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

Thu Apr 24 04:52:29 EDT 2014

Ok, so I'm not far!
In fact, I think that what I see as "residual band" is the correct thing,
but not correctly align with the correct frequency in the y-axis. The high
power band in the bottom could be an artefact in the edge.
So, I'm interested by your edits.
Thank

2014-04-23 18:17 GMT+02:00 Denis A. Engemann <denis.engemann at gmail.com>:

> I was playing a bit with you example and got reasonable results with a
> clear 10 hz modulation using the  single trial tfr function.
> I can share my edits later with you. Btw. why don't we meet at Neurospin
> at some point for lunch or a coffee --- maybe things are easier to tackle
> then.
> For raw and epochs and evoked API take a look here:
>
>
> http://martinos.org/mne/stable/auto_examples/plot_from_raw_to_epochs_to_evoked.html
>
>
> Best,
> Denis
>
> On Apr 23, 2014, at 4:58 PM, Arnaud Ferre <arnaud.ferre.pro at gmail.com>
> wrote:
>
> 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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