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

Wed Apr 23 05:22:31 EDT 2014

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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