[Mne_analysis] Time-frequency PSD with CWT (morlet wavelet) in a single trial

Wed Apr 23 10:58:57 EDT 2014

Hi Denis,

I have tested with single_trial_power() but I obtain exactly the same
results that my use with _time_frequency(). Here is my code:
https://gist.github.com/arnaudferre/11215335. I don’t understand what the
problem is. With a sinusoid, I must have a band of high power around the
fundamental frequency of the sinusoid, right?

For the GUI, I don’t find documentation on the use with Windows. But ok, I
must compile the sources with the makefile. It’s been a long time that I
didn’t play with C! But I will try (I believe that I must download the
software Make to begin). But in fact, I don’t know why I spoke of GUI,
sorry. I think that I thought at a possibility to play with data directly
with a GUI in the way that I want.

I’m not sure to understand what you name “Raw object”. Is it the name of an
existing object from MNE? But, with the knowledge of this object, I can
write a function which return this directly. My problem is that I’m not an
expert on the data and her format. But if it’s substantially a problem of
parsing, I can step in the discussion.

I read your link on the S-transform. Yes, it could be very interesting to
test my data with this method. But I must already test older results from a
study with Fourier Transform. In literature, the wavelet transform with
morlet wavelet seems to be adequate to my project (Phase-Amplitude coupling
then cross-frequency coupling). So, I want finish with this method to have
my first result. But thank you, I keep it in a corner for later.

Best,
Arnaud

2014-04-23 11:22 GMT+02:00 Denis-Alexander Engemann <
denis.engemann at gmail.com>:

> Hi Arnaud,
>
>
> On Wed, Apr 23, 2014 at 10:54 AM, Arnaud Ferre <arnaud.ferre.pro at gmail.com
> > wrote:
>
>> Hi Denis,
>> Thanks for the fast reply.
>>
>> Yes I can share my test. Here:
>> https://gist.github.com/arnaudferre/11206945.
>>
>>
> Thanks, will have a look later.
>
>
>>  Ok, I will try to use single_trial_power() function now.
>>
>> For the GUI, unfortunately, I must develop a ‘biologists-friendly’
>> software. In consequence (and with others constraints), I must develop on
>> Windows and the GUI doesn’t work on Windows if I have correctly understood.
>>
>>
> Which GUI? The MNE C GUI indeed compile on Windows. However,
> `mne.gui.coregistration` in Python is supposed to work on Windows.
>
>
>
>>  For my file format, I have already develop my own functions to parse
>> the original data (my goal: adapt raw signal to can use just the useful
>> data). This format can be ‘CED Spike2 SMR files’ or an alternative in TXT
>> from Local Field Potential acquisition. So, I store the data of a single
>> trial in a dictionary, then in a pickle file (maybe not a good idea…).
>>
>
> I agree. I would strongly encourage you to write a custom constructor
> function that returns a Raw object from your data. We're happy assist you
> with that Also it would be a great test case for new tools we're about to
> develop that aim at making exactly this task easier. In fact I need to
> write a couple of functions very soon that allow me to read in data stored
> in Mat files. Sounds like that would follow the same logic.
>
>
>> I do this certainly with my personal way. For these reasons, I tried to
>> adapt the MNE-Python script to read my data. It seems not far yet! But I
>> don’t know if I can really add idea in your conversation due to these
>> specific data.
>>
>>
> I think you can. See above. Also we're happy to add support to additional
> EEG / electrophysiology formats.
>
> Anyway, it seems that MNE contains all the tools what we need here. It’s
>> very encouraging yeah. But, I think we need time to know to use these tools.
>>
>> Arnaud
>>
>>
> FYI something I'm working on at the moment that might also be of interest
> to you:
>
> https://github.com/mne-tools/mne-python/pull/1233
>
> Best,
> Denis
>
>
>>
>>
>> 2014-04-19 12:34 GMT+02:00 Denis-Alexander Engemann <
>> denis.engemann at gmail.com>:
>>
>> Hi Arno,
>>>
>>> let my reply inline,
>>>
>>> On Fri, Apr 18, 2014 at 6:55 PM, Arnaud Ferre <
>>> arnaud.ferre.pro at gmail.com> wrote:
>>>
>>>> Hi all,
>>>> I work on EEG data in behavioral field. I understand the basics of
>>>> signal processing and I’m not so bad in Python. But for a beginner like me,
>>>> MNE-Python is pretty huge. I was advised to use MNE knowing my constraints,
>>>> but I’m starting to think that it’s maybe too evolved for a non-expert
>>>> scientist in this field like me.
>>>>
>>>  I’m just trying to draw a time-frequency PSD from a single trial with a
>>>> CWT (with morlet wavelets). I thought to have found what functions used,
>>>> but in testing my script, I don’t obtain correct result.
>>>>
>>>
>>>> In fact, I tested with a simple sinusoid function with a frequency of
>>>> 10Hz on 1sec (1000points). I expected to see a lot of "red blobs" aligned
>>>> on the 10Hz in y-axis but not. I have a continuous and very thin band
>>>> around 1.5 Hz and a residual band around the 90Hz. I looked the wavelets
>>>> and it seems fine. What is strange is that I see the correct number of
>>>> blob, so I think it’s not so far of correct result. In first, I thought of
>>>> a problem in adjusting my display, but it seems not.
>>>>
>>>
>>> Could you share an example script, e.g. using https://gist.github.com/
>>> That would be very helpful.
>>>
>>>
>>>>
>>>> I use mainly the function _time_frequency(data, Ws), one of the
>>>> functions in tfr.py in mne.time_frequency where data is a 2D-array
>>>> containing only my signal in data[0].
>>>>
>>>> I read this link:
>>>> http://martinos.org/mne/stable/auto_examples/stats/plot_cluster_1samp_test_time_frequency.html,
>>>> but as I don’t use data with the standard format, it seemed to me
>>>> complicated. Moreover, I think that _time_frequency(data, Ws) is just
>>>> needed to do what I want. And yet, maybe that the specificities of the
>>>> function single_trial_power in tfr.py is the solution…
>>>>
>>>>
>>>>
>>> In fact `single_trial_power` would be the way to go. (
>>> http://martinos.org/mne/dev/generated/mne.time_frequency.single_trial_power.html#mne.time_frequency.single_trial_power
>>> )
>>> In general it's not recommended not use functions starting with
>>> underscores unless you know exactly what you do. Things are much easier
>>> once you use the top-level API. Is your file format that prevents you from
>>> doing this? What kind of EEG  data do you use? We're currently working on
>>> improving support for custom data:
>>>
>>> https://github.com/mne-tools/mne-python/issues/1229
>>>
>>> Please feel free to participate in the discussion on Github and tell us
>>> more about your use case.
>>>
>>>
>>>> Thanks in advance
>>>> Arnaud
>>>>
>>>>
>>> I hope we can encourage you to keep exploring the new terrain ;-)
>>>
>>> Denis
>>>
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