[Mne_analysis] Mne_analysis Digest, Vol 33, Issue 1: phase locking value

[Kyle Lepage]

Some additions:
I meant power line frequencies and integer multiples of these frequencies.

Also, there is a phase capture effect,
http://books.google.com/books?id=-kyPyn3Dst8C&pg=PA140&lpg=PA140&dq=what+is+phase+capture+in+communications+engineering&source=bl&ots=OxC5oGQnBU&sig=wufjqByQGx_rRCBAMoXdgBr4pqE&hl=en&ei=nigQTPayJoX7lwfLr8mQDQ&sa=X&oi=book_result&ct=result&resnum=5&ved=0CCgQ6AEwBA#v=onepage&q&f=false

where, the rms of the phase angle increases dramatically (factor of 3) as
the amplitude between the sinusoid of interest (fixed phase) decreases
below the amplitude of an additive, interfering sinusoid with random
phase.


Best,

 Kyle

On Mon, 4 Oct 2010, Kyle Lepage wrote:

>
> Hi, Elisabeth, from  this site:
> http://github.com/dirkneumann/spm8/blob/master/spm_eeg_morlet.m
>
> it looks like the extent of the Morlet window is about  0.0071 seconds
> (full-width half-max).
>
> In the frequency domain this window will extend about 140 Hz.
>
> The complex Morlet wavelet coefficient, at a specific time and frequency,
> is the discrete Fourier transform of  Gaussian windowed data (centered on
> the time of interest) evaluated at the frequency of interest.  This is
> equivalent in the frequency domain to the convolution of the transformed
> Gaussian window with the transformed data (evaluated at the frequency of
> interest).
>
> Synopsis: with a scale factor of 7, estimates at 40-80 Hz will respond to
> frequencies from approximately Nyquist - 30 Hz to 150 Hz.  If this is the
> problem, the solution will be to increase the scale factor; trading
> temporal resolution for resolution in the frequency domain.
>
> Though possibly pre-processed away or taken care of, the power lines
> belong to these frequency ranges.  If you haven't already done so, it's
> probably a good idea to make sure that they are not contributing.
>
> Best,
>
> Kyle Lepage
>