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

[Ross Maddox]

Unfortunately there's no hard and fast rule. In general you should filter
as "gently" as possible, since impulse responses can get shockingly long
with steeper slopes in the frequency domain. The best way to know how
spread in time your filtered signal is going to be is probably to look
directly at the filter impulse response (or the envelope of the IR). That
will give you and idea of how much the estimate at one time point depends
on the time points nearby.

Another good thing to do is to make some synthetic, known input signals and
process them to see how your analysis affects them.

Hope that helps,
Ross


On Tue, Jan 23, 2018 at 9:46 AM, jeanne lusiot <jeanne.lusiot at gmail.com>
wrote:

> Hi Ross,
>
> I agree. I set the transition band to 2 Hz, but I don't know if that will
> provide sufficient temporal resolution. Is there some analytic way to
> determine the temporal/spectral precision based on the width of the
> transition band?
> Best,
> J
>
> On Mon, Jan 22, 2018 at 5:11 PM, Ross Maddox <rmaddox at ur.rochester.edu>
> wrote:
>
>> Hi J,
>>
>> Note that 1 Hz wide filters are very narrow, especially if you want to
>> analyze only a 400 ms window. The higher your frequency resolution, the
>> lower your temporal resolution.
>>
>> Best,
>> Ross
>>
>> --
>> Ross Maddox, Ph.D.
>> Assistant Professor of Biomedical Engineering and Neuroscience
>> School of Medicine and Dentistry
>> Hajim School of Engineering and Applied Sciences
>> University of Rochester
>>
>> Office: KMRB G-9607
>> Phone: 585-275-1835 <(585)%20275-1835>
>>
>> On Mon, Jan 22, 2018 at 3:32 PM, Denis-Alexander Engemann <
>> denis.engemann at gmail.com> wrote:
>>
>>> Yes, this is the example I had in mind.
>>>
>>> On Mon, Jan 22, 2018 at 9:31 PM Alexandre Gramfort <
>>> alexandre.gramfort at inria.fr> wrote:
>>>
>>>> hi,
>>>>
>>>> how about starting with something like this:
>>>>
>>>> http://martinos.org/mne/stable/auto_examples/time_frequency/
>>>> plot_time_frequency_global_field_power.html
>>>>
>>>> ?
>>>>
>>>> HTH
>>>> Alex
>>>>
>>>>
>>>> On Mon, Jan 22, 2018 at 9:27 PM, jeanne lusiot <jeanne.lusiot at gmail.com>
>>>> wrote:
>>>> > 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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