[Mne_analysis] MNE and EEG channel synchrony

[Hari Bharadwaj]

Hi Theodore,

Most connectivity metrics are based on some sort of consistency of the
phase relationship between two signals across epochs/trials... In your
example, the PLV looks for how repeatable the phase difference between two
channels across epochs/trials...
  Thus you may want to consider in what sense you want to compute
synchrony and what that would mean before attempting to use the
spectral_connectivity(.) capabilities of MNE.

HTH,
Hari



On Mon, October 13, 2014 8:46 am, Theodore Vasiloudis wrote:
> Hello,
>
> I would like to use MNE in order to extract some measures of synchrony,
> such as PLV, from EEG
> samples. I saw the related connectivity module in MNE but I am unsure
> about
> the input format
> of the data for the spectral_connectivity function.
>
> What I would like to do is to calculate the synchrony between channels
> that
> are formatted as
> a simple 2d numpy array where each row corresponds to a channel and each
> column is a sample
> so the format is (channel x time).
> However the spectral_connectivity function expects data in the form:
> array, shape=(n_epochs, n_signals, n_times) or generator of array, shape
> =(n_signals, n_times).
>
> So my questions are: Is there some way to use spectral_connectivity or
> some
> other MNE module
> to calculate the synchrony between EEG channels without epoch information?
> Can I translate my 2d array into the array, shape =(n_signals, n_times)
> format that MNE expects?
>
> Regards,
> Theodore
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-- 
Hari Bharadwaj
Post-doctoral Associate,
Center for Computational Neuroscience
  and Neural Technology (CompNet),
Boston University
677 Beacon St.,
Boston, MA 02215

Martinos Center for Biomedical Imaging,
Massachusetts General Hospital
149 Thirteenth Street,
Charlestown, MA 02129

hari at nmr.mgh.harvard.edu
Ph: 734-883-5954
www.haribharadwaj.com