[Mne_analysis] Multitapers and DICS

[Alexandre Gramfort]

hi Andrea,

hum I think you're right.

If I follow what you're saying we should have a noise_csds per
frequency and per taper. Then compute the STCs for each taper and then
average. Is that what you have in mind?

Alex

On Tue, May 24, 2016 at 6:21 AM, Andrea Brovelli
<andrea.brovelli at univ-amu.fr> wrote:
> Dear all,
> I have a question regarding the use of multitapers and DICS.
> As far as I know, the power spectral density using multitaper is the mean
> power averaged across tapers (e.g., equation 6 in the paper from Mitra and
> Pesaran http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1300074/pdf/9929474.pdf)
> At the source level, using DICS for example, I assume that we should compute
> the power for each taper and then average across tapers to get the mean
> power estimate for each source.
> While looking at the example on "Compute source power using DICS beamfomer"
> (http://martinos.org/mne/stable/auto_examples/inverse/plot_dics_source_power.html#sphx-glr-auto-examples-inverse-plot-dics-source-power-py),
> however it looks like that you compute the mean cross-spectral density
> averaged across tapers (which has complex values), and then you use it to
> compute the power at the source level.
> Is that the case ?
> If yes, would it be possible to modify it so to:
> 1) keep the csd for each taper
> 2) apply the spatial filter for each taper to the channel data to compute
> the source power for each taper
> 3) average source power across tapers
>
> Here are the lines of code I refer to in the Example
>
> # Computing the data and noise cross-spectral density matrices
> # The time-frequency window was chosen on the basis of spectrograms from
> # example time_frequency/plot_time_frequency.py
> # As fsum is False compute_epochs_csd returns a list of CrossSpectralDensity
> # instances than can then be passed to dics_source_power
> data_csds = compute_epochs_csd(epochs, mode='multitaper', tmin=0.04,
> tmax=0.15,
>                                fmin=15, fmax=30, fsum=False)
> noise_csds = compute_epochs_csd(epochs, mode='multitaper', tmin=-0.11,
>                                 tmax=-0.001, fmin=15, fmax=30, fsum=False)
>
> # Compute DICS spatial filter and estimate source power
> stc = dics_source_power(epochs.info, forward, noise_csds, data_csds)
>
>
> Thanks a lot,
> Best,
> Andrea
>
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