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FT_CONNECTIVITY_PPC computes pairwise phase consistency or weighted pairwise phase
consistency from a data-matrix containing a cross-spectral density. This implements
the method described in Vinck M, van Wingerden M, Womelsdorf T, Fries P, Pennartz
CM. The pairwise phase consistency: a bias-free measure of rhythmic neuronal
synchronization. Neuroimage. 2010 May 15;51(1):112-22.
Use as
[c, v, n] = ft_connectivity_ppc(input, ...)
The input data input should be organized as:
Repetitions x Channel x Channel (x Frequency) (x Time)
or
Repetitions x Channelcombination (x Frequency) (x Time)
The first dimension should contain repetitions and should not contain an average
already. Also, it should not consist of leave-one-out averages.
Additional optional input arguments come as key-value pairs:
feedback = 'none', 'text', 'textbar' type of feedback showing progress of computation
weighted = 1 (or true) or 0 (or false), we compute unweighted ppc or
weighted ppc, the weighting is according to the magnitude of
the cross-spectrum
The output c contains the ppc, v is a leave-one-out variance estimate which is only
computed if dojack = 1,and n is the number of repetitions in the input data.
See also FT_CONNECTIVITYANALYSIS
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