > dataset = 'case1.ds';
>
> > cfg = [];
>
> > cfg.dataset = dataset;
>
> > % cfg.hpfilter = 'yes';
>
> > % cfg.hpfreq = 10;
>
> > % cfg.lpfilter = 'yes';
>
> > % cfg.lpfreq = 70;
>
> > cfg.channel = {'MEG'};
>
> > data = ft_preprocessing(cfg);
>
>
>
> > %% compute channel-level kurtosis
>
>
>
> > datak = [];
>
> > datak.label = data.label;
>
> > datak.dimord = 'chan';
>
> > datak.kurtosis = kurtosis(data.trial{1}')';
>
>
>
> > cfg = [];
>
> > cfg.comment = 'computed channel-level kurtosis';
>
> > datak = ft_annotate(cfg, datak);
>
>
>
> > %% plot kurtosis topography at channel-level
>
>
>
> > cfg = [];
>
> > cfg.layout = 'CTF275.lay';
>
> > cfg.parameter = 'kurtosis';
>
>
>
> > figure;
>
> > ft_topoplotER(cfg, datak);
>
>
> > ​
>
> > Figure 1 kurtosis topography + no filter + case1.ds
>
> > If the band pass filter is included in the pre-processing, the kurtosis
> > topography is figure 2; the pre-processing matlab program is
>
> > %% preporcessing the channel level data
>
> > dataset = 'case1.ds';
>
> > cfg = [];
>
> > cfg.dataset = dataset;
>
> > cfg.hpfilter = 'yes';
>
> > cfg.hpfreq = 10;
>
> > cfg.lpfilter = 'yes';
>
> > cfg.lpfreq = 70;
>
> > cfg.channel = {'MEG'};
>
> > data = ft_preprocessing(cfg);
>
>
>
> > Figure 2 kurtosis topography + [10Hz 70Hz] filter + case1.ds
>
> > *Question 2:* Why the kurtosis topographies at channel level from two
> > dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
> > case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4
> (filtered))
> > are not consistent? Because these two datasets are measured from the same
> > patient, the kurtosis topography should be consistent. Do you have any
> idea
> > about this?
>
>
> > ​
>
> > Figure 3 kurtosis topography + no filter + case1_cHPI_raw_trans_sss.fif
>
>
> > ​
>
> > Figure 4 kurtosis topography + [10Hz 70Hz] filter +
> > case1_cHPI_raw_trans_sss.fif
>
> > Regards,
>
> > Rui.
>
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