[FieldTrip] Adjacency matrix for debiased weighted phase lag index

[Schoffelen, J.M. (Jan Mathijs)]

Hi Tyler,

Probably you should either use

cfg.output = ‘fourier’ in the call to ft_freqanalysis, or

specify cfg.channelcmb in your call to ft_freqanalysis should do it.

(actually, the quote from the help docstring of (what I asume to be) ft_connectivityanalysis - which you pasted into your e-mail, sums up the above: cfg.channelcmb in ft_connectivityanalysis does not have a functional effect, because the input data was NOT univariate (no ‘fourier’ in output), but the recipe for ft_freqanalysis did not specify the channelcmb, so the data were detected to be bivariate (‘powandcsd’), but only with bivariate auto-pairs)

Please note, that questions asked on this discussion list are only answered by people on a voluntary basis. Nobody has it as their job to answer to this list, so you shouldn’t expect people to answer, and certainly not within a particular time frame. Also, the quality of the question matters, and to be honest the original question had some room for improvement.

Best wishes and good luck with your analysis,

Jan-Mathijs



On 7 Mar 2023, at 15:25, Tyler Durdern via fieldtrip <fieldtrip at science.ru.nl<mailto:fieldtrip at science.ru.nl>> wrote:

Dear all,

I asked this question but I did not receive a response yet:

I computed the debiased weighted phase lag index for all channel combinations of a 30-channel EEG resting state recording. The output file (wpli_debiasedspctrm) has the following dimensions (435x30). I subsequently averaged the file across the second dimension to get an average debiased wpli estimate across the frequency band of interest. Now, I want to put this estimate into an adjacency matrix format (30x30) so I can illustrate the connectivity matrix using e.g. imagesc in Matlab. Is there a way I can achieve this in fieldtrip?

I tried a few approaches in the mean time but I cannot seem to get the results I want. Using a 30-channel EEG recording, I expect a  900x30 output variable corresponding to wpli values for all possible channel combinations (even identical ones) per frequency in both directions (e.g. Cz-Fz and Fz-Cz). I tried to achieve this using ft_channelcombination and although this yields the correct channel combinations, it doesn’t change the wpli output. Looking into the code
I found that this is probably due to the fact that my data is bivariate and the code states that „ This only has an effect when the input data
is univariate“.

Here is the code I’ve used so far:

% Define the resampling parameters
cfg = [];
cfg.resamplefs = 125;

% Resample the data
ft_data_rs = ft_resampledata(cfg, ft_data);

% Cut data into multiple trials
cfg = [];
cfg.length = 1; % 1 sec. segments
cfg.overlap = 0;
ft_data_rs_seg = ft_redefinetrial(cfg, ft_data_rs);

% Freq analysis I
cfg = [];
cfg.method = 'mtmfft'; % use multitaper frequency transformation
cfg.output = 'powandcsd'; % compute power spectrum and cross-spectral density
cfg.taper = 'dpss'; % use DPSS taper window
cfg.foi = 1:30; % frequency range of interest
cfg.keeptrials = 'yes'; % average over trials
cfg.channel = 'all'; % use all channels
cfg.trials = 'all'; % use all trials
cfg.tapsmofrq = 8; % specify the smoothing parameter for DPSS
cfg.pad = 'nextpow2'; % should increase computation speed
freq=ft_freqanalysis(cfg,ft_data_rs_seg);

% Define the connectivity parameters
cfg = [];
cfg.method = 'wpli_debiased';
cfg.channelcmb = {'all' 'all'};
cfg.complex = 'abs';

wpli_data = ft_connectivityanalysis(cfg, freq);

To summarize: I would like to compute debiased wpli for all channels (even identical ones) in both directions. Further, I would like to store
the debiased wpli output in a 30x30 adjacency/connectivity matrix.

As I am still quite new to FieldTrip I am stuck here and I would really appreciate your help on this issue.

Thanks in advance and all the best,

Tyler

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