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

[Arnaud Ferre]

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.

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…


Thanks in advance
Arnaud
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