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reference:ft_connectivity_granger [2018/08/23 14:43] (current)
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 +=====  FT_CONNECTIVITY_GRANGER =====
 +
 +Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_connectivity_granger"​.
 +
 +<​html><​pre>​
 +  <a href=/​reference/​ft_connectivity_granger><​font color=green>​FT_CONNECTIVITY_GRANGER</​font></​a>​ computes spectrally resolved granger causality. This
 +  implementation is loosely based on the code used in Brovelli, et. al., PNAS 101,
 +  9849-9854 (2004).
 + 
 +  Use as
 +    [GRANGER, V, N] = <a href=/​reference/​ft_connectivity_granger><​font color=green>​FT_CONNECTIVITY_GRANGER</​font></​a>​(H,​ Z, S, ...)
 + 
 +  The input data should be
 +    H = spectral transfer matrix, Nrpt x Nchan x Nchan x Nfreq (x Ntime),
 +        or Nrpt x Nchancmb x Nfreq (x Ntime). Nrpt can be 1.
 +    Z = the covariance matrix of the noise, Nrpt x Nchan x Nchan (x Ntime),
 +        or Nrpt x Nchancmb (x Ntime).
 +    S = the cross-spectral density matrix with the same dimensionality as H.
 + 
 +  Additional optional input arguments come as key-value pairs:
 +    '​dimord' ​ = required string specifying how to interpret the input data
 +                supported values are '​rpt_chan_chan_freq(_time) and
 +                '​rpt_chan_freq(_time),​ '​rpt_pos_pos_XXX'​ and '​rpt_pos_XXX'​
 +    '​method' ​ = '​granger'​ (default), or '​instantaneous',​ or '​total'​.
 +    '​hasjack'​ = 0 (default) is a boolean specifying whether the input
 +                contains leave-one-outs,​ required for correct variance
 +                estimate
 +    '​powindx'​ = is a variable determining the exact computation,​ see below
 + 
 +  If the inputdata is such that the channel-pairs are linearly indexed, granger
 +  causality is computed per quadruplet of consecutive entries, where the convention
 +  is as follows:
 + 
 +   H(:, (k-1)*4 + 1, :, :, :) -&gt; '​chan1-chan1'​
 +   H(:, (k-1)*4 + 2, :, :, :) -&gt; '​chan1-&​gt;​chan2'​
 +   H(:, (k-1)*4 + 3, :, :, :) -&gt; '​chan2-&​gt;​chan1'​
 +   H(:, (k-1)*4 + 4, :, :, :) -&gt; '​chan2-&​gt;​chan2'​
 + 
 +  The same holds for the Z and S matrices.
 + 
 +  Pairwise block-granger causality can be computed when the inputdata has
 +  dimensionality Nchan x Nchan. In that case powindx should be specified, as a 1x2
 +  cell-array indexing the individual channels that go into each '​block'​.
 + 
 +  See also <a href=/​reference/​ft_connectivityanalysis><​font color=green>​FT_CONNECTIVITYANALYSIS</​font></​a>​
 +</​pre></​html>​