[Mne_analysis] Width of the transition band when applying a Hilbert transform

[jeanne lusiot]

Hello,
I mainly want to estimate theta, alpha, and beta power in the 200-600ms
postimulus window. Note that I could bandpass filter the data in the
corresponding ranges (e.g., theta: 4-7).





averaged power in a specific temporal window (200 600ms poststimulus)  for
theta bvand, alpha band, and beta band.

On Mon, Jan 22, 2018 at 2:17 PM, Alexandre Gramfort <
alexandre.gramfort at inria.fr> wrote:

> hi J,
>
> may I ask what you are aiming to do afterwards with these filtered data?
>
> Alex
>
> On Sat, Jan 20, 2018 at 11:45 PM, jeanne lusiot <jeanne.lusiot at gmail.com>
> wrote:
> > Hello,
> >
> > My question relates more to a signal processing issue, so apologies in
> > advance if it is not appropriate for the forum.
> > I am currently doing an exploratory EEG power analysis  using the
> > filter-Hilbert transform and would appreciate some advice on the
> > parameterization of the band-pass filter. For each epoch and time step, I
> > want to compute the power of each frequency from 1 to 30 Hz (in steps of
> 1).
> > I am thus bandpass filtering the data prior to the application of the
> > Hilbert transform (so I bandpass filter from 1 to 2Hz, then from 2 to 3hz
> > etc. ).
> > Mne's FIR filter implemented via mne.filter.filter_data is perfect for
> this
> > purpose, but I am wondering if I should use the default automatic width
> of
> > transition band, or whether i should set  l_trans_bandwidth and
> > h_trans_bandwidth to some fixed value x across all frequency bands. If
> so,
> > how should I set x to achieve a good balance between frequency/timing
> > precision ?
> >
> > Best,
> > J.
> >
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