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+ | ===== FT_CONNECTIVITY_CORR ===== | ||
+ | |||
+ | Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_connectivity_corr". | ||
+ | |||
+ | <html><pre> | ||
+ | <a href=/reference/ft_connectivity_corr><font color=green>FT_CONNECTIVITY_CORR</font></a> computes correlation, coherence or a related quantity from a | ||
+ | data-matrix containing a covariance or cross-spectral density. It implements the | ||
+ | methods as described in the following papers: | ||
+ | |||
+ | Coherence: Rosenberg et al, The Fourier approach to the identification of | ||
+ | functional coupling between neuronal spike trains. Prog Biophys Molec | ||
+ | Biol 1989; 53; 1-31 | ||
+ | |||
+ | Partial coherence: Rosenberg et al, Identification of patterns of | ||
+ | neuronal connectivity - partial spectra, partial coherence, and neuronal | ||
+ | interactions. J. Neurosci. Methods, 1998; 83; 57-72 | ||
+ | |||
+ | Phase locking value: Lachaux et al, Measuring phase sychrony in brain | ||
+ | signals. Human Brain Mapping, 1999; 8; 194-208. | ||
+ | |||
+ | Imaginary part of coherency: Nolte et al, Identifying true brain | ||
+ | interaction from EEG data using the imaginary part of coherence. Clinical | ||
+ | Neurophysiology, 2004; 115; 2292-2307 | ||
+ | |||
+ | Use as | ||
+ | [c, v, n] = ft_connectivity_corr(input, ...) | ||
+ | |||
+ | The input data should be an array organized as | ||
+ | Repetitions x Channel x Channel (x Frequency) (x Time) | ||
+ | or | ||
+ | Repetitions x Channelcombination (x Frequency) (x Time) | ||
+ | |||
+ | If the input already contains an average, the first dimension should be singleton. | ||
+ | Furthermore, the input data can be complex-valued cross spectral densities, or | ||
+ | real-valued covariance estimates. If the former is the case, the output will be | ||
+ | coherence (or a derived metric), if the latter is the case, the output will be the | ||
+ | correlation coefficient. | ||
+ | |||
+ | Additional optional input arguments come as key-value pairs: | ||
+ | hasjack = 0 or 1 specifying whether the Repetitions represent | ||
+ | leave-one-out samples | ||
+ | complex = 'abs', 'angle', 'real', 'imag', 'complex', 'logabs' for | ||
+ | post-processing of coherency | ||
+ | feedback = 'none', 'text', 'textbar' type of feedback showing progress of | ||
+ | computation | ||
+ | dimord = specifying how the input matrix should be interpreted | ||
+ | powindx = required if the input data contain linearly indexed | ||
+ | channel pairs. should be an Nx2 matrix indexing on each | ||
+ | row for the respective channel pair the indices of the | ||
+ | corresponding auto-spectra | ||
+ | pownorm = flag that specifies whether normalisation with the | ||
+ | product of the power should be performed (thus should | ||
+ | be true when correlation/coherence is requested, and | ||
+ | false when covariance or cross-spectral density is | ||
+ | requested). | ||
+ | |||
+ | Partialisation can be performed when the input data is (chan x chan). The | ||
+ | following options need to be specified: | ||
+ | |||
+ | pchanindx = index-vector to the channels that need to be | ||
+ | partialised | ||
+ | allchanindx = index-vector to all channels that are used | ||
+ | (including the "to-be-partialised" ones). | ||
+ | |||
+ | The output c contains the correlation/coherence, v is a variance estimate | ||
+ | which only can be computed if the data contains leave-one-out samples, | ||
+ | and n is the number of repetitions in the input data. | ||
+ | |||
+ | See also <a href=/reference/ft_connectivityanalysis><font color=green>FT_CONNECTIVITYANALYSIS</font></a> | ||
+ | </pre></html> | ||