[Mne_analysis] Visualizing power spectrum density of sources on the brain

[Denis-Alexander Engemann]

I can answer in greater detail later, but 1) you need to "hack" the stc
object and figure out the right scale after putting the frequenies in
.times and accordingly scale ; by default our data containers assume time
domain data 2) if you use dSPM as method it is a pseudo F-statistic, for
interpretable power plots you should use MNE as method in the inverse
solver

I hope this helps a bit,

Denis
On Thu, 30 Jun 2016 at 22:49, Gladia Hotan <gladiach at gmail.com> wrote:

> Hi,
>
> I have a couple of questions about the psd of sources:
>
> 1) I used
>
> stc = mne.minimum_norm.compute_source_psd
>
> to get an stc file containing the psd of the sources. It seems like in this stc file,
> frequency has replaced time, but is still called 'time':
>
> <SourceEstimate  |  ... tmin : 0.0 (ms), tmax : 55.0 (ms), tstep : 0.25 (ms) ...>
>
> (I set the function to compute from 0 to 55 Hz; the time duration of the data is
> actually a lot longer). I can use stc.plot or mne.plot_source_estimates to visualize this, but it treats
> the frequencies like times. How can I plot the psd at a particular frequency on the brain?
>
> 2) What are the units of the psd of the sources? According to the tutorial <http://martinos.org/mne/stable/auto_examples/time_frequency/plot_source_power_spectrum.html#sphx-glr-auto-examples-time-frequency-plot-source-power-spectrum-py> the psd is in dB,
> but what is the reference quantity being used when converting to dB? (Ie. what is Pref in P_db = 10*log10(P/Pref)?)
> Am I right that the source amplitudes are in units of ampere-metres?
>
> Thanks and Best,
> Gladia
>
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